WorldWideScience

Sample records for minimum variance control

  1. A note on minimum-variance theory and beyond

    Energy Technology Data Exchange (ETDEWEB)

    Feng Jianfeng [Department of Informatics, Sussex University, Brighton, BN1 9QH (United Kingdom); Tartaglia, Giangaetano [Physics Department, Rome University ' La Sapienza' , Rome 00185 (Italy); Tirozzi, Brunello [Physics Department, Rome University ' La Sapienza' , Rome 00185 (Italy)

    2004-04-30

    We revisit the minimum-variance theory proposed by Harris and Wolpert (1998 Nature 394 780-4), discuss the implications of the theory on modelling the firing patterns of single neurons and analytically find the optimal control signals, trajectories and velocities. Under the rate coding assumption, input control signals employed in the minimum-variance theory should be Fitts processes rather than Poisson processes. Only if information is coded by interspike intervals, Poisson processes are in agreement with the inputs employed in the minimum-variance theory. For the integrate-and-fire model with Fitts process inputs, interspike intervals of efferent spike trains are very irregular. We introduce diffusion approximations to approximate neural models with renewal process inputs and present theoretical results on calculating moments of interspike intervals of the integrate-and-fire model. Results in Feng, et al (2002 J. Phys. A: Math. Gen. 35 7287-304) are generalized. In conclusion, we present a complete picture on the minimum-variance theory ranging from input control signals, to model outputs, and to its implications on modelling firing patterns of single neurons.

  2. A note on minimum-variance theory and beyond

    International Nuclear Information System (INIS)

    Feng Jianfeng; Tartaglia, Giangaetano; Tirozzi, Brunello

    2004-01-01

    We revisit the minimum-variance theory proposed by Harris and Wolpert (1998 Nature 394 780-4), discuss the implications of the theory on modelling the firing patterns of single neurons and analytically find the optimal control signals, trajectories and velocities. Under the rate coding assumption, input control signals employed in the minimum-variance theory should be Fitts processes rather than Poisson processes. Only if information is coded by interspike intervals, Poisson processes are in agreement with the inputs employed in the minimum-variance theory. For the integrate-and-fire model with Fitts process inputs, interspike intervals of efferent spike trains are very irregular. We introduce diffusion approximations to approximate neural models with renewal process inputs and present theoretical results on calculating moments of interspike intervals of the integrate-and-fire model. Results in Feng, et al (2002 J. Phys. A: Math. Gen. 35 7287-304) are generalized. In conclusion, we present a complete picture on the minimum-variance theory ranging from input control signals, to model outputs, and to its implications on modelling firing patterns of single neurons

  3. Minimum Variance Portfolios in the Brazilian Equity Market

    Directory of Open Access Journals (Sweden)

    Alexandre Rubesam

    2013-03-01

    Full Text Available We investigate minimum variance portfolios in the Brazilian equity market using different methods to estimate the covariance matrix, from the simple model of using the sample covariance to multivariate GARCH models. We compare the performance of the minimum variance portfolios to those of the following benchmarks: (i the IBOVESPA equity index, (ii an equally-weighted portfolio, (iii the maximum Sharpe ratio portfolio and (iv the maximum growth portfolio. Our results show that the minimum variance portfolio has higher returns with lower risk compared to the benchmarks. We also consider long-short 130/30 minimum variance portfolios and obtain similar results. The minimum variance portfolio invests in relatively few stocks with low βs measured with respect to the IBOVESPA index, being easily replicable by individual and institutional investors alike.

  4. The Distribution of the Sample Minimum-Variance Frontier

    OpenAIRE

    Raymond Kan; Daniel R. Smith

    2008-01-01

    In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier, and we propose an improved estimator of the population frontier. In addition, we provide the exact distribution of the out-of-sample mean and variance of sample minimum-variance portfolios. This allows us t...

  5. Output Power Control of Wind Turbine Generator by Pitch Angle Control using Minimum Variance Control

    Science.gov (United States)

    Senjyu, Tomonobu; Sakamoto, Ryosei; Urasaki, Naomitsu; Higa, Hiroki; Uezato, Katsumi; Funabashi, Toshihisa

    In recent years, there have been problems such as exhaustion of fossil fuels, e. g., coal and oil, and environmental pollution resulting from consumption. Effective utilization of renewable energies such as wind energy is expected instead of the fossil fuel. Wind energy is not constant and windmill output is proportional to the cube of wind speed, which cause the generated power of wind turbine generators (WTGs) to fluctuate. In order to reduce fluctuating components, there is a method to control pitch angle of blades of the windmill. In this paper, output power leveling of wind turbine generator by pitch angle control using an adaptive control is proposed. A self-tuning regulator is used in adaptive control. The control input is determined by the minimum variance control. It is possible to compensate control input to alleviate generating power fluctuation with using proposed controller. The simulation results with using actual detailed model for wind power system show effectiveness of the proposed controller.

  6. Towards a mathematical foundation of minimum-variance theory

    Energy Technology Data Exchange (ETDEWEB)

    Feng Jianfeng [COGS, Sussex University, Brighton (United Kingdom); Zhang Kewei [SMS, Sussex University, Brighton (United Kingdom); Wei Gang [Mathematical Department, Baptist University, Hong Kong (China)

    2002-08-30

    The minimum-variance theory which accounts for arm and eye movements with noise signal inputs was proposed by Harris and Wolpert (1998 Nature 394 780-4). Here we present a detailed theoretical analysis of the theory and analytical solutions of the theory are obtained. Furthermore, we propose a new version of the minimum-variance theory, which is more realistic for a biological system. For the new version we show numerically that the variance is considerably reduced. (author)

  7. PORTFOLIO COMPOSITION WITH MINIMUM VARIANCE: COMPARISON WITH MARKET BENCHMARKS

    Directory of Open Access Journals (Sweden)

    Daniel Menezes Cavalcante

    2016-07-01

    Full Text Available Portfolio optimization strategies are advocated as being able to allow the composition of stocks portfolios that provide returns above market benchmarks. This study aims to determine whether, in fact, portfolios based on the minimum variance strategy, optimized by the Modern Portfolio Theory, are able to achieve earnings above market benchmarks in Brazil. Time series of 36 securities traded on the BM&FBOVESPA have been analyzed in a long period of time (1999-2012, with sample windows of 12, 36, 60 and 120 monthly observations. The results indicated that the minimum variance portfolio performance is superior to market benchmarks (CDI and IBOVESPA in terms of return and risk-adjusted return, especially in medium and long-term investment horizons.

  8. Deviation of the Variances of Classical Estimators and Negative Integer Moment Estimator from Minimum Variance Bound with Reference to Maxwell Distribution

    Directory of Open Access Journals (Sweden)

    G. R. Pasha

    2006-07-01

    Full Text Available In this paper, we present that how much the variances of the classical estimators, namely, maximum likelihood estimator and moment estimator deviate from the minimum variance bound while estimating for the Maxwell distribution. We also sketch this difference for the negative integer moment estimator. We note the poor performance of the negative integer moment estimator in the said consideration while maximum likelihood estimator attains minimum variance bound and becomes an attractive choice.

  9. Minimum variance and variance of outgoing quality limit MDS-1(c1, c2) plans

    Science.gov (United States)

    Raju, C.; Vidya, R.

    2016-06-01

    In this article, the outgoing quality (OQ) and total inspection (TI) of multiple deferred state sampling plans MDS-1(c1,c2) are studied. It is assumed that the inspection is rejection rectification. Procedures for designing MDS-1(c1,c2) sampling plans with minimum variance of OQ and TI are developed. A procedure for obtaining a plan for a designated upper limit for the variance of the OQ (VOQL) is outlined.

  10. Portfolios Dominating Indices: Optimization with Second-Order Stochastic Dominance Constraints vs. Minimum and Mean Variance Portfolios

    Directory of Open Access Journals (Sweden)

    Neslihan Fidan Keçeci

    2016-10-01

    Full Text Available The paper compares portfolio optimization with the Second-Order Stochastic Dominance (SSD constraints with mean-variance and minimum variance portfolio optimization. As a distribution-free decision rule, stochastic dominance takes into account the entire distribution of return rather than some specific characteristic, such as variance. The paper is focused on practical applications of the portfolio optimization and uses the Portfolio Safeguard (PSG package, which has precoded modules for optimization with SSD constraints, mean-variance and minimum variance portfolio optimization. We have done in-sample and out-of-sample simulations for portfolios of stocks from the Dow Jones, S&P 100 and DAX indices. The considered portfolios’ SSD dominate the Dow Jones, S&P 100 and DAX indices. Simulation demonstrated a superior performance of portfolios with SD constraints, versus mean-variance and minimum variance portfolios.

  11. Minimum variance Monte Carlo importance sampling with parametric dependence

    International Nuclear Information System (INIS)

    Ragheb, M.M.H.; Halton, J.; Maynard, C.W.

    1981-01-01

    An approach for Monte Carlo Importance Sampling with parametric dependence is proposed. It depends upon obtaining by proper weighting over a single stage the overall functional dependence of the variance on the importance function parameter over a broad range of its values. Results corresponding to minimum variance are adapted and other results rejected. Numerical calculation for the estimation of intergrals are compared to Crude Monte Carlo. Results explain the occurrences of the effective biases (even though the theoretical bias is zero) and infinite variances which arise in calculations involving severe biasing and a moderate number of historis. Extension to particle transport applications is briefly discussed. The approach constitutes an extension of a theory on the application of Monte Carlo for the calculation of functional dependences introduced by Frolov and Chentsov to biasing, or importance sample calculations; and is a generalization which avoids nonconvergence to the optimal values in some cases of a multistage method for variance reduction introduced by Spanier. (orig.) [de

  12. Investigating the minimum achievable variance in a Monte Carlo criticality calculation

    Energy Technology Data Exchange (ETDEWEB)

    Christoforou, Stavros; Eduard Hoogenboom, J. [Delft University of Technology, Mekelweg 15, 2629 JB Delft (Netherlands)

    2008-07-01

    The sources of variance in a Monte Carlo criticality calculation are identified and their contributions analyzed. A zero-variance configuration is initially simulated using analytically calculated adjoint functions for biasing. From there, the various sources are analyzed. It is shown that the minimum threshold comes from the fact that the fission source is approximated. In addition, the merits of a simple variance reduction method, such as implicit capture, are shown when compared to an analog simulation. Finally, it is shown that when non-exact adjoint functions are used for biasing, the variance reduction is rather insensitive to the quality of the adjoints, suggesting that the generation of the adjoints should have as low CPU cost as possible, in order to o et the CPU cost in the implementation of the biasing of a simulation. (authors)

  13. Linear-Array Photoacoustic Imaging Using Minimum Variance-Based Delay Multiply and Sum Adaptive Beamforming Algorithm

    OpenAIRE

    Mozaffarzadeh, Moein; Mahloojifar, Ali; Orooji, Mahdi; Kratkiewicz, Karl; Adabi, Saba; Nasiriavanaki, Mohammadreza

    2017-01-01

    In Photoacoustic imaging (PA), Delay-and-Sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely Delay-Multiply-and-Sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a novel beamformer is introduced using Minimum Variance (MV) adaptive beamforming combined with DMAS, so-called Minimum Variance-Based D...

  14. Double Minimum Variance Beamforming Method to Enhance Photoacoustic Imaging

    OpenAIRE

    Paridar, Roya; Mozaffarzadeh, Moein; Nasiriavanaki, Mohammadreza; Orooji, Mahdi

    2018-01-01

    One of the common algorithms used to reconstruct photoacoustic (PA) images is the non-adaptive Delay-and-Sum (DAS) beamformer. However, the quality of the reconstructed PA images obtained by DAS is not satisfying due to its high level of sidelobes and wide mainlobe. In contrast, adaptive beamformers, such as minimum variance (MV), result in an improved image compared to DAS. In this paper, a novel beamforming method, called Double MV (D-MV) is proposed to enhance the image quality compared to...

  15. A Minimum Variance Algorithm for Overdetermined TOA Equations with an Altitude Constraint.

    Energy Technology Data Exchange (ETDEWEB)

    Romero, Louis A; Mason, John J.

    2018-04-01

    We present a direct (non-iterative) method for solving for the location of a radio frequency (RF) emitter, or an RF navigation receiver, using four or more time of arrival (TOA) measurements and an assumed altitude above an ellipsoidal earth. Both the emitter tracking problem and the navigation application are governed by the same equations, but with slightly different interpreta- tions of several variables. We treat the assumed altitude as a soft constraint, with a specified noise level, just as the TOA measurements are handled, with their respective noise levels. With 4 or more TOA measurements and the assumed altitude, the problem is overdetermined and is solved in the weighted least squares sense for the 4 unknowns, the 3-dimensional position and time. We call the new technique the TAQMV (TOA Altitude Quartic Minimum Variance) algorithm, and it achieves the minimum possible error variance for given levels of TOA and altitude estimate noise. The method algebraically produces four solutions, the least-squares solution, and potentially three other low residual solutions, if they exist. In the lightly overdermined cases where multiple local minima in the residual error surface are more likely to occur, this algebraic approach can produce all of the minima even when an iterative approach fails to converge. Algorithm performance in terms of solution error variance and divergence rate for bas eline (iterative) and proposed approach are given in tables.

  16. Portfolios dominating indices: Optimization with second-order stochastic dominance constraints vs. minimum and mean variance portfolios

    OpenAIRE

    Keçeci, Neslihan Fidan; Kuzmenko, Viktor; Uryasev, Stan

    2016-01-01

    The paper compares portfolio optimization with the Second-Order Stochastic Dominance (SSD) constraints with mean-variance and minimum variance portfolio optimization. As a distribution-free decision rule, stochastic dominance takes into account the entire distribution of return rather than some specific characteristic, such as variance. The paper is focused on practical applications of the portfolio optimization and uses the Portfolio Safeguard (PSG) package, which has precoded modules for op...

  17. Portfolios Dominating Indices: Optimization with Second-Order Stochastic Dominance Constraints vs. Minimum and Mean Variance Portfolios

    OpenAIRE

    Neslihan Fidan Keçeci; Viktor Kuzmenko; Stan Uryasev

    2016-01-01

    The paper compares portfolio optimization with the Second-Order Stochastic Dominance (SSD) constraints with mean-variance and minimum variance portfolio optimization. As a distribution-free decision rule, stochastic dominance takes into account the entire distribution of return rather than some specific characteristic, such as variance. The paper is focused on practical applications of the portfolio optimization and uses the Portfolio Safeguard (PSG) package, which has precoded modules for op...

  18. An improved minimum variance beamforming applied to plane-wave imaging in medical ultrasound

    DEFF Research Database (Denmark)

    Deylami, Ali Mohades; Asl, Babak Mohammadzadeh; Jensen, Jørgen Arendt

    2016-01-01

    Minimum variance beamformer (MVB) is an adaptive beamformer which provides images with higher resolution and contrast in comparison with non-adaptive beamformers like delay and sum (DAS). It finds weight vector of beamformer by minimizing output power while keeping the desired signal unchanged. We...

  19. Minimum variance linear unbiased estimators of loss and inventory

    International Nuclear Information System (INIS)

    Stewart, K.B.

    1977-01-01

    The article illustrates a number of approaches for estimating the material balance inventory and a constant loss amount from the accountability data from a sequence of accountability periods. The approaches all lead to linear estimates that have minimum variance. Techniques are shown whereby ordinary least squares, weighted least squares and generalized least squares computer programs can be used. Two approaches are recursive in nature and lend themselves to small specialized computer programs. Another approach is developed that is easy to program; could be used with a desk calculator and can be used in a recursive way from accountability period to accountability period. Some previous results are also reviewed that are very similar in approach to the present ones and vary only in the way net throughput measurements are statistically modeled. 5 refs

  20. Interdependence of NAFTA capital markets: A minimum variance portfolio approach

    Directory of Open Access Journals (Sweden)

    López-Herrera Francisco

    2014-01-01

    Full Text Available We estimate the long-run relationships among NAFTA capital market returns and then calculate the weights of a “time-varying minimum variance portfolio” that includes the Canadian, Mexican, and USA capital markets between March 2007 and March 2009, a period of intense turbulence in international markets. Our results suggest that the behavior of NAFTA market investors is not consistent with that of a theoretical “risk-averse” agent during periods of high uncertainty and may be either considered as irrational or attributed to a possible “home country bias”. This finding represents valuable information for portfolio managers and contributes to a better understanding of the nature of the markets in which they invest. It also has practical implications in the design of international portfolio investment policies.

  1. The Achilles Heel of Normal Determinations via Minimum Variance Techniques: Worldline Dependencies

    Science.gov (United States)

    Ma, Z.; Scudder, J. D.; Omidi, N.

    2002-12-01

    Time series of data collected across current layers are usually organized by divining coordinate transformations (as from minimum variance) that permits a geometrical interpretation for the data collected. Almost without exception the current layer geometry is inferred by supposing that the current carrying layer is locally planar. Only after this geometry is ``determined'' can the various quantities predicted by theory calculated. The precision of reconnection rated ``measured'' and the quantitative support for or against component reconnection be evaluated. This paper defines worldline traversals across fully resolved Hall two fluid models of reconnecting current sheets (with varying sizes of guide fields) and across a 2-D hybrid solution of a super critical shock layer. Along each worldline various variance techniques are used to infer current sheet normals based on the data observed along this worldline alone. We then contrast these inferred normals with those known from the overview of the fully resolved spatial pictures of the layer. Absolute errors of 20 degrees in the normal are quite commonplace, but errors of 40-90 deg are also implied, especially for worldlines that make more and more oblique angles to the true current sheet normal. These mistaken ``inferences'' are traceable to the degree that the data collected sample 2-D variations within these layers or not. While it is not surprising that these variance techniques give incorrect errors in the presence of layers that possess 2-D variations, it is illuminating that such large errors need not be signalled by the traditional error formulae for the error cones on normals that have been previously used to estimate the errors of normal choices. Frequently the absolute errors that depend on worldline path can be 10 times the random error that formulae would predict based on eigenvalues of the covariance matrix. A given time series cannot be associated in any a priori way with a specific worldline

  2. Unbiased minimum variance estimator of a matrix exponential function. Application to Boltzmann/Bateman coupled equations solving

    International Nuclear Information System (INIS)

    Dumonteil, E.; Diop, C. M.

    2009-01-01

    This paper derives an unbiased minimum variance estimator (UMVE) of a matrix exponential function of a normal wean. The result is then used to propose a reference scheme to solve Boltzmann/Bateman coupled equations, thanks to Monte Carlo transport codes. The last section will present numerical results on a simple example. (authors)

  3. Experimental performance assessment of the sub-band minimum variance beamformer for ultrasound imaging

    DEFF Research Database (Denmark)

    Diamantis, Konstantinos; Greenaway, Alan H.; Anderson, Tom

    2017-01-01

    Recent progress in adaptive beamforming techniques for medical ultrasound has shown that current resolution limits can be surpassed. One method of obtaining improved lateral resolution is the Minimum Variance (MV) beamformer. The frequency domain implementation of this method effectively divides...... the broadband ultrasound signals into sub-bands (MVS) to conform with the narrow-band assumption of the original MV theory. This approach is investigated here using experimental Synthetic Aperture (SA) data from wire and cyst phantoms. A 7 MHz linear array transducer is used with the SARUS experimental...

  4. Eigenspace-Based Minimum Variance Adaptive Beamformer Combined with Delay Multiply and Sum: Experimental Study

    OpenAIRE

    Mozaffarzadeh, Moein; Mahloojifar, Ali; Nasiriavanaki, Mohammadreza; Orooji, Mahdi

    2017-01-01

    Delay and sum (DAS) is the most common beamforming algorithm in linear-array photoacoustic imaging (PAI) as a result of its simple implementation. However, it leads to a low resolution and high sidelobes. Delay multiply and sum (DMAS) was used to address the incapabilities of DAS, providing a higher image quality. However, the resolution improvement is not well enough compared to eigenspace-based minimum variance (EIBMV). In this paper, the EIBMV beamformer has been combined with DMAS algebra...

  5. Linear-array photoacoustic imaging using minimum variance-based delay multiply and sum adaptive beamforming algorithm

    Science.gov (United States)

    Mozaffarzadeh, Moein; Mahloojifar, Ali; Orooji, Mahdi; Kratkiewicz, Karl; Adabi, Saba; Nasiriavanaki, Mohammadreza

    2018-02-01

    In photoacoustic imaging, delay-and-sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely delay-multiply-and-sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a beamformer is introduced using minimum variance (MV) adaptive beamforming combined with DMAS, so-called minimum variance-based DMAS (MVB-DMAS). It is shown that expanding the DMAS equation results in multiple terms representing a DAS algebra. It is proposed to use the MV adaptive beamformer instead of the existing DAS. MVB-DMAS is evaluated numerically and experimentally. In particular, at the depth of 45 mm MVB-DMAS results in about 31, 18, and 8 dB sidelobes reduction compared to DAS, MV, and DMAS, respectively. The quantitative results of the simulations show that MVB-DMAS leads to improvement in full-width-half-maximum about 96%, 94%, and 45% and signal-to-noise ratio about 89%, 15%, and 35% compared to DAS, DMAS, MV, respectively. In particular, at the depth of 33 mm of the experimental images, MVB-DMAS results in about 20 dB sidelobes reduction in comparison with other beamformers.

  6. Linear-array photoacoustic imaging using minimum variance-based delay multiply and sum adaptive beamforming algorithm.

    Science.gov (United States)

    Mozaffarzadeh, Moein; Mahloojifar, Ali; Orooji, Mahdi; Kratkiewicz, Karl; Adabi, Saba; Nasiriavanaki, Mohammadreza

    2018-02-01

    In photoacoustic imaging, delay-and-sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely delay-multiply-and-sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a beamformer is introduced using minimum variance (MV) adaptive beamforming combined with DMAS, so-called minimum variance-based DMAS (MVB-DMAS). It is shown that expanding the DMAS equation results in multiple terms representing a DAS algebra. It is proposed to use the MV adaptive beamformer instead of the existing DAS. MVB-DMAS is evaluated numerically and experimentally. In particular, at the depth of 45 mm MVB-DMAS results in about 31, 18, and 8 dB sidelobes reduction compared to DAS, MV, and DMAS, respectively. The quantitative results of the simulations show that MVB-DMAS leads to improvement in full-width-half-maximum about 96%, 94%, and 45% and signal-to-noise ratio about 89%, 15%, and 35% compared to DAS, DMAS, MV, respectively. In particular, at the depth of 33 mm of the experimental images, MVB-DMAS results in about 20 dB sidelobes reduction in comparison with other beamformers. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

  7. A phantom study on temporal and subband Minimum Variance adaptive beamforming

    DEFF Research Database (Denmark)

    Diamantis, Konstantinos; Voxen, Iben Holfort; Greenaway, Alan H.

    2014-01-01

    This paper compares experimentally temporal and subband implementations of the Minimum Variance (MV) adaptive beamformer for medical ultrasound imaging. The performance of the two approaches is tested by comparing wire phantom measurements, obtained by the research ultrasound scanner SARUS. A 7 MHz...... BK8804 linear transducer was used to scan a wire phantom in which wires are separated by 10 mm. Performance is then evaluated by the lateral Full-Width-Half-Maximum (FWHM), the Peak Sidelobe Level (PSL), and the computational load. Beamformed single emission responses are also compared with those...... from conventional Delay-and-Sum (DAS) beamformer. FWHM measured at the depth of 46.6 mm, is 0.02 mm (0.09λ) for both adaptive methods while the corresponding values for Hanning and Boxcar weights are 0.64 and 0.44 mm respectively. Between the MV beamformers a -2 dB difference in PSL is noticed in favor...

  8. Multi-period fuzzy mean-semi variance portfolio selection problem with transaction cost and minimum transaction lots using genetic algorithm

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Barati

    2016-04-01

    Full Text Available Multi-period models of portfolio selection have been developed in the literature with respect to certain assumptions. In this study, for the first time, the portfolio selection problem has been modeled based on mean-semi variance with transaction cost and minimum transaction lots considering functional constraints and fuzzy parameters. Functional constraints such as transaction cost and minimum transaction lots were included. In addition, the returns on assets parameters were considered as trapezoidal fuzzy numbers. An efficient genetic algorithm (GA was designed, results were analyzed using numerical instances and sensitivity analysis were executed. In the numerical study, the problem was solved based on the presence or absence of each mode of constraints including transaction costs and minimum transaction lots. In addition, with the use of sensitivity analysis, the results of the model were presented with the variations of minimum expected rate of programming periods.

  9. Effects of Important Parameters Variations on Computing Eigenspace-Based Minimum Variance Weights for Ultrasound Tissue Harmonic Imaging

    OpenAIRE

    Heidari, Mehdi Haji; Mozaffarzadeh, Moein; Manwar, Rayyan; Nasiriavanaki, Mohammadreza

    2018-01-01

    In recent years, the minimum variance (MV) beamforming has been widely studied due to its high resolution and contrast in B-mode Ultrasound imaging (USI). However, the performance of the MV beamformer is degraded at the presence of noise, as a result of the inaccurate covariance matrix estimation which leads to a low quality image. Second harmonic imaging (SHI) provides many advantages over the conventional pulse-echo USI, such as enhanced axial and lateral resolutions. However, the low signa...

  10. Portfolio optimization with mean-variance model

    Science.gov (United States)

    Hoe, Lam Weng; Siew, Lam Weng

    2016-06-01

    Investors wish to achieve the target rate of return at the minimum level of risk in their investment. Portfolio optimization is an investment strategy that can be used to minimize the portfolio risk and can achieve the target rate of return. The mean-variance model has been proposed in portfolio optimization. The mean-variance model is an optimization model that aims to minimize the portfolio risk which is the portfolio variance. The objective of this study is to construct the optimal portfolio using the mean-variance model. The data of this study consists of weekly returns of 20 component stocks of FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI). The results of this study show that the portfolio composition of the stocks is different. Moreover, investors can get the return at minimum level of risk with the constructed optimal mean-variance portfolio.

  11. Experimental performance assessment of the sub-band minimum variance beamformer for ultrasound imaging

    DEFF Research Database (Denmark)

    Diamantis, Konstantinos; Greenaway, Alan H.; Anderson, Tom

    2017-01-01

    Recent progress in adaptive beamforming techniques for medical ultrasound has shown that current resolution limits can be surpassed. One method of obtaining improved lateral resolution is the Minimum Variance (MV) beamformer. The frequency domain implementation of this method effectively divides...... the broadband ultrasound signals into sub-bands (MVS) to conform with the narrow-band assumption of the original MV theory. This approach is investigated here using experimental Synthetic Aperture (SA) data from wire and cyst phantoms. A 7 MHz linear array transducer is used with the SARUS experimental...... ultrasound scanner for the data acquisition. The lateral resolution and the contrast obtained, are evaluated and compared with those from the conventional Delay-and-Sum (DAS) beamformer and the MV temporal implementation (MVT). From the wire phantom the Full-Width-at-Half-Maximum (FWHM) measured at a depth...

  12. Minimum energy control and optimal-satisfactory control of Boolean control network

    International Nuclear Information System (INIS)

    Li, Fangfei; Lu, Xiwen

    2013-01-01

    In the literatures, to transfer the Boolean control network from the initial state to the desired state, the expenditure of energy has been rarely considered. Motivated by this, this Letter investigates the minimum energy control and optimal-satisfactory control of Boolean control network. Based on the semi-tensor product of matrices and Floyd's algorithm, minimum energy, constrained minimum energy and optimal-satisfactory control design for Boolean control network are given respectively. A numerical example is presented to illustrate the efficiency of the obtained results.

  13. Iterative Minimum Variance Beamformer with Low Complexity for Medical Ultrasound Imaging.

    Science.gov (United States)

    Deylami, Ali Mohades; Asl, Babak Mohammadzadeh

    2018-06-04

    Minimum variance beamformer (MVB) improves the resolution and contrast of medical ultrasound images compared with delay and sum (DAS) beamformer. The weight vector of this beamformer should be calculated for each imaging point independently, with a cost of increasing computational complexity. The large number of necessary calculations limits this beamformer to application in real-time systems. A beamformer is proposed based on the MVB with lower computational complexity while preserving its advantages. This beamformer avoids matrix inversion, which is the most complex part of the MVB, by solving the optimization problem iteratively. The received signals from two imaging points close together do not vary much in medical ultrasound imaging. Therefore, using the previously optimized weight vector for one point as initial weight vector for the new neighboring point can improve the convergence speed and decrease the computational complexity. The proposed method was applied on several data sets, and it has been shown that the method can regenerate the results obtained by the MVB while the order of complexity is decreased from O(L 3 ) to O(L 2 ). Copyright © 2018 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

  14. Eigenspace-based minimum variance adaptive beamformer combined with delay multiply and sum: experimental study

    Science.gov (United States)

    Mozaffarzadeh, Moein; Mahloojifar, Ali; Nasiriavanaki, Mohammadreza; Orooji, Mahdi

    2018-02-01

    Delay and sum (DAS) is the most common beamforming algorithm in linear-array photoacoustic imaging (PAI) as a result of its simple implementation. However, it leads to a low resolution and high sidelobes. Delay multiply and sum (DMAS) was used to address the incapabilities of DAS, providing a higher image quality. However, the resolution improvement is not well enough compared to eigenspace-based minimum variance (EIBMV). In this paper, the EIBMV beamformer has been combined with DMAS algebra, called EIBMV-DMAS, using the expansion of DMAS algorithm. The proposed method is used as the reconstruction algorithm in linear-array PAI. EIBMV-DMAS is experimentally evaluated where the quantitative and qualitative results show that it outperforms DAS, DMAS and EIBMV. The proposed method degrades the sidelobes for about 365 %, 221 % and 40 %, compared to DAS, DMAS and EIBMV, respectively. Moreover, EIBMV-DMAS improves the SNR about 158 %, 63 % and 20 %, respectively.

  15. Multidimensional adaptive testing with a minimum error-variance criterion

    NARCIS (Netherlands)

    van der Linden, Willem J.

    1997-01-01

    The case of adaptive testing under a multidimensional logistic response model is addressed. An adaptive algorithm is proposed that minimizes the (asymptotic) variance of the maximum-likelihood (ML) estimator of a linear combination of abilities of interest. The item selection criterion is a simple

  16. Risk control and the minimum significant risk

    International Nuclear Information System (INIS)

    Seiler, F.A.; Alvarez, J.L.

    1996-01-01

    Risk management implies that the risk manager can, by his actions, exercise at least a modicum of control over the risk in question. In the terminology of control theory, a management action is a control signal imposed as feedback on the system to bring about a desired change in the state of the system. In the terminology of risk management, an action is taken to bring a predicted risk to lower values. Even if it is assumed that the management action taken is 100% effective and that the projected risk reduction is infinitely well known, there is a lower limit to the desired effects that can be achieved. It is based on the fact that all risks, such as the incidence of cancer, exhibit a degree of variability due to a number of extraneous factors such as age at exposure, sex, location, and some lifestyle parameters such as smoking or the consumption of alcohol. If the control signal is much smaller than the variability of the risk, the signal is lost in the noise and control is lost. This defines a minimum controllable risk based on the variability of the risk over the population considered. This quantity is the counterpart of the minimum significant risk which is defined by the uncertainties of the risk model. Both the minimum controllable risk and the minimum significant risk are evaluated for radiation carcinogenesis and are shown to be of the same order of magnitude. For a realistic management action, the assumptions of perfectly effective action and perfect model prediction made above have to be dropped, resulting in an effective minimum controllable risk which is determined by both risk limits. Any action below that effective limit is futile, but it is also unethical due to the ethical requirement of doing more good than harm. Finally, some implications of the effective minimum controllable risk on the use of the ALARA principle and on the evaluation of remedial action goals are presented

  17. Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

    International Nuclear Information System (INIS)

    Yu, Zhiyong

    2013-01-01

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

  18. Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-12-15

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

  19. A Mean-Variance Criterion for Economic Model Predictive Control of Stochastic Linear Systems

    DEFF Research Database (Denmark)

    Sokoler, Leo Emil; Dammann, Bernd; Madsen, Henrik

    2014-01-01

    , the tractability of the resulting optimal control problem is addressed. We use a power management case study to compare different variations of the mean-variance strategy with EMPC based on the certainty equivalence principle. The certainty equivalence strategy is much more computationally efficient than the mean......-variance strategies, but it does not account for the variance of the uncertain parameters. Openloop simulations suggest that a single-stage mean-variance approach yields a significantly lower operating cost than the certainty equivalence strategy. In closed-loop, the single-stage formulation is overly conservative...... be modified to perform almost as well as the two-stage mean-variance formulation. Nevertheless, we argue that the mean-variance approach can be used both as a strategy for evaluating less computational demanding methods such as the certainty equivalence method, and as an individual control strategy when...

  20. Output Feedback Adaptive Control of Non-Minimum Phase Systems Using Optimal Control Modification

    Science.gov (United States)

    Nguyen, Nhan; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

    2018-01-01

    This paper describes output feedback adaptive control approaches for non-minimum phase SISO systems with relative degree 1 and non-strictly positive real (SPR) MIMO systems with uniform relative degree 1 using the optimal control modification method. It is well-known that the standard model-reference adaptive control (MRAC) cannot be used to control non-SPR plants to track an ideal SPR reference model. Due to the ideal property of asymptotic tracking, MRAC attempts an unstable pole-zero cancellation which results in unbounded signals for non-minimum phase SISO systems. The optimal control modification can be used to prevent the unstable pole-zero cancellation which results in a stable adaptation of non-minimum phase SISO systems. However, the tracking performance using this approach could suffer if the unstable zero is located far away from the imaginary axis. The tracking performance can be recovered by using an observer-based output feedback adaptive control approach which uses a Luenberger observer design to estimate the state information of the plant. Instead of explicitly specifying an ideal SPR reference model, the reference model is established from the linear quadratic optimal control to account for the non-minimum phase behavior of the plant. With this non-minimum phase reference model, the observer-based output feedback adaptive control can maintain stability as well as tracking performance. However, in the presence of the mismatch between the SPR reference model and the non-minimum phase plant, the standard MRAC results in unbounded signals, whereas a stable adaptation can be achieved with the optimal control modification. An application of output feedback adaptive control for a flexible wing aircraft illustrates the approaches.

  1. AN ADAPTIVE OPTIMAL KALMAN FILTER FOR STOCHASTIC VIBRATION CONTROL SYSTEM WITH UNKNOWN NOISE VARIANCES

    Institute of Scientific and Technical Information of China (English)

    Li Shu; Zhuo Jiashou; Ren Qingwen

    2000-01-01

    In this paper, an optimal criterion is presented for adaptive Kalman filter in a control sys tem with unknown variances of stochastic vibration by constructing a function of noise variances and minimizing the function. We solve the model and measure variances by using DFP optimal method to guarantee the results of Kalman filter to be optimized. Finally, the control of vibration can be implemented by LQG method.

  2. Reduction of treatment delivery variances with a computer-controlled treatment delivery system

    International Nuclear Information System (INIS)

    Fraass, B.A.; Lash, K.L.; Matrone, G.M.; Lichter, A.S.

    1997-01-01

    Purpose: To analyze treatment delivery variances for 3-D conformal therapy performed at various levels of treatment delivery automation, ranging from manual field setup to virtually complete computer-controlled treatment delivery using a computer-controlled conformal radiotherapy system. Materials and Methods: All external beam treatments performed in our department during six months of 1996 were analyzed to study treatment delivery variances versus treatment complexity. Treatments for 505 patients (40,641 individual treatment ports) on four treatment machines were studied. All treatment variances noted by treatment therapists or quality assurance reviews (39 in all) were analyzed. Machines 'M1' (CLinac (6(100))) and 'M2' (CLinac 1800) were operated in a standard manual setup mode, with no record and verify system (R/V). Machines 'M3' (CLinac 2100CD/MLC) and ''M4'' (MM50 racetrack microtron system with MLC) treated patients under the control of a computer-controlled conformal radiotherapy system (CCRS) which 1) downloads the treatment delivery plan from the planning system, 2) performs some (or all) of the machine set-up and treatment delivery for each field, 3) monitors treatment delivery, 4) records all treatment parameters, and 5) notes exceptions to the electronically-prescribed plan. Complete external computer control is not available on M3, so it uses as many CCRS features as possible, while M4 operates completely under CCRS control and performs semi-automated and automated multi-segment intensity modulated treatments. Analysis of treatment complexity was based on numbers of fields, individual segments (ports), non-axial and non-coplanar plans, multi-segment intensity modulation, and pseudo-isocentric treatments (and other plans with computer-controlled table motions). Treatment delivery time was obtained from the computerized scheduling system (for manual treatments) or from CCRS system logs. Treatment therapists rotate among the machines, so this analysis

  3. Nonlinear unbiased minimum-variance filter for Mars entry autonomous navigation under large uncertainties and unknown measurement bias.

    Science.gov (United States)

    Xiao, Mengli; Zhang, Yongbo; Fu, Huimin; Wang, Zhihua

    2018-05-01

    High-precision navigation algorithm is essential for the future Mars pinpoint landing mission. The unknown inputs caused by large uncertainties of atmospheric density and aerodynamic coefficients as well as unknown measurement biases may cause large estimation errors of conventional Kalman filters. This paper proposes a derivative-free version of nonlinear unbiased minimum variance filter for Mars entry navigation. This filter has been designed to solve this problem by estimating the state and unknown measurement biases simultaneously with derivative-free character, leading to a high-precision algorithm for the Mars entry navigation. IMU/radio beacons integrated navigation is introduced in the simulation, and the result shows that with or without radio blackout, our proposed filter could achieve an accurate state estimation, much better than the conventional unscented Kalman filter, showing the ability of high-precision Mars entry navigation algorithm. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  4. 77 FR 43196 - Minimum Internal Control Standards and Technical Standards

    Science.gov (United States)

    2012-07-24

    ... NATIONAL INDIAN GAMING COMMISSION 25 CFR Parts 543 and 547 Minimum Internal Control Standards [email protected] . SUPPLEMENTARY INFORMATION: Part 543 addresses minimum internal control standards (MICS) for Class II gaming operations. The regulations require tribes to establish controls and implement...

  5. A comparison between temporal and subband minimum variance adaptive beamforming

    Science.gov (United States)

    Diamantis, Konstantinos; Voxen, Iben H.; Greenaway, Alan H.; Anderson, Tom; Jensen, Jørgen A.; Sboros, Vassilis

    2014-03-01

    This paper compares the performance between temporal and subband Minimum Variance (MV) beamformers for medical ultrasound imaging. Both adaptive methods provide an optimized set of apodization weights but are implemented in the time and frequency domains respectively. Their performance is evaluated with simulated synthetic aperture data obtained from Field II and is quantified by the Full-Width-Half-Maximum (FWHM), the Peak-Side-Lobe level (PSL) and the contrast level. From a point phantom, a full sequence of 128 emissions with one transducer element transmitting and all 128 elements receiving each time, provides a FWHM of 0.03 mm (0.14λ) for both implementations at a depth of 40 mm. This value is more than 20 times lower than the one achieved by conventional beamforming. The corresponding values of PSL are -58 dB and -63 dB for time and frequency domain MV beamformers, while a value no lower than -50 dB can be obtained from either Boxcar or Hanning weights. Interestingly, a single emission with central element #64 as the transmitting aperture provides results comparable to the full sequence. The values of FWHM are 0.04 mm and 0.03 mm and those of PSL are -42 dB and -46 dB for temporal and subband approaches. From a cyst phantom and for 128 emissions, the contrast level is calculated at -54 dB and -63 dB respectively at the same depth, with the initial shape of the cyst being preserved in contrast to conventional beamforming. The difference between the two adaptive beamformers is less significant in the case of a single emission, with the contrast level being estimated at -42 dB for the time domain and -43 dB for the frequency domain implementation. For the estimation of a single MV weight of a low resolution image formed by a single emission, 0.44 * 109 calculations per second are required for the temporal approach. The same numbers for the subband approach are 0.62 * 109 for the point and 1.33 * 109 for the cyst phantom. The comparison demonstrates similar

  6. Models of Postural Control: Shared Variance in Joint and COM Motions.

    Directory of Open Access Journals (Sweden)

    Melissa C Kilby

    Full Text Available This paper investigated the organization of the postural control system in human upright stance. To this aim the shared variance between joint and 3D total body center of mass (COM motions was analyzed using multivariate canonical correlation analysis (CCA. The CCA was performed as a function of established models of postural control that varied in their joint degrees of freedom (DOF, namely, an inverted pendulum ankle model (2DOF, ankle-hip model (4DOF, ankle-knee-hip model (5DOF, and ankle-knee-hip-neck model (7DOF. Healthy young adults performed various postural tasks (two-leg and one-leg quiet stances, voluntary AP and ML sway on a foam and rigid surface of support. Based on CCA model selection procedures, the amount of shared variance between joint and 3D COM motions and the cross-loading patterns we provide direct evidence of the contribution of multi-DOF postural control mechanisms to human balance. The direct model fitting of CCA showed that incrementing the DOFs in the model through to 7DOF was associated with progressively enhanced shared variance with COM motion. In the 7DOF model, the first canonical function revealed more active involvement of all joints during more challenging one leg stances and dynamic posture tasks. Furthermore, the shared variance was enhanced during the dynamic posture conditions, consistent with a reduction of dimension. This set of outcomes shows directly the degeneracy of multivariate joint regulation in postural control that is influenced by stance and surface of support conditions.

  7. Optimal control of LQG problem with an explicit trade-off between mean and variance

    Science.gov (United States)

    Qian, Fucai; Xie, Guo; Liu, Ding; Xie, Wenfang

    2011-12-01

    For discrete-time linear-quadratic Gaussian (LQG) control problems, a utility function on the expectation and the variance of the conventional performance index is considered. The utility function is viewed as an overall objective of the system and can perform the optimal trade-off between the mean and the variance of performance index. The nonlinear utility function is first converted into an auxiliary parameters optimisation problem about the expectation and the variance. Then an optimal closed-loop feedback controller for the nonseparable mean-variance minimisation problem is designed by nonlinear mathematical programming. Finally, simulation results are given to verify the algorithm's effectiveness obtained in this article.

  8. Minimum critical power ratio control device for nuclear power plants

    International Nuclear Information System (INIS)

    Kurosawa, Tsuneo.

    1991-01-01

    Reactor core flowrate is determined by comparing a minimum critical power ratio calculated based on the status amount of a nuclear power plant and a control value for the minimum critical power ratio that depends on the reactor core flowrate. Further, the minimum critical power ratio and a control value for the minimum critical power ratio that depends on the reactor thermal power are compared to set a reactor thermal power converted to a reactor core flowrate. Deviation between the thus determined reactor core flowrate and the present reactor core flowrate is calculated. When the obtained deviation is lower than a rated value, a reactor core flowrate set signal is generated to a reactor flowrate control means, to control the reactor power by a recycling flowrate control system of the reactor. On the other hand, when the deviation exceeds the determined value, the reactor core flowrate set signal is converted into a reactor thermal power, to control the position of control rods and control the reactor power. Then, monitor and control can be conducted safely and automatically without depending on operator's individual ability over the entire operation range corresponding to load following operation. (N.H.)

  9. An elementary components of variance analysis for multi-center quality control

    International Nuclear Information System (INIS)

    Munson, P.J.; Rodbard, D.

    1977-01-01

    The serious variability of RIA results from different laboratories indicates the need for multi-laboratory collaborative quality control (QC) studies. Statistical analysis methods for such studies using an 'analysis of variance with components of variance estimation' are discussed. This technique allocates the total variance into components corresponding to between-laboratory, between-assay, and residual or within-assay variability. Components of variance analysis also provides an intelligent way to combine the results of several QC samples run at different evels, from which we may decide if any component varies systematically with dose level; if not, pooling of estimates becomes possible. We consider several possible relationships of standard deviation to the laboratory mean. Each relationship corresponds to an underlying statistical model, and an appropriate analysis technique. Tests for homogeneity of variance may be used to determine if an appropriate model has been chosen, although the exact functional relationship of standard deviation to lab mean may be difficult to establish. Appropriate graphical display of the data aids in visual understanding of the data. A plot of the ranked standard deviation vs. ranked laboratory mean is a convenient way to summarize a QC study. This plot also allows determination of the rank correlation, which indicates a net relationship of variance to laboratory mean. (orig.) [de

  10. An elementary components of variance analysis for multi-centre quality control

    International Nuclear Information System (INIS)

    Munson, P.J.; Rodbard, D.

    1978-01-01

    The serious variability of RIA results from different laboratories indicates the need for multi-laboratory collaborative quality-control (QC) studies. Simple graphical display of data in the form of histograms is useful but insufficient. The paper discusses statistical analysis methods for such studies using an ''analysis of variance with components of variance estimation''. This technique allocates the total variance into components corresponding to between-laboratory, between-assay, and residual or within-assay variability. Problems with RIA data, e.g. severe non-uniformity of variance and/or departure from a normal distribution violate some of the usual assumptions underlying analysis of variance. In order to correct these problems, it is often necessary to transform the data before analysis by using a logarithmic, square-root, percentile, ranking, RIDIT, ''Studentizing'' or other transformation. Ametric transformations such as ranks or percentiles protect against the undue influence of outlying observations, but discard much intrinsic information. Several possible relationships of standard deviation to the laboratory mean are considered. Each relationship corresponds to an underlying statistical model and an appropriate analysis technique. Tests for homogeneity of variance may be used to determine whether an appropriate model has been chosen, although the exact functional relationship of standard deviation to laboratory mean may be difficult to establish. Appropriate graphical display aids visual understanding of the data. A plot of the ranked standard deviation versus ranked laboratory mean is a convenient way to summarize a QC study. This plot also allows determination of the rank correlation, which indicates a net relationship of variance to laboratory mean

  11. 25 CFR 542.7 - What are the minimum internal control standards for bingo?

    Science.gov (United States)

    2010-04-01

    ... 25 Indians 2 2010-04-01 2010-04-01 false What are the minimum internal control standards for bingo... SERVICES MINIMUM INTERNAL CONTROL STANDARDS § 542.7 What are the minimum internal control standards for... utilized, alternate documentation and/or procedures that provide at least the level of control described by...

  12. Application of Minimum-time Optimal Control System in Buck-Boost Bi-linear Converters

    Directory of Open Access Journals (Sweden)

    S. M. M. Shariatmadar

    2017-08-01

    Full Text Available In this study, the theory of minimum-time optimal control system in buck-boost bi-linear converters is described, so that output voltage regulation is carried out within minimum time. For this purpose, the Pontryagin's Minimum Principle is applied to find optimal switching level applying minimum-time optimal control rules. The results revealed that by utilizing an optimal switching level instead of classical switching patterns, output voltage regulation will be carried out within minimum time. However, transient energy index of increased overvoltage significantly reduces in order to attain minimum time optimal control in reduced output load. The laboratory results were used in order to verify numerical simulations.

  13. Minimum throttling feedwater control in VVER-1000 and PWR NPPs

    International Nuclear Information System (INIS)

    Symkin, B.E.; Thaulez, F.

    2004-01-01

    This paper presents an approach for the design and implementation of advanced digital control systems that use a minimum-throttling algorithm for the feedwater control. The minimum-throttling algorithm for the feedwater control, i.e. for the control of steam generators level and of the feedwater pumps speed, is applicable for NPPs with variable speed feedwater pumps. It operates in such a way that the feedwater control valve in the most loaded loop is wide open, steam generator level in this loop being controlled by the feedwater pumps speed, while the feedwater control valves in the other loops are slightly throttling under the action of their control system, to accommodate the slight loop imbalances. This has the advantage of minimizing the valve pressure losses hence minimizing the feedwater pumps power consumption and increasing the net MWe. The benefit has been evaluated for specific plants as being roughly 0.7 and 2.4 MW. The minimum throttling mode has the further advantages of lowering the actuator efforts with potential positive impact in actuator life and of minimizing the feedwater pipelines vibrations. The minimum throttling mode of operation has been developed by the Ukrainian company LvivORGRES. It has been applied with great deal of success on several VVER-1000 NPPs, six units of Zaporizhzha in Ukraine plus, with participation of Westinghouse, Kozloduy 5 and 6 in Bulgaria and South Ukraine 1 to 3 in Ukraine. The concept operates with both ON-OFF valves and true control valves. A study, jointly conducted by Westinghouse and LvivORGRES, is ongoing to demonstrate the applicability of the concept to PWRs having variable speed feedwater pumps and having, or installing, digital feedwater control, standalone or as part of a global digital control system. The implementation of the algorithm at VVER-1000 plants provided both safety improvement and direct commercial benefits. The minimum-throttling algorithm will similarly increase the performance of PWRs. The

  14. 25 CFR 542.14 - What are the minimum internal control standards for the cage?

    Science.gov (United States)

    2010-04-01

    ... 25 Indians 2 2010-04-01 2010-04-01 false What are the minimum internal control standards for the... SERVICES MINIMUM INTERNAL CONTROL STANDARDS § 542.14 What are the minimum internal control standards for... and/or procedures that provide at least the level of control described by the standards in this...

  15. 25 CFR 542.8 - What are the minimum internal control standards for pull tabs?

    Science.gov (United States)

    2010-04-01

    ... 25 Indians 2 2010-04-01 2010-04-01 false What are the minimum internal control standards for pull... SERVICES MINIMUM INTERNAL CONTROL STANDARDS § 542.8 What are the minimum internal control standards for... and/or procedures that provide at least the level of control described by the standards in this...

  16. Minimum variance optimal rate allocation for multiplexed H.264/AVC bitstreams.

    Science.gov (United States)

    Tagliasacchi, Marco; Valenzise, Giuseppe; Tubaro, Stefano

    2008-07-01

    Consider the problem of transmitting multiple video streams to fulfill a constant bandwidth constraint. The available bit budget needs to be distributed across the sequences in order to meet some optimality criteria. For example, one might want to minimize the average distortion or, alternatively, minimize the distortion variance, in order to keep almost constant quality among the encoded sequences. By working in the rho-domain, we propose a low-delay rate allocation scheme that, at each time instant, provides a closed form solution for either the aforementioned problems. We show that minimizing the distortion variance instead of the average distortion leads, for each of the multiplexed sequences, to a coding penalty less than 0.5 dB, in terms of average PSNR. In addition, our analysis provides an explicit relationship between model parameters and this loss. In order to smooth the distortion also along time, we accommodate a shared encoder buffer to compensate for rate fluctuations. Although the proposed scheme is general, and it can be adopted for any video and image coding standard, we provide experimental evidence by transcoding bitstreams encoded using the state-of-the-art H.264/AVC standard. The results of our simulations reveal that is it possible to achieve distortion smoothing both in time and across the sequences, without sacrificing coding efficiency.

  17. Dynamic Allan Variance Analysis Method with Time-Variant Window Length Based on Fuzzy Control

    Directory of Open Access Journals (Sweden)

    Shanshan Gu

    2015-01-01

    Full Text Available To solve the problem that dynamic Allan variance (DAVAR with fixed length of window cannot meet the identification accuracy requirement of fiber optic gyro (FOG signal over all time domains, a dynamic Allan variance analysis method with time-variant window length based on fuzzy control is proposed. According to the characteristic of FOG signal, a fuzzy controller with the inputs of the first and second derivatives of FOG signal is designed to estimate the window length of the DAVAR. Then the Allan variances of the signals during the time-variant window are simulated to obtain the DAVAR of the FOG signal to describe the dynamic characteristic of the time-varying FOG signal. Additionally, a performance evaluation index of the algorithm based on radar chart is proposed. Experiment results show that, compared with different fixed window lengths DAVAR methods, the change of FOG signal with time can be identified effectively and the evaluation index of performance can be enhanced by 30% at least by the DAVAR method with time-variant window length based on fuzzy control.

  18. The scope and control of attention: Sources of variance in working memory capacity.

    Science.gov (United States)

    Chow, Michael; Conway, Andrew R A

    2015-04-01

    Working memory capacity is a strong positive predictor of many cognitive abilities, across various domains. The pattern of positive correlations across domains has been interpreted as evidence for a unitary source of inter-individual differences in behavior. However, recent work suggests that there are multiple sources of variance contributing to working memory capacity. The current study (N = 71) investigates individual differences in the scope and control of attention, in addition to the number and resolution of items maintained in working memory. Latent variable analyses indicate that the scope and control of attention reflect independent sources of variance and each account for unique variance in general intelligence. Also, estimates of the number of items maintained in working memory are consistent across tasks and related to general intelligence whereas estimates of resolution are task-dependent and not predictive of intelligence. These results provide insight into the structure of working memory, as well as intelligence, and raise new questions about the distinction between number and resolution in visual short-term memory.

  19. Analysis of conditional genetic effects and variance components in developmental genetics.

    Science.gov (United States)

    Zhu, J

    1995-12-01

    A genetic model with additive-dominance effects and genotype x environment interactions is presented for quantitative traits with time-dependent measures. The genetic model for phenotypic means at time t conditional on phenotypic means measured at previous time (t-1) is defined. Statistical methods are proposed for analyzing conditional genetic effects and conditional genetic variance components. Conditional variances can be estimated by minimum norm quadratic unbiased estimation (MINQUE) method. An adjusted unbiased prediction (AUP) procedure is suggested for predicting conditional genetic effects. A worked example from cotton fruiting data is given for comparison of unconditional and conditional genetic variances and additive effects.

  20. 25 CFR 542.11 - What are the minimum internal control standards for pari-mutuel wagering?

    Science.gov (United States)

    2010-04-01

    ... 25 Indians 2 2010-04-01 2010-04-01 false What are the minimum internal control standards for pari... INTERIOR HUMAN SERVICES MINIMUM INTERNAL CONTROL STANDARDS § 542.11 What are the minimum internal control... documentation and/or procedures that provide at least the level of control described by the standards in this...

  1. Computing the Expected Value and Variance of Geometric Measures

    DEFF Research Database (Denmark)

    Staals, Frank; Tsirogiannis, Constantinos

    2017-01-01

    distance (MPD), the squared Euclidean distance from the centroid, and the diameter of the minimum enclosing disk. We also describe an efficient (1-e)-approximation algorithm for computing the mean and variance of the mean pairwise distance. We implemented three of our algorithms and we show that our...

  2. Minimum scale controlled topology optimization and experimental test of a micro thermal actuator

    DEFF Research Database (Denmark)

    Heo, S.; Yoon, Gil Ho; Kim, Y.Y.

    2008-01-01

    This paper is concerned with the optimal topology design, fabrication and test of a micro thermal actuator. Because the minimum scale was controlled during the design optimization process, the production yield rate of the actuator was improved considerably; alternatively, the optimization design ...... tested. The test showed that control over the minimum length scale in the design process greatly improves the yield rate and reduces the performance deviation....... without scale control resulted in a very low yield rate. Using the minimum scale controlling topology design method developed earlier by the authors, micro thermal actuators were designed and fabricated through a MEMS process. Moreover, both their performance and production yield were experimentally...

  3. The influence of SO4 and NO3 to the acidity (pH) of rainwater using minimum variance quadratic unbiased estimation (MIVQUE) and maximum likelihood methods

    Science.gov (United States)

    Dilla, Shintia Ulfa; Andriyana, Yudhie; Sudartianto

    2017-03-01

    Acid rain causes many bad effects in life. It is formed by two strong acids, sulfuric acid (H2SO4) and nitric acid (HNO3), where sulfuric acid is derived from SO2 and nitric acid from NOx {x=1,2}. The purpose of the research is to find out the influence of So4 and NO3 levels contained in the rain to the acidity (pH) of rainwater. The data are incomplete panel data with two-way error component model. The panel data is a collection of some of the observations that observed from time to time. It is said incomplete if each individual has a different amount of observation. The model used in this research is in the form of random effects model (REM). Minimum variance quadratic unbiased estimation (MIVQUE) is used to estimate the variance error components, while maximum likelihood estimation is used to estimate the parameters. As a result, we obtain the following model: Ŷ* = 0.41276446 - 0.00107302X1 + 0.00215470X2.

  4. A Decomposition Algorithm for Mean-Variance Economic Model Predictive Control of Stochastic Linear Systems

    DEFF Research Database (Denmark)

    Sokoler, Leo Emil; Dammann, Bernd; Madsen, Henrik

    2014-01-01

    This paper presents a decomposition algorithm for solving the optimal control problem (OCP) that arises in Mean-Variance Economic Model Predictive Control of stochastic linear systems. The algorithm applies the alternating direction method of multipliers to a reformulation of the OCP...

  5. Hedging with stock index futures: downside risk versus the variance

    NARCIS (Netherlands)

    Brouwer, F.; Nat, van der M.

    1995-01-01

    In this paper we investigate hedging a stock portfolio with stock index futures.Instead of defining the hedge ratio as the minimum variance hedge ratio, we considerseveral measures of downside risk: the semivariance according to Markowitz [ 19591 andthe various lower partial moments according to

  6. A Robust Statistics Approach to Minimum Variance Portfolio Optimization

    Science.gov (United States)

    Yang, Liusha; Couillet, Romain; McKay, Matthew R.

    2015-12-01

    We study the design of portfolios under a minimum risk criterion. The performance of the optimized portfolio relies on the accuracy of the estimated covariance matrix of the portfolio asset returns. For large portfolios, the number of available market returns is often of similar order to the number of assets, so that the sample covariance matrix performs poorly as a covariance estimator. Additionally, financial market data often contain outliers which, if not correctly handled, may further corrupt the covariance estimation. We address these shortcomings by studying the performance of a hybrid covariance matrix estimator based on Tyler's robust M-estimator and on Ledoit-Wolf's shrinkage estimator while assuming samples with heavy-tailed distribution. Employing recent results from random matrix theory, we develop a consistent estimator of (a scaled version of) the realized portfolio risk, which is minimized by optimizing online the shrinkage intensity. Our portfolio optimization method is shown via simulations to outperform existing methods both for synthetic and real market data.

  7. Predicting Minimum Control Speed on the Ground (VMCG) and Minimum Control Airspeed (VMCA) of Engine Inoperative Flight Using Aerodynamic Database and Propulsion Database Generators

    Science.gov (United States)

    Hadder, Eric Michael

    There are many computer aided engineering tools and software used by aerospace engineers to design and predict specific parameters of an airplane. These tools help a design engineer predict and calculate such parameters such as lift, drag, pitching moment, takeoff range, maximum takeoff weight, maximum flight range and much more. However, there are very limited ways to predict and calculate the minimum control speeds of an airplane in engine inoperative flight. There are simple solutions, as well as complicated solutions, yet there is neither standard technique nor consistency throughout the aerospace industry. To further complicate this subject, airplane designers have the option of using an Automatic Thrust Control System (ATCS), which directly alters the minimum control speeds of an airplane. This work addresses this issue with a tool used to predict and calculate the Minimum Control Speed on the Ground (VMCG) as well as the Minimum Control Airspeed (VMCA) of any existing or design-stage airplane. With simple line art of an airplane, a program called VORLAX is used to generate an aerodynamic database used to calculate the stability derivatives of an airplane. Using another program called Numerical Propulsion System Simulation (NPSS), a propulsion database is generated to use with the aerodynamic database to calculate both VMCG and VMCA. This tool was tested using two airplanes, the Airbus A320 and the Lockheed Martin C130J-30 Super Hercules. The A320 does not use an Automatic Thrust Control System (ATCS), whereas the C130J-30 does use an ATCS. The tool was able to properly calculate and match known values of VMCG and VMCA for both of the airplanes. The fact that this tool was able to calculate the known values of VMCG and VMCA for both airplanes means that this tool would be able to predict the VMCG and VMCA of an airplane in the preliminary stages of design. This would allow design engineers the ability to use an Automatic Thrust Control System (ATCS) as part

  8. 25 CFR 542.17 - What are the minimum internal control standards for complimentary services or items?

    Science.gov (United States)

    2010-04-01

    ... 25 Indians 2 2010-04-01 2010-04-01 false What are the minimum internal control standards for... THE INTERIOR HUMAN SERVICES MINIMUM INTERNAL CONTROL STANDARDS § 542.17 What are the minimum internal control standards for complimentary services or items? (a) Each Tribal gaming regulatory authority or...

  9. Design of intelligent comfort control system with human learning and minimum power control strategies

    International Nuclear Information System (INIS)

    Liang, J.; Du, R.

    2008-01-01

    This paper presents the design of an intelligent comfort control system by combining the human learning and minimum power control strategies for the heating, ventilating and air conditioning (HVAC) system. In the system, the predicted mean vote (PMV) is adopted as the control objective to improve indoor comfort level by considering six comfort related variables, whilst a direct neural network controller is designed to overcome the nonlinear feature of the PMV calculation for better performance. To achieve the highest comfort level for the specific user, a human learning strategy is designed to tune the user's comfort zone, and then, a VAV and minimum power control strategy is proposed to minimize the energy consumption further. In order to validate the system design, a series of computer simulations are performed based on a derived HVAC and thermal space model. The simulation results confirm the design of the intelligent comfort control system. In comparison to the conventional temperature controller, this system can provide a higher comfort level and better system performance, so it has great potential for HVAC applications in the future

  10. DFT-based channel estimation and noise variance estimation techniques for single-carrier FDMA

    OpenAIRE

    Huang, G; Nix, AR; Armour, SMD

    2010-01-01

    Practical frequency domain equalization (FDE) systems generally require knowledge of the channel and the noise variance to equalize the received signal in a frequency-selective fading channel. Accurate channel estimate and noise variance estimate are thus desirable to improve receiver performance. In this paper we investigate the performance of the denoise channel estimator and the approximate linear minimum mean square error (A-LMMSE) channel estimator with channel power delay profile (PDP) ...

  11. Feedback brake distribution control for minimum pitch

    Science.gov (United States)

    Tavernini, Davide; Velenis, Efstathios; Longo, Stefano

    2017-06-01

    The distribution of brake forces between front and rear axles of a vehicle is typically specified such that the same level of brake force coefficient is imposed at both front and rear wheels. This condition is known as 'ideal' distribution and it is required to deliver the maximum vehicle deceleration and minimum braking distance. For subcritical braking conditions, the deceleration demand may be delivered by different distributions between front and rear braking forces. In this research we show how to obtain the optimal distribution which minimises the pitch angle of a vehicle and hence enhances driver subjective feel during braking. A vehicle model including suspension geometry features is adopted. The problem of the minimum pitch brake distribution for a varying deceleration level demand is solved by means of a model predictive control (MPC) technique. To address the problem of the undesirable pitch rebound caused by a full-stop of the vehicle, a second controller is designed and implemented independently from the braking distribution in use. An extended Kalman filter is designed for state estimation and implemented in a high fidelity environment together with the MPC strategy. The proposed solution is compared with the reference 'ideal' distribution as well as another previous feed-forward solution.

  12. Risk-sensitivity and the mean-variance trade-off: decision making in sensorimotor control.

    Science.gov (United States)

    Nagengast, Arne J; Braun, Daniel A; Wolpert, Daniel M

    2011-08-07

    Numerous psychophysical studies suggest that the sensorimotor system chooses actions that optimize the average cost associated with a movement. Recently, however, violations of this hypothesis have been reported in line with economic theories of decision-making that not only consider the mean payoff, but are also sensitive to risk, that is the variability of the payoff. Here, we examine the hypothesis that risk-sensitivity in sensorimotor control arises as a mean-variance trade-off in movement costs. We designed a motor task in which participants could choose between a sure motor action that resulted in a fixed amount of effort and a risky motor action that resulted in a variable amount of effort that could be either lower or higher than the fixed effort. By changing the mean effort of the risky action while experimentally fixing its variance, we determined indifference points at which participants chose equiprobably between the sure, fixed amount of effort option and the risky, variable effort option. Depending on whether participants accepted a variable effort with a mean that was higher, lower or equal to the fixed effort, they could be classified as risk-seeking, risk-averse or risk-neutral. Most subjects were risk-sensitive in our task consistent with a mean-variance trade-off in effort, thereby, underlining the importance of risk-sensitivity in computational models of sensorimotor control.

  13. Robustification and Optimization in Repetitive Control For Minimum Phase and Non-Minimum Phase Systems

    Science.gov (United States)

    Prasitmeeboon, Pitcha

    repetitive control FIR compensator. The aim is to reduce the final error level by using real time frequency response model updates to successively increase the cutoff frequency, each time creating the improved model needed to produce convergence zero error up to the higher cutoff. Non-minimum phase systems present a difficult design challenge to the sister field of Iterative Learning Control. The third topic investigates to what extent the same challenges appear in RC. One challenge is that the intrinsic non-minimum phase zero mapped from continuous time is close to the pole of repetitive controller at +1 creating behavior similar to pole-zero cancellation. The near pole-zero cancellation causes slow learning at DC and low frequencies. The Min-Max cost function over the learning rate is presented. The Min-Max can be reformulated as a Quadratically Constrained Linear Programming problem. This approach is shown to be an RC design approach that addresses the main challenge of non-minimum phase systems to have a reasonable learning rate at DC. Although it was illustrated that using the Min-Max objective improves learning at DC and low frequencies compared to other designs, the method requires model accuracy at high frequencies. In the real world, models usually have error at high frequencies. The fourth topic addresses how one can merge the quadratic penalty to the Min-Max cost function to increase robustness at high frequencies. The topic also considers limiting the Min-Max optimization to some frequencies interval and applying an FIR zero-phase low-pass filter to cutoff the learning for frequencies above that interval.

  14. Stochastic Modelling and Self Tuning Control of a Continuous Cement Raw Material Mixing System

    Directory of Open Access Journals (Sweden)

    Hannu T. Toivonen

    1980-01-01

    Full Text Available The control of a continuously operating system for cement raw material mixing is studied. The purpose of the mixing system is to maintain a constant composition of the cement raw meal for the kiln despite variations of the raw material compositions. Experimental knowledge of the process dynamics and the characteristics of the various disturbances is used for deriving a stochastic model of the system. The optimal control strategy is then obtained as a minimum variance strategy. The control problem is finally solved using a self-tuning minimum variance regulator, and results from a successful implementation of the regulator are given.

  15. Hypnosis control based on the minimum concentration of anesthetic drug for maintaining appropriate hypnosis.

    Science.gov (United States)

    Furutani, Eiko; Nishigaki, Yuki; Kanda, Chiaki; Takeda, Toshihiro; Shirakami, Gotaro

    2013-01-01

    This paper proposes a novel hypnosis control method using Auditory Evoked Potential Index (aepEX) as a hypnosis index. In order to avoid side effects of an anesthetic drug, it is desirable to reduce the amount of an anesthetic drug during surgery. For this purpose many studies of hypnosis control systems have been done. Most of them use Bispectral Index (BIS), another hypnosis index, but it has problems of dependence on anesthetic drugs and nonsmooth change near some particular values. On the other hand, aepEX has an ability of clear distinction between patient consciousness and unconsciousness and independence of anesthetic drugs. The control method proposed in this paper consists of two elements: estimating the minimum effect-site concentration for maintaining appropriate hypnosis and adjusting infusion rate of an anesthetic drug, propofol, using model predictive control. The minimum effect-site concentration is estimated utilizing the property of aepEX pharmacodynamics. The infusion rate of propofol is adjusted so that effect-site concentration of propofol may be kept near and always above the minimum effect-site concentration. Simulation results of hypnosis control using the proposed method show that the minimum concentration can be estimated appropriately and that the proposed control method can maintain hypnosis adequately and reduce the total infusion amount of propofol.

  16. A method for minimum risk portfolio optimization under hybrid uncertainty

    Science.gov (United States)

    Egorova, Yu E.; Yazenin, A. V.

    2018-03-01

    In this paper, we investigate a minimum risk portfolio model under hybrid uncertainty when the profitability of financial assets is described by fuzzy random variables. According to Feng, the variance of a portfolio is defined as a crisp value. To aggregate fuzzy information the weakest (drastic) t-norm is used. We construct an equivalent stochastic problem of the minimum risk portfolio model and specify the stochastic penalty method for solving it.

  17. Genetic control of residual variance of yearling weight in Nellore beef cattle.

    Science.gov (United States)

    Iung, L H S; Neves, H H R; Mulder, H A; Carvalheiro, R

    2017-04-01

    There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between them. The aim of our study was to investigate the genetic heterogeneity of residual variance on yearling weight (YW; 291.15 ± 46.67) in a Nellore beef cattle population; to compare the results of the statistical approaches, the two-step approach and the double hierarchical generalized linear model (DHGLM); and to evaluate the effectiveness of power transformation to accommodate scale differences. The comparison was based on genetic parameters, accuracy of EBV for residual variance, and cross-validation to assess predictive performance of both approaches. A total of 194,628 yearling weight records from 625 sires were used in the analysis. The results supported the hypothesis of genetic heterogeneity of residual variance on YW in Nellore beef cattle and the opportunity of selection, measured through the genetic coefficient of variation of residual variance (0.10 to 0.12 for the two-step approach and 0.17 for DHGLM, using an untransformed data set). However, low estimates of genetic variance associated with positive genetic correlations between mean and residual variance (about 0.20 for two-step and 0.76 for DHGLM for an untransformed data set) limit the genetic response to selection for uniformity of production while simultaneously increasing YW itself. Moreover, large sire families are needed to obtain accurate estimates of genetic merit for residual variance, as indicated by the low heritability estimates (Box-Cox transformation was able to decrease the dependence of the variance on the mean and decreased the estimates of genetic parameters for residual variance. The transformation reduced but did not eliminate all the genetic heterogeneity of residual variance, highlighting

  18. Variance analysis refines overhead cost control.

    Science.gov (United States)

    Cooper, J C; Suver, J D

    1992-02-01

    Many healthcare organizations may not fully realize the benefits of standard cost accounting techniques because they fail to routinely report volume variances in their internal reports. If overhead allocation is routinely reported on internal reports, managers can determine whether billing remains current or lost charges occur. Healthcare organizations' use of standard costing techniques can lead to more realistic performance measurements and information system improvements that alert management to losses from unrecovered overhead in time for corrective action.

  19. Stable Control of Firing Rate Mean and Variance by Dual Homeostatic Mechanisms.

    Science.gov (United States)

    Cannon, Jonathan; Miller, Paul

    2017-12-01

    Homeostatic processes that provide negative feedback to regulate neuronal firing rates are essential for normal brain function. Indeed, multiple parameters of individual neurons, including the scale of afferent synapse strengths and the densities of specific ion channels, have been observed to change on homeostatic time scales to oppose the effects of chronic changes in synaptic input. This raises the question of whether these processes are controlled by a single slow feedback variable or multiple slow variables. A single homeostatic process providing negative feedback to a neuron's firing rate naturally maintains a stable homeostatic equilibrium with a characteristic mean firing rate; but the conditions under which multiple slow feedbacks produce a stable homeostatic equilibrium have not yet been explored. Here we study a highly general model of homeostatic firing rate control in which two slow variables provide negative feedback to drive a firing rate toward two different target rates. Using dynamical systems techniques, we show that such a control system can be used to stably maintain a neuron's characteristic firing rate mean and variance in the face of perturbations, and we derive conditions under which this happens. We also derive expressions that clarify the relationship between the homeostatic firing rate targets and the resulting stable firing rate mean and variance. We provide specific examples of neuronal systems that can be effectively regulated by dual homeostasis. One of these examples is a recurrent excitatory network, which a dual feedback system can robustly tune to serve as an integrator.

  20. 25 CFR 542.4 - How do these regulations affect minimum internal control standards established in a Tribal-State...

    Science.gov (United States)

    2010-04-01

    ... 25 Indians 2 2010-04-01 2010-04-01 false How do these regulations affect minimum internal control... COMMISSION, DEPARTMENT OF THE INTERIOR HUMAN SERVICES MINIMUM INTERNAL CONTROL STANDARDS § 542.4 How do these regulations affect minimum internal control standards established in a Tribal-State compact? (a) If there is a...

  1. Validation of consistency of Mendelian sampling variance.

    Science.gov (United States)

    Tyrisevä, A-M; Fikse, W F; Mäntysaari, E A; Jakobsen, J; Aamand, G P; Dürr, J; Lidauer, M H

    2018-03-01

    Experiences from international sire evaluation indicate that the multiple-trait across-country evaluation method is sensitive to changes in genetic variance over time. Top bulls from birth year classes with inflated genetic variance will benefit, hampering reliable ranking of bulls. However, none of the methods available today enable countries to validate their national evaluation models for heterogeneity of genetic variance. We describe a new validation method to fill this gap comprising the following steps: estimating within-year genetic variances using Mendelian sampling and its prediction error variance, fitting a weighted linear regression between the estimates and the years under study, identifying possible outliers, and defining a 95% empirical confidence interval for a possible trend in the estimates. We tested the specificity and sensitivity of the proposed validation method with simulated data using a real data structure. Moderate (M) and small (S) size populations were simulated under 3 scenarios: a control with homogeneous variance and 2 scenarios with yearly increases in phenotypic variance of 2 and 10%, respectively. Results showed that the new method was able to estimate genetic variance accurately enough to detect bias in genetic variance. Under the control scenario, the trend in genetic variance was practically zero in setting M. Testing cows with an average birth year class size of more than 43,000 in setting M showed that tolerance values are needed for both the trend and the outlier tests to detect only cases with a practical effect in larger data sets. Regardless of the magnitude (yearly increases in phenotypic variance of 2 or 10%) of the generated trend, it deviated statistically significantly from zero in all data replicates for both cows and bulls in setting M. In setting S with a mean of 27 bulls in a year class, the sampling error and thus the probability of a false-positive result clearly increased. Still, overall estimated genetic

  2. The Preventive Control of a Dengue Disease Using Pontryagin Minimum Principal

    Science.gov (United States)

    Ratna Sari, Eminugroho; Insani, Nur; Lestari, Dwi

    2017-06-01

    Behaviour analysis for host-vector model without control of dengue disease is based on the value of basic reproduction number obtained using next generation matrices. Furthermore, the model is further developed involving a preventive control to minimize the contact between host and vector. The purpose is to obtain an optimal preventive strategy with minimal cost. The Pontryagin Minimum Principal is used to find the optimal control analytically. The derived optimality model is then solved numerically to investigate control effort to reduce infected class.

  3. Use of genomic models to study genetic control of environmental variance

    DEFF Research Database (Denmark)

    Yang, Ye; Christensen, Ole Fredslund; Sorensen, Daniel

    2011-01-01

    . The genomic model commonly found in the literature, with marker effects affecting mean only, is extended to investigate putative effects at the level of the environmental variance. Two classes of models are proposed and their behaviour, studied using simulated data, indicates that they are capable...... of detecting genetic variation at the level of mean and variance. Implementation is via Markov chain Monte Carlo (McMC) algorithms. The models are compared in terms of a measure of global fit, in their ability to detect QTL effects and in terms of their predictive power. The models are subsequently fitted...... to back fat thickness data in pigs. The analysis of back fat thickness shows that the data support genomic models with effects on the mean but not on the variance. The relative sizes of experiment necessary to detect effects on mean and variance is discussed and an extension of the McMC algorithm...

  4. A minimum attention control center for nuclear power plants

    International Nuclear Information System (INIS)

    Meijer, C.H.

    1986-01-01

    Control Centers for Nuclear Power Plants have characteristically been designed for maximum attention by the operating staffs of these plants. Consequently, the monitoring, control and diagnostics oriented cognitive activities by these staffs, were mostly ''data-driven'' in nature. This paper addresses a control center concept, under development by Combustion Engineering, that promotes a more ''information-driven'' cognitive interaction process between the operator and the plant. The more ''intelligent'' and therefore less attentive nature of such interactive process utilizes computer implemented cognitive engineered algorithms. The underlying structure of these algorithms is based upon the Critical Function/Success Path monitoring principle. The paper highlights a typical implementation of the minimum attention concept for the handling of unfamiliar safety related events. (author)

  5. Parameters Tuning of Model Free Adaptive Control Based on Minimum Entropy

    Institute of Scientific and Technical Information of China (English)

    Chao Ji; Jing Wang; Liulin Cao; Qibing Jin

    2014-01-01

    Dynamic linearization based model free adaptive control(MFAC) algorithm has been widely used in practical systems, in which some parameters should be tuned before it is successfully applied to process industries. Considering the random noise existing in real processes, a parameter tuning method based on minimum entropy optimization is proposed,and the feature of entropy is used to accurately describe the system uncertainty. For cases of Gaussian stochastic noise and non-Gaussian stochastic noise, an entropy recursive optimization algorithm is derived based on approximate model or identified model. The extensive simulation results show the effectiveness of the minimum entropy optimization for the partial form dynamic linearization based MFAC. The parameters tuned by the minimum entropy optimization index shows stronger stability and more robustness than these tuned by other traditional index,such as integral of the squared error(ISE) or integral of timeweighted absolute error(ITAE), when the system stochastic noise exists.

  6. STUDY LINKS SOLVING THE MAXIMUM TASK OF LINEAR CONVOLUTION «EXPECTED RETURNS-VARIANCE» AND THE MINIMUM VARIANCE WITH RESTRICTIONS ON RETURNS

    Directory of Open Access Journals (Sweden)

    Maria S. Prokhorova

    2014-01-01

    Full Text Available The article deals with a study of problemsof finding the optimal portfolio securitiesusing convolutions expectation of portfolioreturns and portfolio variance. Value of thecoefficient of risk, in which the problem ofmaximizing the variance - limited yieldis equivalent to maximizing a linear convolution of criteria for «expected returns-variance» is obtained. An automated method for finding the optimal portfolio, onthe basis of which the results of the studydemonstrated is proposed.

  7. Gravity interpretation of dipping faults using the variance analysis method

    International Nuclear Information System (INIS)

    Essa, Khalid S

    2013-01-01

    A new algorithm is developed to estimate simultaneously the depth and the dip angle of a buried fault from the normalized gravity gradient data. This algorithm utilizes numerical first horizontal derivatives computed from the observed gravity anomaly, using filters of successive window lengths to estimate the depth and the dip angle of a buried dipping fault structure. For a fixed window length, the depth is estimated using a least-squares sense for each dip angle. The method is based on computing the variance of the depths determined from all horizontal gradient anomaly profiles using the least-squares method for each dip angle. The minimum variance is used as a criterion for determining the correct dip angle and depth of the buried structure. When the correct dip angle is used, the variance of the depths is always less than the variances computed using wrong dip angles. The technique can be applied not only to the true residuals, but also to the measured Bouguer gravity data. The method is applied to synthetic data with and without random errors and two field examples from Egypt and Scotland. In all cases examined, the estimated depths and other model parameters are found to be in good agreement with the actual values. (paper)

  8. Thermospheric mass density model error variance as a function of time scale

    Science.gov (United States)

    Emmert, J. T.; Sutton, E. K.

    2017-12-01

    In the increasingly crowded low-Earth orbit environment, accurate estimation of orbit prediction uncertainties is essential for collision avoidance. Poor characterization of such uncertainty can result in unnecessary and costly avoidance maneuvers (false positives) or disregard of a collision risk (false negatives). Atmospheric drag is a major source of orbit prediction uncertainty, and is particularly challenging to account for because it exerts a cumulative influence on orbital trajectories and is therefore not amenable to representation by a single uncertainty parameter. To address this challenge, we examine the variance of measured accelerometer-derived and orbit-derived mass densities with respect to predictions by thermospheric empirical models, using the data-minus-model variance as a proxy for model uncertainty. Our analysis focuses mainly on the power spectrum of the residuals, and we construct an empirical model of the variance as a function of time scale (from 1 hour to 10 years), altitude, and solar activity. We find that the power spectral density approximately follows a power-law process but with an enhancement near the 27-day solar rotation period. The residual variance increases monotonically with altitude between 250 and 550 km. There are two components to the variance dependence on solar activity: one component is 180 degrees out of phase (largest variance at solar minimum), and the other component lags 2 years behind solar maximum (largest variance in the descending phase of the solar cycle).

  9. 76 FR 53817 - Minimum Internal Control Standards for Class II Gaming

    Science.gov (United States)

    2011-08-30

    ... DEPARTMENT OF THE INTERIOR National Indian Gaming Commission 25 CFR Parts 542 and 543 Minimum Internal Control Standards for Class II Gaming AGENCY: National Indian Gaming Commission, Interior. ACTION: Final rule; delay of effective date and request for comments. SUMMARY: The National Indian Gaming...

  10. 77 FR 60625 - Minimum Internal Control Standards for Class II Gaming

    Science.gov (United States)

    2012-10-04

    ... DEPARTMENT OF THE INTERIOR National Indian Gaming Commission 25 CFR Parts 542 and 543 RIN 3141-AA-37 Minimum Internal Control Standards for Class II Gaming AGENCY: National Indian Gaming Commission. ACTION: Final rule; delay of effective date; suspension. SUMMARY: The National Indian Gaming Commission...

  11. Ant colony method to control variance reduction techniques in the Monte Carlo simulation of clinical electron linear accelerators

    International Nuclear Information System (INIS)

    Garcia-Pareja, S.; Vilches, M.; Lallena, A.M.

    2007-01-01

    The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the 'hot' regions of the accelerator, an information which is basic to develop a source model for this therapy tool

  12. 75 FR 55269 - Minimum Internal Control Standards for Class II Gaming

    Science.gov (United States)

    2010-09-10

    ... DEPARTMENT OF THE INTERIOR National Indian Gaming Commission 25 CFR Parts 542 and 543 RIN 3141-AA-37 Minimum Internal Control Standards for Class II Gaming AGENCY: National Indian Gaming Commission. ACTION: Delay of effective date of final rule; request for comments. SUMMARY: The National Indian Gaming...

  13. Minimum Thrust Load Control for Floating Wind Turbine

    DEFF Research Database (Denmark)

    Christiansen, Søren; Bak, Thomas; Knudsen, Torben

    2012-01-01

    — Offshore wind energy capitalizes on the higher and less turbulent wind at sea. Shallow water sites are profitable for deployment of monopile wind turbines at water depths of up to 30 meters. Beyond 30 meters, the wind is even stronger and less turbulent. At these depths, floating wind turbines be...... and power stability when using the new control strategy.......— Offshore wind energy capitalizes on the higher and less turbulent wind at sea. Shallow water sites are profitable for deployment of monopile wind turbines at water depths of up to 30 meters. Beyond 30 meters, the wind is even stronger and less turbulent. At these depths, floating wind turbines...... presents a new minimum thrust control strategy capable of stabilizing a floating wind turbine. The new control strategy explores the freedom of variable generator speed above rated wind speed. A comparison to the traditional constant speed strategy, shows improvements in structural fore-aft oscillations...

  14. Ant colony method to control variance reduction techniques in the Monte Carlo simulation of clinical electron linear accelerators

    Energy Technology Data Exchange (ETDEWEB)

    Garcia-Pareja, S. [Servicio de Radiofisica Hospitalaria, Hospital Regional Universitario ' Carlos Haya' , Avda. Carlos Haya, s/n, E-29010 Malaga (Spain)], E-mail: garciapareja@gmail.com; Vilches, M. [Servicio de Fisica y Proteccion Radiologica, Hospital Regional Universitario ' Virgen de las Nieves' , Avda. de las Fuerzas Armadas, 2, E-18014 Granada (Spain); Lallena, A.M. [Departamento de Fisica Atomica, Molecular y Nuclear, Universidad de Granada, E-18071 Granada (Spain)

    2007-09-21

    The ant colony method is used to control the application of variance reduction techniques to the simulation of clinical electron linear accelerators of use in cancer therapy. In particular, splitting and Russian roulette, two standard variance reduction methods, are considered. The approach can be applied to any accelerator in a straightforward way and permits, in addition, to investigate the 'hot' regions of the accelerator, an information which is basic to develop a source model for this therapy tool.

  15. 25 CFR 543.16 - What are the minimum internal controls for information technology?

    Science.gov (United States)

    2010-04-01

    ... controls for information technology? (a) Physical security measures restricting access to agents, including... longer required. (2) In the event of remote access, the information technology employees must prepare a... 25 Indians 2 2010-04-01 2010-04-01 false What are the minimum internal controls for information...

  16. Chaos control in an economic model via minimum entropy strategy

    Energy Technology Data Exchange (ETDEWEB)

    Salarieh, Hassan [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Tehran (Iran, Islamic Republic of)], E-mail: salarieh@mech.sharif.edu; Alasty, Aria [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Tehran (Iran, Islamic Republic of); National Research Institute for Science Policy (NRISP), Soheil Street, Shirazi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: aalasti@sharif.edu

    2009-04-30

    In this paper, minimum entropy algorithm for controlling chaos, is applied to a Cournot duopoly with different constant marginal costs, as a discrete-time dynamical system which shows chaotic behavior. The ME control is implemented through delayed feedback. It is assumed that the equations of the dynamical system are not known, so the feedback gain cannot be obtained analytically from the system equations. In the ME method the feedback gain is obtained adaptively in such a way that the entropy of the system converges to zero, hence a fixed point of the system will be stabilized. Application of the proposed method with different economic control strategies is numerically investigated. Simulation results show the effectiveness of the ME method for controlling chaos in economic systems with unknown equations.

  17. Continuous-Time Mean-Variance Portfolio Selection: A Stochastic LQ Framework

    International Nuclear Information System (INIS)

    Zhou, X.Y.; Li, D.

    2000-01-01

    This paper is concerned with a continuous-time mean-variance portfolio selection model that is formulated as a bicriteria optimization problem. The objective is to maximize the expected terminal return and minimize the variance of the terminal wealth. By putting weights on the two criteria one obtains a single objective stochastic control problem which is however not in the standard form due to the variance term involved. It is shown that this nonstandard problem can be 'embedded' into a class of auxiliary stochastic linear-quadratic (LQ) problems. The stochastic LQ control model proves to be an appropriate and effective framework to study the mean-variance problem in light of the recent development on general stochastic LQ problems with indefinite control weighting matrices. This gives rise to the efficient frontier in a closed form for the original portfolio selection problem

  18. Continuous-Time Mean-Variance Portfolio Selection under the CEV Process

    OpenAIRE

    Ma, Hui-qiang

    2014-01-01

    We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV) process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance effici...

  19. Variance heterogeneity in Saccharomyces cerevisiae expression data: trans-regulation and epistasis.

    Science.gov (United States)

    Nelson, Ronald M; Pettersson, Mats E; Li, Xidan; Carlborg, Örjan

    2013-01-01

    Here, we describe the results from the first variance heterogeneity Genome Wide Association Study (VGWAS) on yeast expression data. Using this forward genetics approach, we show that the genetic regulation of gene-expression in the budding yeast, Saccharomyces cerevisiae, includes mechanisms that can lead to variance heterogeneity in the expression between genotypes. Additionally, we performed a mean effect association study (GWAS). Comparing the mean and variance heterogeneity analyses, we find that the mean expression level is under genetic regulation from a larger absolute number of loci but that a higher proportion of the variance controlling loci were trans-regulated. Both mean and variance regulating loci cluster in regulatory hotspots that affect a large number of phenotypes; a single variance-controlling locus, mapping close to DIA2, was found to be involved in more than 10% of the significant associations. It has been suggested in the literature that variance-heterogeneity between the genotypes might be due to genetic interactions. We therefore screened the multi-locus genotype-phenotype maps for several traits where multiple associations were found, for indications of epistasis. Several examples of two and three locus genetic interactions were found to involve variance-controlling loci, with reports from the literature corroborating the functional connections between the loci. By using a new analytical approach to re-analyze a powerful existing dataset, we are thus able to both provide novel insights to the genetic mechanisms involved in the regulation of gene-expression in budding yeast and experimentally validate epistasis as an important mechanism underlying genetic variance-heterogeneity between genotypes.

  20. The solar and interplanetary causes of the recent minimum in geomagnetic activity (MGA23: a combination of midlatitude small coronal holes, low IMF BZ variances, low solar wind speeds and low solar magnetic fields

    Directory of Open Access Journals (Sweden)

    B. T. Tsurutani

    2011-05-01

    Full Text Available Minima in geomagnetic activity (MGA at Earth at the ends of SC23 and SC22 have been identified. The two MGAs (called MGA23 and MGA22, respectively were present in 2009 and 1997, delayed from the sunspot number minima in 2008 and 1996 by ~1/2–1 years. Part of the solar and interplanetary causes of the MGAs were exceptionally low solar (and thus low interplanetary magnetic fields. Another important factor in MGA23 was the disappearance of equatorial and low latitude coronal holes and the appearance of midlatitude coronal holes. The location of the holes relative to the ecliptic plane led to low solar wind speeds and low IMF (Bz variances (σBz2 and normalized variances (σBz2/B02 at Earth, with concomitant reduced solar wind-magnetospheric energy coupling. One result was the lowest ap indices in the history of ap recording. The results presented here are used to comment on the possible solar and interplanetary causes of the low geomagnetic activity that occurred during the Maunder Minimum.

  1. Solving portfolio selection problems with minimum transaction lots based on conditional-value-at-risk

    Science.gov (United States)

    Setiawan, E. P.; Rosadi, D.

    2017-01-01

    Portfolio selection problems conventionally means ‘minimizing the risk, given the certain level of returns’ from some financial assets. This problem is frequently solved with quadratic or linear programming methods, depending on the risk measure that used in the objective function. However, the solutions obtained by these method are in real numbers, which may give some problem in real application because each asset usually has its minimum transaction lots. In the classical approach considering minimum transaction lots were developed based on linear Mean Absolute Deviation (MAD), variance (like Markowitz’s model), and semi-variance as risk measure. In this paper we investigated the portfolio selection methods with minimum transaction lots with conditional value at risk (CVaR) as risk measure. The mean-CVaR methodology only involves the part of the tail of the distribution that contributed to high losses. This approach looks better when we work with non-symmetric return probability distribution. Solution of this method can be found with Genetic Algorithm (GA) methods. We provide real examples using stocks from Indonesia stocks market.

  2. Downside Variance Risk Premium

    OpenAIRE

    Feunou, Bruno; Jahan-Parvar, Mohammad; Okou, Cedric

    2015-01-01

    We propose a new decomposition of the variance risk premium in terms of upside and downside variance risk premia. The difference between upside and downside variance risk premia is a measure of skewness risk premium. We establish that the downside variance risk premium is the main component of the variance risk premium, and that the skewness risk premium is a priced factor with significant prediction power for aggregate excess returns. Our empirical investigation highlights the positive and s...

  3. Genotypic-specific variance in Caenorhabditis elegans lifetime fecundity.

    Science.gov (United States)

    Diaz, S Anaid; Viney, Mark

    2014-06-01

    Organisms live in heterogeneous environments, so strategies that maximze fitness in such environments will evolve. Variation in traits is important because it is the raw material on which natural selection acts during evolution. Phenotypic variation is usually thought to be due to genetic variation and/or environmentally induced effects. Therefore, genetically identical individuals in a constant environment should have invariant traits. Clearly, genetically identical individuals do differ phenotypically, usually thought to be due to stochastic processes. It is now becoming clear, especially from studies of unicellular species, that phenotypic variance among genetically identical individuals in a constant environment can be genetically controlled and that therefore, in principle, this can be subject to selection. However, there has been little investigation of these phenomena in multicellular species. Here, we have studied the mean lifetime fecundity (thus a trait likely to be relevant to reproductive success), and variance in lifetime fecundity, in recently-wild isolates of the model nematode Caenorhabditis elegans. We found that these genotypes differed in their variance in lifetime fecundity: some had high variance in fecundity, others very low variance. We find that this variance in lifetime fecundity was negatively related to the mean lifetime fecundity of the lines, and that the variance of the lines was positively correlated between environments. We suggest that the variance in lifetime fecundity may be a bet-hedging strategy used by this species.

  4. Local variances in biomonitoring

    International Nuclear Information System (INIS)

    Wolterbeek, H.Th; Verburg, T.G.

    2001-01-01

    The present study was undertaken to explore possibilities to judge survey quality on basis of a limited and restricted number of a-priori observations. Here, quality is defined as the ratio between survey and local variance (signal-to-noise ratio). The results indicate that the presented surveys do not permit such judgement; the discussion also suggests that the 5-fold local sampling strategies do not merit any sound judgement. As it stands, uncertainties in local determinations may largely obscure possibilities to judge survey quality. The results further imply that surveys will benefit from procedures, controls and approaches in sampling and sample handling, to assess both average, variance and the nature of the distribution of elemental concentrations in local sites. This reasoning is compatible with the idea of the site as a basic homogeneous survey unit, which is implicitly and conceptually underlying any survey performed. (author)

  5. Wavelet-based multiscale analysis of minimum toe clearance variability in the young and elderly during walking.

    Science.gov (United States)

    Khandoker, Ahsan H; Karmakar, Chandan K; Begg, Rezaul K; Palaniswami, Marimuthu

    2007-01-01

    As humans age or are influenced by pathology of the neuromuscular system, gait patterns are known to adjust, accommodating for reduced function in the balance control system. The aim of this study was to investigate the effectiveness of a wavelet based multiscale analysis of a gait variable [minimum toe clearance (MTC)] in deriving indexes for understanding age-related declines in gait performance and screening of balance impairments in the elderly. MTC during walking on a treadmill for 30 healthy young, 27 healthy elderly and 10 falls risk elderly subjects with a history of tripping falls were analyzed. The MTC signal from each subject was decomposed to eight detailed signals at different wavelet scales by using the discrete wavelet transform. The variances of detailed signals at scales 8 to 1 were calculated. The multiscale exponent (beta) was then estimated from the slope of the variance progression at successive scales. The variance at scale 5 was significantly (ppathological conditions. Early detection of gait pattern changes due to ageing and balance impairments using wavelet-based multiscale analysis might provide the opportunity to initiate preemptive measures to be undertaken to avoid injurious falls.

  6. R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization.

    Science.gov (United States)

    Dazard, Jean-Eudes; Xu, Hua; Rao, J Sunil

    2011-01-01

    We present an implementation in the R language for statistical computing of our recent non-parametric joint adaptive mean-variance regularization and variance stabilization procedure. The method is specifically suited for handling difficult problems posed by high-dimensional multivariate datasets ( p ≫ n paradigm), such as in 'omics'-type data, among which are that the variance is often a function of the mean, variable-specific estimators of variances are not reliable, and tests statistics have low powers due to a lack of degrees of freedom. The implementation offers a complete set of features including: (i) normalization and/or variance stabilization function, (ii) computation of mean-variance-regularized t and F statistics, (iii) generation of diverse diagnostic plots, (iv) synthetic and real 'omics' test datasets, (v) computationally efficient implementation, using C interfacing, and an option for parallel computing, (vi) manual and documentation on how to setup a cluster. To make each feature as user-friendly as possible, only one subroutine per functionality is to be handled by the end-user. It is available as an R package, called MVR ('Mean-Variance Regularization'), downloadable from the CRAN.

  7. 77 FR 32444 - Minimum Internal Control Standards

    Science.gov (United States)

    2012-06-01

    ... definitions, add and amend existing definitions; amend the term ``variance'' as it applies to establishing an... and audit and accounting procedures into their respective sections. DATES: Submit comments on or... Commission agrees that it does not intend to limit the definition of charitable organizations to those with a...

  8. Estimation of measurement variances

    International Nuclear Information System (INIS)

    Anon.

    1981-01-01

    In the previous two sessions, it was assumed that the measurement error variances were known quantities when the variances of the safeguards indices were calculated. These known quantities are actually estimates based on historical data and on data generated by the measurement program. Session 34 discusses how measurement error parameters are estimated for different situations. The various error types are considered. The purpose of the session is to enable participants to: (1) estimate systematic error variances from standard data; (2) estimate random error variances from data as replicate measurement data; (3) perform a simple analysis of variances to characterize the measurement error structure when biases vary over time

  9. Simulation study on heterogeneous variance adjustment for observations with different measurement error variance

    DEFF Research Database (Denmark)

    Pitkänen, Timo; Mäntysaari, Esa A; Nielsen, Ulrik Sander

    2013-01-01

    of variance correction is developed for the same observations. As automated milking systems are becoming more popular the current evaluation model needs to be enhanced to account for the different measurement error variances of observations from automated milking systems. In this simulation study different...... models and different approaches to account for heterogeneous variance when observations have different measurement error variances were investigated. Based on the results we propose to upgrade the currently applied models and to calibrate the heterogeneous variance adjustment method to yield same genetic......The Nordic Holstein yield evaluation model describes all available milk, protein and fat test-day yields from Denmark, Finland and Sweden. In its current form all variance components are estimated from observations recorded under conventional milking systems. Also the model for heterogeneity...

  10. Minimum variance rooting of phylogenetic trees and implications for species tree reconstruction.

    Science.gov (United States)

    Mai, Uyen; Sayyari, Erfan; Mirarab, Siavash

    2017-01-01

    Phylogenetic trees inferred using commonly-used models of sequence evolution are unrooted, but the root position matters both for interpretation and downstream applications. This issue has been long recognized; however, whether the potential for discordance between the species tree and gene trees impacts methods of rooting a phylogenetic tree has not been extensively studied. In this paper, we introduce a new method of rooting a tree based on its branch length distribution; our method, which minimizes the variance of root to tip distances, is inspired by the traditional midpoint rerooting and is justified when deviations from the strict molecular clock are random. Like midpoint rerooting, the method can be implemented in a linear time algorithm. In extensive simulations that consider discordance between gene trees and the species tree, we show that the new method is more accurate than midpoint rerooting, but its relative accuracy compared to using outgroups to root gene trees depends on the size of the dataset and levels of deviations from the strict clock. We show high levels of error for all methods of rooting estimated gene trees due to factors that include effects of gene tree discordance, deviations from the clock, and gene tree estimation error. Our simulations, however, did not reveal significant differences between two equivalent methods for species tree estimation that use rooted and unrooted input, namely, STAR and NJst. Nevertheless, our results point to limitations of existing scalable rooting methods.

  11. Minimum time control of a pair of two-level quantum systems with opposite drifts

    International Nuclear Information System (INIS)

    Romano, Raffaele; D’Alessandro, Domenico

    2016-01-01

    In this paper we solve two equivalent time optimal control problems. On one hand, we design the control field to implement in minimum time the SWAP (or equivalent) operator on a two-level system, assuming that it interacts with an additional, uncontrollable, two-level system. On the other hand, we synthesize the SWAP operator simultaneously, in minimum time, on a pair of two-level systems subject to opposite drifts. We assume that it is possible to perform three independent control actions, and that the total control strength is bounded. These controls either affect the dynamics of the target system, under the first perspective, or, simultaneously, the dynamics of both systems, in the second view. We obtain our results by using techniques of geometric control theory on Lie groups. In particular, we apply the Pontryagin maximum principle, and provide a complete characterization of singular and nonsingular extremals. Our analysis shows that the problem can be formulated as the motion of a material point in a central force, a well known system in classical mechanics. Although we focus on obtaining the SWAP operator, many of the ideas and techniques developed in this work apply to the time optimal implementation of an arbitrary unitary operator. (paper)

  12. Nano positioning control for dual stage using minimum order observer

    International Nuclear Information System (INIS)

    Kim, Hong Gun

    2012-01-01

    A nano positioning control is developed using the ultra-precision positioning apparatus such as actuator, sensor, guide, power transmission element with an appropriate control method. Using established procedures, a single plane X-Y stage with ultra-precision positioning is manufactured. A global stage for materialization with robust system is combined by using an AC servo motor with a ball screw and rolling guide. An ultra-precision positioning system is developed using a micro stage with an elastic hinge and piezo element. Global and micro servos for positioning with nanometer accuracy are controlled simultaneously using an incremental encoder and a laser interferometer to measure displacement. Using established procedures, an ultra-precision positioning system (100 mm stroke and ±10 nm positioning accuracy) with a single plane X-Y stage is fabricated. Its performance is evaluated through simulation using Matlab. After analyzing previous control algorithms and adapting modern control theory, a dual servo algorithm is developed for a minimum order observer to secure the stability and priority on the controller. The simulations and experiments on the ultra precision positioning and the stability of the ultra-precision positioning system with single plane X-Y stage and the priority of the control algorithm are secured by using Matlab with Simulink and ControlDesk made in dSPACE

  13. Nano positioning control for dual stage using minimum order observer

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hong Gun [Jeonju University, Jeonju (Korea, Republic of)

    2012-03-15

    A nano positioning control is developed using the ultra-precision positioning apparatus such as actuator, sensor, guide, power transmission element with an appropriate control method. Using established procedures, a single plane X-Y stage with ultra-precision positioning is manufactured. A global stage for materialization with robust system is combined by using an AC servo motor with a ball screw and rolling guide. An ultra-precision positioning system is developed using a micro stage with an elastic hinge and piezo element. Global and micro servos for positioning with nanometer accuracy are controlled simultaneously using an incremental encoder and a laser interferometer to measure displacement. Using established procedures, an ultra-precision positioning system (100 mm stroke and {+-}10 nm positioning accuracy) with a single plane X-Y stage is fabricated. Its performance is evaluated through simulation using Matlab. After analyzing previous control algorithms and adapting modern control theory, a dual servo algorithm is developed for a minimum order observer to secure the stability and priority on the controller. The simulations and experiments on the ultra precision positioning and the stability of the ultra-precision positioning system with single plane X-Y stage and the priority of the control algorithm are secured by using Matlab with Simulink and ControlDesk made in dSPACE.

  14. A COSMIC VARIANCE COOKBOOK

    International Nuclear Information System (INIS)

    Moster, Benjamin P.; Rix, Hans-Walter; Somerville, Rachel S.; Newman, Jeffrey A.

    2011-01-01

    Deep pencil beam surveys ( 2 ) are of fundamental importance for studying the high-redshift universe. However, inferences about galaxy population properties (e.g., the abundance of objects) are in practice limited by 'cosmic variance'. This is the uncertainty in observational estimates of the number density of galaxies arising from the underlying large-scale density fluctuations. This source of uncertainty can be significant, especially for surveys which cover only small areas and for massive high-redshift galaxies. Cosmic variance for a given galaxy population can be determined using predictions from cold dark matter theory and the galaxy bias. In this paper, we provide tools for experiment design and interpretation. For a given survey geometry, we present the cosmic variance of dark matter as a function of mean redshift z-bar and redshift bin size Δz. Using a halo occupation model to predict galaxy clustering, we derive the galaxy bias as a function of mean redshift for galaxy samples of a given stellar mass range. In the linear regime, the cosmic variance of these galaxy samples is the product of the galaxy bias and the dark matter cosmic variance. We present a simple recipe using a fitting function to compute cosmic variance as a function of the angular dimensions of the field, z-bar , Δz, and stellar mass m * . We also provide tabulated values and a software tool. The accuracy of the resulting cosmic variance estimates (δσ v /σ v ) is shown to be better than 20%. We find that for GOODS at z-bar =2 and with Δz = 0.5, the relative cosmic variance of galaxies with m * >10 11 M sun is ∼38%, while it is ∼27% for GEMS and ∼12% for COSMOS. For galaxies of m * ∼ 10 10 M sun , the relative cosmic variance is ∼19% for GOODS, ∼13% for GEMS, and ∼6% for COSMOS. This implies that cosmic variance is a significant source of uncertainty at z-bar =2 for small fields and massive galaxies, while for larger fields and intermediate mass galaxies, cosmic

  15. Continuous-Time Mean-Variance Portfolio Selection under the CEV Process

    Directory of Open Access Journals (Sweden)

    Hui-qiang Ma

    2014-01-01

    Full Text Available We consider a continuous-time mean-variance portfolio selection model when stock price follows the constant elasticity of variance (CEV process. The aim of this paper is to derive an optimal portfolio strategy and the efficient frontier. The mean-variance portfolio selection problem is formulated as a linearly constrained convex program problem. By employing the Lagrange multiplier method and stochastic optimal control theory, we obtain the optimal portfolio strategy and mean-variance efficient frontier analytically. The results show that the mean-variance efficient frontier is still a parabola in the mean-variance plane, and the optimal strategies depend not only on the total wealth but also on the stock price. Moreover, some numerical examples are given to analyze the sensitivity of the efficient frontier with respect to the elasticity parameter and to illustrate the results presented in this paper. The numerical results show that the price of risk decreases as the elasticity coefficient increases.

  16. HOTELLING'S T2 CONTROL CHARTS BASED ON ROBUST ESTIMATORS

    Directory of Open Access Journals (Sweden)

    SERGIO YÁÑEZ

    2010-01-01

    Full Text Available Under the presence of multivariate outliers, in a Phase I analysis of historical set of data, the T 2 control chart based on the usual sample mean vector and sample variance covariance matrix performs poorly. Several alternative estimators have been proposed. Among them, estimators based on the minimum volume ellipsoid (MVE and the minimum covariance determinant (MCD are powerful in detecting a reasonable number of outliers. In this paper we propose a T 2 control chart using the biweight S estimators for the location and dispersion parameters when monitoring multivariate individual observations. Simulation studies show that this method outperforms the T 2 control chart based on MVE estimators for a small number of observations.

  17. MCNP variance reduction overview

    International Nuclear Information System (INIS)

    Hendricks, J.S.; Booth, T.E.

    1985-01-01

    The MCNP code is rich in variance reduction features. Standard variance reduction methods found in most Monte Carlo codes are available as well as a number of methods unique to MCNP. We discuss the variance reduction features presently in MCNP as well as new ones under study for possible inclusion in future versions of the code

  18. Significant improvements of electrical discharge machining performance by step-by-step updated adaptive control laws

    Science.gov (United States)

    Zhou, Ming; Wu, Jianyang; Xu, Xiaoyi; Mu, Xin; Dou, Yunping

    2018-02-01

    In order to obtain improved electrical discharge machining (EDM) performance, we have dedicated more than a decade to correcting one essential EDM defect, the weak stability of the machining, by developing adaptive control systems. The instabilities of machining are mainly caused by complicated disturbances in discharging. To counteract the effects from the disturbances on machining, we theoretically developed three control laws from minimum variance (MV) control law to minimum variance and pole placements coupled (MVPPC) control law and then to a two-step-ahead prediction (TP) control law. Based on real-time estimation of EDM process model parameters and measured ratio of arcing pulses which is also called gap state, electrode discharging cycle was directly and adaptively tuned so that a stable machining could be achieved. To this end, we not only theoretically provide three proved control laws for a developed EDM adaptive control system, but also practically proved the TP control law to be the best in dealing with machining instability and machining efficiency though the MVPPC control law provided much better EDM performance than the MV control law. It was also shown that the TP control law also provided a burn free machining.

  19. Spectral Ambiguity of Allan Variance

    Science.gov (United States)

    Greenhall, C. A.

    1996-01-01

    We study the extent to which knowledge of Allan variance and other finite-difference variances determines the spectrum of a random process. The variance of first differences is known to determine the spectrum. We show that, in general, the Allan variance does not. A complete description of the ambiguity is given.

  20. Analysis of Gene Expression Variance in Schizophrenia Using Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Anna A. Igolkina

    2018-06-01

    Full Text Available Schizophrenia (SCZ is a psychiatric disorder of unknown etiology. There is evidence suggesting that aberrations in neurodevelopment are a significant attribute of schizophrenia pathogenesis and progression. To identify biologically relevant molecular abnormalities affecting neurodevelopment in SCZ we used cultured neural progenitor cells derived from olfactory neuroepithelium (CNON cells. Here, we tested the hypothesis that variance in gene expression differs between individuals from SCZ and control groups. In CNON cells, variance in gene expression was significantly higher in SCZ samples in comparison with control samples. Variance in gene expression was enriched in five molecular pathways: serine biosynthesis, PI3K-Akt, MAPK, neurotrophin and focal adhesion. More than 14% of variance in disease status was explained within the logistic regression model (C-value = 0.70 by predictors accounting for gene expression in 69 genes from these five pathways. Structural equation modeling (SEM was applied to explore how the structure of these five pathways was altered between SCZ patients and controls. Four out of five pathways showed differences in the estimated relationships among genes: between KRAS and NF1, and KRAS and SOS1 in the MAPK pathway; between PSPH and SHMT2 in serine biosynthesis; between AKT3 and TSC2 in the PI3K-Akt signaling pathway; and between CRK and RAPGEF1 in the focal adhesion pathway. Our analysis provides evidence that variance in gene expression is an important characteristic of SCZ, and SEM is a promising method for uncovering altered relationships between specific genes thus suggesting affected gene regulation associated with the disease. We identified altered gene-gene interactions in pathways enriched for genes with increased variance in expression in SCZ. These pathways and loci were previously implicated in SCZ, providing further support for the hypothesis that gene expression variance plays important role in the etiology

  1. Robust control of flexible space vehicles with minimum structural excitation: On-off pulse control of flexible space vehicles

    Science.gov (United States)

    Wie, Bong; Liu, Qiang

    1992-01-01

    Both feedback and feedforward control approaches for uncertain dynamical systems (in particular, with uncertainty in structural mode frequency) are investigated. The control objective is to achieve a fast settling time (high performance) and robustness (insensitivity) to plant uncertainty. Preshaping of an ideal, time optimal control input using a tapped-delay filter is shown to provide a fast settling time with robust performance. A robust, non-minimum-phase feedback controller is synthesized with particular emphasis on its proper implementation for a non-zero set-point control problem. It is shown that a properly designed, feedback controller performs well, as compared with a time optimal open loop controller with special preshaping for performance robustness. Also included are two separate papers by the same authors on this subject.

  2. Non-Gaussian Systems Control Performance Assessment Based on Rational Entropy

    Directory of Open Access Journals (Sweden)

    Jinglin Zhou

    2018-05-01

    Full Text Available Control loop Performance Assessment (CPA plays an important role in system operations. Stochastic statistical CPA index, such as a minimum variance controller (MVC-based CPA index, is one of the most widely used CPA indices. In this paper, a new minimum entropy controller (MEC-based CPA method of linear non-Gaussian systems is proposed. In this method, probability density function (PDF and rational entropy (RE are respectively used to describe the characteristics and the uncertainty of random variables. To better estimate the performance benchmark, an improved EDA algorithm, which is used to estimate the system parameters and noise PDF, is given. The effectiveness of the proposed method is illustrated through case studies on an ARMAX system.

  3. Partial volume effect correction in PET using regularized iterative deconvolution with variance control based on local topology

    International Nuclear Information System (INIS)

    Kirov, A S; Schmidtlein, C R; Piao, J Z

    2008-01-01

    Correcting positron emission tomography (PET) images for the partial volume effect (PVE) due to the limited resolution of PET has been a long-standing challenge. Various approaches including incorporation of the system response function in the reconstruction have been previously tested. We present a post-reconstruction PVE correction based on iterative deconvolution using a 3D maximum likelihood expectation-maximization (MLEM) algorithm. To achieve convergence we used a one step late (OSL) regularization procedure based on the assumption of local monotonic behavior of the PET signal following Alenius et al. This technique was further modified to selectively control variance depending on the local topology of the PET image. No prior 'anatomic' information is needed in this approach. An estimate of the noise properties of the image is used instead. The procedure was tested for symmetric and isotropic deconvolution functions with Gaussian shape and full width at half-maximum (FWHM) ranging from 6.31 mm to infinity. The method was applied to simulated and experimental scans of the NEMA NU 2 image quality phantom with the GE Discovery LS PET/CT scanner. The phantom contained uniform activity spheres with diameters ranging from 1 cm to 3.7 cm within uniform background. The optimal sphere activity to variance ratio was obtained when the deconvolution function was replaced by a step function few voxels wide. In this case, the deconvolution method converged in ∼3-5 iterations for most points on both the simulated and experimental images. For the 1 cm diameter sphere, the contrast recovery improved from 12% to 36% in the simulated and from 21% to 55% in the experimental data. Recovery coefficients between 80% and 120% were obtained for all larger spheres, except for the 13 mm diameter sphere in the simulated scan (68%). No increase in variance was observed except for a few voxels neighboring strong activity gradients and inside the largest spheres. Testing the method for

  4. How large are actor and partner effects of personality on relationship satisfaction? The importance of controlling for shared method variance.

    Science.gov (United States)

    Orth, Ulrich

    2013-10-01

    Previous research suggests that the personality of a relationship partner predicts not only the individual's own satisfaction with the relationship but also the partner's satisfaction. Based on the actor-partner interdependence model, the present research tested whether actor and partner effects of personality are biased when the same method (e.g., self-report) is used for the assessment of personality and relationship satisfaction and, consequently, shared method variance is not controlled for. Data came from 186 couples, of whom both partners provided self- and partner reports on the Big Five personality traits. Depending on the research design, actor effects were larger than partner effects (when using only self-reports), smaller than partner effects (when using only partner reports), or of about the same size as partner effects (when using self- and partner reports). The findings attest to the importance of controlling for shared method variance in dyadic data analysis.

  5. A unique concept for automatically controlling the braking action of wheeled vehicles during minimum distance stops

    Science.gov (United States)

    Barthlome, D. E.

    1975-01-01

    Test results of a unique automatic brake control system are outlined and a comparison is made of its mode of operation to that of an existing skid control system. The purpose of the test system is to provide automatic control of braking action such that hydraulic brake pressure is maintained at a near constant, optimum value during minimum distance stops.

  6. Delta-Domain Predictive Control and Identification for Control

    DEFF Research Database (Denmark)

    Lauritsen, Morten Bach

    1997-01-01

    The present thesis is concerned with different aspects of modelling, control and identification of linear systems. Traditionally, discrete-time sampled-data systems are represented using shift-operator parametrizations. Such parametrizations are not suitable at fast sampling rates. An alternative...... minimum-variance predictor as a special case and to have a well-defined continuous-time limit. By means of this new prediction method a unified framework for discrete-time and continuous-time predictive control algorithms is developed. This contains a continuous-time like discrete-time predictive...... controller which is insensitive to the choice of sampling period and has a well-defined limit in the continuous-time case. Also more conventional discrete-time predictive control methods may be described within the unified approach. The predictive control algorithms are extended to frequency weighted...

  7. Bounds on Minimum Energy per Bit for Optical Wireless Relay Channels

    Directory of Open Access Journals (Sweden)

    A. D. Raza

    2014-09-01

    Full Text Available An optical wireless relay channel (OWRC is the classical three node network consisting of source, re- lay and destination nodes with optical wireless connectivity. The channel law is assumed Gaussian. This paper studies the bounds on minimum energy per bit required for reliable communication over an OWRC. It is shown that capacity of an OWRC is concave and energy per bit is monotonically increasing in square of the peak optical signal power, and consequently the minimum energy per bit is inversely pro- portional to the square root of asymptotic capacity at low signal to noise ratio. This has been used to develop upper and lower bound on energy per bit as a function of peak signal power, mean to peak power ratio, and variance of channel noise. The upper and lower bounds on minimum energy per bit derived in this paper correspond respectively to the decode and forward lower bound and the min-max cut upper bound on OWRC capacity

  8. Minimum airflow reset of single-duct VAV terminal boxes

    Science.gov (United States)

    Cho, Young-Hum

    Single duct Variable Air Volume (VAV) systems are currently the most widely used type of HVAC system in the United States. When installing such a system, it is critical to determine the minimum airflow set point of the terminal box, as an optimally selected set point will improve the level of thermal comfort and indoor air quality (IAQ) while at the same time lower overall energy costs. In principle, this minimum rate should be calculated according to the minimum ventilation requirement based on ASHRAE standard 62.1 and maximum heating load of the zone. Several factors must be carefully considered when calculating this minimum rate. Terminal boxes with conventional control sequences may result in occupant discomfort and energy waste. If the minimum rate of airflow is set too high, the AHUs will consume excess fan power, and the terminal boxes may cause significant simultaneous room heating and cooling. At the same time, a rate that is too low will result in poor air circulation and indoor air quality in the air-conditioned space. Currently, many scholars are investigating how to change the algorithm of the advanced VAV terminal box controller without retrofitting. Some of these controllers have been found to effectively improve thermal comfort, indoor air quality, and energy efficiency. However, minimum airflow set points have not yet been identified, nor has controller performance been verified in confirmed studies. In this study, control algorithms were developed that automatically identify and reset terminal box minimum airflow set points, thereby improving indoor air quality and thermal comfort levels, and reducing the overall rate of energy consumption. A theoretical analysis of the optimal minimum airflow and discharge air temperature was performed to identify the potential energy benefits of resetting the terminal box minimum airflow set points. Applicable control algorithms for calculating the ideal values for the minimum airflow reset were developed and

  9. Host nutrition alters the variance in parasite transmission potential.

    Science.gov (United States)

    Vale, Pedro F; Choisy, Marc; Little, Tom J

    2013-04-23

    The environmental conditions experienced by hosts are known to affect their mean parasite transmission potential. How different conditions may affect the variance of transmission potential has received less attention, but is an important question for disease management, especially if specific ecological contexts are more likely to foster a few extremely infectious hosts. Using the obligate-killing bacterium Pasteuria ramosa and its crustacean host Daphnia magna, we analysed how host nutrition affected the variance of individual parasite loads, and, therefore, transmission potential. Under low food, individual parasite loads showed similar mean and variance, following a Poisson distribution. By contrast, among well-nourished hosts, parasite loads were right-skewed and overdispersed, following a negative binomial distribution. Abundant food may, therefore, yield individuals causing potentially more transmission than the population average. Measuring both the mean and variance of individual parasite loads in controlled experimental infections may offer a useful way of revealing risk factors for potential highly infectious hosts.

  10. On Optimal Input Design for Feed-forward Control

    OpenAIRE

    Hägg, Per; Wahlberg, Bo

    2013-01-01

    This paper considers optimal input design when the intended use of the identified model is to construct a feed-forward controller based on measurable disturbances. The objective is to find a minimum power excitation signal to be used in a system identification experiment, such that the corresponding model-based feed-forward controller guarantees, with a given probability, that the variance of the output signal is within given specifications. To start with, some low order model problems are an...

  11. Phenotypic variance explained by local ancestry in admixed African Americans.

    Science.gov (United States)

    Shriner, Daniel; Bentley, Amy R; Doumatey, Ayo P; Chen, Guanjie; Zhou, Jie; Adeyemo, Adebowale; Rotimi, Charles N

    2015-01-01

    We surveyed 26 quantitative traits and disease outcomes to understand the proportion of phenotypic variance explained by local ancestry in admixed African Americans. After inferring local ancestry as the number of African-ancestry chromosomes at hundreds of thousands of genotyped loci across all autosomes, we used a linear mixed effects model to estimate the variance explained by local ancestry in two large independent samples of unrelated African Americans. We found that local ancestry at major and polygenic effect genes can explain up to 20 and 8% of phenotypic variance, respectively. These findings provide evidence that most but not all additive genetic variance is explained by genetic markers undifferentiated by ancestry. These results also inform the proportion of health disparities due to genetic risk factors and the magnitude of error in association studies not controlling for local ancestry.

  12. Solution of the problem of the identified minimum for the tri-variate ...

    Indian Academy of Sciences (India)

    tified minimum is considered below has zero means, and distinct variances. The solution ... and a non-singular covariance matrix , where ij = ρij σi σj for i ...... (i) through (iv) above, we can use (4.29) to identify a2. 21. , a2. 31. , a2. 12. , a2. 32 uniquely. Now we consider (4.28). In this case, there are two possibilities: (A2. 1, B2.

  13. Reexamining financial and economic predictability with new estimators of realized variance and variance risk premium

    DEFF Research Database (Denmark)

    Casas, Isabel; Mao, Xiuping; Veiga, Helena

    This study explores the predictive power of new estimators of the equity variance risk premium and conditional variance for future excess stock market returns, economic activity, and financial instability, both during and after the last global financial crisis. These estimators are obtained from...... time-varying coefficient models are the ones showing considerably higher predictive power for stock market returns and financial instability during the financial crisis, suggesting that an extreme volatility period requires models that can adapt quickly to turmoil........ Moreover, a comparison of the overall results reveals that the conditional variance gains predictive power during the global financial crisis period. Furthermore, both the variance risk premium and conditional variance are determined to be predictors of future financial instability, whereas conditional...

  14. Combined feedforward and model-assisted active disturbance rejection control for non-minimum phase system.

    Science.gov (United States)

    Sun, Li; Li, Donghai; Gao, Zhiqiang; Yang, Zhao; Zhao, Shen

    2016-09-01

    Control of the non-minimum phase (NMP) system is challenging, especially in the presence of modelling uncertainties and external disturbances. To this end, this paper presents a combined feedforward and model-assisted Active Disturbance Rejection Control (MADRC) strategy. Based on the nominal model, the feedforward controller is used to produce a tracking performance that has minimum settling time subject to a prescribed undershoot constraint. On the other hand, the unknown disturbances and uncertain dynamics beyond the nominal model are compensated by MADRC. Since the conventional Extended State Observer (ESO) is not suitable for the NMP system, a model-assisted ESO (MESO) is proposed based on the nominal observable canonical form. The convergence of MESO is proved in time domain. The stability, steady-state characteristics and robustness of the closed-loop system are analyzed in frequency domain. The proposed strategy has only one tuning parameter, i.e., the bandwidth of MESO, which can be readily determined with a prescribed robustness level. Some comparative examples are given to show the efficacy of the proposed method. This paper depicts a promising prospect of the model-assisted ADRC in dealing with complex systems. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  15. Minimum Energy Control of 2D Positive Continuous-Discrete Linear Systems

    Directory of Open Access Journals (Sweden)

    Kaczorek Tadeusz

    2014-09-01

    Full Text Available The minimum energy control problem for the 2D positive continuous-discrete linear systems is formulated and solved. Necessary and sufficient conditions for the reachability at the point of the systems are given. Sufficient conditions for the existence of solution to the problem are established. It is shown that if the system is reachable then there exists an optimal input that steers the state from zero boundary conditions to given final state and minimizing the performance index for only one step (q = 1. A procedure for solving of the problem is proposed and illustrated by a numerical example.

  16. Integrating mean and variance heterogeneities to identify differentially expressed genes.

    Science.gov (United States)

    Ouyang, Weiwei; An, Qiang; Zhao, Jinying; Qin, Huaizhen

    2016-12-06

    In functional genomics studies, tests on mean heterogeneity have been widely employed to identify differentially expressed genes with distinct mean expression levels under different experimental conditions. Variance heterogeneity (aka, the difference between condition-specific variances) of gene expression levels is simply neglected or calibrated for as an impediment. The mean heterogeneity in the expression level of a gene reflects one aspect of its distribution alteration; and variance heterogeneity induced by condition change may reflect another aspect. Change in condition may alter both mean and some higher-order characteristics of the distributions of expression levels of susceptible genes. In this report, we put forth a conception of mean-variance differentially expressed (MVDE) genes, whose expression means and variances are sensitive to the change in experimental condition. We mathematically proved the null independence of existent mean heterogeneity tests and variance heterogeneity tests. Based on the independence, we proposed an integrative mean-variance test (IMVT) to combine gene-wise mean heterogeneity and variance heterogeneity induced by condition change. The IMVT outperformed its competitors under comprehensive simulations of normality and Laplace settings. For moderate samples, the IMVT well controlled type I error rates, and so did existent mean heterogeneity test (i.e., the Welch t test (WT), the moderated Welch t test (MWT)) and the procedure of separate tests on mean and variance heterogeneities (SMVT), but the likelihood ratio test (LRT) severely inflated type I error rates. In presence of variance heterogeneity, the IMVT appeared noticeably more powerful than all the valid mean heterogeneity tests. Application to the gene profiles of peripheral circulating B raised solid evidence of informative variance heterogeneity. After adjusting for background data structure, the IMVT replicated previous discoveries and identified novel experiment

  17. A zero-variance-based scheme for variance reduction in Monte Carlo criticality

    Energy Technology Data Exchange (ETDEWEB)

    Christoforou, S.; Hoogenboom, J. E. [Delft Univ. of Technology, Mekelweg 15, 2629 JB Delft (Netherlands)

    2006-07-01

    A zero-variance scheme is derived and proven theoretically for criticality cases, and a simplified transport model is used for numerical demonstration. It is shown in practice that by appropriate biasing of the transition and collision kernels, a significant reduction in variance can be achieved. This is done using the adjoint forms of the emission and collision densities, obtained from a deterministic calculation, according to the zero-variance scheme. By using an appropriate algorithm, the figure of merit of the simulation increases by up to a factor of 50, with the possibility of an even larger improvement. In addition, it is shown that the biasing speeds up the convergence of the initial source distribution. (authors)

  18. A zero-variance-based scheme for variance reduction in Monte Carlo criticality

    International Nuclear Information System (INIS)

    Christoforou, S.; Hoogenboom, J. E.

    2006-01-01

    A zero-variance scheme is derived and proven theoretically for criticality cases, and a simplified transport model is used for numerical demonstration. It is shown in practice that by appropriate biasing of the transition and collision kernels, a significant reduction in variance can be achieved. This is done using the adjoint forms of the emission and collision densities, obtained from a deterministic calculation, according to the zero-variance scheme. By using an appropriate algorithm, the figure of merit of the simulation increases by up to a factor of 50, with the possibility of an even larger improvement. In addition, it is shown that the biasing speeds up the convergence of the initial source distribution. (authors)

  19. Real-time performance assessment and adaptive control for a water chiller unit in an HVAC system

    Science.gov (United States)

    Bai, Jianbo; Li, Yang; Chen, Jianhao

    2018-02-01

    The paper proposes an adaptive control method for a water chiller unit in a HVAC system. Based on the minimum variance evaluation, the adaptive control method was used to realize better control of the water chiller unit. To verify the performance of the adaptive control method, the proposed method was compared with an a conventional PID controller, the simulation results showed that adaptive control method had superior control performance to that of the conventional PID controller.

  20. Deterministic mean-variance-optimal consumption and investment

    DEFF Research Database (Denmark)

    Christiansen, Marcus; Steffensen, Mogens

    2013-01-01

    In dynamic optimal consumption–investment problems one typically aims to find an optimal control from the set of adapted processes. This is also the natural starting point in case of a mean-variance objective. In contrast, we solve the optimization problem with the special feature that the consum......In dynamic optimal consumption–investment problems one typically aims to find an optimal control from the set of adapted processes. This is also the natural starting point in case of a mean-variance objective. In contrast, we solve the optimization problem with the special feature...... that the consumption rate and the investment proportion are constrained to be deterministic processes. As a result we get rid of a series of unwanted features of the stochastic solution including diffusive consumption, satisfaction points and consistency problems. Deterministic strategies typically appear in unit......-linked life insurance contracts, where the life-cycle investment strategy is age dependent but wealth independent. We explain how optimal deterministic strategies can be found numerically and present an example from life insurance where we compare the optimal solution with suboptimal deterministic strategies...

  1. Sensorless State-Space Control of Elastic Two-Inertia Drive System Using a Minimum State Order Observer

    Directory of Open Access Journals (Sweden)

    V. Comnac

    2009-12-01

    Full Text Available The paper presents sensorless state-space control of two-inertia drive system with resilient coupling. The control structure contains an I+PI controller for load speed regulation and a state feedback controller for effective vibration suppression of the elastic coupling. Mechanical state variable of two-inertia drive are obtained by using a linear minimum-order (Gopinath state observer. The design of the combined (I+PI and state feedback controller is achieved with the extended version of the modulus criterion [5]. The dynamic behavior of presented control structure has been examined, for different conditions, using MATLAB/SIMULINK simulation.

  2. Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.

    Science.gov (United States)

    Dazard, Jean-Eudes; Rao, J Sunil

    2012-07-01

    The paper addresses a common problem in the analysis of high-dimensional high-throughput "omics" data, which is parameter estimation across multiple variables in a set of data where the number of variables is much larger than the sample size. Among the problems posed by this type of data are that variable-specific estimators of variances are not reliable and variable-wise tests statistics have low power, both due to a lack of degrees of freedom. In addition, it has been observed in this type of data that the variance increases as a function of the mean. We introduce a non-parametric adaptive regularization procedure that is innovative in that : (i) it employs a novel "similarity statistic"-based clustering technique to generate local-pooled or regularized shrinkage estimators of population parameters, (ii) the regularization is done jointly on population moments, benefiting from C. Stein's result on inadmissibility, which implies that usual sample variance estimator is improved by a shrinkage estimator using information contained in the sample mean. From these joint regularized shrinkage estimators, we derived regularized t-like statistics and show in simulation studies that they offer more statistical power in hypothesis testing than their standard sample counterparts, or regular common value-shrinkage estimators, or when the information contained in the sample mean is simply ignored. Finally, we show that these estimators feature interesting properties of variance stabilization and normalization that can be used for preprocessing high-dimensional multivariate data. The method is available as an R package, called 'MVR' ('Mean-Variance Regularization'), downloadable from the CRAN website.

  3. Hybrid biasing approaches for global variance reduction

    International Nuclear Information System (INIS)

    Wu, Zeyun; Abdel-Khalik, Hany S.

    2013-01-01

    A new variant of Monte Carlo—deterministic (DT) hybrid variance reduction approach based on Gaussian process theory is presented for accelerating convergence of Monte Carlo simulation and compared with Forward-Weighted Consistent Adjoint Driven Importance Sampling (FW-CADIS) approach implemented in the SCALE package from Oak Ridge National Laboratory. The new approach, denoted the Gaussian process approach, treats the responses of interest as normally distributed random processes. The Gaussian process approach improves the selection of the weight windows of simulated particles by identifying a subspace that captures the dominant sources of statistical response variations. Like the FW-CADIS approach, the Gaussian process approach utilizes particle importance maps obtained from deterministic adjoint models to derive weight window biasing. In contrast to the FW-CADIS approach, the Gaussian process approach identifies the response correlations (via a covariance matrix) and employs them to reduce the computational overhead required for global variance reduction (GVR) purpose. The effective rank of the covariance matrix identifies the minimum number of uncorrelated pseudo responses, which are employed to bias simulated particles. Numerical experiments, serving as a proof of principle, are presented to compare the Gaussian process and FW-CADIS approaches in terms of the global reduction in standard deviation of the estimated responses. - Highlights: ► Hybrid Monte Carlo Deterministic Method based on Gaussian Process Model is introduced. ► Method employs deterministic model to calculate responses correlations. ► Method employs correlations to bias Monte Carlo transport. ► Method compared to FW-CADIS methodology in SCALE code. ► An order of magnitude speed up is achieved for a PWR core model.

  4. Portfolio optimization using median-variance approach

    Science.gov (United States)

    Wan Mohd, Wan Rosanisah; Mohamad, Daud; Mohamed, Zulkifli

    2013-04-01

    Optimization models have been applied in many decision-making problems particularly in portfolio selection. Since the introduction of Markowitz's theory of portfolio selection, various approaches based on mathematical programming have been introduced such as mean-variance, mean-absolute deviation, mean-variance-skewness and conditional value-at-risk (CVaR) mainly to maximize return and minimize risk. However most of the approaches assume that the distribution of data is normal and this is not generally true. As an alternative, in this paper, we employ the median-variance approach to improve the portfolio optimization. This approach has successfully catered both types of normal and non-normal distribution of data. With this actual representation, we analyze and compare the rate of return and risk between the mean-variance and the median-variance based portfolio which consist of 30 stocks from Bursa Malaysia. The results in this study show that the median-variance approach is capable to produce a lower risk for each return earning as compared to the mean-variance approach.

  5. Exploring variance in residential electricity consumption: Household features and building properties

    International Nuclear Information System (INIS)

    Bartusch, Cajsa; Odlare, Monica; Wallin, Fredrik; Wester, Lars

    2012-01-01

    Highlights: ► Statistical analysis of variance are of considerable value in identifying key indicators for policy update. ► Variance in residential electricity use is partly explained by household features. ► Variance in residential electricity use is partly explained by building properties. ► Household behavior has a profound impact on individual electricity use. -- Abstract: Improved means of controlling electricity consumption plays an important part in boosting energy efficiency in the Swedish power market. Developing policy instruments to that end requires more in-depth statistics on electricity use in the residential sector, among other things. The aim of the study has accordingly been to assess the extent of variance in annual electricity consumption in single-family homes as well as to estimate the impact of household features and building properties in this respect using independent samples t-tests and one-way as well as univariate independent samples analyses of variance. Statistically significant variances associated with geographic area, heating system, number of family members, family composition, year of construction, electric water heater and electric underfloor heating have been established. The overall result of the analyses is nevertheless that variance in residential electricity consumption cannot be fully explained by independent variables related to household and building characteristics alone. As for the methodological approach, the results further suggest that methods for statistical analysis of variance are of considerable value in indentifying key indicators for policy update and development.

  6. Efficient Cardinality/Mean-Variance Portfolios

    OpenAIRE

    Brito, R. Pedro; Vicente, Luís Nunes

    2014-01-01

    International audience; We propose a novel approach to handle cardinality in portfolio selection, by means of a biobjective cardinality/mean-variance problem, allowing the investor to analyze the efficient tradeoff between return-risk and number of active positions. Recent progress in multiobjective optimization without derivatives allow us to robustly compute (in-sample) the whole cardinality/mean-variance efficient frontier, for a variety of data sets and mean-variance models. Our results s...

  7. Variable selection for confounder control, flexible modeling and Collaborative Targeted Minimum Loss-based Estimation in causal inference

    Science.gov (United States)

    Schnitzer, Mireille E.; Lok, Judith J.; Gruber, Susan

    2015-01-01

    This paper investigates the appropriateness of the integration of flexible propensity score modeling (nonparametric or machine learning approaches) in semiparametric models for the estimation of a causal quantity, such as the mean outcome under treatment. We begin with an overview of some of the issues involved in knowledge-based and statistical variable selection in causal inference and the potential pitfalls of automated selection based on the fit of the propensity score. Using a simple example, we directly show the consequences of adjusting for pure causes of the exposure when using inverse probability of treatment weighting (IPTW). Such variables are likely to be selected when using a naive approach to model selection for the propensity score. We describe how the method of Collaborative Targeted minimum loss-based estimation (C-TMLE; van der Laan and Gruber, 2010) capitalizes on the collaborative double robustness property of semiparametric efficient estimators to select covariates for the propensity score based on the error in the conditional outcome model. Finally, we compare several approaches to automated variable selection in low-and high-dimensional settings through a simulation study. From this simulation study, we conclude that using IPTW with flexible prediction for the propensity score can result in inferior estimation, while Targeted minimum loss-based estimation and C-TMLE may benefit from flexible prediction and remain robust to the presence of variables that are highly correlated with treatment. However, in our study, standard influence function-based methods for the variance underestimated the standard errors, resulting in poor coverage under certain data-generating scenarios. PMID:26226129

  8. Genetic control of residual variance of yearling weight in nellore beef cattle

    NARCIS (Netherlands)

    Iung, L.H.S.; Neves, H.H.R.; Mulder, H.A.; Carvalheiro, R.

    2017-01-01

    There is evidence for genetic variability in residual variance of livestock traits, which offers the potential for selection for increased uniformity of production. Different statistical approaches have been employed to study this topic; however, little is known about the concordance between

  9. Estimation of the variance of noise in digital imaging for quality control

    International Nuclear Information System (INIS)

    Soro Bua, M.; Otero Martinez, C.; Vazquez Vazquez, R.; Santamarina Vazquez, F.; Lobato Busto, R.; Luna Vega, V.; Mosquera Sueiro, J.; Sanchez Garcia, M.; Pombar Camean, M.

    2011-01-01

    In this work is estimated variance kerma function pixel values for the real response curve nonlinear digital image system, without resorting to any approximation to the behavior of the detector. This result is compared with that obtained for the linearized version of the response curve.

  10. Observer-based attitude controller for lifting re-entry vehicle with non-minimum phase property

    Directory of Open Access Journals (Sweden)

    Wenming Nie

    2017-05-01

    Full Text Available This article concentrates on the attitude control problem for the lifting re-entry vehicle with non-minimum phase property. A novel attitude control method is proposed for this kind of lifting re-entry vehicle without assuming the internal dynamics to be measurable. First, an internal dynamics extended state observer is developed to deal with the unmeasurable problem of the internal dynamics. And then, the control scheme which adopts output feedback method is proposed by modifying the traditional output redefinition technique with internal dynamics extended state observer. This control scheme only requires the system output to be measurable, and it can still stabilize the unstable internal dynamics and track attitude commands. Besides, because of the inherent property of extended state observer in rejecting uncertainties and disturbances, the control precision of the proposed controller is higher than the controller designed with traditional output redefinition technique. Finally, the effectiveness and robustness of the proposed attitude controller are demonstrated by the simulation results.

  11. Approximation errors during variance propagation

    International Nuclear Information System (INIS)

    Dinsmore, Stephen

    1986-01-01

    Risk and reliability analyses are often performed by constructing and quantifying large fault trees. The inputs to these models are component failure events whose probability of occuring are best represented as random variables. This paper examines the errors inherent in two approximation techniques used to calculate the top event's variance from the inputs' variance. Two sample fault trees are evaluated and several three dimensional plots illustrating the magnitude of the error over a wide range of input means and variances are given

  12. Variance in exposed perturbations impairs retention of visuomotor adaptation.

    Science.gov (United States)

    Canaveral, Cesar Augusto; Danion, Frédéric; Berrigan, Félix; Bernier, Pierre-Michel

    2017-11-01

    Sensorimotor control requires an accurate estimate of the state of the body. The brain optimizes state estimation by combining sensory signals with predictions of the sensory consequences of motor commands using a forward model. Given that both sensory signals and predictions are uncertain (i.e., noisy), the brain optimally weights the relative reliance on each source of information during adaptation. In support, it is known that uncertainty in the sensory predictions influences the rate and generalization of visuomotor adaptation. We investigated whether uncertainty in the sensory predictions affects the retention of a new visuomotor relationship. This was done by exposing three separate groups to a visuomotor rotation whose mean was common at 15° counterclockwise but whose variance around the mean differed (i.e., SD of 0°, 3.2°, or 4.5°). Retention was assessed by measuring the persistence of the adapted behavior in a no-vision phase. Results revealed that mean reach direction late in adaptation was similar across groups, suggesting it depended mainly on the mean of exposed rotations and was robust to differences in variance. However, retention differed across groups, with higher levels of variance being associated with a more rapid reversion toward nonadapted behavior. A control experiment ruled out the possibility that differences in retention were accounted for by differences in success rates. Exposure to variable rotations may have increased the uncertainty in sensory predictions, making the adapted forward model more labile and susceptible to change or decay. NEW & NOTEWORTHY The brain predicts the sensory consequences of motor commands through a forward model. These predictions are subject to uncertainty. We use visuomotor adaptation and modulate uncertainty in the sensory predictions by manipulating the variance in exposed rotations. Results reveal that variance does not influence the final extent of adaptation but selectively impairs the retention of

  13. The phenotypic variance gradient - a novel concept.

    Science.gov (United States)

    Pertoldi, Cino; Bundgaard, Jørgen; Loeschcke, Volker; Barker, James Stuart Flinton

    2014-11-01

    Evolutionary ecologists commonly use reaction norms, which show the range of phenotypes produced by a set of genotypes exposed to different environments, to quantify the degree of phenotypic variance and the magnitude of plasticity of morphometric and life-history traits. Significant differences among the values of the slopes of the reaction norms are interpreted as significant differences in phenotypic plasticity, whereas significant differences among phenotypic variances (variance or coefficient of variation) are interpreted as differences in the degree of developmental instability or canalization. We highlight some potential problems with this approach to quantifying phenotypic variance and suggest a novel and more informative way to plot reaction norms: namely "a plot of log (variance) on the y-axis versus log (mean) on the x-axis, with a reference line added". This approach gives an immediate impression of how the degree of phenotypic variance varies across an environmental gradient, taking into account the consequences of the scaling effect of the variance with the mean. The evolutionary implications of the variation in the degree of phenotypic variance, which we call a "phenotypic variance gradient", are discussed together with its potential interactions with variation in the degree of phenotypic plasticity and canalization.

  14. Evolution of Genetic Variance during Adaptive Radiation.

    Science.gov (United States)

    Walter, Greg M; Aguirre, J David; Blows, Mark W; Ortiz-Barrientos, Daniel

    2018-04-01

    Genetic correlations between traits can concentrate genetic variance into fewer phenotypic dimensions that can bias evolutionary trajectories along the axis of greatest genetic variance and away from optimal phenotypes, constraining the rate of evolution. If genetic correlations limit adaptation, rapid adaptive divergence between multiple contrasting environments may be difficult. However, if natural selection increases the frequency of rare alleles after colonization of new environments, an increase in genetic variance in the direction of selection can accelerate adaptive divergence. Here, we explored adaptive divergence of an Australian native wildflower by examining the alignment between divergence in phenotype mean and divergence in genetic variance among four contrasting ecotypes. We found divergence in mean multivariate phenotype along two major axes represented by different combinations of plant architecture and leaf traits. Ecotypes also showed divergence in the level of genetic variance in individual traits and the multivariate distribution of genetic variance among traits. Divergence in multivariate phenotypic mean aligned with divergence in genetic variance, with much of the divergence in phenotype among ecotypes associated with changes in trait combinations containing substantial levels of genetic variance. Overall, our results suggest that natural selection can alter the distribution of genetic variance underlying phenotypic traits, increasing the amount of genetic variance in the direction of natural selection and potentially facilitating rapid adaptive divergence during an adaptive radiation.

  15. 12 CFR 3.6 - Minimum capital ratios.

    Science.gov (United States)

    2010-01-01

    ... should have well-diversified risks, including no undue interest rate risk exposure; excellent control... 12 Banks and Banking 1 2010-01-01 2010-01-01 false Minimum capital ratios. 3.6 Section 3.6 Banks and Banking COMPTROLLER OF THE CURRENCY, DEPARTMENT OF THE TREASURY MINIMUM CAPITAL RATIOS; ISSUANCE...

  16. Confidence Interval Approximation For Treatment Variance In ...

    African Journals Online (AJOL)

    In a random effects model with a single factor, variation is partitioned into two as residual error variance and treatment variance. While a confidence interval can be imposed on the residual error variance, it is not possible to construct an exact confidence interval for the treatment variance. This is because the treatment ...

  17. Quality control methods in accelerometer data processing: defining minimum wear time.

    Directory of Open Access Journals (Sweden)

    Carly Rich

    Full Text Available BACKGROUND: When using accelerometers to measure physical activity, researchers need to determine whether subjects have worn their device for a sufficient period to be included in analyses. We propose a minimum wear criterion using population-based accelerometer data, and explore the influence of gender and the purposeful inclusion of children with weekend data on reliability. METHODS: Accelerometer data obtained during the age seven sweep of the UK Millennium Cohort Study were analysed. Children were asked to wear an ActiGraph GT1M accelerometer for seven days. Reliability coefficients(r of mean daily counts/minute were calculated using the Spearman-Brown formula based on the intraclass correlation coefficient. An r of 1.0 indicates that all the variation is between- rather than within-children and that measurement is 100% reliable. An r of 0.8 is often regarded as acceptable reliability. Analyses were repeated on data from children who met different minimum daily wear times (one to 10 hours and wear days (one to seven days. Analyses were conducted for all children, separately for boys and girls, and separately for children with and without weekend data. RESULTS: At least one hour of wear time data was obtained from 7,704 singletons. Reliability increased as the minimum number of days and the daily wear time increased. A high reliability (r = 0.86 and sample size (n = 6,528 was achieved when children with ≥ two days lasting ≥10 hours/day were included in analyses. Reliability coefficients were similar for both genders. Purposeful sampling of children with weekend data resulted in comparable reliabilities to those calculated independent of weekend wear. CONCLUSION: Quality control procedures should be undertaken before analysing accelerometer data in large-scale studies. Using data from children with ≥ two days lasting ≥10 hours/day should provide reliable estimates of physical activity. It's unnecessary to include only children

  18. Control Performance Management in Industrial Automation Assessment, Diagnosis and Improvement of Control Loop Performance

    CERN Document Server

    Jelali, Mohieddine

    2013-01-01

    Control Performance Management in Industrial Automation provides a coherent and self-contained treatment of a group of methods and applications of burgeoning importance to the detection and solution of problems with control loops that are vital in maintaining product quality, operational safety, and efficiency of material and energy consumption in the process industries. The monograph deals with all aspects of control performance management (CPM), from controller assessment (minimum-variance-control-based and advanced methods), to detection and diagnosis of control loop problems (process non-linearities, oscillations, actuator faults), to the improvement of control performance (maintenance, re-design of loop components, automatic controller re-tuning). It provides a contribution towards the development and application of completely self-contained and automatic methodologies in the field. Moreover, within this work, many CPM tools have been developed that goes far beyond available CPM packages. Control Perform...

  19. Variance analysis of forecasted streamflow maxima in a wet temperate climate

    Science.gov (United States)

    Al Aamery, Nabil; Fox, James F.; Snyder, Mark; Chandramouli, Chandra V.

    2018-05-01

    Coupling global climate models, hydrologic models and extreme value analysis provides a method to forecast streamflow maxima, however the elusive variance structure of the results hinders confidence in application. Directly correcting the bias of forecasts using the relative change between forecast and control simulations has been shown to marginalize hydrologic uncertainty, reduce model bias, and remove systematic variance when predicting mean monthly and mean annual streamflow, prompting our investigation for maxima streamflow. We assess the variance structure of streamflow maxima using realizations of emission scenario, global climate model type and project phase, downscaling methods, bias correction, extreme value methods, and hydrologic model inputs and parameterization. Results show that the relative change of streamflow maxima was not dependent on systematic variance from the annual maxima versus peak over threshold method applied, albeit we stress that researchers strictly adhere to rules from extreme value theory when applying the peak over threshold method. Regardless of which method is applied, extreme value model fitting does add variance to the projection, and the variance is an increasing function of the return period. Unlike the relative change of mean streamflow, results show that the variance of the maxima's relative change was dependent on all climate model factors tested as well as hydrologic model inputs and calibration. Ensemble projections forecast an increase of streamflow maxima for 2050 with pronounced forecast standard error, including an increase of +30(±21), +38(±34) and +51(±85)% for 2, 20 and 100 year streamflow events for the wet temperate region studied. The variance of maxima projections was dominated by climate model factors and extreme value analyses.

  20. Variability of indoor and outdoor VOC measurements: An analysis using variance components

    International Nuclear Information System (INIS)

    Jia, Chunrong; Batterman, Stuart A.; Relyea, George E.

    2012-01-01

    This study examines concentrations of volatile organic compounds (VOCs) measured inside and outside of 162 residences in southeast Michigan, U.S.A. Nested analyses apportioned four sources of variation: city, residence, season, and measurement uncertainty. Indoor measurements were dominated by seasonal and residence effects, accounting for 50 and 31%, respectively, of the total variance. Contributions from measurement uncertainty (<20%) and city effects (<10%) were small. For outdoor measurements, season, city and measurement variation accounted for 43, 29 and 27% of variance, respectively, while residence location had negligible impact (<2%). These results show that, to obtain representative estimates of indoor concentrations, measurements in multiple seasons are required. In contrast, outdoor VOC concentrations can use multi-seasonal measurements at centralized locations. Error models showed that uncertainties at low concentrations might obscure effects of other factors. Variance component analyses can be used to interpret existing measurements, design effective exposure studies, and determine whether the instrumentation and protocols are satisfactory. - Highlights: ► The variability of VOC measurements was partitioned using nested analysis. ► Indoor VOCs were primarily controlled by seasonal and residence effects. ► Outdoor VOC levels were homogeneous within neighborhoods. ► Measurement uncertainty was high for many outdoor VOCs. ► Variance component analysis is useful for designing effective sampling programs. - Indoor VOC concentrations were primarily controlled by seasonal and residence effects; and outdoor concentrations were homogeneous within neighborhoods. Variance component analysis is a useful tool for designing effective sampling programs.

  1. Increased gender variance in autism spectrum disorders and attention deficit hyperactivity disorder.

    Science.gov (United States)

    Strang, John F; Kenworthy, Lauren; Dominska, Aleksandra; Sokoloff, Jennifer; Kenealy, Laura E; Berl, Madison; Walsh, Karin; Menvielle, Edgardo; Slesaransky-Poe, Graciela; Kim, Kyung-Eun; Luong-Tran, Caroline; Meagher, Haley; Wallace, Gregory L

    2014-11-01

    Evidence suggests over-representation of autism spectrum disorders (ASDs) and behavioral difficulties among people referred for gender issues, but rates of the wish to be the other gender (gender variance) among different neurodevelopmental disorders are unknown. This chart review study explored rates of gender variance as reported by parents on the Child Behavior Checklist (CBCL) in children with different neurodevelopmental disorders: ASD (N = 147, 24 females and 123 males), attention deficit hyperactivity disorder (ADHD; N = 126, 38 females and 88 males), or a medical neurodevelopmental disorder (N = 116, 57 females and 59 males), were compared with two non-referred groups [control sample (N = 165, 61 females and 104 males) and non-referred participants in the CBCL standardization sample (N = 1,605, 754 females and 851 males)]. Significantly greater proportions of participants with ASD (5.4%) or ADHD (4.8%) had parent reported gender variance than in the combined medical group (1.7%) or non-referred comparison groups (0-0.7%). As compared to non-referred comparisons, participants with ASD were 7.59 times more likely to express gender variance; participants with ADHD were 6.64 times more likely to express gender variance. The medical neurodevelopmental disorder group did not differ from non-referred samples in likelihood to express gender variance. Gender variance was related to elevated emotional symptoms in ADHD, but not in ASD. After accounting for sex ratio differences between the neurodevelopmental disorder and non-referred comparison groups, gender variance occurred equally in females and males.

  2. A finite state, finite memory minimum principle, part 2. [a discussion of game theory, signaling, stochastic processes, and control theory

    Science.gov (United States)

    Sandell, N. R., Jr.; Athans, M.

    1975-01-01

    The development of the theory of the finite - state, finite - memory (FSFM) stochastic control problem is discussed. The sufficiency of the FSFM minimum principle (which is in general only a necessary condition) was investigated. By introducing the notion of a signaling strategy as defined in the literature on games, conditions under which the FSFM minimum principle is sufficient were determined. This result explicitly interconnects the information structure of the FSFM problem with its optimality conditions. The min-H algorithm for the FSFM problem was studied. It is demonstrated that a version of the algorithm always converges to a particular type of local minimum termed a person - by - person extremal.

  3. Simulation of neoclassical tearing mode stabilization via minimum seeking method on ITER

    Energy Technology Data Exchange (ETDEWEB)

    Park, M. H.; Kim, K.; Na, D. H.; Byun, C. S.; Na, Y. S. [Seoul National Univ., Seoul (Korea, Republic of); Kim, M. [FNC Technology Co. Ltd, Yongin (Korea, Republic of)

    2016-10-15

    Neoclassical tearing modes (NTMs) are well known resistive magnetohydrodynamic (MHD) instabilities. These instabilities are sustained by a helically perturbed bootstrap current. NTMs produce magnetic islands in tokamak plasmas that can degrade confinement and lead to plasma disruption. Because of this, the stabilization of NTMs is one of the key issues for tokamaks that achieve high fusion performance such as ITER. Compensating for the lack of bootstrap current by an Electron Cyclotron Current Drive (ECCD) has been proved experimentally as an effective method to stabilize NTMs. In order to stabilize NTMs, it is important to reduce misalignment. So that even ECCD can destabilize the NTMs when misalignment is large. Feedback control method that does not fully require delicate and accurate real-time measurements and calculations, such as equilibrium reconstruction and EC ray-tracing, has also been proposed. One of the feedback control methods is minimum seeking method. This control method minimizes the island width by tuning the misalignment, assuming that the magnetic island width is a function of the misalignment. As a robust and simple method of controlling NTM, minimum 'island width growth rate' seeking control is purposed and compared with performance of minimum ' island width' seeking control. At the integrated numerical system, simulations of the NTM suppression are performed with two types of minimum seeking controllers; one is a FDM based minimum seeking controller and the other is a sinusoidal perturbation based minimum seeking method. The full suppression is achieved both types of controller. The controllers adjust poloidal angle of EC beam and reduce misalignment to zero. The sinusoidal perturbation based minimum seeking control need to modify the adaptive gain.

  4. Some novel inequalities for fuzzy variables on the variance and its rational upper bound

    Directory of Open Access Journals (Sweden)

    Xiajie Yi

    2016-02-01

    Full Text Available Abstract Variance is of great significance in measuring the degree of deviation, which has gained extensive usage in many fields in practical scenarios. The definition of the variance on the basis of the credibility measure was first put forward in 2002. Following this idea, the calculation of the accurate value of the variance for some special fuzzy variables, like the symmetric and asymmetric triangular fuzzy numbers and the Gaussian fuzzy numbers, is presented in this paper, which turns out to be far more complicated. Thus, in order to better implement variance in real-life projects like risk control and quality management, we suggest a rational upper bound of the variance based on an inequality, together with its calculation formula, which can largely simplify the calculation process within a reasonable range. Meanwhile, some discussions between the variance and its rational upper bound are presented to show the rationality of the latter. Furthermore, two inequalities regarding the rational upper bound of variance and standard deviation of the sum of two fuzzy variables and their individual variances and standard deviations are proved. Subsequently, some numerical examples are illustrated to show the effectiveness and the feasibility of the proposed inequalities.

  5. Self-Tuning Control of Linear Systems Followed by Deadzones

    Directory of Open Access Journals (Sweden)

    K. Kazlauskas

    2014-02-01

    Full Text Available The aim of the present paper is to increase the efficiency of self-tuning generalized minimum variance (GMV control of linear time-invariant (LTI systems followed by deadzone nonlinearities. An approach, based on reordering of observations to be processed for the reconstruction of an unknown internal signal that acts between LTI system and a static nonlinear block of the closed-loop Wiener system, has been developed. The results of GMV self-tuning control of the second order LTI system with an ordinary deadzone are given.

  6. Motor equivalence and structure of variance: multi-muscle postural synergies in Parkinson's disease.

    Science.gov (United States)

    Falaki, Ali; Huang, Xuemei; Lewis, Mechelle M; Latash, Mark L

    2017-07-01

    We explored posture-stabilizing multi-muscle synergies with two methods of analysis of multi-element, abundant systems: (1) Analysis of inter-cycle variance; and (2) Analysis of motor equivalence, both quantified within the framework of the uncontrolled manifold (UCM) hypothesis. Data collected in two earlier studies of patients with Parkinson's disease (PD) were re-analyzed. One study compared synergies in the space of muscle modes (muscle groups with parallel scaling of activation) during tasks performed by early-stage PD patients and controls. The other study explored the effects of dopaminergic medication on multi-muscle-mode synergies. Inter-cycle variance and absolute magnitude of the center of pressure displacement across consecutive cycles were quantified during voluntary whole-body sway within the UCM and orthogonal to the UCM space. The patients showed smaller indices of variance within the UCM and motor equivalence compared to controls. The indices were also smaller in the off-drug compared to on-drug condition. There were strong across-subject correlations between the inter-cycle variance within/orthogonal to the UCM and motor equivalent/non-motor equivalent displacements. This study has shown that, at least for cyclical tasks, analysis of variance and analysis of motor equivalence lead to metrics of stability that correlate with each other and show similar effects of disease and medication. These results show, for the first time, intimate links between indices of variance and motor equivalence. They suggest that analysis of motor equivalence, which requires only a handful of trials, could be used broadly in the field of motor disorders to analyze problems with action stability.

  7. Least-squares variance component estimation

    NARCIS (Netherlands)

    Teunissen, P.J.G.; Amiri-Simkooei, A.R.

    2007-01-01

    Least-squares variance component estimation (LS-VCE) is a simple, flexible and attractive method for the estimation of unknown variance and covariance components. LS-VCE is simple because it is based on the well-known principle of LS; it is flexible because it works with a user-defined weight

  8. Robust Sequential Covariance Intersection Fusion Kalman Filtering over Multi-agent Sensor Networks with Measurement Delays and Uncertain Noise Variances

    Institute of Scientific and Technical Information of China (English)

    QI Wen-Juan; ZHANG Peng; DENG Zi-Li

    2014-01-01

    This paper deals with the problem of designing robust sequential covariance intersection (SCI) fusion Kalman filter for the clustering multi-agent sensor network system with measurement delays and uncertain noise variances. The sensor network is partitioned into clusters by the nearest neighbor rule. Using the minimax robust estimation principle, based on the worst-case conservative sensor network system with conservative upper bounds of noise variances, and applying the unbiased linear minimum variance (ULMV) optimal estimation rule, we present the two-layer SCI fusion robust steady-state Kalman filter which can reduce communication and computation burdens and save energy sources, and guarantee that the actual filtering error variances have a less-conservative upper-bound. A Lyapunov equation method for robustness analysis is proposed, by which the robustness of the local and fused Kalman filters is proved. The concept of the robust accuracy is presented and the robust accuracy relations of the local and fused robust Kalman filters are proved. It is proved that the robust accuracy of the global SCI fuser is higher than those of the local SCI fusers and the robust accuracies of all SCI fusers are higher than that of each local robust Kalman filter. A simulation example for a tracking system verifies the robustness and robust accuracy relations.

  9. The role of respondents’ comfort for variance in stated choice surveys

    DEFF Research Database (Denmark)

    Emang, Diana; Lundhede, Thomas; Thorsen, Bo Jellesmark

    2017-01-01

    they complete surveys correlates with the error variance in stated choice models of their responses. Comfort-related variables are included in the scale functions of the scaled multinomial logit models. The hypothesis was that higher comfort reduces error variance in answers, as revealed by a higher scale...... parameter and vice versa. Information on, e.g., sleep and time since eating (higher comfort) correlated with scale heterogeneity, and produced lower error variance when controlled for in the model. That respondents’ comfort may influence choice behavior suggests that knowledge of the respondents’ activity......Preference elicitation among outdoor recreational users is subject to measurement errors that depend, in part, on survey planning. This study uses data from a choice experiment survey on recreational SCUBA diving to investigate whether self-reported information on respondents’ comfort when...

  10. Genetic variants influencing phenotypic variance heterogeneity.

    Science.gov (United States)

    Ek, Weronica E; Rask-Andersen, Mathias; Karlsson, Torgny; Enroth, Stefan; Gyllensten, Ulf; Johansson, Åsa

    2018-03-01

    Most genetic studies identify genetic variants associated with disease risk or with the mean value of a quantitative trait. More rarely, genetic variants associated with variance heterogeneity are considered. In this study, we have identified such variance single-nucleotide polymorphisms (vSNPs) and examined if these represent biological gene × gene or gene × environment interactions or statistical artifacts caused by multiple linked genetic variants influencing the same phenotype. We have performed a genome-wide study, to identify vSNPs associated with variance heterogeneity in DNA methylation levels. Genotype data from over 10 million single-nucleotide polymorphisms (SNPs), and DNA methylation levels at over 430 000 CpG sites, were analyzed in 729 individuals. We identified vSNPs for 7195 CpG sites (P mean DNA methylation levels. We further showed that variance heterogeneity between genotypes mainly represents additional, often rare, SNPs in linkage disequilibrium (LD) with the respective vSNP and for some vSNPs, multiple low frequency variants co-segregating with one of the vSNP alleles. Therefore, our results suggest that variance heterogeneity of DNA methylation mainly represents phenotypic effects by multiple SNPs, rather than biological interactions. Such effects may also be important for interpreting variance heterogeneity of more complex clinical phenotypes.

  11. MMSE-based algorithm for joint signal detection, channel and noise variance estimation for OFDM systems

    CERN Document Server

    Savaux, Vincent

    2014-01-01

    This book presents an algorithm for the detection of an orthogonal frequency division multiplexing (OFDM) signal in a cognitive radio context by means of a joint and iterative channel and noise estimation technique. Based on the minimum mean square criterion, it performs an accurate detection of a user in a frequency band, by achieving a quasi-optimal channel and noise variance estimation if the signal is present, and by estimating the noise level in the band if the signal is absent. Organized into three chapters, the first chapter provides the background against which the system model is pr

  12. Origin and consequences of the relationship between protein mean and variance.

    Science.gov (United States)

    Vallania, Francesco Luigi Massimo; Sherman, Marc; Goodwin, Zane; Mogno, Ilaria; Cohen, Barak Alon; Mitra, Robi David

    2014-01-01

    Cell-to-cell variance in protein levels (noise) is a ubiquitous phenomenon that can increase fitness by generating phenotypic differences within clonal populations of cells. An important challenge is to identify the specific molecular events that control noise. This task is complicated by the strong dependence of a protein's cell-to-cell variance on its mean expression level through a power-law like relationship (σ2∝μ1.69). Here, we dissect the nature of this relationship using a stochastic model parameterized with experimentally measured values. This framework naturally recapitulates the power-law like relationship (σ2∝μ1.6) and accurately predicts protein variance across the yeast proteome (r2 = 0.935). Using this model we identified two distinct mechanisms by which protein variance can be increased. Variables that affect promoter activation, such as nucleosome positioning, increase protein variance by changing the exponent of the power-law relationship. In contrast, variables that affect processes downstream of promoter activation, such as mRNA and protein synthesis, increase protein variance in a mean-dependent manner following the power-law. We verified our findings experimentally using an inducible gene expression system in yeast. We conclude that the power-law-like relationship between noise and protein mean is due to the kinetics of promoter activation. Our results provide a framework for understanding how molecular processes shape stochastic variation across the genome.

  13. Combination of Markov chain and optimal control solved by Pontryagin’s Minimum Principle for a fuel cell/supercapacitor vehicle

    International Nuclear Information System (INIS)

    Hemi, Hanane; Ghouili, Jamel; Cheriti, Ahmed

    2015-01-01

    Highlights: • A combination of Markov chain and an optimal control solved by Pontryagin’s Minimum Principle is presented. • This strategy is applied to hybrid electric vehicle dynamic model. • The hydrogen consumption is analyzed for two different vehicle mass and drive cycle. • The supercapacitor and fuel cell behavior is analyzed at high or sudden required power. - Abstract: In this article, a real time optimal control strategy based on Pontryagin’s Minimum Principle (PMP) combined with the Markov chain approach is used for a fuel cell/supercapacitor electrical vehicle. In real time, at high power and at high speed, two phenomena are observed. The first is obtained at higher required power, and the second is observed at sudden power demand. To avoid these situations, the Markov chain model is proposed to predict the future power demand during a driving cycle. The optimal control problem is formulated as an equivalent consumption minimization strategy (ECMS), that has to be solved by using the Pontryagin’s Minimum Principle. A Markov chain model is added as a separate block for a prediction of required power. This approach and the whole system are modeled and implemented using the MATLAB/Simulink. The model without Markov chain block and the model is with it are compared. The results presented demonstrate the importance of a Markov chain block added to a model

  14. Speed Variance and Its Influence on Accidents.

    Science.gov (United States)

    Garber, Nicholas J.; Gadirau, Ravi

    A study was conducted to investigate the traffic engineering factors that influence speed variance and to determine to what extent speed variance affects accident rates. Detailed analyses were carried out to relate speed variance with posted speed limit, design speeds, and other traffic variables. The major factor identified was the difference…

  15. 42 CFR 422.382 - Minimum net worth amount.

    Science.gov (United States)

    2010-10-01

    ... that CMS considers appropriate to reduce, control or eliminate start-up administrative costs. (b) After... section. (c) Calculation of the minimum net worth amount—(1) Cash requirement. (i) At the time of application, the organization must maintain at least $750,000 of the minimum net worth amount in cash or cash...

  16. Chaos control of the brushless direct current motor using adaptive dynamic surface control based on neural network with the minimum weights

    International Nuclear Information System (INIS)

    Luo, Shaohua; Wu, Songli; Gao, Ruizhen

    2015-01-01

    This paper investigates chaos control for the brushless DC motor (BLDCM) system by adaptive dynamic surface approach based on neural network with the minimum weights. The BLDCM system contains parameter perturbation, chaotic behavior, and uncertainty. With the help of radial basis function (RBF) neural network to approximate the unknown nonlinear functions, the adaptive law is established to overcome uncertainty of the control gain. By introducing the RBF neural network and adaptive technology into the dynamic surface control design, a robust chaos control scheme is developed. It is proved that the proposed control approach can guarantee that all signals in the closed-loop system are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation results are provided to show that the proposed approach works well in suppressing chaos and parameter perturbation

  17. Chaos control of the brushless direct current motor using adaptive dynamic surface control based on neural network with the minimum weights.

    Science.gov (United States)

    Luo, Shaohua; Wu, Songli; Gao, Ruizhen

    2015-07-01

    This paper investigates chaos control for the brushless DC motor (BLDCM) system by adaptive dynamic surface approach based on neural network with the minimum weights. The BLDCM system contains parameter perturbation, chaotic behavior, and uncertainty. With the help of radial basis function (RBF) neural network to approximate the unknown nonlinear functions, the adaptive law is established to overcome uncertainty of the control gain. By introducing the RBF neural network and adaptive technology into the dynamic surface control design, a robust chaos control scheme is developed. It is proved that the proposed control approach can guarantee that all signals in the closed-loop system are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation results are provided to show that the proposed approach works well in suppressing chaos and parameter perturbation.

  18. MINIMUM VARIANCE BETA ESTIMATION WITH DYNAMIC CONSTRAINTS,

    Science.gov (United States)

    developed (at AFETR ) and is being used to isolate the primary error sources in the beta estimation task. This computer program is additionally used to...determine what success in beta estimation can be achieved with foreseeable instrumentation accuracies. Results are included that illustrate the effects on

  19. Volatility and variance swaps : A comparison of quantitative models to calculate the fair volatility and variance strike

    OpenAIRE

    Röring, Johan

    2017-01-01

    Volatility is a common risk measure in the field of finance that describes the magnitude of an asset’s up and down movement. From only being a risk measure, volatility has become an asset class of its own and volatility derivatives enable traders to get an isolated exposure to an asset’s volatility. Two kinds of volatility derivatives are volatility swaps and variance swaps. The problem with volatility swaps and variance swaps is that they require estimations of the future variance and volati...

  20. Local variances in biomonitoring

    International Nuclear Information System (INIS)

    Wolterbeek, H.T.

    1999-01-01

    The present study deals with the (larger-scaled) biomonitoring survey and specifically focuses on the sampling site. In most surveys, the sampling site is simply selected or defined as a spot of (geographical) dimensions which is small relative to the dimensions of the total survey area. Implicitly it is assumed that the sampling site is essentially homogeneous with respect to the investigated variation in survey parameters. As such, the sampling site is mostly regarded as 'the basic unit' of the survey. As a logical consequence, the local (sampling site) variance should also be seen as a basic and important characteristic of the survey. During the study, work is carried out to gain more knowledge of the local variance. Multiple sampling is carried out at a specific site (tree bark, mosses, soils), multi-elemental analyses are carried out by NAA, and local variances are investigated by conventional statistics, factor analytical techniques, and bootstrapping. Consequences of the outcomes are discussed in the context of sampling, sample handling and survey quality. (author)

  1. Heritable Environmental Variance Causes Nonlinear Relationships Between Traits: Application to Birth Weight and Stillbirth of Pigs

    NARCIS (Netherlands)

    Mulder, H.A.; Hill, W.G.; Knol, E.F.

    2015-01-01

    There is recent evidence from laboratory experiments and analysis of livestock populations that not only the phenotype itself, but also its environmental variance, is under genetic control. Little is known about the relationships between the environmental variance of one trait and mean levels of

  2. Dynamic Mean-Variance Asset Allocation

    OpenAIRE

    Basak, Suleyman; Chabakauri, Georgy

    2009-01-01

    Mean-variance criteria remain prevalent in multi-period problems, and yet not much is known about their dynamically optimal policies. We provide a fully analytical characterization of the optimal dynamic mean-variance portfolios within a general incomplete-market economy, and recover a simple structure that also inherits several conventional properties of static models. We also identify a probability measure that incorporates intertemporal hedging demands and facilitates much tractability in ...

  3. A Random Parameter Model for Continuous-Time Mean-Variance Asset-Liability Management

    Directory of Open Access Journals (Sweden)

    Hui-qiang Ma

    2015-01-01

    Full Text Available We consider a continuous-time mean-variance asset-liability management problem in a market with random market parameters; that is, interest rate, appreciation rates, and volatility rates are considered to be stochastic processes. By using the theories of stochastic linear-quadratic (LQ optimal control and backward stochastic differential equations (BSDEs, we tackle this problem and derive optimal investment strategies as well as the mean-variance efficient frontier analytically in terms of the solution of BSDEs. We find that the efficient frontier is still a parabola in a market with random parameters. Comparing with the existing results, we also find that the liability does not affect the feasibility of the mean-variance portfolio selection problem. However, in an incomplete market with random parameters, the liability can not be fully hedged.

  4. The Variance Composition of Firm Growth Rates

    Directory of Open Access Journals (Sweden)

    Luiz Artur Ledur Brito

    2009-04-01

    Full Text Available Firms exhibit a wide variability in growth rates. This can be seen as another manifestation of the fact that firms are different from one another in several respects. This study investigated this variability using the variance components technique previously used to decompose the variance of financial performance. The main source of variation in growth rates, responsible for more than 40% of total variance, corresponds to individual, idiosyncratic firm aspects and not to industry, country, or macroeconomic conditions prevailing in specific years. Firm growth, similar to financial performance, is mostly unique to specific firms and not an industry or country related phenomenon. This finding also justifies using growth as an alternative outcome of superior firm resources and as a complementary dimension of competitive advantage. This also links this research with the resource-based view of strategy. Country was the second source of variation with around 10% of total variance. The analysis was done using the Compustat Global database with 80,320 observations, comprising 13,221 companies in 47 countries, covering the years of 1994 to 2002. It also compared the variance structure of growth to the variance structure of financial performance in the same sample.

  5. MSEBAG: a dynamic classifier ensemble generation based on `minimum-sufficient ensemble' and bagging

    Science.gov (United States)

    Chen, Lei; Kamel, Mohamed S.

    2016-01-01

    In this paper, we propose a dynamic classifier system, MSEBAG, which is characterised by searching for the 'minimum-sufficient ensemble' and bagging at the ensemble level. It adopts an 'over-generation and selection' strategy and aims to achieve a good bias-variance trade-off. In the training phase, MSEBAG first searches for the 'minimum-sufficient ensemble', which maximises the in-sample fitness with the minimal number of base classifiers. Then, starting from the 'minimum-sufficient ensemble', a backward stepwise algorithm is employed to generate a collection of ensembles. The objective is to create a collection of ensembles with a descending fitness on the data, as well as a descending complexity in the structure. MSEBAG dynamically selects the ensembles from the collection for the decision aggregation. The extended adaptive aggregation (EAA) approach, a bagging-style algorithm performed at the ensemble level, is employed for this task. EAA searches for the competent ensembles using a score function, which takes into consideration both the in-sample fitness and the confidence of the statistical inference, and averages the decisions of the selected ensembles to label the test pattern. The experimental results show that the proposed MSEBAG outperforms the benchmarks on average.

  6. Robust Means Modeling: An Alternative for Hypothesis Testing of Independent Means under Variance Heterogeneity and Nonnormality

    Science.gov (United States)

    Fan, Weihua; Hancock, Gregory R.

    2012-01-01

    This study proposes robust means modeling (RMM) approaches for hypothesis testing of mean differences for between-subjects designs in order to control the biasing effects of nonnormality and variance inequality. Drawing from structural equation modeling (SEM), the RMM approaches make no assumption of variance homogeneity and employ robust…

  7. Experimental evaluation of the MIT-SNL period-generated minimum time control laws for the rapid adjustment of reactor power

    International Nuclear Information System (INIS)

    Bernard, J.A.; Kwok, K.S.; Menadier, P.T.; Thome, F.V.; Wyant, F.J.

    1987-01-01

    The rapid adjustment of reactor neutronic power has recently been achieved by developing control laws that determine the actuator mechanism velocity necessary to produce a specified reactor period. Designated as the 'MIT-SNL Period-Generated Minimum Time Control Laws,' these relations are closed-form expressions of general applicability. In particular, if there is no limitation on the available rate of change of reactivity, these laws can be used to achieve virtually any desired power profile including time optimal ones. The innovative aspect of these laws is that the rate of change of reactivity rather than the reactivity itself is used as the control signal. For example, relative to a time-optimal response, these laws function by altering the rate of change of reactivity so that the instantaneous period is stepped from infinity to its minimum allowed value, held at that value until the desired power level is attained, and then stepped back to infinity. The response is time-optimal because the power adjustment is continuously made at the maximum allowed rate

  8. Estimating the encounter rate variance in distance sampling

    Science.gov (United States)

    Fewster, R.M.; Buckland, S.T.; Burnham, K.P.; Borchers, D.L.; Jupp, P.E.; Laake, J.L.; Thomas, L.

    2009-01-01

    The dominant source of variance in line transect sampling is usually the encounter rate variance. Systematic survey designs are often used to reduce the true variability among different realizations of the design, but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines. We explore the properties of different encounter rate variance estimators under random and systematic designs. We show that a design-based variance estimator improves upon the model-based estimator of Buckland et al. (2001, Introduction to Distance Sampling. Oxford: Oxford University Press, p. 79) when transects are positioned at random. However, if populations exhibit strong spatial trends, both estimators can have substantial positive bias under systematic designs. We show that poststratification is effective in reducing this bias. ?? 2008, The International Biometric Society.

  9. Towards the ultimate variance-conserving convection scheme

    International Nuclear Information System (INIS)

    Os, J.J.A.M. van; Uittenbogaard, R.E.

    2004-01-01

    In the past various arguments have been used for applying kinetic energy-conserving advection schemes in numerical simulations of incompressible fluid flows. One argument is obeying the programmed dissipation by viscous stresses or by sub-grid stresses in Direct Numerical Simulation and Large Eddy Simulation, see e.g. [Phys. Fluids A 3 (7) (1991) 1766]. Another argument is that, according to e.g. [J. Comput. Phys. 6 (1970) 392; 1 (1966) 119], energy-conserving convection schemes are more stable i.e. by prohibiting a spurious blow-up of volume-integrated energy in a closed volume without external energy sources. In the above-mentioned references it is stated that nonlinear instability is due to spatial truncation rather than to time truncation and therefore these papers are mainly concerned with the spatial integration. In this paper we demonstrate that discretized temporal integration of a spatially variance-conserving convection scheme can induce non-energy conserving solutions. In this paper the conservation of the variance of a scalar property is taken as a simple model for the conservation of kinetic energy. In addition, the derivation and testing of a variance-conserving scheme allows for a clear definition of kinetic energy-conserving advection schemes for solving the Navier-Stokes equations. Consequently, we first derive and test a strictly variance-conserving space-time discretization for the convection term in the convection-diffusion equation. Our starting point is the variance-conserving spatial discretization of the convection operator presented by Piacsek and Williams [J. Comput. Phys. 6 (1970) 392]. In terms of its conservation properties, our variance-conserving scheme is compared to other spatially variance-conserving schemes as well as with the non-variance-conserving schemes applied in our shallow-water solver, see e.g. [Direct and Large-eddy Simulation Workshop IV, ERCOFTAC Series, Kluwer Academic Publishers, 2001, pp. 409-287

  10. Controlling spark timing for consecutive cycles to reduce the cyclic variations of SI engines

    International Nuclear Information System (INIS)

    Kaleli, Alirıza; Ceviz, Mehmet Akif; Erenturk, Köksal

    2015-01-01

    Minimization of the cyclic variations is one of the most important design goal for spark-ignited engines. Primary motivation of this study is to reduce the cyclic variations in spark ignition engines by controlling the spark timing for consecutive cycles. A stochastic model was performed between spark timing and in–cylinder maximum pressure by using the system identification techniques. The incylinder maximum pressure of the next cycle was predicted with this model. Minimum variance and generalized minimum variance controllers were designed to regulate the in–cylinder maximum pressure by changing the spark timing for consecutive cycles of the test engine. The produced control algorithms were built in LabView environment and installed to the Field Programmable Gate Arrays (FPGA) chassis. According to the test results, the in–cylinder maximum pressure of the next pressure cycle can be predicted fairly well, and the spark timing can be regulated to keep the in–cylinder maximum pressure in a desired band to reduce the cyclic variations. At fixed spark timing experiments, the COV Pmax and COV imep were 3.764 and 0.677%, whereas they decreased to 3.208 and 0.533% when GMV controller was applied, respectively. - Highlights: • Cycle per cycle spark timing control was carried out. • A stochastic process model was described between P max and the spark timing. • The cyclic variations in P max was decreased by keeping it in a desired band. • Different controllers were used to adjust spark timing signal of the next cycle. • COV Pmax was decreased by about 15% by using GMV controller

  11. Discrete and continuous time dynamic mean-variance analysis

    OpenAIRE

    Reiss, Ariane

    1999-01-01

    Contrary to static mean-variance analysis, very few papers have dealt with dynamic mean-variance analysis. Here, the mean-variance efficient self-financing portfolio strategy is derived for n risky assets in discrete and continuous time. In the discrete setting, the resulting portfolio is mean-variance efficient in a dynamic sense. It is shown that the optimal strategy for n risky assets may be dominated if the expected terminal wealth is constrained to exactly attain a certain goal instead o...

  12. Nonlinear Epigenetic Variance: Review and Simulations

    Science.gov (United States)

    Kan, Kees-Jan; Ploeger, Annemie; Raijmakers, Maartje E. J.; Dolan, Conor V.; van Der Maas, Han L. J.

    2010-01-01

    We present a review of empirical evidence that suggests that a substantial portion of phenotypic variance is due to nonlinear (epigenetic) processes during ontogenesis. The role of such processes as a source of phenotypic variance in human behaviour genetic studies is not fully appreciated. In addition to our review, we present simulation studies…

  13. Revision: Variance Inflation in Regression

    Directory of Open Access Journals (Sweden)

    D. R. Jensen

    2013-01-01

    the intercept; and (iv variance deflation may occur, where ill-conditioned data yield smaller variances than their orthogonal surrogates. Conventional VIFs have all regressors linked, or none, often untenable in practice. Beyond these, our models enable the unlinking of regressors that can be unlinked, while preserving dependence among those intrinsically linked. Moreover, known collinearity indices are extended to encompass angles between subspaces of regressors. To reaccess ill-conditioned data, we consider case studies ranging from elementary examples to data from the literature.

  14. Variance estimation for generalized Cavalieri estimators

    OpenAIRE

    Johanna Ziegel; Eva B. Vedel Jensen; Karl-Anton Dorph-Petersen

    2011-01-01

    The precision of stereological estimators based on systematic sampling is of great practical importance. This paper presents methods of data-based variance estimation for generalized Cavalieri estimators where errors in sampling positions may occur. Variance estimators are derived under perturbed systematic sampling, systematic sampling with cumulative errors and systematic sampling with random dropouts. Copyright 2011, Oxford University Press.

  15. Influence of Family Structure on Variance Decomposition

    DEFF Research Database (Denmark)

    Edwards, Stefan McKinnon; Sarup, Pernille Merete; Sørensen, Peter

    Partitioning genetic variance by sets of randomly sampled genes for complex traits in D. melanogaster and B. taurus, has revealed that population structure can affect variance decomposition. In fruit flies, we found that a high likelihood ratio is correlated with a high proportion of explained ge...... capturing pure noise. Therefore it is necessary to use both criteria, high likelihood ratio in favor of a more complex genetic model and proportion of genetic variance explained, to identify biologically important gene groups...

  16. Multiperiod Mean-Variance Portfolio Optimization via Market Cloning

    International Nuclear Information System (INIS)

    Ankirchner, Stefan; Dermoune, Azzouz

    2011-01-01

    The problem of finding the mean variance optimal portfolio in a multiperiod model can not be solved directly by means of dynamic programming. In order to find a solution we therefore first introduce independent market clones having the same distributional properties as the original market, and we replace the portfolio mean and variance by their empirical counterparts. We then use dynamic programming to derive portfolios maximizing a weighted sum of the empirical mean and variance. By letting the number of market clones converge to infinity we are able to solve the original mean variance problem.

  17. Multiperiod Mean-Variance Portfolio Optimization via Market Cloning

    Energy Technology Data Exchange (ETDEWEB)

    Ankirchner, Stefan, E-mail: ankirchner@hcm.uni-bonn.de [Rheinische Friedrich-Wilhelms-Universitaet Bonn, Institut fuer Angewandte Mathematik, Hausdorff Center for Mathematics (Germany); Dermoune, Azzouz, E-mail: Azzouz.Dermoune@math.univ-lille1.fr [Universite des Sciences et Technologies de Lille, Laboratoire Paul Painleve UMR CNRS 8524 (France)

    2011-08-15

    The problem of finding the mean variance optimal portfolio in a multiperiod model can not be solved directly by means of dynamic programming. In order to find a solution we therefore first introduce independent market clones having the same distributional properties as the original market, and we replace the portfolio mean and variance by their empirical counterparts. We then use dynamic programming to derive portfolios maximizing a weighted sum of the empirical mean and variance. By letting the number of market clones converge to infinity we are able to solve the original mean variance problem.

  18. Kinematic feedback control laws for generating natural arm movements

    International Nuclear Information System (INIS)

    Kim, Donghyun; Jang, Cheongjae; Park, Frank C

    2014-01-01

    We propose a stochastic optimal feedback control law for generating natural robot arm motions. Our approach, inspired by the minimum variance principle of Harris and Wolpert (1998 Nature 394 780–4) and the optimal feedback control principles put forth by Todorov and Jordan (2002 Nature Neurosci. 5 1226–35) for explaining human movements, differs in two crucial respects: (i) the endpoint variance is minimized in joint space rather than Cartesian hand space, and (ii) we ignore the dynamics and instead consider only the second-order differential kinematics. The feedback control law generating the motions can be straightforwardly obtained by backward integration of a set of ordinary differential equations; these equations are obtained exactly, without any linear–quadratic approximations. The only parameters to be determined a priori are the variance scale factors, and for both the two-DOF planar arm and the seven-DOF spatial arm, a table of values is constructed based on the given initial and final arm configurations; these values are determined via an optimal fitting procedure, and consistent with existing findings about neuromuscular motor noise levels of human arm muscles. Experiments conducted with a two-link planar arm and a seven-DOF spatial arm verify that the trajectories generated by our feedback control law closely resemble human arm motions, in the sense of producing nearly straight-line hand trajectories, having bell-shaped velocity profiles, and satisfying Fitts Law. (paper)

  19. Why risk is not variance: an expository note.

    Science.gov (United States)

    Cox, Louis Anthony Tony

    2008-08-01

    Variance (or standard deviation) of return is widely used as a measure of risk in financial investment risk analysis applications, where mean-variance analysis is applied to calculate efficient frontiers and undominated portfolios. Why, then, do health, safety, and environmental (HS&E) and reliability engineering risk analysts insist on defining risk more flexibly, as being determined by probabilities and consequences, rather than simply by variances? This note suggests an answer by providing a simple proof that mean-variance decision making violates the principle that a rational decisionmaker should prefer higher to lower probabilities of receiving a fixed gain, all else being equal. Indeed, simply hypothesizing a continuous increasing indifference curve for mean-variance combinations at the origin is enough to imply that a decisionmaker must find unacceptable some prospects that offer a positive probability of gain and zero probability of loss. Unlike some previous analyses of limitations of variance as a risk metric, this expository note uses only simple mathematics and does not require the additional framework of von Neumann Morgenstern utility theory.

  20. Association analysis using next-generation sequence data from publicly available control groups: the robust variance score statistic.

    Science.gov (United States)

    Derkach, Andriy; Chiang, Theodore; Gong, Jiafen; Addis, Laura; Dobbins, Sara; Tomlinson, Ian; Houlston, Richard; Pal, Deb K; Strug, Lisa J

    2014-08-01

    Sufficiently powered case-control studies with next-generation sequence (NGS) data remain prohibitively expensive for many investigators. If feasible, a more efficient strategy would be to include publicly available sequenced controls. However, these studies can be confounded by differences in sequencing platform; alignment, single nucleotide polymorphism and variant calling algorithms; read depth; and selection thresholds. Assuming one can match cases and controls on the basis of ethnicity and other potential confounding factors, and one has access to the aligned reads in both groups, we investigate the effect of systematic differences in read depth and selection threshold when comparing allele frequencies between cases and controls. We propose a novel likelihood-based method, the robust variance score (RVS), that substitutes genotype calls by their expected values given observed sequence data. We show theoretically that the RVS eliminates read depth bias in the estimation of minor allele frequency. We also demonstrate that, using simulated and real NGS data, the RVS method controls Type I error and has comparable power to the 'gold standard' analysis with the true underlying genotypes for both common and rare variants. An RVS R script and instructions can be found at strug.research.sickkids.ca, and at https://github.com/strug-lab/RVS. lisa.strug@utoronto.ca Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  1. Protocol for the verification of minimum criteria

    International Nuclear Information System (INIS)

    Gaggiano, M.; Spiccia, P.; Gaetano Arnetta, P.

    2014-01-01

    This Protocol has been prepared with reference to the provisions of article 8 of the Legislative Decree of May 26, 2000 No. 187. Quality controls of radiological equipment fit within the larger 'quality assurance Program' and are intended to ensure the correct operation of the same and the maintenance of that State. The pursuit of this objective guarantees that the radiological equipment subjected to those controls also meets the minimum criteria of acceptability set out in annex V of the aforementioned legislative decree establishing the conditions necessary to allow the functions to which each radiological equipment was designed, built and for which it is used. The Protocol is established for the purpose of quality control of radiological equipment of Cone Beam Computer Tomography type and reference document, in the sense that compliance with stated tolerances also ensures the subsistence minimum acceptability requirements, where applicable.

  2. Variance bias analysis for the Gelbard's batch method

    Energy Technology Data Exchange (ETDEWEB)

    Seo, Jae Uk; Shim, Hyung Jin [Seoul National Univ., Seoul (Korea, Republic of)

    2014-05-15

    In this paper, variances and the bias will be derived analytically when the Gelbard's batch method is applied. And then, the real variance estimated from this bias will be compared with the real variance calculated from replicas. Variance and the bias were derived analytically when the batch method was applied. If the batch method was applied to calculate the sample variance, covariance terms between tallies which exist in the batch were eliminated from the bias. With the 2 by 2 fission matrix problem, we could calculate real variance regardless of whether or not the batch method was applied. However as batch size got larger, standard deviation of real variance was increased. When we perform a Monte Carlo estimation, we could get a sample variance as the statistical uncertainty of it. However, this value is smaller than the real variance of it because a sample variance is biased. To reduce this bias, Gelbard devised the method which is called the Gelbard's batch method. It has been certificated that a sample variance get closer to the real variance when the batch method is applied. In other words, the bias get reduced. This fact is well known to everyone in the MC field. However, so far, no one has given the analytical interpretation on it.

  3. Reduced Variance of Gene Expression at Numerous Loci in a Population of Chickens Selected for High Feather Pecking

    DEFF Research Database (Denmark)

    Hughes, A L; Buitenhuis, A J

    2010-01-01

    among populations with respect to mean expression scores, but numerous transcripts showed reduced variance in expression scores in the high FP population in comparison to control and low FP populations. The reduction in variance in the high FP population generally involved transcripts whose expression...

  4. Variance of indoor radon concentration: Major influencing factors

    Energy Technology Data Exchange (ETDEWEB)

    Yarmoshenko, I., E-mail: ivy@ecko.uran.ru [Institute of Industrial Ecology UB RAS, Sophy Kovalevskoy, 20, Ekaterinburg (Russian Federation); Vasilyev, A.; Malinovsky, G. [Institute of Industrial Ecology UB RAS, Sophy Kovalevskoy, 20, Ekaterinburg (Russian Federation); Bossew, P. [German Federal Office for Radiation Protection (BfS), Berlin (Germany); Žunić, Z.S. [Institute of Nuclear Sciences “Vinca”, University of Belgrade (Serbia); Onischenko, A.; Zhukovsky, M. [Institute of Industrial Ecology UB RAS, Sophy Kovalevskoy, 20, Ekaterinburg (Russian Federation)

    2016-01-15

    Variance of radon concentration in dwelling atmosphere is analysed with regard to geogenic and anthropogenic influencing factors. Analysis includes review of 81 national and regional indoor radon surveys with varying sampling pattern, sample size and duration of measurements and detailed consideration of two regional surveys (Sverdlovsk oblast, Russia and Niška Banja, Serbia). The analysis of the geometric standard deviation revealed that main factors influencing the dispersion of indoor radon concentration over the territory are as follows: area of territory, sample size, characteristics of measurements technique, the radon geogenic potential, building construction characteristics and living habits. As shown for Sverdlovsk oblast and Niška Banja town the dispersion as quantified by GSD is reduced by restricting to certain levels of control factors. Application of the developed approach to characterization of the world population radon exposure is discussed. - Highlights: • Influence of lithosphere and anthroposphere on variance of indoor radon is found. • Level-by-level analysis reduces GSD by a factor of 1.9. • Worldwide GSD is underestimated.

  5. Integrating Variances into an Analytical Database

    Science.gov (United States)

    Sanchez, Carlos

    2010-01-01

    For this project, I enrolled in numerous SATERN courses that taught the basics of database programming. These include: Basic Access 2007 Forms, Introduction to Database Systems, Overview of Database Design, and others. My main job was to create an analytical database that can handle many stored forms and make it easy to interpret and organize. Additionally, I helped improve an existing database and populate it with information. These databases were designed to be used with data from Safety Variances and DCR forms. The research consisted of analyzing the database and comparing the data to find out which entries were repeated the most. If an entry happened to be repeated several times in the database, that would mean that the rule or requirement targeted by that variance has been bypassed many times already and so the requirement may not really be needed, but rather should be changed to allow the variance's conditions permanently. This project did not only restrict itself to the design and development of the database system, but also worked on exporting the data from the database to a different format (e.g. Excel or Word) so it could be analyzed in a simpler fashion. Thanks to the change in format, the data was organized in a spreadsheet that made it possible to sort the data by categories or types and helped speed up searches. Once my work with the database was done, the records of variances could be arranged so that they were displayed in numerical order, or one could search for a specific document targeted by the variances and restrict the search to only include variances that modified a specific requirement. A great part that contributed to my learning was SATERN, NASA's resource for education. Thanks to the SATERN online courses I took over the summer, I was able to learn many new things about computers and databases and also go more in depth into topics I already knew about.

  6. Regional sensitivity analysis using revised mean and variance ratio functions

    International Nuclear Information System (INIS)

    Wei, Pengfei; Lu, Zhenzhou; Ruan, Wenbin; Song, Jingwen

    2014-01-01

    The variance ratio function, derived from the contribution to sample variance (CSV) plot, is a regional sensitivity index for studying how much the output deviates from the original mean of model output when the distribution range of one input is reduced and to measure the contribution of different distribution ranges of each input to the variance of model output. In this paper, the revised mean and variance ratio functions are developed for quantifying the actual change of the model output mean and variance, respectively, when one reduces the range of one input. The connection between the revised variance ratio function and the original one is derived and discussed. It is shown that compared with the classical variance ratio function, the revised one is more suitable to the evaluation of model output variance due to reduced ranges of model inputs. A Monte Carlo procedure, which needs only a set of samples for implementing it, is developed for efficiently computing the revised mean and variance ratio functions. The revised mean and variance ratio functions are compared with the classical ones by using the Ishigami function. At last, they are applied to a planar 10-bar structure

  7. Argentine Population Genetic Structure: Large Variance in Amerindian Contribution

    Science.gov (United States)

    Seldin, Michael F.; Tian, Chao; Shigeta, Russell; Scherbarth, Hugo R.; Silva, Gabriel; Belmont, John W.; Kittles, Rick; Gamron, Susana; Allevi, Alberto; Palatnik, Simon A.; Alvarellos, Alejandro; Paira, Sergio; Caprarulo, Cesar; Guillerón, Carolina; Catoggio, Luis J.; Prigione, Cristina; Berbotto, Guillermo A.; García, Mercedes A.; Perandones, Carlos E.; Pons-Estel, Bernardo A.; Alarcon-Riquelme, Marta E.

    2011-01-01

    Argentine population genetic structure was examined using a set of 78 ancestry informative markers (AIMs) to assess the contributions of European, Amerindian, and African ancestry in 94 individuals members of this population. Using the Bayesian clustering algorithm STRUCTURE, the mean European contribution was 78%, the Amerindian contribution was 19.4%, and the African contribution was 2.5%. Similar results were found using weighted least mean square method: European, 80.2%; Amerindian, 18.1%; and African, 1.7%. Consistent with previous studies the current results showed very few individuals (four of 94) with greater than 10% African admixture. Notably, when individual admixture was examined, the Amerindian and European admixture showed a very large variance and individual Amerindian contribution ranged from 1.5 to 84.5% in the 94 individual Argentine subjects. These results indicate that admixture must be considered when clinical epidemiology or case control genetic analyses are studied in this population. Moreover, the current study provides a set of informative SNPs that can be used to ascertain or control for this potentially hidden stratification. In addition, the large variance in admixture proportions in individual Argentine subjects shown by this study suggests that this population is appropriate for future admixture mapping studies. PMID:17177183

  8. The genotype-environment interaction variance in rice-seed protein determination

    International Nuclear Information System (INIS)

    Ismachin, M.

    1976-01-01

    Many environmental factors influence the protein content of cereal seed. This fact procured difficulties in breeding for protein. Yield is another example on which so many environmental factors are of influence. The length of time required by the plant to reach maturity, is also affected by the environmental factors; even though its effect is not too decisive. In this investigation the genotypic variance and the genotype-environment interaction variance which contribute to the total variance or phenotypic variance was analysed, with purpose to give an idea to the breeder how selection should be made. It was found that genotype-environment interaction variance is larger than the genotypic variance in contribution to total variance of protein-seed determination or yield. In the analysis of the time required to reach maturity it was found that genotypic variance is larger than the genotype-environment interaction variance. It is therefore clear, why selection for time required to reach maturity is much easier than selection for protein or yield. Selected protein in one location may be different from that to other locations. (author)

  9. Additive genetic variance in polyandry enables its evolution, but polyandry is unlikely to evolve through sexy or good sperm processes.

    Science.gov (United States)

    Travers, L M; Simmons, L W; Garcia-Gonzalez, F

    2016-05-01

    Polyandry is widespread despite its costs. The sexually selected sperm hypotheses ('sexy' and 'good' sperm) posit that sperm competition plays a role in the evolution of polyandry. Two poorly studied assumptions of these hypotheses are the presence of additive genetic variance in polyandry and sperm competitiveness. Using a quantitative genetic breeding design in a natural population of Drosophila melanogaster, we first established the potential for polyandry to respond to selection. We then investigated whether polyandry can evolve through sexually selected sperm processes. We measured lifetime polyandry and offensive sperm competitiveness (P2 ) while controlling for sampling variance due to male × male × female interactions. We also measured additive genetic variance in egg-to-adult viability and controlled for its effect on P2 estimates. Female lifetime polyandry showed significant and substantial additive genetic variance and evolvability. In contrast, we found little genetic variance or evolvability in P2 or egg-to-adult viability. Additive genetic variance in polyandry highlights its potential to respond to selection. However, the low levels of genetic variance in sperm competitiveness suggest that the evolution of polyandry may not be driven by sexy sperm or good sperm processes. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

  10. Estimation of measurement variances

    International Nuclear Information System (INIS)

    Jaech, J.L.

    1984-01-01

    The estimation of measurement error parameters in safeguards systems is discussed. Both systematic and random errors are considered. A simple analysis of variances to characterize the measurement error structure with biases varying over time is presented

  11. Model-based Acceleration Control of Turbofan Engines with a Hammerstein-Wiener Representation

    Science.gov (United States)

    Wang, Jiqiang; Ye, Zhifeng; Hu, Zhongzhi; Wu, Xin; Dimirovsky, Georgi; Yue, Hong

    2017-05-01

    Acceleration control of turbofan engines is conventionally designed through either schedule-based or acceleration-based approach. With the widespread acceptance of model-based design in aviation industry, it becomes necessary to investigate the issues associated with model-based design for acceleration control. In this paper, the challenges for implementing model-based acceleration control are explained; a novel Hammerstein-Wiener representation of engine models is introduced; based on the Hammerstein-Wiener model, a nonlinear generalized minimum variance type of optimal control law is derived; the feature of the proposed approach is that it does not require the inversion operation that usually upsets those nonlinear control techniques. The effectiveness of the proposed control design method is validated through a detailed numerical study.

  12. 29 CFR 1905.5 - Effect of variances.

    Science.gov (United States)

    2010-07-01

    ...-STEIGER OCCUPATIONAL SAFETY AND HEALTH ACT OF 1970 General § 1905.5 Effect of variances. All variances... Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR... concerning a proposed penalty or period of abatement is pending before the Occupational Safety and Health...

  13. Realized range-based estimation of integrated variance

    DEFF Research Database (Denmark)

    Christensen, Kim; Podolskij, Mark

    2007-01-01

    We provide a set of probabilistic laws for estimating the quadratic variation of continuous semimartingales with the realized range-based variance-a statistic that replaces every squared return of the realized variance with a normalized squared range. If the entire sample path of the process is a...

  14. Control of minimum member size in parameter-free structural shape optimization by a medial axis approximation

    Science.gov (United States)

    Schmitt, Oliver; Steinmann, Paul

    2017-09-01

    We introduce a manufacturing constraint for controlling the minimum member size in structural shape optimization problems, which is for example of interest for components fabricated in a molding process. In a parameter-free approach, whereby the coordinates of the FE boundary nodes are used as design variables, the challenging task is to find a generally valid definition for the thickness of non-parametric geometries in terms of their boundary nodes. Therefore we use the medial axis, which is the union of all points with at least two closest points on the boundary of the domain. Since the effort for the exact computation of the medial axis of geometries given by their FE discretization highly increases with the number of surface elements we use the distance function instead to approximate the medial axis by a cloud of points. The approximation is demonstrated on three 2D examples. Moreover, the formulation of a minimum thickness constraint is applied to a sensitivity-based shape optimization problem of one 2D and one 3D model.

  15. Variance Function Partially Linear Single-Index Models1.

    Science.gov (United States)

    Lian, Heng; Liang, Hua; Carroll, Raymond J

    2015-01-01

    We consider heteroscedastic regression models where the mean function is a partially linear single index model and the variance function depends upon a generalized partially linear single index model. We do not insist that the variance function depend only upon the mean function, as happens in the classical generalized partially linear single index model. We develop efficient and practical estimation methods for the variance function and for the mean function. Asymptotic theory for the parametric and nonparametric parts of the model is developed. Simulations illustrate the results. An empirical example involving ozone levels is used to further illustrate the results, and is shown to be a case where the variance function does not depend upon the mean function.

  16. Optimal coordination and control of posture and movements.

    Science.gov (United States)

    Johansson, Rolf; Fransson, Per-Anders; Magnusson, Måns

    2009-01-01

    This paper presents a theoretical model of stability and coordination of posture and locomotion, together with algorithms for continuous-time quadratic optimization of motion control. Explicit solutions to the Hamilton-Jacobi equation for optimal control of rigid-body motion are obtained by solving an algebraic matrix equation. The stability is investigated with Lyapunov function theory and it is shown that global asymptotic stability holds. It is also shown how optimal control and adaptive control may act in concert in the case of unknown or uncertain system parameters. The solution describes motion strategies of minimum effort and variance. The proposed optimal control is formulated to be suitable as a posture and movement model for experimental validation and verification. The combination of adaptive and optimal control makes this algorithm a candidate for coordination and control of functional neuromuscular stimulation as well as of prostheses. Validation examples with experimental data are provided.

  17. Discrete time and continuous time dynamic mean-variance analysis

    OpenAIRE

    Reiss, Ariane

    1999-01-01

    Contrary to static mean-variance analysis, very few papers have dealt with dynamic mean-variance analysis. Here, the mean-variance efficient self-financing portfolio strategy is derived for n risky assets in discrete and continuous time. In the discrete setting, the resulting portfolio is mean-variance efficient in a dynamic sense. It is shown that the optimal strategy for n risky assets may be dominated if the expected terminal wealth is constrained to exactly attain a certain goal instead o...

  18. Dominance genetic variance for traits under directional selection in Drosophila serrata.

    Science.gov (United States)

    Sztepanacz, Jacqueline L; Blows, Mark W

    2015-05-01

    In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait-fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. Copyright © 2015 by the Genetics Society of America.

  19. Mean-Variance Hedging on Uncertain Time Horizon in a Market with a Jump

    International Nuclear Information System (INIS)

    Kharroubi, Idris; Lim, Thomas; Ngoupeyou, Armand

    2013-01-01

    In this work, we study the problem of mean-variance hedging with a random horizon T∧τ, where T is a deterministic constant and τ is a jump time of the underlying asset price process. We first formulate this problem as a stochastic control problem and relate it to a system of BSDEs with a jump. We then provide a verification theorem which gives the optimal strategy for the mean-variance hedging using the solution of the previous system of BSDEs. Finally, we prove that this system of BSDEs admits a solution via a decomposition approach coming from filtration enlargement theory

  20. Mean-Variance Hedging on Uncertain Time Horizon in a Market with a Jump

    Energy Technology Data Exchange (ETDEWEB)

    Kharroubi, Idris, E-mail: kharroubi@ceremade.dauphine.fr [Université Paris Dauphine, CEREMADE, CNRS UMR 7534 (France); Lim, Thomas, E-mail: lim@ensiie.fr [Université d’Evry and ENSIIE, Laboratoire d’Analyse et Probabilités (France); Ngoupeyou, Armand, E-mail: armand.ngoupeyou@univ-paris-diderot.fr [Université Paris 7, Laboratoire de Probabilités et Modèles Aléatoires (France)

    2013-12-15

    In this work, we study the problem of mean-variance hedging with a random horizon T∧τ, where T is a deterministic constant and τ is a jump time of the underlying asset price process. We first formulate this problem as a stochastic control problem and relate it to a system of BSDEs with a jump. We then provide a verification theorem which gives the optimal strategy for the mean-variance hedging using the solution of the previous system of BSDEs. Finally, we prove that this system of BSDEs admits a solution via a decomposition approach coming from filtration enlargement theory.

  1. CMB-S4 and the hemispherical variance anomaly

    Science.gov (United States)

    O'Dwyer, Márcio; Copi, Craig J.; Knox, Lloyd; Starkman, Glenn D.

    2017-09-01

    Cosmic microwave background (CMB) full-sky temperature data show a hemispherical asymmetry in power nearly aligned with the Ecliptic. In real space, this anomaly can be quantified by the temperature variance in the Northern and Southern Ecliptic hemispheres, with the Northern hemisphere displaying an anomalously low variance while the Southern hemisphere appears unremarkable [consistent with expectations from the best-fitting theory, Lambda Cold Dark Matter (ΛCDM)]. While this is a well-established result in temperature, the low signal-to-noise ratio in current polarization data prevents a similar comparison. This will change with a proposed ground-based CMB experiment, CMB-S4. With that in mind, we generate realizations of polarization maps constrained by the temperature data and predict the distribution of the hemispherical variance in polarization considering two different sky coverage scenarios possible in CMB-S4: full Ecliptic north coverage and just the portion of the North that can be observed from a ground-based telescope at the high Chilean Atacama plateau. We find that even in the set of realizations constrained by the temperature data, the low Northern hemisphere variance observed in temperature is not expected in polarization. Therefore, observing an anomalously low variance in polarization would make the hypothesis that the temperature anomaly is simply a statistical fluke more unlikely and thus increase the motivation for physical explanations. We show, within ΛCDM, how variance measurements in both sky coverage scenarios are related. We find that the variance makes for a good statistic in cases where the sky coverage is limited, however, full northern coverage is still preferable.

  2. Expected Stock Returns and Variance Risk Premia

    DEFF Research Database (Denmark)

    Bollerslev, Tim; Zhou, Hao

    risk premium with the P/E ratio results in an R2 for the quarterly returns of more than twenty-five percent. The results depend crucially on the use of "model-free", as opposed to standard Black-Scholes, implied variances, and realized variances constructed from high-frequency intraday, as opposed...

  3. Allowable variance set on left ventricular function parameter

    International Nuclear Information System (INIS)

    Zhou Li'na; Qi Zhongzhi; Zeng Yu; Ou Xiaohong; Li Lin

    2010-01-01

    Purpose: To evaluate the influence of allowable Variance settings on left ventricular function parameter of the arrhythmia patients during gated myocardial perfusion imaging. Method: 42 patients with evident arrhythmia underwent myocardial perfusion SPECT, 3 different allowable variance with 20%, 60%, 100% would be set before acquisition for every patients,and they will be acquired simultaneously. After reconstruction by Astonish, end-diastole volume(EDV) and end-systolic volume (ESV) and left ventricular ejection fraction (LVEF) would be computed with Quantitative Gated SPECT(QGS). Using SPSS software EDV, ESV, EF values of analysis of variance. Result: there is no statistical difference between three groups. Conclusion: arrhythmia patients undergo Gated myocardial perfusion imaging, Allowable Variance settings on EDV, ESV, EF value does not have a statistical meaning. (authors)

  4. Direct encoding of orientation variance in the visual system.

    Science.gov (United States)

    Norman, Liam J; Heywood, Charles A; Kentridge, Robert W

    2015-01-01

    Our perception of regional irregularity, an example of which is orientation variance, seems effortless when we view two patches of texture that differ in this attribute. Little is understood, however, of how the visual system encodes a regional statistic like orientation variance, but there is some evidence to suggest that it is directly encoded by populations of neurons tuned broadly to high or low levels. The present study shows that selective adaptation to low or high levels of variance results in a perceptual aftereffect that shifts the perceived level of variance of a subsequently viewed texture in the direction away from that of the adapting stimulus (Experiments 1 and 2). Importantly, the effect is durable across changes in mean orientation, suggesting that the encoding of orientation variance is independent of global first moment orientation statistics (i.e., mean orientation). In Experiment 3 it was shown that the variance-specific aftereffect did not show signs of being encoded in a spatiotopic reference frame, similar to the equivalent aftereffect of adaptation to the first moment orientation statistic (the tilt aftereffect), which is represented in the primary visual cortex and exists only in retinotopic coordinates. Experiment 4 shows that a neuropsychological patient with damage to ventral areas of the cortex but spared intact early areas retains sensitivity to orientation variance. Together these results suggest that orientation variance is encoded directly by the visual system and possibly at an early cortical stage.

  5. Network Structure and Biased Variance Estimation in Respondent Driven Sampling.

    Science.gov (United States)

    Verdery, Ashton M; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J

    2015-01-01

    This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network.

  6. Diagnosis of Bearing System using Minimum Variance Cepstrum

    International Nuclear Information System (INIS)

    Lee, Jeong Han; Choi, Young Chul; Park, Jin Ho; Lee, Won Hyung; Kim, Chan Joong

    2005-01-01

    Various bearings are commonly used in rotating machines. The noise and vibration signals that can be obtained from the machines often convey the information of faults and these locations. Monitoring conditions for bearings have received considerable attention for many years, because the majority of problems in rotating machines are caused by faulty bearings. Thus failure alarm for the bearing system is often based on the detection of the onset of localized faults. Many methods are available for detecting faults in the bearing system. The majority of these methods assume that faults in bearings produce impulses. Impulse events can be attributed to bearing faults in the system. McFadden and Smith used the bandpass filter to filter the noise signal and then obtained the envelope by using the envelope detector. D. Ho and R. B Randall also tried envelope spectrum to detect faults in the bearing system, but it is very difficult to find resonant frequency in the noisy environments. S. -K. Lee and P. R. White used improved ANC (adaptive noise cancellation) to find faults. The basic idea of this technique is to remove the noise from the measured vibration signal, but they are not able to show the theoretical foundation of the proposed algorithms. Y.-H. Kim et al. used a moving window. This algorithm is quite powerful in the early detection of faults in a ball bearing system, but it is difficult to decide initial time and step size of the moving window. The early fault signal that is caused by microscopic cracks is commonly embedded in noise. Therefore, the success of detecting fault signal is completely determined by a method's ability to distinguish signal and noise. In 1969, Capon coined maximum likelihood (ML) spectra which estimate a mixed spectrum consisting of line spectrum, corresponding to a deterministic random process, plus arbitrary unknown continuous spectrum. The unique feature of these spectra is that it can detect sinusoidal signal from noise. Our idea essentially comes from this method. In this paper, a technique, which can detect impulse embedded in noise, is introduced. The theory of this technique is derived and the improved ability to detect the faults in a ball bearing system is demonstrated theoretically as well as experimentally

  7. The Variance-covariance Method using IOWGA Operator for Tourism Forecast Combination

    Directory of Open Access Journals (Sweden)

    Liangping Wu

    2014-08-01

    Full Text Available Three combination methods commonly used in tourism forecasting are the simple average method, the variance-covariance method and the discounted MSFE method. These methods assign the different weights that can not change at each time point to each individual forecasting model. In this study, we introduce the IOWGA operator combination method which can overcome the defect of previous three combination methods into tourism forecasting. Moreover, we further investigate the performance of the four combination methods through the theoretical evaluation and the forecasting evaluation. The results of the theoretical evaluation show that the IOWGA operator combination method obtains extremely well performance and outperforms the other forecast combination methods. Furthermore, the IOWGA operator combination method can be of well forecast performance and performs almost the same to the variance-covariance combination method for the forecasting evaluation. The IOWGA operator combination method mainly reflects the maximization of improving forecasting accuracy and the variance-covariance combination method mainly reflects the decrease of the forecast error. For future research, it may be worthwhile introducing and examining other new combination methods that may improve forecasting accuracy or employing other techniques to control the time for updating the weights in combined forecasts.

  8. Adjustable control in the steam zone of a steam power plant; Control ajustable de la zona de vapor de una unidad termoelectrica

    Energy Technology Data Exchange (ETDEWEB)

    Alvarez Gallegos, Joaquin; Bourguet Diaz, Rafael Ernesto [Instituto de Investigaciones Electricas, Cuernavaca (Mexico)

    1991-12-31

    A general description is presented of self adjustable control systems, as well as of the design and its application for steam temperature regulation of a steam power plant unit model. The algorithm employed is a controller of minimum variance that ponders the output deviation as well as the control effort. The results are compared with the ones obtained in a conventional control scheme, showing in general a better performance in the conducted experiments. [Espanol] Se presenta una descripcion general de los sistemas de control autoajustable, asi como del diseno y su aplicacion para regular las temperaturas de vapor de un modelo de unidad termoelectrica. El algoritmo utilizado es un controlador de variancia minima que pondera tanto la desviacion de salida como el esfuerzo de control. Los resultados se comparan con los obtenidos en un esquema de control convencional, mostrando en general un mejor desempeno en los experimentos realizados.

  9. Adjustable control in the steam zone of a steam power plant; Control ajustable de la zona de vapor de una unidad termoelectrica

    Energy Technology Data Exchange (ETDEWEB)

    Alvarez Gallegos, Joaquin; Bourguet Diaz, Rafael Ernesto [Instituto de Investigaciones Electricas, Cuernavaca (Mexico)

    1990-12-31

    A general description is presented of self adjustable control systems, as well as of the design and its application for steam temperature regulation of a steam power plant unit model. The algorithm employed is a controller of minimum variance that ponders the output deviation as well as the control effort. The results are compared with the ones obtained in a conventional control scheme, showing in general a better performance in the conducted experiments. [Espanol] Se presenta una descripcion general de los sistemas de control autoajustable, asi como del diseno y su aplicacion para regular las temperaturas de vapor de un modelo de unidad termoelectrica. El algoritmo utilizado es un controlador de variancia minima que pondera tanto la desviacion de salida como el esfuerzo de control. Los resultados se comparan con los obtenidos en un esquema de control convencional, mostrando en general un mejor desempeno en los experimentos realizados.

  10. Some variance reduction methods for numerical stochastic homogenization.

    Science.gov (United States)

    Blanc, X; Le Bris, C; Legoll, F

    2016-04-28

    We give an overview of a series of recent studies devoted to variance reduction techniques for numerical stochastic homogenization. Numerical homogenization requires that a set of problems is solved at the microscale, the so-called corrector problems. In a random environment, these problems are stochastic and therefore need to be repeatedly solved, for several configurations of the medium considered. An empirical average over all configurations is then performed using the Monte Carlo approach, so as to approximate the effective coefficients necessary to determine the macroscopic behaviour. Variance severely affects the accuracy and the cost of such computations. Variance reduction approaches, borrowed from other contexts in the engineering sciences, can be useful. Some of these variance reduction techniques are presented, studied and tested here. © 2016 The Author(s).

  11. variance components and genetic parameters for live weight

    African Journals Online (AJOL)

    admin

    Against this background the present study estimated the (co)variance .... Starting values for the (co)variance components of two-trait models were ..... Estimates of genetic parameters for weaning weight of beef accounting for direct-maternal.

  12. Restricted Variance Interaction Effects

    DEFF Research Database (Denmark)

    Cortina, Jose M.; Köhler, Tine; Keeler, Kathleen R.

    2018-01-01

    Although interaction hypotheses are increasingly common in our field, many recent articles point out that authors often have difficulty justifying them. The purpose of this article is to describe a particular type of interaction: the restricted variance (RV) interaction. The essence of the RV int...

  13. Variance Swaps in BM&F: Pricing and Viability of Hedge

    Directory of Open Access Journals (Sweden)

    Richard John Brostowicz Junior

    2010-07-01

    Full Text Available A variance swap can theoretically be priced with an infinite set of vanilla calls and puts options considering that the realized variance follows a purely diffusive process with continuous monitoring. In this article we willanalyze the possible differences in pricing considering discrete monitoring of realized variance. It will analyze the pricing of variance swaps with payoff in dollars, since there is a OTC market that works this way and thatpotentially serve as a hedge for the variance swaps traded in BM&F. Additionally, will be tested the feasibility of hedge of variance swaps when there is liquidity in just a few exercise prices, as is the case of FX optionstraded in BM&F. Thus be assembled portfolios containing variance swaps and their replicating portfolios using the available exercise prices as proposed in (DEMETERFI et al., 1999. With these portfolios, the effectiveness of the hedge was not robust in mostly of tests conducted in this work.

  14. Subjective neighborhood assessment and physical inactivity: An examination of neighborhood-level variance.

    Science.gov (United States)

    Prochaska, John D; Buschmann, Robert N; Jupiter, Daniel; Mutambudzi, Miriam; Peek, M Kristen

    2018-06-01

    Research suggests a linkage between perceptions of neighborhood quality and the likelihood of engaging in leisure-time physical activity. Often in these studies, intra-neighborhood variance is viewed as something to be controlled for statistically. However, we hypothesized that intra-neighborhood variance in perceptions of neighborhood quality may be contextually relevant. We examined the relationship between intra-neighborhood variance of subjective neighborhood quality and neighborhood-level reported physical inactivity across 48 neighborhoods within a medium-sized city, Texas City, Texas using survey data from 2706 residents collected between 2004 and 2006. Neighborhoods where the aggregated perception of neighborhood quality was poor also had a larger proportion of residents reporting being physically inactive. However, higher degrees of disagreement among residents within neighborhoods about their neighborhood quality was significantly associated with a lower proportion of residents reporting being physically inactive (p=0.001). Our results suggest that intra-neighborhood variability may be contextually relevant in studies seeking to better understand the relationship between neighborhood quality and behaviors sensitive to neighborhood environments, like physical activity. Copyright © 2017 Elsevier Inc. All rights reserved.

  15. Mean-Variance Portfolio Selection with Margin Requirements

    Directory of Open Access Journals (Sweden)

    Yuan Zhou

    2013-01-01

    Full Text Available We study the continuous-time mean-variance portfolio selection problem in the situation when investors must pay margin for short selling. The problem is essentially a nonlinear stochastic optimal control problem because the coefficients of positive and negative parts of control variables are different. We can not apply the results of stochastic linearquadratic (LQ problem. Also the solution of corresponding Hamilton-Jacobi-Bellman (HJB equation is not smooth. Li et al. (2002 studied the case when short selling is prohibited; therefore they only need to consider the positive part of control variables, whereas we need to handle both the positive part and the negative part of control variables. The main difficulty is that the positive part and the negative part are not independent. The previous results are not directly applicable. By decomposing the problem into several subproblems we figure out the solutions of HJB equation in two disjoint regions and then prove it is the viscosity solution of HJB equation. Finally we formulate solution of optimal portfolio and the efficient frontier. We also present two examples showing how different margin rates affect the optimal solutions and the efficient frontier.

  16. Simultaneous Monte Carlo zero-variance estimates of several correlated means

    International Nuclear Information System (INIS)

    Booth, T.E.

    1998-01-01

    Zero-variance biasing procedures are normally associated with estimating a single mean or tally. In particular, a zero-variance solution occurs when every sampling is made proportional to the product of the true probability multiplied by the expected score (importance) subsequent to the sampling; i.e., the zero-variance sampling is importance weighted. Because every tally has a different importance function, a zero-variance biasing for one tally cannot be a zero-variance biasing for another tally (unless the tallies are perfectly correlated). The way to optimize the situation when the required tallies have positive correlation is shown

  17. Comparing estimates of genetic variance across different relationship models.

    Science.gov (United States)

    Legarra, Andres

    2016-02-01

    Use of relationships between individuals to estimate genetic variances and heritabilities via mixed models is standard practice in human, plant and livestock genetics. Different models or information for relationships may give different estimates of genetic variances. However, comparing these estimates across different relationship models is not straightforward as the implied base populations differ between relationship models. In this work, I present a method to compare estimates of variance components across different relationship models. I suggest referring genetic variances obtained using different relationship models to the same reference population, usually a set of individuals in the population. Expected genetic variance of this population is the estimated variance component from the mixed model times a statistic, Dk, which is the average self-relationship minus the average (self- and across-) relationship. For most typical models of relationships, Dk is close to 1. However, this is not true for very deep pedigrees, for identity-by-state relationships, or for non-parametric kernels, which tend to overestimate the genetic variance and the heritability. Using mice data, I show that heritabilities from identity-by-state and kernel-based relationships are overestimated. Weighting these estimates by Dk scales them to a base comparable to genomic or pedigree relationships, avoiding wrong comparisons, for instance, "missing heritabilities". Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Variance estimation in the analysis of microarray data

    KAUST Repository

    Wang, Yuedong

    2009-04-01

    Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing to the small number of replications. Various methods have been proposed in the literature to overcome this lack of degrees of freedom problem. In this context, it is commonly observed that the variance increases proportionally with the intensity level, which has led many researchers to assume that the variance is a function of the mean. Here we concentrate on estimation of the variance as a function of an unknown mean in two models: the constant coefficient of variation model and the quadratic variance-mean model. Because the means are unknown and estimated with few degrees of freedom, naive methods that use the sample mean in place of the true mean are generally biased because of the errors-in-variables phenomenon. We propose three methods for overcoming this bias. The first two are variations on the theme of the so-called heteroscedastic simulation-extrapolation estimator, modified to estimate the variance function consistently. The third class of estimators is entirely different, being based on semiparametric information calculations. Simulations show the power of our methods and their lack of bias compared with the naive method that ignores the measurement error. The methodology is illustrated by using microarray data from leukaemia patients.

  19. Variance computations for functional of absolute risk estimates.

    Science.gov (United States)

    Pfeiffer, R M; Petracci, E

    2011-07-01

    We present a simple influence function based approach to compute the variances of estimates of absolute risk and functions of absolute risk. We apply this approach to criteria that assess the impact of changes in the risk factor distribution on absolute risk for an individual and at the population level. As an illustration we use an absolute risk prediction model for breast cancer that includes modifiable risk factors in addition to standard breast cancer risk factors. Influence function based variance estimates for absolute risk and the criteria are compared to bootstrap variance estimates.

  20. 76 FR 78698 - Proposed Revocation of Permanent Variances

    Science.gov (United States)

    2011-12-19

    ... Administration (``OSHA'' or ``the Agency'') granted permanent variances to 24 companies engaged in the... DEPARTMENT OF LABOR Occupational Safety and Health Administration [Docket No. OSHA-2011-0054] Proposed Revocation of Permanent Variances AGENCY: Occupational Safety and Health Administration (OSHA...

  1. 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.

  2. Do Minimum Wages Fight Poverty?

    OpenAIRE

    David Neumark; William Wascher

    1997-01-01

    The primary goal of a national minimum wage floor is to raise the incomes of poor or near-poor families with members in the work force. However, estimates of employment effects of minimum wages tell us little about whether minimum wages are can achieve this goal; even if the disemployment effects of minimum wages are modest, minimum wage increases could result in net income losses for poor families. We present evidence on the effects of minimum wages on family incomes from matched March CPS s...

  3. RR-Interval variance of electrocardiogram for atrial fibrillation detection

    Science.gov (United States)

    Nuryani, N.; Solikhah, M.; Nugoho, A. S.; Afdala, A.; Anzihory, E.

    2016-11-01

    Atrial fibrillation is a serious heart problem originated from the upper chamber of the heart. The common indication of atrial fibrillation is irregularity of R peak-to-R-peak time interval, which is shortly called RR interval. The irregularity could be represented using variance or spread of RR interval. This article presents a system to detect atrial fibrillation using variances. Using clinical data of patients with atrial fibrillation attack, it is shown that the variance of electrocardiographic RR interval are higher during atrial fibrillation, compared to the normal one. Utilizing a simple detection technique and variances of RR intervals, we find a good performance of atrial fibrillation detection.

  4. Variance based OFDM frame synchronization

    Directory of Open Access Journals (Sweden)

    Z. Fedra

    2012-04-01

    Full Text Available The paper deals with a new frame synchronization scheme for OFDM systems and calculates the complexity of this scheme. The scheme is based on the computing of the detection window variance. The variance is computed in two delayed times, so a modified Early-Late loop is used for the frame position detection. The proposed algorithm deals with different variants of OFDM parameters including guard interval, cyclic prefix, and has good properties regarding the choice of the algorithm's parameters since the parameters may be chosen within a wide range without having a high influence on system performance. The verification of the proposed algorithm functionality has been performed on a development environment using universal software radio peripheral (USRP hardware.

  5. Global-scale high-resolution ( 1 km) modelling of mean, maximum and minimum annual streamflow

    Science.gov (United States)

    Barbarossa, Valerio; Huijbregts, Mark; Hendriks, Jan; Beusen, Arthur; Clavreul, Julie; King, Henry; Schipper, Aafke

    2017-04-01

    Quantifying mean, maximum and minimum annual flow (AF) of rivers at ungauged sites is essential for a number of applications, including assessments of global water supply, ecosystem integrity and water footprints. AF metrics can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict AF metrics based on climate and catchment characteristics. Yet, so far, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. We developed global-scale regression models that quantify mean, maximum and minimum AF as function of catchment area and catchment-averaged slope, elevation, and mean, maximum and minimum annual precipitation and air temperature. We then used these models to obtain global 30 arc-seconds (˜ 1 km) maps of mean, maximum and minimum AF for each year from 1960 through 2015, based on a newly developed hydrologically conditioned digital elevation model. We calibrated our regression models based on observations of discharge and catchment characteristics from about 4,000 catchments worldwide, ranging from 100 to 106 km2 in size, and validated them against independent measurements as well as the output of a number of process-based global hydrological models (GHMs). The variance explained by our regression models ranged up to 90% and the performance of the models compared well with the performance of existing GHMs. Yet, our AF maps provide a level of spatial detail that cannot yet be achieved by current GHMs.

  6. Means and Variances without Calculus

    Science.gov (United States)

    Kinney, John J.

    2005-01-01

    This article gives a method of finding discrete approximations to continuous probability density functions and shows examples of its use, allowing students without calculus access to the calculation of means and variances.

  7. COVAR: Computer Program for Multifactor Relative Risks and Tests of Hypotheses Using a Variance-Covariance Matrix from Linear and Log-Linear Regression

    Directory of Open Access Journals (Sweden)

    Leif E. Peterson

    1997-11-01

    Full Text Available A computer program for multifactor relative risks, confidence limits, and tests of hypotheses using regression coefficients and a variance-covariance matrix obtained from a previous additive or multiplicative regression analysis is described in detail. Data used by the program can be stored and input from an external disk-file or entered via the keyboard. The output contains a list of the input data, point estimates of single or joint effects, confidence intervals and tests of hypotheses based on a minimum modified chi-square statistic. Availability of the program is also discussed.

  8. Beyond the Mean: Sensitivities of the Variance of Population Growth.

    Science.gov (United States)

    Trotter, Meredith V; Krishna-Kumar, Siddharth; Tuljapurkar, Shripad

    2013-03-01

    Populations in variable environments are described by both a mean growth rate and a variance of stochastic population growth. Increasing variance will increase the width of confidence bounds around estimates of population size, growth, probability of and time to quasi-extinction. However, traditional sensitivity analyses of stochastic matrix models only consider the sensitivity of the mean growth rate. We derive an exact method for calculating the sensitivity of the variance in population growth to changes in demographic parameters. Sensitivities of the variance also allow a new sensitivity calculation for the cumulative probability of quasi-extinction. We apply this new analysis tool to an empirical dataset on at-risk polar bears to demonstrate its utility in conservation biology We find that in many cases a change in life history parameters will increase both the mean and variance of population growth of polar bears. This counterintuitive behaviour of the variance complicates predictions about overall population impacts of management interventions. Sensitivity calculations for cumulative extinction risk factor in changes to both mean and variance, providing a highly useful quantitative tool for conservation management. The mean stochastic growth rate and its sensitivities do not fully describe the dynamics of population growth. The use of variance sensitivities gives a more complete understanding of population dynamics and facilitates the calculation of new sensitivities for extinction processes.

  9. Adaptive Control of Non-Minimum Phase Modal Systems Using Residual Mode Filters2. Parts 1 and 2

    Science.gov (United States)

    Balas, Mark J.; Frost, Susan

    2011-01-01

    Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will modify the adaptive controller with a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. This paper will be divided into two parts. Here in Part I we will review the basic adaptive control approach and introduce the primary ideas. In Part II, we will present the RMF methodology and complete the proofs of all our results. Also, we will apply the above theoretical results to a simple flexible structure example to illustrate the behavior with and without the residual mode filter.

  10. Evaluation of Mean and Variance Integrals without Integration

    Science.gov (United States)

    Joarder, A. H.; Omar, M. H.

    2007-01-01

    The mean and variance of some continuous distributions, in particular the exponentially decreasing probability distribution and the normal distribution, are considered. Since they involve integration by parts, many students do not feel comfortable. In this note, a technique is demonstrated for deriving mean and variance through differential…

  11. Approximate zero-variance Monte Carlo estimation of Markovian unreliability

    International Nuclear Information System (INIS)

    Delcoux, J.L.; Labeau, P.E.; Devooght, J.

    1997-01-01

    Monte Carlo simulation has become an important tool for the estimation of reliability characteristics, since conventional numerical methods are no more efficient when the size of the system to solve increases. However, evaluating by a simulation the probability of occurrence of very rare events means playing a very large number of histories of the system, which leads to unacceptable computation times. Acceleration and variance reduction techniques have to be worked out. We show in this paper how to write the equations of Markovian reliability as a transport problem, and how the well known zero-variance scheme can be adapted to this application. But such a method is always specific to the estimation of one quality, while a Monte Carlo simulation allows to perform simultaneously estimations of diverse quantities. Therefore, the estimation of one of them could be made more accurate while degrading at the same time the variance of other estimations. We propound here a method to reduce simultaneously the variance for several quantities, by using probability laws that would lead to zero-variance in the estimation of a mean of these quantities. Just like the zero-variance one, the method we propound is impossible to perform exactly. However, we show that simple approximations of it may be very efficient. (author)

  12. Quality control of brachytherapy equipment in the Netherlands and Belgium: current practice and minimum requirements

    International Nuclear Information System (INIS)

    Elfrink, Robert J.M.; Kolkman-Deurloo, Inger-Karine K.; Kleffens, Herman J. van; Rijnders, Alex; Schaeken, Bob; Aalbers, Tony H.L.; Dries, Wim J.F.; Venselaar, Jack L.M.

    2002-01-01

    Background and purpose: Brachytherapy is applied in 39 radiotherapy institutions in The Netherlands and Belgium. Each institution has its own quality control (QC) programme to ensure safe and accurate dose delivery to the patient. The main goal of this work is to gain insight into the current practice of QC of brachytherapy in The Netherlands and Belgium and to reduce possible variations in test frequencies and tolerances by formulating a set of minimum QC-requirements. Materials and methods: An extensive questionnaire about QC of brachytherapy was distributed to and completed by the 39 radiotherapy institutions. A separate smaller questionnaire was sent to nine institutions performing intracoronary brachytherapy. The questions were related to safety systems, physical irradiation parameters and total time spent on QC. The results of the questionnaires were compared with recommendations given in international brachytherapy QC reports. Results: The answers to the questionnaires showed large variations in test frequencies and test methods. Furthermore, large variations in time spent on QC exist, which is mainly due to differences in QC-philosophy and differences in the available resources. Conclusions: Based on the results of the questionnaires and the comparison with the international recommendations, a set of minimum requirements for QC of brachytherapy has been formulated. These guidelines will be implemented in the radiotherapy institutions in The Netherlands and Belgium

  13. Nonlinear Dynamic Surface Control of Chaos in Permanent Magnet Synchronous Motor Based on the Minimum Weights of RBF Neural Network

    Directory of Open Access Journals (Sweden)

    Shaohua Luo

    2014-01-01

    Full Text Available This paper is concerned with the problem of the nonlinear dynamic surface control (DSC of chaos based on the minimum weights of RBF neural network for the permanent magnet synchronous motor system (PMSM wherein the unknown parameters, disturbances, and chaos are presented. RBF neural network is used to approximate the nonlinearities and an adaptive law is employed to estimate unknown parameters. Then, a simple and effective controller is designed by introducing dynamic surface control technique on the basis of first-order filters. Asymptotically tracking stability in the sense of uniformly ultimate boundedness is achieved in a short time. Finally, the performance of the proposed controller is testified through simulation results.

  14. Analysis of Postural Control During Quiet Standing in a Population with Diabetic Peripheral Neuropathy Undergoing Moderate Intensity Aerobic Exercise Training: A Single Blind, Randomized Controlled Trial.

    Science.gov (United States)

    Dixit, Snehil; Maiya, Arun; Shastry, Barkur A; Guddattu, Vasudev

    2016-07-01

    The aim of this study was to investigate the effect of 8 wks of moderate-intensity aerobic exercise on postural control during quiet standing in type 2 diabetic peripheral neuropathy. Individuals were included in the study if they had type 2 diabetes with clinical neuropathy, defined by a minimum score of 7 on the Michigan Diabetic Neuropathy Score, following which the patients were randomly assigned to an 8-wk program by computer-generated random number tables to study or control group. Repeated-measures analysis of variance was used for data analysis (P < 0.05 was considered significant). After final randomization, there were 36 patients in the study group and 45 in the control group. On comparison of results for control and study groups using repeated-measures analysis of variance only in the eyes closed on foam condition was there was a significant difference between the two groups for sway velocity along the x-axis (df1, df2 = 1, 18, F = 3.86, P = 0.04) and mediolateral displacement (df1, df2 = 1, 18, F = 4.04, P = 0.03). Aerobic exercise training could exert a therapeutic effect on center of pressure movement only along the x-axis in the eyes closed condition on foam surface during quiet standing.

  15. Variance in binary stellar population synthesis

    Science.gov (United States)

    Breivik, Katelyn; Larson, Shane L.

    2016-03-01

    In the years preceding LISA, Milky Way compact binary population simulations can be used to inform the science capabilities of the mission. Galactic population simulation efforts generally focus on high fidelity models that require extensive computational power to produce a single simulated population for each model. Each simulated population represents an incomplete sample of the functions governing compact binary evolution, thus introducing variance from one simulation to another. We present a rapid Monte Carlo population simulation technique that can simulate thousands of populations in less than a week, thus allowing a full exploration of the variance associated with a binary stellar evolution model.

  16. A Mean variance analysis of arbitrage portfolios

    Science.gov (United States)

    Fang, Shuhong

    2007-03-01

    Based on the careful analysis of the definition of arbitrage portfolio and its return, the author presents a mean-variance analysis of the return of arbitrage portfolios, which implies that Korkie and Turtle's results ( B. Korkie, H.J. Turtle, A mean-variance analysis of self-financing portfolios, Manage. Sci. 48 (2002) 427-443) are misleading. A practical example is given to show the difference between the arbitrage portfolio frontier and the usual portfolio frontier.

  17. Mean-Variance Optimization in Markov Decision Processes

    OpenAIRE

    Mannor, Shie; Tsitsiklis, John N.

    2011-01-01

    We consider finite horizon Markov decision processes under performance measures that involve both the mean and the variance of the cumulative reward. We show that either randomized or history-based policies can improve performance. We prove that the complexity of computing a policy that maximizes the mean reward under a variance constraint is NP-hard for some cases, and strongly NP-hard for others. We finally offer pseudo-polynomial exact and approximation algorithms.

  18. Capturing Option Anomalies with a Variance-Dependent Pricing Kernel

    DEFF Research Database (Denmark)

    Christoffersen, Peter; Heston, Steven; Jacobs, Kris

    2013-01-01

    We develop a GARCH option model with a new pricing kernel allowing for a variance premium. While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is nonmonotonic. A negative variance premium makes it U shaped. We present new semiparametric...... evidence to confirm this U-shaped relationship between the risk-neutral and physical probability densities. The new pricing kernel substantially improves our ability to reconcile the time-series properties of stock returns with the cross-section of option prices. It provides a unified explanation...... for the implied volatility puzzle, the overreaction of long-term options to changes in short-term variance, and the fat tails of the risk-neutral return distribution relative to the physical distribution....

  19. Gender Variance and Educational Psychology: Implications for Practice

    Science.gov (United States)

    Yavuz, Carrie

    2016-01-01

    The area of gender variance appears to be more visible in both the media and everyday life. Within educational psychology literature gender variance remains underrepresented. The positioning of educational psychologists working across the three levels of child and family, school or establishment and education authority/council, means that they are…

  20. Demonstration of a zero-variance based scheme for variance reduction to a mini-core Monte Carlo calculation

    Energy Technology Data Exchange (ETDEWEB)

    Christoforou, Stavros, E-mail: stavros.christoforou@gmail.com [Kirinthou 17, 34100, Chalkida (Greece); Hoogenboom, J. Eduard, E-mail: j.e.hoogenboom@tudelft.nl [Department of Applied Sciences, Delft University of Technology (Netherlands)

    2011-07-01

    A zero-variance based scheme is implemented and tested in the MCNP5 Monte Carlo code. The scheme is applied to a mini-core reactor using the adjoint function obtained from a deterministic calculation for biasing the transport kernels. It is demonstrated that the variance of the k{sub eff} estimate is halved compared to a standard criticality calculation. In addition, the biasing does not affect source distribution convergence of the system. However, since the code lacked optimisations for speed, we were not able to demonstrate an appropriate increase in the efficiency of the calculation, because of the higher CPU time cost. (author)

  1. Variance-in-Mean Effects of the Long Forward-Rate Slope

    DEFF Research Database (Denmark)

    Christiansen, Charlotte

    2005-01-01

    This paper contains an empirical analysis of the dependence of the long forward-rate slope on the long-rate variance. The long forward-rate slope and the long rate are described by a bivariate GARCH-in-mean model. In accordance with theory, a negative long-rate variance-in-mean effect for the long...... forward-rate slope is documented. Thus, the greater the long-rate variance, the steeper the long forward-rate curve slopes downward (the long forward-rate slope is negative). The variance-in-mean effect is both statistically and economically significant....

  2. Increasing the genetic variance of rice protein through mutation breeding techniques

    International Nuclear Information System (INIS)

    Ismachin, M.

    1975-01-01

    Recommended rice variety in Indonesia, Pelita I/1 was treated with gamma rays at the doses of 20 krad, 30 krad, and 40 krad. The seeds were also treated with EMS 1%. In M 2 generation, the protein content of seeds from the visible mutants and from the normal looking plants were analyzed by DBC method. No significant increase in the genetic variance was found on the samples treated with 20 krad gamma, and on the normal looking plants treated by EMS 1%. The mean value of the treated samples were mostly significant decrease compared with the mean value of the protein distribution in untreated samples (control). Since significant increase in genetic variance was also found in M 2 normal looking plants - treated with gamma at the doses of 30 krad and 40 krad -selection of protein among these materials could be more valuable. (author)

  3. Analysis of power ramp rate and minimum power controllability of the MMS model for a plant dynamics analysis of a Prototype SFR

    International Nuclear Information System (INIS)

    Kim, Eui Kwang; Kim, Dehee; Joo, Hyungkook; Lee, Taeho

    2014-01-01

    A full plant dynamic model was developed for a prototype SFR using the Modular Modeling System (MMS). It includes the modeling of various subsystems such as the neutronics, primary and intermediate sodium systems of the NSSS, steam and water systems of the BOP, BOP controls, and the supervisory plant controls. The NSSS model is subdivided into component models, such as a Core, IHXs, Pumps, SGs, and the rest of the NSSS loop model. The BOP model is subdivided into a steam subsystem, feedwater subsystem, and preheater subsystem. Plant transient tests were performed to study the operational considerations. It includes varying the power ramp rate and studying the controllability at minimum power. Plant transient tests were performed to study operational considerations by using the MMS model for a prototype SFR. It includes varying the power ramp rate, studying the controllability at the minimum power set point. At a power ramp rate of higher than 2%, the steam temperature has a large deviation from the target. As the power set point decreases, the PHTS hot leg temperature and steam temperature tend to have higher deviations. After further refinement of the MMS model, it can be useful for developing the plant operation logics of the prototype SFR

  4. Variance-based sensitivity indices for models with dependent inputs

    International Nuclear Information System (INIS)

    Mara, Thierry A.; Tarantola, Stefano

    2012-01-01

    Computational models are intensively used in engineering for risk analysis or prediction of future outcomes. Uncertainty and sensitivity analyses are of great help in these purposes. Although several methods exist to perform variance-based sensitivity analysis of model output with independent inputs only a few are proposed in the literature in the case of dependent inputs. This is explained by the fact that the theoretical framework for the independent case is set and a univocal set of variance-based sensitivity indices is defined. In the present work, we propose a set of variance-based sensitivity indices to perform sensitivity analysis of models with dependent inputs. These measures allow us to distinguish between the mutual dependent contribution and the independent contribution of an input to the model response variance. Their definition relies on a specific orthogonalisation of the inputs and ANOVA-representations of the model output. In the applications, we show the interest of the new sensitivity indices for model simplification setting. - Highlights: ► Uncertainty and sensitivity analyses are of great help in engineering. ► Several methods exist to perform variance-based sensitivity analysis of model output with independent inputs. ► We define a set of variance-based sensitivity indices for models with dependent inputs. ► Inputs mutual contributions are distinguished from their independent contributions. ► Analytical and computational tests are performed and discussed.

  5. Simultaneous Monte Carlo zero-variance estimates of several correlated means

    International Nuclear Information System (INIS)

    Booth, T.E.

    1997-08-01

    Zero variance procedures have been in existence since the dawn of Monte Carlo. Previous works all treat the problem of zero variance solutions for a single tally. One often wants to get low variance solutions to more than one tally. When the sets of random walks needed for two tallies are similar, it is more efficient to do zero variance biasing for both tallies in the same Monte Carlo run, instead of two separate runs. The theory presented here correlates the random walks of particles by the similarity of their tallies. Particles with dissimilar tallies rapidly become uncorrelated whereas particles with similar tallies will stay correlated through most of their random walk. The theory herein should allow practitioners to make efficient use of zero-variance biasing procedures in practical problems

  6. Variance swap payoffs, risk premia and extreme market conditions

    DEFF Research Database (Denmark)

    Rombouts, Jeroen V.K.; Stentoft, Lars; Violante, Francesco

    This paper estimates the Variance Risk Premium (VRP) directly from synthetic variance swap payoffs. Since variance swap payoffs are highly volatile, we extract the VRP by using signal extraction techniques based on a state-space representation of our model in combination with a simple economic....... The latter variables and the VRP generate different return predictability on the major US indices. A factor model is proposed to extract a market VRP which turns out to be priced when considering Fama and French portfolios....

  7. An Experimental study on a Method of Computing Minimum flow rate

    International Nuclear Information System (INIS)

    Cho, Yeon Sik; Kim, Tae Hyun; Kim, Chang Hyun

    2009-01-01

    Many pump reliability problems in the Nuclear Power Plants (NPPs) are being attributed to the operation of the pump at flow rates well below its best efficiency point(BEP). Generally, the manufacturer and the user try to avert such problems by specifying a minimum flow, below which the pump should not be operated. Pump minimum flow usually involves two considerations. The first consideration is normally termed the 'thermal minimum flow', which is that flow required to prevent the fluid inside the pump from reaching saturation conditions. The other consideration is often referred to as 'mechanical minimum flow', which is that flow required to prevent mechanical damage. However, the criteria for specifying such a minimum flow are not clearly understood by all parties concerned. Also various factor and information for computing minimum flow are not easily available as considering for the pump manufacturer' proprietary. The objective of this study is to obtain experimental data for computing minimum flow rate and to understand the pump performances due to low flow operation. A test loop consisted of the pump to be used in NPPs, water tank, flow rate measurements and piping system with flow control devices was established for this study

  8. Estimating quadratic variation using realized variance

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Shephard, N.

    2002-01-01

    with a rather general SV model - which is a special case of the semimartingale model. Then QV is integrated variance and we can derive the asymptotic distribution of the RV and its rate of convergence. These results do not require us to specify a model for either the drift or volatility functions, although we...... have to impose some weak regularity assumptions. We illustrate the use of the limit theory on some exchange rate data and some stock data. We show that even with large values of M the RV is sometimes a quite noisy estimator of integrated variance. Copyright © 2002 John Wiley & Sons, Ltd....

  9. Dynamics of Variance Risk Premia, Investors' Sentiment and Return Predictability

    DEFF Research Database (Denmark)

    Rombouts, Jerome V.K.; Stentoft, Lars; Violante, Francesco

    We develop a joint framework linking the physical variance and its risk neutral expectation implying variance risk premia that are persistent, appropriately reacting to changes in level and variability of the variance and naturally satisfying the sign constraint. Using option market data and real...... events and only marginally by the premium associated with normal price fluctuations....

  10. Rising above the Minimum Wage.

    Science.gov (United States)

    Even, William; Macpherson, David

    An in-depth analysis was made of how quickly most people move up the wage scale from minimum wage, what factors influence their progress, and how minimum wage increases affect wage growth above the minimum. Very few workers remain at the minimum wage over the long run, according to this study of data drawn from the 1977-78 May Current Population…

  11. Partitioning of the variance in the growth parameters of Erwinia carotovora on vegetable products.

    Science.gov (United States)

    Shorten, P R; Membré, J-M; Pleasants, A B; Kubaczka, M; Soboleva, T K

    2004-06-01

    The objective of this paper was to estimate and partition the variability in the microbial growth model parameters describing the growth of Erwinia carotovora on pasteurised and non-pasteurised vegetable juice from laboratory experiments performed under different temperature-varying conditions. We partitioned the model parameter variance and covariance components into effects due to temperature profile and replicate using a maximum likelihood technique. Temperature profile and replicate were treated as random effects and the food substrate was treated as a fixed effect. The replicate variance component was small indicating a high level of control in this experiment. Our analysis of the combined E. carotovora growth data sets used the Baranyi primary microbial growth model along with the Ratkowsky secondary growth model. The variability in the microbial growth parameters estimated from these microbial growth experiments is essential for predicting the mean and variance through time of the E. carotovora population size in a product supply chain and is the basis for microbiological risk assessment and food product shelf-life estimation. The variance partitioning made here also assists in the management of optimal product distribution networks by identifying elements of the supply chain contributing most to product variability. Copyright 2003 Elsevier B.V.

  12. Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits

    DEFF Research Database (Denmark)

    Gebreyesus, Grum; Lund, Mogens Sandø; Buitenhuis, Albert Johannes

    2017-01-01

    Accurate genomic prediction requires a large reference population, which is problematic for traits that are expensive to measure. Traits related to milk protein composition are not routinely recorded due to costly procedures and are considered to be controlled by a few quantitative trait loci...... of large effect. The amount of variation explained may vary between regions leading to heterogeneous (co)variance patterns across the genome. Genomic prediction models that can efficiently take such heterogeneity of (co)variances into account can result in improved prediction reliability. In this study, we...... developed and implemented novel univariate and bivariate Bayesian prediction models, based on estimates of heterogeneous (co)variances for genome segments (BayesAS). Available data consisted of milk protein composition traits measured on cows and de-regressed proofs of total protein yield derived for bulls...

  13. Estimating High-Frequency Based (Co-) Variances: A Unified Approach

    DEFF Research Database (Denmark)

    Voev, Valeri; Nolte, Ingmar

    We propose a unified framework for estimating integrated variances and covariances based on simple OLS regressions, allowing for a general market microstructure noise specification. We show that our estimators can outperform, in terms of the root mean squared error criterion, the most recent...... and commonly applied estimators, such as the realized kernels of Barndorff-Nielsen, Hansen, Lunde & Shephard (2006), the two-scales realized variance of Zhang, Mykland & Aït-Sahalia (2005), the Hayashi & Yoshida (2005) covariance estimator, and the realized variance and covariance with the optimal sampling...

  14. Demonstration of a zero-variance based scheme for variance reduction to a mini-core Monte Carlo calculation

    International Nuclear Information System (INIS)

    Christoforou, Stavros; Hoogenboom, J. Eduard

    2011-01-01

    A zero-variance based scheme is implemented and tested in the MCNP5 Monte Carlo code. The scheme is applied to a mini-core reactor using the adjoint function obtained from a deterministic calculation for biasing the transport kernels. It is demonstrated that the variance of the k_e_f_f estimate is halved compared to a standard criticality calculation. In addition, the biasing does not affect source distribution convergence of the system. However, since the code lacked optimisations for speed, we were not able to demonstrate an appropriate increase in the efficiency of the calculation, because of the higher CPU time cost. (author)

  15. The Genealogical Consequences of Fecundity Variance Polymorphism

    Science.gov (United States)

    Taylor, Jesse E.

    2009-01-01

    The genealogical consequences of within-generation fecundity variance polymorphism are studied using coalescent processes structured by genetic backgrounds. I show that these processes have three distinctive features. The first is that the coalescent rates within backgrounds are not jointly proportional to the infinitesimal variance, but instead depend only on the frequencies and traits of genotypes containing each allele. Second, the coalescent processes at unlinked loci are correlated with the genealogy at the selected locus; i.e., fecundity variance polymorphism has a genomewide impact on genealogies. Third, in diploid models, there are infinitely many combinations of fecundity distributions that have the same diffusion approximation but distinct coalescent processes; i.e., in this class of models, ancestral processes and allele frequency dynamics are not in one-to-one correspondence. Similar properties are expected to hold in models that allow for heritable variation in other traits that affect the coalescent effective population size, such as sex ratio or fecundity and survival schedules. PMID:19433628

  16. Employment effects of minimum wages

    OpenAIRE

    Neumark, David

    2014-01-01

    The potential benefits of higher minimum wages come from the higher wages for affected workers, some of whom are in low-income families. The potential downside is that a higher minimum wage may discourage employers from using the low-wage, low-skill workers that minimum wages are intended to help. Research findings are not unanimous, but evidence from many countries suggests that minimum wages reduce the jobs available to low-skill workers.

  17. On Mean-Variance Analysis

    OpenAIRE

    Li, Yang; Pirvu, Traian A

    2011-01-01

    This paper considers the mean variance portfolio management problem. We examine portfolios which contain both primary and derivative securities. The challenge in this context is due to portfolio's nonlinearities. The delta-gamma approximation is employed to overcome it. Thus, the optimization problem is reduced to a well posed quadratic program. The methodology developed in this paper can be also applied to pricing and hedging in incomplete markets.

  18. Unraveling the genetic architecture of environmental variance of somatic cell score using high-density single nucleotide polymorphism and cow data from experimental farms.

    Science.gov (United States)

    Mulder, H A; Crump, R E; Calus, M P L; Veerkamp, R F

    2013-01-01

    In recent years, it has been shown that not only is the phenotype under genetic control, but also the environmental variance. Very little, however, is known about the genetic architecture of environmental variance. The main objective of this study was to unravel the genetic architecture of the mean and environmental variance of somatic cell score (SCS) by identifying genome-wide associations for mean and environmental variance of SCS in dairy cows and by quantifying the accuracy of genome-wide breeding values. Somatic cell score was used because previous research has shown that the environmental variance of SCS is partly under genetic control and reduction of the variance of SCS by selection is desirable. In this study, we used 37,590 single nucleotide polymorphism (SNP) genotypes and 46,353 test-day records of 1,642 cows at experimental research farms in 4 countries in Europe. We used a genomic relationship matrix in a double hierarchical generalized linear model to estimate genome-wide breeding values and genetic parameters. The estimated mean and environmental variance per cow was used in a Bayesian multi-locus model to identify SNP associated with either the mean or the environmental variance of SCS. Based on the obtained accuracy of genome-wide breeding values, 985 and 541 independent chromosome segments affecting the mean and environmental variance of SCS, respectively, were identified. Using a genomic relationship matrix increased the accuracy of breeding values relative to using a pedigree relationship matrix. In total, 43 SNP were significantly associated with either the mean (22) or the environmental variance of SCS (21). The SNP with the highest Bayes factor was on chromosome 9 (Hapmap31053-BTA-111664) explaining approximately 3% of the genetic variance of the environmental variance of SCS. Other significant SNP explained less than 1% of the genetic variance. It can be concluded that fewer genomic regions affect the environmental variance of SCS than the

  19. Modelling volatility by variance decomposition

    DEFF Research Database (Denmark)

    Amado, Cristina; Teräsvirta, Timo

    In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the variance of the model to have a smooth time-varying structure of either additive or multiplicative type. The suggested parameterisations describe both nonlinearity and structural change in the condit...

  20. Genetic Variance in Homophobia: Evidence from Self- and Peer Reports.

    Science.gov (United States)

    Zapko-Willmes, Alexandra; Kandler, Christian

    2018-01-01

    The present twin study combined self- and peer assessments of twins' general homophobia targeting gay men in order to replicate previous behavior genetic findings across different rater perspectives and to disentangle self-rater-specific variance from common variance in self- and peer-reported homophobia (i.e., rater-consistent variance). We hypothesized rater-consistent variance in homophobia to be attributable to genetic and nonshared environmental effects, and self-rater-specific variance to be partially accounted for by genetic influences. A sample of 869 twins and 1329 peer raters completed a seven item scale containing cognitive, affective, and discriminatory homophobic tendencies. After correction for age and sex differences, we found most of the genetic contributions (62%) and significant nonshared environmental contributions (16%) to individual differences in self-reports on homophobia to be also reflected in peer-reported homophobia. A significant genetic component, however, was self-report-specific (38%), suggesting that self-assessments alone produce inflated heritability estimates to some degree. Different explanations are discussed.

  1. Predicting minimum uncertainties in the inversion of ocean color geophysical parameters based on Cramer-Rao bounds.

    Science.gov (United States)

    Jay, Sylvain; Guillaume, Mireille; Chami, Malik; Minghelli, Audrey; Deville, Yannick; Lafrance, Bruno; Serfaty, Véronique

    2018-01-22

    We present an analytical approach based on Cramer-Rao Bounds (CRBs) to investigate the uncertainties in estimated ocean color parameters resulting from the propagation of uncertainties in the bio-optical reflectance modeling through the inversion process. Based on given bio-optical and noise probabilistic models, CRBs can be computed efficiently for any set of ocean color parameters and any sensor configuration, directly providing the minimum estimation variance that can be possibly attained by any unbiased estimator of any targeted parameter. Here, CRBs are explicitly developed using (1) two water reflectance models corresponding to deep and shallow waters, resp., and (2) four probabilistic models describing the environmental noises observed within four Sentinel-2 MSI, HICO, Sentinel-3 OLCI and MODIS images, resp. For both deep and shallow waters, CRBs are shown to be consistent with the experimental estimation variances obtained using two published remote-sensing methods, while not requiring one to perform any inversion. CRBs are also used to investigate to what extent perfect a priori knowledge on one or several geophysical parameters can improve the estimation of remaining unknown parameters. For example, using pre-existing knowledge of bathymetry (e.g., derived from LiDAR) within the inversion is shown to greatly improve the retrieval of bottom cover for shallow waters. Finally, CRBs are shown to provide valuable information on the best estimation performances that may be achieved with the MSI, HICO, OLCI and MODIS configurations for a variety of oceanic, coastal and inland waters. CRBs are thus demonstrated to be an informative and efficient tool to characterize minimum uncertainties in inverted ocean color geophysical parameters.

  2. Decomposition of Variance for Spatial Cox Processes.

    Science.gov (United States)

    Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

    2013-03-01

    Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive or log linear random intensity functions. We moreover consider a new and flexible class of pair correlation function models given in terms of normal variance mixture covariance functions. The proposed methodology is applied to point pattern data sets of locations of tropical rain forest trees.

  3. Grammatical and lexical variance in English

    CERN Document Server

    Quirk, Randolph

    2014-01-01

    Written by one of Britain's most distinguished linguists, this book is concerned with the phenomenon of variance in English grammar and vocabulary across regional, social, stylistic and temporal space.

  4. Variance decomposition in stochastic simulators.

    Science.gov (United States)

    Le Maître, O P; Knio, O M; Moraes, A

    2015-06-28

    This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

  5. Variance decomposition in stochastic simulators

    Science.gov (United States)

    Le Maître, O. P.; Knio, O. M.; Moraes, A.

    2015-06-01

    This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

  6. Variance decomposition in stochastic simulators

    Energy Technology Data Exchange (ETDEWEB)

    Le Maître, O. P., E-mail: olm@limsi.fr [LIMSI-CNRS, UPR 3251, Orsay (France); Knio, O. M., E-mail: knio@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708 (United States); Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa [King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)

    2015-06-28

    This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

  7. Variance-based Salt Body Reconstruction

    KAUST Repository

    Ovcharenko, Oleg

    2017-05-26

    Seismic inversions of salt bodies are challenging when updating velocity models based on Born approximation- inspired gradient methods. We propose a variance-based method for velocity model reconstruction in regions complicated by massive salt bodies. The novel idea lies in retrieving useful information from simultaneous updates corresponding to different single frequencies. Instead of the commonly used averaging of single-iteration monofrequency gradients, our algorithm iteratively reconstructs salt bodies in an outer loop based on updates from a set of multiple frequencies after a few iterations of full-waveform inversion. The variance among these updates is used to identify areas where considerable cycle-skipping occurs. In such areas, we update velocities by interpolating maximum velocities within a certain region. The result of several recursive interpolations is later used as a new starting model to improve results of conventional full-waveform inversion. An application on part of the BP 2004 model highlights the evolution of the proposed approach and demonstrates its effectiveness.

  8. Variance decomposition in stochastic simulators

    KAUST Repository

    Le Maî tre, O. P.; Knio, O. M.; Moraes, Alvaro

    2015-01-01

    This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.

  9. Minimum Wages and Poverty

    OpenAIRE

    Fields, Gary S.; Kanbur, Ravi

    2005-01-01

    Textbook analysis tells us that in a competitive labor market, the introduction of a minimum wage above the competitive equilibrium wage will cause unemployment. This paper makes two contributions to the basic theory of the minimum wage. First, we analyze the effects of a higher minimum wage in terms of poverty rather than in terms of unemployment. Second, we extend the standard textbook model to allow for incomesharing between the employed and the unemployed. We find that there are situation...

  10. Monitoring structural change in variance : With an application to European nominal exchange rate volatility

    NARCIS (Netherlands)

    F. Carsoule (Frédéric); Ph.H.B.F. Franses (Philip Hans)

    1999-01-01

    textabstractIn this paper we propose a sequential testing approach for a structural change in the variance of a time series, which amounts to a procedure with a controlled asymptotic size as we repeat the test. Our approach builds on that taken in Chu, Stinchcombe and White (1996) for structural

  11. 75 FR 6151 - Minimum Capital

    Science.gov (United States)

    2010-02-08

    ... capital and reserve requirements to be issued by order or regulation with respect to a product or activity... minimum capital requirements. Section 1362(a) establishes a minimum capital level for the Enterprises... entities required under this section.\\6\\ \\3\\ The Bank Act's current minimum capital requirements apply to...

  12. A Pareto-Improving Minimum Wage

    OpenAIRE

    Eliav Danziger; Leif Danziger

    2014-01-01

    This paper shows that a graduated minimum wage, in contrast to a constant minimum wage, can provide a strict Pareto improvement over what can be achieved with an optimal income tax. The reason is that a graduated minimum wage requires high-productivity workers to work more to earn the same income as low-productivity workers, which makes it more difficult for the former to mimic the latter. In effect, a graduated minimum wage allows the low-productivity workers to benefit from second-degree pr...

  13. Discussion on variance reduction technique for shielding

    Energy Technology Data Exchange (ETDEWEB)

    Maekawa, Fujio [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

    1998-03-01

    As the task of the engineering design activity of the international thermonuclear fusion experimental reactor (ITER), on 316 type stainless steel (SS316) and the compound system of SS316 and water, the shielding experiment using the D-T neutron source of FNS in Japan Atomic Energy Research Institute has been carried out. However, in these analyses, enormous working time and computing time were required for determining the Weight Window parameter. Limitation or complication was felt when the variance reduction by Weight Window method of MCNP code was carried out. For the purpose of avoiding this difficulty, investigation was performed on the effectiveness of the variance reduction by cell importance method. The conditions of calculation in all cases are shown. As the results, the distribution of fractional standard deviation (FSD) related to neutrons and gamma-ray flux in the direction of shield depth is reported. There is the optimal importance change, and when importance was increased at the same rate as that of the attenuation of neutron or gamma-ray flux, the optimal variance reduction can be done. (K.I.)

  14. Capturing option anomalies with a variance-dependent pricing kernel

    NARCIS (Netherlands)

    Christoffersen, P.; Heston, S.; Jacobs, K.

    2013-01-01

    We develop a GARCH option model with a variance premium by combining the Heston-Nandi (2000) dynamic with a new pricing kernel that nests Rubinstein (1976) and Brennan (1979). While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is

  15. 29 CFR 1904.38 - Variances from the recordkeeping rule.

    Science.gov (United States)

    2010-07-01

    ..., DEPARTMENT OF LABOR RECORDING AND REPORTING OCCUPATIONAL INJURIES AND ILLNESSES Other OSHA Injury and Illness... he or she finds appropriate. (iv) If the Assistant Secretary grants your variance petition, OSHA will... Secretary is reviewing your variance petition. (4) If I have already been cited by OSHA for not following...

  16. Minimum intervention dentistry approach to managing early childhood caries: a randomized control trial.

    Science.gov (United States)

    Arrow, Peter; Klobas, Elizabeth

    2015-12-01

    A pragmatic randomized control trial was undertaken to compare the minimum intervention dentistry (MID) approach, based on the atraumatic restorative treatment procedures (MID-ART: Test), against the standard care approach (Control) to treat early childhood caries in a primary care setting. Consenting parent/child dyads were allocated to the Test or Control group using stratified block randomization. Inclusion and exclusion criteria were applied. Participants were examined at baseline and at follow-up by two calibrated examiners blind to group allocation status (κ = 0.77), and parents completed a questionnaire at baseline and follow-up. Dental therapists trained in MID-ART provided treatment to the Test group and dentists treated the Control group using standard approaches. The primary outcome of interest was the number of children who were referred for specialist pediatric care. Secondary outcomes were the number of teeth treated, changes in child oral health-related quality of life and dental anxiety and parental perceptions of care received. Data were analyzed on an intention to treat basis; risk ratio for referral for specialist care, test of proportions, Wilcoxon rank test and logistic regression were used. Three hundred and seventy parents/carers were initially screened; 273 children were examined at baseline and 254 were randomized (Test = 127; Control = 127): mean age = 3.8 years, SD 0.90; 59% male, mean dmft = 4.9, SD 4.0. There was no statistically significant difference in age, sex, baseline caries experience or child oral health-related quality of life between the Test and Control group. At follow-up (mean interval 11.4 months, SD 3.1 months), 220 children were examined: Test = 115, Control = 105. Case-notes review of 231 children showed Test = 6 (5%) and Control = 53 (49%) were referred for specialist care, P < 0.0001. More teeth were filled in the Test group (mean = 2.93, SD 2.48) than in the Control group (mean = 1.54, SD

  17. Analysis of ulnar variance as a risk factor for developing scaphoid nonunion.

    Science.gov (United States)

    Lirola-Palmero, S; Salvà-Coll, G; Terrades-Cladera, F J

    2015-01-01

    Ulnar variance may be a risk factor of developing scaphoid non-union. A review was made of the posteroanterior wrist radiographs of 95 patients who were diagnosed of scaphoid fracture. All fractures with displacement less than 1mm treated conservatively were included. The ulnar variance was measured in all patients. Ulnar variance was measured in standard posteroanterior wrist radiographs of 95 patients. Eighteen patients (19%) developed scaphoid nonunion, with a mean value of ulnar variance of -1.34 (-/+ 0.85) mm (CI -2.25 - 0.41). Seventy seven patients (81%) healed correctly, and the mean value of ulnar variance was -0.04 (-/+ 1.85) mm (CI -0.46 - 0.38). A significant difference was observed in the distribution of ulnar variance (pvariance less than -1mm, and ulnar variance greater than -1mm. It appears that patients with ulnar variance less than -1mm had an OR 4.58 (CI 1.51 to 13.89) with pvariance less than -1mm have a greater risk of developing scaphoid nonunion, OR 4.58 (CI 1.51 to 13.89) with p<.007. Copyright © 2014 SECOT. Published by Elsevier Espana. All rights reserved.

  18. Minimum Variance Beamforming for High Frame-Rate Ultrasound Imaging

    DEFF Research Database (Denmark)

    Holfort, Iben Kraglund; Gran, Fredrik; Jensen, Jørgen Arendt

    2007-01-01

    , a 7 MHz, 128-element, phased array transducer with lambda/2-spacing was used. Data is obtained using a single element as the transmitting aperture and all 128 elements as the receiving aperture. A full SA sequence consisting of 128 emissions was simulated by gliding the active transmitting element...... weights for each frequency sub-band. As opposed to the conventional, Delay and Sum (DS) beamformer, this approach is dependent on the specific data. The performance of the proposed MV beamformer is tested on simulated synthetic aperture (SA) ultrasound data, obtained using Field II. For the simulations...... across the array. Data for 13 point targets and a circular cyst with a radius of 5 mm were simulated. The performance of the MV beamformer is compared to DS using boxcar weights and Hanning weights, and is quantified by the Full Width at Half Maximum (FWHM) and the peak-side-lobe level (PSL). Single...

  19. 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.

  20. Decomposition of variance in terms of conditional means

    Directory of Open Access Journals (Sweden)

    Alessandro Figà Talamanca

    2013-05-01

    Full Text Available Two different sets of data are used to test an apparently new approach to the analysis of the variance of a numerical variable which depends on qualitative variables. We suggest that this approach be used to complement other existing techniques to study the interdependence of the variables involved. According to our method, the variance is expressed as a sum of orthogonal components, obtained as differences of conditional means, with respect to the qualitative characters. The resulting expression for the variance depends on the ordering in which the characters are considered. We suggest an algorithm which leads to an ordering which is deemed natural. The first set of data concerns the score achieved by a population of students on an entrance examination based on a multiple choice test with 30 questions. In this case the qualitative characters are dyadic and correspond to correct or incorrect answer to each question. The second set of data concerns the delay to obtain the degree for a population of graduates of Italian universities. The variance in this case is analyzed with respect to a set of seven specific qualitative characters of the population studied (gender, previous education, working condition, parent's educational level, field of study, etc..

  1. 42 CFR 456.522 - Content of request for variance.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 4 2010-10-01 2010-10-01 false Content of request for variance. 456.522 Section 456.522 Public Health CENTERS FOR MEDICARE & MEDICAID SERVICES, DEPARTMENT OF HEALTH AND HUMAN... perform UR within the time requirements for which the variance is requested and its good faith efforts to...

  2. On the Endogeneity of the Mean-Variance Efficient Frontier.

    Science.gov (United States)

    Somerville, R. A.; O'Connell, Paul G. J.

    2002-01-01

    Explains that the endogeneity of the efficient frontier in the mean-variance model of portfolio selection is commonly obscured in portfolio selection literature and in widely used textbooks. Demonstrates endogeneity and discusses the impact of parameter changes on the mean-variance efficient frontier and on the beta coefficients of individual…

  3. Assessment of ulnar variance: a radiological investigation in a Dutch population

    Energy Technology Data Exchange (ETDEWEB)

    Schuurman, A.H. [Dept. of Plastic, Reconstructive and Hand Surgery, University Medical Centre, Utrecht (Netherlands); Dept. of Plastic Surgery, University Medical Centre, Utrecht (Netherlands); Maas, M.; Dijkstra, P.F. [Dept. of Radiology, Univ. of Amsterdam (Netherlands); Kauer, J.M.G. [Dept. of Anatomy and Embryology, Univ. of Nijmegen (Netherlands)

    2001-11-01

    Objective: A radiological study was performed to evaluate ulnar variance in 68 Dutch patients using an electronic digitizer compared with Palmer's concentric circle method. Using the digitizer method only, the effect of different wrist positions and grip on ulnar variance was then investigated. Finally the distribution of ulnar variance in the selected patients was investigated also using the digitizer method. Design and patients: All radiographs were performed with the wrist in a standard zero-rotation position (posteroanterior) and in supination (anteroposterior). Palmer's concentric circle method and an electronic digitizer connected to a personal computer were used to measure ulnar variance. The digitizer consists of a Plexiglas plate with an electronically activated grid beneath it. A radiograph is placed on the plate and a cursor activates a point on the grid. Three plots are marked on the radius and one plot on the most distal part of the ulnar head. The digitizer then determines the difference between a radius passing through the radius plots and the ulnar plot. Results and conclusions: Using the concentric circle method we found an ulna plus predominance, but an ulna minus predominance when using the digitizer method. Overall the ulnar variance distribution for Palmer's method was 41.9% ulna plus, 25.7% neutral and 32.4% ulna minus variance, and for the digitizer method was 40.4% ulna plus, 1.5% neutral and 58.1% ulna minus. The percentage ulnar variance greater than 1 mm on standard radiographs increased from 23% to 58% using the digitizer, with maximum grip, clearly demonstrating the (dynamic) effect of grip on ulnar variance. This almost threefold increase was found to be a significant difference. Significant differences were found between ulnar variance when different wrist positions were compared. (orig.)

  4. Minimum critical mass systems

    International Nuclear Information System (INIS)

    Dam, H. van; Leege, P.F.A. de

    1987-01-01

    An analysis is presented of thermal systems with minimum critical mass, based on the use of materials with optimum neutron moderating and reflecting properties. The optimum fissile material distributions in the systems are obtained by calculations with standard computer codes, extended with a routine for flat fuel importance search. It is shown that in the minimum critical mass configuration a considerable part of the fuel is positioned in the reflector region. For 239 Pu a minimum critical mass of 87 g is found, which is the lowest value reported hitherto. (author)

  5. Minimum Wages and School Enrollment of Teenagers: A Look at the 1990's.

    Science.gov (United States)

    Chaplin, Duncan D.; Turner, Mark D.; Pape, Andreas, D.

    2003-01-01

    Estimates the effects of higher minimum wages on school enrollment using the Common Core of Data. Controlling for local labor market conditions and state and year fixed effects, finds some evidence that higher minimum wages reduce teen school enrollment in states where students drop out before age 18. (23 references) (Author/PKP)

  6. Variance and covariance calculations for nuclear materials accounting using ''MAVARIC''

    International Nuclear Information System (INIS)

    Nasseri, K.K.

    1987-07-01

    Determination of the detection sensitivity of a materials accounting system to the loss of special nuclear material (SNM) requires (1) obtaining a relation for the variance of the materials balance by propagation of the instrument errors for the measured quantities that appear in the materials balance equation and (2) substituting measured values and their error standard deviations into this relation and calculating the variance of the materials balance. MAVARIC (Materials Accounting VARIance Calculations) is a custom spreadsheet, designed using the second release of Lotus 1-2-3, that significantly reduces the effort required to make the necessary variance (and covariance) calculations needed to determine the detection sensitivity of a materials accounting system. Predefined macros within the spreadsheet allow the user to carry out long, tedious procedures with only a few keystrokes. MAVARIC requires that the user enter the following data into one of four data tables, depending on the type of the term in the materials balance equation; the SNM concentration, the bulk mass (or solution volume), the measurement error standard deviations, and the number of measurements made during an accounting period. The user can also specify if there are correlations between transfer terms. Based on these data entries, MAVARIC can calculate the variance of the materials balance and the square root of this variance, from which the detection sensitivity of the accounting system can be determined

  7. A versatile omnibus test for detecting mean and variance heterogeneity.

    Science.gov (United States)

    Cao, Ying; Wei, Peng; Bailey, Matthew; Kauwe, John S K; Maxwell, Taylor J

    2014-01-01

    Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene-by-gene (G × G), or gene-by-environment interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (LRT(MV)) or either effect alone (LRT(M) or LRT(V)) in the presence of covariates. Using extensive simulations for our method and others, we found that all parametric tests were sensitive to nonnormality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean-only functional variant, we demonstrate how LD can produce variance-heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D', and relatively low r² values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance-only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect G × G interactions and also how vQTL are related to relationship loci, and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait.

  8. Variance and covariance calculations for nuclear materials accounting using 'MAVARIC'

    International Nuclear Information System (INIS)

    Nasseri, K.K.

    1987-01-01

    Determination of the detection sensitivity of a materials accounting system to the loss of special nuclear material (SNM) requires (1) obtaining a relation for the variance of the materials balance by propagation of the instrument errors for the measured quantities that appear in the materials balance equation and (2) substituting measured values and their error standard deviations into this relation and calculating the variance of the materials balance. MAVARIC (Materials Accounting VARIance Calculations) is a custom spreadsheet, designed using the second release of Lotus 1-2-3, that significantly reduces the effort required to make the necessary variance (and covariance) calculations needed to determine the detection sensitivity of a materials accounting system. Predefined macros within the spreadsheet allow the user to carry out long, tedious procedures with only a few keystrokes. MAVARIC requires that the user enter the following data into one of four data tables, depending on the type of the term in the materials balance equation; the SNM concentration, the bulk mass (or solution volume), the measurement error standard deviations, and the number of measurements made during an accounting period. The user can also specify if there are correlations between transfer terms. Based on these data entries, MAVARIC can calculate the variance of the materials balance and the square root of this variance, from which the detection sensitivity of the accounting system can be determined

  9. Global Variance Risk Premium and Forex Return Predictability

    OpenAIRE

    Aloosh, Arash

    2014-01-01

    In a long-run risk model with stochastic volatility and frictionless markets, I express expected forex returns as a function of consumption growth variances and stock variance risk premiums (VRPs)—the difference between the risk-neutral and statistical expectations of market return variation. This provides a motivation for using the forward-looking information available in stock market volatility indices to predict forex returns. Empirically, I find that stock VRPs predict forex returns at a ...

  10. A Neural Network Controller for Variable-Speed Variable-Pitch Wind Energy Conversion Systems Using Generalized Minimum Entropy Criterion

    Directory of Open Access Journals (Sweden)

    Mifeng Ren

    2014-01-01

    Full Text Available This paper considers the neural network controller design problem for variable pitch wind energy conversion systems (WECS with non-Gaussian wind speed disturbances in the stochastic distribution control framework. The approach here is used to directly model the unknown control law based on a fixed neural network (the number of layers and nodes in a neural network is fixed without the need to construct a separate model for the WECS. In order to characterize the randomness of the WECS, a generalized minimum entropy criterion is established to train connection weights of the neural network. For the train purpose, both kernel density estimation method and sliding window technique are adopted to estimate the PDF of tracking error and entropies. Due to the unknown process dynamics, the gradient of the objective function in a gradient-descent-type algorithm is estimated using an incremental perturbation method. The proposed approach is illustrated on a simulated WECS with non-Gaussian wind speed.

  11. Variance components for body weight in Japanese quails (Coturnix japonica

    Directory of Open Access Journals (Sweden)

    RO Resende

    2005-03-01

    Full Text Available The objective of this study was to estimate the variance components for body weight in Japanese quails by Bayesian procedures. The body weight at hatch (BWH and at 7 (BW07, 14 (BW14, 21 (BW21 and 28 days of age (BW28 of 3,520 quails was recorded from August 2001 to June 2002. A multiple-trait animal model with additive genetic, maternal environment and residual effects was implemented by Gibbs sampling methodology. A single Gibbs sampling with 80,000 rounds was generated by the program MTGSAM (Multiple Trait Gibbs Sampling in Animal Model. Normal and inverted Wishart distributions were used as prior distributions for the random effects and the variance components, respectively. Variance components were estimated based on the 500 samples that were left after elimination of 30,000 rounds in the burn-in period and 100 rounds of each thinning interval. The posterior means of additive genetic variance components were 0.15; 4.18; 14.62; 27.18 and 32.68; the posterior means of maternal environment variance components were 0.23; 1.29; 2.76; 4.12 and 5.16; and the posterior means of residual variance components were 0.084; 6.43; 22.66; 31.21 and 30.85, at hatch, 7, 14, 21 and 28 days old, respectively. The posterior means of heritability were 0.33; 0.35; 0.36; 0.43 and 0.47 at hatch, 7, 14, 21 and 28 days old, respectively. These results indicate that heritability increased with age. On the other hand, after hatch there was a marked reduction in the maternal environment variance proportion of the phenotypic variance, whose estimates were 0.50; 0.11; 0.07; 0.07 and 0.08 for BWH, BW07, BW14, BW21 and BW28, respectively. The genetic correlation between weights at different ages was high, except for those estimates between BWH and weight at other ages. Changes in body weight of quails can be efficiently achieved by selection.

  12. Adaptive control method for core power control in TRIGA Mark II reactor

    Science.gov (United States)

    Sabri Minhat, Mohd; Selamat, Hazlina; Subha, Nurul Adilla Mohd

    2018-01-01

    The 1MWth Reactor TRIGA PUSPATI (RTP) Mark II type has undergone more than 35 years of operation. The existing core power control uses feedback control algorithm (FCA). It is challenging to keep the core power stable at the desired value within acceptable error bands to meet the safety demand of RTP due to the sensitivity of nuclear research reactor operation. Currently, the system is not satisfied with power tracking performance and can be improved. Therefore, a new design core power control is very important to improve the current performance in tracking and regulate reactor power by control the movement of control rods. In this paper, the adaptive controller and focus on Model Reference Adaptive Control (MRAC) and Self-Tuning Control (STC) were applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, adaptive controller model, and control rods selection programming. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The adaptive control model was presented using Lyapunov method to ensure stable close loop system and STC Generalised Minimum Variance (GMV) Controller was not necessary to know the exact plant transfer function in designing the core power control. The performance between proposed adaptive control and FCA will be compared via computer simulation and analysed the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.

  13. 29 CFR 1920.2 - Variances.

    Science.gov (United States)

    2010-07-01

    ...) PROCEDURE FOR VARIATIONS FROM SAFETY AND HEALTH REGULATIONS UNDER THE LONGSHOREMEN'S AND HARBOR WORKERS...) or 6(d) of the Williams-Steiger Occupational Safety and Health Act of 1970 (29 U.S.C. 655). The... under the Williams-Steiger Occupational Safety and Health Act of 1970, and any variance from §§ 1910.13...

  14. Zero-intelligence realized variance estimation

    NARCIS (Netherlands)

    Gatheral, J.; Oomen, R.C.A.

    2010-01-01

    Given a time series of intra-day tick-by-tick price data, how can realized variance be estimated? The obvious estimator—the sum of squared returns between trades—is biased by microstructure effects such as bid-ask bounce and so in the past, practitioners were advised to drop most of the data and

  15. Parameter uncertainty effects on variance-based sensitivity analysis

    International Nuclear Information System (INIS)

    Yu, W.; Harris, T.J.

    2009-01-01

    In the past several years there has been considerable commercial and academic interest in methods for variance-based sensitivity analysis. The industrial focus is motivated by the importance of attributing variance contributions to input factors. A more complete understanding of these relationships enables companies to achieve goals related to quality, safety and asset utilization. In a number of applications, it is possible to distinguish between two types of input variables-regressive variables and model parameters. Regressive variables are those that can be influenced by process design or by a control strategy. With model parameters, there are typically no opportunities to directly influence their variability. In this paper, we propose a new method to perform sensitivity analysis through a partitioning of the input variables into these two groupings: regressive variables and model parameters. A sequential analysis is proposed, where first an sensitivity analysis is performed with respect to the regressive variables. In the second step, the uncertainty effects arising from the model parameters are included. This strategy can be quite useful in understanding process variability and in developing strategies to reduce overall variability. When this method is used for nonlinear models which are linear in the parameters, analytical solutions can be utilized. In the more general case of models that are nonlinear in both the regressive variables and the parameters, either first order approximations can be used, or numerically intensive methods must be used

  16. A Variance Distribution Model of Surface EMG Signals Based on Inverse Gamma Distribution.

    Science.gov (United States)

    Hayashi, Hideaki; Furui, Akira; Kurita, Yuichi; Tsuji, Toshio

    2017-11-01

    Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this variance. Variance distribution estimation based on marginal likelihood maximization is also outlined in this paper. The procedure can be approximated using rectified and smoothed EMG signals, thereby allowing the determination of distribution parameters in real time at low computational cost. Results: A simulation experiment was performed to evaluate the accuracy of distribution estimation using artificially generated EMG signals, with results demonstrating that the proposed model's accuracy is higher than that of maximum-likelihood-based estimation. Analysis of variance distribution using real EMG data also suggested a relationship between variance distribution and signal-dependent noise. Conclusion: The study reported here was conducted to examine the performance of a proposed surface EMG model capable of representing variance distribution and a related distribution parameter estimation method. Experiments using artificial and real EMG data demonstrated the validity of the model. Significance: Variance distribution estimated using the proposed model exhibits potential in the estimation of muscle force. Objective: This paper describes the formulation of a surface electromyogram (EMG) model capable of representing the variance distribution of EMG signals. Methods: In the model, EMG signals are handled based on a Gaussian white noise process with a mean of zero for each variance value. EMG signal variance is taken as a random variable that follows inverse gamma distribution, allowing the representation of noise superimposed onto this

  17. The mean and variance of phylogenetic diversity under rarefaction.

    Science.gov (United States)

    Nipperess, David A; Matsen, Frederick A

    2013-06-01

    Phylogenetic diversity (PD) depends on sampling depth, which complicates the comparison of PD between samples of different depth. One approach to dealing with differing sample depth for a given diversity statistic is to rarefy, which means to take a random subset of a given size of the original sample. Exact analytical formulae for the mean and variance of species richness under rarefaction have existed for some time but no such solution exists for PD.We have derived exact formulae for the mean and variance of PD under rarefaction. We confirm that these formulae are correct by comparing exact solution mean and variance to that calculated by repeated random (Monte Carlo) subsampling of a dataset of stem counts of woody shrubs of Toohey Forest, Queensland, Australia. We also demonstrate the application of the method using two examples: identifying hotspots of mammalian diversity in Australasian ecoregions, and characterising the human vaginal microbiome.There is a very high degree of correspondence between the analytical and random subsampling methods for calculating mean and variance of PD under rarefaction, although the Monte Carlo method requires a large number of random draws to converge on the exact solution for the variance.Rarefaction of mammalian PD of ecoregions in Australasia to a common standard of 25 species reveals very different rank orderings of ecoregions, indicating quite different hotspots of diversity than those obtained for unrarefied PD. The application of these methods to the vaginal microbiome shows that a classical score used to quantify bacterial vaginosis is correlated with the shape of the rarefaction curve.The analytical formulae for the mean and variance of PD under rarefaction are both exact and more efficient than repeated subsampling. Rarefaction of PD allows for many applications where comparisons of samples of different depth is required.

  18. 5 CFR 551.301 - Minimum wage.

    Science.gov (United States)

    2010-01-01

    ... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Minimum wage. 551.301 Section 551.301... FAIR LABOR STANDARDS ACT Minimum Wage Provisions Basic Provision § 551.301 Minimum wage. (a)(1) Except... employees wages at rates not less than the minimum wage specified in section 6(a)(1) of the Act for all...

  19. Using variances to comply with resource conservation and recovery act treatment standards

    International Nuclear Information System (INIS)

    Ranek, N.L.

    2002-01-01

    When a waste generated, treated, or disposed of at a site in the United States is classified as hazardous under the Resource Conservation and Recovery Act and is destined for land disposal, the waste manager responsible for that site must select an approach to comply with land disposal restrictions (LDR) treatment standards. This paper focuses on the approach of obtaining a variance from existing, applicable LDR treatment standards. It describes the types of available variances, which include (1) determination of equivalent treatment (DET); (2) treatability variance; and (3) treatment variance for contaminated soil. The process for obtaining each type of variance is also described. Data are presented showing that historically the U.S. Environmental Protection Agency (EPA) processed DET petitions within one year of their date of submission. However, a 1999 EPA policy change added public participation to the DET petition review, which may lengthen processing time in the future. Regarding site-specific treatability variances, data are presented showing an EPA processing time of between 10 and 16 months. Only one generically applicable treatability variance has been granted, which took 30 months to process. No treatment variances for contaminated soil, which were added to the federal LDR program in 1998, are identified as having been granted.

  20. Unraveling the genetic architecture of environmental variance of somatic cell score using high-density single nucleotide polymorphism and cow data from experimental farms

    NARCIS (Netherlands)

    Mulder, H.A.; Crump, R.E.; Calus, M.P.L.; Veerkamp, R.F.

    2013-01-01

    In recent years, it has been shown that not only is the phenotype under genetic control, but also the environmental variance. Very little, however, is known about the genetic architecture of environmental variance. The main objective of this study was to unravel the genetic architecture of the mean

  1. Gini estimation under infinite variance

    NARCIS (Netherlands)

    A. Fontanari (Andrea); N.N. Taleb (Nassim Nicholas); P. Cirillo (Pasquale)

    2018-01-01

    textabstractWe study the problems related to the estimation of the Gini index in presence of a fat-tailed data generating process, i.e. one in the stable distribution class with finite mean but infinite variance (i.e. with tail index α∈(1,2)). We show that, in such a case, the Gini coefficient

  2. Quality control of radiation counting systems and measurement of minimum detectable activity

    International Nuclear Information System (INIS)

    Song, Byoung Chul; Han, Sung Sim; Kim, Young Bok; Jee, Kwang Yong; Sohn, Se Chul

    2004-01-01

    Various radiation counters have been using to determine radioactivity of radwastes for disposal. A radiation counting system was set up using a radiation detector chosen in this study and its stability was investigated through the periodic determination of background and counting efficiencies in accordance with a quality control program to increase the confidence level. The average background level for the γ-spectrometer was 1.59 cps and the average counting level for the standard sample was 45248 dps within 20 confidence levels. The average alpha background level for the low background α/β counting system was 0.31 cpm and the efficiency for alpha counting was 34.38 %. The average beta background level for the α/β counting system was 1.30 cpm and the efficiency for beta counting was 46.5%. The background level in the region of 3H and 14C for the liquid scintillation counting system was 2.52 and 3.31 cpm and the efficiency for alpha counting was 58.5 and 95.6%, respectively. The minimum detectable activity for the γ-spectrometer was found to be 3.2 Bq/mL and 3.8 Bq/mL for the liquid scintillation counter, and 20.5 and 23.0 Bq/mL, respectively for the α and β counting system

  3. Replica approach to mean-variance portfolio optimization

    Science.gov (United States)

    Varga-Haszonits, Istvan; Caccioli, Fabio; Kondor, Imre

    2016-12-01

    We consider the problem of mean-variance portfolio optimization for a generic covariance matrix subject to the budget constraint and the constraint for the expected return, with the application of the replica method borrowed from the statistical physics of disordered systems. We find that the replica symmetry of the solution does not need to be assumed, but emerges as the unique solution of the optimization problem. We also check the stability of this solution and find that the eigenvalues of the Hessian are positive for r  =  N/T  optimal in-sample variance is found to vanish at the critical point inversely proportional to the divergent estimation error.

  4. Realized Variance and Market Microstructure Noise

    DEFF Research Database (Denmark)

    Hansen, Peter R.; Lunde, Asger

    2006-01-01

    We study market microstructure noise in high-frequency data and analyze its implications for the realized variance (RV) under a general specification for the noise. We show that kernel-based estimators can unearth important characteristics of market microstructure noise and that a simple kernel......-based estimator dominates the RV for the estimation of integrated variance (IV). An empirical analysis of the Dow Jones Industrial Average stocks reveals that market microstructure noise its time-dependent and correlated with increments in the efficient price. This has important implications for volatility...... estimation based on high-frequency data. Finally, we apply cointegration techniques to decompose transaction prices and bid-ask quotes into an estimate of the efficient price and noise. This framework enables us to study the dynamic effects on transaction prices and quotes caused by changes in the efficient...

  5. Spot Variance Path Estimation and its Application to High Frequency Jump Testing

    NARCIS (Netherlands)

    Bos, C.S.; Janus, P.; Koopman, S.J.

    2012-01-01

    This paper considers spot variance path estimation from datasets of intraday high-frequency asset prices in the presence of diurnal variance patterns, jumps, leverage effects, and microstructure noise. We rely on parametric and nonparametric methods. The estimated spot variance path can be used to

  6. ANALISIS PORTOFOLIO RESAMPLED EFFICIENT FRONTIER BERDASARKAN OPTIMASI MEAN-VARIANCE

    OpenAIRE

    Abdurakhman, Abdurakhman

    2008-01-01

    Keputusan alokasi asset yang tepat pada investasi portofolio dapat memaksimalkan keuntungan dan atau meminimalkan risiko. Metode yang sering dipakai dalam optimasi portofolio adalah metode Mean-Variance Markowitz. Dalam prakteknya, metode ini mempunyai kelemahan tidak terlalu stabil. Sedikit perubahan dalam estimasi parameter input menyebabkan perubahan besar pada komposisi portofolio. Untuk itu dikembangkan metode optimasi portofolio yang dapat mengatasi ketidakstabilan metode Mean-Variance ...

  7. Mean-variance Optimal Reinsurance-investment Strategy in Continuous Time

    OpenAIRE

    Daheng Peng; Fang Zhang

    2017-01-01

    In this paper, Lagrange method is used to solve the continuous-time mean-variance reinsurance-investment problem. Proportional reinsurance, multiple risky assets and risk-free asset are considered synthetically in the optimal strategy for insurers. By solving the backward stochastic differential equation for the Lagrange multiplier, we get the mean-variance optimal reinsurance-investment strategy and its effective frontier in explicit forms.

  8. The asymptotic variance of departures in critically loaded queues

    NARCIS (Netherlands)

    Al Hanbali, Ahmad; Mandjes, M.R.H.; Nazarathy, Y.; Whitt, W.

    2011-01-01

    We consider the asymptotic variance of the departure counting process D(t) of the GI/G/1 queue; D(t) denotes the number of departures up to time t. We focus on the case where the system load ϱ equals 1, and prove that the asymptotic variance rate satisfies limt→∞varD(t) / t = λ(1 - 2 / π)(ca2 +

  9. Coupled bias-variance tradeoff for cross-pose face recognition.

    Science.gov (United States)

    Li, Annan; Shan, Shiguang; Gao, Wen

    2012-01-01

    Subspace-based face representation can be looked as a regression problem. From this viewpoint, we first revisited the problem of recognizing faces across pose differences, which is a bottleneck in face recognition. Then, we propose a new approach for cross-pose face recognition using a regressor with a coupled bias-variance tradeoff. We found that striking a coupled balance between bias and variance in regression for different poses could improve the regressor-based cross-pose face representation, i.e., the regressor can be more stable against a pose difference. With the basic idea, ridge regression and lasso regression are explored. Experimental results on CMU PIE, the FERET, and the Multi-PIE face databases show that the proposed bias-variance tradeoff can achieve considerable reinforcement in recognition performance.

  10. Monte Carlo variance reduction approaches for non-Boltzmann tallies

    International Nuclear Information System (INIS)

    Booth, T.E.

    1992-12-01

    Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed

  11. Sensitivity analysis of simulated SOA loadings using a variance-based statistical approach: SENSITIVITY ANALYSIS OF SOA

    Energy Technology Data Exchange (ETDEWEB)

    Shrivastava, Manish [Pacific Northwest National Laboratory, Richland Washington USA; Zhao, Chun [Pacific Northwest National Laboratory, Richland Washington USA; Easter, Richard C. [Pacific Northwest National Laboratory, Richland Washington USA; Qian, Yun [Pacific Northwest National Laboratory, Richland Washington USA; Zelenyuk, Alla [Pacific Northwest National Laboratory, Richland Washington USA; Fast, Jerome D. [Pacific Northwest National Laboratory, Richland Washington USA; Liu, Ying [Pacific Northwest National Laboratory, Richland Washington USA; Zhang, Qi [Department of Environmental Toxicology, University of California Davis, California USA; Guenther, Alex [Department of Earth System Science, University of California, Irvine California USA

    2016-04-08

    We investigate the sensitivity of secondary organic aerosol (SOA) loadings simulated by a regional chemical transport model to 7 selected tunable model parameters: 4 involving emissions of anthropogenic and biogenic volatile organic compounds, anthropogenic semi-volatile and intermediate volatility organics (SIVOCs), and NOx, 2 involving dry deposition of SOA precursor gases, and one involving particle-phase transformation of SOA to low volatility. We adopt a quasi-Monte Carlo sampling approach to effectively sample the high-dimensional parameter space, and perform a 250 member ensemble of simulations using a regional model, accounting for some of the latest advances in SOA treatments based on our recent work. We then conduct a variance-based sensitivity analysis using the generalized linear model method to study the responses of simulated SOA loadings to the tunable parameters. Analysis of SOA variance from all 250 simulations shows that the volatility transformation parameter, which controls whether particle-phase transformation of SOA from semi-volatile SOA to non-volatile is on or off, is the dominant contributor to variance of simulated surface-level daytime SOA (65% domain average contribution). We also split the simulations into 2 subsets of 125 each, depending on whether the volatility transformation is turned on/off. For each subset, the SOA variances are dominated by the parameters involving biogenic VOC and anthropogenic SIVOC emissions. Furthermore, biogenic VOC emissions have a larger contribution to SOA variance when the SOA transformation to non-volatile is on, while anthropogenic SIVOC emissions have a larger contribution when the transformation is off. NOx contributes less than 4.3% to SOA variance, and this low contribution is mainly attributed to dominance of intermediate to high NOx conditions throughout the simulated domain. The two parameters related to dry deposition of SOA precursor gases also have very low contributions to SOA variance

  12. Population Bottlenecks Increase Additive Genetic Variance But Do Not Break a Selection Limit in Rainforest Drosophila

    DEFF Research Database (Denmark)

    van Heerwaarden, Belinda; Willi, Yvonne; Kristensen, Torsten N

    2008-01-01

    for desiccation resistance in the rain forest-restricted fly Drosophila bunnanda. After one generation of single-pair mating, additive genetic variance for desiccation resistance increased to a significant level, on average higher than for the control lines. Line crosses revealed that both dominance and epistatic...

  13. Explicit formulas for the variance of discounted life-cycle cost

    International Nuclear Information System (INIS)

    Noortwijk, Jan M. van

    2003-01-01

    In life-cycle costing analyses, optimal design is usually achieved by minimising the expected value of the discounted costs. As well as the expected value, the corresponding variance may be useful for estimating, for example, the uncertainty bounds of the calculated discounted costs. However, general explicit formulas for calculating the variance of the discounted costs over an unbounded time horizon are not yet available. In this paper, explicit formulas for this variance are presented. They can be easily implemented in software to optimise structural design and maintenance management. The use of the mathematical results is illustrated with some examples

  14. How does variance in fertility change over the demographic transition?

    Science.gov (United States)

    Hruschka, Daniel J; Burger, Oskar

    2016-04-19

    Most work on the human fertility transition has focused on declines in mean fertility. However, understanding changes in the variance of reproductive outcomes can be equally important for evolutionary questions about the heritability of fertility, individual determinants of fertility and changing patterns of reproductive skew. Here, we document how variance in completed fertility among women (45-49 years) differs across 200 surveys in 72 low- to middle-income countries where fertility transitions are currently in progress at various stages. Nearly all (91%) of samples exhibit variance consistent with a Poisson process of fertility, which places systematic, and often severe, theoretical upper bounds on the proportion of variance that can be attributed to individual differences. In contrast to the pattern of total variance, these upper bounds increase from high- to mid-fertility samples, then decline again as samples move from mid to low fertility. Notably, the lowest fertility samples often deviate from a Poisson process. This suggests that as populations move to low fertility their reproduction shifts from a rate-based process to a focus on an ideal number of children. We discuss the implications of these findings for predicting completed fertility from individual-level variables. © 2016 The Author(s).

  15. Mean-variance Optimal Reinsurance-investment Strategy in Continuous Time

    Directory of Open Access Journals (Sweden)

    Daheng Peng

    2017-10-01

    Full Text Available In this paper, Lagrange method is used to solve the continuous-time mean-variance reinsurance-investment problem. Proportional reinsurance, multiple risky assets and risk-free asset are considered synthetically in the optimal strategy for insurers. By solving the backward stochastic differential equation for the Lagrange multiplier, we get the mean-variance optimal reinsurance-investment strategy and its effective frontier in explicit forms.

  16. Using variance structure to quantify responses to perturbation in fish catches

    Science.gov (United States)

    Vidal, Tiffany E.; Irwin, Brian J.; Wagner, Tyler; Rudstam, Lars G.; Jackson, James R.; Bence, James R.

    2017-01-01

    We present a case study evaluation of gill-net catches of Walleye Sander vitreus to assess potential effects of large-scale changes in Oneida Lake, New York, including the disruption of trophic interactions by double-crested cormorants Phalacrocorax auritus and invasive dreissenid mussels. We used the empirical long-term gill-net time series and a negative binomial linear mixed model to partition the variability in catches into spatial and coherent temporal variance components, hypothesizing that variance partitioning can help quantify spatiotemporal variability and determine whether variance structure differs before and after large-scale perturbations. We found that the mean catch and the total variability of catches decreased following perturbation but that not all sampling locations responded in a consistent manner. There was also evidence of some spatial homogenization concurrent with a restructuring of the relative productivity of individual sites. Specifically, offshore sites generally became more productive following the estimated break point in the gill-net time series. These results provide support for the idea that variance structure is responsive to large-scale perturbations; therefore, variance components have potential utility as statistical indicators of response to a changing environment more broadly. The modeling approach described herein is flexible and would be transferable to other systems and metrics. For example, variance partitioning could be used to examine responses to alternative management regimes, to compare variability across physiographic regions, and to describe differences among climate zones. Understanding how individual variance components respond to perturbation may yield finer-scale insights into ecological shifts than focusing on patterns in the mean responses or total variability alone.

  17. A mean–variance objective for robust production optimization in uncertain geological scenarios

    DEFF Research Database (Denmark)

    Capolei, Andrea; Suwartadi, Eka; Foss, Bjarne

    2014-01-01

    directly. In the mean–variance bi-criterion objective function risk appears directly, it also considers an ensemble of reservoir models, and has robust optimization as a special extreme case. The mean–variance objective is common for portfolio optimization problems in finance. The Markowitz portfolio...... optimization problem is the original and simplest example of a mean–variance criterion for mitigating risk. Risk is mitigated in oil production by including both the expected NPV (mean of NPV) and the risk (variance of NPV) for the ensemble of possible reservoir models. With the inclusion of the risk...

  18. Minimum income protection in the Netherlands

    NARCIS (Netherlands)

    van Peijpe, T.

    2009-01-01

    This article offers an overview of the Dutch legal system of minimum income protection through collective bargaining, social security, and statutory minimum wages. In addition to collective agreements, the Dutch statutory minimum wage offers income protection to a small number of workers. Its

  19. Energy-minimum sub-threshold self-timed circuits using current-sensing completion detection

    DEFF Research Database (Denmark)

    Akgun, O. C.; Rodrigues, J. N.; Sparsø, Jens

    2011-01-01

    This study addresses the design of self-timed energy-minimum circuits, operating in the sub-VT domain and a generic implementation template using bundled-data circuitry and current sensing completion detection (CSCD). Furthermore, a fully decoupled latch controller was developed, which integrates......V. Spice simulations indicate a gain of 52.58% in throughput because of asynchronous operation. By trading the throughput improvement, energy dissipation is reduced by 16.8% at the energy-minimum supply voltage....

  20. Asymptotic variance of grey-scale surface area estimators

    DEFF Research Database (Denmark)

    Svane, Anne Marie

    Grey-scale local algorithms have been suggested as a fast way of estimating surface area from grey-scale digital images. Their asymptotic mean has already been described. In this paper, the asymptotic behaviour of the variance is studied in isotropic and sufficiently smooth settings, resulting...... in a general asymptotic bound. For compact convex sets with nowhere vanishing Gaussian curvature, the asymptotics can be described more explicitly. As in the case of volume estimators, the variance is decomposed into a lattice sum and an oscillating term of at most the same magnitude....

  1. Prediction-error variance in Bayesian model updating: a comparative study

    Science.gov (United States)

    Asadollahi, Parisa; Li, Jian; Huang, Yong

    2017-04-01

    In Bayesian model updating, the likelihood function is commonly formulated by stochastic embedding in which the maximum information entropy probability model of prediction error variances plays an important role and it is Gaussian distribution subject to the first two moments as constraints. The selection of prediction error variances can be formulated as a model class selection problem, which automatically involves a trade-off between the average data-fit of the model class and the information it extracts from the data. Therefore, it is critical for the robustness in the updating of the structural model especially in the presence of modeling errors. To date, three ways of considering prediction error variances have been seem in the literature: 1) setting constant values empirically, 2) estimating them based on the goodness-of-fit of the measured data, and 3) updating them as uncertain parameters by applying Bayes' Theorem at the model class level. In this paper, the effect of different strategies to deal with the prediction error variances on the model updating performance is investigated explicitly. A six-story shear building model with six uncertain stiffness parameters is employed as an illustrative example. Transitional Markov Chain Monte Carlo is used to draw samples of the posterior probability density function of the structure model parameters as well as the uncertain prediction variances. The different levels of modeling uncertainty and complexity are modeled through three FE models, including a true model, a model with more complexity, and a model with modeling error. Bayesian updating is performed for the three FE models considering the three aforementioned treatments of the prediction error variances. The effect of number of measurements on the model updating performance is also examined in the study. The results are compared based on model class assessment and indicate that updating the prediction error variances as uncertain parameters at the model

  2. Prediction technique for minimum-heat-flux (MHF)- point condition of saturated pool boiling

    International Nuclear Information System (INIS)

    Nishio, Shigefumi

    1987-01-01

    The temperature-controlled hypothesis for the minimum-heat-flux (MHF)-point condition, in which the MHF-point temperature is regarded as the controlling factor and is expected to be independent of surface configuration and dimensions, is inductively investigated for saturated pool-boiling. In this paper such features of the MHF-point condition are experimentally proved first. Secondly, a correlation of the MHF-point temperature is developed for the effect of system pressure. Finally, a simple technique based on this correlation is presented to estimate the effects of surface configuration, dimensions and system pressure on the minimum heat flux. (author)

  3. Estimation of noise-free variance to measure heterogeneity.

    Directory of Open Access Journals (Sweden)

    Tilo Winkler

    Full Text Available Variance is a statistical parameter used to characterize heterogeneity or variability in data sets. However, measurements commonly include noise, as random errors superimposed to the actual value, which may substantially increase the variance compared to a noise-free data set. Our aim was to develop and validate a method to estimate noise-free spatial heterogeneity of pulmonary perfusion using dynamic positron emission tomography (PET scans. On theoretical grounds, we demonstrate a linear relationship between the total variance of a data set derived from averages of n multiple measurements, and the reciprocal of n. Using multiple measurements with varying n yields estimates of the linear relationship including the noise-free variance as the constant parameter. In PET images, n is proportional to the number of registered decay events, and the variance of the image is typically normalized by the square of its mean value yielding a coefficient of variation squared (CV(2. The method was evaluated with a Jaszczak phantom as reference spatial heterogeneity (CV(r(2 for comparison with our estimate of noise-free or 'true' heterogeneity (CV(t(2. We found that CV(t(2 was only 5.4% higher than CV(r2. Additional evaluations were conducted on 38 PET scans of pulmonary perfusion using (13NN-saline injection. The mean CV(t(2 was 0.10 (range: 0.03-0.30, while the mean CV(2 including noise was 0.24 (range: 0.10-0.59. CV(t(2 was in average 41.5% of the CV(2 measured including noise (range: 17.8-71.2%. The reproducibility of CV(t(2 was evaluated using three repeated PET scans from five subjects. Individual CV(t(2 were within 16% of each subject's mean and paired t-tests revealed no difference among the results from the three consecutive PET scans. In conclusion, our method provides reliable noise-free estimates of CV(t(2 in PET scans, and may be useful for similar statistical problems in experimental data.

  4. A characterization of optimal portfolios under the tail mean-variance criterion

    OpenAIRE

    Owadally, I.; Landsman, Z.

    2013-01-01

    The tail mean–variance model was recently introduced for use in risk management and portfolio choice; it involves a criterion that focuses on the risk of rare but large losses, which is particularly important when losses have heavy-tailed distributions. If returns or losses follow a multivariate elliptical distribution, the use of risk measures that satisfy certain well-known properties is equivalent to risk management in the classical mean–variance framework. The tail mean–variance criterion...

  5. Gender variance in childhood and sexual orientation in adulthood: a prospective study.

    Science.gov (United States)

    Steensma, Thomas D; van der Ende, Jan; Verhulst, Frank C; Cohen-Kettenis, Peggy T

    2013-11-01

    Several retrospective and prospective studies have reported on the association between childhood gender variance and sexual orientation and gender discomfort in adulthood. In most of the retrospective studies, samples were drawn from the general population. The samples in the prospective studies consisted of clinically referred children. In understanding the extent to which the association applies for the general population, prospective studies using random samples are needed. This prospective study examined the association between childhood gender variance, and sexual orientation and gender discomfort in adulthood in the general population. In 1983, we measured childhood gender variance, in 406 boys and 473 girls. In 2007, sexual orientation and gender discomfort were assessed. Childhood gender variance was measured with two items from the Child Behavior Checklist/4-18. Sexual orientation was measured for four parameters of sexual orientation (attraction, fantasy, behavior, and identity). Gender discomfort was assessed by four questions (unhappiness and/or uncertainty about one's gender, wish or desire to be of the other gender, and consideration of living in the role of the other gender). For both men and women, the presence of childhood gender variance was associated with homosexuality for all four parameters of sexual orientation, but not with bisexuality. The report of adulthood homosexuality was 8 to 15 times higher for participants with a history of gender variance (10.2% to 12.2%), compared to participants without a history of gender variance (1.2% to 1.7%). The presence of childhood gender variance was not significantly associated with gender discomfort in adulthood. This study clearly showed a significant association between childhood gender variance and a homosexual sexual orientation in adulthood in the general population. In contrast to the findings in clinically referred gender-variant children, the presence of a homosexual sexual orientation in

  6. 29 CFR 1926.2 - Variances from safety and health standards.

    Science.gov (United States)

    2010-07-01

    ... from safety and health standards. (a) Variances from standards which are, or may be, published in this... 29 Labor 8 2010-07-01 2010-07-01 false Variances from safety and health standards. 1926.2 Section 1926.2 Labor Regulations Relating to Labor (Continued) OCCUPATIONAL SAFETY AND HEALTH ADMINISTRATION...

  7. Integrated identification, modeling and control with applications

    Science.gov (United States)

    Shi, Guojun

    This thesis deals with the integration of system design, identification, modeling and control. In particular, six interdisciplinary engineering problems are addressed and investigated. Theoretical results are established and applied to structural vibration reduction and engine control problems. First, the data-based LQG control problem is formulated and solved. It is shown that a state space model is not necessary to solve this problem; rather a finite sequence from the impulse response is the only model data required to synthesize an optimal controller. The new theory avoids unnecessary reliance on a model, required in the conventional design procedure. The infinite horizon model predictive control problem is addressed for multivariable systems. The basic properties of the receding horizon implementation strategy is investigated and the complete framework for solving the problem is established. The new theory allows the accommodation of hard input constraints and time delays. The developed control algorithms guarantee the closed loop stability. A closed loop identification and infinite horizon model predictive control design procedure is established for engine speed regulation. The developed algorithms are tested on the Cummins Engine Simulator and desired results are obtained. A finite signal-to-noise ratio model is considered for noise signals. An information quality index is introduced which measures the essential information precision required for stabilization. The problems of minimum variance control and covariance control are formulated and investigated. Convergent algorithms are developed for solving the problems of interest. The problem of the integrated passive and active control design is addressed in order to improve the overall system performance. A design algorithm is developed, which simultaneously finds: (i) the optimal values of the stiffness and damping ratios for the structure, and (ii) an optimal output variance constrained stabilizing

  8. Allowing variance may enlarge the safe operating space for exploited ecosystems.

    Science.gov (United States)

    Carpenter, Stephen R; Brock, William A; Folke, Carl; van Nes, Egbert H; Scheffer, Marten

    2015-11-17

    Variable flows of food, water, or other ecosystem services complicate planning. Management strategies that decrease variability and increase predictability may therefore be preferred. However, actions to decrease variance over short timescales (2-4 y), when applied continuously, may lead to long-term ecosystem changes with adverse consequences. We investigated the effects of managing short-term variance in three well-understood models of ecosystem services: lake eutrophication, harvest of a wild population, and yield of domestic herbivores on a rangeland. In all cases, actions to decrease variance can increase the risk of crossing critical ecosystem thresholds, resulting in less desirable ecosystem states. Managing to decrease short-term variance creates ecosystem fragility by changing the boundaries of safe operating spaces, suppressing information needed for adaptive management, cancelling signals of declining resilience, and removing pressures that may build tolerance of stress. Thus, the management of variance interacts strongly and inseparably with the management of resilience. By allowing for variation, learning, and flexibility while observing change, managers can detect opportunities and problems as they develop while sustaining the capacity to deal with them.

  9. Temperature variance study in Monte-Carlo photon transport theory

    International Nuclear Information System (INIS)

    Giorla, J.

    1985-10-01

    We study different Monte-Carlo methods for solving radiative transfer problems, and particularly Fleck's Monte-Carlo method. We first give the different time-discretization schemes and the corresponding stability criteria. Then we write the temperature variance as a function of the variances of temperature and absorbed energy at the previous time step. Finally we obtain some stability criteria for the Monte-Carlo method in the stationary case [fr

  10. Aseptic minimum volume vitrification technique for porcine parthenogenetically activated blastocyst.

    Science.gov (United States)

    Lin, Lin; Yu, Yutao; Zhang, Xiuqing; Yang, Huanming; Bolund, Lars; Callesen, Henrik; Vajta, Gábor

    2011-01-01

    Minimum volume vitrification may provide extremely high cooling and warming rates if the sample and the surrounding medium contacts directly with the respective liquid nitrogen and warming medium. However, this direct contact may result in microbial contamination. In this work, an earlier aseptic technique was applied for minimum volume vitrification. After equilibration, samples were loaded on a plastic film, immersed rapidly into factory derived, filter-sterilized liquid nitrogen, and sealed into sterile, pre-cooled straws. At warming, the straw was cut, the filmstrip was immersed into a 39 degree C warming medium, and the sample was stepwise rehydrated. Cryosurvival rates of porcine blastocysts produced by parthenogenetical activation did not differ from control, vitrified blastocysts with Cryotop. This approach can be used for minimum volume vitrification methods and may be suitable to overcome the biological dangers and legal restrictions that hamper the application of open vitrification techniques.

  11. Study of the variance of a Monte Carlo calculation. Application to weighting; Etude de la variance d'un calcul de Monte Carlo. Application a la ponderation

    Energy Technology Data Exchange (ETDEWEB)

    Lanore, Jeanne-Marie [Commissariat a l' Energie Atomique - CEA, Centre d' Etudes Nucleaires de Fontenay-aux-Roses, Direction des Piles Atomiques, Departement des Etudes de Piles, Service d' Etudes de Protections de Piles (France)

    1969-04-15

    One of the main difficulties in Monte Carlo computations is the estimation of the results variance. Generally, only an apparent variance can be observed over a few calculations, often very different from the actual variance. By studying a large number of short calculations, the authors have tried to evaluate the real variance, and then to apply the obtained results to the optimization of the computations. The program used is the Poker one-dimensional Monte Carlo program. Calculations are performed in two types of fictitious environments: a body with constant cross section, without absorption, where all shocks are elastic and isotropic; a body with variable cross section (presenting a very pronounced peak and hole), with an anisotropy for high energy elastic shocks, and with the possibility of inelastic shocks (this body presents all the features that can appear in a real case)

  12. Adjustment of heterogenous variances and a calving year effect in ...

    African Journals Online (AJOL)

    Data at the beginning and at the end of lactation period, have higher variances than tests in the middle of the lactation. Furthermore, first lactations have lower mean and variances compared to second and third lactations. This is a deviation from the basic assumptions required for the application of repeatability models.

  13. Estimating Predictive Variance for Statistical Gas Distribution Modelling

    International Nuclear Information System (INIS)

    Lilienthal, Achim J.; Asadi, Sahar; Reggente, Matteo

    2009-01-01

    Recent publications in statistical gas distribution modelling have proposed algorithms that model mean and variance of a distribution. This paper argues that estimating the predictive concentration variance entails not only a gradual improvement but is rather a significant step to advance the field. This is, first, since the models much better fit the particular structure of gas distributions, which exhibit strong fluctuations with considerable spatial variations as a result of the intermittent character of gas dispersal. Second, because estimating the predictive variance allows to evaluate the model quality in terms of the data likelihood. This offers a solution to the problem of ground truth evaluation, which has always been a critical issue for gas distribution modelling. It also enables solid comparisons of different modelling approaches, and provides the means to learn meta parameters of the model, to determine when the model should be updated or re-initialised, or to suggest new measurement locations based on the current model. We also point out directions of related ongoing or potential future research work.

  14. Estimating integrated variance in the presence of microstructure noise using linear regression

    Science.gov (United States)

    Holý, Vladimír

    2017-07-01

    Using financial high-frequency data for estimation of integrated variance of asset prices is beneficial but with increasing number of observations so-called microstructure noise occurs. This noise can significantly bias the realized variance estimator. We propose a method for estimation of the integrated variance robust to microstructure noise as well as for testing the presence of the noise. Our method utilizes linear regression in which realized variances estimated from different data subsamples act as dependent variable while the number of observations act as explanatory variable. We compare proposed estimator with other methods on simulated data for several microstructure noise structures.

  15. Girsanov's transformation based variance reduced Monte Carlo simulation schemes for reliability estimation in nonlinear stochastic dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Kanjilal, Oindrila, E-mail: oindrila@civil.iisc.ernet.in; Manohar, C.S., E-mail: manohar@civil.iisc.ernet.in

    2017-07-15

    The study considers the problem of simulation based time variant reliability analysis of nonlinear randomly excited dynamical systems. Attention is focused on importance sampling strategies based on the application of Girsanov's transformation method. Controls which minimize the distance function, as in the first order reliability method (FORM), are shown to minimize a bound on the sampling variance of the estimator for the probability of failure. Two schemes based on the application of calculus of variations for selecting control signals are proposed: the first obtains the control force as the solution of a two-point nonlinear boundary value problem, and, the second explores the application of the Volterra series in characterizing the controls. The relative merits of these schemes, vis-à-vis the method based on ideas from the FORM, are discussed. Illustrative examples, involving archetypal single degree of freedom (dof) nonlinear oscillators, and a multi-degree of freedom nonlinear dynamical system, are presented. The credentials of the proposed procedures are established by comparing the solutions with pertinent results from direct Monte Carlo simulations. - Highlights: • The distance minimizing control forces minimize a bound on the sampling variance. • Establishing Girsanov controls via solution of a two-point boundary value problem. • Girsanov controls via Volterra's series representation for the transfer functions.

  16. Individual and collective bodies: using measures of variance and association in contextual epidemiology.

    Science.gov (United States)

    Merlo, J; Ohlsson, H; Lynch, K F; Chaix, B; Subramanian, S V

    2009-12-01

    Social epidemiology investigates both individuals and their collectives. Although the limits that define the individual bodies are very apparent, the collective body's geographical or cultural limits (eg "neighbourhood") are more difficult to discern. Also, epidemiologists normally investigate causation as changes in group means. However, many variables of interest in epidemiology may cause a change in the variance of the distribution of the dependent variable. In spite of that, variance is normally considered a measure of uncertainty or a nuisance rather than a source of substantive information. This reasoning is also true in many multilevel investigations, whereas understanding the distribution of variance across levels should be fundamental. This means-centric reductionism is mostly concerned with risk factors and creates a paradoxical situation, as social medicine is not only interested in increasing the (mean) health of the population, but also in understanding and decreasing inappropriate health and health care inequalities (variance). Critical essay and literature review. The present study promotes (a) the application of measures of variance and clustering to evaluate the boundaries one uses in defining collective levels of analysis (eg neighbourhoods), (b) the combined use of measures of variance and means-centric measures of association, and (c) the investigation of causes of health variation (variance-altering causation). Both measures of variance and means-centric measures of association need to be included when performing contextual analyses. The variance approach, a new aspect of contextual analysis that cannot be interpreted in means-centric terms, allows perspectives to be expanded.

  17. Genetic heterogeneity of within-family variance of body weight in Atlantic salmon (Salmo salar).

    Science.gov (United States)

    Sonesson, Anna K; Odegård, Jørgen; Rönnegård, Lars

    2013-10-17

    Canalization is defined as the stability of a genotype against minor variations in both environment and genetics. Genetic variation in degree of canalization causes heterogeneity of within-family variance. The aims of this study are twofold: (1) quantify genetic heterogeneity of (within-family) residual variance in Atlantic salmon and (2) test whether the observed heterogeneity of (within-family) residual variance can be explained by simple scaling effects. Analysis of body weight in Atlantic salmon using a double hierarchical generalized linear model (DHGLM) revealed substantial heterogeneity of within-family variance. The 95% prediction interval for within-family variance ranged from ~0.4 to 1.2 kg2, implying that the within-family variance of the most extreme high families is expected to be approximately three times larger than the extreme low families. For cross-sectional data, DHGLM with an animal mean sub-model resulted in severe bias, while a corresponding sire-dam model was appropriate. Heterogeneity of variance was not sensitive to Box-Cox transformations of phenotypes, which implies that heterogeneity of variance exists beyond what would be expected from simple scaling effects. Substantial heterogeneity of within-family variance was found for body weight in Atlantic salmon. A tendency towards higher variance with higher means (scaling effects) was observed, but heterogeneity of within-family variance existed beyond what could be explained by simple scaling effects. For cross-sectional data, using the animal mean sub-model in the DHGLM resulted in biased estimates of variance components, which differed substantially both from a standard linear mean animal model and a sire-dam DHGLM model. Although genetic differences in canalization were observed, selection for increased canalization is difficult, because there is limited individual information for the variance sub-model, especially when based on cross-sectional data. Furthermore, potential macro

  18. The derivative based variance sensitivity analysis for the distribution parameters and its computation

    International Nuclear Information System (INIS)

    Wang, Pan; Lu, Zhenzhou; Ren, Bo; Cheng, Lei

    2013-01-01

    The output variance is an important measure for the performance of a structural system, and it is always influenced by the distribution parameters of inputs. In order to identify the influential distribution parameters and make it clear that how those distribution parameters influence the output variance, this work presents the derivative based variance sensitivity decomposition according to Sobol′s variance decomposition, and proposes the derivative based main and total sensitivity indices. By transforming the derivatives of various orders variance contributions into the form of expectation via kernel function, the proposed main and total sensitivity indices can be seen as the “by-product” of Sobol′s variance based sensitivity analysis without any additional output evaluation. Since Sobol′s variance based sensitivity indices have been computed efficiently by the sparse grid integration method, this work also employs the sparse grid integration method to compute the derivative based main and total sensitivity indices. Several examples are used to demonstrate the rationality of the proposed sensitivity indices and the accuracy of the applied method

  19. Automatic Bayes Factors for Testing Equality- and Inequality-Constrained Hypotheses on Variances.

    Science.gov (United States)

    Böing-Messing, Florian; Mulder, Joris

    2018-05-03

    In comparing characteristics of independent populations, researchers frequently expect a certain structure of the population variances. These expectations can be formulated as hypotheses with equality and/or inequality constraints on the variances. In this article, we consider the Bayes factor for testing such (in)equality-constrained hypotheses on variances. Application of Bayes factors requires specification of a prior under every hypothesis to be tested. However, specifying subjective priors for variances based on prior information is a difficult task. We therefore consider so-called automatic or default Bayes factors. These methods avoid the need for the user to specify priors by using information from the sample data. We present three automatic Bayes factors for testing variances. The first is a Bayes factor with equal priors on all variances, where the priors are specified automatically using a small share of the information in the sample data. The second is the fractional Bayes factor, where a fraction of the likelihood is used for automatic prior specification. The third is an adjustment of the fractional Bayes factor such that the parsimony of inequality-constrained hypotheses is properly taken into account. The Bayes factors are evaluated by investigating different properties such as information consistency and large sample consistency. Based on this evaluation, it is concluded that the adjusted fractional Bayes factor is generally recommendable for testing equality- and inequality-constrained hypotheses on variances.

  20. Minimum Compliance Topology Optimization of Shell-Infill Composites for Additive Manufacturing

    DEFF Research Database (Denmark)

    Wu, Jun; Clausen, Anders; Sigmund, Ole

    2017-01-01

    Additively manufactured parts are often composed of two sub-structures, a solid shell forming their exterior and a porous infill occupying the interior. To account for this feature this paper presents a novel method for generating simultaneously optimized shell and infill in the context of minimum...... interpolation model into a physical density field, upon which the compliance is minimized. Enhanced by an adapted robust formulation for controlling the minimum length scale of the base, our method generates optimized shell-infill composites suitable for additive manufacturing. We demonstrate the effectiveness...

  1. UV spectral fingerprinting and analysis of variance-principal component analysis: a useful tool for characterizing sources of variance in plant materials.

    Science.gov (United States)

    Luthria, Devanand L; Mukhopadhyay, Sudarsan; Robbins, Rebecca J; Finley, John W; Banuelos, Gary S; Harnly, James M

    2008-07-23

    UV spectral fingerprints, in combination with analysis of variance-principal components analysis (ANOVA-PCA), can differentiate between cultivars and growing conditions (or treatments) and can be used to identify sources of variance. Broccoli samples, composed of two cultivars, were grown under seven different conditions or treatments (four levels of Se-enriched irrigation waters, organic farming, and conventional farming with 100 and 80% irrigation based on crop evaporation and transpiration rate). Freeze-dried powdered samples were extracted with methanol-water (60:40, v/v) and analyzed with no prior separation. Spectral fingerprints were acquired for the UV region (220-380 nm) using a 50-fold dilution of the extract. ANOVA-PCA was used to construct subset matrices that permitted easy verification of the hypothesis that cultivar and treatment contributed to a difference in the chemical expression of the broccoli. The sums of the squares of the same matrices were used to show that cultivar, treatment, and analytical repeatability contributed 30.5, 68.3, and 1.2% of the variance, respectively.

  2. MOnthly TEmperature DAtabase of Spain 1951-2010: MOTEDAS (2): The Correlation Decay Distance (CDD) and the spatial variability of maximum and minimum monthly temperature in Spain during (1981-2010).

    Science.gov (United States)

    Cortesi, Nicola; Peña-Angulo, Dhais; Simolo, Claudia; Stepanek, Peter; Brunetti, Michele; Gonzalez-Hidalgo, José Carlos

    2014-05-01

    One of the key point in the develop of the MOTEDAS dataset (see Poster 1 MOTEDAS) in the framework of the HIDROCAES Project (Impactos Hidrológicos del Calentamiento Global en España, Spanish Ministery of Research CGL2011-27574-C02-01) is the reference series for which no generalized metadata exist. In this poster we present an analysis of spatial variability of monthly minimum and maximum temperatures in the conterminous land of Spain (Iberian Peninsula, IP), by using the Correlation Decay Distance function (CDD), with the aim of evaluating, at sub-regional level, the optimal threshold distance between neighbouring stations for producing the set of reference series used in the quality control (see MOTEDAS Poster 1) and the reconstruction (see MOREDAS Poster 3). The CDD analysis for Tmax and Tmin was performed calculating a correlation matrix at monthly scale between 1981-2010 among monthly mean values of maximum (Tmax) and minimum (Tmin) temperature series (with at least 90% of data), free of anomalous data and homogenized (see MOTEDAS Poster 1), obtained from AEMEt archives (National Spanish Meteorological Agency). Monthly anomalies (difference between data and mean 1981-2010) were used to prevent the dominant effect of annual cycle in the CDD annual estimation. For each station, and time scale, the common variance r2 (using the square of Pearson's correlation coefficient) was calculated between all neighbouring temperature series and the relation between r2 and distance was modelled according to the following equation (1): Log (r2ij) = b*°dij (1) being Log(rij2) the common variance between target (i) and neighbouring series (j), dij the distance between them and b the slope of the ordinary least-squares linear regression model applied taking into account only the surrounding stations within a starting radius of 50 km and with a minimum of 5 stations required. Finally, monthly, seasonal and annual CDD values were interpolated using the Ordinary Kriging with a

  3. Adaptive color halftoning for minimum perceived error using the blue noise mask

    Science.gov (United States)

    Yu, Qing; Parker, Kevin J.

    1997-04-01

    Color halftoning using a conventional screen requires careful selection of screen angles to avoid Moire patterns. An obvious advantage of halftoning using a blue noise mask (BNM) is that there are no conventional screen angle or Moire patterns produced. However, a simple strategy of employing the same BNM on all color planes is unacceptable in case where a small registration error can cause objectionable color shifts. In a previous paper by Yao and Parker, strategies were presented for shifting or inverting the BNM as well as using mutually exclusive BNMs for different color planes. In this paper, the above schemes will be studied in CIE-LAB color space in terms of root mean square error and variance for luminance channel and chrominance channel respectively. We will demonstrate that the dot-on-dot scheme results in minimum chrominance error, but maximum luminance error and the 4-mask scheme results in minimum luminance error but maximum chrominance error, while the shift scheme falls in between. Based on this study, we proposed a new adaptive color halftoning algorithm that takes colorimetric color reproduction into account by applying 2-mutually exclusive BNMs on two different color planes and applying an adaptive scheme on other planes to reduce color error. We will show that by having one adaptive color channel, we obtain increased flexibility to manipulate the output so as to reduce colorimetric error while permitting customization to specific printing hardware.

  4. Levine's guide to SPSS for analysis of variance

    CERN Document Server

    Braver, Sanford L; Page, Melanie

    2003-01-01

    A greatly expanded and heavily revised second edition, this popular guide provides instructions and clear examples for running analyses of variance (ANOVA) and several other related statistical tests of significance with SPSS. No other guide offers the program statements required for the more advanced tests in analysis of variance. All of the programs in the book can be run using any version of SPSS, including versions 11 and 11.5. A table at the end of the preface indicates where each type of analysis (e.g., simple comparisons) can be found for each type of design (e.g., mixed two-factor desi

  5. An efficient sampling approach for variance-based sensitivity analysis based on the law of total variance in the successive intervals without overlapping

    Science.gov (United States)

    Yun, Wanying; Lu, Zhenzhou; Jiang, Xian

    2018-06-01

    To efficiently execute the variance-based global sensitivity analysis, the law of total variance in the successive intervals without overlapping is proved at first, on which an efficient space-partition sampling-based approach is subsequently proposed in this paper. Through partitioning the sample points of output into different subsets according to different inputs, the proposed approach can efficiently evaluate all the main effects concurrently by one group of sample points. In addition, there is no need for optimizing the partition scheme in the proposed approach. The maximum length of subintervals is decreased by increasing the number of sample points of model input variables in the proposed approach, which guarantees the convergence condition of the space-partition approach well. Furthermore, a new interpretation on the thought of partition is illuminated from the perspective of the variance ratio function. Finally, three test examples and one engineering application are employed to demonstrate the accuracy, efficiency and robustness of the proposed approach.

  6. Does Public Sector Control Reduce Variance in School Quality?

    Science.gov (United States)

    Pritchett, Lant; Viarengo, Martina

    2015-01-01

    Does the government control of school systems facilitate equality in school quality? Whether centralized or localized control produces more equality depends not only on what "could" happen in principle, but also on what does happen in practice. We use the Programme for International Student Assessment (PISA) database to examine the…

  7. A load factor based mean-variance analysis for fuel diversification

    Energy Technology Data Exchange (ETDEWEB)

    Gotham, Douglas; Preckel, Paul; Ruangpattana, Suriya [State Utility Forecasting Group, Purdue University, West Lafayette, IN (United States); Muthuraman, Kumar [McCombs School of Business, University of Texas, Austin, TX (United States); Rardin, Ronald [Department of Industrial Engineering, University of Arkansas, Fayetteville, AR (United States)

    2009-03-15

    Fuel diversification implies the selection of a mix of generation technologies for long-term electricity generation. The goal is to strike a good balance between reduced costs and reduced risk. The method of analysis that has been advocated and adopted for such studies is the mean-variance portfolio analysis pioneered by Markowitz (Markowitz, H., 1952. Portfolio selection. Journal of Finance 7(1) 77-91). However the standard mean-variance methodology, does not account for the ability of various fuels/technologies to adapt to varying loads. Such analysis often provides results that are easily dismissed by regulators and practitioners as unacceptable, since load cycles play critical roles in fuel selection. To account for such issues and still retain the convenience and elegance of the mean-variance approach, we propose a variant of the mean-variance analysis using the decomposition of the load into various types and utilizing the load factors of each load type. We also illustrate the approach using data for the state of Indiana and demonstrate the ability of the model in providing useful insights. (author)

  8. Understanding the Minimum Wage: Issues and Answers.

    Science.gov (United States)

    Employment Policies Inst. Foundation, Washington, DC.

    This booklet, which is designed to clarify facts regarding the minimum wage's impact on marketplace economics, contains a total of 31 questions and answers pertaining to the following topics: relationship between minimum wages and poverty; impacts of changes in the minimum wage on welfare reform; and possible effects of changes in the minimum wage…

  9. Youth minimum wages and youth employment

    NARCIS (Netherlands)

    Marimpi, Maria; Koning, Pierre

    2018-01-01

    This paper performs a cross-country level analysis on the impact of the level of specific youth minimum wages on the labor market performance of young individuals. We use information on the use and level of youth minimum wages, as compared to the level of adult minimum wages as well as to the median

  10. Discretization of space and time: determining the values of minimum length and minimum time

    OpenAIRE

    Roatta , Luca

    2017-01-01

    Assuming that space and time can only have discrete values, we obtain the expression of the minimum length and the minimum time interval. These values are found to be exactly coincident with the Planck's length and the Planck's time but for the presence of h instead of ħ .

  11. Minimum wage development in the Russian Federation

    OpenAIRE

    Bolsheva, Anna

    2012-01-01

    The aim of this paper is to analyze the effectiveness of the minimum wage policy at the national level in Russia and its impact on living standards in the country. The analysis showed that the national minimum wage in Russia does not serve its original purpose of protecting the lowest wage earners and has no substantial effect on poverty reduction. The national subsistence minimum is too low and cannot be considered an adequate criterion for the setting of the minimum wage. The minimum wage d...

  12. Mixed emotions: Sensitivity to facial variance in a crowd of faces.

    Science.gov (United States)

    Haberman, Jason; Lee, Pegan; Whitney, David

    2015-01-01

    The visual system automatically represents summary information from crowds of faces, such as the average expression. This is a useful heuristic insofar as it provides critical information about the state of the world, not simply information about the state of one individual. However, the average alone is not sufficient for making decisions about how to respond to a crowd. The variance or heterogeneity of the crowd--the mixture of emotions--conveys information about the reliability of the average, essential for determining whether the average can be trusted. Despite its importance, the representation of variance within a crowd of faces has yet to be examined. This is addressed here in three experiments. In the first experiment, observers viewed a sample set of faces that varied in emotion, and then adjusted a subsequent set to match the variance of the sample set. To isolate variance as the summary statistic of interest, the average emotion of both sets was random. Results suggested that observers had information regarding crowd variance. The second experiment verified that this was indeed a uniquely high-level phenomenon, as observers were unable to derive the variance of an inverted set of faces as precisely as an upright set of faces. The third experiment replicated and extended the first two experiments using method-of-constant-stimuli. Together, these results show that the visual system is sensitive to emergent information about the emotional heterogeneity, or ambivalence, in crowds of faces.

  13. On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series.

    Science.gov (United States)

    Thompson, William Hedley; Fransson, Peter

    2016-12-01

    Assessment of dynamic functional brain connectivity based on functional magnetic resonance imaging (fMRI) data is an increasingly popular strategy to investigate temporal dynamics of the brain's large-scale network architecture. Current practice when deriving connectivity estimates over time is to use the Fisher transformation, which aims to stabilize the variance of correlation values that fluctuate around varying true correlation values. It is, however, unclear how well the stabilization of signal variance performed by the Fisher transformation works for each connectivity time series, when the true correlation is assumed to be fluctuating. This is of importance because many subsequent analyses either assume or perform better when the time series have stable variance or adheres to an approximate Gaussian distribution. In this article, using simulations and analysis of resting-state fMRI data, we analyze the effect of applying different variance stabilization strategies on connectivity time series. We focus our investigation on the Fisher transformation, the Box-Cox (BC) transformation and an approach that combines both transformations. Our results show that, if the intention of stabilizing the variance is to use metrics on the time series, where stable variance or a Gaussian distribution is desired (e.g., clustering), the Fisher transformation is not optimal and may even skew connectivity time series away from being Gaussian. Furthermore, we show that the suboptimal performance of the Fisher transformation can be substantially improved by including an additional BC transformation after the dynamic functional connectivity time series has been Fisher transformed.

  14. Solid phase stability of a double-minimum interaction potential system

    International Nuclear Information System (INIS)

    Suematsu, Ayumi; Yoshimori, Akira; Saiki, Masafumi; Matsui, Jun; Odagaki, Takashi

    2014-01-01

    We study phase stability of a system with double-minimum interaction potential in a wide range of parameters by a thermodynamic perturbation theory. The present double-minimum potential is the Lennard-Jones-Gauss potential, which has a Gaussian pocket as well as a standard Lennard-Jones minimum. As a function of the depth and position of the Gaussian pocket in the potential, we determine the coexistence pressure of crystals (fcc and bcc). We show that the fcc crystallizes even at zero pressure when the position of the Gaussian pocket is coincident with the first or third nearest neighbor site of the fcc crystal. The bcc crystal is more stable than the fcc crystal when the position of the Gaussian pocket is coincident with the second nearest neighbor sites of the bcc crystal. The stable crystal structure is determined by the position of the Gaussian pocket. These results show that we can control the stability of the solid phase by tuning the potential function

  15. Variance Swap Replication: Discrete or Continuous?

    Directory of Open Access Journals (Sweden)

    Fabien Le Floc’h

    2018-02-01

    Full Text Available The popular replication formula to price variance swaps assumes continuity of traded option strikes. In practice, however, there is only a discrete set of option strikes traded on the market. We present here different discrete replication strategies and explain why the continuous replication price is more relevant.

  16. Impact of Damping Uncertainty on SEA Model Response Variance

    Science.gov (United States)

    Schiller, Noah; Cabell, Randolph; Grosveld, Ferdinand

    2010-01-01

    Statistical Energy Analysis (SEA) is commonly used to predict high-frequency vibroacoustic levels. This statistical approach provides the mean response over an ensemble of random subsystems that share the same gross system properties such as density, size, and damping. Recently, techniques have been developed to predict the ensemble variance as well as the mean response. However these techniques do not account for uncertainties in the system properties. In the present paper uncertainty in the damping loss factor is propagated through SEA to obtain more realistic prediction bounds that account for both ensemble and damping variance. The analysis is performed on a floor-equipped cylindrical test article that resembles an aircraft fuselage. Realistic bounds on the damping loss factor are determined from measurements acquired on the sidewall of the test article. The analysis demonstrates that uncertainties in damping have the potential to significantly impact the mean and variance of the predicted response.

  17. The Impact of Jump Distributions on the Implied Volatility of Variance

    DEFF Research Database (Denmark)

    Nicolato, Elisa; Pisani, Camilla; Pedersen, David Sloth

    2017-01-01

    We consider a tractable affine stochastic volatility model that generalizes the seminal Heston (1993) model by augmenting it with jumps in the instantaneous variance process. In this framework, we consider both realized variance options and VIX options, and we examine the impact of the distribution...... of jumps on the associated implied volatility smile. We provide sufficient conditions for the asymptotic behavior of the implied volatility of variance for small and large strikes. In particular, by selecting alternative jump distributions, we show that one can obtain fundamentally different shapes...

  18. Replication Variance Estimation under Two-phase Sampling in the Presence of Non-response

    Directory of Open Access Journals (Sweden)

    Muqaddas Javed

    2014-09-01

    Full Text Available Kim and Yu (2011 discussed replication variance estimator for two-phase stratified sampling. In this paper estimators for mean have been proposed in two-phase stratified sampling for different situation of existence of non-response at first phase and second phase. The expressions of variances of these estimators have been derived. Furthermore, replication-based jackknife variance estimators of these variances have also been derived. Simulation study has been conducted to investigate the performance of the suggested estimators.

  19. Minimum emittance of three-bend achromats

    International Nuclear Information System (INIS)

    Li Xiaoyu; Xu Gang

    2012-01-01

    The calculation of the minimum emittance of three-bend achromats (TBAs) made by Mathematical software can ignore the actual magnets lattice in the matching condition of dispersion function in phase space. The minimum scaling factors of two kinds of widely used TBA lattices are obtained. Then the relationship between the lengths and the radii of the three dipoles in TBA is obtained and so is the minimum scaling factor, when the TBA lattice achieves its minimum emittance. The procedure of analysis and the results can be widely used in achromats lattices, because the calculation is not restricted by the actual lattice. (authors)

  20. Estimation of the variance of noise in digital imaging for quality control; Estimacion de la varianza del ruido en imagen digital para control de calidad

    Energy Technology Data Exchange (ETDEWEB)

    Soro Bua, M.; Otero Martinez, C.; Vazquez Vazquez, R.; Santamarina Vazquez, F.; Lobato Busto, R.; Luna Vega, V.; Mosquera Sueiro, J.; Sanchez Garcia, M.; Pombar Camean, M.

    2011-07-01

    In this work is estimated variance kerma function pixel values for the real response curve nonlinear digital image system, without resorting to any approximation to the behavior of the detector. This result is compared with that obtained for the linearized version of the response curve.

  1. How the Weak Variance of Momentum Can Turn Out to be Negative

    Science.gov (United States)

    Feyereisen, M. R.

    2015-05-01

    Weak values are average quantities, therefore investigating their associated variance is crucial in understanding their place in quantum mechanics. We develop the concept of a position-postselected weak variance of momentum as cohesively as possible, building primarily on material from Moyal (Mathematical Proceedings of the Cambridge Philosophical Society, Cambridge University Press, Cambridge, 1949) and Sonego (Found Phys 21(10):1135, 1991) . The weak variance is defined in terms of the Wigner function, using a standard construction from probability theory. We show this corresponds to a measurable quantity, which is not itself a weak value. It also leads naturally to a connection between the imaginary part of the weak value of momentum and the quantum potential. We study how the negativity of the Wigner function causes negative weak variances, and the implications this has on a class of `subquantum' theories. We also discuss the role of weak variances in studying determinism, deriving the classical limit from a variational principle.

  2. Variance gradients and uncertainty budgets for nonlinear measurement functions with independent inputs

    International Nuclear Information System (INIS)

    Campanelli, Mark; Kacker, Raghu; Kessel, Rüdiger

    2013-01-01

    A novel variance-based measure for global sensitivity analysis, termed a variance gradient (VG), is presented for constructing uncertainty budgets under the Guide to the Expression of Uncertainty in Measurement (GUM) framework for nonlinear measurement functions with independent inputs. The motivation behind VGs is the desire of metrologists to understand which inputs' variance reductions would most effectively reduce the variance of the measurand. VGs are particularly useful when the application of the first supplement to the GUM is indicated because of the inadequacy of measurement function linearization. However, VGs reduce to a commonly understood variance decomposition in the case of a linear(ized) measurement function with independent inputs for which the original GUM readily applies. The usefulness of VGs is illustrated by application to an example from the first supplement to the GUM, as well as to the benchmark Ishigami function. A comparison of VGs to other available sensitivity measures is made. (paper)

  3. Variance in parametric images: direct estimation from parametric projections

    International Nuclear Information System (INIS)

    Maguire, R.P.; Leenders, K.L.; Spyrou, N.M.

    2000-01-01

    Recent work has shown that it is possible to apply linear kinetic models to dynamic projection data in PET in order to calculate parameter projections. These can subsequently be back-projected to form parametric images - maps of parameters of physiological interest. Critical to the application of these maps, to test for significant changes between normal and pathophysiology, is an assessment of the statistical uncertainty. In this context, parametric images also include simple integral images from, e.g., [O-15]-water used to calculate statistical parametric maps (SPMs). This paper revisits the concept of parameter projections and presents a more general formulation of the parameter projection derivation as well as a method to estimate parameter variance in projection space, showing which analysis methods (models) can be used. Using simulated pharmacokinetic image data we show that a method based on an analysis in projection space inherently calculates the mathematically rigorous pixel variance. This results in an estimation which is as accurate as either estimating variance in image space during model fitting, or estimation by comparison across sets of parametric images - as might be done between individuals in a group pharmacokinetic PET study. The method based on projections has, however, a higher computational efficiency, and is also shown to be more precise, as reflected in smooth variance distribution images when compared to the other methods. (author)

  4. A geometric approach to multiperiod mean variance optimization of assets and liabilities

    OpenAIRE

    Leippold, Markus; Trojani, Fabio; Vanini, Paolo

    2005-01-01

    We present a geometric approach to discrete time multiperiod mean variance portfolio optimization that largely simplifies the mathematical analysis and the economic interpretation of such model settings. We show that multiperiod mean variance optimal policies can be decomposed in an orthogonal set of basis strategies, each having a clear economic interpretation. This implies that the corresponding multi period mean variance frontiers are spanned by an orthogonal basis of dynamic returns. Spec...

  5. Minimum Energy Requirements in Complex Distillation Arrangements

    Energy Technology Data Exchange (ETDEWEB)

    Halvorsen, Ivar J

    2001-07-01

    Distillation is the most widely used industrial separation technology and distillation units are responsible for a significant part of the total heat consumption in the world's process industry. In this work we focus on directly (fully thermally) coupled column arrangements for separation of multicomponent mixtures. These systems are also denoted Petlyuk arrangements, where a particular implementation is the dividing wall column. Energy savings in the range of 20-40% have been reported with ternary feed mixtures. In addition to energy savings, such integrated units have also a potential for reduced capital cost, making them extra attractive. However, the industrial use has been limited, and difficulties in design and control have been reported as the main reasons. Minimum energy results have only been available for ternary feed mixtures and sharp product splits. This motivates further research in this area, and this thesis will hopefully give some contributions to better understanding of complex column systems. In the first part we derive the general analytic solution for minimum energy consumption in directly coupled columns for a multicomponent feed and any number of products. To our knowledge, this is a new contribution in the field. The basic assumptions are constant relative volatility, constant pressure and constant molar flows and the derivation is based on Underwood's classical methods. An important conclusion is that the minimum energy consumption in a complex directly integrated multi-product arrangement is the same as for the most difficult split between any pair of the specified products when we consider the performance of a conventional two-product column. We also present the Vmin-diagram, which is a simple graphical tool for visualisation of minimum energy related to feed distribution. The Vmin-diagram provides a simple mean to assess the detailed flow requirements for all parts of a complex directly coupled arrangement. The main purpose in the first

  6. Minimum Energy Requirements in Complex Distillation Arrangements

    Energy Technology Data Exchange (ETDEWEB)

    Halvorsen, Ivar J.

    2001-07-01

    Distillation is the most widely used industrial separation technology and distillation units are responsible for a significant part of the total heat consumption in the world's process industry. In this work we focus on directly (fully thermally) coupled column arrangements for separation of multicomponent mixtures. These systems are also denoted Petlyuk arrangements, where a particular implementation is the dividing wall column. Energy savings in the range of 20-40% have been reported with ternary feed mixtures. In addition to energy savings, such integrated units have also a potential for reduced capital cost, making them extra attractive. However, the industrial use has been limited, and difficulties in design and control have been reported as the main reasons. Minimum energy results have only been available for ternary feed mixtures and sharp product splits. This motivates further research in this area, and this thesis will hopefully give some contributions to better understanding of complex column systems. In the first part we derive the general analytic solution for minimum energy consumption in directly coupled columns for a multicomponent feed and any number of products. To our knowledge, this is a new contribution in the field. The basic assumptions are constant relative volatility, constant pressure and constant molar flows and the derivation is based on Underwood's classical methods. An important conclusion is that the minimum energy consumption in a complex directly integrated multi-product arrangement is the same as for the most difficult split between any pair of the specified products when we consider the performance of a conventional two-product column. We also present the Vmin-diagram, which is a simple graphical tool for visualisation of minimum energy related to feed distribution. The Vmin-diagram provides a simple mean to assess the detailed flow requirements for all parts of a complex directly coupled arrangement. The main purpose in

  7. Mean-variance portfolio selection and efficient frontier for defined contribution pension schemes

    DEFF Research Database (Denmark)

    Højgaard, Bjarne; Vigna, Elena

    We solve a mean-variance portfolio selection problem in the accumulation phase of a defined contribution pension scheme. The efficient frontier, which is found for the 2 asset case as well as the n + 1 asset case, gives the member the possibility to decide his own risk/reward profile. The mean...... as a mean-variance optimization problem. It is shown that the corresponding mean and variance of the final fund belong to the efficient frontier and also the opposite, that each point on the efficient frontier corresponds to a target-based optimization problem. Furthermore, numerical results indicate...... that the largely adopted lifestyle strategy seems to be very far from being efficient in the mean-variance setting....

  8. ASYMMETRY OF MARKET RETURNS AND THE MEAN VARIANCE FRONTIER

    OpenAIRE

    SENGUPTA, Jati K.; PARK, Hyung S.

    1994-01-01

    The hypothesis that the skewness and asymmetry have no significant impact on the mean variance frontier is found to be strongly violated by monthly U.S. data over the period January 1965 through December 1974. This result raises serious doubts whether the common market portifolios such as SP 500, value weighted and equal weighted returns can serve as suitable proxies for meanvariance efficient portfolios in the CAPM framework. A new test for assessing the impact of skewness on the variance fr...

  9. Global Gravity Wave Variances from Aura MLS: Characteristics and Interpretation

    Science.gov (United States)

    2008-12-01

    slight longitudinal variations, with secondary high- latitude peaks occurring over Greenland and Europe . As the QBO changes to the westerly phase, the...equatorial GW temperature variances from suborbital data (e.g., Eck- ermann et al. 1995). The extratropical wave variances are generally larger in the...emanating from tropopause altitudes, presumably radiated from tropospheric jet stream in- stabilities associated with baroclinic storm systems that

  10. A New Approach for Predicting the Variance of Random Decrement Functions

    DEFF Research Database (Denmark)

    Asmussen, J. C.; Brincker, Rune

    mean Gaussian distributed processes the RD functions are proportional to the correlation functions of the processes. If a linear structur is loaded by Gaussian white noise the modal parameters can be extracted from the correlation funtions of the response, only. One of the weaknesses of the RD...... technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance...... can be used as basis for a decision about how many time lags from the RD funtions should be used in the modal parameter extraction procedure. This paper suggests a new method for estimating the variance of the RD functions. The method is consistent in the sense that the accuracy of the approach...

  11. A New Approach for Predicting the Variance of Random Decrement Functions

    DEFF Research Database (Denmark)

    Asmussen, J. C.; Brincker, Rune

    1998-01-01

    mean Gaussian distributed processes the RD functions are proportional to the correlation functions of the processes. If a linear structur is loaded by Gaussian white noise the modal parameters can be extracted from the correlation funtions of the response, only. One of the weaknesses of the RD...... technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance...... can be used as basis for a decision about how many time lags from the RD funtions should be used in the modal parameter extraction procedure. This paper suggests a new method for estimating the variance of the RD functions. The method is consistent in the sense that the accuracy of the approach...

  12. 30 CFR 57.19021 - Minimum rope strength.

    Science.gov (United States)

    2010-07-01

    ... feet: Minimum Value=Static Load×(7.0−0.001L) For rope lengths 3,000 feet or greater: Minimum Value=Static Load×4.0. (b) Friction drum ropes. For rope lengths less than 4,000 feet: Minimum Value=Static Load×(7.0−0.0005L) For rope lengths 4,000 feet or greater: Minimum Value=Static Load×5.0. (c) Tail...

  13. 30 CFR 56.19021 - Minimum rope strength.

    Science.gov (United States)

    2010-07-01

    ... feet: Minimum Value=Static Load×(7.0-0.001L) For rope lengths 3,000 feet or greater: Minimum Value=Static Load×4.0 (b) Friction drum ropes. For rope lengths less than 4,000 feet: Minimum Value=Static Load×(7.0-0.0005L) For rope lengths 4,000 feet or greater: Minimum Value=Static Load×5.0 (c) Tail ropes...

  14. Optimising a Model of Minimum Stock Level Control and a Model of Standing Order Cycle in Selected Foundry Plant

    Directory of Open Access Journals (Sweden)

    Szymszal J.

    2013-09-01

    Full Text Available It has been found that the area where one can look for significant reserves in the procurement logistics is a rational management of the stock of raw materials. Currently, the main purpose of projects which increase the efficiency of inventory management is to rationalise all the activities in this area, taking into account and minimising at the same time the total inventory costs. The paper presents a method for optimising the inventory level of raw materials under a foundry plant conditions using two different control models. The first model is based on the estimate of an optimal level of the minimum emergency stock of raw materials, giving information about the need for an order to be placed immediately and about the optimal size of consignments ordered after the minimum emergency level has occurred. The second model is based on the estimate of a maximum inventory level of raw materials and an optimal order cycle. Optimisation of the presented models has been based on the previously done selection and use of rational methods for forecasting the time series of the delivery of a chosen auxiliary material (ceramic filters to a casting plant, including forecasting a mean size of the delivered batch of products and its standard deviation.

  15. Robust design of a 2-DOF GMV controller: a direct self-tuning and fuzzy scheduling approach.

    Science.gov (United States)

    Silveira, Antonio S; Rodríguez, Jaime E N; Coelho, Antonio A R

    2012-01-01

    This paper presents a study on self-tuning control strategies with generalized minimum variance control in a fixed two degree of freedom structure-or simply GMV2DOF-within two adaptive perspectives. One, from the process model point of view, using a recursive least squares estimator algorithm for direct self-tuning design, and another, using a Mamdani fuzzy GMV2DOF parameters scheduling technique based on analytical and physical interpretations from robustness analysis of the system. Both strategies are assessed by simulation and real plants experimentation environments composed of a damped pendulum and an under development wind tunnel from the Department of Automation and Systems of the Federal University of Santa Catarina. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  16. A class of multi-period semi-variance portfolio for petroleum exploration and development

    Science.gov (United States)

    Guo, Qiulin; Li, Jianzhong; Zou, Caineng; Guo, Yujuan; Yan, Wei

    2012-10-01

    Variance is substituted by semi-variance in Markowitz's portfolio selection model. For dynamic valuation on exploration and development projects, one period portfolio selection is extended to multi-period. In this article, a class of multi-period semi-variance exploration and development portfolio model is formulated originally. Besides, a hybrid genetic algorithm, which makes use of the position displacement strategy of the particle swarm optimiser as a mutation operation, is applied to solve the multi-period semi-variance model. For this class of portfolio model, numerical results show that the mode is effective and feasible.

  17. Bayesian evaluation of constrained hypotheses on variances of multiple independent groups

    NARCIS (Netherlands)

    Böing-Messing, F.; van Assen, M.A.L.M.; Hofman, A.D.; Hoijtink, H.; Mulder, J.

    2017-01-01

    Research has shown that independent groups often differ not only in their means, but also in their variances. Comparing and testing variances is therefore of crucial importance to understand the effect of a grouping variable on an outcome variable. Researchers may have specific expectations

  18. Development of a treatability variance guidance document for US DOE mixed-waste streams

    International Nuclear Information System (INIS)

    Scheuer, N.; Spikula, R.; Harms, T.

    1990-03-01

    In response to the US Department of Energy's (DOE's) anticipated need for variances from the Resource Conservation and Recovery Act (RCRA) Land Disposal Restrictions (LDRs), a treatability variance guidance document was prepared. The guidance manual is for use by DOE facilities and operations offices. The manual was prepared as a part of an ongoing effort by DOE-EH to provide guidance for the operations offices and facilities to comply with the RCRA (LDRs). A treatability variance is an alternative treatment standard granted by EPA for a restricted waste. Such a variance is not an exemption from the requirements of the LDRs, but rather is an alternative treatment standard that must be met before land disposal. The manual, Guidance For Obtaining Variance From the Treatment Standards of the RCRA Land Disposal Restrictions (1), leads the reader through the process of evaluating whether a variance from the treatment standard is a viable approach and through the data-gathering and data-evaluation processes required to develop a petition requesting a variance. The DOE review and coordination process is also described and model language for use in petitions for DOE radioactive mixed waste (RMW) is provided. The guidance manual focuses on RMW streams, however the manual also is applicable to nonmixed, hazardous waste streams. 4 refs

  19. 30 CFR 77.1431 - Minimum rope strength.

    Science.gov (United States)

    2010-07-01

    ... feet: Minimum Value=Static Load×(7.0−0.001L) For rope lengths 3,000 feet or greater: Minimum Value=Static Load×4.0 (b) Friction drum ropes. For rope lengths less than 4,000 feet: Minimum Value=Static Load×(7.0−0.0005L) For rope lengths 4,000 feet or greater: Minimum Value=Static Load×5.0 (c) Tail ropes...

  20. On the noise variance of a digital mammography system

    International Nuclear Information System (INIS)

    Burgess, Arthur

    2004-01-01

    A recent paper by Cooper et al. [Med. Phys. 30, 2614-2621 (2003)] contains some apparently anomalous results concerning the relationship between pixel variance and x-ray exposure for a digital mammography system. They found an unexpected peak in a display domain pixel variance plot as a function of 1/mAs (their Fig. 5) with a decrease in the range corresponding to high display data values, corresponding to low x-ray exposures. As they pointed out, if the detector response is linear in exposure and the transformation from raw to display data scales is logarithmic, then pixel variance should be a monotonically increasing function in the figure. They concluded that the total system transfer curve, between input exposure and display image data values, is not logarithmic over the full exposure range. They separated data analysis into two regions and plotted the logarithm of display image pixel variance as a function of the logarithm of the mAs used to produce the phantom images. They found a slope of minus one for high mAs values and concluded that the transfer function is logarithmic in this region. They found a slope of 0.6 for the low mAs region and concluded that the transfer curve was neither linear nor logarithmic for low exposure values. It is known that the digital mammography system investigated by Cooper et al. has a linear relationship between exposure and raw data values [Vedantham et al., Med. Phys. 27, 558-567 (2000)]. The purpose of this paper is to show that the variance effect found by Cooper et al. (their Fig. 5) arises because the transformation from the raw data scale (14 bits) to the display scale (12 bits), for the digital mammography system they investigated, is not logarithmic for raw data values less than about 300 (display data values greater than about 3300). At low raw data values the transformation is linear and prevents over-ranging of the display data scale. Parametric models for the two transformations will be presented. Results of pixel

  1. Spatially tuned normalization explains attention modulation variance within neurons.

    Science.gov (United States)

    Ni, Amy M; Maunsell, John H R

    2017-09-01

    Spatial attention improves perception of attended parts of a scene, a behavioral enhancement accompanied by modulations of neuronal firing rates. These modulations vary in size across neurons in the same brain area. Models of normalization explain much of this variance in attention modulation with differences in tuned normalization across neurons (Lee J, Maunsell JHR. PLoS One 4: e4651, 2009; Ni AM, Ray S, Maunsell JHR. Neuron 73: 803-813, 2012). However, recent studies suggest that normalization tuning varies with spatial location both across and within neurons (Ruff DA, Alberts JJ, Cohen MR. J Neurophysiol 116: 1375-1386, 2016; Verhoef BE, Maunsell JHR. eLife 5: e17256, 2016). Here we show directly that attention modulation and normalization tuning do in fact covary within individual neurons, in addition to across neurons as previously demonstrated. We recorded the activity of isolated neurons in the middle temporal area of two rhesus monkeys as they performed a change-detection task that controlled the focus of spatial attention. Using the same two drifting Gabor stimuli and the same two receptive field locations for each neuron, we found that switching which stimulus was presented at which location affected both attention modulation and normalization in a correlated way within neurons. We present an equal-maximum-suppression spatially tuned normalization model that explains this covariance both across and within neurons: each stimulus generates equally strong suppression of its own excitatory drive, but its suppression of distant stimuli is typically less. This new model specifies how the tuned normalization associated with each stimulus location varies across space both within and across neurons, changing our understanding of the normalization mechanism and how attention modulations depend on this mechanism. NEW & NOTEWORTHY Tuned normalization studies have demonstrated that the variance in attention modulation size seen across neurons from the same cortical

  2. How do minimum cigarette price laws affect cigarette prices at the retail level?

    Science.gov (United States)

    Feighery, E C; Ribisl, K M; Schleicher, N C; Zellers, L; Wellington, N

    2005-04-01

    Half of US states have minimum cigarette price laws that were originally passed to protect small independent retailers from unfair price competition with larger retailers. These laws prohibit cigarettes from being sold below a minimum price that is set by a formula. Many of these laws allow cigarette company promotional incentives offered to retailers, such as buydowns and master-type programmes, to be calculated into the formula. Allowing this provision has the potential to lower the allowable minimum price. This study assesses whether stores in states with minimum price laws have higher cigarette prices and lower rates of retailer participation in cigarette company promotional incentive programmes. Retail cigarette prices and retailer participation in cigarette company incentive programmes in 2001 were compared in eight states with minimum price laws and seven states without them. New York State had the most stringent minimum price law at the time of the study because it excluded promotional incentive programmes in its price setting formula; cigarette prices in New York were compared to all other states included in the study. Cigarette prices were not significantly different in our sample of US states with and without cigarette minimum price laws. Cigarette prices were significantly higher in New York stores than in the 14 other states combined. Most existing minimum cigarette price laws appear to have little impact on the retail price of cigarettes. This may be because they allow the use of promotional programmes, which are used by manufacturers to reduce cigarette prices. New York's strategy to disallow these types of incentive programmes may result in higher minimum cigarette prices, and should also be explored as a potential policy strategy to control cigarette company marketing practices in stores. Strict cigarette minimum price laws may have the potential to reduce cigarette consumption by decreasing demand through increased cigarette prices and reduced

  3. Variance of a product with application to uranium estimation

    International Nuclear Information System (INIS)

    Lowe, V.W.; Waterman, M.S.

    1976-01-01

    The U in a container can either be determined directly by NDA or by estimating the weight of material in the container and the concentration of U in this material. It is important to examine the statistical properties of estimating the amount of U by multiplying the estimates of weight and concentration. The variance of the product determines the accuracy of the estimate of the amount of uranium. This paper examines the properties of estimates of the variance of the product of two random variables

  4. A Phosphate Minimum in the Oxygen Minimum Zone (OMZ) off Peru

    Science.gov (United States)

    Paulmier, A.; Giraud, M.; Sudre, J.; Jonca, J.; Leon, V.; Moron, O.; Dewitte, B.; Lavik, G.; Grasse, P.; Frank, M.; Stramma, L.; Garcon, V.

    2016-02-01

    The Oxygen Minimum Zone (OMZ) off Peru is known to be associated with the advection of Equatorial SubSurface Waters (ESSW), rich in nutrients and poor in oxygen, through the Peru-Chile UnderCurrent (PCUC), but this circulation remains to be refined within the OMZ. During the Pelágico cruise in November-December 2010, measurements of phosphate revealed the presence of a phosphate minimum (Pmin) in various hydrographic stations, which could not be explained so far and could be associated with a specific water mass. This Pmin, localized at a relatively constant layer ( 20minimum with a mean vertical phosphate decrease of 0.6 µM but highly variable between 0.1 and 2.2 µM. In average, these Pmin are associated with a predominant mixing of SubTropical Under- and Surface Waters (STUW and STSW: 20 and 40%, respectively) within ESSW ( 25%), complemented evenly by overlying (ESW, TSW: 8%) and underlying waters (AAIW, SPDW: 7%). The hypotheses and mechanisms leading to the Pmin formation in the OMZ are further explored and discussed, considering the physical regional contribution associated with various circulation pathways ventilating the OMZ and the local biogeochemical contribution including the potential diazotrophic activity.

  5. Accounting for non-stationary variance in geostatistical mapping of soil properties

    NARCIS (Netherlands)

    Wadoux, Alexandre M.J.C.; Brus, Dick J.; Heuvelink, Gerard B.M.

    2018-01-01

    Simple and ordinary kriging assume a constant mean and variance of the soil variable of interest. This assumption is often implausible because the mean and/or variance are linked to terrain attributes, parent material or other soil forming factors. In kriging with external drift (KED)

  6. Ulnar variance: its relationship to ulnar foveal morphology and forearm kinematics.

    Science.gov (United States)

    Kataoka, Toshiyuki; Moritomo, Hisao; Omokawa, Shohei; Iida, Akio; Murase, Tsuyoshi; Sugamoto, Kazuomi

    2012-04-01

    It is unclear how individual differences in the anatomy of the distal ulna affect kinematics and pathology of the distal radioulnar joint. This study evaluated how ulnar variance relates to ulnar foveal morphology and the pronosupination axis of the forearm. We performed 3-dimensional computed tomography studies in vivo on 28 forearms in maximum supination and pronation to determine the anatomical center of the ulnar distal pole and the forearm pronosupination axis. We calculated the forearm pronosupination axis using a markerless bone registration technique, which determined the pronosupination center as the point where the axis emerges on the distal ulnar surface. We measured the depth of the anatomical center and classified it into 2 types: concave, with a depth of 0.8 mm or more, and flat, with a depth less than 0.8 mm. We examined whether ulnar variance correlated with foveal type and the distance between anatomical and pronosupination centers. A total of 18 cases had a concave-type fovea surrounded by the C-shaped articular facet of the distal pole, and 10 had a flat-type fovea with a flat surface without evident central depression. Ulnar variance of the flat type was 3.5 ± 1.2 mm, which was significantly greater than the 1.2 ± 1.1 mm of the concave type. Ulnar variance positively correlated with distance between the anatomical and pronosupination centers. Flat-type ulnar heads have a significantly greater ulnar variance than concave types. The pronosupination axis passes through the ulnar head more medially and farther from the anatomical center with increasing ulnar variance. This study suggests that ulnar variance is related in part to foveal morphology and pronosupination axis. This information provides a starting point for future studies investigating how foveal morphology relates to distal ulnar problems. Copyright © 2012 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.

  7. Minimum short-circuit ratios for grid interconnection of wind farms with induction generators

    Energy Technology Data Exchange (ETDEWEB)

    Reginatto, Romeu; Rocha, Carlos [Western Parana State University (UNIOESTE), Foz do Iguacu, PR (Brazil). Center for Engineering and Exact Sciences], Emails: romeu@unioeste.br, croberto@unioeste.br

    2009-07-01

    This paper concerns the problem of determining the minimum value for the short-circuit ratio which is adequate for the interconnection of a given wind farms to a given grid point. First, a set of 3 criteria is defined in order to characterize the quality/safety of the interconnection: acceptable terminal voltage variations, a minimum active power margin, and an acceptable range for the internal voltage angle. Then, the minimum short circuit ratio requirement is determined for 6 different induction generator based wind turbines, both fixed-speed (with and without reactive power compensation) and variable-speed (with the following control policies: reactive power, power factor, and terminal voltage regulation). The minimum short-circuit ratio is determined and shown in graphical results for the 6 wind turbines considered, for X/R in the range 0-15, also analyzing the effect of more/less stringent tolerances for the interconnection criteria. It is observed that the tighter the tolerances the larger the minimum short-circuit ratio required. For the same tolerances in the interconnection criteria, a comparison of the minimum short circuit ratio required for the interconnection of both squirrel-cage and doubly-fed induction generators is presented, showing that the last requires much smaller values for the short-circuit ratio. (author)

  8. The efficiency of the crude oil markets: Evidence from variance ratio tests

    Energy Technology Data Exchange (ETDEWEB)

    Charles, Amelie, E-mail: acharles@audencia.co [Audencia Nantes, School of Management, 8 route de la Joneliere, 44312 Nantes (France); Darne, Olivier, E-mail: olivier.darne@univ-nantes.f [LEMNA, University of Nantes, IEMN-IAE, Chemin de la Censive du Tertre, 44322 Nantes (France)

    2009-11-15

    This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable.

  9. The efficiency of the crude oil markets. Evidence from variance ratio tests

    International Nuclear Information System (INIS)

    Charles, Amelie; Darne, Olivier

    2009-01-01

    This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable. (author)

  10. The efficiency of the crude oil markets. Evidence from variance ratio tests

    Energy Technology Data Exchange (ETDEWEB)

    Charles, Amelie [Audencia Nantes, School of Management, 8 route de la Joneliere, 44312 Nantes (France); Darne, Olivier [LEMNA, University of Nantes, IEMN-IAE, Chemin de la Censive du Tertre, 44322 Nantes (France)

    2009-11-15

    This study examines the random walk hypothesis for the crude oil markets, using daily data over the period 1982-2008. The weak-form efficient market hypothesis for two crude oil markets (UK Brent and US West Texas Intermediate) is tested with non-parametric variance ratio tests developed by [Wright J.H., 2000. Alternative variance-ratio tests using ranks and signs. Journal of Business and Economic Statistics, 18, 1-9] and [Belaire-Franch J. and Contreras D., 2004. Ranks and signs-based multiple variance ratio tests. Working paper, Department of Economic Analysis, University of Valencia] as well as the wild-bootstrap variance ratio tests suggested by [Kim, J.H., 2006. Wild bootstrapping variance ratio tests. Economics Letters, 92, 38-43]. We find that the Brent crude oil market is weak-form efficiency while the WTI crude oil market seems to be inefficiency on the 1994-2008 sub-period, suggesting that the deregulation have not improved the efficiency on the WTI crude oil market in the sense of making returns less predictable. (author)

  11. Hydrograph variances over different timescales in hydropower production networks

    Science.gov (United States)

    Zmijewski, Nicholas; Wörman, Anders

    2016-08-01

    The operation of water reservoirs involves a spectrum of timescales based on the distribution of stream flow travel times between reservoirs, as well as the technical, environmental, and social constraints imposed on the operation. In this research, a hydrodynamically based description of the flow between hydropower stations was implemented to study the relative importance of wave diffusion on the spectrum of hydrograph variance in a regulated watershed. Using spectral decomposition of the effluence hydrograph of a watershed, an exact expression of the variance in the outflow response was derived, as a function of the trends of hydraulic and geomorphologic dispersion and management of production and reservoirs. We show that the power spectra of involved time-series follow nearly fractal patterns, which facilitates examination of the relative importance of wave diffusion and possible changes in production demand on the outflow spectrum. The exact spectral solution can also identify statistical bounds of future demand patterns due to limitations in storage capacity. The impact of the hydraulic description of the stream flow on the reservoir discharge was examined for a given power demand in River Dalälven, Sweden, as function of a stream flow Peclet number. The regulation of hydropower production on the River Dalälven generally increased the short-term variance in the effluence hydrograph, whereas wave diffusion decreased the short-term variance over periods of white noise) as a result of current production objectives.

  12. Variance reduction methods applied to deep-penetration problems

    International Nuclear Information System (INIS)

    Cramer, S.N.

    1984-01-01

    All deep-penetration Monte Carlo calculations require variance reduction methods. Before beginning with a detailed approach to these methods, several general comments concerning deep-penetration calculations by Monte Carlo, the associated variance reduction, and the similarities and differences of these with regard to non-deep-penetration problems will be addressed. The experienced practitioner of Monte Carlo methods will easily find exceptions to any of these generalities, but it is felt that these comments will aid the novice in understanding some of the basic ideas and nomenclature. Also, from a practical point of view, the discussions and developments presented are oriented toward use of the computer codes which are presented in segments of this Monte Carlo course

  13. Cumulative prospect theory and mean variance analysis. A rigorous comparison

    OpenAIRE

    Hens, Thorsten; Mayer, Janos

    2012-01-01

    We compare asset allocations derived for cumulative prospect theory(CPT) based on two different methods: Maximizing CPT along the mean–variance efficient frontier and maximizing it without that restriction. We find that with normally distributed returns the difference is negligible. However, using standard asset allocation data of pension funds the difference is considerable. Moreover, with derivatives like call options the restriction to the mean-variance efficient frontier results in a siza...

  14. Variance Reduction Techniques in Monte Carlo Methods

    NARCIS (Netherlands)

    Kleijnen, Jack P.C.; Ridder, A.A.N.; Rubinstein, R.Y.

    2010-01-01

    Monte Carlo methods are simulation algorithms to estimate a numerical quantity in a statistical model of a real system. These algorithms are executed by computer programs. Variance reduction techniques (VRT) are needed, even though computer speed has been increasing dramatically, ever since the

  15. Decomposition of variance for spatial Cox processes

    DEFF Research Database (Denmark)

    Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

    Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models...

  16. Decomposition of variance for spatial Cox processes

    DEFF Research Database (Denmark)

    Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

    2013-01-01

    Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introduce a general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models...

  17. AnovArray: a set of SAS macros for the analysis of variance of gene expression data

    Directory of Open Access Journals (Sweden)

    Renard Jean-Paul

    2005-06-01

    Full Text Available Abstract Background Analysis of variance is a powerful approach to identify differentially expressed genes in a complex experimental design for microarray and macroarray data. The advantage of the anova model is the possibility to evaluate multiple sources of variation in an experiment. Results AnovArray is a package implementing ANOVA for gene expression data using SAS® statistical software. The originality of the package is 1 to quantify the different sources of variation on all genes together, 2 to provide a quality control of the model, 3 to propose two models for a gene's variance estimation and to perform a correction for multiple comparisons. Conclusion AnovArray is freely available at http://www-mig.jouy.inra.fr/stat/AnovArray and requires only SAS® statistical software.

  18. Variance risk premia in CO_2 markets: A political perspective

    International Nuclear Information System (INIS)

    Reckling, Dennis

    2016-01-01

    The European Commission discusses the change of free allocation plans to guarantee a stable market equilibrium. Selling over-allocated contracts effectively depreciates prices and negates the effect intended by the regulator to establish a stable price mechanism for CO_2 assets. Our paper investigates mispricing and allocation issues by quantitatively analyzing variance risk premia of CO_2 markets over the course of changing regimes (Phase I-III) for three different assets (European Union Allowances, Certified Emissions Reductions and European Reduction Units). The research paper gives recommendations to regulatory bodies in order to most effectively cap the overall carbon dioxide emissions. The analysis of an enriched dataset, comprising not only of additional CO_2 assets, but also containing data from the European Energy Exchange, shows that variance risk premia are equal to a sample average of 0.69 for European Union Allowances (EUA), 0.17 for Certified Emissions Reductions (CER) and 0.81 for European Reduction Units (ERU). We identify the existence of a common risk factor across different assets that justifies the presence of risk premia. Various policy implications with regards to gaining investors’ confidence in the market are being reviewed. Consequently, we recommend the implementation of a price collar approach to support stable prices for emission allowances. - Highlights: •Enriched dataset covering all three political phases of the CO_2 markets. •Clear policy implications for regulators to most effectively cap the overall CO_2 emissions pool. •Applying a cross-asset benchmark index for variance beta estimation. •CER contracts have been analyzed with respect to variance risk premia for the first time. •Increased forecasting accuracy for CO_2 asset returns by using variance risk premia.

  19. An Improved Minimum Error Interpolator of CNC for General Curves Based on FPGA

    Directory of Open Access Journals (Sweden)

    Jiye HUANG

    2014-05-01

    Full Text Available This paper presents an improved minimum error interpolation algorithm for general curves generation in computer numerical control (CNC. Compared with the conventional interpolation algorithms such as the By-Point Comparison method, the Minimum- Error method and the Digital Differential Analyzer (DDA method, the proposed improved Minimum-Error interpolation algorithm can find a balance between accuracy and efficiency. The new algorithm is applicable for the curves of linear, circular, elliptical and parabolic. The proposed algorithm is realized on a field programmable gate array (FPGA with Verilog HDL language, and simulated by the ModelSim software, and finally verified on a two-axis CNC lathe. The algorithm has the following advantages: firstly, the maximum interpolation error is only half of the minimum step-size; and secondly the computing time is only two clock cycles of the FPGA. Simulations and actual tests have proved that the high accuracy and efficiency of the algorithm, which shows that it is highly suited for real-time applications.

  20. Perspective projection for variance pose face recognition from camera calibration

    Science.gov (United States)

    Fakhir, M. M.; Woo, W. L.; Chambers, J. A.; Dlay, S. S.

    2016-04-01

    Variance pose is an important research topic in face recognition. The alteration of distance parameters across variance pose face features is a challenging. We provide a solution for this problem using perspective projection for variance pose face recognition. Our method infers intrinsic camera parameters of the image which enable the projection of the image plane into 3D. After this, face box tracking and centre of eyes detection can be identified using our novel technique to verify the virtual face feature measurements. The coordinate system of the perspective projection for face tracking allows the holistic dimensions for the face to be fixed in different orientations. The training of frontal images and the rest of the poses on FERET database determine the distance from the centre of eyes to the corner of box face. The recognition system compares the gallery of images against different poses. The system initially utilises information on position of both eyes then focuses principally on closest eye in order to gather data with greater reliability. Differentiation between the distances and position of the right and left eyes is a unique feature of our work with our algorithm outperforming other state of the art algorithms thus enabling stable measurement in variance pose for each individual.

  1. Improving boiler unit performance using an optimum robust minimum-order observer

    International Nuclear Information System (INIS)

    Moradi, Hamed; Bakhtiari-Nejad, Firooz

    2011-01-01

    Research highlights: → Multivariable model of a boiler unit with uncertainty. → Design of a robust minimum-order observer. → Developing an optimal functional code in MATLAB environment. → Finding optimum region of observer-based controller poles. → Guarantee of robust performance in the presence of parametric uncertainties. - Abstract: To achieve a good performance of the utility boiler, dynamic variables such as drum pressure, steam temperature and water level of drum must be controlled. In this paper, a linear time invariant (LTI) model of a boiler system is considered in which the input variables are feed-water and fuel mass rates. Due to the inaccessibility of some state variables of boiler system, a minimum-order observer is designed based on Luenberger's model to gain an estimate state x-tilde of the true state x. Low cost of design and high accuracy of states estimation are the main advantages of the minimum-order observer; in comparison with previous designed full-order observers. By applying the observer on the closed-loop system, a regulator system is designed. Using an optimal functional code developed in MATLAB environment, desired observer poles are found such that suitable time response specifications of the boiler system are achieved and the gain and phase margin values are adjusted in an acceptable range. However, the real dynamic model may associate with parametric uncertainties. In that case, optimum region of poles of observer-based controller are found such that the robust performance of the boiler system against model uncertainties is guaranteed.

  2. Variance-to-mean method generalized by linear difference filter technique

    International Nuclear Information System (INIS)

    Hashimoto, Kengo; Ohsaki, Hiroshi; Horiguchi, Tetsuo; Yamane, Yoshihiro; Shiroya, Seiji

    1998-01-01

    The conventional variance-to-mean method (Feynman-α method) seriously suffers the divergency of the variance under such a transient condition as a reactor power drift. Strictly speaking, then, the use of the Feynman-α is restricted to a steady state. To apply the method to more practical uses, it is desirable to overcome this kind of difficulty. For this purpose, we propose an usage of higher-order difference filter technique to reduce the effect of the reactor power drift, and derive several new formulae taking account of the filtering. The capability of the formulae proposed was demonstrated through experiments in the Kyoto University Critical Assembly. The experimental results indicate that the divergency of the variance can be effectively suppressed by the filtering technique, and that the higher-order filter becomes necessary with increasing variation rate in power

  3. Estimation of (co)variances for genomic regions of flexible sizes

    DEFF Research Database (Denmark)

    Sørensen, Lars P; Janss, Luc; Madsen, Per

    2012-01-01

    was used. There was a clear difference in the region-wise patterns of genomic correlation among combinations of traits, with distinctive peaks indicating the presence of pleiotropic QTL. CONCLUSIONS: The results show that it is possible to estimate, genome-wide and region-wise genomic (co)variances......BACKGROUND: Multi-trait genomic models in a Bayesian context can be used to estimate genomic (co)variances, either for a complete genome or for genomic regions (e.g. per chromosome) for the purpose of multi-trait genomic selection or to gain further insight into the genomic architecture of related...... with a common prior distribution for the marker allele substitution effects and estimation of the hyperparameters in this prior distribution from the progeny means data. From the Markov chain Monte Carlo samples of the allele substitution effects, genomic (co)variances were calculated on a whole-genome level...

  4. Is residual memory variance a valid method for quantifying cognitive reserve? A longitudinal application

    Science.gov (United States)

    Zahodne, Laura B.; Manly, Jennifer J.; Brickman, Adam M.; Narkhede, Atul; Griffith, Erica Y.; Guzman, Vanessa A.; Schupf, Nicole; Stern, Yaakov

    2016-01-01

    Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point. PMID:26348002

  5. A study of heterogeneity of environmental variance for slaughter weight in pigs

    DEFF Research Database (Denmark)

    Ibánez-Escriche, N; Varona, L; Sorensen, D

    2008-01-01

    This work presents an analysis of heterogeneity of environmental variance for slaughter weight (175 days) in pigs. This heterogeneity is associated with systematic and additive genetic effects. The model also postulates the presence of additive genetic effects affecting the mean and environmental...... variance. The study reveals the presence of genetic variation at the level of the mean and the variance, but an absence of correlation, or a small negative correlation, between both types of additive genetic effects. In addition, we show that both, the additive genetic effects on the mean and those...... on environmental variance have an important influence upon the future economic performance of selected individuals...

  6. 12 CFR 564.4 - Minimum appraisal standards.

    Science.gov (United States)

    2010-01-01

    ... 12 Banks and Banking 5 2010-01-01 2010-01-01 false Minimum appraisal standards. 564.4 Section 564.4 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY APPRAISALS § 564.4 Minimum appraisal standards. For federally related transactions, all appraisals shall, at a minimum: (a...

  7. The minimum wage in the Czech enterprises

    OpenAIRE

    Eva Lajtkepová

    2010-01-01

    Although the statutory minimum wage is not a new category, in the Czech Republic we encounter the definition and regulation of a minimum wage for the first time in the 1990 amendment to Act No. 65/1965 Coll., the Labour Code. The specific amount of the minimum wage and the conditions of its operation were then subsequently determined by government regulation in February 1991. Since that time, the value of minimum wage has been adjusted fifteenth times (the last increase was in January 2007). ...

  8. Biological Variance in Agricultural Products. Theoretical Considerations

    NARCIS (Netherlands)

    Tijskens, L.M.M.; Konopacki, P.

    2003-01-01

    The food that we eat is uniform neither in shape or appearance nor in internal composition or content. Since technology became increasingly important, the presence of biological variance in our food became more and more of a nuisance. Techniques and procedures (statistical, technical) were

  9. Decomposition of variance for spatial Cox processes

    DEFF Research Database (Denmark)

    Jalilian, Abdollah; Guan, Yongtao; Waagepetersen, Rasmus

    Spatial Cox point processes is a natural framework for quantifying the various sources of variation governing the spatial distribution of rain forest trees. We introducea general criterion for variance decomposition for spatial Cox processes and apply it to specific Cox process models with additive...

  10. Regime shifts in mean-variance efficient frontiers: some international evidence

    OpenAIRE

    Massimo Guidolin; Federica Ria

    2010-01-01

    Regime switching models have been assuming a central role in financial applications because of their well-known ability to capture the presence of rich non-linear patterns in the joint distribution of asset returns. This paper examines how the presence of regimes in means, variances, and correlations of asset returns translates into explicit dynamics of the Markowitz mean-variance frontier. In particular, the paper shows both theoretically and through an application to international equity po...

  11. Minimum Wages and Regional Disparity: An analysis on the evolution of price-adjusted minimum wages and their effects on firm profitability (Japanese)

    OpenAIRE

    MORIKAWA Masayuki

    2013-01-01

    This paper, using prefecture level panel data, empirically analyzes 1) the recent evolution of price-adjusted regional minimum wages and 2) the effects of minimum wages on firm profitability. As a result of rapid increases in minimum wages in the metropolitan areas since 2007, the regional disparity of nominal minimum wages has been widening. However, the disparity of price-adjusted minimum wages has been shrinking. According to the analysis of the effects of minimum wages on profitability us...

  12. Learning and Control Model of the Arm for Loading

    Science.gov (United States)

    Kim, Kyoungsik; Kambara, Hiroyuki; Shin, Duk; Koike, Yasuharu

    We propose a learning and control model of the arm for a loading task in which an object is loaded onto one hand with the other hand, in the sagittal plane. Postural control during object interactions provides important points to motor control theories in terms of how humans handle dynamics changes and use the information of prediction and sensory feedback. For the learning and control model, we coupled a feedback-error-learning scheme with an Actor-Critic method used as a feedback controller. To overcome sensory delays, a feedforward dynamics model (FDM) was used in the sensory feedback path. We tested the proposed model in simulation using a two-joint arm with six muscles, each with time delays in muscle force generation. By applying the proposed model to the loading task, we showed that motor commands started increasing, before an object was loaded on, to stabilize arm posture. We also found that the FDM contributes to the stabilization by predicting how the hand changes based on contexts of the object and efferent signals. For comparison with other computational models, we present the simulation results of a minimum-variance model.

  13. The pricing of long and short run variance and correlation risk in stock returns

    NARCIS (Netherlands)

    Cosemans, M.

    2011-01-01

    This paper studies the pricing of long and short run variance and correlation risk. The predictive power of the market variance risk premium for returns is driven by the correlation risk premium and the systematic part of individual variance premia. Furthermore, I find that aggregate volatility risk

  14. A Bias and Variance Analysis for Multistep-Ahead Time Series Forecasting.

    Science.gov (United States)

    Ben Taieb, Souhaib; Atiya, Amir F

    2016-01-01

    Multistep-ahead forecasts can either be produced recursively by iterating a one-step-ahead time series model or directly by estimating a separate model for each forecast horizon. In addition, there are other strategies; some of them combine aspects of both aforementioned concepts. In this paper, we present a comprehensive investigation into the bias and variance behavior of multistep-ahead forecasting strategies. We provide a detailed review of the different multistep-ahead strategies. Subsequently, we perform a theoretical study that derives the bias and variance for a number of forecasting strategies. Finally, we conduct a Monte Carlo experimental study that compares and evaluates the bias and variance performance of the different strategies. From the theoretical and the simulation studies, we analyze the effect of different factors, such as the forecast horizon and the time series length, on the bias and variance components, and on the different multistep-ahead strategies. Several lessons are learned, and recommendations are given concerning the advantages, disadvantages, and best conditions of use of each strategy.

  15. 41 CFR 50-201.1101 - Minimum wages.

    Science.gov (United States)

    2010-07-01

    ... 41 Public Contracts and Property Management 1 2010-07-01 2010-07-01 true Minimum wages. 50-201... Contracts PUBLIC CONTRACTS, DEPARTMENT OF LABOR 201-GENERAL REGULATIONS § 50-201.1101 Minimum wages. Determinations of prevailing minimum wages or changes therein will be published in the Federal Register by the...

  16. Aerobic Microbial Respiration In Oceanic Oxygen Minimum Zones

    DEFF Research Database (Denmark)

    Kalvelage, Tim; Lavik, Gaute; Jensen, Marlene Mark

    2015-01-01

    Oxygen minimum zones are major sites of fixed nitrogen loss in the ocean. Recent studies have highlighted the importance of anaerobic ammonium oxidation, anammox, in pelagic nitrogen removal. Sources of ammonium for the anammox reaction, however, remain controversial, as heterotrophic denitrifica......Oxygen minimum zones are major sites of fixed nitrogen loss in the ocean. Recent studies have highlighted the importance of anaerobic ammonium oxidation, anammox, in pelagic nitrogen removal. Sources of ammonium for the anammox reaction, however, remain controversial, as heterotrophic...... denitrification and alternative anaerobic pathways of organic matter remineralization cannot account for the ammonium requirements of reported anammox rates. Here, we explore the significance of microaerobic respiration as a source of ammonium during organic matter degradation in the oxygen-deficient waters off...... Namibia and Peru. Experiments with additions of double-labelled oxygen revealed high aerobic activity in the upper OMZs, likely controlled by surface organic matter export. Consistently observed oxygen consumption in samples retrieved throughout the lower OMZs hints at efficient exploitation of vertically...

  17. Variance inflation in high dimensional Support Vector Machines

    DEFF Research Database (Denmark)

    Abrahamsen, Trine Julie; Hansen, Lars Kai

    2013-01-01

    Many important machine learning models, supervised and unsupervised, are based on simple Euclidean distance or orthogonal projection in a high dimensional feature space. When estimating such models from small training sets we face the problem that the span of the training data set input vectors...... the case of Support Vector Machines (SVMS) and we propose a non-parametric scheme to restore proper generalizability. We illustrate the algorithm and its ability to restore performance on a wide range of benchmark data sets....... follow a different probability law with less variance. While the problem and basic means to reconstruct and deflate are well understood in unsupervised learning, the case of supervised learning is less well understood. We here investigate the effect of variance inflation in supervised learning including...

  18. Minimum Wage Laws and the Distribution of Employment.

    Science.gov (United States)

    Lang, Kevin

    The desirability of raising the minimum wage long revolved around just one question: the effect of higher minimum wages on the overall level of employment. An even more critical effect of the minimum wage rests on the composition of employment--who gets the minimum wage job. An examination of employment in eating and drinking establishments…

  19. Studying Variance in the Galactic Ultra-compact Binary Population

    Science.gov (United States)

    Larson, Shane; Breivik, Katelyn

    2017-01-01

    In the years preceding LISA, Milky Way compact binary population simulations can be used to inform the science capabilities of the mission. Galactic population simulation efforts generally focus on high fidelity models that require extensive computational power to produce a single simulated population for each model. Each simulated population represents an incomplete sample of the functions governing compact binary evolution, thus introducing variance from one simulation to another. We present a rapid Monte Carlo population simulation technique that can simulate thousands of populations on week-long timescales, thus allowing a full exploration of the variance associated with a binary stellar evolution model.

  20. 29 CFR 505.3 - Prevailing minimum compensation.

    Science.gov (United States)

    2010-07-01

    ... 29 Labor 3 2010-07-01 2010-07-01 false Prevailing minimum compensation. 505.3 Section 505.3 Labor... HUMANITIES § 505.3 Prevailing minimum compensation. (a)(1) In the absence of an alternative determination...)(2) of this section, the prevailing minimum compensation required to be paid under the Act to the...

  1. Variance estimates for transport in stochastic media by means of the master equation

    International Nuclear Information System (INIS)

    Pautz, S. D.; Franke, B. C.; Prinja, A. K.

    2013-01-01

    The master equation has been used to examine properties of transport in stochastic media. It has been shown previously that not only may the Levermore-Pomraning (LP) model be derived from the master equation for a description of ensemble-averaged transport quantities, but also that equations describing higher-order statistical moments may be obtained. We examine in greater detail the equations governing the second moments of the distribution of the angular fluxes, from which variances may be computed. We introduce a simple closure for these equations, as well as several models for estimating the variances of derived transport quantities. We revisit previous benchmarks for transport in stochastic media in order to examine the error of these new variance models. We find, not surprisingly, that the errors in these variance estimates are at least as large as the corresponding estimates of the average, and sometimes much larger. We also identify patterns in these variance estimates that may help guide the construction of more accurate models. (authors)

  2. Markov switching mean-variance frontier dynamics: theory and international evidence

    OpenAIRE

    M. Guidolin; F. Ria

    2010-01-01

    It is well-known that regime switching models are able to capture the presence of rich non-linear patterns in the joint distribution of asset returns. After reviewing key concepts and technical issues related to specifying, estimating, and using multivariate Markov switching models in financial applications, in this paper we map the presence of regimes in means, variances, and covariances of asset returns into explicit dynamics of the Markowitz mean-variance frontier. In particular, we show b...

  3. Visual SLAM Using Variance Grid Maps

    Science.gov (United States)

    Howard, Andrew B.; Marks, Tim K.

    2011-01-01

    An algorithm denoted Gamma-SLAM performs further processing, in real time, of preprocessed digitized images acquired by a stereoscopic pair of electronic cameras aboard an off-road robotic ground vehicle to build accurate maps of the terrain and determine the location of the vehicle with respect to the maps. Part of the name of the algorithm reflects the fact that the process of building the maps and determining the location with respect to them is denoted simultaneous localization and mapping (SLAM). Most prior real-time SLAM algorithms have been limited in applicability to (1) systems equipped with scanning laser range finders as the primary sensors in (2) indoor environments (or relatively simply structured outdoor environments). The few prior vision-based SLAM algorithms have been feature-based and not suitable for real-time applications and, hence, not suitable for autonomous navigation on irregularly structured terrain. The Gamma-SLAM algorithm incorporates two key innovations: Visual odometry (in contradistinction to wheel odometry) is used to estimate the motion of the vehicle. An elevation variance map (in contradistinction to an occupancy or an elevation map) is used to represent the terrain. The Gamma-SLAM algorithm makes use of a Rao-Blackwellized particle filter (RBPF) from Bayesian estimation theory for maintaining a distribution over poses and maps. The core idea of the RBPF approach is that the SLAM problem can be factored into two parts: (1) finding the distribution over robot trajectories, and (2) finding the map conditioned on any given trajectory. The factorization involves the use of a particle filter in which each particle encodes both a possible trajectory and a map conditioned on that trajectory. The base estimate of the trajectory is derived from visual odometry, and the map conditioned on that trajectory is a Cartesian grid of elevation variances. In comparison with traditional occupancy or elevation grid maps, the grid elevation variance

  4. Comparing Variance/Covariance and Historical Simulation in the Context of the Financial Crisis – Do Extreme Movements Have an Influence onto Portfolio Selection?

    Directory of Open Access Journals (Sweden)

    Svend Reuse

    2010-09-01

    Full Text Available Portfolio theory and the basic ideas of Markowitz have been extended in the recent past by alternative risk models as historical simulation or even copula functions. The central question of this paper is if these approaches lead to different results compared to the classical variance/covariance approach. Therefore, empirical data of the last 10 years is analysed. Both approaches are compared in the special context of the financial crisis. The worst case optimization and the Value at Risk (VaR are defined in order to define the minimum risk portfolio before and after the financial crisis. The result is that the financial crisis has nearly no impact onto the portfolio, but the two approaches lead to different results.

  5. Temporal variance reverses the impact of high mean intensity of stress in climate change experiments.

    Science.gov (United States)

    Benedetti-Cecchi, Lisandro; Bertocci, Iacopo; Vaselli, Stefano; Maggi, Elena

    2006-10-01

    Extreme climate events produce simultaneous changes to the mean and to the variance of climatic variables over ecological time scales. While several studies have investigated how ecological systems respond to changes in mean values of climate variables, the combined effects of mean and variance are poorly understood. We examined the response of low-shore assemblages of algae and invertebrates of rocky seashores in the northwest Mediterranean to factorial manipulations of mean intensity and temporal variance of aerial exposure, a type of disturbance whose intensity and temporal patterning of occurrence are predicted to change with changing climate conditions. Effects of variance were often in the opposite direction of those elicited by changes in the mean. Increasing aerial exposure at regular intervals had negative effects both on diversity of assemblages and on percent cover of filamentous and coarsely branched algae, but greater temporal variance drastically reduced these effects. The opposite was observed for the abundance of barnacles and encrusting coralline algae, where high temporal variance of aerial exposure either reversed a positive effect of mean intensity (barnacles) or caused a negative effect that did not occur under low temporal variance (encrusting algae). These results provide the first experimental evidence that changes in mean intensity and temporal variance of climatic variables affect natural assemblages of species interactively, suggesting that high temporal variance may mitigate the ecological impacts of ongoing and predicted climate changes.

  6. Genetic and environmental variance in content dimensions of the MMPI.

    Science.gov (United States)

    Rose, R J

    1988-08-01

    To evaluate genetic and environmental variance in the Minnesota Multiphasic Personality Inventory (MMPI), I studied nine factor scales identified in the first item factor analysis of normal adult MMPIs in a sample of 820 adolescent and young adult co-twins. Conventional twin comparisons documented heritable variance in six of the nine MMPI factors (Neuroticism, Psychoticism, Extraversion, Somatic Complaints, Inadequacy, and Cynicism), whereas significant influence from shared environmental experience was found for four factors (Masculinity versus Femininity, Extraversion, Religious Orthodoxy, and Intellectual Interests). Genetic variance in the nine factors was more evident in results from twin sisters than those of twin brothers, and a developmental-genetic analysis, using hierarchical multiple regressions of double-entry matrixes of the twins' raw data, revealed that in four MMPI factor scales, genetic effects were significantly modulated by age or gender or their interaction during the developmental period from early adolescence to early adulthood.

  7. Is residual memory variance a valid method for quantifying cognitive reserve? A longitudinal application.

    Science.gov (United States)

    Zahodne, Laura B; Manly, Jennifer J; Brickman, Adam M; Narkhede, Atul; Griffith, Erica Y; Guzman, Vanessa A; Schupf, Nicole; Stern, Yaakov

    2015-10-01

    Cognitive reserve describes the mismatch between brain integrity and cognitive performance. Older adults with high cognitive reserve are more resilient to age-related brain pathology. Traditionally, cognitive reserve is indexed indirectly via static proxy variables (e.g., years of education). More recently, cross-sectional studies have suggested that reserve can be expressed as residual variance in episodic memory performance that remains after accounting for demographic factors and brain pathology (whole brain, hippocampal, and white matter hyperintensity volumes). The present study extends these methods to a longitudinal framework in a community-based cohort of 244 older adults who underwent two comprehensive neuropsychological and structural magnetic resonance imaging sessions over 4.6 years. On average, residual memory variance decreased over time, consistent with the idea that cognitive reserve is depleted over time. Individual differences in change in residual memory variance predicted incident dementia, independent of baseline residual memory variance. Multiple-group latent difference score models revealed tighter coupling between brain and language changes among individuals with decreasing residual memory variance. These results suggest that changes in residual memory variance may capture a dynamic aspect of cognitive reserve and could be a useful way to summarize individual cognitive responses to brain changes. Change in residual memory variance among initially non-demented older adults was a better predictor of incident dementia than residual memory variance measured at one time-point. Copyright © 2015. Published by Elsevier Ltd.

  8. Heritability, variance components and genetic advance of some ...

    African Journals Online (AJOL)

    Heritability, variance components and genetic advance of some yield and yield related traits in Ethiopian ... African Journal of Biotechnology ... randomized complete block design at Adet Agricultural Research Station in 2008 cropping season.

  9. Minimum Time Trajectory Optimization of CNC Machining with Tracking Error Constraints

    Directory of Open Access Journals (Sweden)

    Qiang Zhang

    2014-01-01

    Full Text Available An off-line optimization approach of high precision minimum time feedrate for CNC machining is proposed. Besides the ordinary considered velocity, acceleration, and jerk constraints, dynamic performance constraint of each servo drive is also considered in this optimization problem to improve the tracking precision along the optimized feedrate trajectory. Tracking error is applied to indicate the servo dynamic performance of each axis. By using variable substitution, the tracking error constrained minimum time trajectory planning problem is formulated as a nonlinear path constrained optimal control problem. Bang-bang constraints structure of the optimal trajectory is proved in this paper; then a novel constraint handling method is proposed to realize a convex optimization based solution of the nonlinear constrained optimal control problem. A simple ellipse feedrate planning test is presented to demonstrate the effectiveness of the approach. Then the practicability and robustness of the trajectory generated by the proposed approach are demonstrated by a butterfly contour machining example.

  10. Modality-Driven Classification and Visualization of Ensemble Variance

    Energy Technology Data Exchange (ETDEWEB)

    Bensema, Kevin; Gosink, Luke; Obermaier, Harald; Joy, Kenneth I.

    2016-10-01

    Advances in computational power now enable domain scientists to address conceptual and parametric uncertainty by running simulations multiple times in order to sufficiently sample the uncertain input space. While this approach helps address conceptual and parametric uncertainties, the ensemble datasets produced by this technique present a special challenge to visualization researchers as the ensemble dataset records a distribution of possible values for each location in the domain. Contemporary visualization approaches that rely solely on summary statistics (e.g., mean and variance) cannot convey the detailed information encoded in ensemble distributions that are paramount to ensemble analysis; summary statistics provide no information about modality classification and modality persistence. To address this problem, we propose a novel technique that classifies high-variance locations based on the modality of the distribution of ensemble predictions. Additionally, we develop a set of confidence metrics to inform the end-user of the quality of fit between the distribution at a given location and its assigned class. We apply a similar method to time-varying ensembles to illustrate the relationship between peak variance and bimodal or multimodal behavior. These classification schemes enable a deeper understanding of the behavior of the ensemble members by distinguishing between distributions that can be described by a single tendency and distributions which reflect divergent trends in the ensemble.

  11. Do Some Workers Have Minimum Wage Careers?

    Science.gov (United States)

    Carrington, William J.; Fallick, Bruce C.

    2001-01-01

    Most workers who begin their careers in minimum-wage jobs eventually gain more experience and move on to higher paying jobs. However, more than 8% of workers spend at least half of their first 10 working years in minimum wage jobs. Those more likely to have minimum wage careers are less educated, minorities, women with young children, and those…

  12. Does the Minimum Wage Affect Welfare Caseloads?

    Science.gov (United States)

    Page, Marianne E.; Spetz, Joanne; Millar, Jane

    2005-01-01

    Although minimum wages are advocated as a policy that will help the poor, few studies have examined their effect on poor families. This paper uses variation in minimum wages across states and over time to estimate the impact of minimum wage legislation on welfare caseloads. We find that the elasticity of the welfare caseload with respect to the…

  13. 29 CFR 4.159 - General minimum wage.

    Science.gov (United States)

    2010-07-01

    ... 29 Labor 1 2010-07-01 2010-07-01 true General minimum wage. 4.159 Section 4.159 Labor Office of... General minimum wage. The Act, in section 2(b)(1), provides generally that no contractor or subcontractor... a contract less than the minimum wage specified under section 6(a)(1) of the Fair Labor Standards...

  14. The variance of the locally measured Hubble parameter explained with different estimators

    DEFF Research Database (Denmark)

    Odderskov, Io Sandberg Hess; Hannestad, Steen; Brandbyge, Jacob

    2017-01-01

    We study the expected variance of measurements of the Hubble constant, H0, as calculated in either linear perturbation theory or using non-linear velocity power spectra derived from N-body simulations. We compare the variance with that obtained by carrying out mock observations in the N......-body simulations, and show that the estimator typically used for the local Hubble constant in studies based on perturbation theory is different from the one used in studies based on N-body simulations. The latter gives larger weight to distant sources, which explains why studies based on N-body simulations tend...... to obtain a smaller variance than that found from studies based on the power spectrum. Although both approaches result in a variance too small to explain the discrepancy between the value of H0 from CMB measurements and the value measured in the local universe, these considerations are important in light...

  15. Variance Risk Premia on Stocks and Bonds

    DEFF Research Database (Denmark)

    Mueller, Philippe; Sabtchevsky, Petar; Vedolin, Andrea

    Investors in fixed income markets are willing to pay a very large premium to be hedged against shocks in expected volatility and the size of this premium can be studied through variance swaps. Using thirty years of option and high-frequency data, we document the following novel stylized facts...

  16. Effect of exercising at minimum recommendations of the multiple sclerosis exercise guideline combined with structured education or attention control education - secondary results of the step it up randomised controlled trial.

    Science.gov (United States)

    Coote, Susan; Uszynski, Marcin; Herring, Matthew P; Hayes, Sara; Scarrott, Carl; Newell, John; Gallagher, Stephen; Larkin, Aidan; Motl, Robert W

    2017-06-24

    Recent exercise guidelines for people with multiple sclerosis (MS) recommend a minimum of 30 min moderate intensity aerobic exercise and resistance exercise twice per week. This trial compared the secondary outcomes of a combined 10-week guideline based intervention and a Social Cognitive Theory (SCT) education programme with the same exercise intervention involving an attention control education. Physically inactive people with MS, scoring 0-3 on Patient Determined Disease Steps Scale, with no MS relapse or change in MS medication, were randomised to 10-week exercise plus SCT education or exercise plus attention control education conditions. Outcomes included fatigue, depression, anxiety, strength, physical activity, SCT constructs and impact of MS and were measured by a blinded assessor pre and post-intervention and 3 and 6 month follow up. One hundred and seventy-four expressed interest, 92 were eligible and 65 enrolled. Using linear mixed effects models, the differences between groups on all secondary measures post-intervention and at follow-up were not significant. Post-hoc, exploratory, within group analysis identified improvements in both groups post intervention in fatigue (mean ∆(95% CI) SCT -4.99(-9.87, -0.21), p = 0.04, Control -7.68(-12.13, -3.23), p = 0.00), strength (SCT -1.51(-2.41, -0.60), p exercise planning (SCT 5.88(3.37, 8.39), p Exercising at the minimum guideline amount has a positive effect on fatigue, strength and PA that is sustained at 3 and 6 months following the cessation of the program. ClinicalTrials.gov, NCT02301442 , retrospectively registered on November 13th 2014.

  17. Variance in total levels of phospholipase C zeta (PLC-ζ) in human sperm may limit the applicability of quantitative immunofluorescent analysis as a diagnostic indicator of oocyte activation capability.

    Science.gov (United States)

    Kashir, Junaid; Jones, Celine; Mounce, Ginny; Ramadan, Walaa M; Lemmon, Bernadette; Heindryckx, Bjorn; de Sutter, Petra; Parrington, John; Turner, Karen; Child, Tim; McVeigh, Enda; Coward, Kevin

    2013-01-01

    To examine whether similar levels of phospholipase C zeta (PLC-ζ) protein are present in sperm from men whose ejaculates resulted in normal oocyte activation, and to examine whether a predominant pattern of PLC-ζ localization is linked to normal oocyte activation ability. Laboratory study. University laboratory. Control subjects (men with proven oocyte activation capacity; n = 16) and men whose sperm resulted in recurrent intracytoplasmic sperm injection failure (oocyte activation deficient [OAD]; n = 5). Quantitative immunofluorescent analysis of PLC-ζ protein in human sperm. Total levels of PLC-ζ fluorescence, proportions of sperm exhibiting PLC-ζ immunoreactivity, and proportions of PLC-ζ localization patterns in sperm from control and OAD men. Sperm from control subjects presented a significantly higher proportion of sperm exhibiting PLC-ζ immunofluorescence compared with infertile men diagnosed with OAD (82.6% and 27.4%, respectively). Total levels of PLC-ζ in sperm from individual control and OAD patients exhibited significant variance, with sperm from 10 out of 16 (62.5%) exhibiting levels similar to OAD samples. Predominant PLC-ζ localization patterns varied between control and OAD samples with no predictable or consistent pattern. The results indicate that sperm from control men exhibited significant variance in total levels of PLC-ζ protein, as well as significant variance in the predominant localization pattern. Such variance may hinder the diagnostic application of quantitative PLC-ζ immunofluorescent analysis. Copyright © 2013 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

  18. On Mean-Variance Hedging of Bond Options with Stochastic Risk Premium Factor

    NARCIS (Netherlands)

    Aihara, ShinIchi; Bagchi, Arunabha; Kumar, Suresh K.

    2014-01-01

    We consider the mean-variance hedging problem for pricing bond options using the yield curve as the observation. The model considered contains infinite-dimensional noise sources with the stochastically- varying risk premium. Hence our model is incomplete. We consider mean-variance hedging under the

  19. Problems of variance reduction in the simulation of random variables

    International Nuclear Information System (INIS)

    Lessi, O.

    1987-01-01

    The definition of the uniform linear generator is given and some of the mostly used tests to evaluate the uniformity and the independence of the obtained determinations are listed. The problem of calculating, through simulation, some moment W of a random variable function is taken into account. The Monte Carlo method enables the moment W to be estimated and the estimator variance to be obtained. Some techniques for the construction of other estimators of W with a reduced variance are introduced

  20. Mean-variance portfolio allocation with a value at risk constraint

    OpenAIRE

    Enrique Sentana

    2001-01-01

    In this Paper, I first provide a simple unifying approach to static Mean-Variance analysis and Value at Risk, which highlights their similarities and differences. Then I use it to explain how fund managers can take investment decisions that satisfy the VaR restrictions imposed on them by regulators, within the well-known Mean-Variance allocation framework. I do so by introducing a new type of line to the usual mean-standard deviation diagram, called IsoVaR,which represents all the portfolios ...

  1. Variance-based sensitivity analysis for wastewater treatment plant modelling.

    Science.gov (United States)

    Cosenza, Alida; Mannina, Giorgio; Vanrolleghem, Peter A; Neumann, Marc B

    2014-02-01

    Global sensitivity analysis (GSA) is a valuable tool to support the use of mathematical models that characterise technical or natural systems. In the field of wastewater modelling, most of the recent applications of GSA use either regression-based methods, which require close to linear relationships between the model outputs and model factors, or screening methods, which only yield qualitative results. However, due to the characteristics of membrane bioreactors (MBR) (non-linear kinetics, complexity, etc.) there is an interest to adequately quantify the effects of non-linearity and interactions. This can be achieved with variance-based sensitivity analysis methods. In this paper, the Extended Fourier Amplitude Sensitivity Testing (Extended-FAST) method is applied to an integrated activated sludge model (ASM2d) for an MBR system including microbial product formation and physical separation processes. Twenty-one model outputs located throughout the different sections of the bioreactor and 79 model factors are considered. Significant interactions among the model factors are found. Contrary to previous GSA studies for ASM models, we find the relationship between variables and factors to be non-linear and non-additive. By analysing the pattern of the variance decomposition along the plant, the model factors having the highest variance contributions were identified. This study demonstrates the usefulness of variance-based methods in membrane bioreactor modelling where, due to the presence of membranes and different operating conditions than those typically found in conventional activated sludge systems, several highly non-linear effects are present. Further, the obtained results highlight the relevant role played by the modelling approach for MBR taking into account simultaneously biological and physical processes. © 2013.

  2. Experimental investigations of the minimum ignition energy and the minimum ignition temperature of inert and combustible dust cloud mixtures

    Energy Technology Data Exchange (ETDEWEB)

    Addai, Emmanuel Kwasi, E-mail: emmanueladdai41@yahoo.com; Gabel, Dieter; Krause, Ulrich

    2016-04-15

    Highlights: • Ignition sensitivity of a highly flammable dust decreases upon addition of inert dust. • Minimum ignition temperature of a highly flammable dust increases when inert concentration increase. • Minimum ignition energy of a highly flammable dust increases when inert concentration increase. • The permissible range for the inert mixture to minimize the ignition risk lies between 60 to 80%. - Abstract: The risks associated with dust explosions still exist in industries that either process or handle combustible dust. This explosion risk could be prevented or mitigated by applying the principle of inherent safety (moderation). This is achieved by adding an inert material to a highly combustible material in order to decrease the ignition sensitivity of the combustible dust. The presented paper deals with the experimental investigation of the influence of adding an inert dust on the minimum ignition energy and the minimum ignition temperature of the combustible/inert dust mixtures. The experimental investigation was done in two laboratory scale equipment: the Hartmann apparatus and the Godbert-Greenwald furnace for the minimum ignition energy and the minimum ignition temperature test respectively. This was achieved by mixing various amounts of three inert materials (magnesium oxide, ammonium sulphate and sand) and six combustible dusts (brown coal, lycopodium, toner, niacin, corn starch and high density polyethylene). Generally, increasing the inert materials concentration increases the minimum ignition energy as well as the minimum ignition temperatures until a threshold is reached where no ignition was obtained. The permissible range for the inert mixture to minimize the ignition risk lies between 60 to 80%.

  3. Experimental investigations of the minimum ignition energy and the minimum ignition temperature of inert and combustible dust cloud mixtures

    International Nuclear Information System (INIS)

    Addai, Emmanuel Kwasi; Gabel, Dieter; Krause, Ulrich

    2016-01-01

    Highlights: • Ignition sensitivity of a highly flammable dust decreases upon addition of inert dust. • Minimum ignition temperature of a highly flammable dust increases when inert concentration increase. • Minimum ignition energy of a highly flammable dust increases when inert concentration increase. • The permissible range for the inert mixture to minimize the ignition risk lies between 60 to 80%. - Abstract: The risks associated with dust explosions still exist in industries that either process or handle combustible dust. This explosion risk could be prevented or mitigated by applying the principle of inherent safety (moderation). This is achieved by adding an inert material to a highly combustible material in order to decrease the ignition sensitivity of the combustible dust. The presented paper deals with the experimental investigation of the influence of adding an inert dust on the minimum ignition energy and the minimum ignition temperature of the combustible/inert dust mixtures. The experimental investigation was done in two laboratory scale equipment: the Hartmann apparatus and the Godbert-Greenwald furnace for the minimum ignition energy and the minimum ignition temperature test respectively. This was achieved by mixing various amounts of three inert materials (magnesium oxide, ammonium sulphate and sand) and six combustible dusts (brown coal, lycopodium, toner, niacin, corn starch and high density polyethylene). Generally, increasing the inert materials concentration increases the minimum ignition energy as well as the minimum ignition temperatures until a threshold is reached where no ignition was obtained. The permissible range for the inert mixture to minimize the ignition risk lies between 60 to 80%.

  4. Fundamentals of exploratory analysis of variance

    CERN Document Server

    Hoaglin, David C; Tukey, John W

    2009-01-01

    The analysis of variance is presented as an exploratory component of data analysis, while retaining the customary least squares fitting methods. Balanced data layouts are used to reveal key ideas and techniques for exploration. The approach emphasizes both the individual observations and the separate parts that the analysis produces. Most chapters include exercises and the appendices give selected percentage points of the Gaussian, t, F chi-squared and studentized range distributions.

  5. On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models

    Science.gov (United States)

    Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.

    2017-12-01

    Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.

  6. Physiological and Molecular Response of Prorocentrum minimum to Tannic Acid: An Experimental Study to Evaluate the Feasibility of Using Tannic Acid in Controling the Red Tide in a Eutrophic Coastal Water

    Directory of Open Access Journals (Sweden)

    Byungkwan Jeong

    2016-05-01

    Full Text Available Bioassay and gene expression experiments were conducted in order to evaluate the growth and physiology of Prorocentrum minimum isolated from a eutrophic coastal water in response to tannic acid. In the bioassay experiments, variations in abundance, chlorophyll (chl a concentration, maximum fluorescence (in vivo Fm, and photosynthetic efficiency (Fv/Fm were measured over the course of a seven-day incubation. Moreover, stress-related gene expression in both the control and an experimental (2.5 ppm TA treatment group was observed for 24 h and 48 h. The molecular markers used in this study were the heat shock proteins (Hsp70 and Hsp90 and cyclophilin (CYP. The findings show that P. minimum can thrive and grow at low concentrations (<2.5 ppm of tannic acid, and, above this concentration, cells begin to slow down development. In addition, TA concentration of 10 ppm halted photosynthetic activity. At the molecular level, treatment with tannic acid increased the expression of Hsp70, Hsp90, and CYP, and heat shock proteins are more upregulated than the cyclophilin gene. Exposure to tannic acid increased the expression of stress factors over time (48 h by 10- to 27-fold the expression level of the control group. These results suggest that tannic acid can be used to control harmful algal blooms such as those containing P. minimum in eutrophic coastal waters.

  7. A new variance stabilizing transformation for gene expression data analysis.

    Science.gov (United States)

    Kelmansky, Diana M; Martínez, Elena J; Leiva, Víctor

    2013-12-01

    In this paper, we introduce a new family of power transformations, which has the generalized logarithm as one of its members, in the same manner as the usual logarithm belongs to the family of Box-Cox power transformations. Although the new family has been developed for analyzing gene expression data, it allows a wider scope of mean-variance related data to be reached. We study the analytical properties of the new family of transformations, as well as the mean-variance relationships that are stabilized by using its members. We propose a methodology based on this new family, which includes a simple strategy for selecting the family member adequate for a data set. We evaluate the finite sample behavior of different classical and robust estimators based on this strategy by Monte Carlo simulations. We analyze real genomic data by using the proposed transformation to empirically show how the new methodology allows the variance of these data to be stabilized.

  8. Pricing perpetual American options under multiscale stochastic elasticity of variance

    International Nuclear Information System (INIS)

    Yoon, Ji-Hun

    2015-01-01

    Highlights: • We study the effects of the stochastic elasticity of variance on perpetual American option. • Our SEV model consists of a fast mean-reverting factor and a slow mean-revering factor. • A slow scale factor has a very significant impact on the option price. • We analyze option price structures through the market prices of elasticity risk. - Abstract: This paper studies pricing the perpetual American options under a constant elasticity of variance type of underlying asset price model where the constant elasticity is replaced by a fast mean-reverting Ornstein–Ulenbeck process and a slowly varying diffusion process. By using a multiscale asymptotic analysis, we find the impact of the stochastic elasticity of variance on the option prices and the optimal exercise prices with respect to model parameters. Our results enhance the existing option price structures in view of flexibility and applicability through the market prices of elasticity risk

  9. New Minimum Wage Research: A Symposium.

    Science.gov (United States)

    Ehrenberg, Ronald G.; And Others

    1992-01-01

    Includes "Introduction" (Ehrenberg); "Effect of the Minimum Wage [MW] on the Fast-Food Industry" (Katz, Krueger); "Using Regional Variation in Wages to Measure Effects of the Federal MW" (Card); "Do MWs Reduce Employment?" (Card); "Employment Effects of Minimum and Subminimum Wages" (Neumark,…

  10. Teaching the Minimum Wage in Econ 101 in Light of the New Economics of the Minimum Wage.

    Science.gov (United States)

    Krueger, Alan B.

    2001-01-01

    Argues that the recent controversy over the effect of the minimum wage on employment offers an opportunity for teaching introductory economics. Examines eight textbooks to determine topic coverage but finds little consensus. Describes how minimum wage effects should be taught. (RLH)

  11. Passivity Based Stabilization of Non-minimum Phase Nonlinear Systems

    Czech Academy of Sciences Publication Activity Database

    Travieso-Torres, J.C.; Duarte-Mermoud, M.A.; Zagalak, Petr

    2009-01-01

    Roč. 45, č. 3 (2009), s. 417-426 ISSN 0023-5954 R&D Projects: GA ČR(CZ) GA102/07/1596 Institutional research plan: CEZ:AV0Z10750506 Keywords : nonlinear systems * stabilisation * passivity * state feedback Subject RIV: BC - Control Systems Theory Impact factor: 0.445, year: 2009 http://library.utia.cas.cz/separaty/2009/AS/zagalak-passivity based stabilization of non-minimum phase nonlinear systems.pdf

  12. Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation.

    Science.gov (United States)

    Yang, Ye; Christensen, Ole F; Sorensen, Daniel

    2011-02-01

    Over recent years, statistical support for the presence of genetic factors operating at the level of the environmental variance has come from fitting a genetically structured heterogeneous variance model to field or experimental data in various species. Misleading results may arise due to skewness of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box-Cox transformations. Litter size data in rabbits and pigs that had previously been analysed in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box-Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected by the presence of asymmetry in the distribution of data. We recommend that to avoid one important source of spurious inferences, future work seeking support for a genetic component acting on environmental variation using a parametric approach based on normality assumptions confirms that these are met.

  13. Methods to estimate the between‐study variance and its uncertainty in meta‐analysis†

    Science.gov (United States)

    Jackson, Dan; Viechtbauer, Wolfgang; Bender, Ralf; Bowden, Jack; Knapp, Guido; Kuss, Oliver; Higgins, Julian PT; Langan, Dean; Salanti, Georgia

    2015-01-01

    Meta‐analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between‐study variability, which is typically modelled using a between‐study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between‐study variance, has been long challenged. Our aim is to identify known methods for estimation of the between‐study variance and its corresponding uncertainty, and to summarise the simulation and empirical evidence that compares them. We identified 16 estimators for the between‐study variance, seven methods to calculate confidence intervals, and several comparative studies. Simulation studies suggest that for both dichotomous and continuous data the estimator proposed by Paule and Mandel and for continuous data the restricted maximum likelihood estimator are better alternatives to estimate the between‐study variance. Based on the scenarios and results presented in the published studies, we recommend the Q‐profile method and the alternative approach based on a ‘generalised Cochran between‐study variance statistic’ to compute corresponding confidence intervals around the resulting estimates. Our recommendations are based on a qualitative evaluation of the existing literature and expert consensus. Evidence‐based recommendations require an extensive simulation study where all methods would be compared under the same scenarios. © 2015 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd. PMID:26332144

  14. 30 CFR 75.1431 - Minimum rope strength.

    Science.gov (United States)

    2010-07-01

    ..., including rotation resistant). For rope lengths less than 3,000 feet: Minimum Value=Static Load×(7.0−0.001L) For rope lengths 3,000 feet or greater: Minimum Value=Static Load×4.0 (b) Friction drum ropes. For rope lengths less than 4,000 feet: Minimum Value=Static Load×(7.0−0.0005L) For rope lengths 4,000 feet...

  15. Genetic variance in micro-environmental sensitivity for milk and milk quality in Walloon Holstein cattle.

    Science.gov (United States)

    Vandenplas, J; Bastin, C; Gengler, N; Mulder, H A

    2013-09-01

    Animals that are robust to environmental changes are desirable in the current dairy industry. Genetic differences in micro-environmental sensitivity can be studied through heterogeneity of residual variance between animals. However, residual variance between animals is usually assumed to be homogeneous in traditional genetic evaluations. The aim of this study was to investigate genetic heterogeneity of residual variance by estimating variance components in residual variance for milk yield, somatic cell score, contents in milk (g/dL) of 2 groups of milk fatty acids (i.e., saturated and unsaturated fatty acids), and the content in milk of one individual fatty acid (i.e., oleic acid, C18:1 cis-9), for first-parity Holstein cows in the Walloon Region of Belgium. A total of 146,027 test-day records from 26,887 cows in 747 herds were available. All cows had at least 3 records and a known sire. These sires had at least 10 cows with records and each herd × test-day had at least 5 cows. The 5 traits were analyzed separately based on fixed lactation curve and random regression test-day models for the mean. Estimation of variance components was performed by running iteratively expectation maximization-REML algorithm by the implementation of double hierarchical generalized linear models. Based on fixed lactation curve test-day mean models, heritability for residual variances ranged between 1.01×10(-3) and 4.17×10(-3) for all traits. The genetic standard deviation in residual variance (i.e., approximately the genetic coefficient of variation of residual variance) ranged between 0.12 and 0.17. Therefore, some genetic variance in micro-environmental sensitivity existed in the Walloon Holstein dairy cattle for the 5 studied traits. The standard deviations due to herd × test-day and permanent environment in residual variance ranged between 0.36 and 0.45 for herd × test-day effect and between 0.55 and 0.97 for permanent environmental effect. Therefore, nongenetic effects also

  16. Variance estimation for complex indicators of poverty and inequality using linearization techniques

    Directory of Open Access Journals (Sweden)

    Guillaume Osier

    2009-12-01

    Full Text Available The paper presents the Eurostat experience in calculating measures of precision, including standard errors, confidence intervals and design effect coefficients - the ratio of the variance of a statistic with the actual sample design to the variance of that statistic with a simple random sample of same size - for the "Laeken" indicators, that is, a set of complex indicators of poverty and inequality which had been set out in the framework of the EU-SILC project (European Statistics on Income and Living Conditions. The Taylor linearization method (Tepping, 1968; Woodruff, 1971; Wolter, 1985; Tille, 2000 is actually a well-established method to obtain variance estimators for nonlinear statistics such as ratios, correlation or regression coefficients. It consists of approximating a nonlinear statistic with a linear function of the observations by using first-order Taylor Series expansions. Then, an easily found variance estimator of the linear approximation is used as an estimator of the variance of the nonlinear statistic. Although the Taylor linearization method handles all the nonlinear statistics which can be expressed as a smooth function of estimated totals, the approach fails to encompass the "Laeken" indicators since the latter are having more complex mathematical expressions. Consequently, a generalized linearization method (Deville, 1999, which relies on the concept of influence function (Hampel, Ronchetti, Rousseeuw and Stahel, 1986, has been implemented. After presenting the EU-SILC instrument and the main target indicators for which variance estimates are needed, the paper elaborates on the main features of the linearization approach based on influence functions. Ultimately, estimated standard errors, confidence intervals and design effect coefficients obtained from this approach are presented and discussed.

  17. An Efficient SDN Load Balancing Scheme Based on Variance Analysis for Massive Mobile Users

    Directory of Open Access Journals (Sweden)

    Hong Zhong

    2015-01-01

    Full Text Available In a traditional network, server load balancing is used to satisfy the demand for high data volumes. The technique requires large capital investment while offering poor scalability and flexibility, which difficultly supports highly dynamic workload demands from massive mobile users. To solve these problems, this paper analyses the principle of software-defined networking (SDN and presents a new probabilistic method of load balancing based on variance analysis. The method can be used to dynamically manage traffic flows for supporting massive mobile users in SDN networks. The paper proposes a solution using the OpenFlow virtual switching technology instead of the traditional hardware switching technology. A SDN controller monitors data traffic of each port by means of variance analysis and provides a probability-based selection algorithm to redirect traffic dynamically with the OpenFlow technology. Compared with the existing load balancing methods which were designed to support traditional networks, this solution has lower cost, higher reliability, and greater scalability which satisfy the needs of mobile users.

  18. Fluctuations in atomic collision cascades - variance and correlations in sputtering and defect distributions

    International Nuclear Information System (INIS)

    Chakarova, R.; Pazsit, I.

    1997-01-01

    Fluctuation phenomena are investigated in various collision processes, i.e. ion bombardment induced sputtering and defect creation. The mean and variance of the sputter yield and the vacancies and interstitials are calculated as functions of the ion energy and the ion-target mass ratio. It is found that the relative variance of the defects in half-spaces and the relative variance of the sputter yield are not monotonous functions of the mass ratio. Two-point correlation functions in the depth variable, as well as sputtered energy, are also calculated. These functions help interpreting the behaviour of the relative variances of the integrated quantities, as well as understanding the cascade dynamics. All calculations are based on Lindhard power-law cross sections and use a binary collision Monte Carlo algorithm. 30 refs, 25 figs

  19. Fluctuations in atomic collision cascades - variance and correlations in sputtering and defect distributions

    Energy Technology Data Exchange (ETDEWEB)

    Chakarova, R.; Pazsit, I.

    1997-01-01

    Fluctuation phenomena are investigated in various collision processes, i.e. ion bombardment induced sputtering and defect creation. The mean and variance of the sputter yield and the vacancies and interstitials are calculated as functions of the ion energy and the ion-target mass ratio. It is found that the relative variance of the defects in half-spaces and the relative variance of the sputter yield are not monotonous functions of the mass ratio. Two-point correlation functions in the depth variable, as well as sputtered energy, are also calculated. These functions help interpreting the behaviour of the relative variances of the integrated quantities, as well as understanding the cascade dynamics. All calculations are based on Lindhard power-law cross sections and use a binary collision Monte Carlo algorithm. 30 refs, 25 figs.

  20. On discrete stochastic processes with long-lasting time dependence in the variance

    Science.gov (United States)

    Queirós, S. M. D.

    2008-11-01

    In this manuscript, we analytically and numerically study statistical properties of an heteroskedastic process based on the celebrated ARCH generator of random variables whose variance is defined by a memory of qm-exponencial, form (eqm=1 x=ex). Specifically, we inspect the self-correlation function of squared random variables as well as the kurtosis. In addition, by numerical procedures, we infer the stationary probability density function of both of the heteroskedastic random variables and the variance, the multiscaling properties, the first-passage times distribution, and the dependence degree. Finally, we introduce an asymmetric variance version of the model that enables us to reproduce the so-called leverage effect in financial markets.

  1. A Cure for Variance Inflation in High Dimensional Kernel Principal Component Analysis

    DEFF Research Database (Denmark)

    Abrahamsen, Trine Julie; Hansen, Lars Kai

    2011-01-01

    Small sample high-dimensional principal component analysis (PCA) suffers from variance inflation and lack of generalizability. It has earlier been pointed out that a simple leave-one-out variance renormalization scheme can cure the problem. In this paper we generalize the cure in two directions......: First, we propose a computationally less intensive approximate leave-one-out estimator, secondly, we show that variance inflation is also present in kernel principal component analysis (kPCA) and we provide a non-parametric renormalization scheme which can quite efficiently restore generalizability in kPCA....... As for PCA our analysis also suggests a simplified approximate expression. © 2011 Trine J. Abrahamsen and Lars K. Hansen....

  2. Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.

    Science.gov (United States)

    Ritz, Christian; Van der Vliet, Leana

    2009-09-01

    The advantages of using regression-based techniques to derive endpoints from environmental toxicity data are clear, and slowly, this superior analytical technique is gaining acceptance. As use of regression-based analysis becomes more widespread, some of the associated nuances and potential problems come into sharper focus. Looking at data sets that cover a broad spectrum of standard test species, we noticed that some model fits to data failed to meet two key assumptions-variance homogeneity and normality-that are necessary for correct statistical analysis via regression-based techniques. Failure to meet these assumptions often is caused by reduced variance at the concentrations showing severe adverse effects. Although commonly used with linear regression analysis, transformation of the response variable only is not appropriate when fitting data using nonlinear regression techniques. Through analysis of sample data sets, including Lemna minor, Eisenia andrei (terrestrial earthworm), and algae, we show that both the so-called Box-Cox transformation and use of the Poisson distribution can help to correct variance heterogeneity and nonnormality and so allow nonlinear regression analysis to be implemented. Both the Box-Cox transformation and the Poisson distribution can be readily implemented into existing protocols for statistical analysis. By correcting for nonnormality and variance heterogeneity, these two statistical tools can be used to encourage the transition to regression-based analysis and the depreciation of less-desirable and less-flexible analytical techniques, such as linear interpolation.

  3. Analysis of force variance for a continuous miner drum using the Design of Experiments method

    Energy Technology Data Exchange (ETDEWEB)

    S. Somanchi; V.J. Kecojevic; C.J. Bise [Pennsylvania State University, University Park, PA (United States)

    2006-06-15

    Continuous miners (CMs) are excavating machines designed to extract a variety of minerals by underground mining. The variance in force experienced by the cutting drum is a very important aspect that must be considered during drum design. A uniform variance essentially means that an equal load is applied on the individual cutting bits and this, in turn, enables better cutting action, greater efficiency, and longer bit and machine life. There are certain input parameters used in the drum design whose exact relationships with force variance are not clearly understood. This paper determines (1) the factors that have a significant effect on the force variance of the drum and (2) the values that can be assigned to these factors to minimize the force variance. A computer program, Continuous Miner Drum (CMD), was developed in collaboration with Kennametal, Inc. to facilitate the mechanical design of CM drums. CMD also facilitated data collection for determining significant factors affecting force variance. Six input parameters, including centre pitch, outer pitch, balance angle, shift angle, set angle and relative angle were tested at two levels. Trials were configured using the Design of Experiments (DoE) method where 2{sup 6} full-factorial experimental design was selected to investigate the effect of these factors on force variance. Results from the analysis show that all parameters except balance angle, as well as their interactions, significantly affect the force variance.

  4. Executive functions cannot be distinguished from general intelligence: Two variations on a single theme within a symphony of latent variance

    Directory of Open Access Journals (Sweden)

    Donald R Royall

    2014-10-01

    Full Text Available The empirical foundation of executive control function (ECF remains controversial. We have employed structural equation models (SEM to explicitly distinguish domain-specific variance in ECF performance from memory (MEM and shared cognitive performance variance, i.e., Spearman’s g. ECF does not survive adjustment for both MEM and g in a well fitting model of data obtained from non-demented older persons (N = 193. Instead, the variance in putative ECF measures is attributable only to g, and related to functional status only through a fraction of that construct (i.e., dECF. dECF is a homolog of the latent variable δ, which we have previously associated specifically with the Default Mode Network (DMN. These findings undermine the validity of ECF and its putative association with the frontal lobe. ECF may have no existence independent of general intelligence, and no functionally salient association with the frontal lobe outside of that structure’s contribution to the DMN.

  5. 78 FR 14122 - Revocation of Permanent Variances

    Science.gov (United States)

    2013-03-04

    ... Douglas Fir planking had to have at least a 1,900 fiber stress and 1,900,000 modulus of elasticity, while the Yellow Pine planking had to have at least 2,500 fiber stress and 2,000,000 modulus of elasticity... the permanent variances, and affected employees, to submit written data, views, and arguments...

  6. Minimum Entropy-Based Cascade Control for Governing Hydroelectric Turbines

    Directory of Open Access Journals (Sweden)

    Mifeng Ren

    2014-06-01

    Full Text Available In this paper, an improved cascade control strategy is presented for hydroturbine speed governors. Different from traditional proportional-integral-derivative (PID control and model predictive control (MPC strategies, the performance index of the outer controller is constructed by integrating the entropy and mean value of the tracking error with the constraints on control energy. The inner controller is implemented by a proportional controller. Compared with the conventional PID-P and MPC-P cascade control methods, the proposed cascade control strategy can effectively decrease fluctuations of hydro-turbine speed under non-Gaussian disturbance conditions in practical hydropower plants. Simulation results show the advantages of the proposed cascade control method.

  7. Fuzzy Stabilization for Nonlinear Discrete Ship Steering Stochastic Systems Subject to State Variance and Passivity Constraints

    Directory of Open Access Journals (Sweden)

    Wen-Jer Chang

    2014-01-01

    Full Text Available For nonlinear discrete-time stochastic systems, a fuzzy controller design methodology is developed in this paper subject to state variance constraint and passivity constraint. According to fuzzy model based control technique, the nonlinear discrete-time stochastic systems considered in this paper are represented by the discrete-time Takagi-Sugeno fuzzy models with multiplicative noise. Employing Lyapunov stability theory, upper bound covariance control theory, and passivity theory, some sufficient conditions are derived to find parallel distributed compensation based fuzzy controllers. In order to solve these sufficient conditions, an iterative linear matrix inequality algorithm is applied based on the linear matrix inequality technique. Finally, the fuzzy stabilization problem for nonlinear discrete ship steering stochastic systems is investigated in the numerical example to illustrate the feasibility and validity of proposed fuzzy controller design method.

  8. The impact of the UK National Minimum Wage on mental health

    Directory of Open Access Journals (Sweden)

    Christoph Kronenberg

    2017-12-01

    Full Text Available Despite an emerging literature, there is still sparse and mixed evidence on the wider societal benefits of Minimum Wage policies, including their effects on mental health. Furthermore, causal evidence on the relationship between earnings and mental health is limited. We focus on low-wage earners, who are at higher risk of psychological distress, and exploit the quasi-experiment provided by the introduction of the UK National Minimum Wage (NMW to identify the causal impact of wage increases on mental health. We employ difference-in-differences models and find that the introduction of the UK NMW had no effect on mental health. Our estimates do not appear to support earlier findings which indicate that minimum wages affect mental health of low-wage earners. A series of robustness checks accounting for measurement error, as well as treatment and control group composition, confirm our main results. Overall, our findings suggest that policies aimed at improving the mental health of low-wage earners should either consider the non-wage characteristics of employment or potentially larger wage increases.

  9. The impact of the UK National Minimum Wage on mental health.

    Science.gov (United States)

    Kronenberg, Christoph; Jacobs, Rowena; Zucchelli, Eugenio

    2017-12-01

    Despite an emerging literature, there is still sparse and mixed evidence on the wider societal benefits of Minimum Wage policies, including their effects on mental health. Furthermore, causal evidence on the relationship between earnings and mental health is limited. We focus on low-wage earners, who are at higher risk of psychological distress, and exploit the quasi-experiment provided by the introduction of the UK National Minimum Wage (NMW) to identify the causal impact of wage increases on mental health. We employ difference-in-differences models and find that the introduction of the UK NMW had no effect on mental health. Our estimates do not appear to support earlier findings which indicate that minimum wages affect mental health of low-wage earners. A series of robustness checks accounting for measurement error, as well as treatment and control group composition, confirm our main results. Overall, our findings suggest that policies aimed at improving the mental health of low-wage earners should either consider the non-wage characteristics of employment or potentially larger wage increases.

  10. Estimation Methods for Non-Homogeneous Regression - Minimum CRPS vs Maximum Likelihood

    Science.gov (United States)

    Gebetsberger, Manuel; Messner, Jakob W.; Mayr, Georg J.; Zeileis, Achim

    2017-04-01

    Non-homogeneous regression models are widely used to statistically post-process numerical weather prediction models. Such regression models correct for errors in mean and variance and are capable to forecast a full probability distribution. In order to estimate the corresponding regression coefficients, CRPS minimization is performed in many meteorological post-processing studies since the last decade. In contrast to maximum likelihood estimation, CRPS minimization is claimed to yield more calibrated forecasts. Theoretically, both scoring rules used as an optimization score should be able to locate a similar and unknown optimum. Discrepancies might result from a wrong distributional assumption of the observed quantity. To address this theoretical concept, this study compares maximum likelihood and minimum CRPS estimation for different distributional assumptions. First, a synthetic case study shows that, for an appropriate distributional assumption, both estimation methods yield to similar regression coefficients. The log-likelihood estimator is slightly more efficient. A real world case study for surface temperature forecasts at different sites in Europe confirms these results but shows that surface temperature does not always follow the classical assumption of a Gaussian distribution. KEYWORDS: ensemble post-processing, maximum likelihood estimation, CRPS minimization, probabilistic temperature forecasting, distributional regression models

  11. Variance estimation in the analysis of microarray data

    KAUST Repository

    Wang, Yuedong; Ma, Yanyuan; Carroll, Raymond J.

    2009-01-01

    Microarrays are one of the most widely used high throughput technologies. One of the main problems in the area is that conventional estimates of the variances that are required in the t-statistic and other statistics are unreliable owing

  12. 30 CFR 281.30 - Minimum royalty.

    Science.gov (United States)

    2010-07-01

    ... 30 Mineral Resources 2 2010-07-01 2010-07-01 false Minimum royalty. 281.30 Section 281.30 Mineral Resources MINERALS MANAGEMENT SERVICE, DEPARTMENT OF THE INTERIOR OFFSHORE LEASING OF MINERALS OTHER THAN OIL, GAS, AND SULPHUR IN THE OUTER CONTINENTAL SHELF Financial Considerations § 281.30 Minimum royalty...

  13. On the Minimum Induced Drag of Wings -or- Thinking Outside the Box

    Science.gov (United States)

    Bowers, Albion H.

    2011-01-01

    Of all the types of drag, induced drag is associated with the creation and generation of lift over wings. Induced drag is directly driven by the span load that the aircraft is flying at. The tools by which to calculate and predict induced drag we use were created by Ludwig Prandtl in 1903. Within a decade after Prandtl created a tool for calculating induced drag, Prandtl and his students had optimized the problem to solve the minimum induced drag for a wing of a given span, formalized and written about in 1920. This solution is quoted in textbooks extensively today. Prandtl did not stop with this first solution, and came to a dramatically different solution in 1932. Subsequent development of this 1932 solution solves several aeronautics design difficulties simultaneously, including maximum performance, minimum structure, minimum drag loss due to control input, and solution to adverse yaw without a vertical tail. This presentation lists that solution by Prandtl, and the refinements by Horten, Jones, Kline, Viswanathan, and Whitcomb.

  14. State cigarette minimum price laws - United States, 2009.

    Science.gov (United States)

    2010-04-09

    Cigarette price increases reduce the demand for cigarettes and thereby reduce smoking prevalence, cigarette consumption, and youth initiation of smoking. Excise tax increases are the most effective government intervention to increase the price of cigarettes, but cigarette manufacturers use trade discounts, coupons, and other promotions to counteract the effects of these tax increases and appeal to price-sensitive smokers. State cigarette minimum price laws, initiated by states in the 1940s and 1950s to protect tobacco retailers from predatory business practices, typically require a minimum percentage markup to be added to the wholesale and/or retail price. If a statute prohibits trade discounts from the minimum price calculation, these laws have the potential to counteract discounting by cigarette manufacturers. To assess the status of cigarette minimum price laws in the United States, CDC surveyed state statutes and identified those states with minimum price laws in effect as of December 31, 2009. This report summarizes the results of that survey, which determined that 25 states had minimum price laws for cigarettes (median wholesale markup: 4.00%; median retail markup: 8.00%), and seven of those states also expressly prohibited the use of trade discounts in the minimum retail price calculation. Minimum price laws can help prevent trade discounting from eroding the positive effects of state excise tax increases and higher cigarette prices on public health.

  15. Decomposing variation in male reproductive success: age-specific variances and covariances through extra-pair and within-pair reproduction.

    Science.gov (United States)

    Lebigre, Christophe; Arcese, Peter; Reid, Jane M

    2013-07-01

    Age-specific variances and covariances in reproductive success shape the total variance in lifetime reproductive success (LRS), age-specific opportunities for selection, and population demographic variance and effective size. Age-specific (co)variances in reproductive success achieved through different reproductive routes must therefore be quantified to predict population, phenotypic and evolutionary dynamics in age-structured populations. While numerous studies have quantified age-specific variation in mean reproductive success, age-specific variances and covariances in reproductive success, and the contributions of different reproductive routes to these (co)variances, have not been comprehensively quantified in natural populations. We applied 'additive' and 'independent' methods of variance decomposition to complete data describing apparent (social) and realised (genetic) age-specific reproductive success across 11 cohorts of socially monogamous but genetically polygynandrous song sparrows (Melospiza melodia). We thereby quantified age-specific (co)variances in male within-pair and extra-pair reproductive success (WPRS and EPRS) and the contributions of these (co)variances to the total variances in age-specific reproductive success and LRS. 'Additive' decomposition showed that within-age and among-age (co)variances in WPRS across males aged 2-4 years contributed most to the total variance in LRS. Age-specific (co)variances in EPRS contributed relatively little. However, extra-pair reproduction altered age-specific variances in reproductive success relative to the social mating system, and hence altered the relative contributions of age-specific reproductive success to the total variance in LRS. 'Independent' decomposition showed that the (co)variances in age-specific WPRS, EPRS and total reproductive success, and the resulting opportunities for selection, varied substantially across males that survived to each age. Furthermore, extra-pair reproduction increased

  16. Some asymptotic theory for variance function smoothing | Kibua ...

    African Journals Online (AJOL)

    Simple selection of the smoothing parameter is suggested. Both homoscedastic and heteroscedastic regression models are considered. Keywords: Asymptotic, Smoothing, Kernel, Bandwidth, Bias, Variance, Mean squared error, Homoscedastic, Heteroscedastic. > East African Journal of Statistics Vol. 1 (1) 2005: pp. 9-22 ...

  17. Properties of realized variance under alternative sampling schemes

    NARCIS (Netherlands)

    Oomen, R.C.A.

    2006-01-01

    This paper investigates the statistical properties of the realized variance estimator in the presence of market microstructure noise. Different from the existing literature, the analysis relies on a pure jump process for high frequency security prices and explicitly distinguishes among alternative

  18. Estimation of Genetic Variance Components Including Mutation and Epistasis using Bayesian Approach in a Selection Experiment on Body Weight in Mice

    DEFF Research Database (Denmark)

    Widyas, Nuzul; Jensen, Just; Nielsen, Vivi Hunnicke

    Selection experiment was performed for weight gain in 13 generations of outbred mice. A total of 18 lines were included in the experiment. Nine lines were allotted to each of the two treatment diets (19.3 and 5.1 % protein). Within each diet three lines were selected upwards, three lines were...... selected downwards and three lines were kept as controls. Bayesian statistical methods are used to estimate the genetic variance components. Mixed model analysis is modified including mutation effect following the methods by Wray (1990). DIC was used to compare the model. Models including mutation effect...... have better fit compared to the model with only additive effect. Mutation as direct effect contributes 3.18% of the total phenotypic variance. While in the model with interactions between additive and mutation, it contributes 1.43% as direct effect and 1.36% as interaction effect of the total variance...

  19. Analysis of a genetically structured variance heterogeneity model using the Box-Cox transformation

    DEFF Research Database (Denmark)

    Yang, Ye; Christensen, Ole Fredslund; Sorensen, Daniel

    2011-01-01

    of the marginal distribution of the data. To investigate how the scale of measurement affects inferences, the genetically structured heterogeneous variance model is extended to accommodate the family of Box–Cox transformations. Litter size data in rabbits and pigs that had previously been analysed...... in the untransformed scale were reanalysed in a scale equal to the mode of the marginal posterior distribution of the Box–Cox parameter. In the rabbit data, the statistical evidence for a genetic component at the level of the environmental variance is considerably weaker than that resulting from an analysis...... in the original metric. In the pig data, the statistical evidence is stronger, but the coefficient of correlation between additive genetic effects affecting mean and variance changes sign, compared to the results in the untransformed scale. The study confirms that inferences on variances can be strongly affected...

  20. The influence of beam energy, mode and focal length on the control of laser ignition in an internal combustion engine

    International Nuclear Information System (INIS)

    Mullett, J D; Dodd, R; Williams, C J; Triantos, G; Dearden, G; Shenton, A T; Watkins, K G; Carroll, S D; Scarisbrick, A D; Keen, S

    2007-01-01

    This work involves a study on laser ignition (LI) in an internal combustion (IC) engine and investigates the effects on control of engine combustion performance and stability of varying specific laser parameters (beam energy, beam quality, minimum beam waist size, focal point volume and focal length). A Q-switched Nd : YAG laser operating at the fundamental wavelength 1064 nm was successfully used to ignite homogeneous stoichiometric gasoline and air mixtures in one cylinder of a 1.6 litre IC test engine, where the remaining three cylinders used conventional electrical spark ignition (SI). A direct comparison between LI and conventional SI is presented in terms of changes in coefficient of variability in indicated mean effective pressure (COV IMEP ) and the variance in the peak cylinder pressure position (Var PPP ). The laser was individually operated in three different modes by changing the diameter of the cavity aperture, where the results show that for specific parameters, LI performed better than SI in terms of combustion performance and stability. Minimum ignition energies for misfire free combustion ranging from 4 to 28 mJ were obtained for various optical and laser configurations and were compared with the equivalent minimum optical breakdown energies in air