Output Power Control of Wind Turbine Generator by Pitch Angle Control using Minimum Variance Control
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.
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.
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
The Distribution of the Sample Minimum-Variance Frontier
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...
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.
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)
Minimum variance and variance of outgoing quality limit MDS-1(c1, c2) plans
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.
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
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.
Double Minimum Variance Beamforming Method to Enhance Photoacoustic Imaging
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...
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.
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
A comparison between temporal and subband minimum variance adaptive beamforming
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
Multidimensional adaptive testing with a minimum error-variance criterion
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
A Robust Statistics Approach to Minimum Variance Portfolio Optimization
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.
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.
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...
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)
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...
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.
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.
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...
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...
The Achilles Heel of Normal Determinations via Minimum Variance Techniques: Worldline Dependencies
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
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...
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...
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...
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...
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.
Variance analysis refines overhead cost control.
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.
Iterative Minimum Variance Beamformer with Low Complexity for Medical Ultrasound Imaging.
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.
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)
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...
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
Minimum variance optimal rate allocation for multiplexed H.264/AVC bitstreams.
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.
Minimum variance rooting of phylogenetic trees and implications for species tree reconstruction.
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.
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).
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.
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.
Feedback brake distribution control for minimum pitch
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.
77 FR 32444 - Minimum Internal Control Standards
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...
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.
77 FR 43196 - Minimum Internal Control Standards and Technical Standards
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...
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.
Optimal control of LQG problem with an explicit trade-off between mean and variance
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.
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...
Does Public Sector Control Reduce Variance in School Quality?
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…
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.
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.)
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.
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.
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...
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
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
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
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.
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
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)
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
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.
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.
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.
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.
The scope and control of attention: Sources of variance in working memory capacity.
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.
Risk-sensitivity and the mean-variance trade-off: decision making in sensorimotor control.
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.
25 CFR 542.7 - What are the minimum internal control standards for bingo?
2010-04-01
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25 CFR 542.14 - What are the minimum internal control standards for the cage?
2010-04-01
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25 CFR 542.8 - What are the minimum internal control standards for pull tabs?
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...
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...
Stable Control of Firing Rate Mean and Variance by Dual Homeostatic Mechanisms.
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.
Output Feedback Adaptive Control of Non-Minimum Phase Systems Using Optimal Control Modification
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.
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.
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
Genetic control of residual variance of yearling weight in Nellore beef cattle.
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
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.
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...
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.
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...
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
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.
Genetic control of residual variance of yearling weight in nellore beef cattle
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
The singular minimum entropy $H_\\infty$ control problem
Stoorvogel, A.A.
1990-01-01
In this paper we search for controllers which minimize an entropy function of the closed loop transfer matrix under the constraint of internal stability and under the constraint that the closed loop transfer matrix has $H_\\infty$ norm less than some a priori given bound $\\gamma$. We find an explicit
14 CFR 25.149 - Minimum control speed.
2010-01-01
... used to simulate critical engine failure must represent the most critical mode of powerplant failure with respect to controllability expected in service. (b) VMC is the calibrated airspeed at which, when... be necessary to reduce power or thrust of the operative engines. During recovery, the airplane may...
14 CFR 23.149 - Minimum control speed.
2010-01-01
... not more than 5 degrees. The method used to simulate critical engine failure must represent the most critical mode of powerplant failure expected in service with respect to controllability. (b) VMC for... the critical engine is made inoperative to the point at which recovery to a direction parallel to the...
25 CFR 542.11 - What are the minimum internal control standards for pari-mutuel wagering?
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...
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.
Minimum detectable activities of contamination control survey equipment
International Nuclear Information System (INIS)
Goles, R.W.; Baumann, B.L.; Johnson, M.L.
1991-08-01
The Instrumentation ampersand External Dosimetry (I ampersand ED) Section of the Health Physics Department at the Pacific Northwest Laboratory (PNL) has performed a series of tests to determine the ability of portable survey instruments used at Hanford to detect radioactive contamination at levels required by DOE 5480.11. This semi-empirical study combines instrumental, statistical, and human factors as necessary to derive operational detection limits. These threshold detection values have been compared to existing contamination control requirements, and detection deficiencies have been identified when present. Portable survey instruments used on the Hanford Site identify the presence of radioactive surface contamination based on the detection of α-, β-, γ-, and/or x-radiation. However, except in some unique circumstances, most contamination monitors in use at Hanford are configured to detect either α-radiation alone or β- and γ-radiation together. Testing was therefore conducted on only these two categories of radiation detection devices. Nevertheless, many of the results obtained are generally applicable to all survey instruments, allowing performance evaluations to be extended to monitoring devices which are exclusively γ- and/or x-ray- sensitive. 6 figs., 2 tabs
Minimum power requirement for environmental control of aircraft
International Nuclear Information System (INIS)
Ordonez, Juan Carlos; Bejan, Adrian
2003-01-01
This paper addresses two basic issues in the thermodynamic optimization of environmental control systems (ECS) for aircraft: realistic limits for the minimal power requirement, and design features that facilitate operation at minimal power consumption. Four models are proposed and optimized. In the first, the ECS operates reversibly, the air stream in the cabin is mixed to one temperature, and the cabin experiences heat transfer with the ambient, across its insulation. The cabin temperature is fixed. In the second model, the fixed cabin temperature is assigned to the internal solid surfaces of the cabin, and a thermal resistance separates these surfaces from the air mixed in the cabin. In the third model, the ECS operates irreversibly, based on the bootstrap air cycle. The fourth model combines the ECS features of the third model with the cabin-environment interaction features of the second model. It is shown that in all models the temperature of the air stream that the ECS delivers to the cabin can be optimized for operation at minimal power. The effect of other design parameters and flying conditions is documented. The optimized air delivery temperature is relatively insensitive to the complexity of the model; for example, it is insensitive to the size of the heat exchanger used in the bootstrap air cycle. This study adds to the view that robustness is a characteristic of optimized complex flow systems, and that thermodynamic optimization results can be used for orientation in the pursuit of more complex and realistic designs
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.
MINIMUM VARIANCE BETA ESTIMATION WITH DYNAMIC CONSTRAINTS,
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
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.
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...
25 CFR 542.17 - What are the minimum internal control standards for complimentary services or items?
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...
25 CFR 543.16 - What are the minimum internal controls for information technology?
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...
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
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.
75 FR 55269 - Minimum Internal Control Standards for Class II Gaming
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...
76 FR 53817 - Minimum Internal Control Standards for Class II Gaming
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...
77 FR 60625 - Minimum Internal Control Standards for Class II Gaming
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...
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
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.
Colwell, Janice C; Pittman, Joyce; Raizman, Rose; Salvadalena, Ginger
To compare ostomy-related costs and incidence of peristomal skin complications (PSCs) for ceramide-infused ostomy skin barriers and control skin barriers. The ADVOCATE trial is a multi-centered randomized controlled trial, and double-blinded international study with an adaptive design. The sample comprised 153 adults from 25 sites from the United States, Canada, and Europe. Participants were seen in hospital and outpatient care settings. Data were collected by investigators at each site during face-to-face visits and during telephone check-in calls between visits. Cost of care data were collected using a questionnaire developed specifically for the study. The peristomal skin was assessed using the Ostomy Skin Tool. Health-related quality of life was measured using the SF-12v2. Patient-reported outcomes were collected using a patient-centered study-specific questionnaire. Cost of care was analyzed via analysis of covariance comparing total cost of care for 12 weeks between the 2 groups. The incidence of PSC was analyzed via Barnard's exact test comparing the incidence of PSCs between the control and treatment groups. Tertiary outcomes were exploratory in nature and not statistically powered. Use of the ceramide-infused barrier significantly reduced stoma-related cost of care over a 12-week period, resulting in a $36.46 decrease in cost (14% relative decrease). The adjusted average costs were $223.73 in the treatment group and $260.19 in the control group (P = .017). The overall incidence of PSCs in the study was 47.7%; PSC incidence was 40.5% for the treatment group versus 55.4% for controls (P = .069, 95% confidence interval of the difference: -1.2 to 30.4). Significantly more participants using the ceramide-infused skin barrier were "very satisfied" with barrier performance (75% vs 55%; P = .033), prevention of leakage (63% vs 38%; P < .01), and prevention of itching (53% vs 31%; P = .016). General postoperative improvement in health-related quality of life was
The Preventive Control of a Dengue Disease Using Pontryagin Minimum Principal
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.
Orthogonal control of expression mean and variance by epigenetic features at different genomic loci.
Dey, Siddharth S; Foley, Jonathan E; Limsirichai, Prajit; Schaffer, David V; Arkin, Adam P
2015-05-05
While gene expression noise has been shown to drive dramatic phenotypic variations, the molecular basis for this variability in mammalian systems is not well understood. Gene expression has been shown to be regulated by promoter architecture and the associated chromatin environment. However, the exact contribution of these two factors in regulating expression noise has not been explored. Using a dual-reporter lentiviral model system, we deconvolved the influence of the promoter sequence to systematically study the contribution of the chromatin environment at different genomic locations in regulating expression noise. By integrating a large-scale analysis to quantify mRNA levels by smFISH and protein levels by flow cytometry in single cells, we found that mean expression and noise are uncorrelated across genomic locations. Furthermore, we showed that this independence could be explained by the orthogonal control of mean expression by the transcript burst size and noise by the burst frequency. Finally, we showed that genomic locations displaying higher expression noise are associated with more repressed chromatin, thereby indicating the contribution of the chromatin environment in regulating expression noise. © 2015 The Authors. Published under the terms of the CC BY 4.0 license.
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.
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)
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.
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.
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.
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
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)
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.
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
Downside Variance Risk Premium
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...
Portfolio optimization with mean-variance model
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.
Davarian, F.
1994-01-01
The LOOP computer program was written to simulate the Automatic Frequency Control (AFC) subsystem of a Differential Minimum Shift Keying (DMSK) receiver with a bit rate of 2400 baud. The AFC simulated by LOOP is a first order loop configuration with a first order R-C filter. NASA has been investigating the concept of mobile communications based on low-cost, low-power terminals linked via geostationary satellites. Studies have indicated that low bit rate transmission is suitable for this application, particularly from the frequency and power conservation point of view. A bit rate of 2400 BPS is attractive due to its applicability to the linear predictive coding of speech. Input to LOOP includes the following: 1) the initial frequency error; 2) the double-sided loop noise bandwidth; 3) the filter time constants; 4) the amount of intersymbol interference; and 5) the bit energy to noise spectral density. LOOP output includes: 1) the bit number and the frequency error of that bit; 2) the computed mean of the frequency error; and 3) the standard deviation of the frequency error. LOOP is written in MS SuperSoft FORTRAN 77 for interactive execution and has been implemented on an IBM PC operating under PC DOS with a memory requirement of approximately 40K of 8 bit bytes. This program was developed in 1986.
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
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
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
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.
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
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.
DEFF Research Database (Denmark)
Due, Pernille; de Beaufort, Carine; Damsgaard, Mogens Trab
2013-01-01
. The frequency of intake of fruit, vegetables, sweets, sugary soft drinks, and daily breakfast was compared between the two groups. The glycemic control of the adolescents in the HSG cohort was determined by measuring glycated hemoglobin (HbA1c). RESULTS: Across countries in the HSBC survey...
Bouwman, R.; Young, K.; Lazzari, B.; Ravaglia, V.; Broeders, M.J.M.; Engen, R. van
2009-01-01
According to the European Guidelines for quality assured breast cancer screening and diagnosis, noise analysis is one of the measurements that needs to be performed as part of quality control procedures on digital mammography systems. However, the method recommended in the European Guidelines does
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
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
International Nuclear Information System (INIS)
Bouwman, R; Broeders, M; Van Engen, R; Young, K; Lazzari, B; Ravaglia, V
2009-01-01
According to the European Guidelines for quality assured breast cancer screening and diagnosis, noise analysis is one of the measurements that needs to be performed as part of quality control procedures on digital mammography systems. However, the method recommended in the European Guidelines does not discriminate sufficiently between systems with and without additional noise besides quantum noise. This paper attempts to give an alternative and relatively simple method for noise analysis which can divide noise into electronic noise, structured noise and quantum noise. Quantum noise needs to be the dominant noise source in clinical images for optimal performance of a digital mammography system, and therefore the amount of electronic and structured noise should be minimal. For several digital mammography systems, the noise was separated into components based on the measured pixel value, standard deviation (SD) of the image and the detector entrance dose. The results showed that differences between systems exist. Our findings confirm that the proposed method is able to discriminate systems based on their noise performance and is able to detect possible quality problems. Therefore, we suggest to replace the current method for noise analysis as described in the European Guidelines by the alternative method described in this paper.
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
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
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...
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.
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.
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.
Axial stability of VVER-1000 reactor with control with minimum standard deviation
International Nuclear Information System (INIS)
Afanas'ev, A.M.; Torlin, B.Z.
1980-01-01
Results are given of investigations on the stability of a reactor which has, in addition to an automatic controller, a height distribution regulator (HDR) based on an auxiliary control rod (CR) or a special shortened absorption rod (SAR). The HDR was controlled by using either a special ionization chamber (IC), generating an imbalance signal which sets the CR in motion, or two ionization chambers whose difference signal causes a displacement of the SAR. Since data from numerous pickups can be used to control the height field of the VVER-1000, it is of interest to analyze how this would affect the stability of the reactor. The analysis was carried out with the improved IRINA programs. 11 refs
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.
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...
Adaptive control of nonlinear system using online error minimum neural networks.
Jia, Chao; Li, Xiaoli; Wang, Kang; Ding, Dawei
2016-11-01
In this paper, a new learning algorithm named OEM-ELM (Online Error Minimized-ELM) is proposed based on ELM (Extreme Learning Machine) neural network algorithm and the spreading of its main structure. The core idea of this OEM-ELM algorithm is: online learning, evaluation of network performance, and increasing of the number of hidden nodes. It combines the advantages of OS-ELM and EM-ELM, which can improve the capability of identification and avoid the redundancy of networks. The adaptive control based on the proposed algorithm OEM-ELM is set up which has stronger adaptive capability to the change of environment. The adaptive control of chemical process Continuous Stirred Tank Reactor (CSTR) is also given for application. The simulation results show that the proposed algorithm with respect to the traditional ELM algorithm can avoid network redundancy and improve the control performance greatly. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Minimum-Voltage Vector Injection Method for Sensorless Control of PMSM for Low-Speed Operations
DEFF Research Database (Denmark)
Xie, Ge; Lu, Kaiyuan; Kumar, Dwivedi Sanjeet
2016-01-01
In this paper, a simple signal injection method is proposed for sensorless control of PMSM at low speed, which ideally requires one voltage vector only for position estimation. The proposed method is easy to implement resulting in low computation burden. No filters are needed for extracting...... may also be further developed to inject two opposite voltage vectors to reduce the effects of inverter voltage error on the position estimation accuracy. The effectiveness of the proposed method is demonstrated by comparing with other sensorless control method. Theoretical analysis and experimental...
Adaptive Control of Non-Minimum Phase Modal Systems Using Residual Mode Filters2. Parts 1 and 2
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.
25 CFR 542.12 - What are the minimum internal control standards for table games?
2010-04-01
... this section, if a gaming operation uses plastic cards (not plastic-coated cards), the cards may be... distribution, use, and control. Personnel from the cashier or pit departments shall have no access to the... cards and dice shall be maintained in a secure location to prevent unauthorized access and to reduce the...
Accuracy assessment of minimum control points for UAV photography and georeferencing
Skarlatos, D.; Procopiou, E.; Stavrou, G.; Gregoriou, M.
2013-08-01
In recent years, Autonomous Unmanned Aerial Vehicles (AUAV) became popular among researchers across disciplines because they combine many advantages. One major application is monitoring and mapping. Their ability to fly beyond eye sight autonomously, collecting data over large areas whenever, wherever, makes them excellent platform for monitoring hazardous areas or disasters. In both cases rapid mapping is needed while human access isn't always a given. Indeed, current automatic processing of aerial photos using photogrammetry and computer vision algorithms allows for rapid orthophomap production and Digital Surface Model (DSM) generation, as tools for monitoring and damage assessment. In such cases, control point measurement using GPS is either impossible, or time consuming or costly. This work investigates accuracies that can be attained using few or none control points over areas of one square kilometer, in two test sites; a typical block and a corridor survey. On board GPS data logged during AUAV's flight are being used for direct georeferencing, while ground check points are being used for evaluation. In addition various control point layouts are being tested using bundle adjustment for accuracy evaluation. Results indicate that it is possible to use on board single frequency GPS for direct georeferencing in cases of disaster management or areas without easy access, or even over featureless areas. Due to large numbers of tie points in the bundle adjustment, horizontal accuracy can be fulfilled with a rather small number of control points, but vertical accuracy may not.
Causal Tracking Control of a Non-Minimum Phase HIL Transmission Test System
Wang, Pengfei
2009-01-01
The automotive industry has long relied on testing powertrain components in real vehicles, which causes the development process to be slow and expensive. Therefore, hardware in the loop (HIL) testing techniques are increasingly being adopted to develop electronic control units (ECU) for engine and other components of a vehicle. In this thesis, HIL testing system is developed to provide a laboratory testing environment for continuously variable transmissions (CVTs). Two induction motors were u...
Stabilizing unstable fixed points of chaotic maps via minimum entropy control
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)
2008-08-15
In this paper the problem of chaos control in nonlinear maps using minimization of entropy function is investigated. Invariant probability measure of a chaotic dynamics can be used to produce an entropy function in the sense of Shannon. In this paper it is shown that how the entropy control technique is utilized for chaos elimination. Using only the measured states of a chaotic map the probability measure of the system is numerically estimated and this estimated measure is used to obtain an estimation for the entropy of the chaotic map. The control variable of the chaotic system is determined in such a way that the entropy function descends until the chaotic trajectory of the map is replaced with a regular one. The proposed idea is applied for stabilizing the fixed points of the logistic and the Henon maps as some cases of study. Simulation results show the effectiveness of the method in chaos rejection when only the statistical information is available from the under-study systems.
Continuous-Time Mean-Variance Portfolio Selection with Random Horizon
International Nuclear Information System (INIS)
Yu, Zhiyong
2013-01-01
This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right
Continuous-Time Mean-Variance Portfolio Selection with Random Horizon
Energy Technology Data Exchange (ETDEWEB)
Yu, Zhiyong, E-mail: yuzhiyong@sdu.edu.cn [Shandong University, School of Mathematics (China)
2013-12-15
This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right.
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.
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.
Minimum energy control for a two-compartment neuron to extracellular electric fields
Yi, Guo-Sheng; Wang, Jiang; Li, Hui-Yan; Wei, Xi-Le; Deng, Bin
2016-11-01
The energy optimization of extracellular electric field (EF) stimulus for a neuron is considered in this paper. We employ the optimal control theory to design a low energy EF input for a reduced two-compartment model. It works by driving the neuron to closely track a prescriptive spike train. A cost function is introduced to balance the contradictory objectives, i.e., tracking errors and EF stimulus energy. By using the calculus of variations, we transform the minimization of cost function to a six-dimensional two-point boundary value problem (BVP). Through solving the obtained BVP in the cases of three fundamental bifurcations, it is shown that the control method is able to provide an optimal EF stimulus of reduced energy for the neuron to effectively track a prescriptive spike train. Further, the feasibility of the adopted method is interpreted from the point of view of the biophysical basis of spike initiation. These investigations are conducive to designing stimulating dose for extracellular neural stimulation, which are also helpful to interpret the effects of extracellular field on neural activity.
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)
Patterning control strategies for minimum edge placement error in logic devices
Mulkens, Jan; Hanna, Michael; Slachter, Bram; Tel, Wim; Kubis, Michael; Maslow, Mark; Spence, Chris; Timoshkov, Vadim
2017-03-01
In this paper we discuss the edge placement error (EPE) for multi-patterning semiconductor manufacturing. In a multi-patterning scheme the creation of the final pattern is the result of a sequence of lithography and etching steps, and consequently the contour of the final pattern contains error sources of the different process steps. We describe the fidelity of the final pattern in terms of EPE, which is defined as the relative displacement of the edges of two features from their intended target position. We discuss our holistic patterning optimization approach to understand and minimize the EPE of the final pattern. As an experimental test vehicle we use the 7-nm logic device patterning process flow as developed by IMEC. This patterning process is based on Self-Aligned-Quadruple-Patterning (SAQP) using ArF lithography, combined with line cut exposures using EUV lithography. The computational metrology method to determine EPE is explained. It will be shown that ArF to EUV overlay, CDU from the individual process steps, and local CD and placement of the individual pattern features, are the important contributors. Based on the error budget, we developed an optimization strategy for each individual step and for the final pattern. Solutions include overlay and CD metrology based on angle resolved scatterometry, scanner actuator control to enable high order overlay corrections and computational lithography optimization to minimize imaging induced pattern placement errors of devices and metrology targets.
Spectral Ambiguity of Allan Variance
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.
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
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.
Directory of Open Access Journals (Sweden)
Kristine Vander Mijnsbrugge
2016-11-01
Full Text Available Prunus spinosa is a highly esteemed shrub in forest and landscape plantings. Shrubs with larger organs occur often and are considered either as large fruited forms of P. spinosa or as P. x fruticans, involving a hybridization process with the ancient cultivated P. insititia (crop-to-wild gene flow. As climate change may augment hybridization processes in the future, a hybrid origin is important to detect. In addition, studying crop-to-wild gene flow can give insights in putative consequences for the wild populations. We studied the P. spinosa – P. x fruticans group, focusing on morphology and phenology in three experimental plantations. Two plantings harbored cuttings of P. spinosa (clone plantations. A third plantation comprised of a half-sib offspring from a population with both P. spinosa and P. x fruticans (family plantation. Several results point to a hybridization process as the origin of P. x fruticans. The clone plantation revealed endocarp traits to be more genetically controlled than fruit size, while this was the opposite in the family plantation, suggesting the control of fruit size being derived from the putative P. insititia parent. Bud burst, flower opening and leaf fall were genetically controlled in the clone plantation, whereas in the family plantation intrafamily variability was remarkably large for the bud burst and leaf fall, but not for the flower opening. This suggests there is a reduced genetic control for the first two phenophases, possibly caused by historic hybridization events. Pubescence on the long shoot leaves in the family plantation deviated from the short shoot leaves on the same plants and from long and short shoot leaves in the clone plantation, suggesting again a P. insititia origin. Finally, we quantified spatial phenotypic plasticity, indicating how P. spinosa may react in a changing environment. In contrast to the bud burst and leaf fall, flower opening did not demonstrate plasticity. The fruit size was
International Nuclear Information System (INIS)
Bihoreau, C.
1981-03-01
This thesis presents the proposal for a water control level method likely to improve performance, especially at low power. Particular problems are analyzed in detail. Finally, computerized simulations are presented; they confirm the algorithm performance [fr
Validation of consistency of Mendelian sampling variance.
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
Introduction to variance estimation
Wolter, Kirk M
2007-01-01
We live in the information age. Statistical surveys are used every day to determine or evaluate public policy and to make important business decisions. Correct methods for computing the precision of the survey data and for making inferences to the target population are absolutely essential to sound decision making. Now in its second edition, Introduction to Variance Estimation has for more than twenty years provided the definitive account of the theory and methods for correct precision calculations and inference, including examples of modern, complex surveys in which the methods have been used successfully. The book provides instruction on the methods that are vital to data-driven decision making in business, government, and academe. It will appeal to survey statisticians and other scientists engaged in the planning and conduct of survey research, and to those analyzing survey data and charged with extracting compelling information from such data. It will appeal to graduate students and university faculty who...
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
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...
Hedging with stock index futures: downside risk versus the variance
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
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
Means and Variances without Calculus
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.
Kirk, J C
1998-01-01
The popularization and transformation of scuba diving into a broadly practiced sport has served to ignite the interest of technically oriented divers into ever more demanding areas. This, along with the gradual release of military data, equipment, and techniques of closed circuit underwater breathing apparatus, has resulted in a virtual explosion of semiclosed and closed circuit systems for divers. Although many of these systems have been carefully thought out by capable designers, the impulse to rush to market with equipment that has not been fully developed and carefully tested is irresistible to marketers. In addition, the presence of systems developed by well-intentioned and otherwise competent designers who are, nonetheless, inexperienced in the field of life support can result in the sale of failure-prone equipment to divers who lack the knowledge and skills to identify deficiencies before disaster occurs. For this reason, a set of industry standards establishing minimum requirements and testing is needed to guide the designers of this equipment, and to protect the user community from incomplete or inadequate design. Many different technologies go into the development of closed circuit scuba. One key area is the design of electronics to monitor and maintain the critical gas mixtures of the closed circuit loop. Much of the system reliability and inherent danger is resident in the design of the circuitry and the software (if any) that runs it. This article will present a set of proposed minimum requirements, with the goal of establishing a dialog for the creation of guidelines for the classification, rating, design, and testing of embedded electronics for life support systems used in closed circuit applications. These guidelines will serve as the foundation for the later creation of a set of industry specifications.
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
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.
Ghousiya Begum, K; Seshagiri Rao, A; Radhakrishnan, T K
2017-05-01
Internal model control (IMC) with optimal H 2 minimization framework is proposed in this paper for design of proportional-integral-derivative (PID) controllers. The controller design is addressed for integrating and double integrating time delay processes with right half plane (RHP) zeros. Blaschke product is used to derive the optimal controller. There is a single adjustable closed loop tuning parameter for controller design. Systematic guidelines are provided for selection of this tuning parameter based on maximum sensitivity. Simulation studies have been carried out on various integrating time delay processes to show the advantages of the proposed method. The proposed controller provides enhanced closed loop performances when compared to recently reported methods in the literature. Quantitative comparative analysis has been carried out using the performance indices, Integral Absolute Error (IAE) and Total Variation (TV). Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
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
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...
Gini estimation under infinite variance
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
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.
Variance decomposition in stochastic simulators.
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.
Variance decomposition in stochastic simulators
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.
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.
Variance decomposition in stochastic simulators
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.
2010-04-01
... sensitive keys, the tracing of source documents to summarized documentation and accounting records, and... source documents to summarized documentation and accounting records, reconciliation to restricted copies... limited to, game write and payout procedures, sensitive key location and control, and a review of keno...
2010-04-01
... drop cabinet access, tracing of source documents to summarized documentation and accounting records...) Keno, including but not limited to, game write and payout procedures, sensitive key location and control, and a review of keno auditing procedures; (v) Pari-mutual wagering, including write and payout...
2010-04-01
... sensitive keys, the tracing of source documents to summarized documentation and accounting records, and... source documents to summarized documentation and accounting records, reconciliation to restricted copies... limited to, game write and payout procedures, sensitive key location and control, and a review of keno...
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.
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 ...
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.
Energy Technology Data Exchange (ETDEWEB)
Magashima, K. [Railway Technical Research Institute, Tokyo (Japan); Iwasa, Y. [Francis Bitter Magnet Laboratory, Canbridge (United States); Sawa, K. [keio University, Tokyo (Japan); Murakami, M. [Superconductivity research Laboratory, Tokyo (Japan)
1999-11-25
The levitation of bulk Y-Ba-Cu-O superconductors can be controlled using a Bi-Sr-Ca-Cu-O (Bi2223) superconducting electromagnet. It was found that stable levitation without tilting could be obtained only when the sample trapped a certain amount of fields, the minimum of which depended on the external field and sample dimensions. We employed a novel analysis method for levitation based on the total energy balance, which is much simpler than the force method and could be applied to understanding general levitation behavior. Numerical analyses thus developed showed that stable levitation of superconductors with large dimensions cen only be achieved when the induced currents can flow with three-dimensional freedom. (author)
Genotypic-specific variance in Caenorhabditis elegans lifetime fecundity.
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.
Silva, Leonardo W. T.; Barros, Vitor F.; Silva, Sandro G.
2014-01-01
In launching operations, Rocket Tracking Systems (RTS) process the trajectory data obtained by radar sensors. In order to improve functionality and maintenance, radars can be upgraded by replacing antennas with parabolic reflectors (PRs) with phased arrays (PAs). These arrays enable the electronic control of the radiation pattern by adjusting the signal supplied to each radiating element. However, in projects of phased array radars (PARs), the modeling of the problem is subject to various combinations of excitation signals producing a complex optimization problem. In this case, it is possible to calculate the problem solutions with optimization methods such as genetic algorithms (GAs). For this, the Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) method was developed to control the radiation pattern of PAs. The GA-MMC uses a reconfigurable algorithm with multiple objectives, differentiated coding and a new crossover genetic operator. This operator has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, GA-MMC was successful in more than 90% of the tests for each application, increased the fitness of the final population by more than 20% and reduced the premature convergence. PMID:25196013
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...
Speed Variance and Its Influence on Accidents.
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…
Variance function estimation for immunoassays
International Nuclear Information System (INIS)
Raab, G.M.; Thompson, R.; McKenzie, I.
1980-01-01
A computer program is described which implements a recently described, modified likelihood method of determining an appropriate weighting function to use when fitting immunoassay dose-response curves. The relationship between the variance of the response and its mean value is assumed to have an exponential form, and the best fit to this model is determined from the within-set variability of many small sets of repeated measurements. The program estimates the parameter of the exponential function with its estimated standard error, and tests the fit of the experimental data to the proposed model. Output options include a list of the actual and fitted standard deviation of the set of responses, a plot of actual and fitted standard deviation against the mean response, and an ordered list of the 10 sets of data with the largest ratios of actual to fitted standard deviation. The program has been designed for a laboratory user without computing or statistical expertise. The test-of-fit has proved valuable for identifying outlying responses, which may be excluded from further analysis by being set to negative values in the input file. (Auth.)
Integrating mean and variance heterogeneities to identify differentially expressed genes.
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
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)
Phenotypic variance explained by local ancestry in admixed African Americans.
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.
Host nutrition alters the variance in parasite transmission potential.
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.
Evolution of Genetic Variance during Adaptive Radiation.
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.
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)
Continuous-Time Mean-Variance Portfolio Selection under the CEV Process
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...
DFT-based channel estimation and noise variance estimation techniques for single-carrier FDMA
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) ...
Minimum entropy production principle
Czech Academy of Sciences Publication Activity Database
Maes, C.; Netočný, Karel
2013-01-01
Roč. 8, č. 7 (2013), s. 9664-9677 ISSN 1941-6016 Institutional support: RVO:68378271 Keywords : MINEP Subject RIV: BE - Theoretical Physics http://www.scholarpedia.org/article/Minimum_entropy_production_principle
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...
Efficient Cardinality/Mean-Variance Portfolios
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...
The phenotypic variance gradient - a novel concept.
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.
Analysis of conditional genetic effects and variance components in developmental genetics.
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.
A method for minimum risk portfolio optimization under hybrid uncertainty
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.
Least-squares variance component estimation
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
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...
Nonlinear Epigenetic Variance: Review and Simulations
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…
Variance estimation for generalized Cavalieri estimators
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.
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.
Directory of Open Access Journals (Sweden)
Lonsdale Adam J
2012-11-01
Full Text Available Abstract Background UK drinkers regularly consume alcohol in excess of guideline limits. One reason for this may be the high availability of low-cost alcoholic beverages. The introduction of a minimum price per unit of alcohol policy has been proposed as a means to reduce UK alcohol consumption. However, there is little in-depth research investigating public attitudes and beliefs regarding a minimum pricing policy. The aim of the present research was to investigate people’s attitudes and beliefs toward the introduction of a minimum price per unit of alcohol policy and their views on how the policy could be made acceptable to the general public. Methods Twenty-eight focus groups were conducted to gain in-depth data on attitudes, knowledge, and beliefs regarding the introduction of a minimum price per unit of alcohol policy. Participants (total N = 218 were asked to give their opinions about the policy, its possible outcomes, and how its introduction might be made more acceptable. Transcribed focus-group discussions were analysed for emergent themes using inductive thematic content analysis. Results Analysis indicated that participants’ objections to a minimum price had three main themes: (1 scepticism of minimum pricing as an effective means to reduce harmful alcohol consumption; (2 a dislike of the policy for a number of reasons (e.g., it was perceived to ‘punish’ the moderate drinker; and (3 concern that the policy might create or exacerbate existing social problems. There was a general perception that the policy was aimed at ‘problem’ and underage drinkers. Participants expressed some qualified support for the policy but stated that it would only work as part of a wider campaign including other educational elements. Conclusions There was little evidence to suggest that people would support the introduction of a minimum price per unit of alcohol policy. Scepticism about the effectiveness of the policy is likely to represent the most
2012-01-01
Background UK drinkers regularly consume alcohol in excess of guideline limits. One reason for this may be the high availability of low-cost alcoholic beverages. The introduction of a minimum price per unit of alcohol policy has been proposed as a means to reduce UK alcohol consumption. However, there is little in-depth research investigating public attitudes and beliefs regarding a minimum pricing policy. The aim of the present research was to investigate people’s attitudes and beliefs toward the introduction of a minimum price per unit of alcohol policy and their views on how the policy could be made acceptable to the general public. Methods Twenty-eight focus groups were conducted to gain in-depth data on attitudes, knowledge, and beliefs regarding the introduction of a minimum price per unit of alcohol policy. Participants (total N = 218) were asked to give their opinions about the policy, its possible outcomes, and how its introduction might be made more acceptable. Transcribed focus-group discussions were analysed for emergent themes using inductive thematic content analysis. Results Analysis indicated that participants’ objections to a minimum price had three main themes: (1) scepticism of minimum pricing as an effective means to reduce harmful alcohol consumption; (2) a dislike of the policy for a number of reasons (e.g., it was perceived to ‘punish’ the moderate drinker); and (3) concern that the policy might create or exacerbate existing social problems. There was a general perception that the policy was aimed at ‘problem’ and underage drinkers. Participants expressed some qualified support for the policy but stated that it would only work as part of a wider campaign including other educational elements. Conclusions There was little evidence to suggest that people would support the introduction of a minimum price per unit of alcohol policy. Scepticism about the effectiveness of the policy is likely to represent the most significant barrier to
Lonsdale, Adam J; Hardcastle, Sarah J; Hagger, Martin S
2012-11-23
UK drinkers regularly consume alcohol in excess of guideline limits. One reason for this may be the high availability of low-cost alcoholic beverages. The introduction of a minimum price per unit of alcohol policy has been proposed as a means to reduce UK alcohol consumption. However, there is little in-depth research investigating public attitudes and beliefs regarding a minimum pricing policy. The aim of the present research was to investigate people's attitudes and beliefs toward the introduction of a minimum price per unit of alcohol policy and their views on how the policy could be made acceptable to the general public. Twenty-eight focus groups were conducted to gain in-depth data on attitudes, knowledge, and beliefs regarding the introduction of a minimum price per unit of alcohol policy. Participants (total N = 218) were asked to give their opinions about the policy, its possible outcomes, and how its introduction might be made more acceptable. Transcribed focus-group discussions were analysed for emergent themes using inductive thematic content analysis. Analysis indicated that participants' objections to a minimum price had three main themes: (1) scepticism of minimum pricing as an effective means to reduce harmful alcohol consumption; (2) a dislike of the policy for a number of reasons (e.g., it was perceived to 'punish' the moderate drinker); and (3) concern that the policy might create or exacerbate existing social problems. There was a general perception that the policy was aimed at 'problem' and underage drinkers. Participants expressed some qualified support for the policy but stated that it would only work as part of a wider campaign including other educational elements. There was little evidence to suggest that people would support the introduction of a minimum price per unit of alcohol policy. Scepticism about the effectiveness of the policy is likely to represent the most significant barrier to public support. Findings also suggest that clearer
Portfolio optimization using median-variance approach
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.
Directory of Open Access Journals (Sweden)
Avidan Michael S
2009-11-01
Full Text Available Abstract Background The incidence of intraoperative awareness with explicit recall is 1-2/1000 cases in the United States. The Bispectral Index monitor is an electroencephalographic method of assessing anesthetic depth that has been shown in one prospective study to reduce the incidence of awareness in the high-risk population. In the B-Aware trial, the number needed to treat in order to prevent one case of awareness in the high-risk population was 138. Since the number needed to treat and the associated cost of treatment would be much higher in the general population, the efficacy of the Bispectral Index monitor in preventing awareness in all anesthetized patients needs to be clearly established. This is especially true given the findings of the B-Unaware trial, which demonstrated no significant difference between protocols based on the Bispectral Index monitor or minimum alveolar concentration for the reduction of awareness in high risk patients. Methods/Design To evaluate efficacy in the general population, we are conducting a prospective, randomized, controlled trial comparing the Bispectral Index monitor to a non-electroencephalographic gauge of anesthetic depth. The total recruitment for the study is targeted for 30,000 patients at both low and high risk for awareness. We have developed a novel algorithm that is capable of real-time analysis of our electronic perioperative information system. In one arm of the study, anesthesia providers will receive an electronic page if the Bispectral Index value is >60. In the other arm of the study, anesthesia providers will receive a page if the age-adjusted minimum alveolar concentration is Discussion Awareness during general anesthesia is a persistent problem and the role of the Bispectral Index monitor in its prevention is still unclear. The Michigan Awareness Control Study is the largest prospective trial of awareness prevention ever conducted. Trial Registration Clinical Trial NCT00689091
Grammatical and lexical variance in English
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.
A Mean variance analysis of arbitrage portfolios
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.
Dynamic Mean-Variance Asset Allocation
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 ...
Genetic variants influencing phenotypic variance heterogeneity.
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.
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.
Rising above the Minimum Wage.
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…
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.
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...
Minimum Error Entropy Classification
Marques de Sá, Joaquim P; Santos, Jorge M F; Alexandre, Luís A
2013-01-01
This book explains the minimum error entropy (MEE) concept applied to data classification machines. Theoretical results on the inner workings of the MEE concept, in its application to solving a variety of classification problems, are presented in the wider realm of risk functionals. Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi‐layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE‐like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.
Thermospheric mass density model error variance as a function of time scale
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).
Variance in exposed perturbations impairs retention of visuomotor adaptation.
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
Do Minimum Wages Fight Poverty?
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...
Integrating Variances into an Analytical Database
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.
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.
Decomposition of Variance for Spatial Cox Processes.
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.
Variance in binary stellar population synthesis
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.
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....
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...
78 FR 14122 - Revocation of Permanent Variances
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...
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...
Biological Variance in Agricultural Products. Theoretical Considerations
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
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...
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...
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...
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.
Zero-intelligence realized variance estimation
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
Variance Reduction Techniques in Monte Carlo Methods
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
Employment effects of minimum wages
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.
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.
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...
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...
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
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…
R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization.
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.
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...
The Theory of Variances in Equilibrium Reconstruction
International Nuclear Information System (INIS)
Zakharov, Leonid E.; Lewandowski, Jerome; Foley, Elizabeth L.; Levinton, Fred M.; Yuh, Howard Y.; Drozdov, Vladimir; McDonald, Darren
2008-01-01
The theory of variances of equilibrium reconstruction is presented. It complements existing practices with information regarding what kind of plasma profiles can be reconstructed, how accurately, and what remains beyond the abilities of diagnostic systems. The σ-curves, introduced by the present theory, give a quantitative assessment of quality of effectiveness of diagnostic systems in constraining equilibrium reconstructions. The theory also suggests a method for aligning the accuracy of measurements of different physical nature
Fundamentals of exploratory analysis of variance
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.
The Genealogical Consequences of Fecundity Variance Polymorphism
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
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.)
Pavez, Juan C; Hawkins, Michelle G; Pascoe, Peter J; Knych, Heather K DiMaio; Kass, Philip H
2011-07-01
To determine the impact of three different target plasma concentrations of fentanyl on the minimum anaesthetic concentration (MAC) for isoflurane in the red-tailed hawk and the effects on the haemodynamic profile. Experimental study. Six healthy adult red-tailed hawks (Buteo jamaicensis) of unknown sex with body weights (mean ± SD) of 1.21 ± 0.15 kg. This study was undertaken in two phases. In the first phase anaesthesia was induced with isoflurane in oxygen via facemask and maintained with isoflurane delivered in oxygen via a Bain circuit. Following instrumentation baseline determination of the MAC for isoflurane was made for each animal using the bracketing method and a supramaximal electrical stimulus. End-tidal isoflurane concentration (E'Iso) was then set at 0.75 × MAC and after an appropriate equilibration period a bolus of fentanyl (20 μg kg(-1)) was administered intravenously (IV) in order to determine the pharmacokinetics of fentanyl in the isoflurane-anaesthetized red-tailed hawk. During the second phase anaesthesia was induced in a similar manner and E'Iso was set at 0.75 × MAC for each individual. Fentanyl was infused IV to achieve target plasma concentrations between 8 and 32 ng mL(-1). At each fentanyl plasma concentration, the MAC for isoflurane and cardiovascular variables were determined. Data were analyzed by use of repeated-measures anova. Mean ± SD fentanyl plasma concentrations and isoflurane MACs were 0 ± 0, 8.51 ± 4, 14.85 ± 4.82 and 29.25 ± 11.52 ng mL(-1), and 2.05 ± 0.45%, 1.42 ± 0.53%, 1.14 ± 0.31% and 0.93 ± 0.32% for the target concentrations of 0, 8, 16 and 32 ng mL(-1), respectively. At these concentrations fentanyl significantly (p = 0.0016) decreased isoflurane MAC by 31%, 44% and 55%, respectively. Dose had no significant effect on heart rate, systolic, diastolic or mean arterial blood pressure. Fentanyl produced a dose-related decrease of isoflurane MAC with minimal effects on measured cardiovascular parameters in
Real-time performance assessment and adaptive control for a water chiller unit in an HVAC system
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.
Visual SLAM Using Variance Grid Maps
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
Markov bridges, bisection and variance reduction
DEFF Research Database (Denmark)
Asmussen, Søren; Hobolth, Asger
. In this paper we firstly consider the problem of generating sample paths from a continuous-time Markov chain conditioned on the endpoints using a new algorithm based on the idea of bisection. Secondly we study the potential of the bisection algorithm for variance reduction. In particular, examples are presented......Time-continuous Markov jump processes is a popular modelling tool in disciplines ranging from computational finance and operations research to human genetics and genomics. The data is often sampled at discrete points in time, and it can be useful to simulate sample paths between the datapoints...
The value of travel time variance
Fosgerau, Mogens; Engelson, Leonid
2010-01-01
This paper considers the value of travel time variability under scheduling preferences that are de�fined in terms of linearly time-varying utility rates associated with being at the origin and at the destination. The main result is a simple expression for the value of travel time variability that does not depend on the shape of the travel time distribution. The related measure of travel time variability is the variance of travel time. These conclusions apply equally to travellers who can free...
International Nuclear Information System (INIS)
Yuguchi, Takashi; Yamaguchi, Takashi; Iwamoto, Manji-rou; Eguchi, Hibiki; Isobe, Hiroshi; Nishiyama, Tadao
2012-01-01
This paper presents the temperature and pressure dependence of the minimum binary diffusivity in granitic melts. The minimum diffusivities are determined by monitoring the temporal development of the diffusion-controlled melt layer(DCM) in granitic systems (albite (Ab)-quartz (Qtz)-H 2 O and orthoclase (Or)-Qtz-H 2 O) gathered during 31 melting experiments under conditions of 800-900degC and 100-200 MPa for durations of 19-72 h. The DCM is formed between single crystals (Ab or Or crystals) and powdered quartz in all runs and is characterized by a distinct concentration gradient. The maximum thickness of the DCM increases systematically with temperature, pressure, and run duration. Temporal development of the DCM obeys the parabolic growth rate law, using which the diffusivity can be estimated. Plots of concentrations along the diffusion paths in ternary diagrams (Na 2 O-Al 2 O 3 -SiO 2 diagram for the Ab-Qtz-H 2 O system and K 2 O-Al 2 O 3 -SiO 2 diagram for the Or-Qtz-H 2 O system) show linear trends rather than S-shaped trends, indicating that binary nature of diffusion occurs in these systems. Therefore, the diffusive component can be interpreted as an albite component or orthoclase and quartz components (SiO 2 ) rather than an oxide or a cation. (author)
Variance-based Salt Body Reconstruction
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.
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.
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.
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
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)
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)
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.
International Nuclear Information System (INIS)
Tingey, F.H.
1979-01-01
A viable safeguards system includes among other things the development and use of indices which trigger various courses of action. The usual limit of error calculation provides such an index. The classical approach is one of constructing tests which, under certain assumptions, make the likelihood of a false alarm small. Of concern also is the test's failure to indicate a loss (diversion) when in fact one has occurred. Since false alarms are usually costly and losses both costly and of extreme strategic sinificance, there remains the task of balancing the probability of false alarm and its consequences against the probability of undetected loss and its consequences. The application of other than classical hypothesis testing procedures are considered in this paper. Using various consequence models, trigger indices are derived which have certain optimum properties. Application of the techniques would enhance the material control function
Variance heterogeneity in Saccharomyces cerevisiae expression data: trans-regulation and epistasis.
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.
Power Estimation in Multivariate Analysis of Variance
Directory of Open Access Journals (Sweden)
Jean François Allaire
2007-09-01
Full Text Available Power is often overlooked in designing multivariate studies for the simple reason that it is believed to be too complicated. In this paper, it is shown that power estimation in multivariate analysis of variance (MANOVA can be approximated using a F distribution for the three popular statistics (Hotelling-Lawley trace, Pillai-Bartlett trace, Wilk`s likelihood ratio. Consequently, the same procedure, as in any statistical test, can be used: computation of the critical F value, computation of the noncentral parameter (as a function of the effect size and finally estimation of power using a noncentral F distribution. Various numerical examples are provided which help to understand and to apply the method. Problems related to post hoc power estimation are discussed.
Analysis of Variance in Statistical Image Processing
Kurz, Ludwik; Hafed Benteftifa, M.
1997-04-01
A key problem in practical image processing is the detection of specific features in a noisy image. Analysis of variance (ANOVA) techniques can be very effective in such situations, and this book gives a detailed account of the use of ANOVA in statistical image processing. The book begins by describing the statistical representation of images in the various ANOVA models. The authors present a number of computationally efficient algorithms and techniques to deal with such problems as line, edge, and object detection, as well as image restoration and enhancement. By describing the basic principles of these techniques, and showing their use in specific situations, the book will facilitate the design of new algorithms for particular applications. It will be of great interest to graduate students and engineers in the field of image processing and pattern recognition.
Variance Risk Premia on Stocks and Bonds
DEFF Research Database (Denmark)
Mueller, Philippe; Sabtchevsky, Petar; Vedolin, Andrea
We study equity (EVRP) and Treasury variance risk premia (TVRP) jointly and document a number of findings: First, relative to their volatility, TVRP are comparable in magnitude to EVRP. Second, while there is mild positive co-movement between EVRP and TVRP unconditionally, time series estimates...... equity returns for horizons up to 6-months, long maturity TVRP contain robust information for long run equity returns. Finally, exploiting the dynamics of real and nominal Treasuries we document that short maturity break-even rates are a power determinant of the joint dynamics of EVRP, TVRP and their co-movement...... of correlation display distinct spikes in both directions and have been notably volatile since the financial crisis. Third $(i)$ short maturity TVRP predict excess returns on short maturity bonds; $(ii)$ long maturity TVRP and EVRP predict excess returns on long maturity bonds; and $(iii)$ while EVRP predict...
The value of travel time variance
DEFF Research Database (Denmark)
Fosgerau, Mogens; Engelson, Leonid
2011-01-01
This paper considers the value of travel time variability under scheduling preferences that are defined in terms of linearly time varying utility rates associated with being at the origin and at the destination. The main result is a simple expression for the value of travel time variability...... that does not depend on the shape of the travel time distribution. The related measure of travel time variability is the variance of travel time. These conclusions apply equally to travellers who can freely choose departure time and to travellers who use a scheduled service with fixed headway. Depending...... on parameters, travellers may be risk averse or risk seeking and the value of travel time may increase or decrease in the mean travel time....
Moura, Ed Carlos Rey; de Oliveira Honda, Claudio A; Bringel, Roberto Cesar Teixeira; Leal, Plinio da Cunha; Filho, Gasper de Jesus Lopes; Sakata, Rioko Kinmiko
2016-01-01
Adequate analgesia is important for early hospital discharge after meniscectomy. A femoral nerve block may reduce the need for systemic analgesics, with fewer side effects; however, motor block can occur. Ultrasound-guided femoral nerve block may reduce the required local anesthetic concentration, preventing motor block. The primary objective of this study was to determine the lowest effective analgesic concentration of bupivacaine in 50% (EC50) and in 90% (EC90) of patients for a successful ultrasound-guided femoral nerve block in arthroscopic knee meniscectomy. This was a prospective, randomized, double-blind, controlled trial. This study was conducted at Hospital São Domingos. A total of 52 patients undergoing arthroscopic knee meniscectomy were submitted to ultrasound-guided femoral nerve block using 22 mL bupivacaine. The bupivacaine concentration given to a study patient was determined by the response of the previous patient (a biased-coin design up-down sequential method). If the previous patient had a negative response, the bupivacaine concentration was increased by 0.05% for the next case. If the previous patient had a positive response, the next patient was randomized to receive the same bupivacaine concentration (with a probability of 0.89) or to have a decrease by 0.05% (with a probability of 0.11). A successful block was defined by a numerical pain intensity scale score different evaluations. If the pain intensity score was = 4 (moderate or severe pain) at any time, the block was considered failed. General anesthesia was induced with 30 µg/kg alfentanil and 2 mg/kg propofol, followed by propofol maintanance, plus remifentanil if needed. Postoperative analgesia supplementation was performed with dipyrone; ketoprofen and tramadol were given if needed. The following parameters were evaluated: numerical pain intensity score, duration of analgesia, supplementary analgesic dose in 24 hours, and need for intraoperative remifentanil. The EC50 was 0.160 (95
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...
Argentine Population Genetic Structure: Large Variance in Amerindian Contribution
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
Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.
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.
76 FR 78698 - Proposed Revocation of Permanent Variances
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...
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.
42 CFR 422.382 - Minimum net worth amount.
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...
12 CFR 3.6 - Minimum capital ratios.
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...
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....
78 FR 11793 - Minimum Internal Control Standards
2013-02-20
... count begins, to ensure the accuracy of the equipment. (7) If a currency counter interface is used: (i.... 543.2 by adding a definition for currency cassette in alphabetical order to read as follows: Sec. 543.2 What are the definitions for this part? * * * * * Currency cassette. A locked compartment that...
78 FR 63873 - Minimum Internal Control Standards
2013-10-25
...--though less stringent than--the drop and count process for player interfaces and card tables. By removing... count standards for player interfaces and card games, and intends to address the issue comprehensively... surveillance of kiosks and for the collection and count of their contents. The Commission published a proposed...
77 FR 58707 - Minimum Internal Control Standards
2012-09-21
..., if any), counted, inventoried, and secured by an authorized agent. (ii) Bingo card inventory records... comprehensive standards for the entire Class II gaming environment. The new sections include, for example: Card games; drop and count; surveillance; and gaming promotions and player tracking. The amendments also...
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
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.
Minimum airflow reset of single-duct VAV terminal boxes
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
Simultaneously learning and optimizing using controlled variance pricing
Boer, den A.V.; Zwart, B.
2014-01-01
Price experimentation is an important tool for firms to find the optimal selling price of their products. It should be conducted properly, since experimenting with selling prices can be costly. A firm, therefore, needs to find a pricing policy that optimally balances between learning the optimal
Gene set analysis using variance component tests.
Huang, Yen-Tsung; Lin, Xihong
2013-06-28
Gene set analyses have become increasingly important in genomic research, as many complex diseases are contributed jointly by alterations of numerous genes. Genes often coordinate together as a functional repertoire, e.g., a biological pathway/network and are highly correlated. However, most of the existing gene set analysis methods do not fully account for the correlation among the genes. Here we propose to tackle this important feature of a gene set to improve statistical power in gene set analyses. We propose to model the effects of an independent variable, e.g., exposure/biological status (yes/no), on multiple gene expression values in a gene set using a multivariate linear regression model, where the correlation among the genes is explicitly modeled using a working covariance matrix. We develop TEGS (Test for the Effect of a Gene Set), a variance component test for the gene set effects by assuming a common distribution for regression coefficients in multivariate linear regression models, and calculate the p-values using permutation and a scaled chi-square approximation. We show using simulations that type I error is protected under different choices of working covariance matrices and power is improved as the working covariance approaches the true covariance. The global test is a special case of TEGS when correlation among genes in a gene set is ignored. Using both simulation data and a published diabetes dataset, we show that our test outperforms the commonly used approaches, the global test and gene set enrichment analysis (GSEA). We develop a gene set analyses method (TEGS) under the multivariate regression framework, which directly models the interdependence of the expression values in a gene set using a working covariance. TEGS outperforms two widely used methods, GSEA and global test in both simulation and a diabetes microarray data.
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.
Minimum Q Electrically Small Antennas
DEFF Research Database (Denmark)
Kim, O. S.
2012-01-01
Theoretically, the minimum radiation quality factor Q of an isolated resonance can be achieved in a spherical electrically small antenna by combining TM1m and TE1m spherical modes, provided that the stored energy in the antenna spherical volume is totally suppressed. Using closed-form expressions...... for a multiarm spherical helix antenna confirm the theoretical predictions. For example, a 4-arm spherical helix antenna with a magnetic-coated perfectly electrically conducting core (ka=0.254) exhibits the Q of 0.66 times the Chu lower bound, or 1.25 times the minimum Q....
Variance in elective surgery for chronic pancreatitis.
Shah, Nehal S; Siriwardena, Ajith K
2009-01-08
Evidence to guide selection of optimal surgical treatment for patients with painful chronic pancreatitis is limited. Baseline assessment data are limited and thus patients in different centres may be presenting at different stages of their illness. This study undertakes a systematic overview of reports of elective surgical intervention in chronic pancreatitis with particular reference to reporting of quality of life and baseline assessment and relation between disease and type of procedure. A computerised search of the PubMed, Embase and Cochrane databases was undertaken for the period January 1997 to March 2007 yielding 46 manuscripts providing data on 4,626 patients undergoing elective surgery for chronic pancreatitis. The median number of patients per study was 71 (range: 4-484). The median period for recruitment of patients was 10 years (range: 2-36 years). An externally validated quality of life questionnaire is reported in 8 (17.4%) of 46 manuscripts covering 441 (9.5%) of 4,626 patients. Formal comparison of pre-operative and post-operative pain scores was provided in 15 (32.6%) of manuscripts. Only seven (15.2%) reports provide a formal rationale or indication for selection of the type of elective surgical procedure for a stated disease variant and these papers cover 481 (10.4%) patients. In conclusion, this study demonstrates that there is a lack of standardization between units of the criteria for operative intervention in painful chronic pancreatitis. At a minimum, formal quality of life testing using a validated system should be undertaken in all patients prior to elective surgery for painful chronic pancreatitis.
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
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
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...
Fermat and the Minimum Principle
Indian Academy of Sciences (India)
Arguably, least action and minimum principles were offered or applied much earlier. This (or these) principle(s) is/are among the fundamental, basic, unifying or organizing ones used to describe a variety of natural phenomena. It considers the amount of energy expended in performing a given action to be the least required ...
Coupling between minimum scattering antennas
DEFF Research Database (Denmark)
Andersen, J.; Lessow, H; Schjær-Jacobsen, Hans
1974-01-01
Coupling between minimum scattering antennas (MSA's) is investigated by the coupling theory developed by Wasylkiwskyj and Kahn. Only rotationally symmetric power patterns are considered, and graphs of relative mutual impedance are presented as a function of distance and pattern parameters. Crossed...
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.
Estimating the encounter rate variance in distance sampling
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.
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
On Optimal Input Design for Feed-forward Control
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...
Origin and consequences of the relationship between protein mean and variance.
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.
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....
Variance analysis of forecasted streamflow maxima in a wet temperate climate
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.
Increased gender variance in autism spectrum disorders and attention deficit hyperactivity disorder.
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.
Spatially tuned normalization explains attention modulation variance within neurons.
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
RR-Interval variance of electrocardiogram for atrial fibrillation detection
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.
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.
Network Structure and Biased Variance Estimation in Respondent Driven Sampling.
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.
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.
Discrete and continuous time dynamic mean-variance analysis
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...
Discrete time and continuous time dynamic mean-variance analysis
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...
Quantum mechanics the theoretical minimum
Susskind, Leonard
2014-01-01
From the bestselling author of The Theoretical Minimum, an accessible introduction to the math and science of quantum mechanicsQuantum Mechanics is a (second) book for anyone who wants to learn how to think like a physicist. In this follow-up to the bestselling The Theoretical Minimum, physicist Leonard Susskind and data engineer Art Friedman offer a first course in the theory and associated mathematics of the strange world of quantum mechanics. Quantum Mechanics presents Susskind and Friedman’s crystal-clear explanations of the principles of quantum states, uncertainty and time dependence, entanglement, and particle and wave states, among other topics. An accessible but rigorous introduction to a famously difficult topic, Quantum Mechanics provides a tool kit for amateur scientists to learn physics at their own pace.
Minimum resolvable power contrast model
Qian, Shuai; Wang, Xia; Zhou, Jingjing
2018-01-01
Signal-to-noise ratio and MTF are important indexs to evaluate the performance of optical systems. However,whether they are used alone or joint assessment cannot intuitively describe the overall performance of the system. Therefore, an index is proposed to reflect the comprehensive system performance-Minimum Resolvable Radiation Performance Contrast (MRP) model. MRP is an evaluation model without human eyes. It starts from the radiance of the target and the background, transforms the target and background into the equivalent strips,and considers attenuation of the atmosphere, the optical imaging system, and the detector. Combining with the signal-to-noise ratio and the MTF, the Minimum Resolvable Radiation Performance Contrast is obtained. Finally the detection probability model of MRP is given.
Understanding the Minimum Wage: Issues and Answers.
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…
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...
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.
ANALISIS PORTOFOLIO RESAMPLED EFFICIENT FRONTIER BERDASARKAN OPTIMASI MEAN-VARIANCE
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 ...
Capturing option anomalies with a variance-dependent pricing kernel
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
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...
Diagnostic checking in linear processes with infinit variance
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.
Evaluation of Mean and Variance Integrals without Integration
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…
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.
Direct encoding of orientation variance in the visual system.
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.
Beyond the Mean: Sensitivities of the Variance of Population Growth.
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.
On the Endogeneity of the Mean-Variance Efficient Frontier.
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…
42 CFR 456.522 - Content of request for variance.
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...
29 CFR 1905.5 - Effect of variances.
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...
29 CFR 1904.38 - Variances from the recordkeeping rule.
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...
Gender Variance and Educational Psychology: Implications for Practice
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…
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...
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
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
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.
Comparing estimates of genetic variance across different relationship models.
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.
The minimum yield in channeling
International Nuclear Information System (INIS)
Uguzzoni, A.; Gaertner, K.; Lulli, G.; Andersen, J.U.
2000-01-01
A first estimate of the minimum yield was obtained from Lindhard's theory, with the assumption of a statistical equilibrium in the transverse phase-space of channeled particles guided by a continuum axial potential. However, computer simulations have shown that this estimate should be corrected by a fairly large factor, C (approximately equal to 2.5), called the Barrett factor. We have shown earlier that the concept of a statistical equilibrium can be applied to understand this result, with the introduction of a constraint in phase-space due to planar channeling of axially channeled particles. Here we present an extended test of these ideas on the basis of computer simulation of the trajectories of 2 MeV α particles in Si. In particular, the gradual trend towards a full statistical equilibrium is studied. We also discuss the introduction of this modification of standard channeling theory into descriptions of the multiple scattering of channeled particles (dechanneling) by a master equation and show that the calculated minimum yields are in very good agreement with the results of a full computer simulation
International Nuclear Information System (INIS)
Kwee, Regina
2010-01-01
Since the restart of the LHC in November 2009, ATLAS has collected inelastic pp collisions to perform first measurements on charged particle densities. These measurements will help to constrain various models describing phenomenologically soft parton interactions. Understanding the trigger efficiencies for different event types are therefore crucial to minimize any possible bias in the event selection. ATLAS uses two main minimum bias triggers, featuring complementary detector components and trigger levels. While a hardware based first trigger level situated in the forward regions with 2.2 < |η| < 3.8 has been proven to select pp-collisions very efficiently, the Inner Detector based minimum bias trigger uses a random seed on filled bunches and central tracking detectors for the event selection. Both triggers were essential for the analysis of kinematic spectra of charged particles. Their performance and trigger efficiency measurements as well as studies on possible bias sources will be presented. We also highlight the advantage of these triggers for particle correlation analyses. (author)
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.
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...
Variance computations for functional of absolute risk estimates.
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.
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...
Meta-analysis of SNPs involved in variance heterogeneity using Levene's test for equal variances
Deng, Wei Q; Asma, Senay; Paré, Guillaume
2014-01-01
Meta-analysis is a commonly used approach to increase the sample size for genome-wide association searches when individual studies are otherwise underpowered. Here, we present a meta-analysis procedure to estimate the heterogeneity of the quantitative trait variance attributable to genetic variants using Levene's test without needing to exchange individual-level data. The meta-analysis of Levene's test offers the opportunity to combine the considerable sample size of a genome-wide meta-analysis to identify the genetic basis of phenotypic variability and to prioritize single-nucleotide polymorphisms (SNPs) for gene–gene and gene–environment interactions. The use of Levene's test has several advantages, including robustness to departure from the normality assumption, freedom from the influence of the main effects of SNPs, and no assumption of an additive genetic model. We conducted a meta-analysis of the log-transformed body mass index of 5892 individuals and identified a variant with a highly suggestive Levene's test P-value of 4.28E-06 near the NEGR1 locus known to be associated with extreme obesity. PMID:23921533
Motor equivalence and structure of variance: multi-muscle postural synergies in Parkinson's disease.
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.
Advanced Variance Reduction Strategies for Optimizing Mesh Tallies in MAVRIC
International Nuclear Information System (INIS)
Peplow, Douglas E.; Blakeman, Edward D; Wagner, John C
2007-01-01
More often than in the past, Monte Carlo methods are being used to compute fluxes or doses over large areas using mesh tallies (a set of region tallies defined on a mesh that overlays the geometry). For problems that demand that the uncertainty in each mesh cell be less than some set maximum, computation time is controlled by the cell with the largest uncertainty. This issue becomes quite troublesome in deep-penetration problems, and advanced variance reduction techniques are required to obtain reasonable uncertainties over large areas. The CADIS (Consistent Adjoint Driven Importance Sampling) methodology has been shown to very efficiently optimize the calculation of a response (flux or dose) for a single point or a small region using weight windows and a biased source based on the adjoint of that response. This has been incorporated into codes such as ADVANTG (based on MCNP) and the new sequence MAVRIC, which will be available in the next release of SCALE. In an effort to compute lower uncertainties everywhere in the problem, Larsen's group has also developed several methods to help distribute particles more evenly, based on forward estimates of flux. This paper focuses on the use of a forward estimate to weight the placement of the source in the adjoint calculation used by CADIS, which we refer to as a forward-weighted CADIS (FW-CADIS)
Comparison of variance estimators for metaanalysis of instrumental variable estimates
Schmidt, A. F.; Hingorani, A. D.; Jefferis, B. J.; White, J.; Groenwold, R. H H; Dudbridge, F.; Ben-Shlomo, Y.; Chaturvedi, N.; Engmann, J.; Hughes, A.; Humphries, S.; Hypponen, E.; Kivimaki, M.; Kuh, D.; Kumari, M.; Menon, U.; Morris, R.; Power, C.; Price, J.; Wannamethee, G.; Whincup, P.
2016-01-01
Background: Mendelian randomization studies perform instrumental variable (IV) analysis using genetic IVs. Results of individual Mendelian randomization studies can be pooled through meta-analysis. We explored how different variance estimators influence the meta-analysed IV estimate. Methods: Two
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....
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)
Advanced methods of analysis variance on scenarios of nuclear prospective
International Nuclear Information System (INIS)
Blazquez, J.; Montalvo, C.; Balbas, M.; Garcia-Berrocal, A.
2011-01-01
Traditional techniques of propagation of variance are not very reliable, because there are uncertainties of 100% relative value, for this so use less conventional methods, such as Beta distribution, Fuzzy Logic and the Monte Carlo Method.
Some variance reduction methods for numerical stochastic homogenization.
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).
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.
Variance Function Partially Linear Single-Index Models1.
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.
Variance estimation in the analysis of microarray data
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
Minimum Delay Moving Object Detection
Lao, Dong
2017-11-09
We present a general framework and method for detection of an object in a video based on apparent motion. The object moves relative to background motion at some unknown time in the video, and the goal is to detect and segment the object as soon it moves in an online manner. Due to unreliability of motion between frames, more than two frames are needed to reliably detect the object. Our method is designed to detect the object(s) with minimum delay, i.e., frames after the object moves, constraining the false alarms. Experiments on a new extensive dataset for moving object detection show that our method achieves less delay for all false alarm constraints than existing state-of-the-art.
Approximating the minimum cycle mean
Directory of Open Access Journals (Sweden)
Krishnendu Chatterjee
2013-07-01
Full Text Available We consider directed graphs where each edge is labeled with an integer weight and study the fundamental algorithmic question of computing the value of a cycle with minimum mean weight. Our contributions are twofold: (1 First we show that the algorithmic question is reducible in O(n^2 time to the problem of a logarithmic number of min-plus matrix multiplications of n-by-n matrices, where n is the number of vertices of the graph. (2 Second, when the weights are nonnegative, we present the first (1 + ε-approximation algorithm for the problem and the running time of our algorithm is ilde(O(n^ω log^3(nW/ε / ε, where O(n^ω is the time required for the classic n-by-n matrix multiplication and W is the maximum value of the weights.
Minimum Delay Moving Object Detection
Lao, Dong
2017-01-08
We present a general framework and method for detection of an object in a video based on apparent motion. The object moves relative to background motion at some unknown time in the video, and the goal is to detect and segment the object as soon it moves in an online manner. Due to unreliability of motion between frames, more than two frames are needed to reliably detect the object. Our method is designed to detect the object(s) with minimum delay, i.e., frames after the object moves, constraining the false alarms. Experiments on a new extensive dataset for moving object detection show that our method achieves less delay for all false alarm constraints than existing state-of-the-art.
Minimum Delay Moving Object Detection
Lao, Dong; Sundaramoorthi, Ganesh
2017-01-01
We present a general framework and method for detection of an object in a video based on apparent motion. The object moves relative to background motion at some unknown time in the video, and the goal is to detect and segment the object as soon it moves in an online manner. Due to unreliability of motion between frames, more than two frames are needed to reliably detect the object. Our method is designed to detect the object(s) with minimum delay, i.e., frames after the object moves, constraining the false alarms. Experiments on a new extensive dataset for moving object detection show that our method achieves less delay for all false alarm constraints than existing state-of-the-art.
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...
ASYMMETRY OF MARKET RETURNS AND THE MEAN VARIANCE FRONTIER
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...
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
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
Cumulative prospect theory and mean variance analysis. A rigorous comparison
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...
Global Variance Risk Premium and Forex Return Predictability
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 ...
Global Gravity Wave Variances from Aura MLS: Characteristics and Interpretation
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
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
Mean-Variance Optimization in Markov Decision Processes
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.
The asymptotic variance of departures in critically loaded queues
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 +
Youth minimum wages and youth employment
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
Do Some Workers Have Minimum Wage Careers?
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…
Does the Minimum Wage Affect Welfare Caseloads?
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…
Minimum income protection in the 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
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
Variance estimation in the analysis of microarray data
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.
Why risk is not variance: an expository note.
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.
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)
A versatile omnibus test for detecting mean and variance heterogeneity.
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.
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.
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
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.
Minimum wage development in the Russian Federation
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...
CMB-S4 and the hemispherical variance anomaly
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.
Minimum Delay Moving Object Detection
Lao, Dong
2017-05-14
This thesis presents a general framework and method for detection of an object in a video based on apparent motion. The object moves, at some unknown time, differently than the “background” motion, which can be induced from camera motion. The goal of proposed method is to detect and segment the object as soon it moves in an online manner. Since motion estimation can be unreliable between frames, more than two frames are needed to reliably detect the object. Observing more frames before declaring a detection may lead to a more accurate detection and segmentation, since more motion may be observed leading to a stronger motion cue. However, this leads to greater delay. The proposed method is designed to detect the object(s) with minimum delay, i.e., frames after the object moves, constraining the false alarms, defined as declarations of detection before the object moves or incorrect or inaccurate segmentation at the detection time. Experiments on a new extensive dataset for moving object detection show that our method achieves less delay for all false alarm constraints than existing state-of-the-art.
Genetic Variance in Homophobia: Evidence from Self- and Peer Reports.
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.
How does variance in fertility change over the demographic transition?
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).
Improving precision in gel electrophoresis by stepwisely decreasing variance components.
Schröder, Simone; Brandmüller, Asita; Deng, Xi; Ahmed, Aftab; Wätzig, Hermann
2009-10-15
Many methods have been developed in order to increase selectivity and sensitivity in proteome research. However, gel electrophoresis (GE) which is one of the major techniques in this area, is still known for its often unsatisfactory precision. Percental relative standard deviations (RSD%) up to 60% have been reported. In this case the improvement of precision and sensitivity is absolutely essential, particularly for the quality control of biopharmaceuticals. Our work reflects the remarkable and completely irregular changes of the background signal from gel to gel. This irregularity was identified as one of the governing error sources. These background changes can be strongly reduced by using a signal detection in the near-infrared (NIR) range. This particular detection method provides the most sensitive approach for conventional CCB (Colloidal Coomassie Blue) stained gels, which is reflected in a total error of just 5% (RSD%). In order to further investigate variance components in GE, an experimental Plackett-Burman screening design was performed. The influence of seven potential factors on the precision was investigated using 10 proteins with different properties analyzed by NIR detection. The results emphasized the individuality of the proteins. Completely different factors were identified to be significant for each protein. However, out of seven investigated parameters, just four showed a significant effect on some proteins, namely the parameters of: destaining time, staining temperature, changes of detergent additives (SDS and LDS) in the sample buffer, and the age of the gels. As a result, precision can only be improved individually for each protein or protein classes. Further understanding of the unique properties of proteins should enable us to improve the precision in gel electrophoresis.
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
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
Impact of Damping Uncertainty on SEA Model Response Variance
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.
Genetic and environmental variance in content dimensions of the MMPI.
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.
A new variance stabilizing transformation for gene expression data analysis.
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.
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
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
Minimum Additive Waste Stabilization (MAWS)
International Nuclear Information System (INIS)
1994-02-01
In the Minimum Additive Waste Stabilization(MAWS) concept, actual waste streams are utilized as additive resources for vitrification, which may contain the basic components (glass formers and fluxes) for making a suitable glass or glassy slag. If too much glass former is present, then the melt viscosity or temperature will be too high for processing; while if there is too much flux, then the durability may suffer. Therefore, there are optimum combinations of these two important classes of constituents depending on the criteria required. The challenge is to combine these resources in such a way that minimizes the use of non-waste additives yet yields a processable and durable final waste form for disposal. The benefit to this approach is that the volume of the final waste form is minimized (waste loading maximized) since little or no additives are used and vitrification itself results in volume reduction through evaporation of water, combustion of organics, and compaction of the solids into a non-porous glass. This implies a significant reduction in disposal costs due to volume reduction alone, and minimizes future risks/costs due to the long term durability and leach resistance of glass. This is accomplished by using integrated systems that are both cost-effective and produce an environmentally sound waste form for disposal. individual component technologies may include: vitrification; thermal destruction; soil washing; gas scrubbing/filtration; and, ion-exchange wastewater treatment. The particular combination of technologies will depend on the waste streams to be treated. At the heart of MAWS is vitrification technology, which incorporates all primary and secondary waste streams into a final, long-term, stabilized glass wasteform. The integrated technology approach, and view of waste streams as resources, is innovative yet practical to cost effectively treat a broad range of DOE mixed and low-level wastes
The mean and variance of phylogenetic diversity under rarefaction.
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.
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.
Partitioning of the variance in the growth parameters of Erwinia carotovora on vegetable products.
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.
Variance estimation for sensitivity analysis of poverty and inequality measures
Directory of Open Access Journals (Sweden)
Christian Dudel
2017-04-01
Full Text Available Estimates of poverty and inequality are often based on application of a single equivalence scale, despite the fact that a large number of different equivalence scales can be found in the literature. This paper describes a framework for sensitivity analysis which can be used to account for the variability of equivalence scales and allows to derive variance estimates of results of sensitivity analysis. Simulations show that this method yields reliable estimates. An empirical application reveals that accounting for both variability of equivalence scales and sampling variance leads to confidence intervals which are wide.
Studying Variance in the Galactic Ultra-compact Binary Population
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.
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
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.
Levine's guide to SPSS for analysis of variance
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
Variance squeezing and entanglement of the XX central spin model
International Nuclear Information System (INIS)
El-Orany, Faisal A A; Abdalla, M Sebawe
2011-01-01
In this paper, we study the quantum properties for a system that consists of a central atom interacting with surrounding spins through the Heisenberg XX couplings of equal strength. Employing the Heisenberg equations of motion we manage to derive an exact solution for the dynamical operators. We consider that the central atom and its surroundings are initially prepared in the excited state and in the coherent spin state, respectively. For this system, we investigate the evolution of variance squeezing and entanglement. The nonclassical effects have been remarked in the behavior of all components of the system. The atomic variance can exhibit revival-collapse phenomenon based on the value of the detuning parameter.
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....
Variance squeezing and entanglement of the XX central spin model
Energy Technology Data Exchange (ETDEWEB)
El-Orany, Faisal A A [Department of Mathematics and Computer Science, Faculty of Science, Suez Canal University, Ismailia (Egypt); Abdalla, M Sebawe, E-mail: m.sebaweh@physics.org [Mathematics Department, College of Science, King Saud University PO Box 2455, Riyadh 11451 (Saudi Arabia)
2011-01-21
In this paper, we study the quantum properties for a system that consists of a central atom interacting with surrounding spins through the Heisenberg XX couplings of equal strength. Employing the Heisenberg equations of motion we manage to derive an exact solution for the dynamical operators. We consider that the central atom and its surroundings are initially prepared in the excited state and in the coherent spin state, respectively. For this system, we investigate the evolution of variance squeezing and entanglement. The nonclassical effects have been remarked in the behavior of all components of the system. The atomic variance can exhibit revival-collapse phenomenon based on the value of the detuning parameter.
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.
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)
A Pareto-Improving Minimum Wage
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...
The minimum wage in the Czech enterprises
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). ...
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)
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)
Multivariate Variance Targeting in the BEKK-GARCH Model
DEFF Research Database (Denmark)
Pedersen, Rasmus Søndergaard; Rahbek, Anders
This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By de…nition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modi…ed like- lihood function, or estimating function, corresponding...
Multivariate Variance Targeting in the BEKK-GARCH Model
DEFF Research Database (Denmark)
Pedersen, Rasmus Søndergaard; Rahbek, Anders
2014-01-01
This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By definition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modified likelihood function, or estimating function, corresponding...
Multivariate Variance Targeting in the BEKK-GARCH Model
DEFF Research Database (Denmark)
Pedersen, Rasmus Søndergaard; Rahbek, Anders
This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By de…nition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modi…ed likelihood function, or estimating function, corresponding...
Analysis of Variance: What Is Your Statistical Software Actually Doing?
Li, Jian; Lomax, Richard G.
2011-01-01
Users assume statistical software packages produce accurate results. In this article, the authors systematically examined Statistical Package for the Social Sciences (SPSS) and Statistical Analysis System (SAS) for 3 analysis of variance (ANOVA) designs, mixed-effects ANOVA, fixed-effects analysis of covariance (ANCOVA), and nested ANOVA. For each…
Genetic variance components for residual feed intake and feed ...
African Journals Online (AJOL)
Feeding costs of animals is a major determinant of profitability in livestock production enterprises. Genetic selection to improve feed efficiency aims to reduce feeding cost in beef cattle and thereby improve profitability. This study estimated genetic (co)variances between weaning weight and other production, reproduction ...
Cumulative Prospect Theory, Option Returns, and the Variance Premium
Baele, Lieven; Driessen, Joost; Ebert, Sebastian; Londono Yarce, J.M.; Spalt, Oliver
The variance premium and the pricing of out-of-the-money (OTM) equity index options are major challenges to standard asset pricing models. We develop a tractable equilibrium model with Cumulative Prospect Theory (CPT) preferences that can overcome both challenges. The key insight is that the
Hydrograph variances over different timescales in hydropower production networks
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.
Bounds for Tail Probabilities of the Sample Variance
Directory of Open Access Journals (Sweden)
Van Zuijlen M
2009-01-01
Full Text Available We provide bounds for tail probabilities of the sample variance. The bounds are expressed in terms of Hoeffding functions and are the sharpest known. They are designed having in mind applications in auditing as well as in processing data related to environment.
Robust estimation of the noise variance from background MR data
Sijbers, J.; Den Dekker, A.J.; Poot, D.; Bos, R.; Verhoye, M.; Van Camp, N.; Van der Linden, A.
2006-01-01
In the literature, many methods are available for estimation of the variance of the noise in magnetic resonance (MR) images. A commonly used method, based on the maximum of the background mode of the histogram, is revisited and a new, robust, and easy to use method is presented based on maximum
Stable limits for sums of dependent infinite variance random variables
DEFF Research Database (Denmark)
Bartkiewicz, Katarzyna; Jakubowski, Adam; Mikosch, Thomas
2011-01-01
The aim of this paper is to provide conditions which ensure that the affinely transformed partial sums of a strictly stationary process converge in distribution to an infinite variance stable distribution. Conditions for this convergence to hold are known in the literature. However, most of these...
Estimation of the additive and dominance variances in South African ...
African Journals Online (AJOL)
The objective of this study was to estimate dominance variance for number born alive (NBA), 21- day litter weight (LWT21) and interval between parities (FI) in South African Landrace pigs. A total of 26223 NBA, 21335 LWT21 and 16370 FI records were analysed. Bayesian analysis via Gibbs sampling was used to estimate ...
A Visual Model for the Variance and Standard Deviation
Orris, J. B.
2011-01-01
This paper shows how the variance and standard deviation can be represented graphically by looking at each squared deviation as a graphical object--in particular, as a square. A series of displays show how the standard deviation is the size of the average square.
Asymptotics of variance of the lattice point count
Czech Academy of Sciences Publication Activity Database
Janáček, Jiří
2008-01-01
Roč. 58, č. 3 (2008), s. 751-758 ISSN 0011-4642 R&D Projects: GA AV ČR(CZ) IAA100110502 Institutional research plan: CEZ:AV0Z50110509 Keywords : point lattice * variance Subject RIV: BA - General Mathematics Impact factor: 0.210, year: 2008
Vertical velocity variances and Reynold stresses at Brookhaven
DEFF Research Database (Denmark)
Busch, Niels E.; Brown, R.M.; Frizzola, J.A.
1970-01-01
Results of wind tunnel tests of the Brookhaven annular bivane are presented. The energy transfer functions describing the instrument response and the numerical filter employed in the data reduction process have been used to obtain corrected values of the normalized variance of the vertical wind v...
Estimates of variance components for postweaning feed intake and ...
African Journals Online (AJOL)
Mike
2013-03-09
Mar 9, 2013 ... transformation of RFIp and RDGp to z-scores (mean = 0.0, variance = 1.0) and then ... generation pedigree (n = 9 653) used for this analysis. ..... Nkrumah, J.D., Basarab, J.A., Wang, Z., Li, C., Price, M.A., Okine, E.K., Crews Jr., ...
An observation on the variance of a predicted response in ...
African Journals Online (AJOL)
... these properties and computational simplicity. To avoid over fitting, along with the obvious advantage of having a simpler equation, it is shown that the addition of a variable to a regression equation does not reduce the variance of a predicted response. Key words: Linear regression; Partitioned matrix; Predicted response ...
An entropy approach to size and variance heterogeneity
Balasubramanyan, L.; Stefanou, S.E.; Stokes, J.R.
2012-01-01
In this paper, we investigate the effect of bank size differences on cost efficiency heterogeneity using a heteroskedastic stochastic frontier model. This model is implemented by using an information theoretic maximum entropy approach. We explicitly model both bank size and variance heterogeneity
The Threat of Common Method Variance Bias to Theory Building
Reio, Thomas G., Jr.
2010-01-01
The need for more theory building scholarship remains one of the pressing issues in the field of HRD. Researchers can employ quantitative, qualitative, and/or mixed methods to support vital theory-building efforts, understanding however that each approach has its limitations. The purpose of this article is to explore common method variance bias as…
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)
40 CFR 268.44 - Variance from a treatment standard.
2010-07-01
... complete petition may be requested as needed to send to affected states and Regional Offices. (e) The... provide an opportunity for public comment. The final decision on a variance from a treatment standard will... than) the concentrations necessary to minimize short- and long-term threats to human health and the...
Application of effective variance method for contamination monitor calibration
International Nuclear Information System (INIS)
Goncalez, O.L.; Freitas, I.S.M. de.
1990-01-01
In this report, the calibration of a thin window Geiger-Muller type monitor for alpha superficial contamination is presented. The calibration curve is obtained by the method of the least-squares fitting with effective variance. The method and the approach for the calculation are briefly discussed. (author)
The VIX, the Variance Premium, and Expected Returns
DEFF Research Database (Denmark)
Osterrieder, Daniela Maria; Ventosa-Santaulària, Daniel; Vera-Valdés, Eduardo
2018-01-01
. These problems are eliminated if risk is captured by the variance premium (VP) instead; it is unobservable, however. We propose a 2SLS estimator that produces consistent estimates without observing the VP. Using this method, we find a positive risk–return trade-off and long-run return predictability. Our...
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 ...
Variance-optimal hedging for processes with stationary independent increments
DEFF Research Database (Denmark)
Hubalek, Friedrich; Kallsen, J.; Krawczyk, L.
We determine the variance-optimal hedge when the logarithm of the underlying price follows a process with stationary independent increments in discrete or continuous time. Although the general solution to this problem is known as backward recursion or backward stochastic differential equation, we...
Adaptive Nonparametric Variance Estimation for a Ratio Estimator ...
African Journals Online (AJOL)
Kernel estimators for smooth curves require modifications when estimating near end points of the support, both for practical and asymptotic reasons. The construction of such boundary kernels as solutions of variational problem is a difficult exercise. For estimating the error variance of a ratio estimator, we suggest an ...
Handling nonnormality and variance heterogeneity for quantitative sublethal toxicity tests.
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.
Molecular variance of the Tunisian almond germplasm assessed by ...
African Journals Online (AJOL)
The genetic variance analysis of 82 almond (Prunus dulcis Mill.) genotypes was performed using ten genomic simple sequence repeats (SSRs). A total of 50 genotypes from Tunisia including local landraces identified while prospecting the different sites of Bizerte and Sidi Bouzid (Northern and central parts) which are the ...
Starting design for use in variance exchange algorithms | Iwundu ...
African Journals Online (AJOL)
A new method of constructing the initial design for use in variance exchange algorithms is presented. The method chooses support points to go into the design as measures of distances of the support points from the centre of the geometric region and of permutation-invariant sets. The initial design is as close as possible to ...
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..
A Hold-out method to correct PCA variance inflation
DEFF Research Database (Denmark)
Garcia-Moreno, Pablo; Artes-Rodriguez, Antonio; Hansen, Lars Kai
2012-01-01
In this paper we analyze the problem of variance inflation experienced by the PCA algorithm when working in an ill-posed scenario where the dimensionality of the training set is larger than its sample size. In an earlier article a correction method based on a Leave-One-Out (LOO) procedure...
Heterogeneity of variance and its implications on dairy cattle breeding
African Journals Online (AJOL)
Milk yield data (n = 12307) from 116 Holstein-Friesian herds were grouped into three production environments based on mean and standard deviation of herd 305-day milk yield and evaluated for within herd variation using univariate animal model procedures. Variance components were estimated by derivative free REML ...
Effects of Diversification of Assets on Mean and Variance | Jayeola ...
African Journals Online (AJOL)
Diversification is a means of minimizing risk and maximizing returns by investing in a variety of assets of the portfolio. This paper is written to determine the effects of diversification of three types of Assets; uncorrelated, perfectly correlated and perfectly negatively correlated assets on mean and variance. To go about this, ...
Perspective projection for variance pose face recognition from camera calibration
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.
On zero variance Monte Carlo path-stretching schemes
International Nuclear Information System (INIS)
Lux, I.
1983-01-01
A zero variance path-stretching biasing scheme proposed for a special case by Dwivedi is derived in full generality. The procedure turns out to be the generalization of the exponential transform. It is shown that the biased game can be interpreted as an analog simulation procedure, thus saving some computational effort in comparison with the corresponding nonanalog game
A mean-variance frontier in discrete and continuous time
Bekker, Paul A.
2004-01-01
The paper presents a mean-variance frontier based on dynamic frictionless investment strategies in continuous time. The result applies to a finite number of risky assets whose price process is given by multivariate geometric Brownian motion with deterministically varying coefficients. The derivation
The variance quadtree algorithm: use for spatial sampling design
Minasny, B.; McBratney, A.B.; Walvoort, D.J.J.
2007-01-01
Spatial sampling schemes are mainly developed to determine sampling locations that can cover the variation of environmental properties in the area of interest. Here we proposed the variance quadtree algorithm for sampling in an area with prior information represented as ancillary or secondary
Properties of realized variance under alternative sampling schemes
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
Variance component and heritability estimates of early growth traits ...
African Journals Online (AJOL)
as selection criteria for meat production in sheep (Anon, 1970; Olson et ai., 1976;. Lasslo et ai., 1985; Badenhorst et ai., 1991). If these traits are to be included in a breeding programme, accurate estimates of breeding values will be needed to optimize selection programmes. This requires a knowledge of variance and co-.
Variances in consumers prices of selected food Items among ...
African Journals Online (AJOL)
The study focused on the determination of variances among consumer prices of rice (local white), beans (white) and garri (yellow) in Watts, Okurikang and 8 Miles markets in southern zone of Cross River State. Completely randomized design was used to test the research hypothesis. Comparing the consumer prices of rice, ...
Age Differences in the Variance of Personality Characteristics
Czech Academy of Sciences Publication Activity Database
Mottus, R.; Allik, J.; Hřebíčková, Martina; Kööts-Ausmees, L.; Realo, A.
2016-01-01
Roč. 30, č. 1 (2016), s. 4-11 ISSN 0890-2070 R&D Projects: GA ČR GA13-25656S Institutional support: RVO:68081740 Keywords : variance * individual differences * personality * five-factor model Subject RIV: AN - Psychology Impact factor: 3.707, year: 2016
Aseptic minimum volume vitrification technique for porcine parthenogenetically activated blastocyst.
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.
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.
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
Stochastic variational approach to minimum uncertainty states
Energy Technology Data Exchange (ETDEWEB)
Illuminati, F.; Viola, L. [Dipartimento di Fisica, Padova Univ. (Italy)
1995-05-21
We introduce a new variational characterization of Gaussian diffusion processes as minimum uncertainty states. We then define a variational method constrained by kinematics of diffusions and Schroedinger dynamics to seek states of local minimum uncertainty for general non-harmonic potentials. (author)
Zero forcing parameters and minimum rank problems
Barioli, F.; Barrett, W.; Fallat, S.M.; Hall, H.T.; Hogben, L.; Shader, B.L.; Driessche, van den P.; Holst, van der H.
2010-01-01
The zero forcing number Z(G), which is the minimum number of vertices in a zero forcing set of a graph G, is used to study the maximum nullity/minimum rank of the family of symmetric matrices described by G. It is shown that for a connected graph of order at least two, no vertex is in every zero
30 CFR 281.30 - Minimum royalty.
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...
New Minimum Wage Research: A Symposium.
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,…
Minimum Wage Effects in the Longer Run
Neumark, David; Nizalova, Olena
2007-01-01
Exposure to minimum wages at young ages could lead to adverse longer-run effects via decreased labor market experience and tenure, and diminished education and training, while beneficial longer-run effects could arise if minimum wages increase skill acquisition. Evidence suggests that as individuals reach their late 20s, they earn less the longer…
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...
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)
Adaptation to Variance of Stimuli in Drosophila Larva Navigation
Wolk, Jason; Gepner, Ruben; Gershow, Marc
In order to respond to stimuli that vary over orders of magnitude while also being capable of sensing very small changes, neural systems must be capable of rapidly adapting to the variance of stimuli. We study this adaptation in Drosophila larvae responding to varying visual signals and optogenetically induced fictitious odors using an infrared illuminated arena and custom computer vision software. Larval navigational decisions (when to turn) are modeled as the output a linear-nonlinear Poisson process. The development of the nonlinear turn rate in response to changes in variance is tracked using an adaptive point process filter determining the rate of adaptation to different stimulus profiles. Supported by NIH Grant 1DP2EB022359 and NSF Grant PHY-1455015.
Compounding approach for univariate time series with nonstationary variances
Schäfer, Rudi; Barkhofen, Sonja; Guhr, Thomas; Stöckmann, Hans-Jürgen; Kuhl, Ulrich
2015-12-01
A defining feature of nonstationary systems is the time dependence of their statistical parameters. Measured time series may exhibit Gaussian statistics on short time horizons, due to the central limit theorem. The sample statistics for long time horizons, however, averages over the time-dependent variances. To model the long-term statistical behavior, we compound the local distribution with the distribution of its parameters. Here, we consider two concrete, but diverse, examples of such nonstationary systems: the turbulent air flow of a fan and a time series of foreign exchange rates. Our main focus is to empirically determine the appropriate parameter distribution for the compounding approach. To this end, we extract the relevant time scales by decomposing the time signals into windows and determine the distribution function of the thus obtained local variances.
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...
Robust LOD scores for variance component-based linkage analysis.
Blangero, J; Williams, J T; Almasy, L
2000-01-01
The variance component method is now widely used for linkage analysis of quantitative traits. Although this approach offers many advantages, the importance of the underlying assumption of multivariate normality of the trait distribution within pedigrees has not been studied extensively. Simulation studies have shown that traits with leptokurtic distributions yield linkage test statistics that exhibit excessive Type I error when analyzed naively. We derive analytical formulae relating the deviation from the expected asymptotic distribution of the lod score to the kurtosis and total heritability of the quantitative trait. A simple correction constant yields a robust lod score for any deviation from normality and for any pedigree structure, and effectively eliminates the problem of inflated Type I error due to misspecification of the underlying probability model in variance component-based linkage analysis.
Response variance in functional maps: neural darwinism revisited.
Directory of Open Access Journals (Sweden)
Hirokazu Takahashi
Full Text Available The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.
Response variance in functional maps: neural darwinism revisited.
Takahashi, Hirokazu; Yokota, Ryo; Kanzaki, Ryohei
2013-01-01
The mechanisms by which functional maps and map plasticity contribute to cortical computation remain controversial. Recent studies have revisited the theory of neural Darwinism to interpret the learning-induced map plasticity and neuronal heterogeneity observed in the cortex. Here, we hypothesize that the Darwinian principle provides a substrate to explain the relationship between neuron heterogeneity and cortical functional maps. We demonstrate in the rat auditory cortex that the degree of response variance is closely correlated with the size of its representational area. Further, we show that the response variance within a given population is altered through training. These results suggest that larger representational areas may help to accommodate heterogeneous populations of neurons. Thus, functional maps and map plasticity are likely to play essential roles in Darwinian computation, serving as effective, but not absolutely necessary, structures to generate diverse response properties within a neural population.
Replica approach to mean-variance portfolio optimization
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.
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
Spatial analysis based on variance of moving window averages
Wu, B M; Subbarao, K V; Ferrandino, F J; Hao, J J
2006-01-01
A new method for analysing spatial patterns was designed based on the variance of moving window averages (VMWA), which can be directly calculated in geographical information systems or a spreadsheet program (e.g. MS Excel). Different types of artificial data were generated to test the method. Regardless of data types, the VMWA method correctly determined the mean cluster sizes. This method was also employed to assess spatial patterns in historical plant disease survey data encompassing both a...
A mean-variance frontier in discrete and continuous time
Bekker, Paul A.
2004-01-01
The paper presents a mean-variance frontier based on dynamic frictionless investment strategies in continuous time. The result applies to a finite number of risky assets whose price process is given by multivariate geometric Brownian motion with deterministically varying coefficients. The derivation is based on the solution for the frontier in discrete time. Using the same multiperiod framework as Li and Ng (2000), I provide an alternative derivation and an alternative formulation of the solu...
Efficient Scores, Variance Decompositions and Monte Carlo Swindles.
1984-08-28
to ;r Then a version .of Pythagoras ’ theorem gives the variance decomposition (6.1) varT var S var o(T-S) P P0 0 0 One way to see this is to note...complete sufficient statistics for (B, a) , and that the standard- ized residuals a(y - XB) 6 are ancillary. Basu’s sufficiency- ancillarity theorem
Variance-based sensitivity analysis for wastewater treatment plant modelling.
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.
The mean and variance of phylogenetic diversity under rarefaction
Nipperess, David A.; Matsen, Frederick A.
2013-01-01
Phylogenetic diversity (PD) depends on sampling intensity, 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 t...
On mean reward variance in semi-Markov processes
Czech Academy of Sciences Publication Activity Database
Sladký, Karel
2005-01-01
Roč. 62, č. 3 (2005), s. 387-397 ISSN 1432-2994 R&D Projects: GA ČR(CZ) GA402/05/0115; GA ČR(CZ) GA402/04/1294 Institutional research plan: CEZ:AV0Z10750506 Keywords : Markov and semi-Markov processes with rewards * variance of cumulative reward * asymptotic behaviour Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.259, year: 2005
Mean-Variance Analysis in a Multiperiod Setting
Frauendorfer, Karl; Siede, Heiko
1997-01-01
Similar to the classical Markowitz approach it is possible to apply a mean-variance criterion to a multiperiod setting to obtain efficient portfolios. To represent the stochastic dynamic characteristics necessary for modelling returns a process of asset returns is discretized with respect to time and space and summarized in a scenario tree. The resulting optimization problem is solved by means of stochastic multistage programming. The optimal solutions show equivalent structural properties as...
Analytic solution to variance optimization with no short positions
Kondor, Imre; Papp, Gábor; Caccioli, Fabio
2017-12-01
We consider the variance portfolio optimization problem with a ban on short selling. We provide an analytical solution by means of the replica method for the case of a portfolio of independent, but not identically distributed, assets. We study the behavior of the solution as a function of the ratio r between the number N of assets and the length T of the time series of returns used to estimate risk. The no-short-selling constraint acts as an asymmetric \
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.
Improved estimation of the variance in Monte Carlo criticality calculations
International Nuclear Information System (INIS)
Hoogenboom, J. Eduard
2008-01-01
Results for the effective multiplication factor in a Monte Carlo criticality calculations are often obtained from averages over a number of cycles or batches after convergence of the fission source distribution to the fundamental mode. Then the standard deviation of the effective multiplication factor is also obtained from the k eff results over these cycles. As the number of cycles will be rather small, the estimate of the variance or standard deviation in k eff will not be very reliable, certainly not for the first few cycles after source convergence. In this paper the statistics for k eff are based on the generation of new fission neutron weights during each history in a cycle. It is shown that this gives much more reliable results for the standard deviation even after a small number of cycles. Also attention is paid to the variance of the variance (VoV) and the standard deviation of the standard deviation. A derivation is given how to obtain an unbiased estimate for the VoV, even for a small number of samples. (authors)
Improved estimation of the variance in Monte Carlo criticality calculations
Energy Technology Data Exchange (ETDEWEB)
Hoogenboom, J. Eduard [Delft University of Technology, Delft (Netherlands)
2008-07-01
Results for the effective multiplication factor in a Monte Carlo criticality calculations are often obtained from averages over a number of cycles or batches after convergence of the fission source distribution to the fundamental mode. Then the standard deviation of the effective multiplication factor is also obtained from the k{sub eff} results over these cycles. As the number of cycles will be rather small, the estimate of the variance or standard deviation in k{sub eff} will not be very reliable, certainly not for the first few cycles after source convergence. In this paper the statistics for k{sub eff} are based on the generation of new fission neutron weights during each history in a cycle. It is shown that this gives much more reliable results for the standard deviation even after a small number of cycles. Also attention is paid to the variance of the variance (VoV) and the standard deviation of the standard deviation. A derivation is given how to obtain an unbiased estimate for the VoV, even for a small number of samples. (authors)
A general transform for variance reduction in Monte Carlo simulations
International Nuclear Information System (INIS)
Becker, T.L.; Larsen, E.W.
2011-01-01
This paper describes a general transform to reduce the variance of the Monte Carlo estimate of some desired solution, such as flux or biological dose. This transform implicitly includes many standard variance reduction techniques, including source biasing, collision biasing, the exponential transform for path-length stretching, and weight windows. Rather than optimizing each of these techniques separately or choosing semi-empirical biasing parameters based on the experience of a seasoned Monte Carlo practitioner, this General Transform unites all these variance techniques to achieve one objective: a distribution of Monte Carlo particles that attempts to optimize the desired solution. Specifically, this transform allows Monte Carlo particles to be distributed according to the user's specification by using information obtained from a computationally inexpensive deterministic simulation of the problem. For this reason, we consider the General Transform to be a hybrid Monte Carlo/Deterministic method. The numerical results con rm that the General Transform distributes particles according to the user-specified distribution and generally provide reasonable results for shielding applications. (author)
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.
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...
Minimum emittance in TBA and MBA lattices
Xu, Gang; Peng, Yue-Mei
2015-03-01
For reaching a small emittance in a modern light source, triple bend achromats (TBA), theoretical minimum emittance (TME) and even multiple bend achromats (MBA) have been considered. This paper derived the necessary condition for achieving minimum emittance in TBA and MBA theoretically, where the bending angle of inner dipoles has a factor of 31/3 bigger than that of the outer dipoles. Here, we also calculated the conditions attaining the minimum emittance of TBA related to phase advance in some special cases with a pure mathematics method. These results may give some directions on lattice design.
Minimum emittance in TBA and MBA lattices
International Nuclear Information System (INIS)
Xu Gang; Peng Yuemei
2015-01-01
For reaching a small emittance in a modern light source, triple bend achromats (TBA), theoretical minimum emittance (TME) and even multiple bend achromats (MBA) have been considered. This paper derived the necessary condition for achieving minimum emittance in TBA and MBA theoretically, where the bending angle of inner dipoles has a factor of 3 1/3 bigger than that of the outer dipoles. Here, we also calculated the conditions attaining the minimum emittance of TBA related to phase advance in some special cases with a pure mathematics method. These results may give some directions on lattice design. (authors)
Who Benefits from a Minimum Wage Increase?
John W. Lopresti; Kevin J. Mumford
2015-01-01
This paper addresses the question of how a minimum wage increase affects the wages of low-wage workers. Most studies assume that there is a simple mechanical increase in the wage for workers earning a wage between the old and the new minimum wage, with some studies allowing for spillovers to workers with wages just above this range. Rather than assume that the wages of these workers would have remained constant, this paper estimates how a minimum wage increase impacts a low-wage worker's wage...
Wage inequality, minimum wage effects and spillovers
Stewart, Mark B.
2011-01-01
This paper investigates possible spillover effects of the UK minimum wage. The halt in the growth in inequality in the lower half of the wage distribution (as measured by the 50:10 percentile ratio) since the mid-1990s, in contrast to the continued inequality growth in the upper half of the distribution, suggests the possibility of a minimum wage effect and spillover effects on wages above the minimum. This paper analyses individual wage changes, using both a difference-in-differences estimat...
A proxy for variance in dense matching over homogeneous terrain
Altena, Bas; Cockx, Liesbet; Goedemé, Toon
2014-05-01
Automation in photogrammetry and avionics have brought highly autonomous UAV mapping solutions on the market. These systems have great potential for geophysical research, due to their mobility and simplicity of work. Flight planning can be done on site and orientation parameters are estimated automatically. However, one major drawback is still present: if contrast is lacking, stereoscopy fails. Consequently, topographic information cannot be obtained precisely through photogrammetry for areas with low contrast. Even though more robustness is added in the estimation through multi-view geometry, a precise product is still lacking. For the greater part, interpolation is applied over these regions, where the estimation is constrained by uniqueness, its epipolar line and smoothness. Consequently, digital surface models are generated with an estimate of the topography, without holes but also without an indication of its variance. Every dense matching algorithm is based on a similarity measure. Our methodology uses this property to support the idea that if only noise is present, no correspondence can be detected. Therefore, the noise level is estimated in respect to the intensity signal of the topography (SNR) and this ratio serves as a quality indicator for the automatically generated product. To demonstrate this variance indicator, two different case studies were elaborated. The first study is situated at an open sand mine near the village of Kiezegem, Belgium. Two different UAV systems flew over the site. One system had automatic intensity regulation, and resulted in low contrast over the sandy interior of the mine. That dataset was used to identify the weak estimations of the topography and was compared with the data from the other UAV flight. In the second study a flight campaign with the X100 system was conducted along the coast near Wenduine, Belgium. The obtained images were processed through structure-from-motion software. Although the beach had a very low
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.
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
How unprecedented a solar minimum was it?
Russell, C T; Jian, L K; Luhmann, J G
2013-05-01
The end of the last solar cycle was at least 3 years late, and to date, the new solar cycle has seen mainly weaker activity since the onset of the rising phase toward the new solar maximum. The newspapers now even report when auroras are seen in Norway. This paper is an update of our review paper written during the deepest part of the last solar minimum [1]. We update the records of solar activity and its consequent effects on the interplanetary fields and solar wind density. The arrival of solar minimum allows us to use two techniques that predict sunspot maximum from readings obtained at solar minimum. It is clear that the Sun is still behaving strangely compared to the last few solar minima even though we are well beyond the minimum phase of the cycle 23-24 transition.
Impact of the Minimum Wage on Compression.
Wolfe, Michael N.; Candland, Charles W.
1979-01-01
Assesses the impact of increases in the minimum wage on salary schedules, provides guidelines for creating a philosophy to deal with the impact, and outlines options and presents recommendations. (IRT)
Quantitative Research on the Minimum Wage
Goldfarb, Robert S.
1975-01-01
The article reviews recent research examining the impact of minimum wage requirements on the size and distribution of teenage employment and earnings. The studies measure income distribution, employment levels and effect on unemployment. (MW)
Determining minimum lubrication film for machine parts
Hamrock, B. J.; Dowson, D.
1978-01-01
Formula predicts minimum film thickness required for fully-flooded ball bearings, gears, and cams. Formula is result of study to determine complete theoretical solution of isothermal elasto-hydrodynamic lubrication of fully-flooded elliptical contacts.
Long Term Care Minimum Data Set (MDS)
U.S. Department of Health & Human Services — The Long-Term Care Minimum Data Set (MDS) is a standardized, primary screening and assessment tool of health status that forms the foundation of the comprehensive...
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.
The SME gauge sector with minimum length
Energy Technology Data Exchange (ETDEWEB)
Belich, H.; Louzada, H.L.C. [Universidade Federal do Espirito Santo, Departamento de Fisica e Quimica, Vitoria, ES (Brazil)
2017-12-15
We study the gauge sector of the Standard Model Extension (SME) with the Lorentz covariant deformed Heisenberg algebra associated to the minimum length. In order to find and estimate corrections, we clarify whether the violation of Lorentz symmetry and the existence of a minimum length are independent phenomena or are, in some way, related. With this goal, we analyze the dispersion relations of this theory. (orig.)
The SME gauge sector with minimum length
Belich, H.; Louzada, H. L. C.
2017-12-01
We study the gauge sector of the Standard Model Extension (SME) with the Lorentz covariant deformed Heisenberg algebra associated to the minimum length. In order to find and estimate corrections, we clarify whether the violation of Lorentz symmetry and the existence of a minimum length are independent phenomena or are, in some way, related. With this goal, we analyze the dispersion relations of this theory.
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.
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.
Minimum Wages and School Enrollment of Teenagers: A Look at the 1990's.
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)
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
Fringe biasing: A variance reduction technique for optically thick meshes
Energy Technology Data Exchange (ETDEWEB)
Smedley-Stevenson, R. P. [AWE PLC, Aldermaston Reading, Berkshire, RG7 4PR (United Kingdom)
2013-07-01
Fringe biasing is a stratified sampling scheme applicable to Monte Carlo thermal radiation transport codes. The thermal emission source in optically thick cells is partitioned into separate contributions from the cell interiors (where the likelihood of the particles escaping the cells is virtually zero) and the 'fringe' regions close to the cell boundaries. Thermal emission in the cell interiors can now be modelled with fewer particles, the remaining particles being concentrated in the fringes so that they are more likely to contribute to the energy exchange between cells. Unlike other techniques for improving the efficiency in optically thick regions (such as random walk and discrete diffusion treatments), fringe biasing has the benefit of simplicity, as the associated changes are restricted to the sourcing routines with the particle tracking routines being unaffected. This paper presents an analysis of the potential for variance reduction achieved from employing the fringe biasing technique. The aim of this analysis is to guide the implementation of this technique in Monte Carlo thermal radiation codes, specifically in order to aid the choice of the fringe width and the proportion of particles allocated to the fringe (which are interrelated) in multi-dimensional simulations, and to confirm that the significant levels of variance reduction achieved in simulations can be understood by studying the behaviour for simple test cases. The variance reduction properties are studied for a single cell in a slab geometry purely absorbing medium, investigating the accuracy of the scalar flux and current tallies on one of the interfaces with the surrounding medium. (authors)
Fringe biasing: A variance reduction technique for optically thick meshes
International Nuclear Information System (INIS)
Smedley-Stevenson, R. P.
2013-01-01
Fringe biasing is a stratified sampling scheme applicable to Monte Carlo thermal radiation transport codes. The thermal emission source in optically thick cells is partitioned into separate contributions from the cell interiors (where the likelihood of the particles escaping the cells is virtually zero) and the 'fringe' regions close to the cell boundaries. Thermal emission in the cell interiors can now be modelled with fewer particles, the remaining particles being concentrated in the fringes so that they are more likely to contribute to the energy exchange between cells. Unlike other techniques for improving the efficiency in optically thick regions (such as random walk and discrete diffusion treatments), fringe biasing has the benefit of simplicity, as the associated changes are restricted to the sourcing routines with the particle tracking routines being unaffected. This paper presents an analysis of the potential for variance reduction achieved from employing the fringe biasing technique. The aim of this analysis is to guide the implementation of this technique in Monte Carlo thermal radiation codes, specifically in order to aid the choice of the fringe width and the proportion of particles allocated to the fringe (which are interrelated) in multi-dimensional simulations, and to confirm that the significant levels of variance reduction achieved in simulations can be understood by studying the behaviour for simple test cases. The variance reduction properties are studied for a single cell in a slab geometry purely absorbing medium, investigating the accuracy of the scalar flux and current tallies on one of the interfaces with the surrounding medium. (authors)
An Empirical Temperature Variance Source Model in Heated Jets
Khavaran, Abbas; Bridges, James
2012-01-01
An acoustic analogy approach is implemented that models the sources of jet noise in heated jets. The equivalent sources of turbulent mixing noise are recognized as the differences between the fluctuating and Favre-averaged Reynolds stresses and enthalpy fluxes. While in a conventional acoustic analogy only Reynolds stress components are scrutinized for their noise generation properties, it is now accepted that a comprehensive source model should include the additional entropy source term. Following Goldstein s generalized acoustic analogy, the set of Euler equations are divided into two sets of equations that govern a non-radiating base flow plus its residual components. When the base flow is considered as a locally parallel mean flow, the residual equations may be rearranged to form an inhomogeneous third-order wave equation. A general solution is written subsequently using a Green s function method while all non-linear terms are treated as the equivalent sources of aerodynamic sound and are modeled accordingly. In a previous study, a specialized Reynolds-averaged Navier-Stokes (RANS) solver was implemented to compute the variance of thermal fluctuations that determine the enthalpy flux source strength. The main objective here is to present an empirical model capable of providing a reasonable estimate of the stagnation temperature variance in a jet. Such a model is parameterized as a function of the mean stagnation temperature gradient in the jet, and is evaluated using commonly available RANS solvers. The ensuing thermal source distribution is compared with measurements as well as computational result from a dedicated RANS solver that employs an enthalpy variance and dissipation rate model. Turbulent mixing noise predictions are presented for a wide range of jet temperature ratios from 1.0 to 3.20.
A Note on the Kinks at the Mean Variance Frontier
Vörös, J.; Kriens, J.; Strijbosch, L.W.G.
1997-01-01
In this paper the standard portfolio case with short sales restrictions is analyzed.Dybvig pointed out that if there is a kink at a risky portfolio on the efficient frontier, then the securities in this portfolio have equal expected return and the converse of this statement is false.For the existence of kinks at the efficient frontier the sufficient condition is given here and a new procedure is used to derive the efficient frontier, i.e. the characteristics of the mean variance frontier.