WorldWideScience

Sample records for autocorrelation

  1. Parallel auto-correlative statistics with VTK.

    Energy Technology Data Exchange (ETDEWEB)

    Pebay, Philippe Pierre; Bennett, Janine Camille

    2013-08-01

    This report summarizes existing statistical engines in VTK and presents both the serial and parallel auto-correlative statistics engines. It is a sequel to [PT08, BPRT09b, PT09, BPT09, PT10] which studied the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k-means, and order statistics engines. The ease of use of the new parallel auto-correlative statistics engine is illustrated by the means of C++ code snippets and algorithm verification is provided. This report justifies the design of the statistics engines with parallel scalability in mind, and provides scalability and speed-up analysis results for the autocorrelative statistics engine.

  2. Inference for local autocorrelations in locally stationary models.

    Science.gov (United States)

    Zhao, Zhibiao

    2015-04-01

    For non-stationary processes, the time-varying correlation structure provides useful insights into the underlying model dynamics. We study estimation and inferences for local autocorrelation process in locally stationary time series. Our constructed simultaneous confidence band can be used to address important hypothesis testing problems, such as whether the local autocorrelation process is indeed time-varying and whether the local autocorrelation is zero. In particular, our result provides an important generalization of the R function acf() to locally stationary Gaussian processes. Simulation studies and two empirical applications are developed. For the global temperature series, we find that the local autocorrelations are time-varying and have a "V" shape during 1910-1960. For the S&P 500 index, we conclude that the returns satisfy the efficient-market hypothesis whereas the magnitudes of returns show significant local autocorrelations.

  3. A simple method to estimate interwell autocorrelation

    Energy Technology Data Exchange (ETDEWEB)

    Pizarro, J.O.S.; Lake, L.W. [Univ. of Texas, Austin, TX (United States)

    1997-08-01

    The estimation of autocorrelation in the lateral or interwell direction is important when performing reservoir characterization studies using stochastic modeling. This paper presents a new method to estimate the interwell autocorrelation based on parameters, such as the vertical range and the variance, that can be estimated with commonly available data. We used synthetic fields that were generated from stochastic simulations to provide data to construct the estimation charts. These charts relate the ratio of areal to vertical variance and the autocorrelation range (expressed variously) in two directions. Three different semivariogram models were considered: spherical, exponential and truncated fractal. The overall procedure is demonstrated using field data. We find that the approach gives the most self-consistent results when it is applied to previously identified facies. Moreover, the autocorrelation trends follow the depositional pattern of the reservoir, which gives confidence in the validity of the approach.

  4. Linear Prediction Using Refined Autocorrelation Function

    Directory of Open Access Journals (Sweden)

    M. Shahidur Rahman

    2007-07-01

    Full Text Available This paper proposes a new technique for improving the performance of linear prediction analysis by utilizing a refined version of the autocorrelation function. Problems in analyzing voiced speech using linear prediction occur often due to the harmonic structure of the excitation source, which causes the autocorrelation function to be an aliased version of that of the vocal tract impulse response. To estimate the vocal tract characteristics accurately, however, the effect of aliasing must be eliminated. In this paper, we employ homomorphic deconvolution technique in the autocorrelation domain to eliminate the aliasing effect occurred due to periodicity. The resulted autocorrelation function of the vocal tract impulse response is found to produce significant improvement in estimating formant frequencies. The accuracy of formant estimation is verified on synthetic vowels for a wide range of pitch frequencies typical for male and female speakers. The validity of the proposed method is also illustrated by inspecting the spectral envelopes of natural speech spoken by high-pitched female speaker. The synthesis filter obtained by the current method is guaranteed to be stable, which makes the method superior to many of its alternatives.

  5. Functional Maximum Autocorrelation Factors

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Nielsen, Allan Aasbjerg

    2005-01-01

    MAF outperforms the functional PCA in concentrating the interesting' spectra/shape variation in one end of the eigenvalue spectrum and allows for easier interpretation of effects. Conclusions. Functional MAF analysis is a useful methods for extracting low dimensional models of temporally or spatially......Purpose. We aim at data where samples of an underlying function are observed in a spatial or temporal layout. Examples of underlying functions are reflectance spectra and biological shapes. We apply functional models based on smoothing splines and generalize the functional PCA in......\\verb+~+\\$\\backslash\\$cite{ramsay97} to functional maximum autocorrelation factors (MAF)\\verb+~+\\$\\backslash\\$cite{switzer85,larsen2001d}. We apply the method to biological shapes as well as reflectance spectra. {\\$\\backslash\\$bf Methods}. MAF seeks linear combination of the original variables that maximize autocorrelation between...

  6. Autocorrelation in queuing network type production systems - revisited

    DEFF Research Database (Denmark)

    Nielsen, Erland Hejn

    -production systems (Takahashi and Nakamura, 1998) establishes that autocorrelation plays definitely a non-negligible role in relation to the dimensioning as well as functioning of Kanban-controlled production flow lines . This must logically either imply that production managers are missing an important aspect...... in their production planning reasoning, or that the 'realistic' autocorrelation patterns , inherent in actual production setups , are not like those so far considered in the literature. In this paper, an attempt to characterise relevant and 'realistic' types of autocorrelation schemes as well as their levels...

  7. Autocorrelation in queuing network-type production systems - revisited

    DEFF Research Database (Denmark)

    Nielsen, Erland Hejn

    2007-01-01

    , either production managers are missing important aspects in production planning, or the 'realistic' autocorrelation patterns inherent in actual production setups are not like those considered in the literature. In this paper, relevant and 'realistic' types of autocorrelation schemes are characterised...

  8. Some notes concerning the fourier transformation of auto-correlation functions; Quelques notes sur la transformee de fourier des fonctions d'autocorrelation

    Energy Technology Data Exchange (ETDEWEB)

    Froelicher, B; Dalfes, A [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

    1968-07-01

    A study is made of the passage of the auto-correlation function to the frequency spectrum by a numerical Fourier transformation. Two principal characteristics of auto-correlation functions, the time between two points and the total time, are related to two oscillations which appear in the frequency spectrum and which deform it. Various methods are proposed for reducing the effect of these two parasitic oscillations and for re-obtaining the real spectrum. (authors) [French] On etudie le passage de la fonction d'autocorrelation au spectre de frequence par transformee de Fourier numerique. Deux caracteristiques principales des fonctions d'autocorrelation, la duree entre points et la duree totale sont reliees a deux oscillations qui apparaissent dans le spectre de frequence et le deforment. Diverses methodes sont proposees pour reduire l'effet de ces deux oscillations parasites, et retrouver le spectre reel. (auteurs)

  9. Spatial Autocorrelation and Uncertainty Associated with Remotely-Sensed Data

    Directory of Open Access Journals (Sweden)

    Daniel A. Griffith

    2016-06-01

    Full Text Available Virtually all remotely sensed data contain spatial autocorrelation, which impacts upon their statistical features of uncertainty through variance inflation, and the compounding of duplicate information. Estimating the nature and degree of this spatial autocorrelation, which is usually positive and very strong, has been hindered by computational intensity associated with the massive number of pixels in realistically-sized remotely-sensed images, a situation that more recently has changed. Recent advances in spatial statistical estimation theory support the extraction of information and the distilling of knowledge from remotely-sensed images in a way that accounts for latent spatial autocorrelation. This paper summarizes an effective methodological approach to achieve this end, illustrating results with a 2002 remotely sensed-image of the Florida Everglades, and simulation experiments. Specifically, uncertainty of spatial autocorrelation parameter in a spatial autoregressive model is modeled with a beta-beta mixture approach and is further investigated with three different sampling strategies: coterminous sampling, random sub-region sampling, and increasing domain sub-regions. The results suggest that uncertainty associated with remotely-sensed data should be cast in consideration of spatial autocorrelation. It emphasizes that one remaining challenge is to better quantify the spatial variability of spatial autocorrelation estimates across geographic landscapes.

  10. Consequences of spatial autocorrelation for niche-based models

    DEFF Research Database (Denmark)

    Segurado, P.; Araújo, Miguel B.; Kunin, W. E.

    2006-01-01

    1.  Spatial autocorrelation is an important source of bias in most spatial analyses. We explored the bias introduced by spatial autocorrelation on the explanatory and predictive power of species' distribution models, and make recommendations for dealing with the problem. 2.  Analyses were based o...

  11. Balance Maintenance in the Upright Body Position: Analysis of Autocorrelation

    Directory of Open Access Journals (Sweden)

    Stodolka¹ Jacek

    2016-04-01

    Full Text Available The present research aimed to analyze values of the autocorrelation function measured for different time values of ground reaction forces during stable upright standing. It was hypothesized that if recording of force in time depended on the quality and way of regulating force by the central nervous system (as a regulator, then the application of autocorrelation for time series in the analysis of force changes in time function would allow to determine regulator properties and its functioning. The study was performed on 82 subjects (students, athletes, senior and junior soccer players and subjects who suffered from lower limb injuries. The research was conducted with the use of two Kistler force plates and was based on measurements of ground reaction forces taken during a 15 s period of standing upright while relaxed. The results of the autocorrelation function were statistically analyzed. The research revealed a significant correlation between a derivative extreme and velocity of reaching the extreme by the autocorrelation function, described as gradient strength. Low correlation values (all statistically significant were observed between time of the autocorrelation curve passing through 0 axis and time of reaching the first peak by the said function. Parameters computed on the basis of the autocorrelation function are a reliable means to evaluate the process of flow of stimuli in the nervous system. Significant correlations observed between the parameters of the autocorrelation function indicate that individual parameters provide similar properties of the central nervous system.

  12. General simulation algorithm for autocorrelated binary processes.

    Science.gov (United States)

    Serinaldi, Francesco; Lombardo, Federico

    2017-02-01

    The apparent ubiquity of binary random processes in physics and many other fields has attracted considerable attention from the modeling community. However, generation of binary sequences with prescribed autocorrelation is a challenging task owing to the discrete nature of the marginal distributions, which makes the application of classical spectral techniques problematic. We show that such methods can effectively be used if we focus on the parent continuous process of beta distributed transition probabilities rather than on the target binary process. This change of paradigm results in a simulation procedure effectively embedding a spectrum-based iterative amplitude-adjusted Fourier transform method devised for continuous processes. The proposed algorithm is fully general, requires minimal assumptions, and can easily simulate binary signals with power-law and exponentially decaying autocorrelation functions corresponding, for instance, to Hurst-Kolmogorov and Markov processes. An application to rainfall intermittency shows that the proposed algorithm can also simulate surrogate data preserving the empirical autocorrelation.

  13. General simulation algorithm for autocorrelated binary processes

    Science.gov (United States)

    Serinaldi, Francesco; Lombardo, Federico

    2017-02-01

    The apparent ubiquity of binary random processes in physics and many other fields has attracted considerable attention from the modeling community. However, generation of binary sequences with prescribed autocorrelation is a challenging task owing to the discrete nature of the marginal distributions, which makes the application of classical spectral techniques problematic. We show that such methods can effectively be used if we focus on the parent continuous process of beta distributed transition probabilities rather than on the target binary process. This change of paradigm results in a simulation procedure effectively embedding a spectrum-based iterative amplitude-adjusted Fourier transform method devised for continuous processes. The proposed algorithm is fully general, requires minimal assumptions, and can easily simulate binary signals with power-law and exponentially decaying autocorrelation functions corresponding, for instance, to Hurst-Kolmogorov and Markov processes. An application to rainfall intermittency shows that the proposed algorithm can also simulate surrogate data preserving the empirical autocorrelation.

  14. Velocity and stress autocorrelation decay in isothermal dissipative particle dynamics

    Science.gov (United States)

    Chaudhri, Anuj; Lukes, Jennifer R.

    2010-02-01

    The velocity and stress autocorrelation decay in a dissipative particle dynamics ideal fluid model is analyzed in this paper. The autocorrelation functions are calculated at three different friction parameters and three different time steps using the well-known Groot/Warren algorithm and newer algorithms including self-consistent leap-frog, self-consistent velocity Verlet and Shardlow first and second order integrators. At low friction values, the velocity autocorrelation function decays exponentially at short times, shows slower-than exponential decay at intermediate times, and approaches zero at long times for all five integrators. As friction value increases, the deviation from exponential behavior occurs earlier and is more pronounced. At small time steps, all the integrators give identical decay profiles. As time step increases, there are qualitative and quantitative differences between the integrators. The stress correlation behavior is markedly different for the algorithms. The self-consistent velocity Verlet and the Shardlow algorithms show very similar stress autocorrelation decay with change in friction parameter, whereas the Groot/Warren and leap-frog schemes show variations at higher friction factors. Diffusion coefficients and shear viscosities are calculated using Green-Kubo integration of the velocity and stress autocorrelation functions. The diffusion coefficients match well-known theoretical results at low friction limits. Although the stress autocorrelation function is different for each integrator, fluctuates rapidly, and gives poor statistics for most of the cases, the calculated shear viscosities still fall within range of theoretical predictions and nonequilibrium studies.

  15. Operator theory of angular momentum nad orientational auto-correlation functions

    International Nuclear Information System (INIS)

    Evans, M.W.

    1982-01-01

    The rigorous relation between the orientational auto-correlation function and the angular momentum autocorrelation function is described in two cases of interest. First when description of the complete zero THz- spectrum is required from the Mori continued fraction expansion for the angular momentum autocorrelation function and second when rotation/translation effects are important. The Mori-Evans theory of 1976, relying on the simple Shimizu relation is found to be essentially unaffected by the higher order corrections recently worked out by Ford and co-workers in the Markov limit. The mutual interaction of rotation and translation is important in determining the details of both the orientational and angular momentum auto-correlation function's (a.c.f.'s) in the presence of sample anisotropy or a symmetry breaking field. In this case it is essential to regard the angular momentum a.c.f. as non-Markovian and methods are developed to relate this to the orientational a.c.f. in the presence of rotation/translation coupling. (author)

  16. New approaches for calculating Moran's index of spatial autocorrelation.

    Science.gov (United States)

    Chen, Yanguang

    2013-01-01

    Spatial autocorrelation plays an important role in geographical analysis; however, there is still room for improvement of this method. The formula for Moran's index is complicated, and several basic problems remain to be solved. Therefore, I will reconstruct its mathematical framework using mathematical derivation based on linear algebra and present four simple approaches to calculating Moran's index. Moran's scatterplot will be ameliorated, and new test methods will be proposed. The relationship between the global Moran's index and Geary's coefficient will be discussed from two different vantage points: spatial population and spatial sample. The sphere of applications for both Moran's index and Geary's coefficient will be clarified and defined. One of theoretical findings is that Moran's index is a characteristic parameter of spatial weight matrices, so the selection of weight functions is very significant for autocorrelation analysis of geographical systems. A case study of 29 Chinese cities in 2000 will be employed to validate the innovatory models and methods. This work is a methodological study, which will simplify the process of autocorrelation analysis. The results of this study will lay the foundation for the scaling analysis of spatial autocorrelation.

  17. New approaches for calculating Moran's index of spatial autocorrelation.

    Directory of Open Access Journals (Sweden)

    Yanguang Chen

    Full Text Available Spatial autocorrelation plays an important role in geographical analysis; however, there is still room for improvement of this method. The formula for Moran's index is complicated, and several basic problems remain to be solved. Therefore, I will reconstruct its mathematical framework using mathematical derivation based on linear algebra and present four simple approaches to calculating Moran's index. Moran's scatterplot will be ameliorated, and new test methods will be proposed. The relationship between the global Moran's index and Geary's coefficient will be discussed from two different vantage points: spatial population and spatial sample. The sphere of applications for both Moran's index and Geary's coefficient will be clarified and defined. One of theoretical findings is that Moran's index is a characteristic parameter of spatial weight matrices, so the selection of weight functions is very significant for autocorrelation analysis of geographical systems. A case study of 29 Chinese cities in 2000 will be employed to validate the innovatory models and methods. This work is a methodological study, which will simplify the process of autocorrelation analysis. The results of this study will lay the foundation for the scaling analysis of spatial autocorrelation.

  18. Autocorrelated process control: Geometric Brownian Motion approach versus Box-Jenkins approach

    Science.gov (United States)

    Salleh, R. M.; Zawawi, N. I.; Gan, Z. F.; Nor, M. E.

    2018-04-01

    Existing of autocorrelation will bring a significant effect on the performance and accuracy of process control if the problem does not handle carefully. When dealing with autocorrelated process, Box-Jenkins method will be preferred because of the popularity. However, the computation of Box-Jenkins method is too complicated and challenging which cause of time-consuming. Therefore, an alternative method which known as Geometric Brownian Motion (GBM) is introduced to monitor the autocorrelated process. One real case of furnace temperature data is conducted to compare the performance of Box-Jenkins and GBM methods in monitoring autocorrelation process. Both methods give the same results in terms of model accuracy and monitoring process control. Yet, GBM is superior compared to Box-Jenkins method due to its simplicity and practically with shorter computational time.

  19. MATLAB-Based Program for Teaching Autocorrelation Function and Noise Concepts

    Science.gov (United States)

    Jovanovic Dolecek, G.

    2012-01-01

    An attractive MATLAB-based tool for teaching the basics of autocorrelation function and noise concepts is presented in this paper. This tool enhances traditional in-classroom lecturing. The demonstrations of the tool described here highlight the description of the autocorrelation function (ACF) in a general case for wide-sense stationary (WSS)…

  20. Generalised partial autocorrelations and the mutual information between past and future

    DEFF Research Database (Denmark)

    Proietti, Tommaso; Luati, Alessandra

    the generalized partial autocorrelations as the partial autocorrelation coefficients of an auxiliary process, we derive their properties and relate them to essential features of the original process. Based on a parameterisation suggested by Barndorff-Nielsen and Schou (1973) and on Whittle likelihood, we develop...

  1. Adaptive endpoint detection of seismic signal based on auto-correlated function

    International Nuclear Information System (INIS)

    Fan Wanchun; Shi Ren

    2001-01-01

    Based on the analysis of auto-correlation function, the notion of the distance between auto-correlation function was quoted, and the characterization of the noise and the signal with noise were discussed by using the distance. Then, the method of auto- adaptable endpoint detection of seismic signal based on auto-correlated similarity was summed up. The steps of implementation and determining of the thresholds were presented in detail. The experimental results that were compared with the methods based on artificial detecting show that this method has higher sensitivity even in a low signal with noise ratio circumstance

  2. The specification of weight structures in network autocorrelation models of social influence

    NARCIS (Netherlands)

    Leenders, Roger Th.A.J.

    2002-01-01

    Many physical and social phenomena are embedded within networks of interdependencies, the so-called 'context' of these phenomena. In network analysis, this type of process is typically modeled as a network autocorrelation model. Parameter estimates and inferences based on autocorrelation models,

  3. Spectrum sensing algorithm based on autocorrelation energy in cognitive radio networks

    Science.gov (United States)

    Ren, Shengwei; Zhang, Li; Zhang, Shibing

    2016-10-01

    Cognitive radio networks have wide applications in the smart home, personal communications and other wireless communication. Spectrum sensing is the main challenge in cognitive radios. This paper proposes a new spectrum sensing algorithm which is based on the autocorrelation energy of signal received. By taking the autocorrelation energy of the received signal as the statistics of spectrum sensing, the effect of the channel noise on the detection performance is reduced. Simulation results show that the algorithm is effective and performs well in low signal-to-noise ratio. Compared with the maximum generalized eigenvalue detection (MGED) algorithm, function of covariance matrix based detection (FMD) algorithm and autocorrelation-based detection (AD) algorithm, the proposed algorithm has 2 11 dB advantage.

  4. A Quantized Analog Delay for an ir-UWB Quadrature Downconversion Autocorrelation Receiver

    NARCIS (Netherlands)

    Bagga, S.; Zhang, L.; Serdijn, W.A.; Long, J.R.; Busking, E.B.

    2005-01-01

    A quantized analog delay is designed as a requirement for the autocorrelation function in the quadrature downconversion autocorrelation receiver (QDAR). The quantized analog delay is comprised of a quantizer, multiple binary delay lines and an adder circuit. Being the foremost element, the quantizer

  5. Binary codes with impulse autocorrelation functions for dynamic experiments

    International Nuclear Information System (INIS)

    Corran, E.R.; Cummins, J.D.

    1962-09-01

    A series of binary codes exist which have autocorrelation functions approximating to an impulse function. Signals whose behaviour in time can be expressed by such codes have spectra which are 'whiter' over a limited bandwidth and for a finite time than signals from a white noise generator. These codes are used to determine system dynamic responses using the correlation technique. Programmes have been written to compute codes of arbitrary length and to compute 'cyclic' autocorrelation and cross-correlation functions. Complete listings of these programmes are given, and a code of 1019 bits is presented. (author)

  6. Adaptive non-collinear autocorrelation of few-cycle pulses with an angular tunable bi-mirror

    Energy Technology Data Exchange (ETDEWEB)

    Treffer, A., E-mail: treffer@mbi-berlin.de; Bock, M.; König, S.; Grunwald, R. [Max Born Institute for Nonlinear Optics and Short-Pulse Spectroscopy, Max Born Strasse 2A, D-12489 Berlin (Germany); Brunne, J.; Wallrabe, U. [Laboratory for Microactuators, Department of Microsystems Engineering, IMTEK, University of Freiburg, Georges-Koehler-Allee 102, Freiburg 79110 (Germany)

    2016-02-01

    Adaptive autocorrelation with an angular tunable micro-electro-mechanical system is reported. A piezo-actuated Fresnel bi-mirror structure was applied to measure the second order autocorrelation of near-infrared few-cycle laser pulses in a non-collinear setup at tunable superposition angles. Because of enabling measurements with variable scaling and minimizing the influence of distortions by adaptive self-reconstruction, the approach extends the capability of autocorrelators. Flexible scaling and robustness against localized amplitude obscurations are demonstrated. The adaptive reconstruction of temporal frequency information by the Fourier analysis of autocorrelation data is shown. Experimental results and numerical simulations of the beam propagation and interference are compared for variable angles.

  7. Momentum autocorrelation function of a classic diatomic chain

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Ming B., E-mail: mingbyu@gmail.com

    2016-10-23

    A classical harmonic diatomic chain is studied using the recurrence relations method. The momentum autocorrelation function results from contributions of acoustic and optical branches. By use of convolution theorem, analytical expressions for the acoustic and optical contributions are derived as even-order Bessel function expansions with coefficients given in terms of integrals of elliptic functions in real axis and a contour parallel to the imaginary axis, respectively. - Highlights: • Momentum autocorrelation function of a classic diatomic chain is studied. • It is derived as even-order Bessel function expansion using the convolution theorem. • The expansion coefficients are integrals of elliptic functions. • Addition theorem is used to reduce complex elliptic function to complex sum of real ones.

  8. Biometric feature extraction using local fractal auto-correlation

    International Nuclear Information System (INIS)

    Chen Xi; Zhang Jia-Shu

    2014-01-01

    Image texture feature extraction is a classical means for biometric recognition. To extract effective texture feature for matching, we utilize local fractal auto-correlation to construct an effective image texture descriptor. Three main steps are involved in the proposed scheme: (i) using two-dimensional Gabor filter to extract the texture features of biometric images; (ii) calculating the local fractal dimension of Gabor feature under different orientations and scales using fractal auto-correlation algorithm; and (iii) linking the local fractal dimension of Gabor feature under different orientations and scales into a big vector for matching. Experiments and analyses show our proposed scheme is an efficient biometric feature extraction approach. (condensed matter: structural, mechanical, and thermal properties)

  9. Crude oil market efficiency and modeling. Insights from the multiscaling autocorrelation pattern

    International Nuclear Information System (INIS)

    Alvarez-Ramirez, Jose; Alvarez, Jesus; Solis, Ricardo

    2010-01-01

    Empirical research on market inefficiencies focuses on the detection of autocorrelations in price time series. In the case of crude oil markets, statistical support is claimed for weak efficiency over a wide range of time-scales. However, the results are still controversial since theoretical arguments point to deviations from efficiency as prices tend to revert towards an equilibrium path. This paper studies the efficiency of crude oil markets by using lagged detrended fluctuation analysis (DFA) to detect delay effects in price autocorrelations quantified in terms of a multiscaling Hurst exponent (i.e., autocorrelations are dependent of the time scale). Results based on spot price data for the period 1986-2009 indicate important deviations from efficiency associated to lagged autocorrelations, so imposing the random walk for crude oil prices has pronounced costs for forecasting. Evidences in favor of price reversion to a continuously evolving mean underscores the importance of adequately incorporating delay effects and multiscaling behavior in the modeling of crude oil price dynamics. (author)

  10. Crude oil market efficiency and modeling. Insights from the multiscaling autocorrelation pattern

    Energy Technology Data Exchange (ETDEWEB)

    Alvarez-Ramirez, Jose [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico D.F., 09340 (Mexico); Departamento de Economia, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico D.F., 09340 (Mexico); Alvarez, Jesus [Departamento de Ingenieria de Procesos e Hidraulica, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico D.F., 09340 (Mexico); Solis, Ricardo [Departamento de Economia, Universidad Autonoma Metropolitana-Iztapalapa, Apartado Postal 55-534, Mexico D.F., 09340 (Mexico)

    2010-09-15

    Empirical research on market inefficiencies focuses on the detection of autocorrelations in price time series. In the case of crude oil markets, statistical support is claimed for weak efficiency over a wide range of time-scales. However, the results are still controversial since theoretical arguments point to deviations from efficiency as prices tend to revert towards an equilibrium path. This paper studies the efficiency of crude oil markets by using lagged detrended fluctuation analysis (DFA) to detect delay effects in price autocorrelations quantified in terms of a multiscaling Hurst exponent (i.e., autocorrelations are dependent of the time scale). Results based on spot price data for the period 1986-2009 indicate important deviations from efficiency associated to lagged autocorrelations, so imposing the random walk for crude oil prices has pronounced costs for forecasting. Evidences in favor of price reversion to a continuously evolving mean underscores the importance of adequately incorporating delay effects and multiscaling behavior in the modeling of crude oil price dynamics. (author)

  11. Adaptive endpoint detection of seismic signal based on auto-correlated function

    International Nuclear Information System (INIS)

    Fan Wanchun; Shi Ren

    2000-01-01

    There are certain shortcomings for the endpoint detection by time-waveform envelope and/or by checking the travel table (both labelled as the artificial detection method). Based on the analysis of the auto-correlation function, the notion of the distance between auto-correlation functions was quoted, and the characterizations of the noise and the signal with noise were discussed by using the distance. Then, the method of auto-adaptable endpoint detection of seismic signal based on auto-correlated similarity was summed up. The steps of implementation and determining of the thresholds were presented in detail. The experimental results that were compared with the methods based on artificial detecting show that this method has higher sensitivity even in a low SNR circumstance

  12. A broadly tunable autocorrelator for ultra-short, ultra-high power infrared optical pulses

    Energy Technology Data Exchange (ETDEWEB)

    Szarmes, E.B.; Madey, J.M.J. [Duke Univ., Durham, NC (United States)

    1995-12-31

    We describe the design of a crossed-beam, optical autocorrelator that uses an uncoated, birefringent beamsplitter to split a linearly polarized incident pulse into two orthogonally polarized pulses, and a Type II, SHG crystal to generate the intensity autocorrelation function. The uncoated beamsplitter accommodates extremely broad tunability while precluding any temporal distortion of ultrashort optical pulses at the dielectric interface, and the specific design provides efficient operation between 1 {mu}m and 4 {mu}m. Furthermore, the use of Type II SHG completely eliminates any single-beam doubling, so the autocorrelator can be operated at very shallow crossed-beam angles without generating a background pedestal. The autocorrelator has been constructed and installed in the Mark III laboratory at Duke University as a broadband diagnostic for ongoing compression experiments on the chirped-pulse FEL.

  13. Rigorous home range estimation with movement data: a new autocorrelated kernel density estimator.

    Science.gov (United States)

    Fleming, C H; Fagan, W F; Mueller, T; Olson, K A; Leimgruber, P; Calabrese, J M

    2015-05-01

    Quantifying animals' home ranges is a key problem in ecology and has important conservation and wildlife management applications. Kernel density estimation (KDE) is a workhorse technique for range delineation problems that is both statistically efficient and nonparametric. KDE assumes that the data are independent and identically distributed (IID). However, animal tracking data, which are routinely used as inputs to KDEs, are inherently autocorrelated and violate this key assumption. As we demonstrate, using realistically autocorrelated data in conventional KDEs results in grossly underestimated home ranges. We further show that the performance of conventional KDEs actually degrades as data quality improves, because autocorrelation strength increases as movement paths become more finely resolved. To remedy these flaws with the traditional KDE method, we derive an autocorrelated KDE (AKDE) from first principles to use autocorrelated data, making it perfectly suited for movement data sets. We illustrate the vastly improved performance of AKDE using analytical arguments, relocation data from Mongolian gazelles, and simulations based upon the gazelle's observed movement process. By yielding better minimum area estimates for threatened wildlife populations, we believe that future widespread use of AKDE will have significant impact on ecology and conservation biology.

  14. Nanoscale and femtosecond optical autocorrelator based on a single plasmonic nanostructure

    International Nuclear Information System (INIS)

    Melentiev, P N; Afanasiev, A E; Balykin, V I; Tausenev, A V; Konyaschenko, A V; Klimov, V V

    2014-01-01

    We demonstrated a nanoscale size, ultrafast and multiorder optical autocorrelator with a single plasmonic nanostructure for measuring the spatio-temporal dynamics of femtosecond laser light. As a nanostructure, we use a split hole resonator (SHR), which was made in an aluminium nanofilm. The Al material yields the fastest response time (100 as). The SHR nanostructure ensures a high nonlinear optical efficiency of the interaction with laser radiation, which leads to (1) the second, (2) the third harmonics generation and (3) the multiphoton luminescence, which, in turn, are used to perform multi-order autocorrelation measurements. The nano-sized SHR makes it possible to conduct autocorrelation measurements (i) with a subwavelength spatial resolution and (ii) with no significant influence on the duration of the laser pulse. The time response realized by the SHR nanostructure is about 10 fs. (letter)

  15. Thirty-two phase sequences design with good autocorrelation ...

    Indian Academy of Sciences (India)

    mum peak aperiodic autocorrelation sidelobe level one are called Barker Sequences. ... the generation and processing of polyphase signals have now become easy ..... Cook C E, Bernfield M 1967 An introduction to theory and application.

  16. Spectral Velocity Estimation using the Autocorrelation Function and Sparse data Sequences

    DEFF Research Database (Denmark)

    Jensen, Jørgen Arendt

    2005-01-01

    Ultrasound scanners can be used for displaying the distribution of velocities in blood vessels by finding the power spectrum of the received signal. It is desired to show a B-mode image for orientation and data for this has to be acquired interleaved with the flow data. Techniques for maintaining...... both the B-mode frame rate, and at the same time have the highest possible $f_{prf}$ only limited by the depth of investigation, are, thus, of great interest. The power spectrum can be calculated from the Fourier transform of the autocorrelation function $R_r(k)$. The lag $k$ corresponds...... of the sequence. The audio signal has also been synthesized from the autocorrelation data by passing white, Gaussian noise through a filter designed from the power spectrum of the autocorrelation function. The results show that both the full velocity range can be maintained at the same time as a B-mode image...

  17. Performing T-tests to Compare Autocorrelated Time Series Data Collected from Direct-Reading Instruments.

    Science.gov (United States)

    O'Shaughnessy, Patrick; Cavanaugh, Joseph E

    2015-01-01

    Industrial hygienists now commonly use direct-reading instruments to evaluate hazards in the workplace. The stored values over time from these instruments constitute a time series of measurements that are often autocorrelated. Given the need to statistically compare two occupational scenarios using values from a direct-reading instrument, a t-test must consider measurement autocorrelation or the resulting test will have a largely inflated type-1 error probability (false rejection of the null hypothesis). A method is described for both the one-sample and two-sample cases which properly adjusts for autocorrelation. This method involves the computation of an "equivalent sample size" that effectively decreases the actual sample size when determining the standard error of the mean for the time series. An example is provided for the one-sample case, and an example is given where a two-sample t-test is conducted for two autocorrelated time series comprised of lognormally distributed measurements.

  18. Modified Exponential Weighted Moving Average (EWMA) Control Chart on Autocorrelation Data

    Science.gov (United States)

    Herdiani, Erna Tri; Fandrilla, Geysa; Sunusi, Nurtiti

    2018-03-01

    In general, observations of the statistical process control are assumed to be mutually independence. However, this assumption is often violated in practice. Consequently, statistical process controls were developed for interrelated processes, including Shewhart, Cumulative Sum (CUSUM), and exponentially weighted moving average (EWMA) control charts in the data that were autocorrelation. One researcher stated that this chart is not suitable if the same control limits are used in the case of independent variables. For this reason, it is necessary to apply the time series model in building the control chart. A classical control chart for independent variables is usually applied to residual processes. This procedure is permitted provided that residuals are independent. In 1978, Shewhart modification for the autoregressive process was introduced by using the distance between the sample mean and the target value compared to the standard deviation of the autocorrelation process. In this paper we will examine the mean of EWMA for autocorrelation process derived from Montgomery and Patel. Performance to be investigated was investigated by examining Average Run Length (ARL) based on the Markov Chain Method.

  19. Covariance Estimation and Autocorrelation of NORAD Two-Line Element Sets

    National Research Council Canada - National Science Library

    Osweiler, Victor P

    2006-01-01

    This thesis investigates NORAD two-line element sets (TLE) containing satellite mean orbital elements for the purpose of estimating a covariance matrix and formulating an autocorrelation relationship...

  20. Spatial autocorrelation analysis of tourist arrivals using municipal data: A Serbian example

    Directory of Open Access Journals (Sweden)

    Stankov Uglješa

    2017-01-01

    Full Text Available Spatial autocorrelation methodologies can be used to reveal patterns and temporal changes of different spatial variables, including tourism arrivals. The research adopts a GIS-based approach to spatially analyse tourist arrivals in Serbia, using Global Moran's I and Anselin's Local Moran's I statistics applied on the level of municipalities. To assess feasibility of this approach the article discusses spatial changes of tourist arrivals in order to identify potentially significant trends of interest for tourism development policy in Serbia. There is a significant spatial inequality in the distribution of tourism arrivals in Serbia that is not adequately addressed in tourism development plans. The results of global autocorrelation suggest the existence of low and decreasing spatial clustering for domestic tourist arrivals and high, relatively stable spatial clustering for international tourists. Local autocorrelation statistics revealed different of domestic and international tourism arrivals. In order to assess feasibility of this approach these results are discussed in their significance to tourism development policy in Serbia.

  1. Performances Of Estimators Of Linear Models With Autocorrelated ...

    African Journals Online (AJOL)

    The performances of five estimators of linear models with Autocorrelated error terms are compared when the independent variable is autoregressive. The results reveal that the properties of the estimators when the sample size is finite is quite similar to the properties of the estimators when the sample size is infinite although ...

  2. Waveguide superconducting single-photon autocorrelators for quantum photonic applications

    NARCIS (Netherlands)

    Sahin, D.; Gaggero, A.; Frucci, G.; Jahanmirinejad, S.; Sprengers, J.P.; Mattioli, F.; Leoni, R.; Beetz, J.; Lermer, M.; Kamp, M.; Höfling, S.; Fiore, A.; Hasan, Z.U.; Hemmer, P.R.; Lee, H.; Santori, C.M.

    2013-01-01

    We report a novel component for integrated quantum photonic applications, a waveguide single-photon autocorrelator. It is based on two superconducting nanowire detectors patterned onto the same GaAs ridge waveguide. Combining the electrical output of the two detectors in a correlation card enables

  3. Performances of estimators of linear auto-correlated error model ...

    African Journals Online (AJOL)

    The performances of five estimators of linear models with autocorrelated disturbance terms are compared when the independent variable is exponential. The results reveal that for both small and large samples, the Ordinary Least Squares (OLS) compares favourably with the Generalized least Squares (GLS) estimators in ...

  4. Distributions of Autocorrelated First-Order Kinetic Outcomes: Illness Severity.

    Directory of Open Access Journals (Sweden)

    James D Englehardt

    Full Text Available Many complex systems produce outcomes having recurring, power law-like distributions over wide ranges. However, the form necessarily breaks down at extremes, whereas the Weibull distribution has been demonstrated over the full observed range. Here the Weibull distribution is derived as the asymptotic distribution of generalized first-order kinetic processes, with convergence driven by autocorrelation, and entropy maximization subject to finite positive mean, of the incremental compounding rates. Process increments represent multiplicative causes. In particular, illness severities are modeled as such, occurring in proportion to products of, e.g., chronic toxicant fractions passed by organs along a pathway, or rates of interacting oncogenic mutations. The Weibull form is also argued theoretically and by simulation to be robust to the onset of saturation kinetics. The Weibull exponential parameter is shown to indicate the number and widths of the first-order compounding increments, the extent of rate autocorrelation, and the degree to which process increments are distributed exponential. In contrast with the Gaussian result in linear independent systems, the form is driven not by independence and multiplicity of process increments, but by increment autocorrelation and entropy. In some physical systems the form may be attracting, due to multiplicative evolution of outcome magnitudes towards extreme values potentially much larger and smaller than control mechanisms can contain. The Weibull distribution is demonstrated in preference to the lognormal and Pareto I for illness severities versus (a toxicokinetic models, (b biologically-based network models, (c scholastic and psychological test score data for children with prenatal mercury exposure, and (d time-to-tumor data of the ED01 study.

  5. Estimating the variation, autocorrelation, and environmental sensitivity of phenotypic selection

    NARCIS (Netherlands)

    Chevin, Luis-Miguel; Visser, Marcel E.; Tufto, Jarle

    2015-01-01

    Despite considerable interest in temporal and spatial variation of phenotypic selection, very few methods allow quantifying this variation while correctly accounting for the error variance of each individual estimate. Furthermore, the available methods do not estimate the autocorrelation of

  6. Estimating the variation, autocorrelation, and environmental sensitivity of phenotypic selection

    NARCIS (Netherlands)

    Chevin, Luis-Miguel; Visser, Marcel E.; Tufto, Jarle

    Despite considerable interest in temporal and spatial variation of phenotypic selection, very few methods allow quantifying this variation while correctly accounting for the error variance of each individual estimate. Furthermore, the available methods do not estimate the autocorrelation of

  7. Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts.

    Science.gov (United States)

    Crase, Beth; Liedloff, Adam; Vesk, Peter A; Fukuda, Yusuke; Wintle, Brendan A

    2014-08-01

    Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate

  8. Recursive Estimation for Dynamical Systems with Different Delay Rates Sensor Network and Autocorrelated Process Noises

    Directory of Open Access Journals (Sweden)

    Jianxin Feng

    2014-01-01

    Full Text Available The recursive estimation problem is studied for a class of uncertain dynamical systems with different delay rates sensor network and autocorrelated process noises. The process noises are assumed to be autocorrelated across time and the autocorrelation property is described by the covariances between different time instants. The system model under consideration is subject to multiplicative noises or stochastic uncertainties. The sensor delay phenomenon occurs in a random way and each sensor in the sensor network has an individual delay rate which is characterized by a binary switching sequence obeying a conditional probability distribution. By using the orthogonal projection theorem and an innovation analysis approach, the desired recursive robust estimators including recursive robust filter, predictor, and smoother are obtained. Simulation results are provided to demonstrate the effectiveness of the proposed approaches.

  9. What autocorrelation tells us about motor variability: insights from dart throwing.

    Directory of Open Access Journals (Sweden)

    Robert J van Beers

    Full Text Available In sports such as golf and darts it is important that one can produce ballistic movements of an object towards a goal location with as little variability as possible. A factor that influences this variability is the extent to which motor planning is updated from movement to movement based on observed errors. Previous work has shown that for reaching movements, our motor system uses the learning rate (the proportion of an error that is corrected for in the planning of the next movement that is optimal for minimizing the endpoint variability. Here we examined whether the learning rate is hard-wired and therefore automatically optimal, or whether it is optimized through experience. We compared the performance of experienced dart players and beginners in a dart task. A hallmark of the optimal learning rate is that the lag-1 autocorrelation of movement endpoints is zero. We found that the lag-1 autocorrelation of experienced dart players was near zero, implying a near-optimal learning rate, whereas it was negative for beginners, suggesting a larger than optimal learning rate. We conclude that learning rates for trial-by-trial motor learning are optimized through experience. This study also highlights the usefulness of the lag-1 autocorrelation as an index of performance in studying motor-skill learning.

  10. Coded aperture imagery filtered autocorrelation decoding; Imagerie par ouverture de codage decodage par autocorrelation filtree

    Energy Technology Data Exchange (ETDEWEB)

    Rouyer, A. [CEA Bruyeres-le-Chatel, 91 (France)

    2005-10-15

    Coded aperture imagery is particularly suited for imaging objects emitting penetrating radiation (hard X rays, gamma, neutrons), or for particles with rectilinear trajectories (electrons, protons, alpha particles, etc.). It is used when methods based on classical optical principles (reflection, refraction, diffraction), are invalid, or when the source emission is too weak for the well known pinhole method to give a usable image. The optical system consists in an aperture through an absorbing screen, named coding aperture, whose transmission is calculated in such a way that the spatial resolution is similar to that of a simple pinhole device, but with a far superior radiation collecting efficiency. We present a new decoding method,, called filtered autocorrelation, and illustrate its performances on images obtained with various coding apertures. (author)

  11. Spatial autocorrelation in farmland grasshopper assemblages (Orthoptera: Acrididae) in western France.

    Science.gov (United States)

    Badenhausser, I; Gouat, M; Goarant, A; Cornulier, T; Bretagnolle, V

    2012-10-01

    Agricultural intensification in western Europe has caused a dramatic loss of grassland surfaces in farmlands, which have resulted in strong declines in grassland invertebrates, leading to cascade effects at higher trophic levels among consumers of invertebrates. Grasshoppers are important components of grassland invertebrate assemblages in European agricultural ecosystems, particularly as prey for bird species. Understanding how grasshopper populations are distributed in fragmented landscapes with low grassland availability is critical for both studies in biodiversity conservation and insect management. We assessed the range and strength of spatial autocorrelation for two grasshopper taxa (Gomphocerinae subfamily and Calliptamus italicus L.) across an intensive farmland in western France. Data from surveys carried out over 8 yr in 1,715 grassland fields were analyzed using geostatistics. Weak spatial patterns were observed at small spatial scales, suggesting important local effects of management practices on grasshopper densities. Spatial autocorrelation patterns for both grasshopper taxa were only detected at intermediate scales. For Gomphocerinae, the range of spatial autocorrelation varied from 802 to 2,613 m according to the year, depending both on grasshopper density and on grassland surfaces in the study site, whereas spatial patterns for the Italian locust were more variable and not related to grasshopper density or grassland surfaces. Spatial patterns in the distribution of Gomphocerinae supported our hypothesis that habitat availability was a major driver of grasshopper distribution in the landscape, and suggested it was related to density-dependent processes such as dispersal.

  12. Detecting land cover change using a sliding window temporal autocorrelation approach

    CSIR Research Space (South Africa)

    Kleynhans, W

    2012-07-01

    Full Text Available There has been recent developments in the use of hypertemporal satellite time series data for land cover change detection and classification. Recently, an Autocorrelation function (ACF) change detection method was proposed to detect the development...

  13. Sum rule and hydrodynamic analyses of the velocity autocorrelation function in strongly coupled plasmas

    International Nuclear Information System (INIS)

    Nagano, Seido; Ichimaru, Setsuo

    1980-01-01

    The memory function for the velocity autocorrelation function in a strongly coupled, one-component plasma is analyzed in the short time and long time domains, respectively, with the aid of the frequency-moment sum rules and the hydrodynamic consideration evoking the idea of the generalized Stokes friction. A series of interpolation schemes with successively improved accuracies are then introduced. Numerical investigations of those interpolation schemes clarify the physical origin of the three different types of the velocity autocorrelation function observed in the molecular dynamics simulation at different regimes of the coupling constant. (author)

  14. The Effect of Autocorrelation on the Hotelling T-2 Control Chart

    DEFF Research Database (Denmark)

    Vanhatalo, Erik; Kulahci, Murat

    2015-01-01

    One of the basic assumptions for traditional univariate and multivariate control charts is that the data are independent in time. For the latter, in many cases, the data are serially dependent (autocorrelated) and cross-correlated because of, for example, frequent sampling and process dynamics......- correlation structures for different magnitudes of shifts in the process mean is not fully explored in the literature. In this article, the performance of the Hotelling T-2 control chart for different shift sizes and various autocorrelation and cross- correlation structures are compared based on the average...... and using the raw data with adjusted control limits calculated through Monte Carlo simulations; and (iii) constructing the control chart for the residuals from a multivariate time series model fitted to the raw data. To limit the complexity, we use a first-order vector autoregressive process and focus...

  15. OFDM Signal Detector Based on Cyclic Autocorrelation Function and its Properties

    Directory of Open Access Journals (Sweden)

    Z. Fedra

    2011-12-01

    Full Text Available This paper is devoted to research of the general and particular properties of the OFDM signal detector based on the cyclic autocorrelation function. The cyclic autocorrelation function is estimated using DFT. The parameters of the testing signal have been chosen according to 802.11g WLAN. Some properties are described analytically; all events are examined via computer simulations. It is shown that the detector is able to detect an OFDM signal in the case of multipath propagation, inexact frequency synchronization and without time synchronization. The sensitivity of the detector could be decreased in the above cases. An important condition for proper value of the detector sampling interval was derived. Three types of the channels were studied and compared. Detection threshold SNR=-9 dB was found for the signal under consideration and for two-way propagation.

  16. Spatial autocorrelation method using AR model; Kukan jiko sokanho eno AR model no tekiyo

    Energy Technology Data Exchange (ETDEWEB)

    Yamamoto, H; Obuchi, T; Saito, T [Iwate University, Iwate (Japan). Faculty of Engineering

    1996-05-01

    Examination was made about the applicability of the AR model to the spatial autocorrelation (SAC) method, which analyzes the surface wave phase velocity in a microtremor, for the estimation of the underground structure. In this examination, microtremor data recorded in Morioka City, Iwate Prefecture, was used. In the SAC method, a spatial autocorrelation function with the frequency as a variable is determined from microtremor data observed by circular arrays. Then, the Bessel function is adapted to the spatial autocorrelation coefficient with the distance between seismographs as a variable for the determination of the phase velocity. The result of the AR model application in this study and the results of the conventional BPF and FFT method were compared. It was then found that the phase velocities obtained by the BPF and FFT methods were more dispersed than the same obtained by the AR model. The dispersion in the BPF method is attributed to the bandwidth used in the band-pass filter and, in the FFT method, to the impact of the bandwidth on the smoothing of the cross spectrum. 2 refs., 7 figs.

  17. Toward sub-femtosecond pump-probe experiments: a dispersionless autocorrelator with attosecond resolution

    Energy Technology Data Exchange (ETDEWEB)

    Constant, E.; Mevel, E.; Zair, A.; Bagnoud, V.; Salin, F. [Bordeaux-1 Univ., Talence (FR). Centre Lasers Intenses et Applications (CELIA)

    2001-07-01

    We designed a dispersionless autocorrelator with a sub-femtosecond resolution suitable for the characterization of ultrashort X-UV pulses. We present a proof of feasibility experiment with 11 fs infrared pulses. (orig.)

  18. Estimating the Autocorrelated Error Model with Trended Data: Further Results,

    Science.gov (United States)

    1979-11-01

    Perhaps the most serious deficiency of OLS in the presence of autocorrelation is not inefficiency but bias in its estimated standard errors--a bias...k for all t has variance var(b) = o2/ Tk2 2This refutes Maeshiro’s (1976) conjecture that "an estimator utilizing relevant extraneous information

  19. Autocorrelation as a source of truncated Lévy flights in foreign exchange rates

    Science.gov (United States)

    Figueiredo, Annibal; Gleria, Iram; Matsushita, Raul; Da Silva, Sergio

    2003-05-01

    We suggest that the ultraslow speed of convergence associated with truncated Lévy flights (Phys. Rev. Lett. 73 (1994) 2946) may well be explained by autocorrelations in data. We show how a particular type of autocorrelation generates power laws consistent with a truncated Lévy flight. Stock exchanges have been suggested to be modeled by a truncated Lévy flight (Nature 376 (1995) 46; Physica A 297 (2001) 509; Econom. Bull. 7 (2002) 1). Here foreign exchange rate data are taken instead. Scaling power laws in the “probability of return to the origin” are shown to emerge for most currencies. A novel approach to measure how distant a process is from a Gaussian regime is presented.

  20. Multivariate Process Control with Autocorrelated Data

    DEFF Research Database (Denmark)

    Kulahci, Murat

    2011-01-01

    As sensor and computer technology continues to improve, it becomes a normal occurrence that we confront with high dimensional data sets. As in many areas of industrial statistics, this brings forth various challenges in statistical process control and monitoring. This new high dimensional data...... often exhibit not only cross-­‐correlation among the quality characteristics of interest but also serial dependence as a consequence of high sampling frequency and system dynamics. In practice, the most common method of monitoring multivariate data is through what is called the Hotelling’s T2 statistic....... In this paper, we discuss the effect of autocorrelation (when it is ignored) on multivariate control charts based on these methods and provide some practical suggestions and remedies to overcome this problem....

  1. Simultaneous maximization of spatial and temporal autocorrelation in spatio-temporal data

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2002-01-01

    . This is done by solving the generalized eigenproblem represented by the Rayleigh coefficient where is the dispersion of and is the dispersion of the difference between and spatially shifted. Hence, the new variates are obtained from the conjugate eigenvectors and the autocorrelations obtained are , i.e., high...

  2. ON THE EFFECTS OF THE PRESENCE AND METHODS OF THE ELIMINATION HETEROSCEDASTICITY AND AUTOCORRELATION IN THE REGRESSION MODEL

    Directory of Open Access Journals (Sweden)

    Nina L. Timofeeva

    2014-01-01

    Full Text Available The article presents the methodological and technical bases for the creation of regression models that adequately reflect reality. The focus is on methods of removing residual autocorrelation in models. Algorithms eliminating heteroscedasticity and autocorrelation of the regression model residuals: reweighted least squares method, the method of Cochran-Orkutta are given. A model of "pure" regression is build, as well as to compare the effect on the dependent variable of the different explanatory variables when the latter are expressed in different units, a standardized form of the regression equation. The scheme of abatement techniques of heteroskedasticity and autocorrelation for the creation of regression models specific to the social and cultural sphere is developed.

  3. Robustness of variance and autocorrelation as indicators of critical slowing down

    NARCIS (Netherlands)

    Dakos, V.; Nes, van E.H.; Odorico, D' P.; Scheffer, M.

    2012-01-01

    Ecosystems close to a critical threshold lose resilience, in the sense that perturbations can more easily push them into an alternative state. Recently, it has been proposed that such loss of resilience may be detected from elevated autocorrelation and variance in the fluctuations of the state of an

  4. A spatio-temporal autocorrelation change detection approach using hyper-temporal satellite data

    CSIR Research Space (South Africa)

    Kleynhans, W

    2013-07-01

    Full Text Available -1 IEEE International Geoscience and Remote Sensing Symposium, Melbourne, Australia 21-26 July 2013 A SPATIO-TEMPORAL AUTOCORRELATION CHANGE DETECTION APPROACH USING HYPER-TEMPORAL SATELLITE DATA yzW. Kleynhans, yz,B.P Salmon,zK. J. Wessels...

  5. Power properties of invariant tests for spatial autocorrelation in linear regression

    NARCIS (Netherlands)

    Martellosio, F.

    2006-01-01

    Many popular tests for residual spatial autocorrelation in the context of the linear regression model belong to the class of invariant tests. This paper derives a number of exact properties of the power function of such tests. In particular, we extend the work of Krämer (2005, Journal of Statistical

  6. Velocity-Autocorrelation Function in Liquids, Deduced from Neutron Incoherent Scattering Results

    DEFF Research Database (Denmark)

    Carneiro, Kim

    1976-01-01

    The Fourier transform p(ω) of the velocity-autocorrelation function is derived from neutron incoherent scattering results, obtained from the two liquids Ar and H2. The quality and significance of the results are discussed with special emphasis on the long-time t-3/2 tail, found in computer simula...

  7. Spatial Autocorrelation Patterns of Understory Plant Species in a Subtropical Rainforest at Lanjenchi, Southern Taiwan

    Directory of Open Access Journals (Sweden)

    Su-Wei Fan

    2010-06-01

    Full Text Available Many studies described relationships between plant species and intrinsic or exogenous factors, but few quantified spatial scales of species patterns. In this study, quantitative methods were used to explore the spatial scale of understory species (including resident and transient species, in order to identify the influential factors of species distribution. Resident species (including herbaceous species, climbers and tree ferns < 1 m high were investigated on seven transects, each 5-meter wide and 300-meter long, at Lanjenchi plot in Nanjenshan Reserve, southern Taiwan. Transient species (seedling of canopy, subcanopy and shrub species < 1 cm diameter at breast height were censused in three of the seven transects. The herb coverage and seedling abundance were calculated for each 5 × 5 m quadrat along the transects, and Moran’s I and Galiano’s new local variance (NLV indices were then used to identify the spatial scale of autocorrelation for each species. Patterns of species abundance of understory layer varied among species at fine scale within 50 meters. Resident species showed a higher proportion of significant autocorrelation than the transient species. Species with large size or prolonged fronds or stems tended to show larger scales in autocorrelation. However, dispersal syndromes and fruit types did not relate to any species’ spatial patterns. Several species showed a significant autocorrelation at a 180-meter class which happened to correspond to the local replicates of topographical features in hilltops. The spatial patterns of understory species at Lanjenchi plot are mainly influenced by species’ intrinsic traits and topographical characteristics.

  8. Autocorrelation and cross-correlation in time series of homicide and attempted homicide

    Science.gov (United States)

    Machado Filho, A.; da Silva, M. F.; Zebende, G. F.

    2014-04-01

    We propose in this paper to establish the relationship between homicides and attempted homicides by a non-stationary time-series analysis. This analysis will be carried out by Detrended Fluctuation Analysis (DFA), Detrended Cross-Correlation Analysis (DCCA), and DCCA cross-correlation coefficient, ρ(n). Through this analysis we can identify a positive cross-correlation between homicides and attempted homicides. At the same time, looked at from the point of view of autocorrelation (DFA), this analysis can be more informative depending on time scale. For short scale (days), we cannot identify auto-correlations, on the scale of weeks DFA presents anti-persistent behavior, and for long time scales (n>90 days) DFA presents a persistent behavior. Finally, the application of this new type of statistical analysis proved to be efficient and, in this sense, this paper can contribute to a more accurate descriptive statistics of crime.

  9. Field test comparison of an autocorrelation technique for determining grain size using a digital 'beachball' camera versus traditional methods

    Science.gov (United States)

    Barnard, P.L.; Rubin, D.M.; Harney, J.; Mustain, N.

    2007-01-01

    This extensive field test of an autocorrelation technique for determining grain size from digital images was conducted using a digital bed-sediment camera, or 'beachball' camera. Using 205 sediment samples and >1200 images from a variety of beaches on the west coast of the US, grain size ranging from sand to granules was measured from field samples using both the autocorrelation technique developed by Rubin [Rubin, D.M., 2004. A simple autocorrelation algorithm for determining grain size from digital images of sediment. Journal of Sedimentary Research, 74(1): 160-165.] and traditional methods (i.e. settling tube analysis, sieving, and point counts). To test the accuracy of the digital-image grain size algorithm, we compared results with manual point counts of an extensive image data set in the Santa Barbara littoral cell. Grain sizes calculated using the autocorrelation algorithm were highly correlated with the point counts of the same images (r2 = 0.93; n = 79) and had an error of only 1%. Comparisons of calculated grain sizes and grain sizes measured from grab samples demonstrated that the autocorrelation technique works well on high-energy dissipative beaches with well-sorted sediment such as in the Pacific Northwest (r2 ??? 0.92; n = 115). On less dissipative, more poorly sorted beaches such as Ocean Beach in San Francisco, results were not as good (r2 ??? 0.70; n = 67; within 3% accuracy). Because the algorithm works well compared with point counts of the same image, the poorer correlation with grab samples must be a result of actual spatial and vertical variability of sediment in the field; closer agreement between grain size in the images and grain size of grab samples can be achieved by increasing the sampling volume of the images (taking more images, distributed over a volume comparable to that of a grab sample). In all field tests the autocorrelation method was able to predict the mean and median grain size with ???96% accuracy, which is more than

  10. Auto-correlation analysis of wave heights in the Bay of Bengal

    Indian Academy of Sciences (India)

    Time series observations of significant wave heights in the Bay of Bengal were subjected to auto- correlation analysis to determine temporal variability scale. The analysis indicates an exponen- tial fall of auto-correlation in the first few hours with a decorrelation time scale of about six hours. A similar figure was found earlier ...

  11. A Comparison of Weights Matrices on Computation of Dengue Spatial Autocorrelation

    Science.gov (United States)

    Suryowati, K.; Bekti, R. D.; Faradila, A.

    2018-04-01

    Spatial autocorrelation is one of spatial analysis to identify patterns of relationship or correlation between locations. This method is very important to get information on the dispersal patterns characteristic of a region and linkages between locations. In this study, it applied on the incidence of Dengue Hemorrhagic Fever (DHF) in 17 sub districts in Sleman, Daerah Istimewa Yogyakarta Province. The link among location indicated by a spatial weight matrix. It describe the structure of neighbouring and reflects the spatial influence. According to the spatial data, type of weighting matrix can be divided into two types: point type (distance) and the neighbourhood area (contiguity). Selection weighting function is one determinant of the results of the spatial analysis. This study use queen contiguity based on first order neighbour weights, queen contiguity based on second order neighbour weights, and inverse distance weights. Queen contiguity first order and inverse distance weights shows that there is the significance spatial autocorrelation in DHF, but not by queen contiguity second order. Queen contiguity first and second order compute 68 and 86 neighbour list

  12. A model-free approach to eliminate autocorrelation when testing for process capability

    DEFF Research Database (Denmark)

    Vanmann, Kerstin; Kulahci, Murat

    2008-01-01

    There is an increasing use of on-line data acquisition systems in industry. This usually leads to autocorrelated data and implies that the assumption of independent observations has to be re-examined. Most decision procedures for capability analysis assume independent data. In this article we pre...

  13. BetaBit: A fast generator of autocorrelated binary processes for geophysical research

    Science.gov (United States)

    Serinaldi, Francesco; Lombardo, Federico

    2017-05-01

    We introduce a fast and efficient non-iterative algorithm, called BetaBit, to simulate autocorrelated binary processes describing the occurrence of natural hazards, system failures, and other physical and geophysical phenomena characterized by persistence, temporal clustering, and low rate of occurrence. BetaBit overcomes the simulation constraints posed by the discrete nature of the marginal distributions of binary processes by using the link existing between the correlation coefficients of this process and those of the standard Gaussian processes. The performance of BetaBit is tested on binary signals with power-law and exponentially decaying autocorrelation functions (ACFs) corresponding to Hurst-Kolmogorov and Markov processes, respectively. An application to real-world sequences describing rainfall intermittency and the occurrence of strong positive phases of the North Atlantic Oscillation (NAO) index shows that BetaBit can also simulate surrogate data preserving the empirical ACF as well as signals with autoregressive moving average (ARMA) dependence structures. Extensions to cyclo-stationary processes accounting for seasonal fluctuations are also discussed.

  14. Size determinations of plutonium colloids using autocorrelation photon spectroscopy

    International Nuclear Information System (INIS)

    Triay, I.R.; Rundberg, R.S.; Mitchell, A.J.; Ott, M.A.; Hobart, D.E.; Palmer, P.D.; Newton, T.W.; Thompson, J.L.

    1989-01-01

    Autocorrelation Photon Spectroscopy (APS) is a light-scattering technique utilized to determine the size distribution of colloidal suspensions. The capabilities of the APS methodology have been assessed by analyzing colloids of known sizes. Plutonium(IV) colloid samples were prepared by a variety of methods including: dilution; peptization; and alpha-induced auto-oxidation of Pu(III). The size of theses Pu colloids was analyzed using APS. The sizes determined for the Pu colloids studied varied from 1 to 370 nanometers. 7 refs., 5 figs., 3 tabs

  15. Response predictions using the observed autocorrelation function

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam; H. Brodtkorb, Astrid; Jensen, Jørgen Juncher

    2018-01-01

    This article studies a procedure that facilitates short-time, deterministic predictions of the wave-induced motion of a marine vessel, where it is understood that the future motion of the vessel is calculated ahead of time. Such predictions are valuable to assist in the execution of many marine......-induced response in study. Thus, predicted (future) values ahead of time for a given time history recording are computed through a mathematical combination of the sample autocorrelation function and previous measurements recorded just prior to the moment of action. Importantly, the procedure does not need input...... show that predictions can be successfully made in a time horizon corresponding to about 8-9 wave periods ahead of current time (the moment of action)....

  16. Logistic regression for southern pine beetle outbreaks with spatial and temporal autocorrelation

    Science.gov (United States)

    M. L. Gumpertz; C.-T. Wu; John M. Pye

    2000-01-01

    Regional outbreaks of southern pine beetle (Dendroctonus frontalis Zimm.) show marked spatial and temporal patterns. While these patterns are of interest in themselves, we focus on statistical methods for estimating the effects of underlying environmental factors in the presence of spatial and temporal autocorrelation. The most comprehensive available information on...

  17. First measurements of subpicosecond electron beam structure by autocorrelation of coherent diffraction radiation

    CERN Document Server

    Lumpkin, Alex H; Rule, D W

    2001-01-01

    We report the initial measurements of subpicosecond electron beam structure using a nonintercepting technique based on the autocorrelation of coherent diffraction radiation (CDR). A far infrared (FIR) Michelson interferometer with a Golay detector was used to obtain the autocorrelation. The radiation was generated by a thermionic rf gun beam at 40 MeV as it passed through a 5-mm-tall slit/aperture in a metal screen whose surface was at 45 deg. to the beam direction. For the observed bunch lengths of about 450 fs (FWHM) with a shorter time spike on the leading edge, peak currents of about 100 A are indicated. Also a model was developed and used to calculate the CDR from the back of two metal strips separated by a 5-mm vertical gap. The demonstrated nonintercepting aspect of this method could allow on-line bunch length characterizations to be done during free-electron laser experiments.

  18. Autocorrelation based reconstruction of two-dimensional binary objects

    International Nuclear Information System (INIS)

    Mejia-Barbosa, Y.; Castaneda, R.

    2005-10-01

    A method for reconstructing two-dimensional binary objects from its autocorrelation function is discussed. The objects consist of a finite set of identical elements. The reconstruction algorithm is based on the concept of class of element pairs, defined as the set of element pairs with the same separation vector. This concept allows to solve the redundancy introduced by the element pairs of each class. It is also shown that different objects, consisting of an equal number of elements and the same classes of pairs, provide Fraunhofer diffraction patterns with identical intensity distributions. However, the method predicts all the possible objects that produce the same Fraunhofer pattern. (author)

  19. Auto-correlation of velocity-fluctuations and frequency-dependent diffusion constant for hot electrons

    International Nuclear Information System (INIS)

    Roy, M.D.; Nag, B.R.

    1981-01-01

    A method has been developed for determining the auto-correlation functions of the fluctuations in the transverse and the parallel components of hot carrier-velocity in a semiconductor by Monte Carlo simulation. The functions for electrons in InSb are determined by this method for applied electric fields of 50 V/cm, 75 V/cm, and 100 V/cm. With increasing value of the time interval the transverse auto-correlation function fall nearly exponentially to zero, but the parallel function falls sharply to a negative peak, then rises to positive values and finally becomes zero. The interval beyond which the auto-correlation function is zero and the correlation time are also evaluated. The correlation time is found to be approximately 1.6 times the relaxation time calculated from the chord mobility. The effect of the flight sampling time on the value of variance of the displacement, is investigated in terms of the low frequency diffusion constants, determined from the variation of the correlation functions. It is found that the diffusion constants become independent of the sampling time if it is of the order of one hundred times the relaxation time. The frequency-dependent diffusion constants are calculated from the correlation functions. The transverse diffusion constant falls monotonically with frequency for all the field strengths studied. The parallel diffusion constant has similar variation for the lower fields (50 V/cm and 75 V/cm) but it has a peak at about 44 GHz for the field of 100 V/cm. (orig.)

  20. Damage detection and isolation via autocorrelation: a step toward passive sensing

    Science.gov (United States)

    Chang, Y. S.; Yuan, F. G.

    2018-03-01

    Passive sensing technique may eliminate the need of expending power from actuators and thus provide a means of developing a compact and simple structural health monitoring system. More importantly, it may provide a solution for monitoring the aircraft subjected to environmental loading from air flow during operation. In this paper, a non-contact auto-correlation based technique is exploited as a feasibility study for passive sensing application to detect damage and isolate the damage location. Its theoretical basis bears some resemblance to reconstructing Green's function from diffusive wavefield through cross-correlation. Localized high pressure air from air compressor are randomly and continuously applied on the one side surface of the aluminum panels through the air blow gun. A laser Doppler vibrometer (LDV) was used to scan a 90 mm × 90 mm area to create a 6 × 6 2D-array signals from the opposite side of the panels. The scanned signals were auto-correlated to reconstruct a "selfimpulse response" (or Green's function). The premise for stably reconstructing the accurate Green's function requires long sensing times. For a 609.6 mm × 609.6 mm flat aluminum panel, the sensing times roughly at least four seconds is sufficient to establish converged Green's function through correlation. For the integral stiffened aluminum panel, the geometrical features of the panel expedite the formation of the diffusive wavefield and thus shorten the sensing times. The damage is simulated by gluing a magnet onto the panels. Reconstructed Green's functions (RGFs) are used for damage detection and damage isolation based on an imaging condition with mean square deviation of the RGFs from the pristine and the damaged structure and the results are shown in color maps. The auto-correlation based technique is shown to consistently detect the simulated damage, image and isolate the damage in the structure subjected to high pressure air excitation. This technique may be transformed into

  1. Assessment of smoothed spectra using autocorrelation function

    International Nuclear Information System (INIS)

    Urbanski, P.; Kowalska, E.

    2006-01-01

    Recently, data and signal smoothing became almost standard procedures in the spectrometric and chromatographic methods. In radiometry, the main purpose to apply smoothing is minimisation of the statistical fluctuation and avoid distortion. The aim of the work was to find a qualitative parameter, which could be used, as a figure of merit for detecting distortion of the smoothed spectra, based on the linear model. It is assumed that as long as the part of the raw spectrum removed by the smoothing procedure (v s ) will be of random nature, the smoothed spectrum can be considered as undistorted. Thanks to this feature of the autocorrelation function, drifts of the mean value in the removed noise vs as well as its periodicity can be more easily detected from the autocorrelogram than from the original data

  2. Break point on the auto-correlation function of Elsässer variable z- in the super-Alfvénic solar wind fluctuations

    Science.gov (United States)

    Wang, X.; Tu, C. Y.; He, J.; Wang, L.

    2017-12-01

    It has been a longstanding debate on what the nature of Elsässer variables z- observed in the Alfvénic solar wind is. It is widely believed that z- represents inward propagating Alfvén waves and undergoes non-linear interaction with z+ to produce energy cascade. However, z- variations sometimes show nature of convective structures. Here we present a new data analysis on z- autocorrelation functions to get some definite information on its nature. We find that there is usually a break point on the z- auto-correlation function when the fluctuations show nearly pure Alfvénicity. The break point observed by Helios-2 spacecraft near 0.3 AU is at the first time lag ( 81 s), where the autocorrelation coefficient has the value less than that at zero-time lag by a factor of more than 0.4. The autocorrelation function breaks also appear in the WIND observations near 1 AU. The z- autocorrelation function is separated by the break into two parts: fast decreasing part and slowly decreasing part, which cannot be described in a whole by an exponential formula. The breaks in the z- autocorrelation function may represent that the z- time series are composed of high-frequency white noise and low-frequency apparent structures, which correspond to the flat and steep parts of the function, respectively. This explanation is supported by a simple test with a superposition of an artificial random data series and a smoothed random data series. Since in many cases z- autocorrelation functions do not decrease very quickly at large time lag and cannot be considered as the Lanczos type, no reliable value for correlation-time can be derived. Our results showed that in these cases with high Alfvénicity, z- should not be considered as inward-propagating wave. The power-law spectrum of z+ should be made by fluid turbulence cascade process presented by Kolmogorov.

  3. Partial autocorrelation functions of the fractional ARIMA processes with negative degree of differencing

    OpenAIRE

    Inoue, Akihiko; Kasahara, Yukio

    2004-01-01

    Let {Xn : ∈Z} be a fractional ARIMA(p,d,q) process with partial autocorrelation function α(·). In this paper, we prove that if d∈(−1/2,0) then |α(n)|~|d|/n as n→∞. This extends the previous result for the case 0

  4. Noise-tolerant instantaneous heart rate and R-peak detection using short-term autocorrelation for wearable healthcare systems.

    Science.gov (United States)

    Fujii, Takahide; Nakano, Masanao; Yamashita, Ken; Konishi, Toshihiro; Izumi, Shintaro; Kawaguchi, Hiroshi; Yoshimoto, Masahiko

    2013-01-01

    This paper describes a robust method of Instantaneous Heart Rate (IHR) and R-peak detection from noisy electrocardiogram (ECG) signals. Generally, the IHR is calculated from the R-wave interval. Then, the R-waves are extracted from the ECG using a threshold. However, in wearable bio-signal monitoring systems, noise increases the incidence of misdetection and false detection of R-peaks. To prevent incorrect detection, we introduce a short-term autocorrelation (STAC) technique and a small-window autocorrelation (SWAC) technique, which leverages the similarity of QRS complex waveforms. Simulation results show that the proposed method improves the noise tolerance of R-peak detection.

  5. Stable Blind Deconvolution over the Reals from Additional Autocorrelations

    KAUST Repository

    Walk, Philipp

    2017-10-22

    Recently the one-dimensional time-discrete blind deconvolution problem was shown to be solvable uniquely, up to a global phase, by a semi-definite program for almost any signal, provided its autocorrelation is known. We will show in this work that under a sufficient zero separation of the corresponding signal in the $z-$domain, a stable reconstruction against additive noise is possible. Moreover, the stability constant depends on the signal dimension and on the signals magnitude of the first and last coefficients. We give an analytical expression for this constant by using spectral bounds of Vandermonde matrices.

  6. Geostatistical prediction of microbial water quality throughout a stream network using meteorology, land cover, and spatiotemporal autocorrelation.

    Science.gov (United States)

    Holcomb, David Andrew; Messier, Kyle P; Serre, Marc L; Rowny, Jakob G; Stewart, Jill R

    2018-06-11

    Predictive modeling is promising as an inexpensive tool to assess water quality. We developed geostatistical predictive models of microbial water quality that empirically modelled spatiotemporal autocorrelation in measured fecal coliform (FC) bacteria concentrations to improve prediction. We compared five geostatistical models featuring different autocorrelation structures, fit to 676 observations from 19 locations in North Carolina's Jordan Lake watershed using meteorological and land cover predictor variables. Though stream distance metrics (with and without flow-weighting) failed to improve prediction over the Euclidean distance metric, incorporating temporal autocorrelation substantially improved prediction over the space-only models. We predicted FC throughout the stream network daily for one year, designating locations "impaired", "unimpaired", or "unassessed" if the probability of exceeding the state standard was >90%, 10% but <90%, respectively. We could assign impairment status to more of the stream network on days any FC were measured, suggesting frequent sample-based monitoring remains necessary, though implementing spatiotemporal predictive models may reduce the number of concurrent sampling locations required to adequately assess water quality. Together, these results suggest that prioritizing sampling at different times and conditions using geographically sparse monitoring networks is adequate to build robust and informative geostatistical models of water quality impairment.

  7. A simulation-based approach to capturing auto-correlated demand parameter uncertainty in inventory management

    NARCIS (Netherlands)

    Akçay, A.E.; Biller, B.; Tayur, S.

    2012-01-01

    We consider a repeated newsvendor setting where the parameters of the demand distribution are unknown, and we study the problem of setting inventory targets using only a limited amount of historical demand data. We assume that the demand process is autocorrelated and represented by an

  8. Panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable

    NARCIS (Netherlands)

    Elhorst, J. Paul

    2001-01-01

    This paper surveys panel data models extended to spatial error autocorrelation or a spatially lagged dependent variable. In particular, it focuses on the specification and estimation of four panel data models commonly used in applied research: the fixed effects model, the random effects model, the

  9. Assessment of drug-induced arrhythmic risk using limit cycle and autocorrelation analysis of human iPSC-cardiomyocyte contractility

    Energy Technology Data Exchange (ETDEWEB)

    Kirby, R. Jason [Sanford Burnham Prebys Medical Discovery Institute, Conrad Prebys Center for Chemical Genomics, 6400 Sanger Rd, Orlando, FL 32827 (United States); Qi, Feng [Sanford Burnham Prebys Medical Discovery Institute, Applied Bioinformatics Facility, 6400 Sanger Rd, Orlando, FL 32827 (United States); Phatak, Sharangdhar; Smith, Layton H. [Sanford Burnham Prebys Medical Discovery Institute, Conrad Prebys Center for Chemical Genomics, 6400 Sanger Rd, Orlando, FL 32827 (United States); Malany, Siobhan, E-mail: smalany@sbpdiscovery.org [Sanford Burnham Prebys Medical Discovery Institute, Conrad Prebys Center for Chemical Genomics, 6400 Sanger Rd, Orlando, FL 32827 (United States)

    2016-08-15

    Cardiac safety assays incorporating label-free detection of human stem-cell derived cardiomyocyte contractility provide human relevance and medium throughput screening to assess compound-induced cardiotoxicity. In an effort to provide quantitative analysis of the large kinetic datasets resulting from these real-time studies, we applied bioinformatic approaches based on nonlinear dynamical system analysis, including limit cycle analysis and autocorrelation function, to systematically assess beat irregularity. The algorithms were integrated into a software program to seamlessly generate results for 96-well impedance-based data. Our approach was validated by analyzing dose- and time-dependent changes in beat patterns induced by known proarrhythmic compounds and screening a cardiotoxicity library to rank order compounds based on their proarrhythmic potential. We demonstrate a strong correlation for dose-dependent beat irregularity monitored by electrical impedance and quantified by autocorrelation analysis to traditional manual patch clamp potency values for hERG blockers. In addition, our platform identifies non-hERG blockers known to cause clinical arrhythmia. Our method provides a novel suite of medium-throughput quantitative tools for assessing compound effects on cardiac contractility and predicting compounds with potential proarrhythmia and may be applied to in vitro paradigms for pre-clinical cardiac safety evaluation. - Highlights: • Impedance-based monitoring of human iPSC-derived cardiomyocyte contractility • Limit cycle analysis of impedance data identifies aberrant oscillation patterns. • Nonlinear autocorrelation function quantifies beat irregularity. • Identification of hERG and non-hERG inhibitors with known risk of arrhythmia • Automated software processes limit cycle and autocorrelation analyses of 96w data.

  10. Assessment of drug-induced arrhythmic risk using limit cycle and autocorrelation analysis of human iPSC-cardiomyocyte contractility

    International Nuclear Information System (INIS)

    Kirby, R. Jason; Qi, Feng; Phatak, Sharangdhar; Smith, Layton H.; Malany, Siobhan

    2016-01-01

    Cardiac safety assays incorporating label-free detection of human stem-cell derived cardiomyocyte contractility provide human relevance and medium throughput screening to assess compound-induced cardiotoxicity. In an effort to provide quantitative analysis of the large kinetic datasets resulting from these real-time studies, we applied bioinformatic approaches based on nonlinear dynamical system analysis, including limit cycle analysis and autocorrelation function, to systematically assess beat irregularity. The algorithms were integrated into a software program to seamlessly generate results for 96-well impedance-based data. Our approach was validated by analyzing dose- and time-dependent changes in beat patterns induced by known proarrhythmic compounds and screening a cardiotoxicity library to rank order compounds based on their proarrhythmic potential. We demonstrate a strong correlation for dose-dependent beat irregularity monitored by electrical impedance and quantified by autocorrelation analysis to traditional manual patch clamp potency values for hERG blockers. In addition, our platform identifies non-hERG blockers known to cause clinical arrhythmia. Our method provides a novel suite of medium-throughput quantitative tools for assessing compound effects on cardiac contractility and predicting compounds with potential proarrhythmia and may be applied to in vitro paradigms for pre-clinical cardiac safety evaluation. - Highlights: • Impedance-based monitoring of human iPSC-derived cardiomyocyte contractility • Limit cycle analysis of impedance data identifies aberrant oscillation patterns. • Nonlinear autocorrelation function quantifies beat irregularity. • Identification of hERG and non-hERG inhibitors with known risk of arrhythmia • Automated software processes limit cycle and autocorrelation analyses of 96w data

  11. An improved triple collocation algorithm for decomposing autocorrelated and white soil moisture retrieval errors

    Science.gov (United States)

    If not properly account for, auto-correlated errors in observations can lead to inaccurate results in soil moisture data analysis and reanalysis. Here, we propose a more generalized form of the triple collocation algorithm (GTC) capable of decomposing the total error variance of remotely-sensed surf...

  12. Determination of the friction coefficient via the force autocorrelation function. A molecular dynamics investigation for a dense Lennard-Jones fluid

    International Nuclear Information System (INIS)

    Vogelsang, R.; Hoheisel, C.

    1987-01-01

    For a large region of dense fluid states of a Lennard-Jones system, they have calculated the friction coefficient by the force autocorrelation function of a Brownian-type particle by molecular dynamics (MD). The time integral over the force autocorrelation function showed an interesting behavior and the expected plateau value when the mass of the Brownian particle was chosen to be about a factor of 100 larger than the mass of the fluid particle. Sufficient agreement was found for the friction coefficient calculated by this way and that obtained by calculations of the self-diffusion coefficient using the common relation between these coefficients. Furthermore, a modified friction coefficient was determined by integration of the force autocorrelation function up to the first maximum. This coefficient can successfully be used to derive a reasonable soft part of the friction coefficient necessary for the Rice-Allnatt approximation for the shear velocity and simple liquids

  13. An asymptotic theory for cross-correlation between auto-correlated sequences and its application on neuroimaging data.

    Science.gov (United States)

    Zhou, Yunyi; Tao, Chenyang; Lu, Wenlian; Feng, Jianfeng

    2018-04-20

    Functional connectivity is among the most important tools to study brain. The correlation coefficient, between time series of different brain areas, is the most popular method to quantify functional connectivity. Correlation coefficient in practical use assumes the data to be temporally independent. However, the time series data of brain can manifest significant temporal auto-correlation. A widely applicable method is proposed for correcting temporal auto-correlation. We considered two types of time series models: (1) auto-regressive-moving-average model, (2) nonlinear dynamical system model with noisy fluctuations, and derived their respective asymptotic distributions of correlation coefficient. These two types of models are most commonly used in neuroscience studies. We show the respective asymptotic distributions share a unified expression. We have verified the validity of our method, and shown our method exhibited sufficient statistical power for detecting true correlation on numerical experiments. Employing our method on real dataset yields more robust functional network and higher classification accuracy than conventional methods. Our method robustly controls the type I error while maintaining sufficient statistical power for detecting true correlation in numerical experiments, where existing methods measuring association (linear and nonlinear) fail. In this work, we proposed a widely applicable approach for correcting the effect of temporal auto-correlation on functional connectivity. Empirical results favor the use of our method in functional network analysis. Copyright © 2018. Published by Elsevier B.V.

  14. Multilevel models for multiple-baseline data: modeling across-participant variation in autocorrelation and residual variance.

    Science.gov (United States)

    Baek, Eun Kyeng; Ferron, John M

    2013-03-01

    Multilevel models (MLM) have been used as a method for analyzing multiple-baseline single-case data. However, some concerns can be raised because the models that have been used assume that the Level-1 error covariance matrix is the same for all participants. The purpose of this study was to extend the application of MLM of single-case data in order to accommodate across-participant variation in the Level-1 residual variance and autocorrelation. This more general model was then used in the analysis of single-case data sets to illustrate the method, to estimate the degree to which the autocorrelation and residual variances differed across participants, and to examine whether inferences about treatment effects were sensitive to whether or not the Level-1 error covariance matrix was allowed to vary across participants. The results from the analyses of five published studies showed that when the Level-1 error covariance matrix was allowed to vary across participants, some relatively large differences in autocorrelation estimates and error variance estimates emerged. The changes in modeling the variance structure did not change the conclusions about which fixed effects were statistically significant in most of the studies, but there was one exception. The fit indices did not consistently support selecting either the more complex covariance structure, which allowed the covariance parameters to vary across participants, or the simpler covariance structure. Given the uncertainty in model specification that may arise when modeling single-case data, researchers should consider conducting sensitivity analyses to examine the degree to which their conclusions are sensitive to modeling choices.

  15. Limit theory for the sample autocorrelations and extremes of a GARCH (1,1) process

    NARCIS (Netherlands)

    Mikosch, T; Starica, C

    2000-01-01

    The asymptotic theory for the sample autocorrelations and extremes of a GARCH(I, 1) process is provided. Special attention is given to the case when the sum of the ARCH and GARCH parameters is close to 1, that is, when one is close to an infinite Variance marginal distribution. This situation has

  16. Broadband short pulse measurement by autocorrelation with a sum-frequency generation set-up

    International Nuclear Information System (INIS)

    Glotin, F.; Jaroszynski, D.; Marcouille, O.

    1995-01-01

    Previous spectral and laser pulse length measurements carried out on the CLIO FEL at wavelength λ=8.5 μm suggested that very short light pulses could be generated, about 500 fs wide (FWHM). For these measurements a Michelson interferometer with a Te crystal, as a non-linear detector, was used as a second order autocorrelation device. More recent measurements in similar conditions have confirmed that the laser pulses observed are indeed single: they are not followed by other pulses distant by the slippage length Nλ. As the single micropulse length is likely to depend on the slippage, more measurements at different wavelengths would be useful. This is not directly possible with our actual interferometer set-up, based on a phase-matched non-linear crystal. However, we can use the broadband non-linear medium provided by one of our users' experiments: Sum-Frequency Generation over surfaces. With such autocorrelation set-up, interference fringes are no more visible, but this is largely compensated by the frequency range provided. First tests at 8 μm have already been performed to validate the technic, leading to results similar to those obtained with our previous Michelson set-up

  17. Hotspot detection using image pattern recognition based on higher-order local auto-correlation

    Science.gov (United States)

    Maeda, Shimon; Matsunawa, Tetsuaki; Ogawa, Ryuji; Ichikawa, Hirotaka; Takahata, Kazuhiro; Miyairi, Masahiro; Kotani, Toshiya; Nojima, Shigeki; Tanaka, Satoshi; Nakagawa, Kei; Saito, Tamaki; Mimotogi, Shoji; Inoue, Soichi; Nosato, Hirokazu; Sakanashi, Hidenori; Kobayashi, Takumi; Murakawa, Masahiro; Higuchi, Tetsuya; Takahashi, Eiichi; Otsu, Nobuyuki

    2011-04-01

    Below 40nm design node, systematic variation due to lithography must be taken into consideration during the early stage of design. So far, litho-aware design using lithography simulation models has been widely applied to assure that designs are printed on silicon without any error. However, the lithography simulation approach is very time consuming, and under time-to-market pressure, repetitive redesign by this approach may result in the missing of the market window. This paper proposes a fast hotspot detection support method by flexible and intelligent vision system image pattern recognition based on Higher-Order Local Autocorrelation. Our method learns the geometrical properties of the given design data without any defects as normal patterns, and automatically detects the design patterns with hotspots from the test data as abnormal patterns. The Higher-Order Local Autocorrelation method can extract features from the graphic image of design pattern, and computational cost of the extraction is constant regardless of the number of design pattern polygons. This approach can reduce turnaround time (TAT) dramatically only on 1CPU, compared with the conventional simulation-based approach, and by distributed processing, this has proven to deliver linear scalability with each additional CPU.

  18. Effect of nonlinear crystal thickness on the parameters of the autocorrelator of femtosecond light pulses

    International Nuclear Information System (INIS)

    Masalov, Anatolii V; Chudnovsky, Aleksandr V

    2004-01-01

    It is shown that the finite thickness of the second-harmonic crystal distorts the results of measurements in nonlinear autocorrelators intended for measuring the durations and fields of femtosecond light pulses mainly due to dispersive broadening (or compression) of the pulses being measured, as well as due to the group velocity mismatch between the fundamental and sum-frequency pulses. The refractive index dispersion of the crystal, scaled by half its thickness, distorts the pulse duration to a certain extent depending on its initial chirp and thus determines the width of the energy distribution recorded in the autocorrelator. As the crystal thickness increases, the group velocity mismatch leads to a transformation of the recorded distribution from the correlation function of intensity to the squared modulus of the field correlation function. In the case of Gaussian pulses, such a transformation does not affect significantly the recorded distribution. Errors of pulse duration measurements are estimated. (nonlinear optical phenomena)

  19. Disease Mapping and Regression with Count Data in the Presence of Overdispersion and Spatial Autocorrelation: A Bayesian Model Averaging Approach

    Science.gov (United States)

    Mohebbi, Mohammadreza; Wolfe, Rory; Forbes, Andrew

    2014-01-01

    This paper applies the generalised linear model for modelling geographical variation to esophageal cancer incidence data in the Caspian region of Iran. The data have a complex and hierarchical structure that makes them suitable for hierarchical analysis using Bayesian techniques, but with care required to deal with problems arising from counts of events observed in small geographical areas when overdispersion and residual spatial autocorrelation are present. These considerations lead to nine regression models derived from using three probability distributions for count data: Poisson, generalised Poisson and negative binomial, and three different autocorrelation structures. We employ the framework of Bayesian variable selection and a Gibbs sampling based technique to identify significant cancer risk factors. The framework deals with situations where the number of possible models based on different combinations of candidate explanatory variables is large enough such that calculation of posterior probabilities for all models is difficult or infeasible. The evidence from applying the modelling methodology suggests that modelling strategies based on the use of generalised Poisson and negative binomial with spatial autocorrelation work well and provide a robust basis for inference. PMID:24413702

  20. Spectral velocity estimation using autocorrelation functions for sparse data sets

    DEFF Research Database (Denmark)

    2006-01-01

    The distribution of velocities of blood or tissue is displayed using ultrasound scanners by finding the power spectrum of the received signal. This is currently done by making a Fourier transform of the received signal and then showing spectra in an M-mode display. It is desired to show a B......-mode image for orientation, and data for this has to acquired interleaved with the flow data. The power spectrum can be calculated from the Fourier transform of the autocorrelation function Ry (k), where its span of lags k is given by the number of emission N in the data segment for velocity estimation...

  1. Microfluidic volumetric flow determination using optical coherence tomography speckle: An autocorrelation approach

    Energy Technology Data Exchange (ETDEWEB)

    De Pretto, Lucas R., E-mail: lucas.de.pretto@usp.br; Nogueira, Gesse E. C.; Freitas, Anderson Z. [Instituto de Pesquisas Energéticas e Nucleares, IPEN–CNEN/SP, Avenida Lineu Prestes, 2242, 05508-000 São Paulo (Brazil)

    2016-04-28

    Functional modalities of Optical Coherence Tomography (OCT) based on speckle analysis are emerging in the literature. We propose a simple approach to the autocorrelation of OCT signal to enable volumetric flow rate differentiation, based on decorrelation time. Our results show that this technique could distinguish flows separated by 3 μl/min, limited by the acquisition speed of the system. We further perform a B-scan of gradient flow inside a microchannel, enabling the visualization of the drag effect on the walls.

  2. Determination of modulation transfer function of a printer by measuring the autocorrelation of the transmission function of a printed Ronchi grating

    International Nuclear Information System (INIS)

    Madanipour, Khosro; Tavassoly, Mohammad T.

    2009-01-01

    We show theoretically and verify experimentally that the modulation transfer function (MTF) of a printing system can be determined by measuring the autocorrelation of a printed Ronchi grating. In practice, two similar Ronchi gratings are printed on two transparencies and the transparencies are superimposed with parallel grating lines. Then, the gratings are uniformly illuminated and the transmitted light from a large section is measured versus the displacement of one grating with respect to the other in a grating pitch interval. This measurement provides the required autocorrelation function for determination of the MTF

  3. Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage.

    Directory of Open Access Journals (Sweden)

    Brady J Mattsson

    Full Text Available Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

  4. An autocorrelation method to detect low frequency earthquakes within tremor

    Science.gov (United States)

    Brown, J.R.; Beroza, G.C.; Shelly, D.R.

    2008-01-01

    Recent studies have shown that deep tremor in the Nankai Trough under western Shikoku consists of a swarm of low frequency earthquakes (LFEs) that occur as slow shear slip on the down-dip extension of the primary seismogenic zone of the plate interface. The similarity of tremor in other locations suggests a similar mechanism, but the absence of cataloged low frequency earthquakes prevents a similar analysis. In this study, we develop a method for identifying LFEs within tremor. The method employs a matched-filter algorithm, similar to the technique used to infer that tremor in parts of Shikoku is comprised of LFEs; however, in this case we do not assume the origin times or locations of any LFEs a priori. We search for LFEs using the running autocorrelation of tremor waveforms for 6 Hi-Net stations in the vicinity of the tremor source. Time lags showing strong similarity in the autocorrelation represent either repeats, or near repeats, of LFEs within the tremor. We test the method on an hour of Hi-Net recordings of tremor and demonstrates that it extracts both known and previously unidentified LFEs. Once identified, we cross correlate waveforms to measure relative arrival times and locate the LFEs. The results are able to explain most of the tremor as a swarm of LFEs and the locations of newly identified events appear to fill a gap in the spatial distribution of known LFEs. This method should allow us to extend the analysis of Shelly et al. (2007a) to parts of the Nankai Trough in Shikoku that have sparse LFE coverage, and may also allow us to extend our analysis to other regions that experience deep tremor, but where LFEs have not yet been identified. Copyright 2008 by the American Geophysical Union.

  5. On the Decay Ratio Determination in BWR Stability Analysis by Auto-Correlation Function Techniques

    International Nuclear Information System (INIS)

    Behringer, K.; Hennig, D.

    2002-11-01

    A novel auto-correlation function (ACF) method has been investigated for determining the oscillation frequency and the decay ratio in BWR stability analyses. The neutron signals are band-pass filtered to separate the oscillation peak in the power spectral density (PSD) from background. Two linear second-order oscillation models are considered. These models, corrected for signal filtering and including a background term under the peak in the PSD, are then least-squares fitted to the ACF of the previously filtered neutron signal, in order to determine the oscillation frequency and the decay ratio. Our method uses fast Fourier transform techniques with signal segmentation for filtering and ACF estimation. Gliding 'short-term' ACF estimates on a record allow the evaluation of uncertainties. Numerical results are given which have been obtained from neutron data of the recent Forsmark I and Forsmark II NEA benchmark project. Our results are compared with those obtained by other participants in the benchmark project. The present PSI report is an extended version of the publication K. Behringer, D. Hennig 'A novel auto-correlation function method for the determination of the decay ratio in BWR stability studies' (Behringer, Hennig, 2002)

  6. Wave packet autocorrelation functions for quantum hard-disk and hard-sphere billiards in the high-energy, diffraction regime.

    Science.gov (United States)

    Goussev, Arseni; Dorfman, J R

    2006-07-01

    We consider the time evolution of a wave packet representing a quantum particle moving in a geometrically open billiard that consists of a number of fixed hard-disk or hard-sphere scatterers. Using the technique of multiple collision expansions we provide a first-principle analytical calculation of the time-dependent autocorrelation function for the wave packet in the high-energy diffraction regime, in which the particle's de Broglie wavelength, while being small compared to the size of the scatterers, is large enough to prevent the formation of geometric shadow over distances of the order of the particle's free flight path. The hard-disk or hard-sphere scattering system must be sufficiently dilute in order for this high-energy diffraction regime to be achievable. Apart from the overall exponential decay, the autocorrelation function exhibits a generally complicated sequence of relatively strong peaks corresponding to partial revivals of the wave packet. Both the exponential decay (or escape) rate and the revival peak structure are predominantly determined by the underlying classical dynamics. A relation between the escape rate, and the Lyapunov exponents and Kolmogorov-Sinai entropy of the counterpart classical system, previously known for hard-disk billiards, is strengthened by generalization to three spatial dimensions. The results of the quantum mechanical calculation of the time-dependent autocorrelation function agree with predictions of the semiclassical periodic orbit theory.

  7. Periodicity in the autocorrelation function as a mechanism for regularly occurring zero crossings or extreme values of a Gaussian process.

    Science.gov (United States)

    Wilson, Lorna R M; Hopcraft, Keith I

    2017-12-01

    The problem of zero crossings is of great historical prevalence and promises extensive application. The challenge is to establish precisely how the autocorrelation function or power spectrum of a one-dimensional continuous random process determines the density function of the intervals between the zero crossings of that process. This paper investigates the case where periodicities are incorporated into the autocorrelation function of a smooth process. Numerical simulations, and statistics about the number of crossings in a fixed interval, reveal that in this case the zero crossings segue between a random and deterministic point process depending on the relative time scales of the periodic and nonperiodic components of the autocorrelation function. By considering the Laplace transform of the density function, we show that incorporating correlation between successive intervals is essential to obtaining accurate results for the interval variance. The same method enables prediction of the density function tail in some regions, and we suggest approaches for extending this to cover all regions. In an ever-more complex world, the potential applications for this scale of regularity in a random process are far reaching and powerful.

  8. Can spatial autocorrelation method be applied to arbitrary array shape; Kukan jiko sokanho no nin`i array eno tekiyo kanosei

    Energy Technology Data Exchange (ETDEWEB)

    Yamamoto, H; Iwamoto, K; Saito, T; Tachibana, M [Iwate University, Iwate (Japan). Faculty of Engineering

    1997-05-27

    Methods to learn underground structures by utilizing the dispersion phenomenon of surface waves contained in microtremors include the frequency-wave number analysis method (the F-K method) and the spatial autocorrelation method (the SAC method). Despite the fact that the SAC method is capable of exploring structures at greater depths, the method is not utilized because of its stringent restriction in arrangement of seismometers during observation that they must be arranged evenly on the same circumference. In order to eliminate this restriction in the SAC method, a research group in the Hokuriku University has proposed an expanded spatial autocorrelation (ESAC) method. Using the concept of the ESAC method as its base, a method was realized to improve phase velocity estimation by making a simulation on an array shifted to the radius direction. As a result of the discussion, it was found that the proposed improvement method can be applied to places where waves come from a number of directions, such as urban areas. If the improvement method can be applied, the spatial autocorrelation function needs not be even in the circumferential direction. In other words, the SAC method can be applied to arbitrary arrays. 1 ref., 7 figs.

  9. Periodicity in the autocorrelation function as a mechanism for regularly occurring zero crossings or extreme values of a Gaussian process

    Science.gov (United States)

    Wilson, Lorna R. M.; Hopcraft, Keith I.

    2017-12-01

    The problem of zero crossings is of great historical prevalence and promises extensive application. The challenge is to establish precisely how the autocorrelation function or power spectrum of a one-dimensional continuous random process determines the density function of the intervals between the zero crossings of that process. This paper investigates the case where periodicities are incorporated into the autocorrelation function of a smooth process. Numerical simulations, and statistics about the number of crossings in a fixed interval, reveal that in this case the zero crossings segue between a random and deterministic point process depending on the relative time scales of the periodic and nonperiodic components of the autocorrelation function. By considering the Laplace transform of the density function, we show that incorporating correlation between successive intervals is essential to obtaining accurate results for the interval variance. The same method enables prediction of the density function tail in some regions, and we suggest approaches for extending this to cover all regions. In an ever-more complex world, the potential applications for this scale of regularity in a random process are far reaching and powerful.

  10. Evaluating the coefficients of autocorrelation in a series of annual run-off of the Far East rivers

    Energy Technology Data Exchange (ETDEWEB)

    Sakharyuk, A V

    1981-01-01

    An evaluation is made of the coefficients of autocorrelation in series of annual river run-off based on group analysis using data on the distribution law of sampling correlation coefficients of temporal series subordinate to the III type Pearson's distribution.

  11. A single-shot nonlinear autocorrelation approach for time-resolved physics in the vacuum ultraviolet spectral range

    International Nuclear Information System (INIS)

    Rompotis, Dimitrios

    2016-02-01

    In this work, a single-shot temporal metrology scheme operating in the vacuum-extreme ultraviolet spectral range has been designed and experimentally implemented. Utilizing an anti-collinear geometry, a second-order intensity autocorrelation measurement of a vacuum ultraviolet pulse can be performed by encoding temporal delay information on the beam propagation coordinate. An ion-imaging time-of-flight spectrometer, offering micrometer resolution has been set-up for this purpose. This instrument enables the detection of a magnified image of the spatial distribution of ions exclusively generated by direct two-photon absorption in the combined counter-propagating pulse focus and thus obtain the second-order intensity autocorrelation measurement on a single-shot basis. Additionally, an intense VUV light source based on high-harmonic generation has been experimentally realized. It delivers intense sub-20 fs Ti:Sa fifth-harmonic pulses utilizing a loose-focusing geometry in a long Ar gas cell. The VUV pulses centered at 161.8 nm reach pulse energies of 1.1 μJ per pulse, while the corresponding pulse duration is measured with a second-order, fringe-resolved autocorrelation scheme to be 18 ± 1 fs on average. Non-resonant, two-photon ionization of Kr and Xe and three-photon ionization of Ne verify the fifth-harmonic pulse intensity and indicate the feasibility of multi-photon VUV pump/VUV probe studies of ultrafast atomic and molecular dynamics. Finally, the extended functionally of the counter-propagating pulse metrology approach is demonstrated by a single-shot VUV pump/VUV probe experiment aiming at the investigation of ultrafast dissociation dynamics of O 2 excited in the Schumann-Runge continuum at 162 nm.

  12. Transforming the autocorrelation function of a time series to detect land cover change

    CSIR Research Space (South Africa)

    Salmon

    2015-07-01

    Full Text Available stream_source_info Salmon_2016.pdf.txt stream_content_type text/plain stream_size 1090 Content-Encoding ISO-8859-1 stream_name Salmon_2016.pdf.txt Content-Type text/plain; charset=ISO-8859-1 International Geoscience... and Remote Sensing Symposium (IEEE IGARSS), 10-15 July 2016, Beijing Transforming the autocorrelation function of a time series to detect land cover change Salmon, B.P., Kleynhans, W., Olivier, J.C. and Schwegmann, C.P. ABSTRACT Regional...

  13. Autocorrelation analysis of plasma plume light emissions in deep penetration laser welding of steel

    Czech Academy of Sciences Publication Activity Database

    Mrňa, Libor; Šarbort, Martin; Řeřucha, Šimon; Jedlička, Petr

    2017-01-01

    Roč. 29, č. 1 (2017), s. 1-10, č. článku 012009. ISSN 1042-346X R&D Projects: GA MŠk(CZ) LO1212; GA MŠk ED0017/01/01 Institutional support: RVO:68081731 Keywords : laser welding * plasma plume * light emissions * autocorrelation analysis * weld depth Subject RIV: BH - Optics, Masers, Lasers OBOR OECD: Optics (including laser optics and quantum optics) Impact factor: 1.492, year: 2016

  14. New autocorrelation technique for the IR FEL optical pulse width measurements

    Energy Technology Data Exchange (ETDEWEB)

    Amirmadhi, F.; Brau, K.A.; Becker, C. [Vanderbilt Univ., Nashville, TN (United States)] [and others

    1995-12-31

    We have developed a new technique for the autocorrelation measurement of optical pulse width at the Vanderbilt University FEL center. This method is based on nonlinear absorption and transmission characteristics of semiconductors such as Ge, Te and InAs suitable for the wavelength range from 2 to over 6 microns. This approach, aside being simple and low cost, removes the phase matching condition that is generally required for the standard frequency doubling technique and covers a greater wavelength range per nonlinear material. In this paper we will describe the apparatus, explain the principal mechanism involved and compare data which have been acquired with both frequency doubling and two-photon absorption.

  15. A Novel Acoustic Liquid Level Determination Method for Coal Seam Gas Wells Based on Autocorrelation Analysis

    Directory of Open Access Journals (Sweden)

    Ximing Zhang

    2017-11-01

    Full Text Available In coal seam gas (CSG wells, water is periodically removed from the wellbore in order to keep the bottom-hole flowing pressure at low levels, facilitating the desorption of methane gas from the coal bed. In order to calculate gas flow rate and further optimize well performance, it is necessary to accurately monitor the liquid level in real-time. This paper presents a novel method based on autocorrelation function (ACF analysis for determining the liquid level in CSG wells under intense noise conditions. The method involves the calculation of the acoustic travel time in the annulus and processing the autocorrelation signal in order to extract the weak echo under high background noise. In contrast to previous works, the non-linear dependence of the acoustic velocity on temperature and pressure is taken into account. To locate the liquid level of a coal seam gas well the travel time is computed iteratively with the non-linear velocity model. Afterwards, the proposed method is validated using experimental laboratory investigations that have been developed for liquid level detection under two scenarios, representing the combination of low pressure, weak signal, and intense noise generated by gas flowing and leakage. By adopting an evaluation indicator called Crest Factor, the results have shown the superiority of the ACF-based method compared to Fourier filtering (FFT. In the two scenarios, the maximal measurement error from the proposed method was 0.34% and 0.50%, respectively. The latent periodic characteristic of the reflected signal can be extracted by the ACF-based method even when the noise is larger than 1.42 Pa, which is impossible for FFT-based de-noising. A case study focused on a specific CSG well is presented to illustrate the feasibility of the proposed approach, and also to demonstrate that signal processing with autocorrelation analysis can improve the sensitivity of the detection system.

  16. Building a three-dimensional model of CYP2C9 inhibition using the Autocorrelator: an autonomous model generator.

    Science.gov (United States)

    Lardy, Matthew A; Lebrun, Laurie; Bullard, Drew; Kissinger, Charles; Gobbi, Alberto

    2012-05-25

    In modern day drug discovery campaigns, computational chemists have to be concerned not only about improving the potency of molecules but also reducing any off-target ADMET activity. There are a plethora of antitargets that computational chemists may have to consider. Fortunately many antitargets have crystal structures deposited in the PDB. These structures are immediately useful to our Autocorrelator: an automated model generator that optimizes variables for building computational models. This paper describes the use of the Autocorrelator to construct high quality docking models for cytochrome P450 2C9 (CYP2C9) from two publicly available crystal structures. Both models result in strong correlation coefficients (R² > 0.66) between the predicted and experimental determined log(IC₅₀) values. Results from the two models overlap well with each other, converging on the same scoring function, deprotonated charge state, and predicted the binding orientation for our collection of molecules.

  17. LETTER TO THE EDITOR: Exhaustive search for low-autocorrelation binary sequences

    Science.gov (United States)

    Mertens, S.

    1996-09-01

    Binary sequences with low autocorrelations are important in communication engineering and in statistical mechanics as ground states of the Bernasconi model. Computer searches are the main tool in the construction of such sequences. Owing to the exponential size 0305-4470/29/18/005/img1 of the configuration space, exhaustive searches are limited to short sequences. We discuss an exhaustive search algorithm with run-time characteristic 0305-4470/29/18/005/img2 and apply it to compile a table of exact ground states of the Bernasconi model up to N = 48. The data suggest F > 9 for the optimal merit factor in the limit 0305-4470/29/18/005/img3.

  18. Real-time autocorrelator for fluorescence correlation spectroscopy based on graphical-processor-unit architecture: method, implementation, and comparative studies

    Science.gov (United States)

    Laracuente, Nicholas; Grossman, Carl

    2013-03-01

    We developed an algorithm and software to calculate autocorrelation functions from real-time photon-counting data using the fast, parallel capabilities of graphical processor units (GPUs). Recent developments in hardware and software have allowed for general purpose computing with inexpensive GPU hardware. These devices are more suited for emulating hardware autocorrelators than traditional CPU-based software applications by emphasizing parallel throughput over sequential speed. Incoming data are binned in a standard multi-tau scheme with configurable points-per-bin size and are mapped into a GPU memory pattern to reduce time-expensive memory access. Applications include dynamic light scattering (DLS) and fluorescence correlation spectroscopy (FCS) experiments. We ran the software on a 64-core graphics pci card in a 3.2 GHz Intel i5 CPU based computer running Linux. FCS measurements were made on Alexa-546 and Texas Red dyes in a standard buffer (PBS). Software correlations were compared to hardware correlator measurements on the same signals. Supported by HHMI and Swarthmore College

  19. Artificial fingerprint recognition by using optical coherence tomography with autocorrelation analysis

    Science.gov (United States)

    Cheng, Yezeng; Larin, Kirill V.

    2006-12-01

    Fingerprint recognition is one of the most widely used methods of biometrics. This method relies on the surface topography of a finger and, thus, is potentially vulnerable for spoofing by artificial dummies with embedded fingerprints. In this study, we applied the optical coherence tomography (OCT) technique to distinguish artificial materials commonly used for spoofing fingerprint scanning systems from the real skin. Several artificial fingerprint dummies made from household cement and liquid silicone rubber were prepared and tested using a commercial fingerprint reader and an OCT system. While the artificial fingerprints easily spoofed the commercial fingerprint reader, OCT images revealed the presence of them at all times. We also demonstrated that an autocorrelation analysis of the OCT images could be potentially used in automatic recognition systems.

  20. Disentangling the effects of forage, social rank, and risk on movement autocorrelation of elephants using Fourier and wavelet analyses.

    Science.gov (United States)

    Wittemyer, George; Polansky, Leo; Douglas-Hamilton, Iain; Getz, Wayne M

    2008-12-09

    The internal state of an individual-as it relates to thirst, hunger, fear, or reproductive drive-can be inferred by referencing points on its movement path to external environmental and sociological variables. Using time-series approaches to characterize autocorrelative properties of step-length movements collated every 3 h for seven free-ranging African elephants, we examined the influence of social rank, predation risk, and seasonal variation in resource abundance on periodic properties of movement. The frequency domain methods of Fourier and wavelet analyses provide compact summaries of temporal autocorrelation and show both strong diurnal and seasonal based periodicities in the step-length time series. This autocorrelation is weaker during the wet season, indicating random movements are more common when ecological conditions are good. Periodograms of socially dominant individuals are consistent across seasons, whereas subordinate individuals show distinct differences diverging from that of dominants during the dry season. We link temporally localized statistical properties of movement to landscape features and find that diurnal movement correlation is more common within protected wildlife areas, and multiday movement correlations found among lower ranked individuals are typically outside of protected areas where predation risks are greatest. A frequency-related spatial analysis of movement-step lengths reveal that rest cycles related to the spatial distribution of critical resources (i.e., forage and water) are responsible for creating the observed patterns. Our approach generates unique information regarding the spatial-temporal interplay between environmental and individual characteristics, providing an original approach for understanding the movement ecology of individual animals and the spatial organization of animal populations.

  1. Velocity auto-correlation and hot-electron diffusion constant in GaAs and InP

    International Nuclear Information System (INIS)

    Deb Roy, M.

    1982-01-01

    Auto-correlation functions of the fluctuations in the electron velocities transverse and parallel to the applied electric field are calculated by the Monte Carlo method for GaAs and InP at three different values of field strength which are around three times the threshold field for negative differential mobility in each case. From these the frequency-dependent diffusion coefficients transverse and parallel to the applied field and the figure of merit for noise performance when used in a microwave amplifying device are determined. The results indicate that the transverse auto-correlation function Csub(t)(s) falls nearly exponentially to zero with increasing interval s while the parallel function Csub(p)(s) falls sharply, attains a minimum and then rises towards zero. In each case a higher field gives a higher rate of fall and makes the correlation functions zero within a shorter interval. The transverses diffusion coefficient falls monotonically with the frequency but the parallel diffusion coefficient generally starts with a low value at low frequencies, rises to a maximum and then falls. InP, with a larger separation between the central and the satellite valleys, has a higher value of the low frequency transverse diffusion coefficient and a lower value of its parallel counterpart. The noise performance of microwave semiconductor amplifying devices depends mainly on the low frequency parallel diffusion constant and consequently devices made out of materials like InP with a large separation between valleys are likely to have better noise characteristics. (orig.)

  2. A Comparison of Various Forecasting Methods for Autocorrelated Time Series

    Directory of Open Access Journals (Sweden)

    Karin Kandananond

    2012-07-01

    Full Text Available The accuracy of forecasts significantly affects the overall performance of a whole supply chain system. Sometimes, the nature of consumer products might cause difficulties in forecasting for the future demands because of its complicated structure. In this study, two machine learning methods, artificial neural network (ANN and support vector machine (SVM, and a traditional approach, the autoregressive integrated moving average (ARIMA model, were utilized to predict the demand for consumer products. The training data used were the actual demand of six different products from a consumer product company in Thailand. Initially, each set of data was analysed using Ljung‐Box‐Q statistics to test for autocorrelation. Afterwards, each method was applied to different sets of data. The results indicated that the SVM method had a better forecast quality (in terms of MAPE than ANN and ARIMA in every category of products.

  3. Intensity autocorrelation measurements of frequency combs in the terahertz range

    Science.gov (United States)

    Benea-Chelmus, Ileana-Cristina; Rösch, Markus; Scalari, Giacomo; Beck, Mattias; Faist, Jérôme

    2017-09-01

    We report on direct measurements of the emission character of quantum cascade laser based frequency combs, using intensity autocorrelation. Our implementation is based on fast electro-optic sampling, with a detection spectral bandwidth matching the emission bandwidth of the comb laser, around 2.5 THz. We find the output of these frequency combs to be continuous even in the locked regime, but accompanied by a strong intensity modulation. Moreover, with our record temporal resolution of only few hundreds of femtoseconds, we can resolve correlated intensity modulation occurring on time scales as short as the gain recovery time, about 4 ps. By direct comparison with pulsed terahertz light originating from a photoconductive emitter, we demonstrate the peculiar emission pattern of these lasers. The measurement technique is self-referenced and ultrafast, and requires no reconstruction. It will be of significant importance in future measurements of ultrashort pulses from quantum cascade lasers.

  4. Influence of the nuclear autocorrelation function on the positron production in heavy-ion collisions

    International Nuclear Information System (INIS)

    Tomoda, T.; Weidenmueller, H.A.

    1983-01-01

    The influence of a nuclear reaction on atomic positron production in heavy-ion collisions is investigated. Using statistical concepts, we describe the nuclear S matrix for a heavy-ion induced reaction as a statistically fluctuating function of energy. The positron production rate is then dependent on the autocorrelation function of this S matrix, and on the ratio of the ''direct'' versus the ''fluctuating'' part of the nuclear cross section. Numerical calculations show that in this way, current experimental results on positron production in heavy-ion collisions can be reproduced in a semiquantitative fashion

  5. A comparison of two least-squared random coefficient autoregressive models: with and without autocorrelated errors

    OpenAIRE

    Autcha Araveeporn

    2013-01-01

    This paper compares a Least-Squared Random Coefficient Autoregressive (RCA) model with a Least-Squared RCA model based on Autocorrelated Errors (RCA-AR). We looked at only the first order models, denoted RCA(1) and RCA(1)-AR(1). The efficiency of the Least-Squared method was checked by applying the models to Brownian motion and Wiener process, and the efficiency followed closely the asymptotic properties of a normal distribution. In a simulation study, we compared the performance of RCA(1) an...

  6. Sign reversals of the output autocorrelation function for the stochastic Bernoulli-Verhulst equation

    Energy Technology Data Exchange (ETDEWEB)

    Lumi, N., E-mail: Neeme.Lumi@tlu.ee; Mankin, R., E-mail: Romi.Mankin@tlu.ee [Institute of Mathematics and Natural Sciences, Tallinn University, 29 Narva Road, 10120 Tallinn (Estonia)

    2015-10-28

    We consider a stochastic Bernoulli-Verhulst equation as a model for population growth processes. The effect of fluctuating environment on the carrying capacity of a population is modeled as colored dichotomous noise. Relying on the composite master equation an explicit expression for the stationary autocorrelation function (ACF) of population sizes is found. On the basis of this expression a nonmonotonic decay of the ACF by increasing lag-time is shown. Moreover, in a certain regime of the noise parameters the ACF demonstrates anticorrelation as well as related sign reversals at some values of the lag-time. The conditions for the appearance of this highly unexpected effect are also discussed.

  7. Nodule detection methods using autocorrelation features on 3D chest CT scans

    International Nuclear Information System (INIS)

    Hara, T.; Zhou, X.; Okura, S.; Fujita, H.; Kiryu, T.; Hoshi, H.

    2007-01-01

    Lung cancer screening using low dose X-ray CT scan has been an acceptable examination to detect cancers at early stage. We have been developing an automated detection scheme for lung nodules on CT scan by using second-order autocorrelation features and the initial performance for small nodules (< 10 mm) shows a high true-positive rate with less than four false-positive marks per case. In this study, an open database of lung images, LIDC (Lung Image Database Consortium), was employed to evaluate our detection scheme as an consistency test. The detection performance for solid and solitary nodules in LIDC, included in the first data set opened by the consortium, was 83% (10/12) true-positive rate with 3.3 false-positive marks per case. (orig.)

  8. Autocorrelation spectra of an air-fluidized granular system measured by NMR

    Science.gov (United States)

    Lasic, S.; Stepisnik, J.; Mohoric, A.; Sersa, I.; Planinsic, G.

    2006-09-01

    A novel insight into the dynamics of a fluidized granular system is given by a nuclear magnetic resonance method that yields the spin-echo attenuation proportional to the spectrum of the grain positional fluctuation. Measurements of the air-fluidized oil-filled spheres and mustard seeds at different degrees of fluidization and grain volume fractions provide the velocity autocorrelation that differs from the commonly anticipated exponential Enskog decay. An empiric formula, which corresponds to the model of grain caging at collisions with adjacent beads, fits well to the experimental data. Its parameters are the characteristic collision time, the free path between collisions and the cage-breaking rate or the diffusion-like constant, which decreases with increasing grain volume fraction. Mean-squared displacements calculated from the correlation spectrum clearly show transitions from ballistic, through sub-diffusion and into diffusion regimes of grain motion.

  9. Autocorrelation exponent of conserved spin systems in the scaling regime following a critical quench.

    Science.gov (United States)

    Sire, Clément

    2004-09-24

    We study the autocorrelation function of a conserved spin system following a quench at the critical temperature. Defining the correlation length L(t) approximately t(1/z), we find that for times t' and t satisfying L(t')infinity limit, we show that lambda(')(c)=d+2 and phi=z/2. We give a heuristic argument suggesting that this result is, in fact, valid for any dimension d and spin vector dimension n. We present numerical simulations for the conserved Ising model in d=1 and d=2, which are fully consistent with the present theory.

  10. The Effect of Nonzero Autocorrelation Coefficients on the Distributions of Durbin-Watson Test Estimator: Three Autoregressive Models

    Directory of Open Access Journals (Sweden)

    Mei-Yu LEE

    2014-11-01

    Full Text Available This paper investigates the effect of the nonzero autocorrelation coefficients on the sampling distributions of the Durbin-Watson test estimator in three time-series models that have different variance-covariance matrix assumption, separately. We show that the expected values and variances of the Durbin-Watson test estimator are slightly different, but the skewed and kurtosis coefficients are considerably different among three models. The shapes of four coefficients are similar between the Durbin-Watson model and our benchmark model, but are not the same with the autoregressive model cut by one-lagged period. Second, the large sample case shows that the three models have the same expected values, however, the autoregressive model cut by one-lagged period explores different shapes of variance, skewed and kurtosis coefficients from the other two models. This implies that the large samples lead to the same expected values, 2(1 – ρ0, whatever the variance-covariance matrix of the errors is assumed. Finally, comparing with the two sample cases, the shape of each coefficient is almost the same, moreover, the autocorrelation coefficients are negatively related with expected values, are inverted-U related with variances, are cubic related with skewed coefficients, and are U related with kurtosis coefficients.

  11. On the 2nd order autocorrelation of an XUV attosecond pulse train

    International Nuclear Information System (INIS)

    Tzallas, P.; Benis, E.; Nikolopoulos, L.A.A.; Tsakiris, G.D.; Witte, K.; Charalambidis, P

    2005-01-01

    Full text: We present the first direct measurement of sub-fs light bunching that has been achieved, extending well established fs optical metrology to XUV as pulses. A mean train pulse duration of 780 as has been extracted through a 2 nd order autocorrelation approach, utilizing a nonlinear effect that is induced solely by the XUV radiation to be characterized. The approach is based on (i) a bisected spherical mirror XUV wavefront divider used as an autocorrelator and (ii) the two photon ionization of atomic He by a superposition of the 7 th to the 15 th harmonic of a Ti:sapph laser. The measured temporal mean width is more than twice its Fourier transform limited (FTL) value, in contrast to the as train pulse durations measured through other approaches, which where found much closer to the FTL values. We have investigated, and discuss here the origin of this discrepancy. An assessment of the validity of the 2 nd order AC approach for the broad band XUV radiation of as pulses is implemented through ab initio calculations (solution of the 3D TDSE of He in the presence of the superposition of the harmonic superposition) modeling the spectral and temporal response of the two-XUV-photon He ionization detector employed. It is found that both the spectral and temporal response are not affecting the measured duration. The mean width of the as train bursts is estimated from the spectral phases of the individual harmonics as they result from the rescattering model, taking into account the spatially modulated temporal width of the radiation due to the spatiotemporal intensity distribution of the driving field during the harmonic generation process. The measured value is found in reasonable agreement with the estimated duration. The method used for the 2 nd order AC in itself initiates further XUV-pump-XUV-probe studies of sub-fs-scale dynamics and at the same time becomes highly pertinent in connection with nonlinear experiments using XUV free - electron laser sources. Refs

  12. Positron-electron autocorrelation function study of E-center in phosphorus-doped silicon

    International Nuclear Information System (INIS)

    Ho, K.F.; Beling, C.D.; Fung, S.; Biasini, M.; Ferro, G.; Gong, M.

    2004-01-01

    Two dimensional fourier transformed angular correlation of annihilation radiation (2D-FT-ACAR) spectra have been taken for 10 19 cm -3 phosphorus-doped Si in the as grown state and after being subjected to 1.8 MeV e - fluences of 2 x 10 18 cm -2 . In the spectra of the irradiated samples, the zero-crossing points are observed to displace outwards from the bravais lattice positions. It is suggested that this results from positrons annihilating with electrons in localized orbitals at the defect site. An attempt is made to extract just the component of the defect's positron-electron autocorrelation function that relates to the localized defect orbitals. It is argued that such an extracted real-space function may provide a suitable means for obtaining a mapping of localized defect orbitals. (orig.)

  13. Simulating land-use changes by incorporating spatial autocorrelation and self-organization in CLUE-S modeling: a case study in Zengcheng District, Guangzhou, China

    Science.gov (United States)

    Mei, Zhixiong; Wu, Hao; Li, Shiyun

    2018-06-01

    The Conversion of Land Use and its Effects at Small regional extent (CLUE-S), which is a widely used model for land-use simulation, utilizes logistic regression to estimate the relationships between land use and its drivers, and thus, predict land-use change probabilities. However, logistic regression disregards possible spatial autocorrelation and self-organization in land-use data. Autologistic regression can depict spatial autocorrelation but cannot address self-organization, while logistic regression by considering only self-organization (NElogistic regression) fails to capture spatial autocorrelation. Therefore, this study developed a regression (NE-autologistic regression) method, which incorporated both spatial autocorrelation and self-organization, to improve CLUE-S. The Zengcheng District of Guangzhou, China was selected as the study area. The land-use data of 2001, 2005, and 2009, as well as 10 typical driving factors, were used to validate the proposed regression method and the improved CLUE-S model. Then, three future land-use scenarios in 2020: the natural growth scenario, ecological protection scenario, and economic development scenario, were simulated using the improved model. Validation results showed that NE-autologistic regression performed better than logistic regression, autologistic regression, and NE-logistic regression in predicting land-use change probabilities. The spatial allocation accuracy and kappa values of NE-autologistic-CLUE-S were higher than those of logistic-CLUE-S, autologistic-CLUE-S, and NE-logistic-CLUE-S for the simulations of two periods, 2001-2009 and 2005-2009, which proved that the improved CLUE-S model achieved the best simulation and was thereby effective to a certain extent. The scenario simulation results indicated that under all three scenarios, traffic land and residential/industrial land would increase, whereas arable land and unused land would decrease during 2009-2020. Apparent differences also existed in the

  14. Autocorrelation Study of Solar Wind Plasma and IMF Properties as Measured by the MAVEN Spacecraft

    Science.gov (United States)

    Marquette, Melissa L.; Lillis, Robert J.; Halekas, J. S.; Luhmann, J. G.; Gruesbeck, J. R.; Espley, J. R.

    2018-04-01

    It has long been a goal of the heliophysics community to understand solar wind variability at heliocentric distances other than 1 AU, especially at ˜1.5 AU due to not only the steepening of solar wind stream interactions outside 1 AU but also the number of missions available there to measure it. In this study, we use 35 months of solar wind and interplanetary magnetic field (IMF) data taken at Mars by the Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft to conduct an autocorrelation analysis of the solar wind speed, density, and dynamic pressure, which is derived from the speed and density, as well as the IMF strength and orientation. We found that the solar wind speed is coherent, that is, has an autocorrelation coefficient above 1/e, over roughly 56 hr, while the density and pressure are coherent over smaller intervals of roughly 25 and 20 hr, respectively, and that the IMF strength is coherent over time intervals of approximately 20 hr, while the cone and clock angles are considerably less steady but still somewhat coherent up to time lags of roughly 16 hr. We also found that when the speed, density, pressure, or IMF strength is higher than average, the solar wind or IMF becomes uncorrelated more quickly, while when they are below average, it tends to be steadier. This analysis allows us to make estimates of the values of solar wind plasma and IMF parameters when they are not directly measured and provide an approximation of the error associated with that estimate.

  15. Auto-correlation based intelligent technique for complex waveform presentation and measurement

    International Nuclear Information System (INIS)

    Rana, K P S; Singh, R; Sayann, K S

    2009-01-01

    Waveform acquisition and presentation forms the heart of many measurement systems. Particularly, data acquisition and presentation of repeating complex signals like sine sweep and frequency-modulated signals introduces the challenge of waveform time period estimation and live waveform presentation. This paper presents an intelligent technique, for waveform period estimation of both the complex and simple waveforms, based on the normalized auto-correlation method. The proposed technique is demonstrated using LabVIEW based intensive simulations on several simple and complex waveforms. Implementation of the technique is successfully demonstrated using LabVIEW based virtual instrumentation. Sine sweep vibration waveforms are successfully presented and measured for electrodynamic shaker system generated vibrations. The proposed method is also suitable for digital storage oscilloscope (DSO) triggering, for complex signals acquisition and presentation. This intelligence can be embodied into the DSO, making it an intelligent measurement system, catering wide varieties of the waveforms. The proposed technique, simulation results, robustness study and implementation results are presented in this paper.

  16. Risk-based transfer responses to climate change, simulated through autocorrelated stochastic methods

    Science.gov (United States)

    Kirsch, B.; Characklis, G. W.

    2009-12-01

    Maintaining municipal water supply reliability despite growing demands can be achieved through a variety of mechanisms, including supply strategies such as temporary transfers. However, much of the attention on transfers has been focused on market-based transfers in the western United States largely ignoring the potential for transfers in the eastern U.S. The different legal framework of the eastern and western U.S. leads to characteristic differences between their respective transfers. Western transfers tend to be agricultural-to-urban and involve raw, untreated water, with the transfer often involving a simple change in the location and/or timing of withdrawals. Eastern transfers tend to be contractually established urban-to-urban transfers of treated water, thereby requiring the infrastructure to transfer water between utilities. Utilities require the tools to be able to evaluate transfer decision rules and the resulting expected future transfer behavior. Given the long-term planning horizons of utilities, potential changes in hydrologic patterns due to climate change must be considered. In response, this research develops a method for generating a stochastic time series that reproduces the historic autocorrelation and can be adapted to accommodate future climate scenarios. While analogous in operation to an autoregressive model, this method reproduces the seasonal autocorrelation structure, as opposed to assuming the strict stationarity produced by an autoregressive model. Such urban-to-urban transfers are designed to be rare, transient events used primarily during times of severe drought, and incorporating Monte Carlo techniques allows for the development of probability distributions of likely outcomes. This research evaluates a system risk-based, urban-to-urban transfer agreement between three utilities in the Triangle region of North Carolina. Two utilities maintain their own surface water supplies in adjoining watersheds and look to obtain transfers via

  17. Assessing thermal comfort and energy efficiency in buildings by statistical quality control for autocorrelated data

    International Nuclear Information System (INIS)

    Barbeito, Inés; Zaragoza, Sonia; Tarrío-Saavedra, Javier; Naya, Salvador

    2017-01-01

    Highlights: • Intelligent web platform development for energy efficiency management in buildings. • Controlling and supervising thermal comfort and energy consumption in buildings. • Statistical quality control procedure to deal with autocorrelated data. • Open source alternative using R software. - Abstract: In this paper, a case study of performing a reliable statistical procedure to evaluate the quality of HVAC systems in buildings using data retrieved from an ad hoc big data web energy platform is presented. The proposed methodology based on statistical quality control (SQC) is used to analyze the real state of thermal comfort and energy efficiency of the offices of the company FRIDAMA (Spain) in a reliable way. Non-conformities or alarms, and the actual assignable causes of these out of control states are detected. The capability to meet specification requirements is also analyzed. Tools and packages implemented in the open-source R software are employed to apply the different procedures. First, this study proposes to fit ARIMA time series models to CTQ variables. Then, the application of Shewhart and EWMA control charts to the time series residuals is proposed to control and monitor thermal comfort and energy consumption in buildings. Once thermal comfort and consumption variability are estimated, the implementation of capability indexes for autocorrelated variables is proposed to calculate the degree to which standards specifications are met. According with case study results, the proposed methodology has detected real anomalies in HVAC installation, helping to detect assignable causes and to make appropriate decisions. One of the goals is to perform and describe step by step this statistical procedure in order to be replicated by practitioners in a better way.

  18. Recommended number of strides for automatic assessment of gait symmetry and regularity in above-knee amputees by means of accelerometry and autocorrelation analysis

    Directory of Open Access Journals (Sweden)

    Tura Andrea

    2012-02-01

    Full Text Available Abstract Background Symmetry and regularity of gait are essential outcomes of gait retraining programs, especially in lower-limb amputees. This study aims presenting an algorithm to automatically compute symmetry and regularity indices, and assessing the minimum number of strides for appropriate evaluation of gait symmetry and regularity through autocorrelation of acceleration signals. Methods Ten transfemoral amputees (AMP and ten control subjects (CTRL were studied. Subjects wore an accelerometer and were asked to walk for 70 m at their natural speed (twice. Reference values of step and stride regularity indices (Ad1 and Ad2 were obtained by autocorrelation analysis of the vertical and antero-posterior acceleration signals, excluding initial and final strides. The Ad1 and Ad2 coefficients were then computed at different stages by analyzing increasing portions of the signals (considering both the signals cleaned by initial and final strides, and the whole signals. At each stage, the difference between Ad1 and Ad2 values and the corresponding reference values were compared with the minimum detectable difference, MDD, of the index. If that difference was less than MDD, it was assumed that the portion of signal used in the analysis was of sufficient length to allow reliable estimation of the autocorrelation coefficient. Results All Ad1 and Ad2 indices were lower in AMP than in CTRL (P Conclusions Without the need to identify and eliminate the phases of gait initiation and termination, twenty strides can provide a reasonable amount of information to reliably estimate gait regularity in transfemoral amputees.

  19. AFM topographies of densely packed nanoparticles: a quick way to determine the lateral size distribution by autocorrelation function analysis

    Czech Academy of Sciences Publication Activity Database

    Fekete, Ladislav; Kůsová, Kateřina; Petrák, Václav; Kratochvílová, Irena

    2012-01-01

    Roč. 14, č. 8 (2012), s. 1-10 ISSN 1388-0764 R&D Projects: GA AV ČR KAN200100801; GA TA ČR TA01011165; GA ČR(CZ) GAP304/10/1951; GA ČR GPP204/12/P235 Institutional research plan: CEZ:AV0Z10100520 Keywords : lateral grain size distribution * AFM * autocorrelation function * nanodiamond Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 2.175, year: 2012

  20. Long-time tails of the velocity autocorrelation function in 2D and 3D lattice gas cellular automata: a test of mode-coupling theory

    NARCIS (Netherlands)

    Hoef, M.A. van der; Frenkel, D.

    1990-01-01

    We report simulations of the velocity autocorrelation function (VACF) of a tagged particle in two- and three-dimensional lattice-gas cellular automata, using a new technique that is about a million times more efficient than the conventional techniques. The simulations clearly show the algebraic

  1. Autocorrelation and cross-correlation between hCGβ and PAPP-A in repeated sampling during first trimester of pregnancy

    DEFF Research Database (Denmark)

    Nørgaard, Pernille; Wright, Dave; Ball, Susan

    2013-01-01

    Theoretically, repeated sampling of free β-human chorionic gonadotropin (hCGβ) and pregnancy associated plasma protein-A (PAPP-A) in the first trimester of pregnancy might improve performance of risk assessment of trisomy 21 (T21). To assess the performance of a screening test involving repeated...... measures of biochemical markers, correlations between markers must be estimated. The aims of this study were to calculate the autocorrelation and cross-correlation between hCGβ and PAPP-A in the first trimester of pregnancy and to investigate the possible impact of gestational age at the first sample...

  2. Autocorrelation studies of the arrival directions of UHECRs measured by the surface detector of the Pierre Auger Observatory

    Energy Technology Data Exchange (ETDEWEB)

    Schulte, Stephan

    2011-07-11

    The history of cosmic rays started in the beginning of the 20th century. Since then one of the main questions is their origin. Due to the very low flux at the highest energies huge areas have to be instrumented to answer this question. For this purpose the distribution of the arrival directions of cosmic rays is studied. The largest experiment so far is the Pierre Auger Observatory, located in the Pampa in western Argentina with an area of about 3000 km{sup 2}. In recent years it provided many major contributions to the field of cosmic ray physics and its data is the basis of this work. Among other things a correlation analysis of Ultra High Energy Cosmic Rays (UHECRs) with Active Galactic Nuclei (AGN) was performed leading to the first evidence that UHECRs are not isotropically distributed. Here the distribution of arrival directions of cosmic rays at the highest energies (>50 EeV) is examined by using autocorrelation methods to check whether it is compatible with the isotropic expectation or not.This thesis is organised as follows: in the first two chapters a short introduction to the topic is given, followed by a more general discussion on cosmic rays including models of acceleration, possible sources and the propagation of UHECRs in the third chapter. The fourth chapter focuses on the detector design of the Pierre Auger Observatory and event reconstruction at highest energies. Special attention is paid to the monitoring of the High Elevation Auger Telescopes (HEAT). It is a low energy enhancement of the observatory consisting of three tiltable fluorescence telescopes. The calibration of the new sensor setups is described as well as the installation in each HEAT shelter. The next chapter starts with a detailed description of the underlying ideas and motivations of autocorrelation methods: a representation of the 2pt-Correlation Function and its extension, a Minimum Spanning Tree and a Cluster Algorithm with different weighting procedures. The principle of each

  3. Autocorrelation studies of the arrival directions of UHECRs measured by the surface detector of the Pierre Auger Observatory

    International Nuclear Information System (INIS)

    Schulte, Stephan

    2011-01-01

    The history of cosmic rays started in the beginning of the 20th century. Since then one of the main questions is their origin. Due to the very low flux at the highest energies huge areas have to be instrumented to answer this question. For this purpose the distribution of the arrival directions of cosmic rays is studied. The largest experiment so far is the Pierre Auger Observatory, located in the Pampa in western Argentina with an area of about 3000 km 2 . In recent years it provided many major contributions to the field of cosmic ray physics and its data is the basis of this work. Among other things a correlation analysis of Ultra High Energy Cosmic Rays (UHECRs) with Active Galactic Nuclei (AGN) was performed leading to the first evidence that UHECRs are not isotropically distributed. Here the distribution of arrival directions of cosmic rays at the highest energies (>50 EeV) is examined by using autocorrelation methods to check whether it is compatible with the isotropic expectation or not.This thesis is organised as follows: in the first two chapters a short introduction to the topic is given, followed by a more general discussion on cosmic rays including models of acceleration, possible sources and the propagation of UHECRs in the third chapter. The fourth chapter focuses on the detector design of the Pierre Auger Observatory and event reconstruction at highest energies. Special attention is paid to the monitoring of the High Elevation Auger Telescopes (HEAT). It is a low energy enhancement of the observatory consisting of three tiltable fluorescence telescopes. The calibration of the new sensor setups is described as well as the installation in each HEAT shelter. The next chapter starts with a detailed description of the underlying ideas and motivations of autocorrelation methods: a representation of the 2pt-Correlation Function and its extension, a Minimum Spanning Tree and a Cluster Algorithm with different weighting procedures. The principle of each

  4. The Green-Kubo formula, autocorrelation function and fluctuation spectrum for finite Markov chains with continuous time

    International Nuclear Information System (INIS)

    Chen Yong; Chen Xi; Qian Minping

    2006-01-01

    A general form of the Green-Kubo formula, which describes the fluctuations pertaining to all the steady states whether equilibrium or non-equilibrium, for a system driven by a finite Markov chain with continuous time (briefly, MC) {ξ t }, is shown. The equivalence of different forms of the Green-Kubo formula is exploited. We also look at the differences in terms of the autocorrelation function and the fluctuation spectrum between the equilibrium state and the non-equilibrium steady state. Also, if the MC is in the non-equilibrium steady state, we can always find a complex function ψ, such that the fluctuation spectrum of {φ(ξ t )} is non-monotonous in [0, + ∞)

  5. Perceptual interaction between carrier periodicity and amplitude modulation in broadband stimuli: A comparison of the autocorrelation and modulation-filterbank model

    DEFF Research Database (Denmark)

    Stein, A.; Ewert, Stephan; Wiegrebe, L.

    2005-01-01

    , autocorrelation is applied. Considering the large overlap in pitch and modulation perception, this is not parsimonious. Two experiments are presented to investigate the interaction between carrier periodicity, which produces strong pitch sensations, and envelope periodicity using broadband stimuli. Results show......Recent temporal models of pitch and amplitude modulation perception converge on a relatively realistic implementation of cochlear processing followed by a temporal analysis of periodicity. However, for modulation perception, a modulation filterbank is applied whereas for pitch perception...

  6. Cut contribution to momentum autocorrelation function of an impurity in a classical diatomic chain

    Science.gov (United States)

    Yu, Ming B.

    2018-02-01

    A classic diatomic chain with a mass impurity is studied using the recurrence relations method. The momentum autocorrelation function of the impurity is a sum of contributions from two pairs of resonant poles and three branch cuts. The former results in cosine function and the latter in acoustic and optical branches. By use of convolution theorem, analytical expressions for the acoustic and optical branches are derived as even-order Bessel function expansions. The expansion coefficients are integrals of elliptic functions in the real axis for the acoustic branch and along a contour parallel to the imaginary axis for the optical branch, respectively. An integral is carried out for the calculation of optical branch: ∫0 ϕ dθ/√((1 - r 1 2 sin2 θ)(1 - r 2 2 sin2 θ)) = igsn -1 (sin ϕ) ( r 2 2 > r 1 2 > 1, g is a constant).

  7. ISAR Imaging of Ship Targets Based on an Integrated Cubic Phase Bilinear Autocorrelation Function

    Directory of Open Access Journals (Sweden)

    Jibin Zheng

    2017-03-01

    Full Text Available For inverse synthetic aperture radar (ISAR imaging of a ship target moving with ocean waves, the image constructed with the standard range-Doppler (RD technique is blurred and the range-instantaneous-Doppler (RID technique has to be used to improve the image quality. In this paper, azimuth echoes in a range cell of the ship target are modeled as noisy multicomponent cubic phase signals (CPSs after the motion compensation and a RID ISAR imaging algorithm is proposed based on the integrated cubic phase bilinear autocorrelation function (ICPBAF. The ICPBAF is bilinear and based on the two-dimensionally coherent energy accumulation. Compared to five other estimation algorithms, the ICPBAF can acquire higher cross term suppression and anti-noise performance with a reasonable computational cost. Through simulations and analyses with the synthetic model and real radar data, we verify the effectiveness of the ICPBAF and corresponding RID ISAR imaging algorithm.

  8. Search for neutrino point sources with an all-sky autocorrelation analysis in IceCube

    Energy Technology Data Exchange (ETDEWEB)

    Turcati, Andrea; Bernhard, Anna; Coenders, Stefan [TU, Munich (Germany); Collaboration: IceCube-Collaboration

    2016-07-01

    The IceCube Neutrino Observatory is a cubic kilometre scale neutrino telescope located in the Antarctic ice. Its full-sky field of view gives unique opportunities to study the neutrino emission from the Galactic and extragalactic sky. Recently, IceCube found the first signal of astrophysical neutrinos with energies up to the PeV scale, but the origin of these particles still remains unresolved. Given the observed flux, the absence of observations of bright point-sources is explainable with the presence of numerous weak sources. This scenario can be tested using autocorrelation methods. We present here the sensitivities and discovery potentials of a two-point angular correlation analysis performed on seven years of IceCube data, taken between 2008 and 2015. The test is applied on the northern and southern skies separately, using the neutrino energy information to improve the effectiveness of the method.

  9. An attempt at solving the problem of autocorrelation associated with use of mean approach for pooling cross-section and time series in regression modelling

    International Nuclear Information System (INIS)

    Nuamah, N.N.N.N.

    1990-12-01

    The paradoxical nature of results of the mean approach in pooling cross-section and time series data has been identified to be caused by the presence in the normal equations of phenomena such as autocovariances, multicollinear covariances, drift covariances and drift multicollinear covariances. This paper considers the problem of autocorrelation and suggests ways of solving it. (author). 4 refs

  10. The Green-Kubo formula, autocorrelation function and fluctuation spectrum for finite Markov chains with continuous time

    Energy Technology Data Exchange (ETDEWEB)

    Chen Yong; Chen Xi; Qian Minping [School of Mathematical Sciences, Peking University, Beijing 100871 (China)

    2006-03-17

    A general form of the Green-Kubo formula, which describes the fluctuations pertaining to all the steady states whether equilibrium or non-equilibrium, for a system driven by a finite Markov chain with continuous time (briefly, MC) {l_brace}{xi}{sub t}{r_brace}, is shown. The equivalence of different forms of the Green-Kubo formula is exploited. We also look at the differences in terms of the autocorrelation function and the fluctuation spectrum between the equilibrium state and the non-equilibrium steady state. Also, if the MC is in the non-equilibrium steady state, we can always find a complex function {psi}, such that the fluctuation spectrum of {l_brace}{phi}({xi}{sub t}){r_brace} is non-monotonous in [0, + {infinity})

  11. Simultaneous measurement of particle velocity and size based on gray difference and autocorrelation

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    The gray of two images of a same particle taken by a digital camera with different exposure times is different too. Based on the gray difference of particle images in a double-exposed photo and autocorrelation processing of digital images,this paper proposes a method for measuring particle velocities and sizes simultaneously. This paper also introduces the theoretical foundation of this method,the process of particle imaging and image processing,and the simultaneous measurement of velocity and size of a low speed flow field with 35 μm and 75 μm standard particles. The graphical measurement results can really reflect the flow characteristics of the flow field. In addition,although the measured velocity and size histograms of these two kinds of standard particles are slightly wider than the theoretical ones,they are all still similar to the normal distribution,and the peak velocities and diameters of the histograms are consistent with the default values. Therefore,this measurement method is capable of providing moderate measurement accuracy,and it can be further developed for high-speed flow field measurements.

  12. How cosmic microwave background correlations at large angles relate to mass autocorrelations in space

    Science.gov (United States)

    Blumenthal, George R.; Johnston, Kathryn V.

    1994-01-01

    The Sachs-Wolfe effect is known to produce large angular scale fluctuations in the cosmic microwave background radiation (CMBR) due to gravitational potential fluctuations. We show how the angular correlation function of the CMBR can be expressed explicitly in terms of the mass autocorrelation function xi(r) in the universe. We derive analytic expressions for the angular correlation function and its multipole moments in terms of integrals over xi(r) or its second moment, J(sub 3)(r), which does not need to satisfy the sort of integral constraint that xi(r) must. We derive similar expressions for bulk flow velocity in terms of xi and J(sub 3). One interesting result that emerges directly from this analysis is that, for all angles theta, there is a substantial contribution to the correlation function from a wide range of distance r and that radial shape of this contribution does not vary greatly with angle.

  13. An investigation on thermal patterns in Iran based on spatial autocorrelation

    Science.gov (United States)

    Fallah Ghalhari, Gholamabbas; Dadashi Roudbari, Abbasali

    2018-02-01

    The present study aimed at investigating temporal-spatial patterns and monthly patterns of temperature in Iran using new spatial statistical methods such as cluster and outlier analysis, and hotspot analysis. To do so, climatic parameters, monthly average temperature of 122 synoptic stations, were assessed. Statistical analysis showed that January with 120.75% had the most fluctuation among the studied months. Global Moran's Index revealed that yearly changes of temperature in Iran followed a strong spatially clustered pattern. Findings showed that the biggest thermal cluster pattern in Iran, 0.975388, occurred in May. Cluster and outlier analyses showed that thermal homogeneity in Iran decreases in cold months, while it increases in warm months. This is due to the radiation angle and synoptic systems which strongly influence thermal order in Iran. The elevations, however, have the most notable part proved by Geographically weighted regression model. Iran's thermal analysis through hotspot showed that hot thermal patterns (very hot, hot, and semi-hot) were dominant in the South, covering an area of 33.5% (about 552,145.3 km2). Regions such as mountain foot and low lands lack any significant spatial autocorrelation, 25.2% covering about 415,345.1 km2. The last is the cold thermal area (very cold, cold, and semi-cold) with about 25.2% covering about 552,145.3 km2 of the whole area of Iran.

  14. Processing of pulse oximeter signals using adaptive filtering and autocorrelation to isolate perfusion and oxygenation components

    Science.gov (United States)

    Ibey, Bennett; Subramanian, Hariharan; Ericson, Nance; Xu, Weijian; Wilson, Mark; Cote, Gerard L.

    2005-03-01

    A blood perfusion and oxygenation sensor has been developed for in situ monitoring of transplanted organs. In processing in situ data, motion artifacts due to increased perfusion can create invalid oxygenation saturation values. In order to remove the unwanted artifacts from the pulsatile signal, adaptive filtering was employed using a third wavelength source centered at 810nm as a reference signal. The 810 nm source resides approximately at the isosbestic point in the hemoglobin absorption curve where the absorbance of light is nearly equal for oxygenated and deoxygenated hemoglobin. Using an autocorrelation based algorithm oxygenation saturation values can be obtained without the need for large sampling data sets allowing for near real-time processing. This technique has been shown to be more reliable than traditional techniques and proven to adequately improve the measurement of oxygenation values in varying perfusion states.

  15. High-Responsivity Graphene-Boron Nitride Photodetector and Autocorrelator in a Silicon Photonic Integrated Circuit.

    Science.gov (United States)

    Shiue, Ren-Jye; Gao, Yuanda; Wang, Yifei; Peng, Cheng; Robertson, Alexander D; Efetov, Dmitri K; Assefa, Solomon; Koppens, Frank H L; Hone, James; Englund, Dirk

    2015-11-11

    Graphene and other two-dimensional (2D) materials have emerged as promising materials for broadband and ultrafast photodetection and optical modulation. These optoelectronic capabilities can augment complementary metal-oxide-semiconductor (CMOS) devices for high-speed and low-power optical interconnects. Here, we demonstrate an on-chip ultrafast photodetector based on a two-dimensional heterostructure consisting of high-quality graphene encapsulated in hexagonal boron nitride. Coupled to the optical mode of a silicon waveguide, this 2D heterostructure-based photodetector exhibits a maximum responsivity of 0.36 A/W and high-speed operation with a 3 dB cutoff at 42 GHz. From photocurrent measurements as a function of the top-gate and source-drain voltages, we conclude that the photoresponse is consistent with hot electron mediated effects. At moderate peak powers above 50 mW, we observe a saturating photocurrent consistent with the mechanisms of electron-phonon supercollision cooling. This nonlinear photoresponse enables optical on-chip autocorrelation measurements with picosecond-scale timing resolution and exceptionally low peak powers.

  16. ADDING A NEW STEP WITH SPATIAL AUTOCORRELATION TO IMPROVE THE FOUR-STEP TRAVEL DEMAND MODEL WITH FEEDBACK FOR A DEVELOPING CITY

    Directory of Open Access Journals (Sweden)

    Xuesong FENG, Ph.D Candidate

    2009-01-01

    Full Text Available It is expected that improvement of transport networks could give rise to the change of spatial distributions of population-related factors and car ownership, which are expected to further influence travel demand. To properly reflect such an interdependence mechanism, an aggregate multinomial logit (A-MNL model was firstly applied to represent the spatial distributions of these exogenous variables of the travel demand model by reflecting the influence of transport networks. Next, the spatial autocorrelation analysis is introduced into the log-transformed A-MNL model (called SPA-MNL model. Thereafter, the SPA-MNL model is integrated into the four-step travel demand model with feedback (called 4-STEP model. As a result, an integrated travel demand model is newly developed and named as the SPA-STEP model. Using person trip data collected in Beijing, the performance of the SPA-STEP model is empirically compared with the 4-STEP model. It was proven that the SPA-STEP model is superior to the 4-STEP model in accuracy; most of the estimated parameters showed statistical differences in values. Moreover, though the results of the simulations to the same set of assumed scenarios by the 4-STEP model and the SPA-STEP model consistently suggested the same sustainable path for the future development of Beijing, it was found that the environmental sustainability and the traffic congestion for these scenarios were generally overestimated by the 4-STEP model compared with the corresponding analyses by the SPA-STEP model. Such differences were clearly generated by the introduction of the new modeling step with spatial autocorrelation.

  17. Temporal and spatial distribution characteristics in the natural plague foci of Chinese Mongolian gerbils based on spatial autocorrelation.

    Science.gov (United States)

    Du, Hai-Wen; Wang, Yong; Zhuang, Da-Fang; Jiang, Xiao-San

    2017-08-07

    The nest flea index of Meriones unguiculatus is a critical indicator for the prevention and control of plague, which can be used not only to detect the spatial and temporal distributions of Meriones unguiculatus, but also to reveal its cluster rule. This research detected the temporal and spatial distribution characteristics of the plague natural foci of Mongolian gerbils by body flea index from 2005 to 2014, in order to predict plague outbreaks. Global spatial autocorrelation was used to describe the entire spatial distribution pattern of the body flea index in the natural plague foci of typical Chinese Mongolian gerbils. Cluster and outlier analysis and hot spot analysis were also used to detect the intensity of clusters based on geographic information system methods. The quantity of M. unguiculatus nest fleas in the sentinel surveillance sites from 2005 to 2014 and host density data of the study area from 2005 to 2010 used in this study were provided by Chinese Center for Disease Control and Prevention. The epidemic focus regions of the Mongolian gerbils remain the same as the hot spot regions relating to the body flea index. High clustering areas possess a similar pattern as the distribution pattern of the body flea index indicating that the transmission risk of plague is relatively high. In terms of time series, the area of the epidemic focus gradually increased from 2005 to 2007, declined rapidly in 2008 and 2009, and then decreased slowly and began trending towards stability from 2009 to 2014. For the spatial change, the epidemic focus regions began moving northward from the southwest epidemic focus of the Mongolian gerbils from 2005 to 2007, and then moved from north to south in 2007 and 2008. The body flea index of Chinese gerbil foci reveals significant spatial and temporal aggregation characteristics through the employing of spatial autocorrelation. The diversity of temporary and spatial distribution is mainly affected by seasonal variation, the human

  18. Quantifying uncertainty in soot volume fraction estimates using Bayesian inference of auto-correlated laser-induced incandescence measurements

    Science.gov (United States)

    Hadwin, Paul J.; Sipkens, T. A.; Thomson, K. A.; Liu, F.; Daun, K. J.

    2016-01-01

    Auto-correlated laser-induced incandescence (AC-LII) infers the soot volume fraction (SVF) of soot particles by comparing the spectral incandescence from laser-energized particles to the pyrometrically inferred peak soot temperature. This calculation requires detailed knowledge of model parameters such as the absorption function of soot, which may vary with combustion chemistry, soot age, and the internal structure of the soot. This work presents a Bayesian methodology to quantify such uncertainties. This technique treats the additional "nuisance" model parameters, including the soot absorption function, as stochastic variables and incorporates the current state of knowledge of these parameters into the inference process through maximum entropy priors. While standard AC-LII analysis provides a point estimate of the SVF, Bayesian techniques infer the posterior probability density, which will allow scientists and engineers to better assess the reliability of AC-LII inferred SVFs in the context of environmental regulations and competing diagnostics.

  19. A New Multi-Gaussian Auto-Correlation Function for the Modeling of Realistic Shot Peened Random Rough Surfaces

    International Nuclear Information System (INIS)

    Hassan, W.; Blodgett, M.

    2006-01-01

    Shot peening is the primary surface treatment used to create a uniform, consistent, and reliable sub-surface compressive residual stress layer in aero engine components. A by-product of the shot peening process is random surface roughness that can affect the measurements of the resulting residual stresses and therefore impede their NDE assessment. High frequency eddy current conductivity measurements have the potential to assess these residual stresses in Ni-base super alloys. However, the effect of random surface roughness is expected to become significant in the desired measurement frequency range of 10 to 100 MHz. In this paper, a new Multi-Gaussian (MG) auto-correlation function is proposed for modeling the resulting pseudo-random rough profiles. Its use in the calculation of the Apparent Eddy Current Conductivity (AECC) loss due to surface roughness is demonstrated. The numerical results presented need to be validated with experimental measurements

  20. Streams of events and performance of queuing systems: The basic anatomy of arrival/departure processes, when the focus is set on autocorrelation

    DEFF Research Database (Denmark)

    Nielsen, Erland Hejn

    2004-01-01

    significant nature or (2) aggregate system behaviour is in general very different from just the summing-up (even for finite sets of micro-behavioural patterns) and/or (3) it is simply a wrong assumption that in many cases is chosen by mere convention or plain convenience. It is evident that before choosing...... method or some autocorrelation extended descriptive sampling method, can then easily be applied. The results from the Livny, Melamed and Tsiolis (1993) study as well as the results from this work both indicates that system performance measures as for instance average waiting time or average time...

  1. FREQUENCY ANALYSIS OF RLE-BLOCKS REPETITIONS IN THE SERIES OF BINARY CODES WITH OPTIMAL MINIMAX CRITERION OF AUTOCORRELATION FUNCTION

    Directory of Open Access Journals (Sweden)

    A. A. Kovylin

    2013-01-01

    Full Text Available The article describes the problem of searching for binary pseudo-random sequences with quasi-ideal autocorrelation function, which are to be used in contemporary communication systems, including mobile and wireless data transfer interfaces. In the synthesis of binary sequences sets, the target set is manning them based on the minimax criterion by which a sequence is considered to be optimal according to the intended application. In the course of the research the optimal sequences with order of up to 52 were obtained; the analysis of Run Length Encoding was carried out. The analysis showed regularities in the distribution of series number of different lengths in the codes that are optimal on the chosen criteria, which would make it possible to optimize the searching process for such codes in the future.

  2. Coarsening in 3D nonconserved Ising model at zero temperature: Anomaly in structure and slow relaxation of order-parameter autocorrelation

    Science.gov (United States)

    Chakraborty, Saikat; Das, Subir K.

    2017-09-01

    Via Monte Carlo simulations we study pattern and aging during coarsening in a nonconserved nearest-neighbor Ising model, following quenches from infinite to zero temperature, in space dimension d = 3. The decay of the order-parameter autocorrelation function appears to obey a power-law behavior, as a function of the ratio between the observation and waiting times, in the large ratio limit. However, the exponent of the power law, estimated accurately via a state-of-the-art method, violates a well-known lower bound. This surprising fact has been discussed in connection with a quantitative picture of the structural anomaly that the 3D Ising model exhibits during coarsening at zero temperature. These results are compared with those for quenches to a temperature above that of the roughening transition.

  3. Análise quantitativa da influência de um novo paradigma ecológico: autocorrelação espacial - DOI: 10.4025/actascibiolsci.v25i1.2113 Quantitative analysis of the influence of a new ecological paradigm: spatial autocorrelation - DOI: 10.4025/actascibiolsci.v25i1.2113

    Directory of Open Access Journals (Sweden)

    Luis Mauricio Bini

    2003-04-01

    Full Text Available O objetivo desse trabalho foi o de avaliar a influência da autocorrelação espacial (ausência de independência estatística de observações obtidas ao longo do espaço geográfico nos estudos ecológicos. Para tanto, uma avaliação dos trabalhos que empregaram os métodos necessários para a quantificação da autocorrelação espacial foi realizada, utilizando os dados fornecidos pelo “Institute for Scientific Information”. Os resultados demonstraram que existe uma tendência crescente da utilização das análises de autocorrelação espacial em estudos ecológicos, e que a presença de autocorrelação espacial significativa foi detectada na maior parte dos estudos. Além disso, esses estudos foram desenvolvidos em vários países, por cientistas de diferentes nacionalidades, com diferentes grupos de organismos e em diferentes tipos de ecossistemas. Dessa forma, pode-se considerar que o reconhecimento explícito da estrutura espacial dos processos naturais, por meio da análise da autocorrelação espacial, é um novo paradigma dos estudos ecológicosThe aim of this paper was to evaluate the influence of the spatial autocorrelation (absence of independence among observations gathered along geographical space in ecological studies. For this task, an evaluation of the studies that used spatial autocorrelation analysis was carried out using the data furnished by the Institute for Scientific Information. There is a positive temporal tendency in the number of studies that used spatial autocorrelation analysis. A significant autocorrelation was detected in most studies. Moreover, scientist of several nationalities carried out these studies in different countries, with different organisms and in different types of ecosystems. In this way, it is possible to consider that the explicit incorporation of the spatial structure of natural processes, through the autocorrelation analysis, is a new ecological paradigm

  4. Autocorrelation descriptor improvements for QSAR: 2DA_Sign and 3DA_Sign

    Science.gov (United States)

    Sliwoski, Gregory; Mendenhall, Jeffrey; Meiler, Jens

    2016-03-01

    Quantitative structure-activity relationship (QSAR) is a branch of computer aided drug discovery that relates chemical structures to biological activity. Two well established and related QSAR descriptors are two- and three-dimensional autocorrelation (2DA and 3DA). These descriptors encode the relative position of atoms or atom properties by calculating the separation between atom pairs in terms of number of bonds (2DA) or Euclidean distance (3DA). The sums of all values computed for a given small molecule are collected in a histogram. Atom properties can be added with a coefficient that is the product of atom properties for each pair. This procedure can lead to information loss when signed atom properties are considered such as partial charge. For example, the product of two positive charges is indistinguishable from the product of two equivalent negative charges. In this paper, we present variations of 2DA and 3DA called 2DA_Sign and 3DA_Sign that avoid information loss by splitting unique sign pairs into individual histograms. We evaluate these variations with models trained on nine datasets spanning a range of drug target classes. Both 2DA_Sign and 3DA_Sign significantly increase model performance across all datasets when compared with traditional 2DA and 3DA. Lastly, we find that limiting 3DA_Sign to maximum atom pair distances of 6 Å instead of 12 Å further increases model performance, suggesting that conformational flexibility may hinder performance with longer 3DA descriptors. Consistent with this finding, limiting the number of bonds in 2DA_Sign from 11 to 5 fails to improve performance.

  5. AFM topographies of densely packed nanoparticles: a quick way to determine the lateral size distribution by autocorrelation function analysis

    International Nuclear Information System (INIS)

    Fekete, L.; Kůsová, K.; Petrák, V.; Kratochvílová, I.

    2012-01-01

    The distribution of sizes is one of the basic characteristics of nanoparticles. Here, we propose a novel way to determine the lateral distribution of sizes from AFM topographies. Our algorithm is based on the autocorrelation function and can be applied both on topographies containing spatially separated and densely packed nanoparticles as well as on topographies of polycrystalline films. As no manual treatment is required, this algorithm can be easily automatable for batch processing. The algorithm works in principle with any kind of spatially mapped information (AFM current maps, optical microscope images, etc.), and as such has no size limitations. However, in the case of AFM topographies, the tip/sample convolution effects will be the factor limiting the smallest size to which the algorithm is applicable. Here, we demonstrate the usefulness of this algorithm on objects with sizes ranging between 20 nm and 1.5 μm.

  6. A hierarchical model of daily stream temperature using air-water temperature synchronization, autocorrelation, and time lags

    Directory of Open Access Journals (Sweden)

    Benjamin H. Letcher

    2016-02-01

    Full Text Available Water temperature is a primary driver of stream ecosystems and commonly forms the basis of stream classifications. Robust models of stream temperature are critical as the climate changes, but estimating daily stream temperature poses several important challenges. We developed a statistical model that accounts for many challenges that can make stream temperature estimation difficult. Our model identifies the yearly period when air and water temperature are synchronized, accommodates hysteresis, incorporates time lags, deals with missing data and autocorrelation and can include external drivers. In a small stream network, the model performed well (RMSE = 0.59°C, identified a clear warming trend (0.63 °C decade−1 and a widening of the synchronized period (29 d decade−1. We also carefully evaluated how missing data influenced predictions. Missing data within a year had a small effect on performance (∼0.05% average drop in RMSE with 10% fewer days with data. Missing all data for a year decreased performance (∼0.6 °C jump in RMSE, but this decrease was moderated when data were available from other streams in the network.

  7. Spot auto-focusing and spot auto-stigmation methods with high-definition auto-correlation function in high-resolution TEM.

    Science.gov (United States)

    Isakozawa, Shigeto; Fuse, Taishi; Amano, Junpei; Baba, Norio

    2018-04-01

    As alternatives to the diffractogram-based method in high-resolution transmission electron microscopy, a spot auto-focusing (AF) method and a spot auto-stigmation (AS) method are presented with a unique high-definition auto-correlation function (HD-ACF). The HD-ACF clearly resolves the ACF central peak region in small amorphous-thin-film images, reflecting the phase contrast transfer function. At a 300-k magnification for a 120-kV transmission electron microscope, the smallest areas used are 64 × 64 pixels (~3 nm2) for the AF and 256 × 256 pixels for the AS. A useful advantage of these methods is that the AF function has an allowable accuracy even for a low s/n (~1.0) image. A reference database on the defocus dependency of the HD-ACF by the pre-acquisition of through-focus amorphous-thin-film images must be prepared to use these methods. This can be very beneficial because the specimens are not limited to approximations of weak phase objects but can be extended to objects outside such approximations.

  8. Auto-correlation in the motor/imaginary human EEG signals: A vision about the FDFA fluctuations.

    Directory of Open Access Journals (Sweden)

    Gilney Figueira Zebende

    Full Text Available In this paper we analyzed, by the FDFA root mean square fluctuation (rms function, the motor/imaginary human activity produced by a 64-channel electroencephalography (EEG. We utilized the Physionet on-line databank, a publicly available database of human EEG signals, as a standardized reference database for this study. Herein, we report the use of detrended fluctuation analysis (DFA method for EEG analysis. We show that the complex time series of the EEG exhibits characteristic fluctuations depending on the analyzed channel in the scalp-recorded EEG. In order to demonstrate the effectiveness of the proposed technique, we analyzed four distinct channels represented here by F332, F637 (frontal region of the head and P349, P654 (parietal region of the head. We verified that the amplitude of the FDFA rms function is greater for the frontal channels than for the parietal. To tabulate this information in a better way, we define and calculate the difference between FDFA (in log scale for the channels, thus defining a new path for analysis of EEG signals. Finally, related to the studied EEG signals, we obtain the auto-correlation exponent, αDFA by DFA method, that reveals self-affinity at specific time scale. Our results shows that this strategy can be applied to study the human brain activity in EEG processing.

  9. Exploring the effects of spatial autocorrelation when identifying key drivers of wildlife crop-raiding.

    Science.gov (United States)

    Songhurst, Anna; Coulson, Tim

    2014-03-01

    Few universal trends in spatial patterns of wildlife crop-raiding have been found. Variations in wildlife ecology and movements, and human spatial use have been identified as causes of this apparent unpredictability. However, varying spatial patterns of spatial autocorrelation (SA) in human-wildlife conflict (HWC) data could also contribute. We explicitly explore the effects of SA on wildlife crop-raiding data in order to facilitate the design of future HWC studies. We conducted a comparative survey of raided and nonraided fields to determine key drivers of crop-raiding. Data were subsampled at different spatial scales to select independent raiding data points. The model derived from all data was fitted to subsample data sets. Model parameters from these models were compared to determine the effect of SA. Most methods used to account for SA in data attempt to correct for the change in P-values; yet, by subsampling data at broader spatial scales, we identified changes in regression estimates. We consequently advocate reporting both model parameters across a range of spatial scales to help biological interpretation. Patterns of SA vary spatially in our crop-raiding data. Spatial distribution of fields should therefore be considered when choosing the spatial scale for analyses of HWC studies. Robust key drivers of elephant crop-raiding included raiding history of a field and distance of field to a main elephant pathway. Understanding spatial patterns and determining reliable socio-ecological drivers of wildlife crop-raiding is paramount for designing mitigation and land-use planning strategies to reduce HWC. Spatial patterns of HWC are complex, determined by multiple factors acting at more than one scale; therefore, studies need to be designed with an understanding of the effects of SA. Our methods are accessible to a variety of practitioners to assess the effects of SA, thereby improving the reliability of conservation management actions.

  10. Genetic evolution, plasticity, and bet-hedging as adaptive responses to temporally autocorrelated fluctuating selection: A quantitative genetic model.

    Science.gov (United States)

    Tufto, Jarle

    2015-08-01

    Adaptive responses to autocorrelated environmental fluctuations through evolution in mean reaction norm elevation and slope and an independent component of the phenotypic variance are analyzed using a quantitative genetic model. Analytic approximations expressing the mutual dependencies between all three response modes are derived and solved for the joint evolutionary outcome. Both genetic evolution in reaction norm elevation and plasticity are favored by slow temporal fluctuations, with plasticity, in the absence of microenvironmental variability, being the dominant evolutionary outcome for reasonable parameter values. For fast fluctuations, tracking of the optimal phenotype through genetic evolution and plasticity is limited. If residual fluctuations in the optimal phenotype are large and stabilizing selection is strong, selection then acts to increase the phenotypic variance (bet-hedging adaptive). Otherwise, canalizing selection occurs. If the phenotypic variance increases with plasticity through the effect of microenvironmental variability, this shifts the joint evolutionary balance away from plasticity in favor of genetic evolution. If microenvironmental deviations experienced by each individual at the time of development and selection are correlated, however, more plasticity evolves. The adaptive significance of evolutionary fluctuations in plasticity and the phenotypic variance, transient evolution, and the validity of the analytic approximations are investigated using simulations. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

  11. A method of noise reduction in heterodyne interferometric vibration metrology by combining auto-correlation analysis and spectral filtering

    Science.gov (United States)

    Hao, Hongliang; Xiao, Wen; Chen, Zonghui; Ma, Lan; Pan, Feng

    2018-01-01

    Heterodyne interferometric vibration metrology is a useful technique for dynamic displacement and velocity measurement as it can provide a synchronous full-field output signal. With the advent of cost effective, high-speed real-time signal processing systems and software, processing of the complex signals encountered in interferometry has become more feasible. However, due to the coherent nature of the laser sources, the sequence of heterodyne interferogram are corrupted by a mixture of coherent speckle and incoherent additive noise, which can severely degrade the accuracy of the demodulated signal and the optical display. In this paper, a new heterodyne interferometric demodulation method by combining auto-correlation analysis and spectral filtering is described leading to an expression for the dynamic displacement and velocity of the object under test that is significantly more accurate in both the amplitude and frequency of the vibrating waveform. We present a mathematical model of the signals obtained from interferograms that contain both vibration information of the measured objects and the noise. A simulation of the signal demodulation process is presented and used to investigate the noise from the system and external factors. The experimental results show excellent agreement with measurements from a commercial Laser Doppler Velocimetry (LDV).

  12. Quantifying Temporal Autocorrelations for the Expression of Geobacter species mRNA Gene Transcripts at Variable Ammonium Levels during in situ U(VI) Bioremediation

    Science.gov (United States)

    Mouser, P. J.

    2010-12-01

    In order to develop decision-making tools for the prediction and optimization of subsurface bioremediation strategies, we must be able to link the molecular-scale activity of microorganisms involved in remediation processes with biogeochemical processes observed at the field-scale. This requires the ability to quantify changes in the in situ metabolic condition of dominant microbes and associate these changes to fluctuations in nutrient levels throughout the bioremediation process. It also necessitates a need to understand the spatiotemporal variability of the molecular-scale information to develop meaningful parameters and constraint ranges in complex bio-physio-chemical models. The expression of three Geobacter species genes (ammonium transporter (amtB), nitrogen fixation (nifD), and a housekeeping gene (recA)) were tracked at two monitoring locations that differed significantly in ammonium (NH4+) concentrations during a field-scale experiment where acetate was injected into the subsurface to simulate Geobacteraceae in a uranium-contaminated aquifer. Analysis of amtB and nifD mRNA transcript levels indicated that NH4+ was the primary form of fixed nitrogen during bioremediation. Overall expression levels of amtB were on average 8-fold higher at NH4+ concentrations of 300 μM or more than at lower NH4+ levels (average 60 μM). The degree of temporal correlation in Geobacter species mRNA expression levels was calculated at both locations using autocorrelation methods that describe the relationship between sample semi-variance and time lag. At the monitoring location with lower NH4+, a temporal correlation lag of 8 days was observed for both amtB and nifD transcript patterns. At the location where higher NH4+ levels were observed, no discernable temporal correlation lag above the sampling frequency (approximately every 2 days) was observed for amtB or nifD transcript fluctuations. Autocorrelation trends in recA expression levels at both locations indicated that

  13. A novel auto-correlation function method and FORTRAN codes for the determination of the decay ratio in BWR stability analysis

    International Nuclear Information System (INIS)

    Behringer, K.

    2001-08-01

    A novel auto-correlation function (ACF) method has been investigated for determining the oscillation frequency and the decay ratio in BWR stability analyses. The report describes not only the method but also documents comprehensively the used and developed FORTRAN codes. The neutron signals are band-pass filtered to separate the oscillation peak in the power spectral density (PSD) from background. Two linear second-order oscillation models are considered. The ACF of each model, corrected for signal filtering and with the inclusion of a background term under the peak in the PSD, is then least-squares fitted to the ACF estimated on the previously filtered neutron signals, in order to determine the oscillation frequency and the decay ratio. The procedures of filtering and ACF estimation use fast Fourier transform techniques with signal segmentation. Gliding 'short-time' ACF estimates along a signal record allow the evaluation of uncertainties. Some numerical results are given which have been obtained from neutron signal data offered by the recent Forsmark I and Forsmark II NEA benchmark project. They are compared with those from other benchmark participants using different other analysis methods. (author)

  14. A novel auto-correlation function method and FORTRAN codes for the determination of the decay ratio in BWR stability analysis

    Energy Technology Data Exchange (ETDEWEB)

    Behringer, K

    2001-08-01

    A novel auto-correlation function (ACF) method has been investigated for determining the oscillation frequency and the decay ratio in BWR stability analyses. The report describes not only the method but also documents comprehensively the used and developed FORTRAN codes. The neutron signals are band-pass filtered to separate the oscillation peak in the power spectral density (PSD) from background. Two linear second-order oscillation models are considered. The ACF of each model, corrected for signal filtering and with the inclusion of a background term under the peak in the PSD, is then least-squares fitted to the ACF estimated on the previously filtered neutron signals, in order to determine the oscillation frequency and the decay ratio. The procedures of filtering and ACF estimation use fast Fourier transform techniques with signal segmentation. Gliding 'short-time' ACF estimates along a signal record allow the evaluation of uncertainties. Some numerical results are given which have been obtained from neutron signal data offered by the recent Forsmark I and Forsmark II NEA benchmark project. They are compared with those from other benchmark participants using different other analysis methods. (author)

  15. Accounting for and predicting the influence of spatial autocorrelation in water quality modeling

    Science.gov (United States)

    Miralha, L.; Kim, D.

    2017-12-01

    Although many studies have attempted to investigate the spatial trends of water quality, more attention is yet to be paid to the consequences of considering and ignoring the spatial autocorrelation (SAC) that exists in water quality parameters. Several studies have mentioned the importance of accounting for SAC in water quality modeling, as well as the differences in outcomes between models that account for and ignore SAC. However, the capacity to predict the magnitude of such differences is still ambiguous. In this study, we hypothesized that SAC inherently possessed by a response variable (i.e., water quality parameter) influences the outcomes of spatial modeling. We evaluated whether the level of inherent SAC is associated with changes in R-Squared, Akaike Information Criterion (AIC), and residual SAC (rSAC), after accounting for SAC during modeling procedure. The main objective was to analyze if water quality parameters with higher Moran's I values (inherent SAC measure) undergo a greater increase in R² and a greater reduction in both AIC and rSAC. We compared a non-spatial model (OLS) to two spatial regression approaches (spatial lag and error models). Predictor variables were the principal components of topographic (elevation and slope), land cover, and hydrological soil group variables. We acquired these data from federal online sources (e.g. USGS). Ten watersheds were selected, each in a different state of the USA. Results revealed that water quality parameters with higher inherent SAC showed substantial increase in R² and decrease in rSAC after performing spatial regressions. However, AIC values did not show significant changes. Overall, the higher the level of inherent SAC in water quality variables, the greater improvement of model performance. This indicates a linear and direct relationship between the spatial model outcomes (R² and rSAC) and the degree of SAC in each water quality variable. Therefore, our study suggests that the inherent level of

  16. Rolling element bearing fault diagnosis based on Over-Complete rational dilation wavelet transform and auto-correlation of analytic energy operator

    Science.gov (United States)

    Singh, Jaskaran; Darpe, A. K.; Singh, S. P.

    2018-02-01

    Local damage in rolling element bearings usually generates periodic impulses in vibration signals. The severity, repetition frequency and the fault excited resonance zone by these impulses are the key indicators for diagnosing bearing faults. In this paper, a methodology based on over complete rational dilation wavelet transform (ORDWT) is proposed, as it enjoys a good shift invariance. ORDWT offers flexibility in partitioning the frequency spectrum to generate a number of subbands (filters) with diverse bandwidths. The selection of the optimal filter that perfectly overlaps with the bearing fault excited resonance zone is based on the maximization of a proposed impulse detection measure "Temporal energy operated auto correlated kurtosis". The proposed indicator is robust and consistent in evaluating the impulsiveness of fault signals in presence of interfering vibration such as heavy background noise or sporadic shocks unrelated to the fault or normal operation. The structure of the proposed indicator enables it to be sensitive to fault severity. For enhanced fault classification, an autocorrelation of the energy time series of the signal filtered through the optimal subband is proposed. The application of the proposed methodology is validated on simulated and experimental data. The study shows that the performance of the proposed technique is more robust and consistent in comparison to the original fast kurtogram and wavelet kurtogram.

  17. Poincaré plot analysis of autocorrelation function of RR intervals in patients with acute myocardial infarction.

    Science.gov (United States)

    Chuang, Shin-Shin; Wu, Kung-Tai; Lin, Chen-Yang; Lee, Steven; Chen, Gau-Yang; Kuo, Cheng-Deng

    2014-08-01

    The Poincaré plot of RR intervals (RRI) is obtained by plotting RRIn+1 against RRIn. The Pearson correlation coefficient (ρRRI), slope (SRRI), Y-intercept (YRRI), standard deviation of instantaneous beat-to-beat RRI variability (SD1RR), and standard deviation of continuous long-term RRI variability (SD2RR) can be defined to characterize the plot. Similarly, the Poincaré plot of autocorrelation function (ACF) of RRI can be obtained by plotting ACFk+1 against ACFk. The corresponding Pearson correlation coefficient (ρACF), slope (SACF), Y-intercept (YACF), SD1ACF, and SD2ACF can be defined similarly to characterize the plot. By comparing the indices of Poincaré plots of RRI and ACF between patients with acute myocardial infarction (AMI) and patients with patent coronary artery (PCA), we found that the ρACF and SACF were significantly larger, whereas the RMSSDACF/SDACF and SD1ACF/SD2ACF were significantly smaller in AMI patients. The ρACF and SACF correlated significantly and negatively with normalized high-frequency power (nHFP), and significantly and positively with normalized very low-frequency power (nVLFP) of heart rate variability in both groups of patients. On the contrary, the RMSSDACF/SDACF and SD1ACF/SD2ACF correlated significantly and positively with nHFP, and significantly and negatively with nVLFP and low-/high-frequency power ratio (LHR) in both groups of patients. We concluded that the ρACF, SACF, RMSSDACF/SDACF, and SD1ACF/SD2ACF, among many other indices of ACF Poincaré plot, can be used to differentiate between patients with AMI and patients with PCA, and that the increase in ρACF and SACF and the decrease in RMSSDACF/SDACF and SD1ACF/SD2ACF suggest an increased sympathetic and decreased vagal modulations in both groups of patients.

  18. Computation and analysis of the transverse current autocorrelation function, Ct(k,t), for small wave vectors: A molecular-dynamics study for a Lennard-Jones fluid

    Science.gov (United States)

    Vogelsang, R.; Hoheisel, C.

    1987-02-01

    Molecular-dynamics (MD) calculations are reported for three thermodynamic states of a Lennard-Jones fluid. Systems of 2048 particles and 105 integration steps were used. The transverse current autocorrelation function, Ct(k,t), has been determined for wave vectors of the range 0.5viscosities which showed a systematic behavior as a function of k. Extrapolation to the hydrodynamic region at k=0 gave shear viscosity coefficients in good agreement with direct Green-Kubo results obtained in previous work. The two-exponential model fit for the memory function proposed by other authors does not provide a reasonable description of the MD results, as the fit parameters show no systematic wave-vector dependence, although the Ct(k,t) functions are somewhat better fitted. Similarly, the semiempirical interpolation formula for the decay time based on the viscoelastic concept proposed by Akcasu and Daniels fails to reproduce the correct k dependence for the wavelength range investigated herein.

  19. Application of lag-k autocorrelation coefficient and the TGA signals approach to detecting and quantifying adulterations of extra virgin olive oil with inferior edible oils

    Energy Technology Data Exchange (ETDEWEB)

    Torrecilla, Jose S., E-mail: jstorre@quim.ucm.es [Department of Chemical Engineering, Faculty of Chemistry, University Complutense of Madrid, 28040 Madrid (Spain); Garcia, Julian; Garcia, Silvia; Rodriguez, Francisco [Department of Chemical Engineering, Faculty of Chemistry, University Complutense of Madrid, 28040 Madrid (Spain)

    2011-03-04

    The combination of lag-k autocorrelation coefficients (LCCs) and thermogravimetric analyzer (TGA) equipment is defined here as a tool to detect and quantify adulterations of extra virgin olive oil (EVOO) with refined olive (ROO), refined olive pomace (ROPO), sunflower (SO) or corn (CO) oils, when the adulterating agents concentration are less than 14%. The LCC is calculated from TGA scans of adulterated EVOO samples. Then, the standardized skewness of this coefficient has been applied to classify pure and adulterated samples of EVOO. In addition, this chaotic parameter has also been used to quantify the concentration of adulterant agents, by using successful linear correlation of LCCs and ROO, ROPO, SO or CO in 462 EVOO adulterated samples. In the case of detection, more than 82% of adulterated samples have been correctly classified. In the case of quantification of adulterant concentration, by an external validation process, the LCC/TGA approach estimates the adulterant agents concentration with a mean correlation coefficient (estimated versus real adulterant agent concentration) greater than 0.90 and a mean square error less than 4.9%.

  20. Application of lag-k autocorrelation coefficient and the TGA signals approach to detecting and quantifying adulterations of extra virgin olive oil with inferior edible oils

    International Nuclear Information System (INIS)

    Torrecilla, Jose S.; Garcia, Julian; Garcia, Silvia; Rodriguez, Francisco

    2011-01-01

    The combination of lag-k autocorrelation coefficients (LCCs) and thermogravimetric analyzer (TGA) equipment is defined here as a tool to detect and quantify adulterations of extra virgin olive oil (EVOO) with refined olive (ROO), refined olive pomace (ROPO), sunflower (SO) or corn (CO) oils, when the adulterating agents concentration are less than 14%. The LCC is calculated from TGA scans of adulterated EVOO samples. Then, the standardized skewness of this coefficient has been applied to classify pure and adulterated samples of EVOO. In addition, this chaotic parameter has also been used to quantify the concentration of adulterant agents, by using successful linear correlation of LCCs and ROO, ROPO, SO or CO in 462 EVOO adulterated samples. In the case of detection, more than 82% of adulterated samples have been correctly classified. In the case of quantification of adulterant concentration, by an external validation process, the LCC/TGA approach estimates the adulterant agents concentration with a mean correlation coefficient (estimated versus real adulterant agent concentration) greater than 0.90 and a mean square error less than 4.9%.

  1. Auto-correlation of journal impact factor for consensus research reporting statements: a cohort study.

    Science.gov (United States)

    Shanahan, Daniel R

    2016-01-01

    journal in which a reporting statement was published was shown to influence the number of citations that statement will gather over time. Similarly, the number of article accesses also influenced the number of citations, although to a lesser extent than the impact factor. This demonstrates that citation counts are not purely a reflection of scientific merit and the impact factor is, in fact, auto-correlated.

  2. Auto-correlation of journal impact factor for consensus research reporting statements: a cohort study

    Directory of Open Access Journals (Sweden)

    Daniel R. Shanahan

    2016-03-01

    . The impact factor of the journal in which a reporting statement was published was shown to influence the number of citations that statement will gather over time. Similarly, the number of article accesses also influenced the number of citations, although to a lesser extent than the impact factor. This demonstrates that citation counts are not purely a reflection of scientific merit and the impact factor is, in fact, auto-correlated.

  3. Discussion on sensor location in circular array for spatial autocorrelation method; Kukan jiko sokanho no enkei array ni okeru jishinkei haichi no kento

    Energy Technology Data Exchange (ETDEWEB)

    Yamamoto, H; Iwamoto, K; Saito, T; Yoshida, A [Iwate University, Iwate (Japan). Faculty of Engineering

    1997-05-27

    Methods to derive underground structures by utilizing the dispersion phenomenon of surface waves contained in microtremors include the frequency-wave number analysis method (the F-K method) and the spatial autocorrelation method (SAC method). The SAC method is said capable of estimating the structures to deeper depths than with the F-K method if the same seismometer is used. However, the F-K method is used more frequently. This is because the SAC method imposes a strict restriction that seismometers must be arranged evenly on the same circumference, while the F-K method allows seismometers to be arranged arbitrarily during an observation. Therefore, the present study has discussed whether the SAC method can be applied to observations with the seismometers arranged in the same way as in the F-K method, by using microtremor data acquired from actual observations. It was made clear that a seismometer arrangement for the SAC method may be sufficed with at least three meters arranged on the same circumference. These meters may not have to be arranged evenly, but because the acquired phase velocities may vary according to wave arriving directions and seismometer arrangement, it is desirable to perform observations with seismometers arranged as evenly as possible. 13 figs.

  4. Comparison of the equivalent width, the autocorrelation width, and the variance as figures of merit for XPS narrow scans

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Bhupinder [Department of Chemistry and Biochemistry, C-100 BNSN, Brigham Young University, Provo, UT 84602 (United States); Velázquez, Daniel; Terry, Jeff [Department of Physics, Illinois Institute of Technology, Chicago, IL 60616 (United States); Linford, Matthew R., E-mail: mrlinford@chem.byu.edu [Department of Chemistry and Biochemistry, C-100 BNSN, Brigham Young University, Provo, UT 84602 (United States)

    2014-12-15

    Highlights: • We apply the equivalent and autocorrelation widths and variance to XPS narrow scans. • This approach is complementary to traditional peak fitting methods. • It is bias free and responsive to subtle chemical changes in spectra. • It has the potential for machine interpretation of spectra and quality control. • It has the potential for analysis of complex spectra and tracking charging/artifacts. - Abstract: X-ray photoelectron spectroscopy (XPS) is widely used in surface and materials laboratories around the world. It is a near surface technique, providing detailed chemical information about samples in the form of survey and narrow scans. To extract the maximum amount of information about materials it is often necessary to peak fit XPS narrow scans. And while indispensable to XPS data analysis, even experienced practitioners can struggle with their peak fitting. In our previous publication, we introduced the equivalent width (EW{sub XPS}) as both a possible machine automated method, one that requires less expert judgment for characterizing XPS narrow scans, and as an approach that may be well suited for the analysis of complex spectra. The EW{sub XPS} figure of merit was applied to four different data sets. However, as previously noted, other width functions are also regularly employed for analyzing functions. Here we evaluate two other width functions for XPS narrow scan analysis: the autocorrelation width (AW{sub XPS}) and the variance (σ{sub XPS}{sup 2}). These widths were applied to the same four sets of spectra studied before: (a) four C 1s narrow scans of ozone-treated carbon nanotubes (CNTs) (EW{sub XPS}: ∼2.11–2.16 eV, AW{sub XPS}: ∼3.9–4.1 eV, σ{sub XPS}{sup 2}: ∼5.0–5.2 eV, and a modified form of σ{sub XPS}{sup 2}, denoted σ{sub XPS}{sup 2*}: ∼6.3–6.8 eV), (b) silicon wafers with different oxide thicknesses (EW{sub XPS}: ∼1.5–2.9 eV, AW{sub XPS}: ∼2.28–4.9, and σ{sub XPS}{sup 2}: ∼0.7–4.9 eV), (iii

  5. Mono-static GPR without transmitting anything for pavement damage inspection: interferometry by auto-correlation applied to mobile phone signals

    Science.gov (United States)

    Feld, R.; Slob, E. C.; Thorbecke, J.

    2015-12-01

    Creating virtual sources at locations where physical receivers have measured a response is known as seismic interferometry. A much appreciated benefit of interferometry is its independence of the actual source locations. The use of ambient noise as actual source is therefore not uncommon in this field. Ambient noise can be commercial noise, like for example mobile phone signals. For GPR this can be useful in cases where it is not possible to place a source, for instance when it is prohibited by laws and regulations. A mono-static GPR antenna can measure ambient noise. Interferometry by auto-correlation (AC) places a virtual source on this antenna's position, without actually transmitting anything. This can be used for pavement damage inspection. Earlier work showed very promising results with 2D numerical models of damaged pavement. 1D and 2D heterogeneities were compared, both modelled in a 2D pavement world. In a 1D heterogeneous model energy leaks away to the sides, whereas in a 2D heterogeneous model rays can reflect and therefore still add to the signal reconstruction (see illustration). In the first case the amount of stationary points is strictly limited, while in the other case the amount of stationary points is very large. We extend these models to a 3D world and optimise an experimental configuration. The illustration originates from the journal article under submission 'Non-destructive pavement damage inspection by mono-static GPR without transmitting anything' by R. Feld, E.C. Slob, and J.W. Thorbecke. (a) 2D heterogeneous pavement model with three irregular-shaped misalignments between the base and subbase layer (marked by arrows). Mono-antenna B-scan positions are shown schematically. (b) Ideal output: a real source at the receiver's position. The difference w.r.t. the trace found in the middle is shown. (c) AC output: a virtual source at the receiver's position. There is a clear overlap with the ideal output.

  6. Exploration of underground basement structures in Kanto plain using the spatial autocorrelation method. 1. S-wave velocity structure along the line from Hatoyama, Saitama to Noda, Chiba; Kukan jiko sokanho ni yoru Kanto heiya no kiban kozo tansa. 1. Saitamaken Hatoyama machi - Chibaken Nodashi kan no S ha sokudo kozo

    Energy Technology Data Exchange (ETDEWEB)

    Matsuoka, T; Umezawa, N; Shiraishi, H [Saitama Institute of Environmental Pollution, Saitama (Japan)

    1997-05-27

    The Saitama prefectural government has been conducting basement structure exploration using the spatial autocorrelation method by dividing the entire plain area into meshes, for the purpose of improving the accuracy of estimating large-scale seismic damages. This paper reports the result of explorations on meshes in the east-west direction in the central part of Saitama Prefecture. The present exploration was intended on ten meshes in the east-west direction along the north latitude 36-degree line. The number of exploration points is 13 comprising three points on the hilly area bordering on the eastern edge of the Kanto mountainous area and ten points on the plain area. The arrangement constitutes a traverse line with a total distance of about 33 km from the west edge (Hatoyama-machi in Saitama Prefecture) to the east edge (Noda City in Chiba Prefecture). The phase velocities were estimated from the result of the array microtremor observations using the spatial autocorrelation method applied with the FET. The phase velocities were used to estimate underground structures by using an inverse analysis. As a result, detailed two-dimensional S-wave velocity structures were revealed on the traverse line. The velocity cross section expresses change in the basement structures with sufficient resolution, and at the same time the information is judged highly harmonious with existing deep boring data and the result of artificial earthquake exploration. 15 refs., 6 figs.

  7. Molecular dynamics test of the Brownian description of Na+ motion in water

    International Nuclear Information System (INIS)

    Wilson, M.A.; Pohorille, A.; Pratt, L.R.

    1985-01-01

    The autocorrelation function of the velocity of an infinitely dilute Na + ion in aqueous solution, and the autocorrelation function of the force exerted on a stationary Na + under the same conditions are evaluated by molecular dynamics calculations. The results are used to test the accuracy of Brownian motion assumptions which are basic to hydrodynamic models of ion dynamics in solution. The self-diffusion coefficient of the Na + ion predicted by Brownian motion theory is (0.65 +- 0.1) x 10 -5 cm 2 /s. This value is about 60% greater than the one obtained for the proper dynamics of the finite mass ion, (0.4 +- 0.1) x 10 -5 cm 2 /s. The numerically correct velocity autocorrelation function is nonexponential, and the autocorrelation of the force on the stationary ion does not decay faster than the ion velocity autocorrelation function. Motivated by previous hydrodynamic modeling of friction kernels, we examine the approximation in which the memory function for the velocity autocorrelation function is identified with the autocorrelation function of the force on the stationary ion. The overall agreement between this approximation for the velocity autocorrelation function and the numerically correct answer is quite good

  8. Application of the Spatial Auto-Correlation Method for Shear-Wave Velocity Studies Using Ambient Noise

    Science.gov (United States)

    Asten, M. W.; Hayashi, K.

    2018-05-01

    Ambient seismic noise or microtremor observations used in spatial auto-correlation (SPAC) array methods consist of a wide frequency range of surface waves from the frequency of about 0.1 Hz to several tens of Hz. The wavelengths (and hence depth sensitivity of such surface waves) allow determination of the site S-wave velocity model from a depth of 1 or 2 m down to a maximum of several kilometres; it is a passive seismic method using only ambient noise as the energy source. Application usually uses a 2D seismic array with a small number of seismometers (generally between 2 and 15) to estimate the phase velocity dispersion curve and hence the S-wave velocity depth profile for the site. A large number of methods have been proposed and used to estimate the dispersion curve; SPAC is the one of the oldest and the most commonly used methods due to its versatility and minimal instrumentation requirements. We show that direct fitting of observed and model SPAC spectra generally gives a superior bandwidth of useable data than does the more common approach of inversion after the intermediate step of constructing an observed dispersion curve. Current case histories demonstrate the method with a range of array types including two-station arrays, L-shaped multi-station arrays, triangular and circular arrays. Array sizes from a few metres to several-km in diameter have been successfully deployed in sites ranging from downtown urban settings to rural and remote desert sites. A fundamental requirement of the method is the ability to average wave propagation over a range of azimuths; this can be achieved with either or both of the wave sources being widely distributed in azimuth, and the use of a 2D array sampling the wave field over a range of azimuths. Several variants of the method extend its applicability to under-sampled data from sparse arrays, the complexity of multiple-mode propagation of energy, and the problem of precise estimation where array geometry departs from an

  9. Spatial Autocorrelation, Source Water and the Distribution of Total and Viable Microbial Abundances within a Crystalline Formation to a Depth of 800 m

    Directory of Open Access Journals (Sweden)

    E. D. Beaton

    2017-09-01

    Full Text Available Proposed radioactive waste repositories require long residence times within deep geological settings for which we have little knowledge of local or regional subsurface dynamics that could affect the transport of hazardous species over the period of radioactive decay. Given the role of microbial processes on element speciation and transport, knowledge and understanding of local microbial ecology within geological formations being considered as host formations can aid predictions for long term safety. In this relatively unexplored environment, sampling opportunities are few and opportunistic. We combined the data collected for geochemistry and microbial abundances from multiple sampling opportunities from within a proposed host formation and performed multivariate mixing and mass balance (M3 modeling, spatial analysis and generalized linear modeling to address whether recharge can explain how subsurface communities assemble within fracture water obtained from multiple saturated fractures accessed by boreholes drilled into the crystalline formation underlying the Chalk River Laboratories site (Deep River, ON, Canada. We found that three possible source waters, each of meteoric origin, explained 97% of the samples, these are: modern recharge, recharge from the period of the Laurentide ice sheet retreat (ca. ∼12000 years before present and a putative saline source assigned as Champlain Sea (also ca. 12000 years before present. The distributed microbial abundances and geochemistry provide a conceptual model of two distinct regions within the subsurface associated with bicarbonate – used as a proxy for modern recharge – and manganese; these regions occur at depths relevant to a proposed repository within the formation. At the scale of sampling, the associated spatial autocorrelation means that abundances linked with geochemistry were not unambiguously discerned, although fine scale Moran’s eigenvector map (MEM coefficients were correlated with

  10. Hydrodynamic description of the long-time tails of the linear and rotational velocity autocorrelation functions of a particle in a confined geometry.

    Science.gov (United States)

    Frydel, Derek; Rice, Stuart A

    2007-12-01

    We report a hydrodynamic analysis of the long-time behavior of the linear and angular velocity autocorrelation functions of an isolated colloid particle constrained to have quasi-two-dimensional motion, and compare the predicted behavior with the results of lattice-Boltzmann simulations. Our analysis uses the singularity method to characterize unsteady linear motion of an incompressible fluid. For bounded fluids we construct an image system with a discrete set of fundamental solutions of the Stokes equation from which we extract the long-time decay of the velocity. For the case that there are free slip boundary conditions at walls separated by H particle diameters, the time evolution of the parallel linear velocity and the perpendicular rotational velocity following impulsive excitation both correspond to the time evolution of a two-dimensional (2D) fluid with effective density rho_(2D)=rhoH. For the case that there are no slip boundary conditions at the walls, the same types of motion correspond to 2D fluid motions with a coefficient of friction xi=pi(2)nu/H(2) modulo a prefactor of order 1, with nu the kinematic viscosity. The linear particle motion perpendicular to the walls also experiences an effective frictional force, but the time dependence is proportional to t(-2) , which cannot be related to either pure 3D or pure 2D fluid motion. Our incompressible fluid model predicts correct self-diffusion constants but it does not capture all of the effects of the fluid confinement on the particle motion. In particular, the linear motion of a particle perpendicular to the walls is influenced by coupling between the density flux and the velocity field, which leads to damped velocity oscillations whose frequency is proportional to c_(s)/H , with c_(s) the velocity of sound. For particle motion parallel to no slip walls there is a slowing down of a density flux that spreads diffusively, which generates a long-time decay proportional to t(-1) .

  11. Time-Frequency Based Instantaneous Frequency Estimation of Sparse Signals from an Incomplete Set of Samples

    Science.gov (United States)

    2014-06-17

    100 0 2 4 Wigner distribution 0 50 100 0 0.5 1 Auto-correlation function 0 50 100 0 2 4 L- Wigner distribution 0 50 100 0 0.5 1 Auto-correlation function ...bilinear or higher order autocorrelation functions will increase the number of missing samples, the analysis shows that accurate instantaneous...frequency estimation can be achieved even if we deal with only few samples, as long as the auto-correlation function is properly chosen to coincide with

  12. Spatio-temporal Variability in Surface Ocean pCO2 Inferred from Observations

    OpenAIRE

    Jones, Steve

    2012-01-01

    The variability of surface ocean pCO2 is examined on multiple spatial and temporal scales. Temporal autocorrelation analysis is used to examine pCO2 variability over multiple years. Spatial autocorrelation analysis describes pCO2 variability over multiple spatial scales. Spatial autocorrelation lengths range between

  13. Is a larger equity market more information efficient? Evidence from intervalling effect

    Directory of Open Access Journals (Sweden)

    KiHoon Hong

    2016-07-01

    Full Text Available This paper investigates the impact of equity return autocorrelation on financial market efficiency via intervalling effect. A simple model is proposed to show that the degree of intervalling effect is related to the security return autocorrelation. A more general version of Levy and Levhari hypothesis is proposed to find that the degree of the autocorrelations of the security and the market returns determines the existence and the direction of the intervalling effect and the size of the intervalling effect are dependent on the degree of the security autocorrelations. Empirical evidence of the latter is presented

  14. Lack of negative autocorrelations of daily food intake on successive days challenges the concept of the regulation of body weight in humans.

    Science.gov (United States)

    Levitsky, David A; Raea Limb, Ji Eun; Wilkinson, Lua; Sewall, Anna; Zhong, Yingyi; Olabi, Ammar; Hunter, Jean

    2017-09-01

    According to most theories, the amount of food consumed on one day should be negatively related to intake on subsequent days. Several studies have observed such a negative correlation between the amount consumed on one day and the amount consumed two to four days later. The present study attempted to replicate this observation by re-examining data from a previous study where all food ingested over a 30-day observation period was measured. Nine male and seven female participants received a vegan diet prepared, dispensed, and measured in a metabolic unit. Autocorrelations were performed on total food intake consume on one day and that consumed one to five days later. A significant positive correlation was detected between the weight of food eaten on one day and on the amount consumed on the following day (r = 0.29, 95% CI [0.37, 0.20]). No correlation was found between weights of food consumed on one day and up to twelve days later (r = 0.09, 95% CI [0.24, -0.06]), (r = 0.11, 95% CI [0.26, -0.0.26]) (r = 0.02, 95% CI [0.15, -0.7]) (r = -0.08, 95% CI [0.11, -0.09]). The same positive correlation with the previous day's intake was observed at the succeeding breakfast but not at either lunch or dinner. However, the participants underestimated their daily energy need resulting in a small, but statistically significant weight loss. Daily food intake increased slightly (13 g/day), but significantly, across the 30-day period. An analysis of the previous studies revealed that the negative correlations observed by others was caused by a statistical artifact resulting from normalizing data before testing for the correlations. These results, when combined with the published literature, indicate that there is little evidence that humans precisely compensate for the previous day's intake by altering the amount consumed on subsequent days. Moreover, the small but persistent increase in food intake suggests that physiological mechanisms that affect food intake

  15. Longitudinal and bulk viscosities of Lennard-Jones fluids

    Science.gov (United States)

    Tankeshwar, K.; Pathak, K. N.; Ranganathan, S.

    1996-12-01

    Expressions for the longitudinal and bulk viscosities have been derived using Green Kubo formulae involving the time integral of the longitudinal and bulk stress autocorrelation functions. The time evolution of stress autocorrelation functions are determined using the Mori formalism and a memory function which is obtained from the Mori equation of motion. The memory function is of hyperbolic secant form and involves two parameters which are related to the microscopic sum rules of the respective autocorrelation function. We have derived expressions for the zeroth-, second-and fourth- order sum rules of the longitudinal and bulk stress autocorrelation functions. These involve static correlation functions up to four particles. The final expressions for these have been put in a form suitable for numerical calculations using low- order decoupling approximations. The numerical results have been obtained for the sum rules of longitudinal and bulk stress autocorrelation functions. These have been used to calculate the longitudinal and bulk viscosities and time evolution of the longitudinal stress autocorrelation function of the Lennard-Jones fluids over wide ranges of densities and temperatures. We have compared our results with the available computer simulation data and found reasonable agreement.

  16. Blind CP-OFDM and ZP-OFDM Parameter Estimation in Frequency Selective Channels

    Directory of Open Access Journals (Sweden)

    Vincent Le Nir

    2009-01-01

    Full Text Available A cognitive radio system needs accurate knowledge of the radio spectrum it operates in. Blind modulation recognition techniques have been proposed to discriminate between single-carrier and multicarrier modulations and to estimate their parameters. Some powerful techniques use autocorrelation- and cyclic autocorrelation-based features of the transmitted signal applying to OFDM signals using a Cyclic Prefix time guard interval (CP-OFDM. In this paper, we propose a blind parameter estimation technique based on a power autocorrelation feature applying to OFDM signals using a Zero Padding time guard interval (ZP-OFDM which in particular excludes the use of the autocorrelation- and cyclic autocorrelation-based techniques. The proposed technique leads to an efficient estimation of the symbol duration and zero padding duration in frequency selective channels, and is insensitive to receiver phase and frequency offsets. Simulation results are given for WiMAX and WiMedia signals using realistic Stanford University Interim (SUI and Ultra-Wideband (UWB IEEE 802.15.4a channel models, respectively.

  17. Mixed Portmanteau Test for Diagnostic Checking of Time Series Models

    Directory of Open Access Journals (Sweden)

    Sohail Chand

    2014-01-01

    Full Text Available Model criticism is an important stage of model building and thus goodness of fit tests provides a set of tools for diagnostic checking of the fitted model. Several tests are suggested in literature for diagnostic checking. These tests use autocorrelation or partial autocorrelation in the residuals to criticize the adequacy of fitted model. The main idea underlying these portmanteau tests is to identify if there is any dependence structure which is yet unexplained by the fitted model. In this paper, we suggest mixed portmanteau tests based on autocorrelation and partial autocorrelation functions of the residuals. We derived the asymptotic distribution of the mixture test and studied its size and power using Monte Carlo simulations.

  18. On-site processing systems for determination of the phase velocity of Rayleigh waves in microtremors using the spatial autocorrelation method; Kukan jiko sokanho wo mochiita bidochu no Rayleigh ha iso sokudo no genba kettei system

    Energy Technology Data Exchange (ETDEWEB)

    Matsuoka, T; Umezawa, N [Saitama Institute of Environmental Pollution, Saitama (Japan)

    1996-05-01

    To render the spatial autocorrelation (SAC) method easier to use, a system has been constructed that can be used with ease on the site for the calculation of phase velocities. This system can perform two observation methods of the same frequency characteristics, that is, the simultaneous multi-point observation and one-point independent observation. The pickup is a velocity type seismograph of a natural period of 1 second that has been so electrically adjusted as to work on an apparent natural period of 7 seconds. Among the frequency characteristics, those related to phase are regarded as important because the SAC method is based on the measurement of coherence between two points. The analysis software runs on a waveform processing software DADiSP/WIN designed for personal computers. To know the operability of this system on the site and to accumulate records using the SAC method, observations were made at the depth of 100-500m at 6 locations in Saitama Prefecture where the underground structure was known thanks to prior PS logging. As the result, a dispersion curve was obtained by use of an array of appropriate dimensions at every location agreeing with the underground structure. 9 refs., 10 figs.

  19. vector bilinear autoregressive time series model and its superiority

    African Journals Online (AJOL)

    KEYWORDS: Linear time series, Autoregressive process, Autocorrelation function, Partial autocorrelation function,. Vector time .... important result on matrix algebra with respect to the spectral ..... application to covariance analysis of super-.

  20. The use of spatio-temporal correlation to forecast critical transitions

    Science.gov (United States)

    Karssenberg, Derek; Bierkens, Marc F. P.

    2010-05-01

    Complex dynamical systems may have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been observed in systems ranging from the human body system to financial markets and the Earth system. Forecasting the timing of critical transitions before they are reached is of paramount importance because critical transitions are associated with a large shift in dynamical regime of the system under consideration. However, it is hard to forecast critical transitions, because the state of the system shows relatively little change before the threshold is reached. Recently, it was shown that increased spatio-temporal autocorrelation and variance can serve as alternative early warning signal for critical transitions. However, thus far these second order statistics have not been used for forecasting in a data assimilation framework. Here we show that the use of spatio-temporal autocorrelation and variance in the state of the system reduces the uncertainty in the predicted timing of critical transitions compared to classical approaches that use the value of the system state only. This is shown by assimilating observed spatio-temporal autocorrelation and variance into a dynamical system model using a Particle Filter. We adapt a well-studied distributed model of a logistically growing resource with a fixed grazing rate. The model describes the transition from an underexploited system with high resource biomass to overexploitation as grazing pressure crosses the critical threshold, which is a fold bifurcation. To represent limited prior information, we use a large variance in the prior probability distributions of model parameters and the system driver (grazing rate). First, we show that the rate of increase in spatio-temporal autocorrelation and variance prior to reaching the critical threshold is relatively consistent across the uncertainty range of the driver and parameter values used. This indicates that an increase in

  1. Autocorrelations in hybrid Monte Carlo simulations

    International Nuclear Information System (INIS)

    Schaefer, Stefan; Virotta, Francesco

    2010-11-01

    Simulations of QCD suffer from severe critical slowing down towards the continuum limit. This problem is known to be prominent in the topological charge, however, all observables are affected to various degree by these slow modes in the Monte Carlo evolution. We investigate the slowing down in high statistics simulations and propose a new error analysis method, which gives a realistic estimate of the contribution of the slow modes to the errors. (orig.)

  2. Time dependent auto-correlation, autospectrum and decay ratio estimation of transient signals in JET soft X-ray records

    International Nuclear Information System (INIS)

    Por, G.

    1999-08-01

    A program package was developed to estimate the time dependent auto-correlation function (ACF) from the time signals of soft X-ray records taken along the various lines-of-sights in JET-SHOTS, and also to estimate the time dependent Decay Ratio (DR) from that. On the basis of ACF the time dependent auto-power spectral density (APSD) was also calculated. The steps and objectives of this work were: eliminating the white detection noise, trends and slow variation from the time signals, since ordinary methods can give good estimate of the time dependent ACF and DR only for 'nearly' stationary signals, developing an automatic algorithm for finding the maxima and minima of ACF, since they are the basis for DR estimation, evaluating and testing different DR estimators for JET-SHOT, with the aim of finding parts of the signals, where the oscillating character is strong, estimating time dependent ACF and APSD that can follow the relatively fast variation in the time signal. The methods that we have developed for data processing of transient signals are: White detection noise removal and preparation for trend removal - weak components, white detection noise and high frequency components are filtered from the signal using the so-called soft-threshold wavelet filter. Removal of trends and slow variation - Three-point differentiation of the pre-filtered signal is used to remove trends and slow variation. Here we made use of the DERIV function of IDL program language. This leads to a filtered signal that has zero mean value in each time step. Calculation of the time dependent ACF - The signal treated by the two previous steps is used as the input. Calculated ACF value is added in each new time step, but the previously accumulated ACF value is multiplied by a weighting factor. Thus the new sample has 100% contribution, while the contributions from the previous samples are forgotten quickly. DR calculation - DR is a measure of the decay of oscillating ACF. This parameter was shown

  3. Non-Gaussian wave packet dynamics in anharmonic potential: Cumulant expansion treatment

    International Nuclear Information System (INIS)

    Toutounji, Mohamad

    2015-01-01

    This manuscript utilizes cumulant expansion as an alternative algebraic approach to evaluating integrals and solving a system of nonlinear differential equations for probing anharmonic dynamics in condensed phase systems using Morse oscillator. These integrals and differential equations become harder to solve as the anharmonicity of the system goes beyond that of Morse oscillator description. This algebraic approach becomes critically important in case of Morse oscillator as it tends to exhibit divergent dynamics and numerical uncertainties at low temperatures. The autocorrelation function is calculated algebraically and compared to the exact one for they match perfectly. It is also compared to the approximate autocorrelation function using the differential equations technique reported in Toutounji (2014) for weak and strong electron–phonon coupling cases. It is found that the present cumulant method is more efficient, and easier to use, than the exact expression. Deviation between the approximate autocorrelation function and the exact autocorrelation function starts to arise as the electron–phonon coupling strength increases. The autocorrelation function obtained using cumulants identically matches the exact autocorrelation function, thereby surpassing the approach presented in Toutounji (2014). The advantage of the present methodology is its applicability to various types of electron–phonon coupling cases. Additionally, the herein approach only uses algebraic techniques, thereby avoiding both the divergence integral and solving a set of linear first- and second-order partial differential equations as was done in previous work. Model calculations are presented to demonstrate the accuracy of the herein work

  4. Decorrelation scales for Arctic Ocean hydrography - Part I: Amerasian Basin

    Science.gov (United States)

    Sumata, Hiroshi; Kauker, Frank; Karcher, Michael; Rabe, Benjamin; Timmermans, Mary-Louise; Behrendt, Axel; Gerdes, Rüdiger; Schauer, Ursula; Shimada, Koji; Cho, Kyoung-Ho; Kikuchi, Takashi

    2018-03-01

    Any use of observational data for data assimilation requires adequate information of their representativeness in space and time. This is particularly important for sparse, non-synoptic data, which comprise the bulk of oceanic in situ observations in the Arctic. To quantify spatial and temporal scales of temperature and salinity variations, we estimate the autocorrelation function and associated decorrelation scales for the Amerasian Basin of the Arctic Ocean. For this purpose, we compile historical measurements from 1980 to 2015. Assuming spatial and temporal homogeneity of the decorrelation scale in the basin interior (abyssal plain area), we calculate autocorrelations as a function of spatial distance and temporal lag. The examination of the functional form of autocorrelation in each depth range reveals that the autocorrelation is well described by a Gaussian function in space and time. We derive decorrelation scales of 150-200 km in space and 100-300 days in time. These scales are directly applicable to quantify the representation error, which is essential for use of ocean in situ measurements in data assimilation. We also describe how the estimated autocorrelation function and decorrelation scale should be applied for cost function calculation in a data assimilation system.

  5. DCS TERRAIN SUBMISSION for ONEIDA COUNTY, NEW York, USA

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — For Oneida County, NY, there were two types of elevation datasets. The first type is LiDAR and the second one is Auto-correlation DEM. Auto-correlation DEM data was...

  6. 2008 FEMA Lidar: South Oneida County (NY)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — For Oneida County, NY, there were two types of elevation datasets. The first type is LiDAR and the second one is Auto-correlation DEM. Auto-correlation DEM data was...

  7. A Delay Filter for an ir-UWB Front-End

    NARCIS (Netherlands)

    Bagga, S.; Haddad, S.A.P.; Serdijn, W.A.; Lang, J.R.; Busking, E.B.

    2005-01-01

    A continuous-time analog delay is designed as a requirement for the autocorrelation function in the quadrature downconversion autocorrelation receiver (QDAR). An eight-order Fade approximation of its transfer function is selected to implement this delay. Subsequently, the orthonormal form is

  8. Method and apparatus for in-situ characterization of energy storage and energy conversion devices

    Science.gov (United States)

    Christophersen, Jon P [Idaho Falls, ID; Motloch, Chester G [Idaho Falls, ID; Morrison, John L [Butte, MT; Albrecht, Weston [Layton, UT

    2010-03-09

    Disclosed are methods and apparatuses for determining an impedance of an energy-output device using a random noise stimulus applied to the energy-output device. A random noise signal is generated and converted to a random noise stimulus as a current source correlated to the random noise signal. A bias-reduced response of the energy-output device to the random noise stimulus is generated by comparing a voltage at the energy-output device terminal to an average voltage signal. The random noise stimulus and bias-reduced response may be periodically sampled to generate a time-varying current stimulus and a time-varying voltage response, which may be correlated to generate an autocorrelated stimulus, an autocorrelated response, and a cross-correlated response. Finally, the autocorrelated stimulus, the autocorrelated response, and the cross-correlated response may be combined to determine at least one of impedance amplitude, impedance phase, and complex impedance.

  9. Concentration dependence of the wings of a dipole-broadened magnetic resonance line in magnetically diluted lattices

    Energy Technology Data Exchange (ETDEWEB)

    Zobov, V. E., E-mail: rsa@iph.krasn.ru [Russian Academy of Sciences, Kirenskii Institute of Physics, Siberian Branch (Russian Federation); Kucherov, M. M. [Siberian Federal University, Institute of Space and Information Technologies (Russian Federation)

    2017-01-15

    The singularities of the time autocorrelation functions (ACFs) of magnetically diluted spin systems with dipole–dipole interaction (DDI), which determine the high-frequency asymptotics of autocorrelation functions and the wings of a magnetic resonance line, are studied. Using the self-consistent fluctuating local field approximation, nonlinear equations are derived for autocorrelation functions averaged over the independent random arrangement of spins (magnetic atoms) in a diamagnetic lattice with different spin concentrations. The equations take into account the specificity of the dipole–dipole interaction. First, due to its axial symmetry in a strong static magnetic field, the autocorrelation functions of longitudinal and transverse spin components are described by different equations. Second, the long-range type of the dipole–dipole interaction is taken into account by separating contributions into the local field from distant and near spins. The recurrent equations are obtained for the expansion coefficients of autocorrelation functions in power series in time. From them, the numerical value of the coordinate of the nearest singularity of the autocorrelation function is found on the imaginary time axis, which is equal to the radius of convergence of these expansions. It is shown that in the strong dilution case, the logarithmic concentration dependence of the coordinate of the singularity is observed, which is caused by the presence of a cluster of near spins whose fraction is small but contribution to the modulation frequency is large. As an example a silicon crystal with different {sup 29}Si concentrations in magnetic fields directed along three crystallographic axes is considered.

  10. Spatial variability of microbial richness and diversity and relationships with soil organic carbon, texture and structure across an agricultural field

    DEFF Research Database (Denmark)

    Naveed, Muhammad; Herath, Lasantha; Møldrup, Per

    2016-01-01

    Highlights •Bacterial richness and Shannon diversity showed strong spatial autocorrelations. •Fungal richness and Shannon diversity did not show any clear spatial autocorrelations. •Ratio of clay to organic carbon was found a best predictor of bacterial richness and diversities. •Soil water...

  11. A technique to detect periodic and non-periodic ultra-rapid flux time variations with standard radio-astronomical data

    Science.gov (United States)

    Borra, Ermanno F.; Romney, Jonathan D.; Trottier, Eric

    2018-06-01

    We demonstrate that extremely rapid and weak periodic and non-periodic signals can easily be detected by using the autocorrelation of intensity as a function of time. We use standard radio-astronomical observations that have artificial periodic and non-periodic signals generated by the electronics of terrestrial origin. The autocorrelation detects weak signals that have small amplitudes because it averages over long integration times. Another advantage is that it allows a direct visualization of the shape of the signals, while it is difficult to see the shape with a Fourier transform. Although Fourier transforms can also detect periodic signals, a novelty of this work is that we demonstrate another major advantage of the autocorrelation, that it can detect non-periodic signals while the Fourier transform cannot. Another major novelty of our work is that we use electric fields taken in a standard format with standard instrumentation at a radio observatory and therefore no specialized instrumentation is needed. Because the electric fields are sampled every 15.625 ns, they therefore allow detection of very rapid time variations. Notwithstanding the long integration times, the autocorrelation detects very rapid intensity variations as a function of time. The autocorrelation could also detect messages from Extraterrestrial Intelligence as non-periodic signals.

  12. Simulation of diffusion in a two-dimensional lattice gas cellular automaton: a test of mode-coupling theory

    NARCIS (Netherlands)

    Frenkel, D.; Ernst, M.H.

    1989-01-01

    We compute the velocity autocorrelation function of a tagged particle in a two-dimensional lattice-gas cellular automaton using a method that is about a million times more efficient than existing techniques. A t-1 algebraic tail in the tagged-particle velocity autocorrelation function is clearly

  13. Analytical solution of Mori's equation with secant hyperbolic memory

    International Nuclear Information System (INIS)

    Tankeshwar, K.; Pathak, K.N.

    1993-07-01

    The equation of motion of the auto-correlation function has been solved analytically using a secant-hyperbolic form of the memory function. The analytical results obtained for the long time expansion together with the short time expansion provide a good description over the whole time domain as judged by their comparison with the numerical solution of Mori's equation of motion. We also find that the time evolution of the auto-correlation function is determined by a single parameter τ which is related to the frequency sum rules up to the fourth order. The auto-correlation function has been found to show simple decaying or oscillatory behaviour depending on whether the parameter τ is greater than or less than some critical values. Similarities as well as differences in time evolution of the auto-correlation have been discussed for exponential, secant-hyperbolic and Gaussian approaches of the memory function. (author). 16 refs, 5 figs

  14. Superaging and Subaging Phenomena in a Nonequilibrium Critical Behavior of the Structurally Disordered Two-Dimensional XY Model

    Science.gov (United States)

    Prudnikov, V. V.; Prudnikov, P. V.; Popov, I. S.

    2018-03-01

    A Monte Carlo numerical simulation of the specific features of nonequilibrium critical behavior is carried out for the two-dimensional structurally disordered XY model during its evolution from a low-temperature initial state. On the basis of the analysis of the two-time dependence of autocorrelation functions and dynamic susceptibility for systems with spin concentrations of p = 1.0, 0.9, and 0.6, aging phenomena characterized by a slowing down of the relaxation system with increasing waiting time and the violation of the fluctuation-dissipation theorem (FDT) are revealed. The values of the universal limiting fluctuation-dissipation ratio (FDR) are obtained for the systems considered. As a result of the analysis of the two-time scaling dependence for spin-spin and connected spin autocorrelation functions, it is found that structural defects lead to subaging phenomena in the behavior of the spin-spin autocorrelation function and superaging phenomena in the behavior of the connected spin autocorrelation function.

  15. The Latent Curve ARMA (P, Q) Panel Model: Longitudinal Data Analysis in Educational Research and Evaluation

    Science.gov (United States)

    Sivo, Stephen; Fan, Xitao

    2008-01-01

    Autocorrelated residuals in longitudinal data are widely reported as common to longitudinal data. Yet few, if any, researchers modeling growth processes evaluate a priori whether their data have this feature. Sivo, Fan, and Witta (2005) found that not modeling autocorrelated residuals present in longitudinal data severely biases latent curve…

  16. Orthogonal transformations for change detection, Matlab code

    DEFF Research Database (Denmark)

    2005-01-01

    Matlab code to do multivariate alteration detection (MAD) analysis, maximum autocorrelation factor (MAF) analysis, canonical correlation analysis (CCA) and principal component analysis (PCA) on image data.......Matlab code to do multivariate alteration detection (MAD) analysis, maximum autocorrelation factor (MAF) analysis, canonical correlation analysis (CCA) and principal component analysis (PCA) on image data....

  17. Vector bilinear autoregressive time series model and its superiority ...

    African Journals Online (AJOL)

    In this research, a vector bilinear autoregressive time series model was proposed and used to model three revenue series (X1, X2, X3) . The “orders” of the three series were identified on the basis of the distribution of autocorrelation and partial autocorrelation functions and were used to construct the vector bilinear models.

  18. A general statistical test for correlations in a finite-length time series.

    Science.gov (United States)

    Hanson, Jeffery A; Yang, Haw

    2008-06-07

    The statistical properties of the autocorrelation function from a time series composed of independently and identically distributed stochastic variables has been studied. Analytical expressions for the autocorrelation function's variance have been derived. It has been found that two common ways of calculating the autocorrelation, moving-average and Fourier transform, exhibit different uncertainty characteristics. For periodic time series, the Fourier transform method is preferred because it gives smaller uncertainties that are uniform through all time lags. Based on these analytical results, a statistically robust method has been proposed to test the existence of correlations in a time series. The statistical test is verified by computer simulations and an application to single-molecule fluorescence spectroscopy is discussed.

  19. Investment Dynamics with Natural Expectations.

    Science.gov (United States)

    Fuster, Andreas; Hebert, Benjamin; Laibson, David

    2010-01-01

    We study an investment model in which agents have the wrong beliefs about the dynamic properties of fundamentals. Specifically, we assume that agents underestimate the rate of mean reversion. The model exhibits the following six properties: (i) Beliefs are excessively optimistic in good times and excessively pessimistic in bad times. (ii) Asset prices are too volatile. (iii) Excess returns are negatively autocorrelated. (iv) High levels of corporate profits predict negative future excess returns. (v) Real economic activity is excessively volatile; the economy experiences amplified investment cycles. (vi) Corporate profits are positively autocorrelated in the short run and negatively autocorrelated in the medium run. The paper provides an illustrative model of animal spirits, amplified business cycles, and excess volatility.

  20. Spatial occupancy models applied to atlas data show Southern Ground Hornbills strongly depend on protected areas.

    Science.gov (United States)

    Broms, Kristin M; Johnson, Devin S; Altwegg, Res; Conquest, Loveday L

    2014-03-01

    Determining the range of a species and exploring species--habitat associations are central questions in ecology and can be answered by analyzing presence--absence data. Often, both the sampling of sites and the desired area of inference involve neighboring sites; thus, positive spatial autocorrelation between these sites is expected. Using survey data for the Southern Ground Hornbill (Bucorvus leadbeateri) from the Southern African Bird Atlas Project, we compared advantages and disadvantages of three increasingly complex models for species occupancy: an occupancy model that accounted for nondetection but assumed all sites were independent, and two spatial occupancy models that accounted for both nondetection and spatial autocorrelation. We modeled the spatial autocorrelation with an intrinsic conditional autoregressive (ICAR) model and with a restricted spatial regression (RSR) model. Both spatial models can readily be applied to any other gridded, presence--absence data set using a newly introduced R package. The RSR model provided the best inference and was able to capture small-scale variation that the other models did not. It showed that ground hornbills are strongly dependent on protected areas in the north of their South African range, but less so further south. The ICAR models did not capture any spatial autocorrelation in the data, and they took an order, of magnitude longer than the RSR models to run. Thus, the RSR occupancy model appears to be an attractive choice for modeling occurrences at large spatial domains, while accounting for imperfect detection and spatial autocorrelation.

  1. Analysis of reactor noise; Analiza reaktorskih sumova

    Energy Technology Data Exchange (ETDEWEB)

    Velickovic, Lj [Institute of Nuclear Sciences Boris Kidric, Vinca, Beograd (Yugoslavia)

    1967-11-15

    This paper describes the theoretical model for interpretation of experimental results, experimental method for study of reactor noise at the RB reactor, numerical treatment of experimental results by correlation technique for analysis of reactor noise. A computer code was written to obtain autocorrelation function and spectral density function. Experimental results obtained by oscillator technique, pulse technique, and autocorrelation method are presented and discussed.

  2. Models for Surface Roughness Scattering of Electrons in a 2DEG

    International Nuclear Information System (INIS)

    Yarar, Z.

    2004-01-01

    In this work surface roughness scattering of electrons in a two dimensional electron gas (2DEG) formed at heterojunction interfaces is investigated for different auto-correlation tions and potential forms. Gaussian, exponentiaI and lorentsian auto-correlation tions are used to represent surface roughness. Both an infinitely deep triangular potential model and the potential that is found from the numerical solution of Poisson Shrodinger equations self consistently are used as the potential that holds 2DEG at the hetero Interface. Using the wave functions appropriate for the potentials just mentioned and the auto-correlation functions indicated above, the scattering rates due to surface roughness are calculated. The calculations were repeated when the effect of screening is also included for the case of triangular potential

  3. Employing the Hilbert-Huang Transform to analyze observed natural complex signals: Calm wind meandering cases

    Science.gov (United States)

    Martins, Luis Gustavo Nogueira; Stefanello, Michel Baptistella; Degrazia, Gervásio Annes; Acevedo, Otávio Costa; Puhales, Franciano Scremin; Demarco, Giuliano; Mortarini, Luca; Anfossi, Domenico; Roberti, Débora Regina; Costa, Felipe Denardin; Maldaner, Silvana

    2016-11-01

    In this study we analyze natural complex signals employing the Hilbert-Huang spectral analysis. Specifically, low wind meandering meteorological data are decomposed into turbulent and non turbulent components. These non turbulent movements, responsible for the absence of a preferential direction of the horizontal wind, provoke negative lobes in the meandering autocorrelation functions. The meandering characteristic time scales (meandering periods) are determined from the spectral peak provided by the Hilbert-Huang marginal spectrum. The magnitudes of the temperature and horizontal wind meandering period obtained agree with the results found from the best fit of the heuristic meandering autocorrelation functions. Therefore, the new method represents a new procedure to evaluate meandering periods that does not employ mathematical expressions to represent observed meandering autocorrelation functions.

  4. Investment Dynamics with Natural Expectations*

    Science.gov (United States)

    Fuster, Andreas; Hebert, Benjamin; Laibson, David

    2012-01-01

    We study an investment model in which agents have the wrong beliefs about the dynamic properties of fundamentals. Specifically, we assume that agents underestimate the rate of mean reversion. The model exhibits the following six properties: (i) Beliefs are excessively optimistic in good times and excessively pessimistic in bad times. (ii) Asset prices are too volatile. (iii) Excess returns are negatively autocorrelated. (iv) High levels of corporate profits predict negative future excess returns. (v) Real economic activity is excessively volatile; the economy experiences amplified investment cycles. (vi) Corporate profits are positively autocorrelated in the short run and negatively autocorrelated in the medium run. The paper provides an illustrative model of animal spirits, amplified business cycles, and excess volatility. PMID:23243469

  5. Molecular dynamics simulations

    International Nuclear Information System (INIS)

    Alder, B.J.

    1985-07-01

    The molecular dynamics computer simulation discovery of the slow decay of the velocity autocorrelation function in fluids is briefly reviewed in order to contrast that long time tail with those observed for the stress autocorrelation function in fluids and the velocity autocorrelation function in the Lorentz gas. For a non-localized particle in the Lorentz gas it is made plausible that even if it behaved quantum mechanically its long time tail would be the same as the classical one. The generalization of Fick's law for diffusion for the Lorentz gas, necessary to avoid divergences due to the slow decay of correlations, is presented. For fluids, that generalization has not yet been established, but the region of validity of generalized hydrodynamics is discussed. 20 refs., 5 figs

  6. A Detection Algorithm for the BOC Signal Based on Quadrature Channel Correlation

    Directory of Open Access Journals (Sweden)

    Bo Qian

    2018-01-01

    Full Text Available In order to solve the problem of detecting a BOC signal, which uses a long-period pseudo random sequence, an algorithm is presented based on quadrature channel correlation. The quadrature channel correlation method eliminates the autocorrelation component of the carrier wave, allowing for the extraction of the absolute autocorrelation peaks of the BOC sequence. If the same lag difference and height difference exist for the adjacent peaks, the BOC signal can be detected effectively using a statistical analysis of the multiple autocorrelation peaks. The simulation results show that the interference of the carrier wave component is eliminated and the autocorrelation peaks of the BOC sequence are obtained effectively without demodulation. The BOC signal can be detected effectively when the SNR is greater than −12 dB. The detection ability can be improved further by increasing the number of sampling points. The higher the ratio of the square wave subcarrier speed to the pseudo random sequence speed is, the greater the detection ability is with a lower SNR. The algorithm presented in this paper is superior to the algorithm based on the spectral correlation.

  7. Drag reduction mechanism by microbubble injection within a channel boundary layer

    International Nuclear Information System (INIS)

    Ling Zhen; Hassan, Y.

    2005-01-01

    In this study, the drag reduction due to microbubble injection in the boundary layer of a fully developed turbulent channel flow was investigated. Particle Image Velocimetry (PIV) techniques were taken. The effects of the presence of microbubbles in the boundary layer were assessed. A drag reduction of 38.4% was obtained with void fraction of 4.9%. The algorithms of wavelet auto-correlation maps were applied to the PIV velocity field measurement. Modifications in the wavelet auto-correlation maps due to the presence of microbubbles were studied and compared in three-dimensions. By using 3-D plotting routines and the wavelet auto-correlation maps, it can be deduced from this study that the microbubble injection within the boundary layer increases the turbulent energy of the streamwise velocity components of the large scale (large eddy size, low frequency) range and decreases the energy of the small scale (small eddy size, high frequency) range. The wavelet auto-correlation maps of the normal velocities indicate that the microbubble presence decrease the turbulent energy of normal velocity components for both the large scale (large eddy size, low frequency) and the small scale (small eddy size, high frequency) ranges. (authors)

  8. Development of a real-time stability measurement system for boiling water reactors

    International Nuclear Information System (INIS)

    March-Leuba, J.; King, W.T.

    1987-01-01

    This paper describes the development of a portable, real time system for boiling water reactor (BWR) stability measurements. The system provides a means for the operator to monitor the reactor stability using existing plant instrumentation and commercially available hardware. The noise component (i.e., perturbations around steady state) of the neutron signal in BWRs has been shown to contain information about reactor stability, and several algorithms have been developed to extract that information. For the present work, the authors have used an algorithm that has been implemented on a portable personal computer. This algorithm uses the autocorrelation function of naturally occurring neutron noise (measured without special plant perturbations) and an autoregressive modeling technique to produce the asymptotic DR. For this real-time implementation, neutron noise data is preconditioned (i.e., filtered and amplified) and sampled at a 5-Hz sampling rate using a commercial data-acquisition system. Approximately every 1.5 min, the current (snapshot) autocorrelation function is computed directly from the data, and the average autocorrelation is updated. The current and average DR estimates are evaluated with the same periodicity and are displayed on the screen along with the autocorrelations and average power spectrum of the neutron noise

  9. Linking landscape characteristics to local grizzly bear abundance using multiple detection methods in a hierarchical model

    Science.gov (United States)

    Graves, T.A.; Kendall, Katherine C.; Royle, J. Andrew; Stetz, J.B.; Macleod, A.C.

    2011-01-01

    Few studies link habitat to grizzly bear Ursus arctos abundance and these have not accounted for the variation in detection or spatial autocorrelation. We collected and genotyped bear hair in and around Glacier National Park in northwestern Montana during the summer of 2000. We developed a hierarchical Markov chain Monte Carlo model that extends the existing occupancy and count models by accounting for (1) spatially explicit variables that we hypothesized might influence abundance; (2) separate sub-models of detection probability for two distinct sampling methods (hair traps and rub trees) targeting different segments of the population; (3) covariates to explain variation in each sub-model of detection; (4) a conditional autoregressive term to account for spatial autocorrelation; (5) weights to identify most important variables. Road density and per cent mesic habitat best explained variation in female grizzly bear abundance; spatial autocorrelation was not supported. More female bears were predicted in places with lower road density and with more mesic habitat. Detection rates of females increased with rub tree sampling effort. Road density best explained variation in male grizzly bear abundance and spatial autocorrelation was supported. More male bears were predicted in areas of low road density. Detection rates of males increased with rub tree and hair trap sampling effort and decreased over the sampling period. We provide a new method to (1) incorporate multiple detection methods into hierarchical models of abundance; (2) determine whether spatial autocorrelation should be included in final models. Our results suggest that the influence of landscape variables is consistent between habitat selection and abundance in this system.

  10. Orthogonal transformations for change detection, Matlab code (ENVI-like headers)

    DEFF Research Database (Denmark)

    2007-01-01

    Matlab code to do (iteratively reweighted) multivariate alteration detection (MAD) analysis, maximum autocorrelation factor (MAF) analysis, canonical correlation analysis (CCA) and principal component analysis (PCA) on image data; accommodates ENVI (like) header files.......Matlab code to do (iteratively reweighted) multivariate alteration detection (MAD) analysis, maximum autocorrelation factor (MAF) analysis, canonical correlation analysis (CCA) and principal component analysis (PCA) on image data; accommodates ENVI (like) header files....

  11. Porous media: Analysis, reconstruction and percolation

    DEFF Research Database (Denmark)

    Rogon, Thomas Alexander

    1995-01-01

    functions of Gaussian fields and spatial autocorrelation functions of binary fields. An enhanced approach which embodies semi-analytical solutions for the conversions has been made. The scope and limitations of the method have been analysed in terms of realizability of different model correlation functions...... stereological methods. The measured sample autocorrelations are modeled by analytical correlation functions. A method for simulating porous networks from their porosity and spatial correlation originally developed by Joshi (14) is presented. This method is based on a conversion between spatial autocorrelation...... in binary fields. Percolation threshold of reconstructed porous media has been determined for different discretizations of a selected model correlation function. Also critical exponents such as the correlation length exponent v, the strength of the infinite network and the mean size of finite clusters have...

  12. Desert locust populations, rainfall and climate change: insights from phenomenological models using gridded monthly data

    OpenAIRE

    Tratalos, Jamie A.; Cheke, Robert A.; Healey, Richard G.; Stenseth, Nils Chr.

    2010-01-01

    Using autocorrelation analysis and autoregressive integrated moving average (ARIMA)modelling, we analysed a time series of the monthly number of 1° grid squares infested with desert locust Schistocerca gregaria swarms throughout the geographical range of the species from 1930–1987. Statistically significant first- and higher-order autocorrelations were found in the series. Although endogenous components captured much of the variance, adding rainfall data improved endogenous ARIMA models and r...

  13. Auto-correlation analysis of ocean surface wind vectors

    Indian Academy of Sciences (India)

    M. Senthilkumar (Newgen Imaging) 1461 1996 Oct 15 13:05:22

    time series data of surface winds measured in situ by a deep water buoy in the Indian Ocean has been carried out. ... A case study using the TRMM Microwave Imager (TMI) and ... parameter is essential when the values of the parameter ...

  14. On a method to detect long-latency excitations and inhibitions of single hand muscle motoneurons in man.

    Science.gov (United States)

    Awiszus, F; Feistner, H; Schäfer, S S

    1991-01-01

    The peri-stimulus-time histogram (PSTH) analysis of stimulus-related neuronal spike train data is usually regarded as a method to detect stimulus-induced excitations or inhibitions. However, for a fairly regularly discharging neuron such as the human alpha-motoneuron, long-latency modulations of a PSTH are difficult to interpret as PSTH modulations can also occur as a consequence of a modulated neuronal autocorrelation. The experiments reported here were made (i) to investigate the extent to which a PSTH of a human hand-muscle motoneuron may be contaminated by features of the autocorrelation and (ii) to develop methods that display the motoneuronal excitations and inhibitions without such contamination. Responses of 29 single motor units to electrical ulnar nerve stimulation below motor threshold were investigated in the first dorsal interosseous muscle of three healthy volunteers using an experimental protocol capable of demonstrating the presence of autocorrelative modulations in the neuronal response. It was found for all units that the PSTH as well as the cumulative sum (CUSUM) derived from these responses were severely affected by the presence of autocorrelative features. On the other hand, calculating the CUSUM in a slightly modified form yielded--for all units investigated--a neuronal output feature sensitive only to motoneuronal excitations and inhibitions induced by the afferent volley. The price that has to be paid to arrive at such a modified CUSUM (mCUSUM) was a high computational effort prohibiting the on-line availability of this output feature during the experiment. It was found, however, that an interspike interval superposition plot (IISP)--easily obtainable during the experiment--is also free of autocorrelative features.(ABSTRACT TRUNCATED AT 250 WORDS)

  15. [Characteristics of temporal-spatial differentiation in landscape pattern vulnerability in Nansihu Lake wetland, China.

    Science.gov (United States)

    Liang, Jia Xin; Li, Xin Ju

    2018-02-01

    With remote sensing images from 1985, 2000 Lantsat 5 TM and 2015 Lantsat 8 OLI as data sources, we tried to select the suitable research scale and examine the temporal-spatial diffe-rentiation with such scale in the Nansihu Lake wetland by using landscape pattern vulnerability index constructed by sensitivity index and adaptability index, and combined with space statistics such as semivariogram and spatial autocorrelation. The results showed that 1 km × 1 km equidistant grid was the suitable research scale, which could eliminate the influence of spatial heterogeneity induced by random factors. From 1985 to 2015, the landscape pattern vulnerability in the Nansihu Lake wetland deteriorated gradually. The high-risk area of landscape pattern vulnerability dramatically expanded with time. The spatial heterogeneity of landscape pattern vulnerability increased, and the influence of non-structural factors on landscape pattern vulnerability strengthened. Spatial variability affected by spatial autocorrelation slightly weakened. Landscape pattern vulnerability had strong general spatial positive correlation, with the significant form of spatial agglomeration. The positive spatial autocorrelation continued to increase and the phenomenon of spatial concentration was more and more obvious over time. The local autocorrelation mainly based on high-high accumulation zone and low-low accumulation zone had stronger spatial autocorrelation among neighboring space units. The high-high accumulation areas showed the strongest level of significance, and the significant level of low-low accumulation zone increased with time. Natural factors, such as temperature and precipitation, affected water-level and landscape distribution, and thus changed the landscape patterns vulnerability of Nansihu Lake wetland. The dominant driver for the deterioration of landscape patterns vulnerability was human activities, including social economy activity and policy system.

  16. Life expectancy impacts due to heating energy utilization in China: Distribution, relations, and policy implications.

    Science.gov (United States)

    Wang, Shaobin; Luo, Kunli

    2018-01-01

    The relation between life expectancy and energy utilization is of particular concern. Different viewpoints concerned the health impacts of heating policy in China. However, it is still obscure that what kind of heating energy or what pattern of heating methods is the most related with the difference of life expectancies in China. The aim of this paper is to comprehensively investigate the spatial relations between life expectancy at birth (LEB) and different heating energy utilization in China by using spatial autocorrelation models including global spatial autocorrelation, local spatial autocorrelation and hot spot analysis. The results showed that: (1) Most of heating energy exhibit a distinct north-south difference, such as central heating supply, stalks and domestic coal. Whereas spatial distribution of domestic natural gas and electricity exhibited west-east differences. (2) Consumption of central heating, stalks and domestic coal show obvious spatial dependence. Whereas firewood, natural gas and electricity did not show significant spatial autocorrelation. It exhibited an extinct south-north difference of heat supply, stalks and domestic coal which were identified to show significant positive spatial autocorrelation. (3) Central heating, residential boilers and natural gas did not show any significant correlations with LEB. While, the utilization of domestic coal and biomass showed significant negative correlations with LEB, and household electricity shows positive correlations. The utilization of domestic coal in China showed a negative effect on LEB, rather than central heating. To improve the solid fuel stoves and control consumption of domestic coal consumption and other low quality solid fuel is imperative to improve the public health level in China in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Effect of surface roughness scattering on the transport properties of a 2DEG

    International Nuclear Information System (INIS)

    Yarar, Z.

    2004-01-01

    In this work surface roughness scattering of electrons in a two dimensional electron gas (2DEG) formed at heterojunction interfaces is investigated for various auto-correlation functions. Gaussian, exponential and Lorentzian auto-correlation functions are used to represent surface roughness. Poisson and Schrodinger equations are solved self consistently at the hetero interface to find the energy levels, the wave functions corresponding to each level and electron concentrations at each level. Using these wave functions and the auto-correlation functions mentioned above, the scattering rates due to surface roughness are calculated. Scattering rates resulting from acoustic and optical phonons are also calculated. These rates are used to study the transport properties of the two dimensional electrons using ensemble Monte Carlo method at various temperatures. Emphasis is given to the effect of surface roughness scattering on the transport properties of the electrons

  18. On the interpretation of Stratonovich calculus

    International Nuclear Information System (INIS)

    Moon, W; Wettlaufer, J S

    2014-01-01

    The Itô–Stratonovich dilemma is revisited from the perspective of the interpretation of Stratonovich calculus using shot noise. Over the long time scales of the displacement of an observable, the principal issue is how to deal with finite/zero autocorrelation of the stochastic noise. The former (non-zero) noise autocorrelation structure preserves the normal chain rule using a mid-point selection scheme, which is the basis Stratonovich calculus, whereas the instantaneous autocorrelation structure of Itô's approach does not. By considering the finite decay of the noise correlations on time scales very short relative to the overall displacement times of the observable, we suggest a generalization of the integral Taylor expansion criterion of Wong and Zakai (1965 Ann. Math. Stat. 36 1560–4) for the validity of the Stratonovich approach. (paper)

  19. Characterization of a quantum phase transition in Dirac systems by means of the wave-packet dynamics

    Directory of Open Access Journals (Sweden)

    E. Romera

    2012-12-01

    Full Text Available We study the signatures of phase transitions in the time evolution of wave-packets by analyzing two simple model systems: a graphene quantum dot model in a magnetic field and a Dirac oscillator in a magnetic field. We have characterized the phase transitions using the autocorrelation function. Our work also reveals that the description in terms of Shannon entropy of the autocorrelation function is a clear phase transition indicator.

  20. Tissue strain rate estimator using ultrafast IQ complex data

    OpenAIRE

    TERNIFI , Redouane; Elkateb Hachemi , Melouka; Remenieras , Jean-Pierre

    2012-01-01

    International audience; Pulsatile motion of brain parenchyma results from cardiac and breathing cycles. In this study, transient motion of brain tissue was estimated using an Aixplorer® imaging system allowing an ultrafast 2D acquisition mode. The strain was computed directly from the ultrafast IQ complex data using the extended autocorrelation strain estimator (EASE), which provides great SNRs regardless of depth. The EASE first evaluates the autocorrelation function at each depth over a set...

  1. User's guide to Monte Carlo methods for evaluating path integrals

    Science.gov (United States)

    Westbroek, Marise J. E.; King, Peter R.; Vvedensky, Dimitri D.; Dürr, Stephan

    2018-04-01

    We give an introduction to the calculation of path integrals on a lattice, with the quantum harmonic oscillator as an example. In addition to providing an explicit computational setup and corresponding pseudocode, we pay particular attention to the existence of autocorrelations and the calculation of reliable errors. The over-relaxation technique is presented as a way to counter strong autocorrelations. The simulation methods can be extended to compute observables for path integrals in other settings.

  2. Data acquisition card for fluctuation correlation spectroscopy allowing full access to the detected photon sequence

    OpenAIRE

    Eid, JS; Muller, JD; Gratton, E

    2000-01-01

    Typically, fluctuation correlation spectroscopy (FCS) data acquisition cards measure the number of photon events per time interval (i.e., bin) - time mode. Commercial FCS cards combine the bins through hardware in order to calculate the autocorrelation function. Such a design therefore does not yield the time resolved photon sequence, but only the autocorrelation of that sequence. A different acquisition method which measures the number of time intervals between photon events has been impleme...

  3. A Bayesian Approach for Summarizing and Modeling Time-Series Exposure Data with Left Censoring.

    Science.gov (United States)

    Houseman, E Andres; Virji, M Abbas

    2017-08-01

    Direct reading instruments are valuable tools for measuring exposure as they provide real-time measurements for rapid decision making. However, their use is limited to general survey applications in part due to issues related to their performance. Moreover, statistical analysis of real-time data is complicated by autocorrelation among successive measurements, non-stationary time series, and the presence of left-censoring due to limit-of-detection (LOD). A Bayesian framework is proposed that accounts for non-stationary autocorrelation and LOD issues in exposure time-series data in order to model workplace factors that affect exposure and estimate summary statistics for tasks or other covariates of interest. A spline-based approach is used to model non-stationary autocorrelation with relatively few assumptions about autocorrelation structure. Left-censoring is addressed by integrating over the left tail of the distribution. The model is fit using Markov-Chain Monte Carlo within a Bayesian paradigm. The method can flexibly account for hierarchical relationships, random effects and fixed effects of covariates. The method is implemented using the rjags package in R, and is illustrated by applying it to real-time exposure data. Estimates for task means and covariates from the Bayesian model are compared to those from conventional frequentist models including linear regression, mixed-effects, and time-series models with different autocorrelation structures. Simulations studies are also conducted to evaluate method performance. Simulation studies with percent of measurements below the LOD ranging from 0 to 50% showed lowest root mean squared errors for task means and the least biased standard deviations from the Bayesian model compared to the frequentist models across all levels of LOD. In the application, task means from the Bayesian model were similar to means from the frequentist models, while the standard deviations were different. Parameter estimates for covariates

  4. Short-term predictability of crude oil markets: A detrended fluctuation analysis approach

    International Nuclear Information System (INIS)

    Alvarez-Ramirez, Jose; Alvarez, Jesus; Rodriguez, Eduardo

    2008-01-01

    This paper analyzes the auto-correlations of international crude oil prices on the basis of the estimation of the Hurst exponent dynamics for returns over the period from 1987 to 2007. In doing so, a model-free statistical approach - detrended fluctuation analysis - that reduces the effects of non-stationary market trends and focuses on the intrinsic auto-correlation structure of market fluctuations over different time horizons, is used. Tests for time variations of the Hurst exponent indicate that over long horizons the crude oil market is consistent with the efficient market hypothesis. However, meaningful auto-correlations cannot be excluded for time horizons smaller than one month where the Hurst exponent manifests cyclic, non-periodic dynamics. This means that the market exhibits a time-varying short-term inefficient behavior that becomes efficient in the long term. The proposed methodology and its findings are put in perspective with previous studies and results. (author)

  5. Influence of the boundary conditions on a temperature field in the turbulent flow near the heated wall

    International Nuclear Information System (INIS)

    Bergant, R.; Tiselj, I.

    2002-01-01

    Direct Numerical Simulation (DNS) of the fully developed velocity and temperature fields in the two-dimensional turbulent channel flow was performed for friction Reynolds number Reτ = 150 and Prandtl number Pr 0.71. Two thermal boundary conditions (BCs), isothermal and isoflux, were carried out. The main difference between two ideal types of boundary conditions is in temperature fluctuations, which retain a nonzero value on the wall for isoflux BC, and zero for isothermal BC. Very interesting effect is seen in streamwise temperature auto-correlation functions. While the auto-correlation function for isothermal BC decreases close to zero in the observed computational domain, the decrease of the auto-correlation function for the isoflux BC is slower and remains well above zero. Therefore, another DNS at two times longer computational domain was performed, but results did not show any differences larger than the statistical uncertainty.(author)

  6. a Study of the Concentration Dependence of Macromolecular Diffusion Using Photon Correlation Spectroscopy.

    Science.gov (United States)

    Marlowe, Robert Lloyd

    The dynamic light scattering technique of photon correlation spectroscopy has been used to investigate the dependence of the mutual diffusion coefficient of a macromolecular system upon concentration. The first part of the research was devoted to the design and construction of a single-clipping autocorrelator based on newly-developed integrated circuits. The resulting 128 channel instrument can perform real time autocorrelation for sample time intervals >(, )10 (mu)s, and batch processed autocorrelation for intervals down to 3 (mu)s. An improved design for a newer, all-digital autocorrelator is given. Homodyne light scattering experiments were then undertaken on monodisperse solutions of polystyrene spheres. The single-mode TEM(,oo) beam of an argon-ion laser ((lamda) = 5145 (ANGSTROM)) was used as the light source; all solutions were studied at room temperature. The scattering angle was varied from 30(DEGREES) to 110(DEGREES). Excellent agreement with the manufacturer's specification for the particle size was obtained from the photon correlation studies. Finally, aqueous solutions of the globular protein ovalbumin, ranging in concentration from 18.9 to 244.3 mg/ml, were illuminated under the same conditions of temperature and wavelength as before; the homodyne scattered light was detected at a fixed scattering angle of 30(DEGREES). The single-clipped photocount autocorrelation function was analyzed using the homodyne exponential integral method of Meneely et al. The resulting diffusion coefficients showed a general linear dependence upon concentration, as predicted by the generalized Stokes-Einstein equation. However, a clear peak in the data was evident at c (TURNEQ) 100 mg/ml, which could not be explained on the basis of a non -interacting particle theory. A semi-quantitative approach based on the Debye-Huckel theory of electrostatic interactions is suggested as the probable cause for the peak's rise, and an excluded volume effect for its decline.

  7. Spatial and temporal changes in the structure of groundwater nitrate concentration time series (1935 1999) as demonstrated by autoregressive modelling

    Science.gov (United States)

    Jones, A. L.; Smart, P. L.

    2005-08-01

    Autoregressive modelling is used to investigate the internal structure of long-term (1935-1999) records of nitrate concentration for five karst springs in the Mendip Hills. There is a significant short term (1-2 months) positive autocorrelation at three of the five springs due to the availability of sufficient nitrate within the soil store to maintain concentrations in winter recharge for several months. The absence of short term (1-2 months) positive autocorrelation in the other two springs is due to the marked contrast in land use between the limestone and swallet parts of the catchment, rapid concentrated recharge from the latter causing short term switching in the dominant water source at the spring and thus fluctuating nitrate concentrations. Significant negative autocorrelation is evident at lags varying from 4 to 7 months through to 14-22 months for individual springs, with positive autocorrelation at 19-20 months at one site. This variable timing is explained by moderation of the exhaustion effect in the soil by groundwater storage, which gives longer residence times in large catchments and those with a dominance of diffuse flow. The lags derived from autoregressive modelling may therefore provide an indication of average groundwater residence times. Significant differences in the structure of the autocorrelation function for successive 10-year periods are evident at Cheddar Spring, and are explained by the effect the ploughing up of grasslands during the Second World War and increased fertiliser usage on available nitrogen in the soil store. This effect is moderated by the influence of summer temperatures on rates of mineralization, and of both summer and winter rainfall on the timing and magnitude of nitrate leaching. The pattern of nitrate leaching also appears to have been perturbed by the 1976 drought.

  8. The effects of spatial autoregressive dependencies on inference in ordinary least squares: a geometric approach

    Science.gov (United States)

    Smith, Tony E.; Lee, Ka Lok

    2012-01-01

    There is a common belief that the presence of residual spatial autocorrelation in ordinary least squares (OLS) regression leads to inflated significance levels in beta coefficients and, in particular, inflated levels relative to the more efficient spatial error model (SEM). However, our simulations show that this is not always the case. Hence, the purpose of this paper is to examine this question from a geometric viewpoint. The key idea is to characterize the OLS test statistic in terms of angle cosines and examine the geometric implications of this characterization. Our first result is to show that if the explanatory variables in the regression exhibit no spatial autocorrelation, then the distribution of test statistics for individual beta coefficients in OLS is independent of any spatial autocorrelation in the error term. Hence, inferences about betas exhibit all the optimality properties of the classic uncorrelated error case. However, a second more important series of results show that if spatial autocorrelation is present in both the dependent and explanatory variables, then the conventional wisdom is correct. In particular, even when an explanatory variable is statistically independent of the dependent variable, such joint spatial dependencies tend to produce "spurious correlation" that results in over-rejection of the null hypothesis. The underlying geometric nature of this problem is clarified by illustrative examples. The paper concludes with a brief discussion of some possible remedies for this problem.

  9. Reconsidering harmonic and anharmonic coherent states: Partial differential equations approach

    Energy Technology Data Exchange (ETDEWEB)

    Toutounji, Mohamad, E-mail: Mtoutounji@uaeu.ac.ae

    2015-02-15

    This article presents a new approach to dealing with time dependent quantities such as autocorrelation function of harmonic and anharmonic systems using coherent states and partial differential equations. The approach that is normally used to evaluate dynamical quantities involves formidable operator algebra. That operator algebra becomes insurmountable when employing Morse oscillator coherent states. This problem becomes even more complicated in case of Morse oscillator as it tends to exhibit divergent dynamics. This approach employs linear partial differential equations, some of which may be solved exactly and analytically, thereby avoiding the cumbersome noncommutative algebra required to manipulate coherent states of Morse oscillator. Additionally, the arising integrals while using the herein presented method feature stability and high numerical efficiency. The correctness, applicability, and utility of the above approach are tested by reproducing the partition and optical autocorrelation function of the harmonic oscillator. A closed-form expression for the equilibrium canonical partition function of the Morse oscillator is derived using its coherent states and partial differential equations. Also, a nonequilibrium autocorrelation function expression for weak electron–phonon coupling in condensed systems is derived for displaced Morse oscillator in electronic state. Finally, the utility of the method is demonstrated through further simplifying the Morse oscillator partition function or autocorrelation function expressions reported by other researchers in unevaluated form of second-order derivative exponential. Comparison with exact dynamics shows identical results.

  10. Testing algorithms for critical slowing down

    Directory of Open Access Journals (Sweden)

    Cossu Guido

    2018-01-01

    Full Text Available We present the preliminary tests on two modifications of the Hybrid Monte Carlo (HMC algorithm. Both algorithms are designed to travel much farther in the Hamiltonian phase space for each trajectory and reduce the autocorrelations among physical observables thus tackling the critical slowing down towards the continuum limit. We present a comparison of costs of the new algorithms with the standard HMC evolution for pure gauge fields, studying the autocorrelation times for various quantities including the topological charge.

  11. Landau-Placzek ratio for heat density dynamics and its application to heat capacity of liquids.

    Science.gov (United States)

    Bryk, Taras; Ruocco, Giancarlo; Scopigno, Tullio

    2013-01-21

    Exact relation for contributions to heat capacity of liquids is obtained from hydrodynamic theory. It is shown from analysis of the long-wavelength limit of heat density autocorrelation functions that the heat capacity of simple liquids is represented as a sum of two contributions due to "phonon-like" collective excitations and heat relaxation. The ratio of both contributions being the analogy of Landau-Placzek ratio for heat processes depends on the specific heats ratio. The theory of heat density autocorrelation functions in liquids is verified by computer simulations. Molecular dynamics simulations for six liquids having the ratio of specific heats γ in the range 1.1-2.3, were used for evaluation of the heat density autocorrelation functions and predicted Landau-Placzek ratio for heat processes. The dependence of contributions from collective excitations and heat relaxation process to specific heat on γ is shown to be in excellent agreement with the theory.

  12. Environmental variability uncovers disruptive effects of species' interactions on population dynamics.

    Science.gov (United States)

    Gudmundson, Sara; Eklöf, Anna; Wennergren, Uno

    2015-08-07

    How species respond to changes in environmental variability has been shown for single species, but the question remains whether these results are transferable to species when incorporated in ecological communities. Here, we address this issue by analysing the same species exposed to a range of environmental variabilities when (i) isolated or (ii) embedded in a food web. We find that all species in food webs exposed to temporally uncorrelated environments (white noise) show the same type of dynamics as isolated species, whereas species in food webs exposed to positively autocorrelated environments (red noise) can respond completely differently compared with isolated species. This is owing to species following their equilibrium densities in a positively autocorrelated environment that in turn enables species-species interactions to come into play. Our results give new insights into species' response to environmental variation. They especially highlight the importance of considering both species' interactions and environmental autocorrelation when studying population dynamics in a fluctuating environment. © 2015 The Author(s).

  13. The role of fluid-wall interactions on confined liquid diffusion using Mori theory

    International Nuclear Information System (INIS)

    Devi, Reena; Srivastava, Sunita; Tankeshwar, K.

    2015-01-01

    The dynamics of fluid confined in a nano-channel with smooth walls have been studied through velocity autocorrelation function within the memory function approach by incorporating the atomic level interactions of fluid with the confining wall. Expressions for the second and fourth sum rules of velocity autocorrelation have been derived for nano-channel which involves fluid-fluid and fluid-wall interactions. These expressions, in addition, involve pair correlation function and density profiles. The numerical contributions of fluid-wall interaction to sum rules are found to play a very significant role, specifically at smaller channel width. Results obtained for velocity autocorrelation and self-diffusion coefficient of a fluid confined to different widths of the nanochannel have been compared with the computer simulation results. The comparison shows a good agreement except when the width of the channel is of the order of two atomic diameters, where it becomes difficult to estimate sum rules involving the triplet correlation’s contribution

  14. Numerical analysis for finite-range multitype stochastic contact financial market dynamic systems

    International Nuclear Information System (INIS)

    Yang, Ge; Wang, Jun; Fang, Wen

    2015-01-01

    In an attempt to reproduce and study the dynamics of financial markets, a random agent-based financial price model is developed and investigated by the finite-range multitype contact dynamic system, in which the interaction and dispersal of different types of investment attitudes in a stock market are imitated by viruses spreading. With different parameters of birth rates and finite-range, the normalized return series are simulated by Monte Carlo simulation method and numerical studied by power-law distribution analysis and autocorrelation analysis. To better understand the nonlinear dynamics of the return series, a q-order autocorrelation function and a multi-autocorrelation function are also defined in this work. The comparisons of statistical behaviors of return series from the agent-based model and the daily historical market returns of Shanghai Composite Index and Shenzhen Component Index indicate that the proposed model is a reasonable qualitative explanation for the price formation process of stock market systems

  15. Numerical analysis for finite-range multitype stochastic contact financial market dynamic systems

    Science.gov (United States)

    Yang, Ge; Wang, Jun; Fang, Wen

    2015-04-01

    In an attempt to reproduce and study the dynamics of financial markets, a random agent-based financial price model is developed and investigated by the finite-range multitype contact dynamic system, in which the interaction and dispersal of different types of investment attitudes in a stock market are imitated by viruses spreading. With different parameters of birth rates and finite-range, the normalized return series are simulated by Monte Carlo simulation method and numerical studied by power-law distribution analysis and autocorrelation analysis. To better understand the nonlinear dynamics of the return series, a q-order autocorrelation function and a multi-autocorrelation function are also defined in this work. The comparisons of statistical behaviors of return series from the agent-based model and the daily historical market returns of Shanghai Composite Index and Shenzhen Component Index indicate that the proposed model is a reasonable qualitative explanation for the price formation process of stock market systems.

  16. Bunch Length Measurements using Coherent Radiation

    CERN Document Server

    Ischebeck, Rasmus; Barnes, Christopher; Blumenfeld, Ian; Clayton, Chris; Decker, Franz Josef; Deng, Suzhi; Hogan, Mark; Huang Cheng Kun; Iverson, Richard; Johnson, Devon K; Krejcik, Patrick; Lu, Wei; Marsh, Kenneth; Oz, Erdem; Siemann, Robert; Walz, Dieter

    2005-01-01

    The accelerating field that can be obtained in a beam-driven plasma wakefield accelerator depends on the current of the electron beam that excites the wake. In the E-167 experiment, a peak current above 10kA will be delivered at a particle energy of 28GeV. The bunch has a length of a few ten micrometers and several methods are used to measure its longitudinal profile. Among these, autocorrelation of coherent transition radiation (CTR) is employed. The beam passes a thin metallic foil, where it emits transition radiation. For wavelengths greater than the bunch length, this transition radiation is emitted coherently. This amplifies the long-wavelength part of the spectrum. A scanning Michelson interferometer is used to autocorrelate the CTR. However, this method requires the contribution of many bunches to build an autocorrelation trace. The measurement is influenced by the transmission characteristics of the vacuum window and beam splitter. We present here an analysis of materials, as well as possible layouts ...

  17. REGIONAL FIRST ORDER PERIODIC AUTOREGRESSIVE MODELS FOR MONTHLY FLOWS

    Directory of Open Access Journals (Sweden)

    Ceyhun ÖZÇELİK

    2008-01-01

    Full Text Available First order periodic autoregressive models is of mostly used models in modeling of time dependency of hydrological flow processes. In these models, periodicity of the correlogram is preserved as well as time dependency of processes. However, the parameters of these models, namely, inter-monthly lag-1 autocorrelation coefficients may be often estimated erroneously from short samples, since they are statistics of high order moments. Therefore, to constitute a regional model may be a solution that can produce more reliable and decisive estimates, and derive models and model parameters in any required point of the basin considered. In this study, definitions of homogeneous region for lag-1 autocorrelation coefficients are made; five parametric and non parametric models are proposed to set regional models of lag-1 autocorrelation coefficients. Regional models are applied on 30 stream flow gauging stations in Seyhan and Ceyhan basins, and tested by criteria of relative absolute bias, simple and relative root of mean square errors.

  18. Numerical analysis for finite-range multitype stochastic contact financial market dynamic systems

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Ge; Wang, Jun [School of Science, Beijing Jiaotong University, Beijing 100044 (China); Fang, Wen, E-mail: fangwen@bjtu.edu.cn [School of Economics and Management, Beijing Jiaotong University, Beijing 100044 (China)

    2015-04-15

    In an attempt to reproduce and study the dynamics of financial markets, a random agent-based financial price model is developed and investigated by the finite-range multitype contact dynamic system, in which the interaction and dispersal of different types of investment attitudes in a stock market are imitated by viruses spreading. With different parameters of birth rates and finite-range, the normalized return series are simulated by Monte Carlo simulation method and numerical studied by power-law distribution analysis and autocorrelation analysis. To better understand the nonlinear dynamics of the return series, a q-order autocorrelation function and a multi-autocorrelation function are also defined in this work. The comparisons of statistical behaviors of return series from the agent-based model and the daily historical market returns of Shanghai Composite Index and Shenzhen Component Index indicate that the proposed model is a reasonable qualitative explanation for the price formation process of stock market systems.

  19. Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms II: A Method to Obtain First-Level Analysis Residuals with Uniform and Gaussian Spatial Autocorrelation Function and Independent and Identically Distributed Time-Series.

    Science.gov (United States)

    Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Lacey, Simon; Sathian, K

    2018-02-01

    In a recent study Eklund et al. have shown that cluster-wise family-wise error (FWE) rate-corrected inferences made in parametric statistical method-based functional magnetic resonance imaging (fMRI) studies over the past couple of decades may have been invalid, particularly for cluster defining thresholds less stringent than p functions (sACFs) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggest otherwise. Hence, the residuals from general linear model (GLM)-based fMRI activation estimates in these studies may not have possessed a homogenously Gaussian sACF. Here we propose a method based on the assumption that heterogeneity and non-Gaussianity of the sACF of the first-level GLM analysis residuals, as well as temporal autocorrelations in the first-level voxel residual time-series, are caused by unmodeled MRI signal from neuronal and physiological processes as well as motion and other artifacts, which can be approximated by appropriate decompositions of the first-level residuals with principal component analysis (PCA), and removed. We show that application of this method yields GLM residuals with significantly reduced spatial correlation, nearly Gaussian sACF and uniform spatial smoothness across the brain, thereby allowing valid cluster-based FWE-corrected inferences based on assumption of Gaussian spatial noise. We further show that application of this method renders the voxel time-series of first-level GLM residuals independent, and identically distributed across time (which is a necessary condition for appropriate voxel-level GLM inference), without having to fit ad hoc stochastic colored noise models. Furthermore, the detection power of individual subject brain activation analysis is enhanced. This method will be especially useful for case studies, which rely on first-level GLM analysis inferences.

  20. Surface correlation function analysis of high resolution scattering data from mirrored surfaces obtained using a triple-axis X-ray diffractometer

    DEFF Research Database (Denmark)

    Christensen, Finn Erland; Hornstrup, Allan; Schnopper, H. W.

    1988-01-01

    methods is that they are bandwidth-limited. A crucial point in the analysis of data is, therefore, to specify accurately the wavelength bandwidth limitation and to determine the surface autocorrelation function within this bandwidth. The authors present a number of scattering measurements obtained using...... a triple-axis perfect-crystal X-ray diffractometer and the results of an autocorrelation function analysis. Furthermore, they present some measurements of integrated reflectivity, which they believe provide evidence for microroughness in the range from a few angstroms to tens of microns...

  1. Laser light scattering in Brownian medium

    International Nuclear Information System (INIS)

    Suwono; Santoso, Budi; Baiquni, A.

    1983-01-01

    The principle of laser light scattering in Brownian medium and photon correlation spectroscopy are described in detail. Their application to the study of the behaviour of a polystyrene latex solution are discussed. The auto-correlation function of light scattered by the polystyrene latex solution in various angle, various temperature and in various sample times, have been measured. Information on the translation diffusion coefficient and size on the particle can be obtained from the auto-correlation function. Good agreement between the available data and experiment is shown. (author)

  2. Long-range dependence and sea level forecasting

    CERN Document Server

    Ercan, Ali; Abbasov, Rovshan K

    2013-01-01

    This study shows that the Caspian Sea level time series possess long range dependence even after removing linear trends, based on analyses of the Hurst statistic, the sample autocorrelation functions, and the periodogram of the series. Forecasting performance of ARMA, ARIMA, ARFIMA and Trend Line-ARFIMA (TL-ARFIMA) combination models are investigated. The forecast confidence bands and the forecast updating methodology, provided for ARIMA models in the literature, are modified for the ARFIMA models. Sample autocorrelation functions are utilized to estimate the differencing lengths of the ARFIMA

  3. Search paths of swans foraging on spatially autocorrelated tubers

    NARCIS (Netherlands)

    Nolet, B.A.; Mooij, W.M.

    2002-01-01

    1. Tundra swans forage on below-ground pondweed tubers that are heterogeneously distributed in space. The swans have no visual cues to delineate patches. It was tested whether swans employ an area-restricted search tactic. Theory predicts that swans should alternate between an intensive (low-speed,

  4. A second-order autocorrelator for single-shot measurement of ...

    Indian Academy of Sciences (India)

    R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

    from a passively mode-locked, diode pumped Nd:glass laser. It can also be used for measurement of ... different mode-locking techniques (Liu et al 1992; Bilinsky et al 1998). Amplification of ..... IEEE J. Quantum Electron. QE-28: 2097–2122.

  5. Kernel maximum autocorrelation factor and minimum noise fraction transformations

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2010-01-01

    in hyperspectral HyMap scanner data covering a small agricultural area, and 3) maize kernel inspection. In the cases shown, the kernel MAF/MNF transformation performs better than its linear counterpart as well as linear and kernel PCA. The leading kernel MAF/MNF variates seem to possess the ability to adapt...

  6. Sensitivity of MRQAP tests to collinearity and autocorrelation conditions

    NARCIS (Netherlands)

    Dekker, David; Krackhardt, David; Snijders, Tom A. B.

    2007-01-01

    Multiple regression quadratic assignment procedures (MRQAP) tests are permutation tests for multiple linear regression model coefficients for data organized in square matrices of relatedness among n objects. Such a data structure is typical in social network studies, where variables indicate some

  7. Stable Blind Deconvolution over the Reals from Additional Autocorrelations

    KAUST Repository

    Walk, Philipp; Hassibi, Babak

    2017-01-01

    that under a sufficient zero separation of the corresponding signal in the $z-$domain, a stable reconstruction against additive noise is possible. Moreover, the stability constant depends on the signal dimension and on the signals magnitude of the first

  8. A novel framework for parameter selection of the Autocorrelation ...

    African Journals Online (AJOL)

    Human settlement expansion is one of the most prominent types of land cover change in South Africa. These changes typically occur in areas that are covered by natural vegetation. Methods that can rapidly indicate areas having a high probability of change are very valuable to analysts as this can be used to direct their ...

  9. Aging Wiener-Khinchin theorem and critical exponents of 1/f^{β} noise.

    Science.gov (United States)

    Leibovich, N; Dechant, A; Lutz, E; Barkai, E

    2016-11-01

    The power spectrum of a stationary process may be calculated in terms of the autocorrelation function using the Wiener-Khinchin theorem. We here generalize the Wiener-Khinchin theorem for nonstationary processes and introduce a time-dependent power spectrum 〈S_{t_{m}}(ω)〉 where t_{m} is the measurement time. For processes with an aging autocorrelation function of the form 〈I(t)I(t+τ)〉=t^{Υ}ϕ_{EA}(τ/t), where ϕ_{EA}(x) is a nonanalytic function when x is small, we find aging 1/f^{β} noise. Aging 1/f^{β} noise is characterized by five critical exponents. We derive the relations between the scaled autocorrelation function and these exponents. We show that our definition of the time-dependent spectrum retains its interpretation as a density of Fourier modes and discuss the relation to the apparent infrared divergence of 1/f^{β} noise. We illustrate our results for blinking-quantum-dot models, single-file diffusion, and Brownian motion in a logarithmic potential.

  10. MENENTUKAN PORTOFOLIO OPTIMAL MENGGUNAKAN MODEL CONDITIONAL MEAN VARIANCE

    Directory of Open Access Journals (Sweden)

    I GEDE ERY NISCAHYANA

    2016-08-01

    Full Text Available When the returns of stock prices show the existence of autocorrelation and heteroscedasticity, then conditional mean variance models are suitable method to model the behavior of the stocks. In this thesis, the implementation of the conditional mean variance model to the autocorrelated and heteroscedastic return was discussed. The aim of this thesis was to assess the effect of the autocorrelated and heteroscedastic returns to the optimal solution of a portfolio. The margin of four stocks, Fortune Mate Indonesia Tbk (FMII.JK, Bank Permata Tbk (BNLI.JK, Suryamas Dutamakmur Tbk (SMDM.JK dan Semen Gresik Indonesia Tbk (SMGR.JK were estimated by GARCH(1,1 model with standard innovations following the standard normal distribution and the t-distribution.  The estimations were used to construct a portfolio. The portfolio optimal was found when the standard innovation used was t-distribution with the standard deviation of 1.4532 and the mean of 0.8023 consisting of 0.9429 (94% of FMII stock, 0.0473 (5% of  BNLI stock, 0% of SMDM stock, 1% of  SMGR stock.

  11. Tool breakage detection from 2D workpiece profile using vision method

    International Nuclear Information System (INIS)

    Lee, W K; Ratnam, M M; Ahmad, Z A

    2016-01-01

    In-process tool breakage monitoring can significantly save cost and prevent damages to machine tool. In this paper, a machine vision approach was employed to detect the tool fracture in commercial aluminium oxide ceramic cutting tool during turning of AISI 52100 hardened steel. The contour of the workpiece profile was captured with the aid of backlighting during turning using a high-resolution DSLR camera with a shutter speed of 1/4000 s. The surface profile of the workpiece was extracted to sub-pixel accuracy using the invariant moment method. The effect of fracture in ceramic cutting tools on the surface profile signature of the machined workpiece using autocorrelation was studied. Fracture in the aluminum oxide ceramic tool was found to cause the peaks of autocorrelation function of the workpiece profile to decrease rapidly as the lag distance increased. The envelope of the peaks of the autocorrelation function was observed to deviate significantly from one another at different workpiece angles when the tool has fractured due to the continuous fracture of ceramic cutting insert during machining. (paper)

  12. Research on the spatial agglomeration of urban tourism in Yangtze River delta

    Directory of Open Access Journals (Sweden)

    LIU Jinwei

    2015-04-01

    Full Text Available This article on the basis of spatial autocorrelation theory analyzed the interaction spatial relationship and pattern, utilizing Geo da software made quantitative research on the tourism spatial autocorrelation level of 16 cities in Yangtze River delta The results indicate that Domestic tourism and the inbound tourism had a low Moran′s value and field to get through the statistic significant test, showing the non-significant global spatial autocorrelation The progress of tourism without notable gather and differentiation trait The level of tourism emerging random distribution pattern due to the standard of city The cities quadrant chart reflect the congruent relationship between urban hierarchy and tourism performance, Shanghai, Hangzhou, Nanjing and Suzhou are the high value center, along with surrounding cities which obtain low value make up the random spatial situation, the towns encircle the high-value urban are the service and radiation zone of the upper city; the level of the spatial autocorrelation among cities decline from 2005 to 2010, tourism entering the network integration developing stage.

  13. Double-resolution electron holography with simple Fourier transform of fringe-shifted holograms

    International Nuclear Information System (INIS)

    Volkov, V.V.; Han, M.G.; Zhu, Y.

    2013-01-01

    We propose a fringe-shifting holographic method with an appropriate image wave recovery algorithm leading to exact solution of holographic equations. With this new method the complex object image wave recovered from holograms appears to have much less traditional artifacts caused by the autocorrelation band present practically in all Fourier transformed holograms. The new analytical solutions make possible a double-resolution electron holography free from autocorrelation band artifacts and thus push the limits for phase resolution. The new image wave recovery algorithm uses a popular Fourier solution of the side band-pass filter technique, while the fringe-shifting holographic method is simple to implement in practice. - Highlights: • We propose a fringe-shifting holographic method simple enough for practical implementations. • Our new image-wave-recovery algorithm follows from exact solution of holographic equations. • With autocorrelation band removal from holograms it is possible to achieve double-resolution electron holography data free from several commonly known artifacts. • The new fringe-shifting method can reach an image wave resolution close to single fringe spacing

  14. Double-resolution electron holography with simple Fourier transform of fringe-shifted holograms

    Energy Technology Data Exchange (ETDEWEB)

    Volkov, V.V., E-mail: volkov@bnl.gov; Han, M.G.; Zhu, Y.

    2013-11-15

    We propose a fringe-shifting holographic method with an appropriate image wave recovery algorithm leading to exact solution of holographic equations. With this new method the complex object image wave recovered from holograms appears to have much less traditional artifacts caused by the autocorrelation band present practically in all Fourier transformed holograms. The new analytical solutions make possible a double-resolution electron holography free from autocorrelation band artifacts and thus push the limits for phase resolution. The new image wave recovery algorithm uses a popular Fourier solution of the side band-pass filter technique, while the fringe-shifting holographic method is simple to implement in practice. - Highlights: • We propose a fringe-shifting holographic method simple enough for practical implementations. • Our new image-wave-recovery algorithm follows from exact solution of holographic equations. • With autocorrelation band removal from holograms it is possible to achieve double-resolution electron holography data free from several commonly known artifacts. • The new fringe-shifting method can reach an image wave resolution close to single fringe spacing.

  15. Possible Noise Nature of Elsässer Variable z- in Highly Alfvénic Solar Wind Fluctuations

    Science.gov (United States)

    Wang, X.; Tu, C.-Y.; He, J.-S.; Wang, L.-H.; Yao, S.; Zhang, L.

    2018-01-01

    It has been a long-standing debate on the nature of Elsässer variable z- observed in the solar wind fluctuations. It is widely believed that z- represents inward propagating Alfvén waves and interacts nonlinearly with z+ (outward propagating Alfvén waves) to generate energy cascade. However, z- variations sometimes show a feature of convective structures. Here we present a new data analysis on autocorrelation functions of z- in order to get some definite information on its nature. We find that there is usually a large drop on the z- autocorrelation function when the solar wind fluctuations are highly Alfvénic. The large drop observed by Helios 2 spacecraft near 0.3 AU appears at the first nonzero time lag τ = 81 s, where the value of the autocorrelation coefficient drops to 25%-65% of that at τ = 0 s. Beyond the first nonzero time lag, the autocorrelation coefficient decreases gradually to zero. The drop of z- correlation function also appears in the Wind observations near 1 AU. These features of the z- correlation function may suggest that z- fluctuations consist of two components: high-frequency white noise and low-frequency pseudo structures, which correspond to flat and steep parts of z- power spectrum, respectively. This explanation is confirmed by doing a simple test on an artificial time series, which is obtained from the superposition of a random data series on its smoothed sequence. Our results suggest that in highly Alfvénic fluctuations, z- may not contribute importantly to the interactions with z+ to produce energy cascade.

  16. Dangers and uses of cross-correlation in analyzing time series in perception, performance, movement, and neuroscience: The importance of constructing transfer function autoregressive models.

    Science.gov (United States)

    Dean, Roger T; Dunsmuir, William T M

    2016-06-01

    Many articles on perception, performance, psychophysiology, and neuroscience seek to relate pairs of time series through assessments of their cross-correlations. Most such series are individually autocorrelated: they do not comprise independent values. Given this situation, an unfounded reliance is often placed on cross-correlation as an indicator of relationships (e.g., referent vs. response, leading vs. following). Such cross-correlations can indicate spurious relationships, because of autocorrelation. Given these dangers, we here simulated how and why such spurious conclusions can arise, to provide an approach to resolving them. We show that when multiple pairs of series are aggregated in several different ways for a cross-correlation analysis, problems remain. Finally, even a genuine cross-correlation function does not answer key motivating questions, such as whether there are likely causal relationships between the series. Thus, we illustrate how to obtain a transfer function describing such relationships, informed by any genuine cross-correlations. We illustrate the confounds and the meaningful transfer functions by two concrete examples, one each in perception and performance, together with key elements of the R software code needed. The approach involves autocorrelation functions, the establishment of stationarity, prewhitening, the determination of cross-correlation functions, the assessment of Granger causality, and autoregressive model development. Autocorrelation also limits the interpretability of other measures of possible relationships between pairs of time series, such as mutual information. We emphasize that further complexity may be required as the appropriate analysis is pursued fully, and that causal intervention experiments will likely also be needed.

  17. Advanced Sine Wave Modulation of Continuous Wave Laser System for Atmospheric CO2 Differential Absorption Measurements

    Science.gov (United States)

    Campbell, Joel F.; Lin, Bing; Nehrir, Amin R.

    2014-01-01

    NASA Langley Research Center in collaboration with ITT Exelis have been experimenting with Continuous Wave (CW) laser absorption spectrometer (LAS) as a means of performing atmospheric CO2 column measurements from space to support the Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) mission.Because range resolving Intensity Modulated (IM) CW lidar techniques presented here rely on matched filter correlations, autocorrelation properties without side lobes or other artifacts are highly desirable since the autocorrelation function is critical for the measurements of lidar return powers, laser path lengths, and CO2 column amounts. In this paper modulation techniques are investigated that improve autocorrelation properties. The modulation techniques investigated in this paper include sine waves modulated by maximum length (ML) sequences in various hardware configurations. A CW lidar system using sine waves modulated by ML pseudo random noise codes is described, which uses a time shifting approach to separate channels and make multiple, simultaneous online/offline differential absorption measurements. Unlike the pure ML sequence, this technique is useful in hardware that is band pass filtered as the IM sine wave carrier shifts the main power band. Both amplitude and Phase Shift Keying (PSK) modulated IM carriers are investigated that exibit perfect autocorrelation properties down to one cycle per code bit. In addition, a method is presented to bandwidth limit the ML sequence based on a Gaussian filter implemented in terms of Jacobi theta functions that does not seriously degrade the resolution or introduce side lobes as a means of reducing aliasing and IM carrier bandwidth.

  18. Modified Three-Dimensional Multicarrier Optical Prime Codes

    Directory of Open Access Journals (Sweden)

    Rajesh Yadav

    2016-01-01

    Full Text Available We propose a mathematical model for novel three-dimensional multicarrier optical codes in terms of wavelength/time/space based on the prime sequence algorithm. The proposed model has been extensively simulated on MATLAB for prime numbers (P to analyze the performance of code in terms of autocorrelation and cross-correlation. The simulated outcome resembles the mathematical model and gives better results over other methods available in the literature as far as autocorrelation and cross-correlation are concerned. The proposed 3D optical codes are more efficient in terms of cardinality, improved security, and providing quality of services.

  19. Correlation lifetimes of quiet and magnetic granulation from the SOUP instrument on Spacelab 2

    Science.gov (United States)

    Title, A.; Tarbell, T.; Topka, K.; Acton, L.; Duncan, D.; Ferguson, S.; Finch, M.; Frank, Z.; Kelly, G.; Lindgren, R.; Morrill, M.; Pope, T.; Reeves, R.; Rehse, R.; Shine, R.; Simon, G.; Harvey, J.; Leibacher, J.; Livingston, W.; November, L.; Zirker, J.

    The time sequences of diffraction limited granulation images obtained by the Solar Optical Universal Polarimeter on Spacelab 2 are presented. The uncorrection autocorrelation limetime in magnetic regions is dominated by the 5-min oscillation. The removal of this oscillation causes the autocorrelation lifetime to increase by more than a factor of 2. The results suggest that a significant fraction of granule lifetimes are terminated by nearby explosions. Horizontal displacements and transverse velocities in the intensity field are measured. Lower limits to the lifetime in the quiet and magnetic sun are set at 440 s and 950 s, respectively.

  20. A generalization of random matrix theory and its application to statistical physics.

    Science.gov (United States)

    Wang, Duan; Zhang, Xin; Horvatic, Davor; Podobnik, Boris; Eugene Stanley, H

    2017-02-01

    To study the statistical structure of crosscorrelations in empirical data, we generalize random matrix theory and propose a new method of cross-correlation analysis, known as autoregressive random matrix theory (ARRMT). ARRMT takes into account the influence of auto-correlations in the study of cross-correlations in multiple time series. We first analytically and numerically determine how auto-correlations affect the eigenvalue distribution of the correlation matrix. Then we introduce ARRMT with a detailed procedure of how to implement the method. Finally, we illustrate the method using two examples taken from inflation rates for air pressure data for 95 US cities.

  1. Self-diffusion coefficients of the metastable Lennard-Jones vapor

    International Nuclear Information System (INIS)

    Nie Chu; Zhou Youhua; Marlow, W H; Hassan, Y A

    2008-01-01

    Self-diffusion coefficients of a metastable Lennard-Jones vapor were obtained using the memory function formalism and the frequency moments of the velocity autocorrelation function at reduced temperatures from 0.75 to 1.0. The radial density distribution functions used to evaluate the second, fourth and sixth frequency moments of the velocity autocorrelation function were obtained from the restricted canonical ensemble Monte Carlo simulation (Corti and Debenedetti 1994 Chem. Eng. Sci. 49 2717). The self-diffusion coefficients at reduced temperature 0.75 do not vary monotonically as the density increases, and for the other three temperatures the self-diffusion coefficients vary normally

  2. Comparison of high-field Moessbauer and μSR investigations on spin glasses

    International Nuclear Information System (INIS)

    Bogner, J.; Reissner, M.; Steiner, W.; Cywinski, R.; Dann, J.A.; Telling, M.T.F.

    2001-01-01

    We report on the analysis of μSR and Moessbauer measurements of the metallic spin glasses Y(Fe 0.65 Al 0.35 ) 2 and Y(Fe 0.4 Al 0.6 ) 2 above the freezing temperature (T f ) in terms of a model taking into account a dynamical process of stochastic formation and decay of magnetically correlated regions. By this model a comparison of the autocorrelation function determined by the two different measuring techniques is possible. For the temperature dependence of the autocorrelation time we find fair agreement between both experiments for T>2T f

  3. The study for the Spatial Distribution Pattern of NDVI in the Western of Jilin Province

    Science.gov (United States)

    Yang, Shu-jie; Li, Xiao-dong; Yan, Shou-gang

    2018-02-01

    Using methods of spatial autocorrelation analysis and trend analysis, the paper studies the spatial distribution pattern of NDVI based on the GIMMS NDVI dataset (1998-2008), in Western Jilin. The maximum value for 15d is got through the method of MAX processing. Results show that: the NDVI in growing season shows a rising trend in western Jilin in 1998-2008. In the study area, the NDVI in Western Jilin shows positive spatial autocorrelation in the whole region, but the partial NDVI is apt to scattered distribution, which means the vegetation cover of Western Jilin is generally fragmental.

  4. Self-diffusion coefficients of the metastable Lennard-Jones vapor

    Energy Technology Data Exchange (ETDEWEB)

    Nie Chu; Zhou Youhua [School of Physics and Information Engineering, Jianghan University, Wuhan 430056 (China); Marlow, W H; Hassan, Y A [Department of Nuclear Engineering, Texas A and M University, College Station, TX 77843 (United States)], E-mail: yhzhou@jhun.edu.cn

    2008-10-15

    Self-diffusion coefficients of a metastable Lennard-Jones vapor were obtained using the memory function formalism and the frequency moments of the velocity autocorrelation function at reduced temperatures from 0.75 to 1.0. The radial density distribution functions used to evaluate the second, fourth and sixth frequency moments of the velocity autocorrelation function were obtained from the restricted canonical ensemble Monte Carlo simulation (Corti and Debenedetti 1994 Chem. Eng. Sci. 49 2717). The self-diffusion coefficients at reduced temperature 0.75 do not vary monotonically as the density increases, and for the other three temperatures the self-diffusion coefficients vary normally.

  5. Contribution of ultrasound forward scattering to tissue structure study

    International Nuclear Information System (INIS)

    Edee, M.K.

    1987-12-01

    In this paper, we show how to get useful information of tissue structure by merely interpreting some experimental graphs such as energy spectral density and autocorrelation function of an ultrasonic beam travelling through tissues. To support these interpretations, we needed just some well-known theorems rather than heavy and complicated mathematical equations, so we measured the dimensions of scatterers within specimens by using the graphical representation of autocorrelation function. We related these measurements to the scattered peaks which appear in energy density spectrum. The values we found were equal to those obtained from biologists within ∼ 15%. (author) 26 refs, 6 figs, tabs

  6. Method for remote diagnostics of the internal structure of layered media

    International Nuclear Information System (INIS)

    Lychagov, V V; Kal'yanov, A L; Ryabukho, V P; Lyakin, D V

    2008-01-01

    The method of autocorrelation low coherence interferometry is proposed for diagnostics of inhomogeneities and the internal structure of layered technical and biological samples. In this method the low coherence optical field reflected from the layered sample is analysed by using a Michelson interferometer. Because the object is outside the interferometer, the distance between the interferometer and the object under study is not limited and thus the object can move during the measurements. Theoretical substantiation of the autocorrelation method for media with discrete and continuous optical structure modifications is presented. (special issue devoted to application of laser technologies in biophotonics and biomedical studies)

  7. Recursive estimation techniques for detection of small objects in infrared image data

    Science.gov (United States)

    Zeidler, J. R.; Soni, T.; Ku, W. H.

    1992-04-01

    This paper describes a recursive detection scheme for point targets in infrared (IR) images. Estimation of the background noise is done using a weighted autocorrelation matrix update method and the detection statistic is calculated using a recursive technique. A weighting factor allows the algorithm to have finite memory and deal with nonstationary noise characteristics. The detection statistic is created by using a matched filter for colored noise, using the estimated noise autocorrelation matrix. The relationship between the weighting factor, the nonstationarity of the noise and the probability of detection is described. Some results on one- and two-dimensional infrared images are presented.

  8. Measurement of nuclear reactor noise at low power levels; Merenje nuklearnog reaktorskog suma na malim snagama

    Energy Technology Data Exchange (ETDEWEB)

    Velickovic, Lj; Petrovic, M [Boris Kidric Institute of nuclear sciences Vinca, Belgrade (Yugoslavia)

    1968-11-15

    Spatial and time dependence relation of neutrons from fission and other reactions in the reactor core result in non Poisson fluctuations of neutron density. Analytical formula developed for auto-correlation function includes physical parameters which characterize time behaviour of neutrons in the reactor system. Since auto-correlation function can be easily measured, it is a useful tool for experimental determination of these parameters. Noise from the ionization chamber was measured and analyzed by a digital computer. measurements were analyzed completely in the time domain (auto-correlation functions). This enabled separating the noise caused by neutron detection from the noise from neutron density fluctuation in the reactor. All the results can be analyzed by spatial independent reactor theory. Physical analysis of reactor noise was limited to determination of {beta}/l ratio from auto-correlation measurements at 0.5 W power level (RB reactor in Vinca). Three different reactor core lattices were analyzed (lattice pitch 8 cm, 11.3 cm and 14 cm). It was shown that parameter {beta}/l could be determined from auto-correlation measurements of neutron density with high precision (few percents) Prostorna i vremenska povezanost neutrona koji nastaju u fisiji i drugim procesima koji se desavaju u reaktoru dovodi do ne Poisson-ovih fluktuacija neutronske gustine. Analiticka formula, razvijena za autokorelacionu funkciju ovih fluktuacija, sadrzi fizicke parametre koji karakterisu vremensko ponasanje neutrona u reaktorskom sistemu. Kako autokorelaciona funkcija moze lako da se meri, ona je korisno sredstvo za eksperimentalno odredjivanje ovih parametara. Sum iz jonizacione komore digitalno je meren i analiziran u digitalnom racunaru. Merenja su kompletno analizirana u vremenskom domenu (autokorelacione funkeije). To je olaksalo razdvajanje suma izazvanog procesom neutronske detekcije od suma koji potice od fluktuacija neutronske gustine u reaktorskom sistemu. Svi rezultati

  9. Statistical regularities of Carbon emission trading market: Evidence from European Union allowances

    Science.gov (United States)

    Zheng, Zeyu; Xiao, Rui; Shi, Haibo; Li, Guihong; Zhou, Xiaofeng

    2015-05-01

    As an emerging financial market, the trading value of carbon emission trading market has definitely increased. In recent years, the carbon emission allowances have already become a way of investment. They are bought and sold not only by carbon emitters but also by investors. In this paper, we analyzed the price fluctuations of the European Union allowances (EUA) futures in European Climate Exchange (ECX) market from 2007 to 2011. The symmetric and power-law probability density function of return time series was displayed. We found that there are only short-range correlations in price changes (return), while long-range correlations in the absolute of price changes (volatility). Further, detrended fluctuation analysis (DFA) approach was applied with focus on long-range autocorrelations and Hurst exponent. We observed long-range power-law autocorrelations in the volatility that quantify risk, and found that they decay much more slowly than the autocorrelation of return time series. Our analysis also showed that the significant cross correlations exist between return time series of EUA and many other returns. These cross correlations exist in a wide range of fields, including stock markets, energy concerned commodities futures, and financial futures. The significant cross-correlations between energy concerned futures and EUA indicate the physical relationship between carbon emission and energy production process. Additionally, the cross-correlations between financial futures and EUA indicate that the speculation behavior may become an important factor that can affect the price of EUA. Finally we modeled the long-range volatility time series of EUA with a particular version of the GARCH process, and the result also suggests long-range volatility autocorrelations.

  10. Spatial modeling using mixed models: an ecologic study of visceral leishmaniasis in Teresina, Piauí State, Brazil

    Directory of Open Access Journals (Sweden)

    Werneck Guilherme L.

    2002-01-01

    Full Text Available Most ecologic studies use geographical areas as units of observation. Because data from areas close to one another tend to be more alike than those from distant areas, estimation of effect size and confidence intervals should consider spatial autocorrelation of measurements. In this report we demonstrate a method for modeling spatial autocorrelation within a mixed model framework, using data on environmental and socioeconomic determinants of the incidence of visceral leishmaniasis (VL in the city of Teresina, Piauí, Brazil. A model with a spherical covariance structure indicated significant spatial autocorrelation in the data and yielded a better fit than one assuming independent observations. While both models showed a positive association between VL incidence and residence in a favela (slum or in areas with green vegetation, values for the fixed effects and standard errors differed substantially between the models. Exploration of the data's spatial correlation structure through the semivariogram should precede the use of these models. Our findings support the hypothesis of spatial dependence of VL rates and indicate that it might be useful to model spatial correlation in order to obtain more accurate point and standard error estimates.

  11. A new methodology of spatial cross-correlation analysis.

    Science.gov (United States)

    Chen, Yanguang

    2015-01-01

    Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.

  12. Geomagnetic storm under laboratory conditions: randomized experiment

    Science.gov (United States)

    Gurfinkel, Yu I.; Vasin, A. L.; Pishchalnikov, R. Yu; Sarimov, R. M.; Sasonko, M. L.; Matveeva, T. A.

    2017-10-01

    The influence of the previously recorded geomagnetic storm (GS) on human cardiovascular system and microcirculation has been studied under laboratory conditions. Healthy volunteers in lying position were exposed under two artificially created conditions: quiet (Q) and storm (S). The Q regime playbacks a noise-free magnetic field (MF) which is closed to the natural geomagnetic conditions on Moscow's latitude. The S regime playbacks the initially recorded 6-h geomagnetic storm which is repeated four times sequentially. The cardiovascular response to the GS impact was assessed by measuring capillary blood velocity (CBV) and blood pressure (BP) and by the analysis of the 24-h ECG recording. A storm-to-quiet ratio for the cardio intervals (CI) and the heart rate variability (HRV) was introduced in order to reveal the average over group significant differences of HRV. An individual sensitivity to the GS was estimated using the autocorrelation function analysis of the high-frequency (HF) part of the CI spectrum. The autocorrelation analysis allowed for detection a group of subjects of study which autocorrelation functions (ACF) react differently in the Q and S regimes of exposure.

  13. Geomagnetic storm under laboratory conditions: randomized experiment.

    Science.gov (United States)

    Gurfinkel, Yu I; Vasin, A L; Pishchalnikov, R Yu; Sarimov, R M; Sasonko, M L; Matveeva, T A

    2018-04-01

    The influence of the previously recorded geomagnetic storm (GS) on human cardiovascular system and microcirculation has been studied under laboratory conditions. Healthy volunteers in lying position were exposed under two artificially created conditions: quiet (Q) and storm (S). The Q regime playbacks a noise-free magnetic field (MF) which is closed to the natural geomagnetic conditions on Moscow's latitude. The S regime playbacks the initially recorded 6-h geomagnetic storm which is repeated four times sequentially. The cardiovascular response to the GS impact was assessed by measuring capillary blood velocity (CBV) and blood pressure (BP) and by the analysis of the 24-h ECG recording. A storm-to-quiet ratio for the cardio intervals (CI) and the heart rate variability (HRV) was introduced in order to reveal the average over group significant differences of HRV. An individual sensitivity to the GS was estimated using the autocorrelation function analysis of the high-frequency (HF) part of the CI spectrum. The autocorrelation analysis allowed for detection a group of subjects of study which autocorrelation functions (ACF) react differently in the Q and S regimes of exposure.

  14. Predicting the potential distribution of the amphibian pathogen Batrachochytrium dendrobatidis in East and Southeast Asia.

    Science.gov (United States)

    Moriguchi, Sachiko; Tominaga, Atsushi; Irwin, Kelly J; Freake, Michael J; Suzuki, Kazutaka; Goka, Koichi

    2015-04-08

    Batrachochytrium dendrobatidis (Bd) is the pathogen responsible for chytridiomycosis, a disease that is associated with a worldwide amphibian population decline. In this study, we predicted the potential distribution of Bd in East and Southeast Asia based on limited occurrence data. Our goal was to design an effective survey area where efforts to detect the pathogen can be focused. We generated ecological niche models using the maximum-entropy approach, with alleviation of multicollinearity and spatial autocorrelation. We applied eigenvector-based spatial filters as independent variables, in addition to environmental variables, to resolve spatial autocorrelation, and compared the model's accuracy and the degree of spatial autocorrelation with those of a model estimated using only environmental variables. We were able to identify areas of high suitability for Bd with accuracy. Among the environmental variables, factors related to temperature and precipitation were more effective in predicting the potential distribution of Bd than factors related to land use and cover type. Our study successfully predicted the potential distribution of Bd in East and Southeast Asia. This information should now be used to prioritize survey areas and generate a surveillance program to detect the pathogen.

  15. Synchronous scattering and diffraction from gold nanotextured surfaces with structure factors

    Science.gov (United States)

    Gu, Min-Jhong; Lee, Ming-Tsang; Huang, Chien-Hsun; Wu, Chi-Chun; Chen, Yu-Bin

    2018-05-01

    Synchronous scattering and diffraction were demonstrated using reflectance from gold nanotextured surfaces at oblique (θi = 15° and 60°) incidence of wavelength λ = 405 nm. Two samples of unique auto-correlation functions were cost-effectively fabricated. Multiple structure factors of their profiles were confirmed with Fourier expansions. Bi-directional reflectance function (BRDF) from these samples provided experimental proofs. On the other hand, standard deviation of height and unique auto-correlation function of each sample were used to generate surfaces numerically. Comparing their BRDF with those of totally random rough surfaces further suggested that structure factors in profile could reduce specular reflection more than totally random roughness.

  16. Spatial Dependence of Crime in Monterrey, Mexico

    Directory of Open Access Journals (Sweden)

    Ernesto Aguayo Téllez

    2014-06-01

    Full Text Available This paper studies the impact that the characteristics of the environment have on crime using neighborhood aggregate data of the Monterrey Metropolitan Area for the year 2010. Data spatial autocorrelation is corroborated, i.e. neighborhoods with high crime rates have a positive impact on the crime rates of its surrounding neighborhoods. Once it was controlled through the bias caused by spatial autocorrelation and data censoring, it is evidenced that the likelihood of being a crime victim and the probability of becoming an offender is positively related to variables such as unemployment, the percentage of young men and the existence of schools, hospitals or markets in the neighborhood.

  17. Dynamical analyses of the time series for three foreign exchange rates

    Science.gov (United States)

    Kim, Sehyun; Kim, Soo Yong; Jung, Jae-Won; Kim, Kyungsik

    2012-05-01

    In this study, we investigate the multifractal properties of three foreign exchange rates (USD-KRW, USD-JPY, and EUR-USD) that are quoted with different economic scales. We estimate and analyze both the generalized Hurst exponent and the autocorrelation function in three foreign exchange rates. The USD-KRW is shown to have the strongest of the Hurst exponents when compared with the other two foreign exchange rates. In particular, the autocorrelation function of the USD-KRW has the largest memory behavior among three foreign exchange rates. It also exhibits a long-memory property in the first quarter, more than those in the other quarters.

  18. Statistical methods for segmentation and classification of images

    DEFF Research Database (Denmark)

    Rosholm, Anders

    1997-01-01

    The central matter of the present thesis is Bayesian statistical inference applied to classification of images. An initial review of Markov Random Fields relates to the modeling aspect of the indicated main subject. In that connection, emphasis is put on the relatively unknown sub-class of Pickard...... with a Pickard Random Field modeling of a considered (categorical) image phenomemon. An extension of the fast PRF based classification technique is presented. The modification introduces auto-correlation into the model of an involved noise process, which previously has been assumed independent. The suitability...... of the extended model is documented by tests on controlled image data containing auto-correlated noise....

  19. Viscoelastic properties of attractive and repulsive colloidal glasses

    International Nuclear Information System (INIS)

    Puertas, Antonio M; Zaccarelli, Emanuela; Sciortino, Francesco

    2005-01-01

    We report a numerical study of the shear viscosity and the frequency dependent elastic moduli close to dynamical arrest for a model of short range attractive colloids, both for the repulsive and the attractive glass transition. Calculating the stress autocorrelation functions, we find that density fluctuations of wavevectors close to the first peak in the structure factor control the viscosity rise on approaching the repulsive glass, while fluctuations of larger wavevectors control the viscosity close to the attractive glass. On approaching the glass transition, the viscosity diverges with a power law with the same exponent as the density autocorrelation time. (letter to the editor)

  20. Double-resolution electron holography with simple Fourier transform of fringe-shifted holograms.

    Science.gov (United States)

    Volkov, V V; Han, M G; Zhu, Y

    2013-11-01

    We propose a fringe-shifting holographic method with an appropriate image wave recovery algorithm leading to exact solution of holographic equations. With this new method the complex object image wave recovered from holograms appears to have much less traditional artifacts caused by the autocorrelation band present practically in all Fourier transformed holograms. The new analytical solutions make possible a double-resolution electron holography free from autocorrelation band artifacts and thus push the limits for phase resolution. The new image wave recovery algorithm uses a popular Fourier solution of the side band-pass filter technique, while the fringe-shifting holographic method is simple to implement in practice. Published by Elsevier B.V.

  1. Stock Market Autoregressive Dynamics: A Multinational Comparative Study with Quantile Regression

    Directory of Open Access Journals (Sweden)

    Lili Li

    2016-01-01

    Full Text Available We study the nonlinear autoregressive dynamics of stock index returns in seven major advanced economies (G7 and China. The quantile autoregression model (QAR enables us to investigate the autocorrelation across the whole spectrum of return distribution, which provides more insightful conditional information on multinational stock market dynamics than conventional time series models. The relation between index return and contemporaneous trading volume is also investigated. While prior studies have mixed results on stock market autocorrelations, we find that the dynamics is usually state dependent. The results for G7 stock markets exhibit conspicuous similarities, but they are in manifest contrast to the findings on Chinese stock markets.

  2. Thermal sine-Gordon system in the presence of different types of dissipation

    DEFF Research Database (Denmark)

    Salerno, M.; Samuelsen, Mogens Rugholm; Svensmark, Henrik

    1988-01-01

    The effects of thermal fluctuations on solitons and phonons of the sine-Gordon system are investigated in the presence of a αφt-βφxxt dissipation. The analysis requires the assumption of a more general autocorrelation function for the noise than the one used in previous works. We verify that this......The effects of thermal fluctuations on solitons and phonons of the sine-Gordon system are investigated in the presence of a αφt-βφxxt dissipation. The analysis requires the assumption of a more general autocorrelation function for the noise than the one used in previous works. We verify...

  3. Periodicity in spatial data and geostatistical models: autocorrelation between patches

    Science.gov (United States)

    Volker C. Radeloff; Todd F. Miller; Hong S. He; David J. Mladenoff

    2000-01-01

    Several recent studies in landscape ecology have found periodicity in correlograms or semi-variograms calculated, for instance, from spatial data of soils, forests, or animal populations. Some of the studies interpreted this as an indication of regular or periodic landscape patterns. This interpretation is in disagreement with other studies that doubt whether such...

  4. Bulk stress auto-correlation function in simple liquids-sum rules

    International Nuclear Information System (INIS)

    Tankeshwar, K.; Bhandari, R.; Pathak, K.N.

    1990-10-01

    Expressions for the zeroth, second and fourth frequency sum rules of the bulk stress auto correlation function have been derived. The exact expressions involve static correlation function up to four particles. Because of the non availability of any information about static quadruplet correlation function we use a low order decoupling approximation for this. In this work, we have obtained, separately, the sum rules for the different mechanism of momentum transfer in the fluids. The results are expected to be useful in the study of bulk viscosity of the fluids. (author). 9 refs

  5. Autocorrel I: A Neural Network Based Network Event Correlation Approach

    National Research Council Canada - National Science Library

    Japkowicz, Nathalie; Smith, Reuben

    2005-01-01

    .... We use the autoassociator to build prototype software to cluster network alerts generated by a Snort intrusion detection system, and discuss how the results are significant, and how they can be applied to other types of network events.

  6. Testing for Explosive Bubbles in the Presence of Autocorrelated Innovations

    DEFF Research Database (Denmark)

    Pedersen, Thomas Quistgaard; Montes Schütte, Erik Christian

    We analyze an empirically important issue with the recursive right-tailed unit root tests for bubbles in asset prices. First, we show that serially correlated innovations, which is a feature that is present in most financial series used to test for bubbles, can lead to severe size distortions when...

  7. An improved Fuzzy Kappa statistic that accounts for spatial autocorrelation

    NARCIS (Netherlands)

    Hagen - Zanker, A.H.

    2009-01-01

    The Fuzzy Kappa statistic expresses the agreement between two categorical raster maps. The statistic goes beyond cell-by-cell comparison and gives partial credit to cells based on the categories found in the neighborhood. When matching categories are found at shorter distances the agreement is

  8. Dynamic Ecological Risk Assessment and Management of Land Use in the Middle Reaches of the Heihe River Based on Landscape Patterns and Spatial Statistics

    Directory of Open Access Journals (Sweden)

    Jiahui Fan

    2016-06-01

    Full Text Available Land use profoundly changes the terrestrial ecosystem and landscape patterns, and these changes reveal the extent and scope of the ecological influence of land use on the terrestrial ecosystem. The study area selected for this research was the middle reaches of the Heihe River. Based on land use data (1986, 2000, and 2014, we proposed an ecological risk index of land use by combining a landscape disturbance index with a landscape fragility index. An exponential model was selected to perform kriging interpolation, as well as spatial autocorrelations and semivariance analyses which could reveal the spatial aggregation patterns. The results indicated that the ecological risk of the middle reaches of the Heihe River was generally high, and higher in the northwest. The high values of the ecological risk index (ERI tended to decrease, and the low ERI values tended to increase. Positive spatial autocorrelations and a prominent scale-dependence were observed among the ERI values. The main hot areas with High-High local autocorrelations were located in the north, and the cold areas with low-low local autocorrelations were primarily located in the middle corridor plain and Qilian Mountains. From 1986 to 2014, low and relatively low ecological risk areas decreased while relatively high risk areas expanded. A middle level of ecological risk was observed in Ganzhou and Minle counties. Shandan County presented a serious polarization, with high ecological risk areas observed in the north and low ecological risk areas observed in the southern Shandan horse farm. In order to lower the eco-risk and achieve the sustainability of land use, these results suggest policies to strictly control the oasis expansion and the occupation of farmland for urbanization. Some inefficient farmland should transform into grassland in appropriate cases.

  9. Spatial analysis of Schistosomiasis in Hubei Province, China: a GIS-based analysis of Schistosomiasis from 2009 to 2013.

    Directory of Open Access Journals (Sweden)

    Yan-Yan Chen

    Full Text Available Schistosomiasis remains a major public health problem in China. The major endemic areas are located in the lake and marshland regions of southern China, particularly in areas along the middle and low reach of the Yangtze River. Spatial analytical techniques are often used in epidemiology to identify spatial clusters in disease regions. This study assesses the spatial distribution of schistosomiasis and explores high-risk regions in Hubei Province, China to provide guidance on schistosomiasis control in marshland regions.In this study, spatial autocorrelation methodologies, including global Moran's I and local Getis-Ord statistics, were utilized to describe and map spatial clusters and areas where human Schistosoma japonicum infection is prevalent at the county level in Hubei province. In addition, linear logistic regression model was used to determine the characteristics of spatial autocorrelation with time.The infection rates of S. japonicum decreased from 2009 to 2013. The global autocorrelation analysis results on the infection rate of S. japonicum for five years showed statistical significance (Moran's I > 0, P < 0.01, which suggested that spatial clusters were present in the distribution of S. japonicum infection from 2009 to 2013. Local autocorrelation analysis results showed that the number of highly aggregated areas ranged from eight to eleven within the five-year analysis period. The highly aggregated areas were mainly distributed in eight counties.The spatial distribution of human S. japonicum infections did not exhibit a temporal change at the county level in Hubei Province. The risk factors that influence human S. japonicum transmission may not have changed after achieving the national criterion of infection control. The findings indicated that spatial-temporal surveillance of S. japonicum transmission plays a significant role on schistosomiasis control. Timely and integrated prevention should be continued, especially in the Yangtze

  10. Hydrogen bond dynamical properties of adsorbed liquid water monolayers with various TiO2 interfaces

    Science.gov (United States)

    English, Niall J.; Kavathekar, Ritwik S.; MacElroy, J. M. D.

    2012-12-01

    Equilibrium classical molecular dynamics (MD) simulations have been performed to investigate the hydrogen-bonding kinetics of water in contact with rutile-(110), rutile-(101), rutile-(100), and anatase-(101) surfaces at room temperature (300 K). It was observed that anatase-(101) exhibits the longest-lived hydrogen bonds in terms of overall persistence, followed closely by rutile-(110). The relaxation times, defined as the integral of the autocorrelation of the hydrogen bond persistence function, were also longer for these two cases, while decay of the autocorrelation function was slower. The increased number and overall persistence of hydrogen bonds in the adsorbed water monolayers at these surfaces, particularly for anatase-(101), may serve to promote possible water photolysis activity thereon.

  11. Efficiencies of joint non-local update moves in Monte Carlo simulations of coarse-grained polymers

    Science.gov (United States)

    Austin, Kieran S.; Marenz, Martin; Janke, Wolfhard

    2018-03-01

    In this study four update methods are compared in their performance in a Monte Carlo simulation of polymers in continuum space. The efficiencies of the update methods and combinations thereof are compared with the aid of the autocorrelation time with a fixed (optimal) acceptance ratio. Results are obtained for polymer lengths N = 14, 28 and 42 and temperatures below, at and above the collapse transition. In terms of autocorrelation, the optimal acceptance ratio is approximately 0.4. Furthermore, an overview of the step sizes of the update methods that correspond to this optimal acceptance ratio is given. This shall serve as a guide for future studies that rely on efficient computer simulations.

  12. Fluctuation analysis of proficient and dysgraphic handwriting in children

    Science.gov (United States)

    Rosenblum, S.; Roman, H. E.

    2009-03-01

    We analyze handwriting records from several school children with the aim of characterizing the fluctuating behavior of the writing speed. It will be concluded that remarkable differences exist between proficient and dysgraphic handwritings which were unknown so far. It is shown that in the case of proficient handwriting, the variations in handwriting speed are strongly autocorrelated within times corresponding to the completion of a single character or letter, while become uncorrelated at longer times. In the case of dysgraphia, such correlations persist on longer time scales and the autocorrelation function seems to display algebraic time decay, indicating the presence of strong anomalies in the handwriting process. Applications of the results in educational/clinical programs are envisaged.

  13. Time-scale effects on the gain-loss asymmetry in stock indices

    Science.gov (United States)

    Sándor, Bulcsú; Simonsen, Ingve; Nagy, Bálint Zsolt; Néda, Zoltán

    2016-08-01

    The gain-loss asymmetry, observed in the inverse statistics of stock indices is present for logarithmic return levels that are over 2 % , and it is the result of the non-Pearson-type autocorrelations in the index. These non-Pearson-type correlations can be viewed also as functionally dependent daily volatilities, extending for a finite time interval. A generalized time-window shuffling method is used to show the existence of such autocorrelations. Their characteristic time scale proves to be smaller (less than 25 trading days) than what was previously believed. It is also found that this characteristic time scale has decreased with the appearance of program trading in the stock market transactions. Connections with the leverage effect are also established.

  14. Weak Form Efficiency of the Chittagong Stock Exchange: An Empirical Analysis (2006-2016

    Directory of Open Access Journals (Sweden)

    Shahadat Hussain

    2017-01-01

    Full Text Available We study the random walk behavior of Chittagong Stock Exchange (CSE by using daily returns of three indices for the period of 2006 to 2016 employing both non-parametric test (run test and parametric tests [autocorrelation coefficient test, Ljung– Box (LB statistics]. The skewness and kurtosis properties of daily return series are non-normal, with a hint of positively skewed and leptokurtic distribution. The results of run test; autocorrelation and Ljung–Box (LB statistics provide evidences against random walk behavior in the Chittagong Stock Exchange. Overall our result suggest that Chittagong Stock Exchange does not exhibit weak form of efficiency. Hence, there is opportunity of generating a superior return by the active investors.

  15. Multiple scaling behaviour and nonlinear traits in music scores

    Science.gov (United States)

    González-Espinoza, Alfredo; Larralde, Hernán; Martínez-Mekler, Gustavo; Müller, Markus

    2017-12-01

    We present a statistical analysis of music scores from different composers using detrended fluctuation analysis (DFA). We find different fluctuation profiles that correspond to distinct autocorrelation structures of the musical pieces. Further, we reveal evidence for the presence of nonlinear autocorrelations by estimating the DFA of the magnitude series, a result validated by a corresponding study of appropriate surrogate data. The amount and the character of nonlinear correlations vary from one composer to another. Finally, we performed a simple experiment in order to evaluate the pleasantness of the musical surrogate pieces in comparison with the original music and find that nonlinear correlations could play an important role in the aesthetic perception of a musical piece.

  16. Analysis of Radar Doppler Signature from Human Data

    Directory of Open Access Journals (Sweden)

    M. ANDRIĆ

    2014-04-01

    Full Text Available This paper presents the results of time (autocorrelation and time-frequency (spectrogram analyses of radar signals returned from the moving human targets. When a radar signal falls on the human target which is moving toward or away from the radar, the signals reflected from different parts of his body produce a Doppler shift that is proportional to the velocity of those parts. Moving parts of the body causes the characteristic Doppler signature. The main contribution comes from the torso which causes the central Doppler frequency of target. The motion of arms and legs induces modulation on the returned radar signal and generates sidebands around the central Doppler frequency, referred to as micro-Doppler signatures. Through analyses on experimental data it was demonstrated that the human motion signature extraction is better using spectrogram. While the central Doppler frequency can be determined using the autocorrelation and the spectrogram, the extraction of the fundamental cadence frequency using the autocorrelation is unreliable when the target is in the clutter presence. It was shown that the fundamental cadence frequency increases with increasing dynamic movement of people and simultaneously the possibility of its extraction is proportional to the degree of synchronization movements of persons in the group.

  17. Correction of Spatial Bias in Oligonucleotide Array Data

    Directory of Open Access Journals (Sweden)

    Philippe Serhal

    2013-01-01

    Full Text Available Background. Oligonucleotide microarrays allow for high-throughput gene expression profiling assays. The technology relies on the fundamental assumption that observed hybridization signal intensities (HSIs for each intended target, on average, correlate with their target’s true concentration in the sample. However, systematic, nonbiological variation from several sources undermines this hypothesis. Background hybridization signal has been previously identified as one such important source, one manifestation of which appears in the form of spatial autocorrelation. Results. We propose an algorithm, pyn, for the elimination of spatial autocorrelation in HSIs, exploiting the duality of desirable mutual information shared by probes in a common probe set and undesirable mutual information shared by spatially proximate probes. We show that this correction procedure reduces spatial autocorrelation in HSIs; increases HSI reproducibility across replicate arrays; increases differentially expressed gene detection power; and performs better than previously published methods. Conclusions. The proposed algorithm increases both precision and accuracy, while requiring virtually no changes to users’ current analysis pipelines: the correction consists merely of a transformation of raw HSIs (e.g., CEL files for Affymetrix arrays. A free, open-source implementation is provided as an R package, compatible with standard Bioconductor tools. The approach may also be tailored to other platform types and other sources of bias.

  18. Correction of Spatial Bias in Oligonucleotide Array Data

    Science.gov (United States)

    Lemieux, Sébastien

    2013-01-01

    Background. Oligonucleotide microarrays allow for high-throughput gene expression profiling assays. The technology relies on the fundamental assumption that observed hybridization signal intensities (HSIs) for each intended target, on average, correlate with their target's true concentration in the sample. However, systematic, nonbiological variation from several sources undermines this hypothesis. Background hybridization signal has been previously identified as one such important source, one manifestation of which appears in the form of spatial autocorrelation. Results. We propose an algorithm, pyn, for the elimination of spatial autocorrelation in HSIs, exploiting the duality of desirable mutual information shared by probes in a common probe set and undesirable mutual information shared by spatially proximate probes. We show that this correction procedure reduces spatial autocorrelation in HSIs; increases HSI reproducibility across replicate arrays; increases differentially expressed gene detection power; and performs better than previously published methods. Conclusions. The proposed algorithm increases both precision and accuracy, while requiring virtually no changes to users' current analysis pipelines: the correction consists merely of a transformation of raw HSIs (e.g., CEL files for Affymetrix arrays). A free, open-source implementation is provided as an R package, compatible with standard Bioconductor tools. The approach may also be tailored to other platform types and other sources of bias. PMID:23573083

  19. A New Methodology of Spatial Cross-Correlation Analysis

    Science.gov (United States)

    Chen, Yanguang

    2015-01-01

    Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120

  20. [Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

    Science.gov (United States)

    Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

    2018-04-01

    Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

  1. Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process.

    Science.gov (United States)

    Moran, John L; Solomon, Patricia J

    2013-05-24

    Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. Monthly mean raw mortality (at hospital discharge) time series, 1995-2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) "in-control" status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag40 and 35% had autocorrelation through to lag40; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals

  2. 0.1 Trend analysis of δ18O composition of precipitation in Germany: Combining Mann-Kendall trend test and ARIMA models to correct for higher order serial correlation

    Science.gov (United States)

    Klaus, Julian; Pan Chun, Kwok; Stumpp, Christine

    2015-04-01

    Spatio-temporal dynamics of stable oxygen (18O) and hydrogen (2H) isotopes in precipitation can be used as proxies for changing hydro-meteorological and regional and global climate patterns. While spatial patterns and distributions gained much attention in recent years the temporal trends in stable isotope time series are rarely investigated and our understanding of them is still limited. These might be a result of a lack of proper trend detection tools and effort for exploring trend processes. Here we make use of an extensive data set of stable isotope in German precipitation. In this study we investigate temporal trends of δ18O in precipitation at 17 observation station in Germany between 1978 and 2009. For that we test different approaches for proper trend detection, accounting for first and higher order serial correlation. We test if significant trends in the isotope time series based on different models can be observed. We apply the Mann-Kendall trend tests on the isotope series, using general multiplicative seasonal autoregressive integrate moving average (ARIMA) models which account for first and higher order serial correlations. With the approach we can also account for the effects of temperature, precipitation amount on the trend. Further we investigate the role of geographic parameters on isotope trends. To benchmark our proposed approach, the ARIMA results are compared to a trend-free prewhiting (TFPW) procedure, the state of the art method for removing the first order autocorrelation in environmental trend studies. Moreover, we explore whether higher order serial correlations in isotope series affects our trend results. The results show that three out of the 17 stations have significant changes when higher order autocorrelation are adjusted, and four stations show a significant trend when temperature and precipitation effects are considered. Significant trends in the isotope time series are generally observed at low elevation stations (≤315 m a

  3. Quantitative Structure-Activity Relationship Analysis of the ...

    African Journals Online (AJOL)

    Erah

    Quantitative Structure-Activity Relationship Analysis of the Anticonvulsant ... Two types of molecular descriptors, including the 2D autocorrelation ..... It is based on the simulation of natural .... clustering anticonvulsant, antidepressant, and.

  4. Heat capacity of liquids: A hydrodynamic approach

    Directory of Open Access Journals (Sweden)

    T. Bryk

    2015-03-01

    Full Text Available We study autocorrelation functions of energy, heat and entropy densities obtained by molecular dynamics simulations of supercritical Ar and compare them with the predictions of the hydrodynamic theory. It is shown that the predicted by the hydrodynamic theory single-exponential shape of the entropy density autocorrelation functions is perfectly reproduced for small wave numbers by the molecular dynamics simulations and permits the calculation of the wavenumber-dependent specific heat at constant pressure. The estimated wavenumber-dependent specific heats at constant volume and pressure, Cv(k and Cp(k, are shown to be in the long-wavelength limit in good agreement with the macroscopic experimental values of Cv and Cp for the studied thermodynamic points of supercritical Ar.

  5. On the potential of Kriging for forest management planning

    Energy Technology Data Exchange (ETDEWEB)

    Gunnarsson, F

    1997-12-31

    Forest management planning aims at fulfilling the overall goals for the forest owner. The economic optimal scheduling of treatments in spatially discrete forest stands, the time dimension, has been thoroughly investigated in research. The spatial dimension is less investigated. Normally, spatially discrete stands are defined as treatment units. These are inventoried using subjective methods with unknown precision. As an alternative to this conventional way to describe the forest, the present investigation used kriging for estimating forest characteristics spatially continuously using georeferenced sample plots. Using stratification by age, several variables interesting for forest management planning displayed spatial autocorrelation, even though the estate was thoroughly managed. No hardwood variables displayed the autocorrelation necessary for using kriging. 20 refs, 6 figs, 2 tabs

  6. DETERMINANTS OF REGIONAL COMPETITIVENESS IN ROMANIA - A PANEL DATA APPROACH

    Directory of Open Access Journals (Sweden)

    Mihaela-Nona, CHILIAN

    2014-11-01

    Full Text Available In this study, a few panel data models were estimated to analyze the regional competitiveness in the 42 counties (including Bucharest of Romania. The dynamic panel with Arellano "Bover/Blundell" Bond estimators and robust standard errors showed that during 2000-2012 the GDP in the current period depends on the average number of employees and on the GDP value of the previous period. For a fixed effect model, 34.41% (Rho of the total variation is due to the differences within the counties. The Moran's I index in 2000 is negative and close to zero (0.035 suggesting a negative but non-significant spatial autocorrelation. In 2012, the Moran I's suggests a positive and non-significant spatial auto-correlation.

  7. How to statistically analyze nano exposure measurement results: using an ARIMA time series approach

    International Nuclear Information System (INIS)

    Klein Entink, Rinke H.; Fransman, Wouter; Brouwer, Derk H.

    2011-01-01

    Measurement strategies for exposure to nano-sized particles differ from traditional integrated sampling methods for exposure assessment by the use of real-time instruments. The resulting measurement series is a time series, where typically the sequential measurements are not independent from each other but show a pattern of autocorrelation. This article addresses the statistical difficulties when analyzing real-time measurements for exposure assessment to manufactured nano objects. To account for autocorrelation patterns, Autoregressive Integrated Moving Average (ARIMA) models are proposed. A simulation study shows the pitfalls of using a standard t-test and the application of ARIMA models is illustrated with three real-data examples. Some practical suggestions for the data analysis of real-time exposure measurements conclude this article.

  8. Prediction of Second-Order Moments of Inter-Channel Interference with Principal Component Analysis and Neural Networks

    DEFF Research Database (Denmark)

    Jones, Rasmus Thomas; Medeiros Diniz, Júlio César; Yankov, Metodi Plamenov

    2017-01-01

    A machine learning framework for predicting auto-correlation functions of inter-channel nonlinearities within the uncompensated optical fiber link is proposed. Low generalization error is obtained on the test data....

  9. A Digital Correlation Spectrometer Chip with 1 GHz Bandwidth, 4096 Spectral Channels, and 4 W Power Consumption for Passive Microwave Remote Sensing Instruments, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — The scope of this project is to provide a digital auto-correlation spectrometer fabricated on a single integrated circuit for NASA's future Earth-Sun System missions...

  10. Stochastic modelling of the monthly average maximum and minimum temperature patterns in India 1981-2015

    Science.gov (United States)

    Narasimha Murthy, K. V.; Saravana, R.; Vijaya Kumar, K.

    2018-04-01

    The paper investigates the stochastic modelling and forecasting of monthly average maximum and minimum temperature patterns through suitable seasonal auto regressive integrated moving average (SARIMA) model for the period 1981-2015 in India. The variations and distributions of monthly maximum and minimum temperatures are analyzed through Box plots and cumulative distribution functions. The time series plot indicates that the maximum temperature series contain sharp peaks in almost all the years, while it is not true for the minimum temperature series, so both the series are modelled separately. The possible SARIMA model has been chosen based on observing autocorrelation function (ACF), partial autocorrelation function (PACF), and inverse autocorrelation function (IACF) of the logarithmic transformed temperature series. The SARIMA (1, 0, 0) × (0, 1, 1)12 model is selected for monthly average maximum and minimum temperature series based on minimum Bayesian information criteria. The model parameters are obtained using maximum-likelihood method with the help of standard error of residuals. The adequacy of the selected model is determined using correlation diagnostic checking through ACF, PACF, IACF, and p values of Ljung-Box test statistic of residuals and using normal diagnostic checking through the kernel and normal density curves of histogram and Q-Q plot. Finally, the forecasting of monthly maximum and minimum temperature patterns of India for the next 3 years has been noticed with the help of selected model.

  11. Dynamic Assessment on the Landscape Patterns and Spatio-temporal Change in the mainstream of Tarim River

    Science.gov (United States)

    Zhang, Hui; Xue, Lianqing; Yang, Changbing; Chen, Xinfang; Zhang, Luochen; Wei, Guanghui

    2018-01-01

    The Tarim River (TR), as the longest inland river at an arid area in China, is a typical regions of vegetation variation research and plays a crucial role in the sustainable development of regional ecological environment. In this paper, the newest dataset of MODND1M NDVI, at a resolution of 500m, were applied to calculate vegetation index in growing season during the period 2000-2015. Using a vegetation coverage index, a trend line analysis, and the local spatial autocorrelation analysis, this paper investigated the landscape patterns and spatio-temporal variation of vegetation coverage at regional and pixel scales over mainstream of the Tarim River, Xinjiang. The results showed that (1) The bare land area on both sides of Tarim River appeared to have a fluctuated downward trend and there were two obvious valley values in 2005 and 2012. (2) Spatially, the vegetation coverage improved areas is mostly distributed in upstream and the degraded areas is mainly distributed in the left bank of midstream and the end of Tarim River during 2000-2005. (3) The local spatial auto-correlation analysis revealed that vegetation coverage was spatially positive autocorrelated and spatial concentrated. The high-high self-related areas are mainly distributed in upstream, where vegetation cover are relatively good, and the low-low self-related areas are mostly with lower vegetation cover in the lower reaches of Tarim River.

  12. PENGEMBANGAN DAN APLIKASI GEOINFORMATIKA BAYESIAN PADA DATA KEMISKINAN DI INDONESIA (STUDI KASUS JAWA TIMUR

    Directory of Open Access Journals (Sweden)

    Asep Saefuddin

    2012-08-01

    Full Text Available Since a long time ago, poverty has been a problem that can not be solved. Indonesia’s Central Beureu of Statistics (CBS survey on March 2011 show that there are 30.02 million people or 12.49% of total Indonesian are considered poor. From the point of view of many field of sciences the substance and the method to overcome this problem has become a very interesting topic of research. Based on statistical methods, poverty has become very interesting because there is an issue that there is an autocorrelation between data, spatial autocorrelation, error variance heterogenity, spatial interaction, and other statistical issues. The main objective of this research is to find factors that influence poverty rate in a region by developing spatial bayesian statistics. The methods developed in this research include Simultan Autoregressive (SAR, Conditional Autoregressive (CAR, Geographically Weighted Regression (GWR, Small Area Estimation (SAE and hotspot detection. Based on the SAR Bayes model it is shown that the percented of people not graduating elementary school has a significant effect on poverty rate. While the increase of spatial autocorrelation will influence the poverty rate by 0.10 in East Java. Beside that by using hierarchical bayes logit normal model with nearest neighboor spatial weighted found that 40.93% of families of Jember is considered poor.

  13. Lagrangian velocity correlations in homogeneous isotropic turbulence

    International Nuclear Information System (INIS)

    Gotoh, T.; Rogallo, R.S.; Herring, J.R.; Kraichnan, R.H.

    1993-01-01

    The Lagrangian velocity autocorrelation and the time correlations for individual wave-number bands are computed by direct numerical simulation (DNS) using the passive vector method (PVM), and the accuracy of the method is studied. It is found that the PVM is accurate when K max /k d ≥2 where K max is the maximum wave number carried in the simulation and k d is the Kolmogorov wave number. The Eulerian and Lagrangian time correlations for various wave-number bands are compared. At moderate to high wave number the Eulerian time correlation decays faster than the Lagrangian, and the effect of sweep on the former is observed. The time scale of the Eulerian correlation is found to be (kU 0 ) -1 while that of the Lagrangian is [∫ 0 k p 2 E(p)dp] -1/2 . The Lagrangian velocity autocorrelation in a frozen turbulent field is computed using the DIA, ALHDIA, and LRA theories and is compared with DNS measurements. The Markovianized Lagrangian renormalized approximation (MLRA) is compared with the DNS, and good agreement is found for one-time quantities in decaying turbulence at low Reynolds numbers and for the Lagrangian velocity autocorrelation in stationary turbulence at moderate Reynolds number. The effect of non-Gaussianity on the Lagrangian correlation predicted by the theories is also discussed

  14. Ecological Pressure of Carbon Footprint in Passenger Transport: Spatio-Temporal Changes and Regional Disparities

    Directory of Open Access Journals (Sweden)

    Fei Ma

    2018-01-01

    Full Text Available Passenger transport has become a significant producer of carbon emissions in China, thus strongly contributing to climate change. In this paper, we first propose a model of ecological pressure of the carbon footprint in passenger transport (EPcfpt. In the model, the EPcfpt values of all the provinces and autonomous regions of China are calculated and analyzed during the period of 2006–2015. For the outlier EPcfpt values of Beijing, Shanghai and Tianjin, the research areas are classified into two scenarios: the first scenario (all the provinces and autonomous regions and the second scenario (not including Beijing, Shanghai and Tianjin. The global spatial autocorrelation analysis of the first scenario shows that the EPcfpt might be randomly distributed, while it shows positive spatial autocorrelation in the second scenario. Furthermore, we carry out the local spatial autocorrelation analysis of the second scenario, and find that the low aggregation areas are the most common type and are mainly located in the west of China. Then the disparities in EPcfpt between China’s Eight Comprehensive Economic Zones are further analyzed. Finally, we put forward a number of policy recommendations in relation to the spatio-temporal changes and the regional disparities of EPcfpt in China. This study provides related references for proposing effective policy measures to reduce the ecological pressure of carbon emissions from the passenger transport sector.

  15. EDQNM model of a passive scalar with a uniform mean gradient

    International Nuclear Information System (INIS)

    Herr, S.; Wang, L.; Collins, L.R.

    1996-01-01

    Dynamic equations for the scalar autocorrelation and scalar-velocity cross correlation spectra have been derived for a passive scalar with a uniform mean gradient using the Eddy Damped Quasi Normal Markovian (EDQNM) theory. The presence of a mean gradient in the scalar field makes all correlations involving the scalar axisymmetric with respect to the axis pointing in the direction of the mean gradient. Equivalently, all scalar spectra will be functions of the wave number k and the cosine of the azimuthal angle designated as μ. In spite of this complication, it is shown that the cross correlation vector can be completely characterized by a single scalar function Q(k). The scalar autocorrelation spectrum, in contrast, has an unknown dependence on μ. However, this dependency can be expressed as an infinite sum of Legendre polynomials of μ, as first suggested by Herring [Phys. Fluids 17, 859 (1974)]. Furthermore, since the scalar field is initially zero, terms beyond the second order of the Legendre expansion are shown to be exactly zero. The energy, scalar autocorrelation, and scalar-velocity cross correlation were solved numerically from the EDQNM equations and compared to results from direct numerical simulations. The results show that the EDQNM theory is effective in describing single-point and spectral statistics of a passive scalar in the presence of a mean gradient. copyright 1996 American Institute of Physics

  16. Long-range autocorrelations of CpG islands in the human genome.

    Directory of Open Access Journals (Sweden)

    Benjamin Koester

    Full Text Available In this paper, we use a statistical estimator developed in astrophysics to study the distribution and organization of features of the human genome. Using the human reference sequence we quantify the global distribution of CpG islands (CGI in each chromosome and demonstrate that the organization of the CGI across a chromosome is non-random, exhibits surprisingly long range correlations (10 Mb and varies significantly among chromosomes. These correlations of CGI summarize functional properties of the genome that are not captured when considering variation in any particular separate (and local feature. The demonstration of the proposed methods to quantify the organization of CGI in the human genome forms the basis of future studies. The most illuminating of these will assess the potential impact on phenotypic variation of inter-individual variation in the organization of the functional features of the genome within and among chromosomes, and among individuals for particular chromosomes.

  17. Investigation of gas discharge processes in PMTs by the autocorrelation method

    International Nuclear Information System (INIS)

    Morozov, V.A.; Morozova, N.V.

    2012-01-01

    The effect of the potential different at the focusing chamber electrodes of the FEU-85, FEU-87, and FEU-93 photomultipliers on the intensity of afterpulses resulting from gas discharge processes is investigated. With appropriately selected potentials, the number of recorded secondary pulses can be decreased. Charge distribution spectra are obtained for this sort of pulses, which gives a qualitative estimate of both the homogeneity of the charge and mass distribution of residual gases and the ion-electron emission coefficients

  18. A TR-UWB Downconversion Autocorrelation Receiver for Wireless Body Area Network

    Directory of Open Access Journals (Sweden)

    Islam SMRiazul

    2009-01-01

    Full Text Available Low power UWB receiver architecture is proposed for a Wireless Body Area Network (WBAN. This receiving technology is a synergy of existing downconversion-based narrowband rejection mechanism in RF front end and signal processing in frequency domain. Frequency components of converted and filtered UWB pulses are separated into real and imaginary parts, independently correlated and effectively combined to achieve an improved output Signal to noise ratio (SNR. An extensive mathematical analysis has been performed to formulate the close-form expressions for SNRs in order to compare system performances toward favorable BER under BPSK modulation scheme. Analysis shows that optimal rotation of coordination plays an important role for the enhancement of receiving SNR which is further confirmed by computer simulation. A wide range of link level simulation (LLS urges that the proposed system is more power efficient in higher-order modulation (HOM schemes. Transmitted Reference (TR scheme has been considered as the basis for wideband communication.

  19. Correlation factor, velocity autocorrelation function and frequency-dependent tracer diffusion coefficient

    NARCIS (Netherlands)

    Beijeren, H. van; Kehr, K.W.

    1986-01-01

    The correlation factor, defined as the ratio between the tracer diffusion coefficient in lattice gases and the diffusion coefficient for a corresponding uncorrelated random walk, is known to assume a very simple form under certain conditions. A simple derivation of this is given with the aid of

  20. Environmental correlates of the patterns of plant distribution at the mesoscale: a case study from Northern Bohemia (Czech Republic)

    Czech Academy of Sciences Publication Activity Database

    Petřík, Petr; Wild, Jan

    2006-01-01

    Roč. 78, - (2006), s. 211-234 ISSN 0032-7786 Institutional research plan: CEZ:AV0Z60050516 Keywords : biogeography * flora * spatial autocorrelation Subject RIV: EF - Botanics Impact factor: 2.119, year: 2006

  1. Neighborhood interactions influencing tree population dynamics in nonpyrogenous boreal forest in northern Finland

    Czech Academy of Sciences Publication Activity Database

    Doležal, Jiří; Šrůtek, Miroslav; Hara, T.; Sumida, A.; Penttilä, T.

    2006-01-01

    Roč. 185, - (2006), s. 135-150 ISSN 1385-0237 Institutional research plan: CEZ:AV0Z60050516 Keywords : competition * spatial size autocorrelation * Picea Subject RIV: EF - Botanics Impact factor: 1.383, year: 2006

  2. Temporal trend and climate factors of hemorrhagic fever with renal syndrome epidemic in Shenyang City, China

    Directory of Open Access Journals (Sweden)

    Liu Xiaodong

    2011-12-01

    Full Text Available Abstract Background Hemorrhagic fever with renal syndrome (HFRS is an important infectious disease caused by different species of hantaviruses. As a rodent-borne disease with a seasonal distribution, external environmental factors including climate factors may play a significant role in its transmission. The city of Shenyang is one of the most seriously endemic areas for HFRS. Here, we characterized the dynamic temporal trend of HFRS, and identified climate-related risk factors and their roles in HFRS transmission in Shenyang, China. Methods The annual and monthly cumulative numbers of HFRS cases from 2004 to 2009 were calculated and plotted to show the annual and seasonal fluctuation in Shenyang. Cross-correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on HFRS transmission and the autocorrelation of monthly HFRS cases. Principal component analysis was constructed by using climate data from 2004 to 2009 to extract principal components of climate factors to reduce co-linearity. The extracted principal components and autocorrelation terms of monthly HFRS cases were added into a multiple regression model called principal components regression model (PCR to quantify the relationship between climate factors, autocorrelation terms and transmission of HFRS. The PCR model was compared to a general multiple regression model conducted only with climate factors as independent variables. Results A distinctly declining temporal trend of annual HFRS incidence was identified. HFRS cases were reported every month, and the two peak periods occurred in spring (March to May and winter (November to January, during which, nearly 75% of the HFRS cases were reported. Three principal components were extracted with a cumulative contribution rate of 86.06%. Component 1 represented MinRH0, MT1, RH1, and MWV1; component 2 represented RH2, MaxT3, and MAP3; and component 3 represented MaxT2, MAP2, and MWV2. The PCR model

  3. Propagation of mechanical waves through a stochastic medium with spherical symmetry

    Science.gov (United States)

    Avendaño, Carlos G.; Reyes, J. Adrián

    2018-01-01

    We theoretically analyze the propagation of outgoing mechanical waves through an infinite isotropic elastic medium possessing spherical symmetry whose Lamé coefficients and density are spatial random functions characterized by well-defined statistical parameters. We derive the differential equation that governs the average displacement for a system whose properties depend on the radial coordinate. We show that such an equation is an extended version of the well-known Bessel differential equation whose perturbative additional terms contain coefficients that depend directly on the squared noise intensities and the autocorrelation lengths in an exponential decay fashion. We numerically solve the second order differential equation for several values of noise intensities and autocorrelation lengths and compare the corresponding displacement profiles with that of the exact analytic solution for the case of absent inhomogeneities.

  4. A Change Oriented Extension of EOF Analysis Applied to the 1996-1997 AVHRR Sea Surface Temperature Data

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Conradsen, Knut; Andersen, Ole Baltazar

    2002-01-01

    correlation analysis, and maximum autocorrelation factors (MAFs). The method described can be considered as an extension to EOF analysis that is specially tailored for change detection in spatial data since it first maximises differences in the data between two points in time and then maximises...... autocorrelation between neighbouring observations. The results show that the large scale ocean events associated with the El Nino/Southern Oscillation (ENSO) related changes are concentrated in the first SST MAF/MAD mode and the two first SSH MAF/MAD modes. The MAD/MAF analysis also revealed a spatially...... correlated structure in the Western Mediterranean Sea that turned out to be related to a strong semi-annual variation in the SST for 1997 which was difficult to resolve from a traditional principal component analysis....

  5. Asymptotic neutron scattering laws for anomalously diffusing quantum particles

    Energy Technology Data Exchange (ETDEWEB)

    Kneller, Gerald R. [Centre de Biophysique Moléculaire, CNRS, Rue Charles Sadron, 45071 Orléans (France); Université d’Orléans, Chateau de la Source-Ave. du Parc Floral, 45067 Orléans (France); Synchrotron-SOLEIL, L’Orme de Merisiers, 91192 Gif-sur-Yvette (France)

    2016-07-28

    The paper deals with a model-free approach to the analysis of quasielastic neutron scattering intensities from anomalously diffusing quantum particles. All quantities are inferred from the asymptotic form of their time-dependent mean square displacements which grow ∝t{sup α}, with 0 ≤ α < 2. Confined diffusion (α = 0) is here explicitly included. We discuss in particular the intermediate scattering function for long times and the Fourier spectrum of the velocity autocorrelation function for small frequencies. Quantum effects enter in both cases through the general symmetry properties of quantum time correlation functions. It is shown that the fractional diffusion constant can be expressed by a Green-Kubo type relation involving the real part of the velocity autocorrelation function. The theory is exact in the diffusive regime and at moderate momentum transfers.

  6. A new kinetic description for turbulent collisions including mode-coupling

    International Nuclear Information System (INIS)

    Misguich, J.H.; Tchen, C.M.

    1982-07-01

    The usual introduction of higher-order mode-coupling terms in the description of turbulent collisions beyond usual Renormalized Quasi-Linear approximation (RQL) is briefly analyzed. Here new results are derived in the framework of the general kinetic theory, and the equivalence is proved with the long time limit of simple results deduced from the Vlasov equation. The correction to the RQL turbulent collision term is analyzed and a new approximation is proposed. Turbulent collisions are also described by perturbation around the Lagrangian autocorrelation of fluctuating fields. For an homogeneous turbulence, however, the asymptotic integral of this Lagrangian autocorrelation vanishes identically, similarly to what occurs in Brownian motion. For inhomogeneous turbulence this method can nevertheless be used, and higher-order mode-coupling terms can be interpreted as a shielding of elementary Lagrangian turbulent collisions

  7. Low Streamflow Forcasting using Minimum Relative Entropy

    Science.gov (United States)

    Cui, H.; Singh, V. P.

    2013-12-01

    Minimum relative entropy spectral analysis is derived in this study, and applied to forecast streamflow time series. Proposed method extends the autocorrelation in the manner that the relative entropy of underlying process is minimized so that time series data can be forecasted. Different prior estimation, such as uniform, exponential and Gaussian assumption, is taken to estimate the spectral density depending on the autocorrelation structure. Seasonal and nonseasonal low streamflow series obtained from Colorado River (Texas) under draught condition is successfully forecasted using proposed method. Minimum relative entropy determines spectral of low streamflow series with higher resolution than conventional method. Forecasted streamflow is compared to the prediction using Burg's maximum entropy spectral analysis (MESA) and Configurational entropy. The advantage and disadvantage of each method in forecasting low streamflow is discussed.

  8. The Curious Case of Soft Matter Ranjini Bandyopadhyay Raman ...

    Indian Academy of Sciences (India)

    ranjeetha

    My research interests: structure, dynamics, phase behavior and flow of 'soft' ... Examples of soft materials ... You can study them with a microscope, by autocorrelating scattered light intensity ... on the application of very small applied forces.

  9. minimum variance estimation of yield parameters of rubber tree

    African Journals Online (AJOL)

    2013-03-01

    Mar 1, 2013 ... It is our opinion that Kalman filter is a robust estimator of the ... Kalman filter, parameter estimation, rubber clones, Chow failure test, autocorrelation, STAMP, data ...... Mills, T.C. Modelling Current Temperature Trends.

  10. Cryptographic pseudo-random sequences from the chaotic Hénon ...

    Indian Academy of Sciences (India)

    dimensional discrete-time Hénon map is proposed. Properties of the proposed sequences pertaining to linear complexity, linear complexity profile, correlation and auto-correlation are investigated. All these properties of the sequences suggest a ...

  11. A comparative study of the performances of some estimators of ...

    African Journals Online (AJOL)

    In linear regression model, regressors are assumed fixed in repeated sampling. ... error terms when normally distributed regressors are fixed (non – stochastic) with ... of the estimated parameter of the model at different levels of autocorrelation ...

  12. Molecular dynamics of liquid alkaline-earth metals near the melting ...

    Indian Academy of Sciences (India)

    computed the velocity autocorrelation function (VACF), its memory function and ... Since alkaline-earth metals are simple like metals, the main difficulty in the calcu- lation of ..... recall that the conventional binding energy can be written [23] as.

  13. Small area-level variation in the incidence of psychotic disorders in an urban area in France: an ecological study.

    Science.gov (United States)

    Szoke, Andrei; Pignon, Baptiste; Baudin, Grégoire; Tortelli, Andrea; Richard, Jean-Romain; Leboyer, Marion; Schürhoff, Franck

    2016-07-01

    We sought to determine whether significant variation in the incidence of clinically relevant psychoses existed at an ecological level in an urban French setting, and to examine possible factors associated with this variation. We aimed to advance the literature by testing this hypothesis in a novel population setting and by comparing a variety of spatial models. We sought to identify all first episode cases of non-affective and affective psychotic disorders presenting in a defined urban catchment area over a 4 years period, over more than half a million person-years at-risk. Because data from geographic close neighbourhoods usually show spatial autocorrelation, we used for our analyses Bayesian modelling. We included small area neighbourhood measures of deprivation, migrants' density and social fragmentation as putative explanatory variables in the models. Incidence of broad psychotic disorders shows spatial patterning with the best fit for models that included both strong autocorrelation between neighbouring areas and weak autocorrelation between areas further apart. Affective psychotic disorders showed similar spatial patterning and were associated with the proportion of migrants/foreigners in the area (inverse correlation). In contrast, non-affective psychoses did not show spatial patterning. At ecological level, the variation in the number of cases and the factors that influence this variation are different for non-affective and affective psychotic disorders. Important differences in results-compared with previous studies in different settings-point to the importance of the context and the necessity of further studies to understand these differences.

  14. A statistical physics view of pitch fluctuations in the classical music from Bach to Chopin: evidence for scaling.

    Science.gov (United States)

    Liu, Lu; Wei, Jianrong; Zhang, Huishu; Xin, Jianhong; Huang, Jiping

    2013-01-01

    Because classical music has greatly affected our life and culture in its long history, it has attracted extensive attention from researchers to understand laws behind it. Based on statistical physics, here we use a different method to investigate classical music, namely, by analyzing cumulative distribution functions (CDFs) and autocorrelation functions of pitch fluctuations in compositions. We analyze 1,876 compositions of five representative classical music composers across 164 years from Bach, to Mozart, to Beethoven, to Mendelsohn, and to Chopin. We report that the biggest pitch fluctuations of a composer gradually increase as time evolves from Bach time to Mendelsohn/Chopin time. In particular, for the compositions of a composer, the positive and negative tails of a CDF of pitch fluctuations are distributed not only in power laws (with the scale-free property), but also in symmetry (namely, the probability of a treble following a bass and that of a bass following a treble are basically the same for each composer). The power-law exponent decreases as time elapses. Further, we also calculate the autocorrelation function of the pitch fluctuation. The autocorrelation function shows a power-law distribution for each composer. Especially, the power-law exponents vary with the composers, indicating their different levels of long-range correlation of notes. This work not only suggests a way to understand and develop music from a viewpoint of statistical physics, but also enriches the realm of traditional statistical physics by analyzing music.

  15. Signal-to-noise ratio enhancement on SEM images using a cubic spline interpolation with Savitzky-Golay filters and weighted least squares error.

    Science.gov (United States)

    Kiani, M A; Sim, K S; Nia, M E; Tso, C P

    2015-05-01

    A new technique based on cubic spline interpolation with Savitzky-Golay smoothing using weighted least squares error filter is enhanced for scanning electron microscope (SEM) images. A diversity of sample images is captured and the performance is found to be better when compared with the moving average and the standard median filters, with respect to eliminating noise. This technique can be implemented efficiently on real-time SEM images, with all mandatory data for processing obtained from a single image. Noise in images, and particularly in SEM images, are undesirable. A new noise reduction technique, based on cubic spline interpolation with Savitzky-Golay and weighted least squares error method, is developed. We apply the combined technique to single image signal-to-noise ratio estimation and noise reduction for SEM imaging system. This autocorrelation-based technique requires image details to be correlated over a few pixels, whereas the noise is assumed to be uncorrelated from pixel to pixel. The noise component is derived from the difference between the image autocorrelation at zero offset, and the estimation of the corresponding original autocorrelation. In the few test cases involving different images, the efficiency of the developed noise reduction filter is proved to be significantly better than those obtained from the other methods. Noise can be reduced efficiently with appropriate choice of scan rate from real-time SEM images, without generating corruption or increasing scanning time. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

  16. Robust statistics for deterministic and stochastic gravitational waves in non-Gaussian noise. II. Bayesian analyses

    International Nuclear Information System (INIS)

    Allen, Bruce; Creighton, Jolien D.E.; Flanagan, Eanna E.; Romano, Joseph D.

    2003-01-01

    In a previous paper (paper I), we derived a set of near-optimal signal detection techniques for gravitational wave detectors whose noise probability distributions contain non-Gaussian tails. The methods modify standard methods by truncating or clipping sample values which lie in those non-Gaussian tails. The methods were derived, in the frequentist framework, by minimizing false alarm probabilities at fixed false detection probability in the limit of weak signals. For stochastic signals, the resulting statistic consisted of a sum of an autocorrelation term and a cross-correlation term; it was necessary to discard 'by hand' the autocorrelation term in order to arrive at the correct, generalized cross-correlation statistic. In the present paper, we present an alternative derivation of the same signal detection techniques from within the Bayesian framework. We compute, for both deterministic and stochastic signals, the probability that a signal is present in the data, in the limit where the signal-to-noise ratio squared per frequency bin is small, where the signal is nevertheless strong enough to be detected (integrated signal-to-noise ratio large compared to 1), and where the total probability in the non-Gaussian tail part of the noise distribution is small. We show that, for each model considered, the resulting probability is to a good approximation a monotonic function of the detection statistic derived in paper I. Moreover, for stochastic signals, the new Bayesian derivation automatically eliminates the problematic autocorrelation term

  17. A statistical physics view of pitch fluctuations in the classical music from Bach to Chopin: evidence for scaling.

    Directory of Open Access Journals (Sweden)

    Lu Liu

    Full Text Available Because classical music has greatly affected our life and culture in its long history, it has attracted extensive attention from researchers to understand laws behind it. Based on statistical physics, here we use a different method to investigate classical music, namely, by analyzing cumulative distribution functions (CDFs and autocorrelation functions of pitch fluctuations in compositions. We analyze 1,876 compositions of five representative classical music composers across 164 years from Bach, to Mozart, to Beethoven, to Mendelsohn, and to Chopin. We report that the biggest pitch fluctuations of a composer gradually increase as time evolves from Bach time to Mendelsohn/Chopin time. In particular, for the compositions of a composer, the positive and negative tails of a CDF of pitch fluctuations are distributed not only in power laws (with the scale-free property, but also in symmetry (namely, the probability of a treble following a bass and that of a bass following a treble are basically the same for each composer. The power-law exponent decreases as time elapses. Further, we also calculate the autocorrelation function of the pitch fluctuation. The autocorrelation function shows a power-law distribution for each composer. Especially, the power-law exponents vary with the composers, indicating their different levels of long-range correlation of notes. This work not only suggests a way to understand and develop music from a viewpoint of statistical physics, but also enriches the realm of traditional statistical physics by analyzing music.

  18. A Statistical Toolbox For Mining And Modeling Spatial Data

    Directory of Open Access Journals (Sweden)

    D’Aubigny Gérard

    2016-12-01

    Full Text Available Most data mining projects in spatial economics start with an evaluation of a set of attribute variables on a sample of spatial entities, looking for the existence and strength of spatial autocorrelation, based on the Moran’s and the Geary’s coefficients, the adequacy of which is rarely challenged, despite the fact that when reporting on their properties, many users seem likely to make mistakes and to foster confusion. My paper begins by a critical appraisal of the classical definition and rational of these indices. I argue that while intuitively founded, they are plagued by an inconsistency in their conception. Then, I propose a principled small change leading to corrected spatial autocorrelation coefficients, which strongly simplifies their relationship, and opens the way to an augmented toolbox of statistical methods of dimension reduction and data visualization, also useful for modeling purposes. A second section presents a formal framework, adapted from recent work in statistical learning, which gives theoretical support to our definition of corrected spatial autocorrelation coefficients. More specifically, the multivariate data mining methods presented here, are easily implementable on the existing (free software, yield methods useful to exploit the proposed corrections in spatial data analysis practice, and, from a mathematical point of view, whose asymptotic behavior, already studied in a series of papers by Belkin & Niyogi, suggests that they own qualities of robustness and a limited sensitivity to the Modifiable Areal Unit Problem (MAUP, valuable in exploratory spatial data analysis.

  19. Management actions and initiatives for bluefin tuna over the past ...

    African Journals Online (AJOL)

    spamer

    structure, and (3) autocorrelation in recruitment processes is considered within the likelihood framework of the model. .... The inclusion ... Cpue values for Age 4 for two recent years of the as- .... reflects the amount of change (over time period.

  20. Multiscale dipole relaxation in dielectric materials

    DEFF Research Database (Denmark)

    Hansen, Jesper Schmidt

    2016-01-01

    Dipole relaxation from thermally induced perturbations is investigated on different length scales for dielectric materials. From the continuum dynamical equations for the polarisation, expressions for the transverse and longitudinal dipole autocorrelation functions are derived in the limit where ...

  1. Visualizing Influential Observations in Dependent Data

    KAUST Repository

    Genton, Marc G.; Ruiz-Gazen, Anne

    2010-01-01

    , and indices of spatial autocorrelation such as Moran's I belong to the second case.We illustrate our approach on various datasets from time series analysis and spatial statistics. This article has supplementary material online. © 2010 American Statistical

  2. Auto-correlograms and auto-regressive models of trace metal distributions in Cochin backwaters

    Digital Repository Service at National Institute of Oceanography (India)

    Jayalakshmy, K.V.; Sankaranarayanan, V.N.

    Auto-correlation technique has been applied to study fluctuations in concentration profiles of chemical species in Cochin Backwaters (Kerala, India). No stability in time can be detected for particulate Mn at all stations, for Fe at stations 1...

  3. Application of computer intensive data analysis methods to the analysis of digital images and spatial data

    DEFF Research Database (Denmark)

    Windfeld, Kristian

    1992-01-01

    Computer-intensive methods for data analysis in a traditional setting has developed rapidly in the last decade. The application of and adaption of some of these methods to the analysis of multivariate digital images and spatial data are explored, evaluated and compared to well established classical...... into the projection pursuit is presented. Examples from remote sensing are given. The ACE algorithm for computing non-linear transformations for maximizing correlation is extended and applied to obtain a non-linear transformation that maximizes autocorrelation or 'signal' in a multivariate image....... This is a generalization of the minimum /maximum autocorrelation factors (MAF's) which is a linear method. The non-linear method is compared to the linear method when analyzing a multivariate TM image from Greenland. The ACE method is shown to give a more detailed decomposition of the image than the MAF-transformation...

  4. Statistical 2D and 3D shape analysis using Non-Euclidean Metrics

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Hilger, Klaus Baggesen; Wrobel, Mark Christoph

    2002-01-01

    We address the problem of extracting meaningful, uncorrelated biological modes of variation from tangent space shape coordinates in 2D and 3D using non-Euclidean metrics. We adapt the maximum autocorrelation factor analysis and the minimum noise fraction transform to shape decomposition. Furtherm......We address the problem of extracting meaningful, uncorrelated biological modes of variation from tangent space shape coordinates in 2D and 3D using non-Euclidean metrics. We adapt the maximum autocorrelation factor analysis and the minimum noise fraction transform to shape decomposition....... Furthermore, we study metrics based on repated annotations of a training set. We define a way of assessing the correlation between landmarks contrary to landmark coordinates. Finally, we apply the proposed methods to a 2D data set consisting of outlines of lungs and a 3D/(4D) data set consisting of sets...

  5. Frequency spectrum analysis of 252Cf neutron source based on LabVIEW

    International Nuclear Information System (INIS)

    Mi Deling; Li Pengcheng

    2011-01-01

    The frequency spectrum analysis of 252 Cf Neutron source is an extremely important method in nuclear stochastic signal processing. Focused on the special '0' and '1' structure of neutron pulse series, this paper proposes a fast-correlation algorithm to improve the computational rate of the spectrum analysis system. And the multi-core processor technology is employed as well as multi-threaded programming techniques of LabVIEW to construct frequency spectrum analysis system of 252 Cf neutron source based on LabVIEW. It not only obtains the auto-correlation and cross correlation results, but also auto-power spectrum,cross-power spectrum and ratio of spectral density. The results show that: analysis tools based on LabVIEW improve the fast auto-correlation and cross correlation code operating efficiency about by 25% to 35%, also verify the feasibility of using LabVIEW for spectrum analysis. (authors)

  6. Probabilistic Load Models for Simulating the Impact of Load Management

    DEFF Research Database (Denmark)

    Chen, Peiyuan; Bak-Jensen, Birgitte; Chen, Zhe

    2009-01-01

    . It is concluded that the AR(12) model is favored with limited measurement data and that the joint-normal model may provide better results with a large data set. Both models can be applied in general to model load time series and used in time-sequential simulation of distribution system planning.......This paper analyzes a distribution system load time series through autocorrelation coefficient, power spectral density, probabilistic distribution and quantile value. Two probabilistic load models, i.e. the joint-normal model and the autoregressive model of order 12 (AR(12)), are proposed...... to simulate the impact of load management. The joint-normal model is superior in modeling the tail region of the hourly load distribution and implementing the change of hourly standard deviation. Whereas the AR(12) model requires much less parameter and is superior in modeling the autocorrelation...

  7. On the structure of dynamic principal component analysis used in statistical process monitoring

    DEFF Research Database (Denmark)

    Vanhatalo, Erik; Kulahci, Murat; Bergquist, Bjarne

    2017-01-01

    When principal component analysis (PCA) is used for statistical process monitoring it relies on the assumption that data are time independent. However, industrial data will often exhibit serial correlation. Dynamic PCA (DPCA) has been suggested as a remedy for high-dimensional and time...... for determining the number of principal components to retain. The number of retained principal components is determined by visual inspection of the serial correlation in the squared prediction error statistic, Q (SPE), together with the cumulative explained variance of the model. The methods are illustrated using...... driven method to determine the maximum number of lags in DPCA with a foundation in multivariate time series analysis. The method is based on the behavior of the eigenvalues of the lagged autocorrelation and partial autocorrelation matrices. Given a specific lag structure we also propose a method...

  8. Extended families of 2D arrays with near optimal auto and low cross-correlation

    Science.gov (United States)

    Svalbe, I. D.; Tirkel, A. Z.

    2017-12-01

    Families of 2D arrays can be constructed where each array has perfect autocorrelation, and the cross-correlation between any pair of family members is optimally low. We exploit equivalent Hadamard matrices to construct many families of p p × p arrays, where p is any 4k-1 prime. From these families, we assemble extended families of arrays with members that exhibit perfect autocorrelation and next-to-optimally low cross-correlation. Pseudo-Hadamard matrices are used to construct extended families using p = 4k + 1 primes. An optimal family of 31 31 × 31 perfect arrays can provide copyright protection to uniquely stamp a robust, low-visibility watermark within every frame of each second of high-definition, 30 fps video. The extended families permit the embedding of many more perfect watermarks that have next-to-minimal cross-correlations.

  9. Fluctuations of two-time quantities and non-linear response functions

    International Nuclear Information System (INIS)

    Corberi, F; Lippiello, E; Sarracino, A; Zannetti, M

    2010-01-01

    We study the fluctuations of the autocorrelation and autoresponse functions and, in particular, their variances and covariance. In a first general part of the paper, we show the equivalence of the variance of the response function to the second-order susceptibility of a composite operator, and we derive an equilibrium fluctuation-dissipation theorem beyond linear order, relating it to the other variances. In a second part of the paper we apply the formalism in the study of non-disordered ferromagnets, in equilibrium or in the coarsening kinetics following a critical or sub-critical quench. We show numerically that the variances and the non-linear susceptibility obey scaling with respect to the coherence length ξ in equilibrium, and with respect to the growing length L(t) after a quench, similar to what is known for the autocorrelation and the autoresponse functions

  10. Feeding ecology and phylogenetic structure of a complex neotropical termite assemblage, revealed by nitrogen stable isotope ratios

    Czech Academy of Sciences Publication Activity Database

    Bourguignon, T.; Šobotník, Jan; Lepoint, G.; Martin, J. M.; Hardy, O. J.; Dejean, A.; Roisin, Y.

    2011-01-01

    Roč. 36, č. 2 (2011), s. 261-269 ISSN 0307-6946 Institutional research plan: CEZ:AV0Z40550506 Keywords : diet diversity * feeding groups * Isoptera * phylogenetic autocorrelation Subject RIV: CC - Organic Chemistry Impact factor: 1.995, year: 2011

  11. On some asymptotic relations in the Boltzmann-Enskog model

    International Nuclear Information System (INIS)

    Sadovnikov, B.I.; Inozemtseva, N.G.

    1977-04-01

    The coefficients in the tsup(-3/2) asymptotics of the time autocorrelation functions are successively determined in the framework of the non-linear Boltzmann-Enskog model. The left and right eigenfunction systems are constructed for the Boltzmann-Enskog operator

  12. Hyperspectral data mining to identify relevant canopy spectral features for estimating durum wheat growth, nitrogen status, and yield

    Science.gov (United States)

    Modern hyperspectral sensors permit reflectance measurements of crop canopies in hundreds of narrow spectral wavebands. While these sensors describe plant canopy reflectance in greater detail than multispectral sensors, they also suffer from issues with data redundancy and spectral autocorrelation. ...

  13. Diagnostic checking in linear processes with infinit variance

    OpenAIRE

    Krämer, Walter; Runde, Ralf

    1998-01-01

    We consider empirical autocorrelations of residuals from infinite variance autoregressive processes. Unlike the finite-variance case, it emerges that the limiting distribution, after suitable normalization, is not always more concentrated around zero when residuals rather than true innovations are employed.

  14. Single Trial Brain Electrical Patterns of an Auditory and Visual Perceptuomotor Task.

    Science.gov (United States)

    1983-06-01

    approached this issue with scalp-recorded EEGs (Wolter and Shipton, 1951; Brazier and Casby, 1952; Callaway and Harris, 1974; Busk and Galbraith, 1975...autocorrelation studies of electroencephalographic potentials. Electroencephalorphv Clinical NourophvsioloQv, 1952, 4, 201-211. Busk , J. and Galbraith

  15. Research Article Special Issue

    African Journals Online (AJOL)

    pc

    2018-05-01

    May 1, 2018 ... Concerning the development about cellular and furthermore mobile satellite ... telephony Furthermore actually satellite telephone conferencing. ... noise, Linear Prediction coding might make finished by perusing those autocorrelation .... In this project, a usage about utilizing Kalman filtering to speech ...

  16. Seismic interferometry : Reconstructing the earth's reflection response

    NARCIS (Netherlands)

    Draganov, D.S.; Wapenaar, C.P.A.; Thorbecke, J.W.

    2006-01-01

    In 1968, Jon Claerbout showed that the reflection response of a 1D acoustic medium can be reconstructed by autocorrelating the transmission response. Since then, several authors have derived relationships for reconstructing Green's functions at the surface, using crosscorrelations of (noise)

  17. Inhomogeneous Linear Random Differential Equations with Mutual Correlations between Multiplicative, Additive and Initial-Value Terms

    NARCIS (Netherlands)

    Roerdink, J.B.T.M.

    1981-01-01

    The cumulant expansion for linear stochastic differential equations is extended to the general case in which the coefficient matrix, the inhomogeneous part and the initial condition are all random and, moreover, statistically interdependent. The expansion now involves not only the autocorrelation

  18. The Superstatistical Nature and Interoccurrence Time of Atmospheric Mercury Concentration Fluctuations

    Science.gov (United States)

    The probability density function (PDF) of the time intervals between subsequent extreme events in atmospheric Hg0 concentration data series from different latitudes has been investigated. The Hg0 dynamic possesses a long-term memory autocorrelation function. Above a fixed thresh...

  19. Critical fluctuations in cortical models near instability

    NARCIS (Netherlands)

    Aburn, M.J.; Holmes, C.A.; Roberts, J.A.; Boonstra, T.W.; Breakspear, M.

    2012-01-01

    Computational studies often proceed from the premise that cortical dynamics operate in a linearly stable domain, where fluctuations dissipate quickly and show only short memory. Studies of human electroencephalography (EEG), however, have shown significant autocorrelation at time lags on the scale

  20. A spatiotemporal mixed model to assess the influence of environmental and socioeconomic factors on the incidence of hand, foot and mouth disease

    Directory of Open Access Journals (Sweden)

    Lianfa Li

    2018-02-01

    Full Text Available Abstract Background As a common infectious disease, hand, foot and mouth disease (HFMD is affected by multiple environmental and socioeconomic factors, and its pathogenesis is complex. Furthermore, the transmission of HFMD is characterized by strong spatial clustering and autocorrelation, and the classical statistical approach may be biased without consideration of spatial autocorrelation. In this paper, we propose to embed spatial characteristics into a spatiotemporal additive model to improve HFMD incidence assessment. Methods Using incidence data (6439 samples from 137 monitoring district for Shandong Province, China, along with meteorological, environmental and socioeconomic spatial and spatiotemporal covariate data, we proposed a spatiotemporal mixed model to estimate HFMD incidence. Geo-additive regression was used to model the non-linear effects of the covariates on the incidence risk of HFMD in univariate and multivariate models. Furthermore, the spatial effect was constructed to capture spatial autocorrelation at the sub-regional scale, and clusters (hotspots of high risk were generated using spatiotemporal scanning statistics as a predictor. Linear and non-linear effects were compared to illustrate the usefulness of non-linear associations. Patterns of spatial effects and clusters were explored to illustrate the variation of the HFMD incidence across geographical sub-regions. To validate our approach, 10-fold cross-validation was conducted. Results The results showed that there were significant non-linear associations of the temporal index, spatiotemporal meteorological factors and spatial environmental and socioeconomic factors with HFMD incidence. Furthermore, there were strong spatial autocorrelation and clusters for the HFMD incidence. Spatiotemporal meteorological parameters, the normalized difference vegetation index (NDVI, the temporal index, spatiotemporal clustering and spatial effects played important roles as predictors in

  1. Imbalance in Spatial Accessibility to Primary and Secondary Schools in China: Guidance for Education Sustainability

    Directory of Open Access Journals (Sweden)

    Yuan Gao

    2016-11-01

    Full Text Available Compulsory education is an important aspect of the societal development. Meanwhile, education equality safeguards the effectiveness of education systems and is an important part of social equality. This study analyzes the inequality of compulsory education from the perspective of imbalanced spatial distribution. Unlike previous studies that have measured the spatial distribution of education simply based on the spatial position of primary and secondary schools, we explore spatial accessibility based on the shortest travel distance from residents to schools, and then analyze the inequality of compulsory education through the distribution of spatial accessibility. We use 2873 Chinese counties as statistical units, and perform a statistical and graphical analysis of their spatial accessibility using the Theil index and spatial autocorrelation analyses. To analyze the differences in the spatial accessibility distribution on the national and regional levels, we use three partitioned modes: the terrain partitioned mode, the economic development partitioned mode, and the province-level partitioned mode. We then analyze the spatial agglomeration characteristics and distribution patterns of compulsory education accessibility through global autocorrelation, local autocorrelation, and hot-spot and cold-spot analysis. The results demonstrate an obvious imbalance in the distribution of spatial accessibility to compulsory education at the national level. Accessibility and equality in eastern and central regions are significantly better than those in the western region; both are significantly better in coastal regions than in inland regions; and equality alone is better in the municipalities, such as Shanghai, Tianjin, and Chongqing, than in other provinces and autonomous regions. The spatial pattern analysis shows significant global autocorrelation and obvious clusters. Counties in cold-spot areas (clusters of good spatial accessibility are large in number

  2. Searching for the Best Cause: Roles of Mechanism Beliefs, Autocorrelation, and Exploitation

    Science.gov (United States)

    Rottman, Benjamin M.

    2016-01-01

    When testing which of multiple causes (e.g., medicines) works best, the testing sequence has important implications for the validity of the final judgment. Trying each cause for a period of time before switching to the other is important if the causes have tolerance, sensitization, delay, or carryover (TSDC) effects. In contrast, if the outcome…

  3. Femtosecond noncollinear SFG dynamics in autocorrelator setup at low level of photons

    Science.gov (United States)

    Tenishev, Vladimir P.; Persson, A.; Larsson, J.

    2004-06-01

    We report here the characteristics of noncollinear sum frequency generation in nonlinear KDP crystals by ultrashort (80 fsec) IR pulses irradiated by the intense Ti:Sapphire laser and their behavior in single shot auto-crosscorrelator (ACC) configuration. In particular we study the case where one of the beams is very weak. Our aim is to develop a procedure to provide delay time signal between light pulses for time resolved pump probe experiments based on the extraction of the phase-matched SHG spatial distribution by means of pulse shape analysis technique. We intend to apply these results to synchronize a weak short-pulse source and an intense Ti:Sapphire laser and to measure the pulse time jitter between them.

  4. A propagation-separation approach to estimate the autocorrelation in a time-series

    Directory of Open Access Journals (Sweden)

    D. V. Divine

    2008-07-01

    Full Text Available The paper presents an approach to estimate parameters of a local stationary AR(1 time series model by maximization of a local likelihood function. The method is based on a propagation-separation procedure that leads to data dependent weights defining the local model. Using free propagation of weights under homogeneity, the method is capable of separating the time series into intervals of approximate local stationarity. Parameters in different regions will be significantly different. Therefore the method also serves as a test for a stationary AR(1 model. The performance of the method is illustrated by applications to both synthetic data and real time-series of reconstructed NAO and ENSO indices and GRIP stable isotopes.

  5. The festivity effect and liquidity constraints: a test on countries with different calendars

    NARCIS (Netherlands)

    Abadir, K.M.; Spierdijk, L.

    2005-01-01

    We show how investors' liquidity patterns can provide a common framework to explain autocorrelation of returns and volumes, and some calendar anomalies. The method helps us find new anomalies, and contribute to the explanation of older ones. We uncover a \\textquotedblleft festivities

  6. Algorithmic design considerations for geospatial and/or temporal big data

    CSIR Research Space (South Africa)

    Van Zyl, T

    2014-02-01

    Full Text Available Mining. In addition, ignoring the spatiotemporal autocorrelation in the data can lead to spurious results, for instance, the salt and pepper effect when clustering. The solution to the big data challenge is simple to describe yet in most cases...

  7. Statistical analysis of simulation-generated time series : Systolic vs. semi-systolic correlation on the Connection Machine

    NARCIS (Netherlands)

    Dontje, T.; Lippert, Th.; Petkov, N.; Schilling, K.

    1992-01-01

    Autocorrelation becomes an increasingly important tool to verify improvements in the state of the simulational art in Latice Gauge Theory. Semi-systolic and full-systolic algorithms are presented which are intensively used for correlation computations on the Connection Machine CM-2. The

  8. An energy landscape model for glass-forming liquids in three dimensions

    DEFF Research Database (Denmark)

    Pedersen, Ulf Rørbæk; Hecksher, Tina; Dyre, Jeppe

    2006-01-01

    different densities at several temperatures. At high densities and low temperatures the model captures the important characteristics of viscous liquid dynamics. We thus observe non-exponential relaxation in the self part of the density auto-correlation function, and fragility plots of the self...

  9. Machine Vision and Advanced Image Processing in Remote Sensing

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    This paper describes the multivariate alteration detection (MAD) transformation which is based on the established canonical correlation analysis. It also proposes post-processing of the change detected by the MAD variates by means of maximum autocorrelation factor (MAF) analysis. As opposed to mo...

  10. An Assessment of the Impact of Climate Change on Plant Species ...

    African Journals Online (AJOL)

    Lazie

    Abstract. This study assesses the effects of climate change on vegetative species diversity ... and mitigation strategies that are ecosystem and species specific. .... seasonality and values below detection limit. ... Pre-whitening is the process of removing undesirable autocorrelations ..... vegetation, carbon and fire in California.

  11. Agro 2012 June

    African Journals Online (AJOL)

    Nigerian Agriculture (1970 -2009): An Econometric Analysis ... FDAI with untransformed OLS regression model, autocorrelation was detected, hence ..... Cointegration and Unit Root Test: Granger and Newbold (1974), Engle and Granger. (1987) ... When the stochastic process is non-stationary, the use of OLS can produce.

  12. Long time tails in stationary random media. I. Theory

    NARCIS (Netherlands)

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

    1984-01-01

    Diffusion of moving particles in stationary disordered media is studied using a phenomenological mode-coupling theory. The presence of disorder leads to a generalized diffusion equation, with memory kernels having power law long time tails. The velocity autocorrelation function is found to decay

  13. Estimation of vector velocity

    DEFF Research Database (Denmark)

    2000-01-01

    Using a pulsed ultrasound field, the two-dimensional velocity vector can be determined with the invention. The method uses a transversally modulated ultrasound field for probing the moving medium under investigation. A modified autocorrelation approach is used in the velocity estimation. The new...

  14. Estimating relic magnetic fields from CMB temperature correlations

    CERN Document Server

    Giovannini, Massimo

    2009-01-01

    The temperature and polarization inhomogeneities of the Cosmic Microwave Background might bear the mark of pre-decoupling magnetism. The parameters of a putative magnetized background are hereby estimated from the observed temperature autocorrelation as well as from the measured temperature-polarization cross-correlation.

  15. Persistent spatial clusters of plasmacytosis among Danish mink farms

    DEFF Research Database (Denmark)

    Themudo, Goncalo Espregueira Cruz; Østergaard, Jørgen; Ersbøll, Annette Kjær

    2011-01-01

    % in 1996. Nevertheless, the disease persists in the Vendsyssel district of Northern Jutland, despite the eradication efforts. In this study, we used spatial epidemiological analysis to test for spatial autocorrelation of the distribution of farms positive for the disease. We investigated 2375 farms...

  16. Spectral properties of superpositions of Ornstein-Uhlenbeck type processes

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Leonenko, N.N.

    2005-01-01

    Stationary processes with prescribed one-dimensional marginal laws and long-range dependence are constructed. The asymptotic properties of the spectral densities are studied. The possibility of Mittag-Leffler decay in the autocorrelation function of superpositions of Ornstein-Uhlenbeck type...... processes is proved....

  17. Delay signatures in the chaotic intensity output of a quantum dot ...

    Indian Academy of Sciences (India)

    Delay identification from the chaotic intensity output of a quantum dot laser with optical feedback is done using numerical and information theoretic techniques. Four quantifiers, namely autocorrelation function, delayed mutual information, permutation entropy and permutation statistical complexity, are employed in delay ...

  18. Kernel based subspace projection of hyperspectral images

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Nielsen, Allan Aasbjerg; Arngren, Morten

    In hyperspectral image analysis an exploratory approach to analyse the image data is to conduct subspace projections. As linear projections often fail to capture the underlying structure of the data, we present kernel based subspace projections of PCA and Maximum Autocorrelation Factors (MAF...

  19. Analysis of monotonic greening and browning trends from global NDVI time-series

    NARCIS (Netherlands)

    Jong, de R.; Bruin, de S.; Wit, de A.J.W.; Schaepman, M.E.; Dent, D.L.

    2011-01-01

    Remotely sensed vegetation indices are widely used to detect greening and browning trends; especially the global coverage of time-series normalized difference vegetation index (NDVI) data which are available from 1981. Seasonality and serial auto-correlation in the data have previously been dealt

  20. Pressure drop ana velocity measurements in KMRR fuel rod bundles

    International Nuclear Information System (INIS)

    Yagn, Sun Kyu; Chung, Heung June; Chung, Chang Whan; Chun, Se Young; Song, Chul Wha; Won, Soon Yeun; Chung, Moon Ki

    1990-01-01

    The detailed hydraulic characteristic measurements in subchannels of longitudinally finned rod bundles using one-component LDV(Laser Doppler Velocimeter) were performed. Time mean axial velocity, turbulent intensity, and turbulent micro scales, such as time auto-correlation, Eulerian integral and micro scale, Kolmogorov length and time scale, and Taylor micro length scale were measured. The signals from LDV are inherently more or less discontinuous. The spectra of signals having such intermittent defects can be obtained by the fast Fourier transformation (FFT) of the auto-correlation function. The turbulent crossflow mixing rate between neighboring subchannels and dominant frequencies were evaluated from the measured data. Pressure drop data were obtained for the typical 36-element and 18-element fuel rod bundles fabricated by the design requirement of KMRR fuel and for other type of fuels assembled with 6-fin rods to investigate the fin effects on the pressure drop characteristics

  1. World relation per capita between income and emission of carbon dioxide

    Directory of Open Access Journals (Sweden)

    Fernando Artico Bigarani1

    2014-12-01

    Full Text Available The aim of this article is to verify the existence of relation per capita between emission of carbon dioxide and the growth of the income. The used methodology is the exploratory analysis of space data for the years of 1994 and 2009. By means of maps and of the Index of Moran one searched to observe the existence of space autocorrelation enters carbonic gas emission the per capita and per capita Gross domestic product of the countries of the Europe and Africa and to verify the space existence of clusters. The analysis of the results presented significant space autocorrelation between the studied variable and allowed the space identification of clusters in the Europe and Africa. The conclusion confirms the theory of the Curve of Ambient Kuznets and also it was identified that the protocol of Kyoto was capable to promote alterations in univariate clusters analyzed in the period.

  2. Statistical models and time series forecasting of sulfur dioxide: a case study Tehran.

    Science.gov (United States)

    Hassanzadeh, S; Hosseinibalam, F; Alizadeh, R

    2009-08-01

    This study performed a time-series analysis, frequency distribution and prediction of SO(2) levels for five stations (Pardisan, Vila, Azadi, Gholhak and Bahman) in Tehran for the period of 2000-2005. Most sites show a quite similar characteristic with highest pollution in autumn-winter time and least pollution in spring-summer. The frequency distributions show higher peaks at two residential sites. The potential for SO(2) problems is high because of high emissions and the close geographical proximity of the major industrial and urban centers. The ACF and PACF are nonzero for several lags, indicating a mixed (ARMA) model, then at Bahman station an ARMA model was used for forecasting SO(2). The partial autocorrelations become close to 0 after about 5 lags while the autocorrelations remain strong through all the lags shown. The results proved that ARMA (2,2) model can provides reliable, satisfactory predictions for time series.

  3. Conductance Peaks in Open Quantum Dots

    International Nuclear Information System (INIS)

    Ramos, J. G. G. S.; Bazeia, D.; Hussein, M. S.; Lewenkopf, C. H.

    2011-01-01

    We present a simple measure of the conductance fluctuations in open ballistic chaotic quantum dots, extending the number of maxima method originally proposed for the statistical analysis of compound nuclear reactions. The average number of extreme points (maxima and minima) in the dimensionless conductance T as a function of an arbitrary external parameter Z is directly related to the autocorrelation function of T(Z). The parameter Z can be associated with an applied gate voltage causing shape deformation in quantum dot, an external magnetic field, the Fermi energy, etc. The average density of maxima is found to be Z >=α Z /Z c , where α Z is a universal constant and Z c is the conductance autocorrelation length, which is system specific. The analysis of Z > does not require large statistic samples, providing a quite amenable way to access information about parametric correlations, such as Z c .

  4. Symmetric minimally entangled typical thermal states for canonical and grand-canonical ensembles

    Science.gov (United States)

    Binder, Moritz; Barthel, Thomas

    2017-05-01

    Based on the density matrix renormalization group (DMRG), strongly correlated quantum many-body systems at finite temperatures can be simulated by sampling over a certain class of pure matrix product states (MPS) called minimally entangled typical thermal states (METTS). When a system features symmetries, these can be utilized to substantially reduce MPS computation costs. It is conceptually straightforward to simulate canonical ensembles using symmetric METTS. In practice, it is important to alternate between different symmetric collapse bases to decrease autocorrelations in the Markov chain of METTS. To this purpose, we introduce symmetric Fourier and Haar-random block bases that are efficiently mixing. We also show how grand-canonical ensembles can be simulated efficiently with symmetric METTS. We demonstrate these approaches for spin-1 /2 X X Z chains and discuss how the choice of the collapse bases influences autocorrelations as well as the distribution of measurement values and, hence, convergence speeds.

  5. Modelling and predicting biogeographical patterns in river networks

    Directory of Open Access Journals (Sweden)

    Sabela Lois

    2016-04-01

    Full Text Available Statistical analysis and interpretation of biogeographical phenomena in rivers is now possible using a spatially explicit modelling framework, which has seen significant developments in the past decade. I used this approach to identify a spatial extent (geostatistical range in which the abundance of the parasitic freshwater pearl mussel (Margaritifera margaritifera L. is spatially autocorrelated in river networks. I show that biomass and abundance of host fish are a likely explanation for the autocorrelation in mussel abundance within a 15-km spatial extent. The application of universal kriging with the empirical model enabled precise prediction of mussel abundance within segments of river networks, something that has the potential to inform conservation biogeography. Although I used a variety of modelling approaches in my thesis, I focus here on the details of this relatively new spatial stream network model, thus advancing the study of biogeographical patterns in river networks.

  6. Statistical spatial properties of speckle patterns generated by multiple laser beams

    International Nuclear Information System (INIS)

    Le Cain, A.; Sajer, J. M.; Riazuelo, G.

    2011-01-01

    This paper investigates hot spot characteristics generated by the superposition of multiple laser beams. First, properties of speckle statistics are studied in the context of only one laser beam by computing the autocorrelation function. The case of multiple laser beams is then considered. In certain conditions, it is shown that speckles have an ellipsoidal shape. Analytical expressions of hot spot radii generated by multiple laser beams are derived and compared to numerical estimates made from the autocorrelation function. They are also compared to numerical simulations performed within the paraxial approximation. Excellent agreement is found for the speckle width as well as for the speckle length. Application to the speckle patterns generated in the Laser MegaJoule configuration in the zone where all the beams overlap is presented. Influence of polarization on the size of the speckles as well as on their abundance is studied.

  7. Computationally Efficient 2D DOA Estimation with Uniform Rectangular Array in Low-Grazing Angle

    Directory of Open Access Journals (Sweden)

    Junpeng Shi

    2017-02-01

    Full Text Available In this paper, we propose a computationally efficient spatial differencing matrix set (SDMS method for two-dimensional direction of arrival (2D DOA estimation with uniform rectangular arrays (URAs in a low-grazing angle (LGA condition. By rearranging the auto-correlation and cross-correlation matrices in turn among different subarrays, the SDMS method can estimate the two parameters independently with one-dimensional (1D subspace-based estimation techniques, where we only perform difference for auto-correlation matrices and the cross-correlation matrices are kept completely. Then, the pair-matching of two parameters is achieved by extracting the diagonal elements of URA. Thus, the proposed method can decrease the computational complexity, suppress the effect of additive noise and also have little information loss. Simulation results show that, in LGA, compared to other methods, the proposed methods can achieve performance improvement in the white or colored noise conditions.

  8. Convergence monitoring of Markov chains generated for inverse tracking of unknown model parameters in atmospheric dispersion

    International Nuclear Information System (INIS)

    Kim, Joo Yeon; Ryu, Hyung Joon; Jung, Gyu Hwan; Lee, Jai Ki

    2011-01-01

    The dependency within the sequential realizations in the generated Markov chains and their reliabilities are monitored by introducing the autocorrelation and the potential scale reduction factor (PSRF) by model parameters in the atmospheric dispersion. These two diagnostics have been applied for the posterior quantities of the release point and the release rate inferred through the inverse tracking of unknown model parameters for the Yonggwang atmospheric tracer experiment in Korea. The autocorrelations of model parameters are decreasing to low values approaching to zero with increase of lag, resulted in decrease of the dependencies within the two sequential realizations. Their PSRFs are reduced to within 1.2 and the adequate simulation number recognized from these results. From these two convergence diagnostics, the validation of Markov chains generated have been ensured and PSRF then is especially suggested as the efficient tool for convergence monitoring for the source reconstruction in atmospheric dispersion. (author)

  9. Evaporation of nanoscale water on a uniformly complete wetting surface at different temperatures.

    Science.gov (United States)

    Guo, Yuwei; Wan, Rongzheng

    2018-05-03

    The evaporation of nanoscale water films on surfaces affects many processes in nature and industry. Using molecular dynamics (MD) simulations, we show the evaporation of a nanoscale water film on a uniformly complete wetting surface at different temperatures. With the increase in temperature, the growth of the water evaporation rate becomes slow. Analyses show that the hydrogen bond (H-bond) lifetimes and orientational autocorrelation times of the outermost water film decrease slowly with the increase in temperature. Compared to a thicker water film, the H-bond lifetimes and orientational autocorrelation times of a monolayer water film are much slower. This suggests that the lower evaporation rate of the monolayer water film on a uniformly complete wetting surface may be caused by the constriction of the water rotation due to the substrate. This finding may be helpful for controlling nanoscale water evaporation within a certain range of temperatures.

  10. Long-range correlation and market segmentation in bond market

    Science.gov (United States)

    Wang, Zhongxing; Yan, Yan; Chen, Xiaosong

    2017-09-01

    This paper investigates the long-range auto-correlations and cross-correlations in bond market. Based on Detrended Moving Average (DMA) method, empirical results present a clear evidence of long-range persistence that exists in one year scale. The degree of long-range correlation related to maturities has an upward tendency with a peak in short term. These findings confirm the expectations of fractal market hypothesis (FMH). Furthermore, we have developed a method based on a complex network to study the long-range cross-correlation structure and applied it to our data, and found a clear pattern of market segmentation in the long run. We also detected the nature of long-range correlation in the sub-period 2007-2012 and 2011-2016. The result from our research shows that long-range auto-correlations are decreasing in the recent years while long-range cross-correlations are strengthening.

  11. [Incentive for Regional Risk Selection in the German Risk Structure Compensation Scheme].

    Science.gov (United States)

    Wende, Danny

    2017-10-01

    The introduction of the new law GKV-FQWG strengthens the competition between statutory health insurance. If incentives for risk selection exist, they may force a battle for cheap customers. This study aims to document and discuss incentives for regional risk selection in the German risk structure compensation scheme. Identify regional autocorrelation with Moran's l on financial parameters of the risk structure compensation schema. Incentives for regional risk selection do indeed exist. The risk structure compensation schema reduces 91% of the effect and helps to reduce risk selection. Nevertheless, a connection between regional situation and competition could be shown (correlation: 69.5%). Only the integration of regional control variables into the risk compensation eliminates regional autocorrelation. The actual risk structure compensation is leading to regional inequalities and as a consequence to risk selection and distortion in competition. © Georg Thieme Verlag KG Stuttgart · New York.

  12. Sex-biased dispersal at different geographical scales in a cooperative breeder from fragmented rainforest.

    Directory of Open Access Journals (Sweden)

    Carl Vangestel

    Full Text Available Dispersal affects both social behavior and population structure and is therefore a key determinant of long-term population persistence. However, dispersal strategies and responses to spatial habitat alteration may differ between sexes. Here we analyzed spatial and temporal variation in ten polymorphic microsatellite DNA loci of male and female Cabanis's greenbuls (Phyllastrephuscabanisi, a cooperative breeder of Afrotropical rainforest, to quantify rates of gene flow and fine-grained genetic structuring within and among fragmented populations. We found genetic evidence for female-biased dispersal at small spatial scales, but not at the landscape level. Local autocorrelation analysis provided evidence of positive genetic structure within 300 m distance ranges, which is consistent with behavioral observations of short-distance natal dispersal. At a landscape scale, individual-based autocorrelation values decreased over time while levels of admixture increased, possibly indicating increased gene flow over the past decade.

  13. Monte Carlo sampling strategies for lattice gauge calculations

    International Nuclear Information System (INIS)

    Guralnik, G.; Zemach, C.; Warnock, T.

    1985-01-01

    We have sought to optimize the elements of the Monte Carlo processes for thermalizing and decorrelating sequences of lattice gauge configurations and for this purpose, to develop computational and theoretical diagnostics to compare alternative techniques. These have been applied to speed up generations of random matrices, compare heat bath and Metropolis stepping methods, and to study autocorrelations of sequences in terms of the classical moment problem. The efficient use of statistically correlated lattice data is an optimization problem depending on the relation between computer times to generate lattice sequences of sufficiently small correlation and times to analyze them. We can solve this problem with the aid of a representation of auto-correlation data for various step lags as moments of positive definite distributions, using methods known for the moment problem to put bounds on statistical variances, in place of estimating the variances by too-lengthy computer runs

  14. Maximum Likelihood based comparison of the specific growth rates for P. aeruginosa and four mutator strains

    DEFF Research Database (Denmark)

    Philipsen, Kirsten Riber; Christiansen, Lasse Engbo; Mandsberg, Lotte Frigaard

    2008-01-01

    with an exponentially decaying function of the time between observations is suggested. A model with a full covariance structure containing OD-dependent variance and an autocorrelation structure is compared to a model with variance only and with no variance or correlation implemented. It is shown that the model...... are used for parameter estimation. The data is log-transformed such that a linear model can be applied. The transformation changes the variance structure, and hence an OD-dependent variance is implemented in the model. The autocorrelation in the data is demonstrated, and a correlation model...... that best describes data is a model taking into account the full covariance structure. An inference study is made in order to determine whether the growth rate of the five bacteria strains is the same. After applying a likelihood-ratio test to models with a full covariance structure, it is concluded...

  15. The Self-Correlation Function of Real Gases; Fonction d'Autocorrelation des Gaz Reels; 0424 0423 041d 041a 0426 0418 042f 0421 0410 041c 041e 041a 041e 0420 0420 0415 041b 042f 0426 0418 0418 0420 0415 0410 041b 042c 041d 042b 0425 0413 0410 0417 041e 0412 ; La Funcion de Autocorrelacion de los Gases Reales

    Energy Technology Data Exchange (ETDEWEB)

    Sigmar, D. J. [Institute for Theoretical Physics, Technical University of Vienna Vienna (Austria)

    1965-06-15

    In the formal theory of inelastic scattering of neutrons, the self-correlation function has been worked out in terms of statistical averages of the derivatives of die N-body interaction-potential of the scatterer. In the present paper, these averages are evaluated for real gases by means of a cluster-expansion related to that of Mayer-Ursell. This leads to certain non-linear types of clusters, which are investigated with respect to the topology of the graphs, their multiplicity (by combinatorial analysis) and their quadrature. As one expects, in view of the many-body problem, some of the clusters are not separable and have to be machine-integrated. In this way, the self-correlation function {gamma}{sub s}(K, t) is calculated for short times, including also the first non-Gaussian term. The cluster-expansion breaks off after the first interaction term, so that the results are valid for low density only. This still gives rise to very many different types of clusters, containing up to seven points, for each coefficient. The assumed potential is a general two-particle, hard-core type. As Singwi et al. have shown, the long time behaviour of {gamma}s is determined by the time integral of the velocity auto-correlation: {integral}{sup {infinity}}{sub 0} {sub T}dt. To construct the integrand for all times, we can make use of our cluster-expansion for small t and adopt Langevin's diffusion theory for large t. Numerical computations are under way. (author) [French] Dans la theorie formelle de la diffusion inelastique des neutrons, on a etabli la fonction d'autocorrelation en se fondant sur les moyennes statistiques des derivees du potentiel d'interaction a N corps du diffuseur. L'auteur a evalue ces moyennes pour des gaz reels a l'aide d'un developpement par amas en rapport avec celui de Mayer-Ursell. U obtient ainsi des types d'amas non lineaires qu'il etudie du point de vue de la topo- logie des diagrammes, de leur multiplicite (par analyse

  16. Characterizing local traffic contributions to particulate air pollution in street canyons using mobile monitoring techniques

    Science.gov (United States)

    Zwack, Leonard M.; Paciorek, Christopher J.; Spengler, John D.; Levy, Jonathan I.

    2011-05-01

    Traffic within urban street canyons can contribute significantly to ambient concentrations of particulate air pollution. In these settings, it is challenging to separate within-canyon source contributions from urban and regional background concentrations given the highly variable and complex emissions and dispersion characteristics. In this study, we used continuous mobile monitoring of traffic-related particulate air pollutants to assess the contribution to concentrations, above background, of traffic in the street canyons of midtown Manhattan. Concentrations of both ultrafine particles (UFP) and fine particles (PM 2.5) were measured at street level using portable instruments. Statistical modeling techniques accounting for autocorrelation were used to investigate the presence of spatial heterogeneity of pollutant concentrations as well as to quantify the contribution of within-canyon traffic sources. Measurements were also made within Central Park, to examine the impact of offsets from major roadways in this urban environment. On average, an approximate 11% increase in concentrations of UFP and 8% increase in concentrations of PM 2.5 over urban background was estimated during high-traffic periods in street canyons as opposed to low traffic periods. Estimates were 8% and 5%, respectively, after accounting for temporal autocorrelation. Within Central Park, concentrations were 40% higher than background (5% after accounting for temporal autocorrelation) within the first 100 m from the nearest roadway for UFP, with a smaller but statistically significant increase for PM 2.5. Our findings demonstrate the viability of a mobile monitoring protocol coupled with spatiotemporal modeling techniques in characterizing local source contributions in a setting with street canyons.

  17. Space, race, and poverty: Spatial inequalities in walkable neighborhood amenities?

    Directory of Open Access Journals (Sweden)

    John Whalen

    2012-05-01

    Full Text Available BACKGROUND Multiple and varied benefits have been suggested for increased neighborhood walkability. However, spatial inequalities in neighborhood walkability likely exist and may be attributable, in part, to residential segregation. OBJECTIVE Utilizing a spatial demographic perspective, we evaluated potential spatial inequalities in walkable neighborhood amenities across census tracts in Boston, MA (US. METHODS The independent variables included minority racial/ethnic population percentages and percent of families in poverty. Walkable neighborhood amenities were assessed with a composite measure. Spatial autocorrelation in key study variables were first calculated with the Global Moran's I statistic. Then, Spearman correlations between neighborhood socio-demographic characteristics and walkable neighborhood amenities were calculated as well as Spearman correlations accounting for spatial autocorrelation. We fit ordinary least squares (OLS regression and spatial autoregressive models when appropriate as a final step. RESULTS Significant positive spatial autocorrelation was found in neighborhood socio-demographic characteristics (e.g. census tract percent Black, but not walkable neighborhood amenities or in the OLS regression residuals. Spearman correlations between neighborhood socio-demographic characteristics and walkable neighborhood amenities were not statistically significant, nor were neighborhood socio-demographic characteristics significantly associated with walkable neighborhood amenities in OLS regression models. CONCLUSIONS Our results suggest that there is residential segregation in Boston and that spatial inequalities do not necessarily show up using a composite measure. COMMENTS Future research in other geographic areas (including international contexts and using different definitions of neighborhoods (including small-area definitions should evaluate if spatial inequalities are found using composite measures, but also should

  18. Muertes por lesiones de tránsito en Argentina: un análisis espacial para el período 2001-2009 Deaths from road injuries in Argentina: a spatial analysis for the 2001-2009 period

    Directory of Open Access Journals (Sweden)

    Carlos M. Leveau

    2012-05-01

    Full Text Available Las lesiones de tránsito representan la causa más frecuente de muerte por causas externas en Argentina y un problema de creciente magnitud para la salud pública a nivel global. Los principales objetivos de este trabajo son establecer el nivel de autocorrelación espacial experimentado a nivel de departamentos e identificar la conformación de agrupamientos mediante el cálculo de los indicadores locales de asociación espacial a nivel nacional. Los resultados mostraron un nivel de autocorrelación significativamente positivo en Argentina. Al relacionar las tasas de mortalidad por lesiones de tránsito con la densidad poblacional, se registró un nivel de autocorrelación espacial negativo. Se observó también que la mortalidad por lesiones de tránsito podría representar un problema más grave fuera de las grandes aglomeraciones.Traffic injuries in Argentina are the most frequent cause of death from external injuries and a public health problem of increasing magnitude at the global level. The objectives of this study are to establish the level of spatial autocorrelation at the department level and identify the formation of groupings by calculating local indicators of spatial association at the national level. The results reveal a significantly positive level of autocorrelation in Argentina. A negative level of spatial autocorrelation was recorded when mortality from road injuries was related to population density. It was also noted that mortality from road injuries could pose a more serious problem outside large urban areas.

  19. Carbonaceous aerosol at two rural locations in New York State: Characterization and behavior

    Science.gov (United States)

    Sunder Raman, Ramya; Hopke, Philip K.; Holsen, Thomas M.

    2008-06-01

    Fine particle samples were collected to determine the chemical constituents in PM2.5 at two rural background sites (Potsdam and Stockton, N. Y.) in the northeastern United States from November 2002 to August 2005. Samples were collected every third day for 24 h with a speciation network sampler. The measured carbonaceous species included thermal-optical organic carbon (OC), elemental carbon (EC), pyrolytic carbon (OP), black carbon (BC), and water-soluble, short-chain (WSSC) organic acids. Concentration time series, autocorrelations, and seasonal variations of the carbonaceous species were examined. During this multiyear period, the contributions of the total carbon (OC + EC) to the measured fine particle mass were 31.2% and 31.1% at Potsdam and Stockton, respectively. The average sum of the WSSC acids carbon accounted for approximately 2.5% of the organic carbon at Potsdam and 3.0% at Stockton. At Potsdam, the seasonal differences in the autocorrelation function (ACF) and partial autocorrelation function (PACF) values for carbonaceous species suggest that secondary formation may be an important contributor to the observed concentrations of species likely to be secondary in origin, particularly during the photochemically active time of the year (May to October). This study also investigated the relationships between carbonaceous species to better understand the behavior of carbonaceous aerosol and to assess the contribution of secondary organic carbon (SOC) to the total organic carbon mass (the EC tracer method was used to estimate SOC). At Potsdam the average SOC contribution to total OC varied between 66% and 72%, while at Stockton it varied between 58% and 64%.

  20. Spatial occupancy models for large data sets

    Science.gov (United States)

    Johnson, Devin S.; Conn, Paul B.; Hooten, Mevin B.; Ray, Justina C.; Pond, Bruce A.

    2013-01-01

    Since its development, occupancy modeling has become a popular and useful tool for ecologists wishing to learn about the dynamics of species occurrence over time and space. Such models require presence–absence data to be collected at spatially indexed survey units. However, only recently have researchers recognized the need to correct for spatially induced overdisperison by explicitly accounting for spatial autocorrelation in occupancy probability. Previous efforts to incorporate such autocorrelation have largely focused on logit-normal formulations for occupancy, with spatial autocorrelation induced by a random effect within a hierarchical modeling framework. Although useful, computational time generally limits such an approach to relatively small data sets, and there are often problems with algorithm instability, yielding unsatisfactory results. Further, recent research has revealed a hidden form of multicollinearity in such applications, which may lead to parameter bias if not explicitly addressed. Combining several techniques, we present a unifying hierarchical spatial occupancy model specification that is particularly effective over large spatial extents. This approach employs a probit mixture framework for occupancy and can easily accommodate a reduced-dimensional spatial process to resolve issues with multicollinearity and spatial confounding while improving algorithm convergence. Using open-source software, we demonstrate this new model specification using a case study involving occupancy of caribou (Rangifer tarandus) over a set of 1080 survey units spanning a large contiguous region (108 000 km2) in northern Ontario, Canada. Overall, the combination of a more efficient specification and open-source software allows for a facile and stable implementation of spatial occupancy models for large data sets.

  1. The large-scale quasar-Lyman α forest cross-correlation from BOSS

    Energy Technology Data Exchange (ETDEWEB)

    Font-Ribera, Andreu [Institute of Theoretical Physics, University of Zurich, Winterthurerstrasse 190, 8057 Zurich (Switzerland); Arnau, Eduard [Institut de Ciències del Cosmos (IEEC/UB), Martí i Franquès 1, 08028 Barcelona, Catalonia (Spain); Miralda-Escudé, Jordi, E-mail: font@physik.uzh.ch, E-mail: edu.arnau.lazaro@gmail.com, E-mail: miralda@icc.ub.edu [Institució Catalana de Recerca i Estudis Avançats, Passeig Lluís Companys 23, 08010 Barcelona, Catalonia (Spain); and others

    2013-05-01

    We measure the large-scale cross-correlation of quasars with the Lyα forest absorption in redshift space, using ∼ 60000 quasar spectra from Data Release 9 (DR9) of the Baryon Oscillation Spectroscopic Survey (BOSS). The cross-correlation is detected over a wide range of scales, up to comoving separations r of 80 h{sup −1}Mpc. For r > 15 h{sup −1}Mpc, we show that the cross-correlation is well fitted by the linear theory prediction for the mean overdensity around a quasar host halo in the standard ΛCDM model, with the redshift distortions indicative of gravitational evolution detected at high confidence. Using previous determinations of the Lyα forest bias factor obtained from the Lyα autocorrelation, we infer the quasar bias factor to be b{sub q} = 3.64{sup +0.13}{sub −0.15} at a mean redshift z = 2.38, in agreement with previous measurements from the quasar auto-correlation. We also obtain a new estimate of the Lyα forest redshift distortion factor, β{sub F} = 1.1±0.15, slightly larger than but consistent with the previous measurement from the Lyα forest autocorrelation. The simple linear model we use fails at separations r < 15h{sup −1}Mpc, and we show that this may reasonably be due to the enhanced ionization due to radiation from the quasars. We also provide the expected correction that the mass overdensity around the quasar implies for measurements of the ionizing radiation background from the line-of-sight proximity effect.

  2. [Prediction and spatial distribution of recruitment trees of natural secondary forest based on geographically weighted Poisson model].

    Science.gov (United States)

    Zhang, Ling Yu; Liu, Zhao Gang

    2017-12-01

    Based on the data collected from 108 permanent plots of the forest resources survey in Maoershan Experimental Forest Farm during 2004-2016, this study investigated the spatial distribution of recruitment trees in natural secondary forest by global Poisson regression and geographically weighted Poisson regression (GWPR) with four bandwidths of 2.5, 5, 10 and 15 km. The simulation effects of the 5 regressions and the factors influencing the recruitment trees in stands were analyzed, a description was given to the spatial autocorrelation of the regression residuals on global and local levels using Moran's I. The results showed that the spatial distribution of the number of natural secondary forest recruitment was significantly influenced by stands and topographic factors, especially average DBH. The GWPR model with small scale (2.5 km) had high accuracy of model fitting, a large range of model parameter estimates was generated, and the localized spatial distribution effect of the model parameters was obtained. The GWPR model at small scale (2.5 and 5 km) had produced a small range of model residuals, and the stability of the model was improved. The global spatial auto-correlation of the GWPR model residual at the small scale (2.5 km) was the lowe-st, and the local spatial auto-correlation was significantly reduced, in which an ideal spatial distribution pattern of small clusters with different observations was formed. The local model at small scale (2.5 km) was much better than the global model in the simulation effect on the spatial distribution of recruitment tree number.

  3. The large-scale quasar-Lyman α forest cross-correlation from BOSS

    International Nuclear Information System (INIS)

    Font-Ribera, Andreu; Arnau, Eduard; Miralda-Escudé, Jordi

    2013-01-01

    We measure the large-scale cross-correlation of quasars with the Lyα forest absorption in redshift space, using ∼ 60000 quasar spectra from Data Release 9 (DR9) of the Baryon Oscillation Spectroscopic Survey (BOSS). The cross-correlation is detected over a wide range of scales, up to comoving separations r of 80 h −1 Mpc. For r > 15 h −1 Mpc, we show that the cross-correlation is well fitted by the linear theory prediction for the mean overdensity around a quasar host halo in the standard ΛCDM model, with the redshift distortions indicative of gravitational evolution detected at high confidence. Using previous determinations of the Lyα forest bias factor obtained from the Lyα autocorrelation, we infer the quasar bias factor to be b q = 3.64 +0.13 −0.15 at a mean redshift z = 2.38, in agreement with previous measurements from the quasar auto-correlation. We also obtain a new estimate of the Lyα forest redshift distortion factor, β F = 1.1±0.15, slightly larger than but consistent with the previous measurement from the Lyα forest autocorrelation. The simple linear model we use fails at separations r −1 Mpc, and we show that this may reasonably be due to the enhanced ionization due to radiation from the quasars. We also provide the expected correction that the mass overdensity around the quasar implies for measurements of the ionizing radiation background from the line-of-sight proximity effect

  4. Rooting and dating maples (Acer) with an uncorrelated-rates molecular clock: implications for north American/Asian disjunctions.

    Science.gov (United States)

    Renner, Susanne S; Grimm, Guido W; Schneeweiss, Gerald M; Stuessy, Tod F; Ricklefs, Robert E

    2008-10-01

    Simulations suggest that molecular clock analyses can correctly identify the root of a tree even when the clock assumption is severely violated. Clock-based rooting of phylogenies may be particularly useful when outgroup rooting is problematic. Here, we explore relaxed-clock rooting in the Acer/Dipteronia clade of Sapindaceae, which comprises genera of highly uneven species richness and problematic mutual monophyly. Using an approach that does not presuppose rate autocorrelation between ancestral and descendant branches and hence does not require a rooted a priori topology, we analyzed data from up to seven chloroplast loci for some 50 ingroup species. For comparison, we used midpoint and outgroup rooting and dating methods that rely on rooted input trees, namely penalized likelihood, a Bayesian autocorrelated-rates model, and a strict clock. The chloroplast sequences used here reject a single global substitution rate, and the assumption of autocorrelated rates was also rejected. The root was placed between Acer and Dipteronia by all three rooting methods, albeit with low statistical support. Analyses of Acer diversification with a lineage-through-time plot and different survival models, although sensitive to missing data, suggest a gradual decrease in the average diversification rate. The nine North American species of Acer diverged from their nearest relatives at widely different times: eastern American Acer diverged in the Oligocene and Late Miocene; western American species in the Late Eocene and Mid Miocene; and the Acer core clade, including A. saccharum, dates to the Miocene. Recent diversification in North America is strikingly rare compared to diversification in eastern Asia.

  5. [Spatial Distribution Characteristics of Different Species Mercury in Water Body of Changshou Lake in Three Gorges Reservoir Region].

    Science.gov (United States)

    Bai, Wei-yang; Zhang, Cheng; Zhao, Zheng; Tang, Zhen-ya; Wang, Ding-yong

    2015-08-01

    An investigation on the concentrations and the spatial distribution characteristics of different species of mercury in the water body of Changshou Lake in Three Gorges Reservoir region was carried out based on the AreGIS statistics module. The results showed that the concentration of the total mercury in Changshou Lake surface water ranged from 0.50 to 3.78 ng x L(-1), with an average of 1.51 ng x L(-1); the concentration of the total MeHg (methylmercury) ranged from 0.10 to 0.75 ng x L(-1), with an average of 0.23 ng x L(-1). The nugget effect value of total mercury in surface water (50.65%), dissolved mercury (49.80%), particulate mercury (29.94%) and the activity mercury (26.95%) were moderate spatial autocorrelation. It indicated that the autocorrelation was impacted by the intrinsic properties of sediments (such as parent materials and rocks, geological mineral and terrain), and on the other hand it was also disturbed by the exogenous input factors (such as aquaculture, industrial activities, farming etc). The nugget effect value of dissolved methylmercury (DMeHg) in Changshou lake surface water (3.49%) was less than 25%, showing significant strong spatial autocorrelation. The distribution was mainly controlled by environmental factors in water. The proportion of total MeHg in total Hg in Changshou Lake water reached 30% which was the maximum ratio of the total MeHg to total Hg in freshwater lakes and rivers. It implied that mercury was easily methylated in the environment of Chanashou Lake.

  6. Analysis of low-field isotropic vortex glass containing vortex groups in YBa2Cu3O7-x thin films visualized by scanning SQUID microscopy

    NARCIS (Netherlands)

    Wells, Frederick S.; Pan, Alexey V.; Wang, X.; Fedoseev, Sergey A.; Hilgenkamp, Hans

    2015-01-01

    The glass-like vortex distribution in pulsed laser deposited YBa2Cu3O7-x thin films is observed by scanning superconducting quantum interference device microscopy and analysed for ordering after cooling in magnetic fields significantly smaller than the Earth's field. Autocorrelation calculations on

  7. Characterization of foreign exchange market using the threshold-dealer-model

    Science.gov (United States)

    Yamada, Kenta; Takayasu, Hideki; Takayasu, Misako

    2007-08-01

    We introduce a deterministic dealer model which implements most of the empirical laws, such as fat tails in the price change distributions, autocorrelation of price change and non-Poissonian intervals. We also clarify the causality between microscopic dealers’ dynamics and macroscopic market's empirical laws.

  8. Computation of Hopkins' 3-circle integrals using Zernike expansions

    NARCIS (Netherlands)

    Janssen, A.J.E.M.

    2011-01-01

    The integrals occurring in optical diffraction theory under conditions of partial coherence have the form of an incomplete autocorrelation integral of the pupil function of the optical system. The incompleteness is embodied by a spatial coherence function of limited extent. In the case of circular

  9. Delay signatures in the chaotic intensity output of a quantum dot ...

    Indian Academy of Sciences (India)

    journal of. May 2016 physics pp. 1021–1030. Delay signatures in the chaotic intensity output ... Research in complex systems require quantitative predictions of their dynamics, even ... used methods for estimating delay in complex dynamics are autocorrelation function ..... Authors thank BRNS for its financial support.

  10. Fast Monaural Separation of Speech

    DEFF Research Database (Denmark)

    Pontoppidan, Niels Henrik; Dyrholm, Mads

    2003-01-01

    a Factorial Hidden Markov Model, with non-stationary assumptions on the source autocorrelations modelled through the Factorial Hidden Markov Model, leads to separation in the monaural case. By extending Hansens work we find that Roweis' assumptions are necessary for monaural speech separation. Furthermore we...

  11. Single photon emission up to liquid nitrogen temperature from charged excitons confined in GaAs-based epitaxial nanostructures

    NARCIS (Netherlands)

    Dusanowski, L.; Syperek, M.; Marynski, A.; Li, L.H.; Misiewicz, J.; Höfling, S.; Kamp, M.; Fiore, A.; Sek, G.

    2015-01-01

    We demonstrate a non-classical photon emitter at near infrared wavelength based on a single (In,Ga)As/GaAs epitaxially grown columnar quantum dot. Charged exciton complexes have been identified in magneto-photoluminescence. Photon auto-correlation histograms from the recombination of a trion

  12. Computer simulations of long-time tails: what's new?

    NARCIS (Netherlands)

    Hoef, van der M.A.; Frenkel, D.

    1995-01-01

    Twenty five years ago Alder and Wainwright discovered, by simulation, the 'long-time tails' in the velocity autocorrelation function of a single particle in fluid [1]. Since then, few qualitatively new results on long-time tails have been obtained by computer simulations. However, within the

  13. Neighborhood Characteristics and the Social Control of Registered Sex Offenders

    Science.gov (United States)

    Socia, Kelly M.; Stamatel, Janet P.

    2012-01-01

    This study uses geospatial and regression analyses to examine the relationships among social disorganization, collective efficacy, social control, residence restrictions, spatial autocorrelation, and the neighborhood distribution of registered sex offenders (RSOs) in Chicago. RSOs were concentrated in neighborhoods that had higher levels of social…

  14. Semi-supervised adaptation in ssvep-based brain-computer interface using tri-training

    DEFF Research Database (Denmark)

    Bender, Thomas; Kjaer, Troels W.; Thomsen, Carsten E.

    2013-01-01

    This paper presents a novel and computationally simple tri-training based semi-supervised steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI). It is implemented with autocorrelation-based features and a Naïve-Bayes classifier (NBC). The system uses nine characters...

  15. Anomalous transport properties of the quantum Lorentz gas

    NARCIS (Netherlands)

    Hoogeveen, W.; Tjon, J.A.

    The two-scatter contribution to the Laplace transformed velocity autocorrelation function is investigated with the use of a double contour method which contains the microscopic information in terms of off-shell T-matrix elements. By analysing the full off-shell two-scatterer expression both

  16. Dynamics at Intermediate Time Scales and Management of Ecological Populations

    Science.gov (United States)

    2017-05-10

    thinking about the importance of transients is to recognize the importance of serial autocorrelation in time of forcing terms over realistic ecological time...rich areas helps produce divergent home range responses bet - ween individuals from difference age classes. This model has broad applications for

  17. Cosmological measurements with forthcoming radio continuum surveys

    CSIR Research Space (South Africa)

    Raccanelli, A

    2012-08-01

    Full Text Available , while the best measurements of dark energy models will come from galaxy autocorrelation function analyses. Using a combination of the EvolutionaryMap of the Universe (EMU) and WODAN to provide a full-sky survey, it will be possible to measure the dark...

  18. Quality-based fingerprint segmentation

    CSIR Research Space (South Africa)

    Mngenge, NA

    2012-06-01

    Full Text Available is block-wise, it utilizes the auto-correlation matrix of gradients and its eigenvalue to compute the score quality measure of each block. The score quality measures both local contrast and orientation in each block. The threshold is computed by taking...

  19. Journal of Earth System Science | Indian Academy of Sciences

    Indian Academy of Sciences (India)

    Understanding the inherent features of wind speed (variability on different time scales) has become critical for assured wind power availability, grid stability, and effective power management. The study utilizes the wavelet, autocorrelation, and FFT (fast Fourier transform) techniques to analyze and assimilate the fluctuating ...

  20. Untitled

    Indian Academy of Sciences (India)

    Velocity autocorrelation. Two-state random walk model of diffusion 2. Oscillatory diffusion 437. Vibrational constant. On the C-X system of diatomic mercury chloride 147. Vibrational structure. On the C-X system of diatomic mercury chloride 47. Vibrational symmetry coordinates. Symmetry coordinates of nonrigid molecules.

  1. Avaliação e aplicação de testes para a detecção da autocorrelação espacial usando marcadores genéticos Evaluation and application of tests for the detection of spatial autocorrelation using data genetics marks

    Directory of Open Access Journals (Sweden)

    João Marcos Louzada

    2006-04-01

    Full Text Available O índice I de Moran é a ferramenta usual para se medir a intensidade da autocorrelação espacial em dados de marcadores genéticos. A estatística I é assintoticamente normalmente distribuída, podendo ser avaliada como desvios da normal padrão mediante o suposto-N (aproximação normal. Porém, para pequenos números de populações (m25}, deve-se aplicar o teste de Mantel em qualquer das situações simuladas.Moran's I index is the usual tool to measure the intensity of the spatial autocorrelation in genetic markers data. I statistics is asymptotically normally distributed and it may be evaluated as standard normal deviations (assumption-N, normality. However, for small numbers of populations (m<8, the Mantel' s randomness test (assumption-R developed by Mantel (1967 should be applied. Thus, this study was done to evaluate the performance of both tests accordding to type I error rate sand their power. They were evaluated via Monte Carlo simulation, in which, the situations of average allelic frequencies, {p=0,1, p=0,25 and p=0,5} were analyzed under H0. Number for populations varying from {m= 5, 10, 25 and 50}were taken into account and for each population, the number of individuals in {n=1, 2, 5, 10 and 30} was varied as well. As regards to the alternative hypothesis (with spatial pattern, in addition to these same situations simulated in H0, the behavior of these criteria of tests was evaluated according to the variation of the amplitude in the average local allelic frequency in {A=0,1; 0,2; 0,5; 0,8 e 1,0}. Therefore, the performance of the test studied could be analyzed as the degree of variability of the average frequencies generated on a linear surface, related to the geographic space and by means of it's different slopes. The normal approximation was considered better withpopulations as combined with the weighing systems inverse of the distance and inverse of the distance squared in both levels of significance 1% and 5%. The same

  2. Hiding correlation-based Watermark templates using secret modulation

    NARCIS (Netherlands)

    Lichtenauer, J.; Setyawan, I.; Lagendijk, R.

    2004-01-01

    A possible solution to the difficult problem of geometrical distortion of watermarked images in a blind watermarking scenario is to use a template grid in the autocorrelation function. However, the important drawback of this method is that the watermark itself can be estimated and subtracted, or the

  3. G A Adebayo

    Indian Academy of Sciences (India)

    Home; Journals; Pramana – Journal of Physics. G A Adebayo. Articles written in Pramana – Journal of Physics. Volume 64 Issue 2 February 2005 pp 269-279 Research Articles. Structures and autocorrelation functions of liquid Al and Mg modelled via Lennard-Jones potential from molecular dynamics simulation.

  4. Pramana – Journal of Physics | Indian Academy of Sciences

    Indian Academy of Sciences (India)

    Home; Journals; Pramana – Journal of Physics. L A Hussain. Articles written in Pramana – Journal of Physics. Volume 64 Issue 2 February 2005 pp 269-279 Research Articles. Structures and autocorrelation functions of liquid Al and Mg modelled via Lennard-Jones potential from molecular dynamics simulation.

  5. Deterministic Predictions of Vessel Responses Based on Past Measurements

    DEFF Research Database (Denmark)

    Nielsen, Ulrik Dam; Jensen, Jørgen Juncher

    2017-01-01

    The paper deals with a prediction procedure from which global wave-induced responses can be deterministically predicted a short time, 10-50 s, ahead of current time. The procedure relies on the autocorrelation function and takes into account prior measurements only; i.e. knowledge about wave...

  6. Self-diffusion of particles interacting through a square-well or square-shoulder potential

    NARCIS (Netherlands)

    Wilbertz, H.; Michels, J.; Beijeren, H. van; Leegwater, J.A.

    1988-01-01

    The diffusion coefficient and velocity autocorrelation function for a fluid of particles interacting through a square-well or square-shoulder potential are calculated from a kinetic theory similar to the Davis-Rice-Sengers theory and the results are compared to those of computer simulations. At low

  7. Analysis of R-R intervals in patients with atrial fibrillation at rest and during exercise

    NARCIS (Netherlands)

    Bootsma, B.K.; Hoelen, A.J.; Strackee, J.; Meijler, F.L.

    Serial autocorrelation functions and histograms of R-R intervals in patients with atrial fibrillation, with and without digitalis, at rest and during exercise, were produced by a computer. At rest with and without digitalis the first and higher order coefficients did not differ from zero. During

  8. Ultrabright Linearly Polarized Photon Generation from a Nitrogen Vacancy Center in a Nanocube Dimer Antenna

    DEFF Research Database (Denmark)

    Andersen, Sebastian Kim Hjælm; Kumar, Shailesh; Bozhevolnyi, Sergey I.

    2017-01-01

    , while we further achieve strongly polarized emission and high single photon purity, evident by the measured autocorrelation with a g(2)(0) value of 0.08. These photon source features are key parameters for quantum technological applications, such as secure communication based on quantum key distribution...

  9. Model Identification of Integrated ARMA Processes

    Science.gov (United States)

    Stadnytska, Tetiana; Braun, Simone; Werner, Joachim

    2008-01-01

    This article evaluates the Smallest Canonical Correlation Method (SCAN) and the Extended Sample Autocorrelation Function (ESACF), automated methods for the Autoregressive Integrated Moving-Average (ARIMA) model selection commonly available in current versions of SAS for Windows, as identification tools for integrated processes. SCAN and ESACF can…

  10. Pramana – Journal of Physics | Indian Academy of Sciences

    Indian Academy of Sciences (India)

    The data are analyzed to determine the statistical features of overhead ionospheric plasma irregularities which are mostly of small duration < 30 minutes and are predominant during pre-midnight period. The increase of solar activity generally increases the depth of scintillation. The auto-correlation functions and power ...

  11. Pramana – Journal of Physics | Indian Academy of Sciences

    Indian Academy of Sciences (India)

    Home; Journals; Pramana – Journal of Physics. O akinlade. Articles written in Pramana – Journal of Physics. Volume 64 Issue 2 February 2005 pp 269-279 Research Articles. Structures and autocorrelation functions of liquid Al and Mg modelled via Lennard-Jones potential from molecular dynamics simulation.

  12. Predicting alpha diversity of African rain forests: models based on climate and satellite-derived data do not perform better than a purely spatial model

    NARCIS (Netherlands)

    Parmentier, I.; Harrigan, R.; Buermann, W.; Mitchard, E.T.A.; Saatchi, S.; Malhi, Y.; Bongers, F.; Hawthorne, W.D.; Leal, M.E.; Lewis, S.; Nusbaumer, L.; Sheil, D.; Sosef, M.S.M.; Bakayoko, A.; Chuyong, G.; Chatelain, C.; Comiskey, J.; Dauby, G.; Doucet, J.L.; Hardy, O.

    2011-01-01

    Aim Our aim was to evaluate the extent to which we can predict and map tree alpha diversity across broad spatial scales either by using climate and remote sensing data or by exploiting spatial autocorrelation patterns. Location Tropical rain forest, West Africa and Atlantic Central Africa. Methods

  13. Melodic cues for metre

    NARCIS (Netherlands)

    Vos, P G; van Dijk, A; Schomaker, Lambertus

    1994-01-01

    A method of time-series analysis and a time-beating experiment were used to test the structural and perceptual validity of notated metre. Autocorrelation applied to the flow of melodic intervals between notes from thirty fragments of compositions for solo instruments by J S Bach strongly supported

  14. Estimating relic magnetic fields from CMB temperature correlations

    International Nuclear Information System (INIS)

    Giovannini, Massimo

    2009-01-01

    The temperature and polarization inhomogeneities of the cosmic microwave background might bear the mark of predecoupling magnetism. The parameters of a putative magnetized background are hereby estimated, for the first time, from the observed temperature autocorrelation as well as from the measured temperature-polarization cross correlation.

  15. Genetic diversity and dispersal of Phragmites australis in a small river system

    Czech Academy of Sciences Publication Activity Database

    Fér, T.; Hroudová, Zdenka

    2009-01-01

    Roč. 90, č. 2 (2009), s. 165-171 ISSN 0304-3770 R&D Projects: GA AV ČR KJB6111304 Institutional research plan: CEZ:AV0Z60050516 Keywords : genetic variation * long-distance dispersal * spatial autocorrelation Subject RIV: EF - Botanics Impact factor: 1.697, year: 2009

  16. Fine-scale spatial distribution of plants and resources on a sandy soil in the Sahel

    NARCIS (Netherlands)

    Rietkerk, M.G.; Ouedraogo, T.; Kumar, L.; Sanou, S.; Langevelde, F. van; Kiema, A.; Koppel, J. van de; Andel, J. van; Hearne, J.; Skidmore, A.K.; Ridder, N. de; Stroosnijder, L.; Prins, H.H.T.

    2002-01-01

    We studied fine-scale spatial plant distribution in relation to the spatial distribution of erodible soil particles, organic matter, nutrients and soil water on a sandy to sandy loam soil in the Sahel. We hypothesized that the distribution of annual plants would be highly spatially autocorrelated

  17. The rapid cold hardening response of Collembola is influenced by thermal variability of the habitat

    DEFF Research Database (Denmark)

    Bahrndorff, Simon; Loeschcke, Volker; Pertoldi, Cino

    2009-01-01

    of their habitat. Population differences matched the daily fluctuations in temperature (CV) recorded at the site of collection as well as the day-to-day predictability (autocorrelation). The role of phylogenetic inertia was tested using sequence data from the cytochromec oxidase I (COI) gene and no signal...

  18. Visualizing Influential Observations in Dependent Data

    KAUST Repository

    Genton, Marc G.

    2010-01-01

    We introduce the hair-plot to visualize influential observations in dependent data. It consists of all trajectories of the value of an estimator when each observation is modified in turn by an additive perturbation. We define two measures of influence: the local influence which describes the rate of departure from the original estimate due to a small perturbation of each observation; and the asymptotic influence which indicates the influence on the original estimate of the most extreme contamination for each observation. The cases of estimators defined as quadratic forms or ratios of quadratic forms are investigated in detail. Sample autocovariances, covariograms, and variograms belong to the first case. Sample autocorrelations, correlograms, and indices of spatial autocorrelation such as Moran\\'s I belong to the second case.We illustrate our approach on various datasets from time series analysis and spatial statistics. This article has supplementary material online. © 2010 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.

  19. Built-Up Area Detection from High-Resolution Satellite Images Using Multi-Scale Wavelet Transform and Local Spatial Statistics

    Science.gov (United States)

    Chen, Y.; Zhang, Y.; Gao, J.; Yuan, Y.; Lv, Z.

    2018-04-01

    Recently, built-up area detection from high-resolution satellite images (HRSI) has attracted increasing attention because HRSI can provide more detailed object information. In this paper, multi-resolution wavelet transform and local spatial autocorrelation statistic are introduced to model the spatial patterns of built-up areas. First, the input image is decomposed into high- and low-frequency subbands by wavelet transform at three levels. Then the high-frequency detail information in three directions (horizontal, vertical and diagonal) are extracted followed by a maximization operation to integrate the information in all directions. Afterward, a cross-scale operation is implemented to fuse different levels of information. Finally, local spatial autocorrelation statistic is introduced to enhance the saliency of built-up features and an adaptive threshold algorithm is used to achieve the detection of built-up areas. Experiments are conducted on ZY-3 and Quickbird panchromatic satellite images, and the results show that the proposed method is very effective for built-up area detection.

  20. Phonons in a one-dimensional Yukawa chain: Dusty plasma experiment and model

    International Nuclear Information System (INIS)

    Liu Bin; Goree, J.

    2005-01-01

    Phonons in a one-dimensional chain of charged microspheres suspended in a plasma were studied in an experiment. The phonons correspond to random particle motion in the chain; no external manipulation was applied to excite the phonons. Two modes were observed, longitudinal and transverse. The velocity fluctuations in the experiment are analyzed using current autocorrelation functions and a phonon spectrum. The phonon energy was found to be unequally partitioned among phonon modes in the dusty plasma experiment. The experimental phonon spectrum was characterized by a dispersion relation that was found to differ from the dispersion relation for externally excited phonons. This difference is attributed to the presence of frictional damping due to gas, which affects the propagation of externally excited phonons differently from phonons that correspond to random particle motion. A model is developed and fit to the experiment to explain the features of the autocorrelation function, phonon spectrum, and the dispersion relation

  1. Arctic sea ice trends, variability and implications for seasonal ice forecasting.

    Science.gov (United States)

    Serreze, Mark C; Stroeve, Julienne

    2015-07-13

    September Arctic sea ice extent over the period of satellite observations has a strong downward trend, accompanied by pronounced interannual variability with a detrended 1 year lag autocorrelation of essentially zero. We argue that through a combination of thinning and associated processes related to a warming climate (a stronger albedo feedback, a longer melt season, the lack of especially cold winters) the downward trend itself is steepening. The lack of autocorrelation manifests both the inherent large variability in summer atmospheric circulation patterns and that oceanic heat loss in winter acts as a negative (stabilizing) feedback, albeit insufficient to counter the steepening trend. These findings have implications for seasonal ice forecasting. In particular, while advances in observing sea ice thickness and assimilating thickness into coupled forecast systems have improved forecast skill, there remains an inherent limit to predictability owing to the largely chaotic nature of atmospheric variability. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

  2. Pulsed-ultrasound tagging of light in living tissues

    Science.gov (United States)

    Lev, Aner; Rubanov, E.; Pomerantz, Ami; Sfez, Bruno G.

    2004-07-01

    Ultrasound can be used in order to locally modulate, or tag, light in a turbid medium. This tagging process is made possible due to the extreme sensitivity of laser speckle distribution to minute changes within the medium. This hybrid technique presents several advantages compared to all-optical tomographic techniques, in that the image resolution is fixed by the ultrasound focus diameter. To our best knowledge, only in vitro experiments have been performed, either on tissue-like phantoms or meat. However a strong difference exists between these sample and living tissues. In living tissues, different kind of liquids flow through the capillaries, strongly reducing the sspeckle autocorrelation time. We have performed experiments on both mice and humans, showing that the autocorrelation time is much shorter than what was previously thought. We show however that it is possible to obtain signal with acceptable signal to noise ratio down to a few cm depth. We will also discuss the origin and characteristics of the speckle noise.

  3. Real-Time Gait Cycle Parameter Recognition Using a Wearable Accelerometry System

    Directory of Open Access Journals (Sweden)

    Jun-Ming Lu

    2011-07-01

    Full Text Available This paper presents the development of a wearable accelerometry system for real-time gait cycle parameter recognition. Using a tri-axial accelerometer, the wearable motion detector is a single waist-mounted device to measure trunk accelerations during walking. Several gait cycle parameters, including cadence, step regularity, stride regularity and step symmetry can be estimated in real-time by using autocorrelation procedure. For validation purposes, five Parkinson’s disease (PD patients and five young healthy adults were recruited in an experiment. The gait cycle parameters among the two subject groups of different mobility can be quantified and distinguished by the system. Practical considerations and limitations for implementing the autocorrelation procedure in such a real-time system are also discussed. This study can be extended to the future attempts in real-time detection of disabling gaits, such as festinating or freezing of gait in PD patients. Ambulatory rehabilitation, gait assessment and personal telecare for people with gait disorders are also possible applications.

  4. Kernel based subspace projection of near infrared hyperspectral images of maize kernels

    DEFF Research Database (Denmark)

    Larsen, Rasmus; Arngren, Morten; Hansen, Per Waaben

    2009-01-01

    In this paper we present an exploratory analysis of hyper- spectral 900-1700 nm images of maize kernels. The imaging device is a line scanning hyper spectral camera using a broadband NIR illumi- nation. In order to explore the hyperspectral data we compare a series of subspace projection methods ......- tor transform outperform the linear methods as well as kernel principal components in producing interesting projections of the data.......In this paper we present an exploratory analysis of hyper- spectral 900-1700 nm images of maize kernels. The imaging device is a line scanning hyper spectral camera using a broadband NIR illumi- nation. In order to explore the hyperspectral data we compare a series of subspace projection methods...... including principal component analysis and maximum autocorrelation factor analysis. The latter utilizes the fact that interesting phenomena in images exhibit spatial autocorrelation. However, linear projections often fail to grasp the underlying variability on the data. Therefore we propose to use so...

  5. Extended constitutive laws for lamellar phases

    Directory of Open Access Journals (Sweden)

    Chi-Deuk Yoo

    2013-10-01

    Full Text Available Classically, stress and strain rate in linear viscoelastic materials are related by a constitutive relationship involving the viscoelastic modulus G(t. The same constitutive law, within Linear Response Theory, relates currents of conserved quantities and gradients of existing conjugate variables, and it involves the autocorrelation functions of the currents in equilibrium. We explore the consequences of the latter relationship in the case of a mesoscale model of a block copolymer, and derive the resulting relationship between viscous friction and order parameter diffusion that would result in a lamellar phase. We also explicitly consider in our derivation the fact that the dissipative part of the stress tensor must be consistent with the uniaxial symmetry of the phase. We then obtain a relationship between the stress and order parameter autocorrelation functions that can be interpreted as an extended constitutive law, one that offers a way to determine them from microscopic experiment or numerical simulation.

  6. Modelling bursty time series

    International Nuclear Information System (INIS)

    Vajna, Szabolcs; Kertész, János; Tóth, Bálint

    2013-01-01

    Many human-related activities show power-law decaying interevent time distribution with exponents usually varying between 1 and 2. We study a simple task-queuing model, which produces bursty time series due to the non-trivial dynamics of the task list. The model is characterized by a priority distribution as an input parameter, which describes the choice procedure from the list. We give exact results on the asymptotic behaviour of the model and we show that the interevent time distribution is power-law decaying for any kind of input distributions that remain normalizable in the infinite list limit, with exponents tunable between 1 and 2. The model satisfies a scaling law between the exponents of interevent time distribution (β) and autocorrelation function (α): α + β = 2. This law is general for renewal processes with power-law decaying interevent time distribution. We conclude that slowly decaying autocorrelation function indicates long-range dependence only if the scaling law is violated. (paper)

  7. Fetal source extraction from magnetocardiographic recordings by dependent component analysis

    Energy Technology Data Exchange (ETDEWEB)

    Araujo, Draulio B de [Department of Physics and Mathematics, FFCLRP, University of Sao Paulo, Ribeirao Preto, SP (Brazil); Barros, Allan Kardec [Department of Electrical Engineering, Federal University of Maranhao, Sao Luis, Maranhao (Brazil); Estombelo-Montesco, Carlos [Department of Physics and Mathematics, FFCLRP, University of Sao Paulo, Ribeirao Preto, SP (Brazil); Zhao, Hui [Department of Medical Physics, University of Wisconsin, Madison, WI (United States); Filho, A C Roque da Silva [Department of Physics and Mathematics, FFCLRP, University of Sao Paulo, Ribeirao Preto, SP (Brazil); Baffa, Oswaldo [Department of Physics and Mathematics, FFCLRP, University of Sao Paulo, Ribeirao Preto, SP (Brazil); Wakai, Ronald [Department of Medical Physics, University of Wisconsin, Madison, WI (United States); Ohnishi, Noboru [Department of Information Engineering, Nagoya University (Japan)

    2005-10-07

    Fetal magnetocardiography (fMCG) has been extensively reported in the literature as a non-invasive, prenatal technique that can be used to monitor various functions of the fetal heart. However, fMCG signals often have low signal-to-noise ratio (SNR) and are contaminated by strong interference from the mother's magnetocardiogram signal. A promising, efficient tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). Herein we propose an algorithm based on a variation of ICA, where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We model the system using autoregression, and identify the signal component of interest from the poles of the autocorrelation function. We show that the method is effective in removing the maternal signal, and is computationally efficient. We also compare our results to more established ICA methods, such as FastICA.

  8. Weak Form Efficiency of the Insurance Industry: Empirical Evidence from Nigeria

    Directory of Open Access Journals (Sweden)

    Emenike Kalu Onwukwe

    2018-02-01

    Full Text Available This paper evaluated the insurance sector of Nigeria Stock Exchange (NSE for evidence weak-form efficiency using daily returns from January 2009 to February 2016. The study employs descriptive analysis, non-parametric runs test and autocorrelation function as well as Ljung-Box Q statistics in conducting the evaluation. Descriptive statistics of the insurance sector return series showed negative skewness and leptokurtic distribution. Estimates from the Jarque-Bera normality test showed that the insurance sector returns did not follow normal distribution. Results of the runs test reject null hypothesis of randomness in the return series of the insurance sector in the period studied. Furthermore, the autocorrelation functions and the Ljung-Box Q tests provide evidence of serial correlation in the stock returns of the insurance sector. Overall results from the study suggested that the insurance sector of NSE is not weak-form efficient. Consequently, technical analysis on the insurance sector of the NSE may not be fruitless.

  9. Weak-form Efficiency of the Insurance Industry: Empirical Evidence from Nigeria

    Directory of Open Access Journals (Sweden)

    Emenike Kalu Onwukwe

    2018-02-01

    Full Text Available This paper evaluates the insurance sector of Nigeria Stock Exchange (NSE for evidence weak-form efficiency using daily returns from January 2009 to February 2016. The study employs descriptive analysis, non-parametric runs test and autocorrelation function as well as Ljung-Box Q statistics in conducting the evaluation. Descriptive statistics of the insurance sector return series show negative skewness and leptokurtic distribution. Estimates from the Jarque-Bera normality test show that the insurance sector returns do not follow a normal distribution. Results of the runs test reject the null hypothesis of randomness in the return series of the insurance sector in the period studied. Furthermore, the autocorrelation functions and the Ljung-Box Q tests provide evidence of serial correlation in the stock returns of the insurance sector. Overall results from the study suggest that the insurance sector of NSE is not weak-form efficient. Consequently, technical analysis on the insurance sector of the NSE may not be fruitless.

  10. A spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in Greater London.

    Science.gov (United States)

    Rushworth, Alastair; Lee, Duncan; Mitchell, Richard

    2014-07-01

    It has long been known that air pollution is harmful to human health, as many epidemiological studies have been conducted into its effects. Collectively, these studies have investigated both the acute and chronic effects of pollution, with the latter typically based on individual level cohort designs that can be expensive to implement. As a result of the increasing availability of small-area statistics, ecological spatio-temporal study designs are also being used, with which a key statistical problem is allowing for residual spatio-temporal autocorrelation that remains after the covariate effects have been removed. We present a new model for estimating the effects of air pollution on human health, which allows for residual spatio-temporal autocorrelation, and a study into the long-term effects of air pollution on human health in Greater London, England. The individual and joint effects of different pollutants are explored, via the use of single pollutant models and multiple pollutant indices. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

  11. Blind equalization with criterion with memory nonlinearity

    Science.gov (United States)

    Chen, Yuanjie; Nikias, Chrysostomos L.; Proakis, John G.

    1992-06-01

    Blind equalization methods usually combat the linear distortion caused by a nonideal channel via a transversal filter, without resorting to the a priori known training sequences. We introduce a new criterion with memory nonlinearity (CRIMNO) for the blind equalization problem. The basic idea of this criterion is to augment the Godard [or constant modulus algorithm (CMA)] cost function with additional terms that penalize the autocorrelations of the equalizer outputs. Several variations of the CRIMNO algorithms are derived, with the variations dependent on (1) whether the empirical averages or the single point estimates are used to approximate the expectations, (2) whether the recent or the delayed equalizer coefficients are used, and (3) whether the weights applied to the autocorrelation terms are fixed or are allowed to adapt. Simulation experiments show that the CRIMNO algorithm, and especially its adaptive weight version, exhibits faster convergence speed than the Godard (or CMA) algorithm. Extensions of the CRIMNO criterion to accommodate the case of correlated inputs to the channel are also presented.

  12. Forecasting Alcohol Consumption in the Czech Republic

    Directory of Open Access Journals (Sweden)

    Tereza Slováčková

    2016-01-01

    Full Text Available The paper deals with a forecast of developments in alcohol consumption based on current alcohol consumption per capita (expressed in litres of pure alcohol, and time series extrapolations. Alcohol consumption is to be considered from the vantage point of knowing the specifics of the product and the consequences of its excessive consumption. The predictive methodology makes use of the Box‑Jenkins method; the ARIMA model, taking into account the autocorrelation and partial autocorrelation process, which is a prerequisite for the successful identification of a time series model; model parameter estimation; appropriate transformations of time series; determining the order of differentiation and subsequent verification of the model. The chosen methodology for future trends in alcohol consumptions is a prerequisite for the proposed optional measures to control alcohol consumption in the Czech Republic. Due to the long term nature of the process to draw up and implement alcohol consumption regulation measures, the forecast covers the forthcoming 10 years.

  13. An automated approach for segmentation of intravascular ultrasound images based on parametric active contour models

    International Nuclear Information System (INIS)

    Vard, Alireza; Jamshidi, Kamal; Movahhedinia, Naser

    2012-01-01

    This paper presents a fully automated approach to detect the intima and media-adventitia borders in intravascular ultrasound images based on parametric active contour models. To detect the intima border, we compute a new image feature applying a combination of short-term autocorrelations calculated for the contour pixels. These feature values are employed to define an energy function of the active contour called normalized cumulative short-term autocorrelation. Exploiting this energy function, the intima border is separated accurately from the blood region contaminated by high speckle noise. To extract media-adventitia boundary, we define a new form of energy function based on edge, texture and spring forces for the active contour. Utilizing this active contour, the media-adventitia border is identified correctly even in presence of branch openings and calcifications. Experimental results indicate accuracy of the proposed methods. In addition, statistical analysis demonstrates high conformity between manual tracing and the results obtained by the proposed approaches.

  14. A heteroskedastic error covariance matrix estimator using a first-order conditional autoregressive Markov simulation for deriving asympotical efficient estimates from ecological sampled Anopheles arabiensis aquatic habitat covariates

    Directory of Open Access Journals (Sweden)

    Githure John I

    2009-09-01

    Full Text Available Abstract Background Autoregressive regression coefficients for Anopheles arabiensis aquatic habitat models are usually assessed using global error techniques and are reported as error covariance matrices. A global statistic, however, will summarize error estimates from multiple habitat locations. This makes it difficult to identify where there are clusters of An. arabiensis aquatic habitats of acceptable prediction. It is therefore useful to conduct some form of spatial error analysis to detect clusters of An. arabiensis aquatic habitats based on uncertainty residuals from individual sampled habitats. In this research, a method of error estimation for spatial simulation models was demonstrated using autocorrelation indices and eigenfunction spatial filters to distinguish among the effects of parameter uncertainty on a stochastic simulation of ecological sampled Anopheles aquatic habitat covariates. A test for diagnostic checking error residuals in an An. arabiensis aquatic habitat model may enable intervention efforts targeting productive habitats clusters, based on larval/pupal productivity, by using the asymptotic distribution of parameter estimates from a residual autocovariance matrix. The models considered in this research extends a normal regression analysis previously considered in the literature. Methods Field and remote-sampled data were collected during July 2006 to December 2007 in Karima rice-village complex in Mwea, Kenya. SAS 9.1.4® was used to explore univariate statistics, correlations, distributions, and to generate global autocorrelation statistics from the ecological sampled datasets. A local autocorrelation index was also generated using spatial covariance parameters (i.e., Moran's Indices in a SAS/GIS® database. The Moran's statistic was decomposed into orthogonal and uncorrelated synthetic map pattern components using a Poisson model with a gamma-distributed mean (i.e. negative binomial regression. The eigenfunction

  15. Biometric security based on ECG

    NARCIS (Netherlands)

    Ma, L.; Groot, de J.A.; Linnartz, J.P.M.G.

    2011-01-01

    Recently the electrocardiogram (ECG) has been proposed as a novel biometric. This paper aims to construct a reliable ECG verification system, in terms of privacy protection. To this end, an improved expression to estimate the capacity in the autocorrelation (AC) of the ECG is derived, which not only

  16. Monitoring Poisson time series using multi-process models

    DEFF Research Database (Denmark)

    Engebjerg, Malene Dahl Skov; Lundbye-Christensen, Søren; Kjær, Birgitte B.

    aspects of health resource management may also be addressed. In this paper we center on the detection of outbreaks of infectious diseases. This is achieved by a multi-process Poisson state space model taking autocorrelation and overdispersion into account, which has been applied to a data set concerning...

  17. Multichannel signal enhancement using a remote wireless microphone

    NARCIS (Netherlands)

    Bloemendal, Brian; Van De Laar, Jakob; Sommen, Piet

    2012-01-01

    A novel approach to multichannel signal enhancement is presented that exploits data from a remote wireless microphone (RWM). This RWM is placed near an interfering source and transmits only autocorrelation data of its observations to a host, i.e., not the entire signal. The host has access to the

  18. Imaging and Scattering Measurements for Diesel Spray Combustion: Optical Development and Phenomenological Studies

    Science.gov (United States)

    2012-09-30

    the CS2 was contained in a rectangular colorimeter cell with a custom built Teflon cap to alleviate the evaporation of the hazardous chemical...6: A comparison of the image quality between the older colorimeter cell (a) and the new containment cell (b). 2.5 Autocorrelation-Based Pulse Length

  19. Modelling primary branch growth based on a multilevel nonlinear ...

    African Journals Online (AJOL)

    In addition to random effects, various time series correlation structures were evaluated to account for residual autocorrelation, and the AR(1) and ARMA(1,1) structures were selected for the branch diameter and length growth models, respectively. Model validation results using an independent data set confirmed that ...

  20. Spectral Estimation by the Random Dec Technique

    DEFF Research Database (Denmark)

    Brincker, Rune; Jensen, Jacob L.; Krenk, Steen

    1990-01-01

    This paper contains an empirical study of the accuracy of the Random Dec (RDD) technique. Realizations of the response from a single-degree-of-freedom system loaded by white noise are simulated using an ARMA model. The Autocorrelation function is estimated using the RDD technique and the estimated...

  1. Spectral Estimation by the Random DEC Technique

    DEFF Research Database (Denmark)

    Brincker, Rune; Jensen, J. Laigaard; Krenk, S.

    This paper contains an empirical study of the accuracy of the Random Dec (RDD) technique. Realizations of the response from a single-degree-of-freedom system loaded by white noise are simulated using an ARMA model. The Autocorrelation function is estimated using the RDD technique and the estimated...

  2. An application of superpositions of two-state Markovian sources to the modelling of self-similar behaviour

    DEFF Research Database (Denmark)

    Andersen, Allan T.; Nielsen, Bo Friis

    1997-01-01

    We present a modelling framework and a fitting method for modelling second order self-similar behaviour with the Markovian arrival process (MAP). The fitting method is based on fitting to the autocorrelation function of counts a second order self-similar process. It is shown that with this fittin...

  3. An In-vivo investigation of transverse flow estimation

    DEFF Research Database (Denmark)

    Udesen, Jesper; Jensen, Jørgen Arendt

    2004-01-01

    , and 1.4 seconds of data is acquired. Using 2 parallel receive beamformers a transverse oscillation is introduced with an oscillation period 1.2 mm. The velocity estimation is performed using an extended autocorrelation algorithm. The volume flow can be estimated with a relative standard deviation of 13...

  4. On a conjecture of Alley and Alder for fluids and Lorentz models

    NARCIS (Netherlands)

    Ernst, M.H.; Beijeren, H. van

    1981-01-01

    We discuss a conjecture of Alley and Alder predicting a relation between the four-point and the two-point velocity autocorrelation functions for fluids and Lorentz models at sufficiently long times. If the conjecture is correct a modified Burnett coefficient can be defined, which has a finite value,

  5. Option Pricing and Momentum

    NARCIS (Netherlands)

    Rodriguez, J.C.

    2007-01-01

    If managers are reluctant to fully adjust dividends to changes in earnings, stock returns and changes in the dividend yield will tend to be negatively correlated. When this is the case, stock returns will exhibit positive autocorrelation, or mo- mentum. This paper studies the pricing of options in

  6. Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

    Science.gov (United States)

    Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

    2014-01-01

    Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landescommunities' composition turnovers. The relative importance of processes and filters was assessed by distance-based redundancy analysis. This study demonstrates significant community composition turnover rates for soil bacteria and fungi, which were dependent on the region. Bacterial and fungal community composition turnovers were mainly driven by environmental selection explaining from 10% to 20% of community composition variations, but spatial variables also explained 3% to 9% of total variance. These variables highlighted significant spatial autocorrelation of both communities unexplained by the environmental variables measured and could partly be explained by dispersal limitations. Although the identified filters and their hierarchy were dependent on the region and organism, selection was systematically based on a common group of environmental variables: pH, trophic resources, texture and land use. Spatial autocorrelation was also important at coarse (80 to 120 km radius) and/or medium (40 to 65 km radius) spatial scales, suggesting dispersal limitations at these scales.

  7. Why GPS makes distances bigger than they are.

    Science.gov (United States)

    Ranacher, Peter; Brunauer, Richard; Trutschnig, Wolfgang; Van der Spek, Stefan; Reich, Siegfried

    2016-02-01

    Global navigation satellite systems such as the Global Positioning System (GPS) is one of the most important sensors for movement analysis. GPS is widely used to record the trajectories of vehicles, animals and human beings. However, all GPS movement data are affected by both measurement and interpolation errors. In this article we show that measurement error causes a systematic bias in distances recorded with a GPS; the distance between two points recorded with a GPS is - on average - bigger than the true distance between these points. This systematic 'overestimation of distance' becomes relevant if the influence of interpolation error can be neglected, which in practice is the case for movement sampled at high frequencies. We provide a mathematical explanation of this phenomenon and illustrate that it functionally depends on the autocorrelation of GPS measurement error ( C ). We argue that C can be interpreted as a quality measure for movement data recorded with a GPS. If there is a strong autocorrelation between any two consecutive position estimates, they have very similar error. This error cancels out when average speed, distance or direction is calculated along the trajectory. Based on our theoretical findings we introduce a novel approach to determine C in real-world GPS movement data sampled at high frequencies. We apply our approach to pedestrian trajectories and car trajectories. We found that the measurement error in the data was strongly spatially and temporally autocorrelated and give a quality estimate of the data. Most importantly, our findings are not limited to GPS alone. The systematic bias and its implications are bound to occur in any movement data collected with absolute positioning if interpolation error can be neglected.

  8. From fast fluorescence imaging to molecular diffusion law on live cell membranes in a commercial microscope.

    Science.gov (United States)

    Di Rienzo, Carmine; Gratton, Enrico; Beltram, Fabio; Cardarelli, Francesco

    2014-10-09

    It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn't need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on µm-sized membrane regions in the micro-to-milli-second time range.

  9. Regionalization of the Modified Bartlett-Lewis Rectangular Pulse Stochastic Rainfall Model

    Directory of Open Access Journals (Sweden)

    Dongkyun Kim

    2013-01-01

    Full Text Available Parameters of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP stochastic rainfall simulation model were regionalized across the contiguous United States. Three thousand four hundred forty-four National Climate Data Center (NCDC rain gauges were used to obtain spatial and seasonal patterns of the model parameters. The MBLRP model was calibrated to minimize the discrepancy between the precipitation depth statistics between the observed and MBLRP-generated precipitation time series. These statistics included the mean, variance, probability of zero rainfall and autocorrelation at 1-, 3-, 12- and 24-hour accumulation intervals. The Ordinary Kriging interpolation technique was used to generate maps of the six MBLRP model parameters for each of the 12 months of the year. All parameters had clear to discernible regional tendencies; except for one related to rain cell duration distribution. Parameter seasonality was not obvious and it was more apparent in some locations than in others, depending on the seasonality of the rainfall statistics. Cross-validation was used to assess the validity of the parameter maps. The results indicate that the suggested maps reproduce well the observed rainfall statistics for different accumulation intervals, except for the lag-1 autocorrelation coefficient. The boundaries of the expected residual, with 95% confidence, between the observed rainfall statistics and the simulated rainfall statistics based on the map parameters were approximately ±0.064 mm hr-1, ±1.63 mm2 hr-2, ±0.16, and ±0.030 for the mean, variance, lag-1 autocorrelation and probability of zero rainfall at hourly accumulation levels, respectively. The estimated parameter values were also used to estimate the storm and rain cell characteristics.

  10. The algorithm of random length sequences synthesis for frame synchronization of digital television systems

    Directory of Open Access Journals (Sweden)

    Аndriy V. Sadchenko

    2015-12-01

    Full Text Available Digital television systems need to ensure that all digital signals processing operations are performed simultaneously and consistently. Frame synchronization dictated by the need to match phases of transmitter and receiver so that it would be possible to identify the start of a frame. As a frame synchronization signals are often used long length binary sequence with good aperiodic autocorrelation function. Aim: This work is dedicated to the development of the algorithm of random length sequences synthesis. Materials and Methods: The paper provides a comparative analysis of the known sequences, which can be used at present as synchronization ones, revealed their advantages and disadvantages. This work proposes the algorithm for the synthesis of binary synchronization sequences of random length with good autocorrelation properties based on noise generator with a uniform distribution law of probabilities. A "white noise" semiconductor generator is proposed to use as the initial material for the synthesis of binary sequences with desired properties. Results: The statistical analysis of the initial implementations of the "white noise" and synthesized sequences for frame synchronization of digital television is conducted. The comparative analysis of the synthesized sequences with known ones was carried out. The results show the benefits of obtained sequences in compare with known ones. The performed simulations confirm the obtained results. Conclusions: Thus, the search algorithm of binary synchronization sequences with desired autocorrelation properties received. According to this algorithm, the sequence can be longer in length and without length limitations. The received sync sequence can be used for frame synchronization in modern digital communication systems that will increase their efficiency and noise immunity.

  11. A 3D Monte Carlo model of radiation affecting cells, and its application to neuronal cells and GCR irradiation

    Science.gov (United States)

    Ponomarev, Artem; Sundaresan, Alamelu; Kim, Angela; Vazquez, Marcelo E.; Guida, Peter; Kim, Myung-Hee; Cucinotta, Francis A.

    A 3D Monte Carlo model of radiation transport in matter is applied to study the effect of heavy ion radiation on human neuronal cells. Central nervous system effects, including cognitive impairment, are suspected from the heavy ion component of galactic cosmic radiation (GCR) during space missions. The model can count, for instance, the number of direct hits from ions, which will have the most affect on the cells. For comparison, the remote hits, which are received through δ-rays from the projectile traversing space outside the volume of the cell, are also simulated and their contribution is estimated. To simulate tissue effects from irradiation, cellular matrices of neuronal cells, which were derived from confocal microscopy, were simulated in our model. To produce this realistic model of the brain tissue, image segmentation was used to identify cells in the images of cells cultures. The segmented cells were inserted pixel by pixel into the modeled physical space, which represents a volume of interacting cells with periodic boundary conditions (PBCs). PBCs were used to extrapolate the model results to the macroscopic tissue structures. Specific spatial patterns for cell apoptosis are expected from GCR, as heavy ions produce concentrated damage along their trajectories. The apoptotic cell patterns were modeled based on the action cross sections for apoptosis, which were estimated from the available experimental data. The cell patterns were characterized with an autocorrelation function, which values are higher for non-random cell patterns, and the values of the autocorrelation function were compared for X rays and Fe ion irradiations. The autocorrelation function indicates the directionality effects present in apoptotic neuronal cells from GCR.

  12. Critical fluctuations in cortical models near instability

    Directory of Open Access Journals (Sweden)

    Matthew J. Aburn

    2012-08-01

    Full Text Available Computational studies often proceed from the premise that cortical dynamics operate in a linearly stable domain, where fluctuations dissipate quickly and show only short memory. Studies of human EEG, however, have shown significant autocorrelation at time lags on the scale of minutes, indicating the need to consider regimes where nonlinearities influence the dynamics. Statistical properties such as increased autocorrelation length, increased variance, power-law scaling and bistable switching have been suggested as generic indicators of the approach to bifurcation in nonlinear dynamical systems. We study temporal fluctuations in a widely-employed computational model (the Jansen-Rit model of cortical activity, examining the statistical signatures that accompany bifurcations. Approaching supercritical Hopf bifurcations through tuning of the background excitatory input, we find a dramatic increase in the autocorrelation length that depends sensitively on the direction in phase space of the input fluctuations and hence on which neuronal subpopulation is stochastically perturbed. Similar dependence on the input direction is found in the distribution of fluctuation size and duration, which show power law scaling that extends over four orders of magnitude at the Hopf bifurcation. We conjecture that the alignment in phase space between the input noise vector and the center manifold of the Hopf bifurcation is directly linked to these changes. These results are consistent with the possibility of statistical indicators of linear instability being detectable in real EEG time series. However, even in a simple cortical model, we find that these indicators may not necessarily be visible even when bifurcations are present because their expression can depend sensitively on the neuronal pathway of incoming fluctuations.

  13. Does the classically chaotic Henon–Heiles oscillator exhibit ...

    Indian Academy of Sciences (India)

    The threshold intensity of the laser field for an electron moving in the HH potential to reach its continuum is identified and in this region quantum chaos has been diagnosed through a combination of various dynamical signatures such as the autocorrelation function, quantum `phase-space' volume, `phase-space' trajectory, ...

  14. Movements vary according to dispersal stage, group size, and rainfall: The case of the African lion

    Science.gov (United States)

    Nicholas B. Elliot; Samuel A. Cushman; Andrew J. Loveridge; Godfrey Mtare; David W. Macdonald

    2014-01-01

    Dispersal is one of the most important life-history traits affecting species persistence and evolution and is increasingly relevant for conservation biology as ecosystems become more fragmented. However, movement during different dispersal stages has been difficult to study and remains poorly understood. We analyzed movement metrics and patterns of autocorrelation from...

  15. Dissecting components of population-level variation in seed production and the evolution of masting behavior.

    Science.gov (United States)

    W. D. Koenig; D. Kelly; V. L. Sork; R. P. Duncan; J. S. Elkinton; M.S. Peltonen; R. D. Westfall

    2003-01-01

    Mast-fruiting or masting behavior is the cumulative result of the reproductive patterns of individuals within a population and thus involves components of individual variability, between-individual synchrony, and endogenous cycles of temporal autocorrelation. Extending prior work by Herrera, we explore the interrelationships of these components using data on individual...

  16. Dynamics of a Brownian particle in a plasma in the long-time limit

    International Nuclear Information System (INIS)

    Dickman, R.; Varley, R.L.

    1981-01-01

    The velocity autocorrelation function (VAF) of a Brownian particle in a plasma is calculated in the long-time limit. The Brownian particle VAF exhibits the same qualitative behavior as the electron VAF in a one-component plasma: oscillations at the plasma frequency and decay approx. t -3 sup(/) 2 . (orig.)

  17. The Biasing Effects of Unmodeled ARMA Time Series Processes on Latent Growth Curve Model Estimates

    Science.gov (United States)

    Sivo, Stephen; Fan, Xitao; Witta, Lea

    2005-01-01

    The purpose of this study was to evaluate the robustness of estimated growth curve models when there is stationary autocorrelation among manifest variable errors. The results suggest that when, in practice, growth curve models are fitted to longitudinal data, alternative rival hypotheses to consider would include growth models that also specify…

  18. Topological susceptibility and the sampling of field space in Nf=2 lattice QCD simulations

    International Nuclear Information System (INIS)

    Bruno, Mattia; Schaefer, Stefan; Sommer, Rainer

    2014-06-01

    We present a measurement of the topological susceptibility in two flavor QCD. In this observable, large autocorrelations are present and also sizable cutoff effects have to be faced in the continuum extrapolation. Within the statistical accuracy of the computation, the result agrees with the expectation from leading order chiral perturbation theory.

  19. Testing a Fourier Accelerated Hybrid Monte Carlo Algorithm

    OpenAIRE

    Catterall, S.; Karamov, S.

    2001-01-01

    We describe a Fourier Accelerated Hybrid Monte Carlo algorithm suitable for dynamical fermion simulations of non-gauge models. We test the algorithm in supersymmetric quantum mechanics viewed as a one-dimensional Euclidean lattice field theory. We find dramatic reductions in the autocorrelation time of the algorithm in comparison to standard HMC.

  20. SPATIALLY AUTOCORRELATED DEMOGRAPHY AND INTERPOND MIGRATION IN THE CALIFORNIA TIGER SALAMANDER (AMBYSTOME CALIFORNIENSE)

    Science.gov (United States)

    We investigated the metapopulation structure of the California tiger salamander (Ambystoma californiense) using a combination of indirect and direct methods to evaluate two key requirements of modern metapopulation models: 1) that patches support somewhat independent populations ...