Advanced Variance Reduction for Global k-Eigenvalue Simulations in MCNP
Edward W. Larsen
2008-06-01
The "criticality" or k-eigenvalue of a nuclear system determines whether the system is critical (k=1), or the extent to which it is subcritical (k<1) or supercritical (k>1). Calculations of k are frequently performed at nuclear facilities to determine the criticality of nuclear reactor cores, spent nuclear fuel storage casks, and other fissile systems. These calculations can be expensive, and current Monte Carlo methods have certain well-known deficiencies. In this project, we have developed and tested a new "functional Monte Carlo" (FMC) method that overcomes several of these deficiencies. The current state-of-the-art Monte Carlo k-eigenvalue method estimates the fission source for a sequence of fission generations (cycles), during each of which M particles per cycle are processed. After a series of "inactive" cycles during which the fission source "converges," a series of "active" cycles are performed. For each active cycle, the eigenvalue and eigenfunction are estimated; after N >> 1 active cycles are performed, the results are averaged to obtain estimates of the eigenvalue and eigenfunction and their standard deviations. This method has several disadvantages: (i) the estimate of k depends on the number M of particles per cycle, (iii) for optically thick systems, the eigenfunction estimate may not converge due to undersampling of the fission source, and (iii) since the fission source in any cycle depends on the estimated fission source from the previous cycle (the fission sources in different cycles are correlated), the estimated variance in k is smaller than the real variance. For an acceptably large number M of particles per cycle, the estimate of k is nearly independent of M; this essentially takes care of item (i). Item (ii) can be addressed by taking M sufficiently large, but for optically thick systems a sufficiently large M can easily be unrealistic. Item (iii) cannot be accounted for by taking M or N sufficiently large; it is an inherent deficiency due
Advanced Variance Reduction for Global k-Eigenvalue Simulations in MCNP
Edward W. Larsen
2008-06-01
The "criticality" or k-eigenvalue of a nuclear system determines whether the system is critical (k=1), or the extent to which it is subcritical (k<1) or supercritical (k>1). Calculations of k are frequently performed at nuclear facilities to determine the criticality of nuclear reactor cores, spent nuclear fuel storage casks, and other fissile systems. These calculations can be expensive, and current Monte Carlo methods have certain well-known deficiencies. In this project, we have developed and tested a new "functional Monte Carlo" (FMC) method that overcomes several of these deficiencies. The current state-of-the-art Monte Carlo k-eigenvalue method estimates the fission source for a sequence of fission generations (cycles), during each of which M particles per cycle are processed. After a series of "inactive" cycles during which the fission source "converges," a series of "active" cycles are performed. For each active cycle, the eigenvalue and eigenfunction are estimated; after N >> 1 active cycles are performed, the results are averaged to obtain estimates of the eigenvalue and eigenfunction and their standard deviations. This method has several disadvantages: (i) the estimate of k depends on the number M of particles per cycle, (iii) for optically thick systems, the eigenfunction estimate may not converge due to undersampling of the fission source, and (iii) since the fission source in any cycle depends on the estimated fission source from the previous cycle (the fission sources in different cycles are correlated), the estimated variance in k is smaller than the real variance. For an acceptably large number M of particles per cycle, the estimate of k is nearly independent of M; this essentially takes care of item (i). Item (ii) can be addressed by taking M sufficiently large, but for optically thick systems a sufficiently large M can easily be unrealistic. Item (iii) cannot be accounted for by taking M or N sufficiently large; it is an inherent deficiency due
Importance Sampling Variance Reduction in GRESS ATMOSIM
Wakeford, Daniel Tyler [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-04-26
This document is intended to introduce the importance sampling method of variance reduction to a Geant4 user for application to neutral particle Monte Carlo transport through the atmosphere, as implemented in GRESS ATMOSIM.
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 intr
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 intr
Discussion on variance reduction technique for shielding
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.)
Markov bridges, bisection and variance reduction
Asmussen, Søren; Hobolth, Asger
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....... 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...... where the methods of stratification, importance sampling and quasi Monte Carlo are investigated....
Dimension reduction based on weighted variance estimate
无
2009-01-01
In this paper, we propose a new estimate for dimension reduction, called the weighted variance estimate (WVE), which includes Sliced Average Variance Estimate (SAVE) as a special case. Bootstrap method is used to select the best estimate from the WVE and to estimate the structure dimension. And this selected best estimate usually performs better than the existing methods such as Sliced Inverse Regression (SIR), SAVE, etc. Many methods such as SIR, SAVE, etc. usually put the same weight on each observation to estimate central subspace (CS). By introducing a weight function, WVE puts different weights on different observations according to distance of observations from CS. The weight function makes WVE have very good performance in general and complicated situations, for example, the distribution of regressor deviating severely from elliptical distribution which is the base of many methods, such as SIR, etc. And compared with many existing methods, WVE is insensitive to the distribution of the regressor. The consistency of the WVE is established. Simulations to compare the performances of WVE with other existing methods confirm the advantage of WVE.
Dimension reduction based on weighted variance estimate
ZHAO JunLong; XU XingZhong
2009-01-01
In this paper,we propose a new estimate for dimension reduction,called the weighted variance estimate (WVE),which includes Sliced Average Variance Estimate (SAVE) as a special case.Bootstrap method is used to select the best estimate from the WVE and to estimate the structure dimension.And this selected best estimate usually performs better than the existing methods such as Sliced Inverse Regression (SIR),SAVE,etc.Many methods such as SIR,SAVE,etc.usually put the same weight on each observation to estimate central subspace (CS).By introducing a weight function,WVE puts different weights on different observations according to distance of observations from CS.The weight function makes WVE have very good performance in general and complicated situations,for example,the distribution of regressor deviating severely from elliptical distribution which is the base of many methods,such as SIR,etc.And compared with many existing methods,WVE is insensitive to the distribution of the regressor.The consistency of the WVE is established.Simulations to compare the performances of WVE with other existing methods confirm the advantage of WVE.
Delivery Time Variance Reduction in the Military Supply Chain
2010-03-01
DELIVERY TIME VARIANCE REDUCTION IN THE MILITARY SUPPLY CHAIN THESIS...IN THE MILITARY SUPPLY CHAIN THESIS Presented to the Faculty Department of Operational Sciences Graduate School of Engineering...March 2010 APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. AFIT-OR-MS-ENS-10-02 DELIVERY TIME VARIANCE IN THE MILITARY SUPPLY CHAIN Preston
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.
Variance reduction methods applied to deep-penetration problems
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.
Automated Variance Reduction Applied to Nuclear Well-Logging Problems
Wagner, John C [ORNL; Peplow, Douglas E. [ORNL; Evans, Thomas M [ORNL
2009-01-01
The Monte Carlo method enables detailed, explicit geometric, energy and angular representations, and hence is considered to be the most accurate method available for solving complex radiation transport problems. Because of its associated accuracy, the Monte Carlo method is widely used in the petroleum exploration industry to design, benchmark, and simulate nuclear well-logging tools. Nuclear well-logging tools, which contain neutron and/or gamma sources and two or more detectors, are placed in boreholes that contain water (and possibly other fluids) and that are typically surrounded by a formation (e.g., limestone, sandstone, calcites, or a combination). The response of the detectors to radiation returning from the surrounding formation is used to infer information about the material porosity, density, composition, and associated characteristics. Accurate computer simulation is a key aspect of this exploratory technique. However, because this technique involves calculating highly precise responses (at two or more detectors) based on radiation that has interacted with the surrounding formation, the transport simulations are computationally intensive, requiring significant use of variance reduction techniques, parallel computing, or both. Because of the challenging nature of these problems, nuclear well-logging problems have frequently been used to evaluate the effectiveness of variance reduction techniques (e.g., Refs. 1-4). The primary focus of these works has been on improving the computational efficiency associated with calculating the response at the most challenging detector location, which is typically the detector furthest from the source. Although the objective of nuclear well-logging simulations is to calculate the response at multiple detector locations, until recently none of the numerous variance reduction methods/techniques has been well-suited to simultaneous optimization of multiple detector (tally) regions. Therefore, a separate calculation is
AVATAR -- Automatic variance reduction in Monte Carlo calculations
Van Riper, K.A.; Urbatsch, T.J.; Soran, P.D. [and others
1997-05-01
AVATAR{trademark} (Automatic Variance And Time of Analysis Reduction), accessed through the graphical user interface application, Justine{trademark}, is a superset of MCNP{trademark} that automatically invokes THREEDANT{trademark} for a three-dimensional deterministic adjoint calculation on a mesh independent of the Monte Carlo geometry, calculates weight windows, and runs MCNP. Computational efficiency increases by a factor of 2 to 5 for a three-detector oil well logging tool model. Human efficiency increases dramatically, since AVATAR eliminates the need for deep intuition and hours of tedious handwork.
Deflation as a Method of Variance Reduction for Estimating the Trace of a Matrix Inverse
Gambhir, Arjun Singh; Orginos, Kostas
2016-01-01
Many fields require computing the trace of the inverse of a large, sparse matrix. The typical method used for such computations is the Hutchinson method which is a Monte Carlo (MC) averaging over matrix quadratures. To improve its convergence, several variance reductions techniques have been proposed. In this paper, we study the effects of deflating the near null singular value space. We make two main contributions. First, we analyze the variance of the Hutchinson method as a function of the deflated singular values and vectors. Although this provides good intuition in general, by assuming additionally that the singular vectors are random unitary matrices, we arrive at concise formulas for the deflated variance that include only the variance and mean of the singular values. We make the remarkable observation that deflation may increase variance for Hermitian matrices but not for non-Hermitian ones. This is a rare, if not unique, property where non-Hermitian matrices outperform Hermitian ones. The theory can b...
Zoubair, M.; El Bardouni, T.; El Gonnouni, L.; Boulaich, Y.; El Bakkari, B.; El Younoussi, C.
2012-01-01
Computation time constitutes an important and a problematic parameter in Monte Carlo simulations, which is inversely proportional to the statistical errors so there comes the idea to use the variance reduction techniques. These techniques play an important role in reducing uncertainties and improving the statistical results. Several variance reduction techniques have been developed. The most known are Transport cutoffs, Interaction forcing, Bremsstrahlung splitting and Russian roulette. Also, the use of a phase space seems to be appropriate to reduce enormously the computing time. In this work, we applied these techniques on a linear accelerator (LINAC) using the MCNPX computer Monte Carlo code. This code gives a rich palette of variance reduction techniques. In this study we investigated various cards related to the variance reduction techniques provided by MCNPX. The parameters found in this study are warranted to be used efficiently in MCNPX code. Final calculations are performed in two steps that are related by a phase space. Results show that, comparatively to direct simulations (without neither variance-reduction nor phase space), the adopted method allows an improvement in the simulation efficiency by a factor greater than 700.
Larsen, Ryan J.; Newman, Michael; Nikolaidis, Aki
2016-11-01
Multiple methods have been proposed for using Magnetic Resonance Spectroscopy Imaging (MRSI) to measure representative metabolite concentrations of anatomically-defined brain regions. Generally these methods require spectral analysis, quantitation of the signal, and reconciliation with anatomical brain regions. However, to simplify processing pipelines, it is practical to only include those corrections that significantly improve data quality. Of particular importance for cross-sectional studies is knowledge about how much each correction lowers the inter-subject variance of the measurement, thereby increasing statistical power. Here we use a data set of 72 subjects to calculate the reduction in inter-subject variance produced by several corrections that are commonly used to process MRSI data. Our results demonstrate that significant reductions of variance can be achieved by performing water scaling, accounting for tissue type, and integrating MRSI data over anatomical regions rather than simply assigning MRSI voxels with anatomical region labels.
Maucec, M
2005-01-01
Monte Carlo simulations for nuclear logging applications are considered to be highly demanding transport problems. In this paper, the implementation of weight-window variance reduction schemes in a 'manual' fashion to improve the efficiency of calculations for a neutron logging tool is presented. Th
Automatic variance reduction for Monte Carlo simulations via the local importance function transform
Turner, S.A.
1996-02-01
The author derives a transformed transport problem that can be solved theoretically by analog Monte Carlo with zero variance. However, the Monte Carlo simulation of this transformed problem cannot be implemented in practice, so he develops a method for approximating it. The approximation to the zero variance method consists of replacing the continuous adjoint transport solution in the transformed transport problem by a piecewise continuous approximation containing local biasing parameters obtained from a deterministic calculation. He uses the transport and collision processes of the transformed problem to bias distance-to-collision and selection of post-collision energy groups and trajectories in a traditional Monte Carlo simulation of ``real`` particles. He refers to the resulting variance reduction method as the Local Importance Function Transform (LIFI) method. He demonstrates the efficiency of the LIFT method for several 3-D, linearly anisotropic scattering, one-group, and multigroup problems. In these problems the LIFT method is shown to be more efficient than the AVATAR scheme, which is one of the best variance reduction techniques currently available in a state-of-the-art Monte Carlo code. For most of the problems considered, the LIFT method produces higher figures of merit than AVATAR, even when the LIFT method is used as a ``black box``. There are some problems that cause trouble for most variance reduction techniques, and the LIFT method is no exception. For example, the author demonstrates that problems with voids, or low density regions, can cause a reduction in the efficiency of the LIFT method. However, the LIFT method still performs better than survival biasing and AVATAR in these difficult cases.
Automatic variance reduction for Monte Carlo simulations via the local importance function transform
Turner, S.A.
1996-02-01
The author derives a transformed transport problem that can be solved theoretically by analog Monte Carlo with zero variance. However, the Monte Carlo simulation of this transformed problem cannot be implemented in practice, so he develops a method for approximating it. The approximation to the zero variance method consists of replacing the continuous adjoint transport solution in the transformed transport problem by a piecewise continuous approximation containing local biasing parameters obtained from a deterministic calculation. He uses the transport and collision processes of the transformed problem to bias distance-to-collision and selection of post-collision energy groups and trajectories in a traditional Monte Carlo simulation of ``real`` particles. He refers to the resulting variance reduction method as the Local Importance Function Transform (LIFI) method. He demonstrates the efficiency of the LIFT method for several 3-D, linearly anisotropic scattering, one-group, and multigroup problems. In these problems the LIFT method is shown to be more efficient than the AVATAR scheme, which is one of the best variance reduction techniques currently available in a state-of-the-art Monte Carlo code. For most of the problems considered, the LIFT method produces higher figures of merit than AVATAR, even when the LIFT method is used as a ``black box``. There are some problems that cause trouble for most variance reduction techniques, and the LIFT method is no exception. For example, the author demonstrates that problems with voids, or low density regions, can cause a reduction in the efficiency of the LIFT method. However, the LIFT method still performs better than survival biasing and AVATAR in these difficult cases.
Clarke, Peter; Varghese, Philip; Goldstein, David [ASE-EM Department, UT Austin, 210 East 24th St, C0600, Austin, TX 78712 (United States)
2014-12-09
We extend a variance reduced discrete velocity method developed at UT Austin [1, 2] to gas mixtures with large mass ratios and flows with trace species. The mixture is stored as a collection of independent velocity distribution functions, each with a unique grid in velocity space. Different collision types (A-A, A-B, B-B, etc.) are treated independently, and the variance reduction scheme is formulated with different equilibrium functions for each separate collision type. The individual treatment of species enables increased focus on species important to the physics of the flow, even if the important species are present in trace amounts. The method is verified through comparisons to Direct Simulation Monte Carlo computations and the computational workload per time step is investigated for the variance reduced method.
Athènes, Manuel; Terrier, Pierre
2017-05-01
Markov chain Monte Carlo methods are primarily used for sampling from a given probability distribution and estimating multi-dimensional integrals based on the information contained in the generated samples. Whenever it is possible, more accurate estimates are obtained by combining Monte Carlo integration and integration by numerical quadrature along particular coordinates. We show that this variance reduction technique, referred to as conditioning in probability theory, can be advantageously implemented in expanded ensemble simulations. These simulations aim at estimating thermodynamic expectations as a function of an external parameter that is sampled like an additional coordinate. Conditioning therein entails integrating along the external coordinate by numerical quadrature. We prove variance reduction with respect to alternative standard estimators and demonstrate the practical efficiency of the technique by estimating free energies and characterizing a structural phase transition between two solid phases.
Variance reduction technique in a beta radiation beam using an extrapolation chamber.
Polo, Ivón Oramas; Souza Santos, William; de Lara Antonio, Patrícia; Caldas, Linda V E
2017-10-01
This paper aims to show how the variance reduction technique "Geometry splitting/Russian roulette" improves the statistical error and reduces uncertainties in the determination of the absorbed dose rate in tissue using an extrapolation chamber for beta radiation. The results show that the use of this technique can increase the number of events in the chamber cavity leading to a closer approximation of simulation result with the physical problem. There was a good agreement among the experimental measurements, the certificate of manufacture and the simulation results of the absorbed dose rate values and uncertainties. The absorbed dose rate variation coefficient using the variance reduction technique "Geometry splitting/Russian roulette" was 2.85%. Copyright © 2017 Elsevier Ltd. All rights reserved.
Use experiences of MCNP in nuclear energy study. 2. Review of variance reduction techniques
Sakurai, Kiyoshi; Yamamoto, Toshihiro [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment] [eds.
1998-03-01
`MCNP Use Experience` Working Group was established in 1996 under the Special Committee on Nuclear Code Evaluation. This year`s main activity of the working group has been focused on the review of variance reduction techniques of Monte Carlo calculations. This working group dealt with the variance reduction techniques of (1) neutron and gamma ray transport calculation of fusion reactor system, (2) concept design of nuclear transmutation system using accelerator, (3) JMTR core calculation, (4) calculation of prompt neutron decay constant, (5) neutron and gamma ray transport calculation for exposure evaluation, (6) neutron and gamma ray transport calculation of shielding system, etc. Furthermore, this working group started an activity to compile `Guideline of Monte Carlo Calculation` which will be a standard in the future. The appendices of this report include this `Guideline`, the use experience of MCNP 4B and examples of Monte Carlo calculations of high energy charged particles. The 11 papers are indexed individually. (J.P.N.)
Vidal-Codina, F.; Nguyen, N. C.; Giles, M. B.; Peraire, J.
2015-09-01
We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basis approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method.
Vidal-Codina, F., E-mail: fvidal@mit.edu [Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139 (United States); Nguyen, N.C., E-mail: cuongng@mit.edu [Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139 (United States); Giles, M.B., E-mail: mike.giles@maths.ox.ac.uk [Mathematical Institute, University of Oxford, Oxford (United Kingdom); Peraire, J., E-mail: peraire@mit.edu [Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA 02139 (United States)
2015-09-15
We present a model and variance reduction method for the fast and reliable computation of statistical outputs of stochastic elliptic partial differential equations. Our method consists of three main ingredients: (1) the hybridizable discontinuous Galerkin (HDG) discretization of elliptic partial differential equations (PDEs), which allows us to obtain high-order accurate solutions of the governing PDE; (2) the reduced basis method for a new HDG discretization of the underlying PDE to enable real-time solution of the parameterized PDE in the presence of stochastic parameters; and (3) a multilevel variance reduction method that exploits the statistical correlation among the different reduced basis approximations and the high-fidelity HDG discretization to accelerate the convergence of the Monte Carlo simulations. The multilevel variance reduction method provides efficient computation of the statistical outputs by shifting most of the computational burden from the high-fidelity HDG approximation to the reduced basis approximations. Furthermore, we develop a posteriori error estimates for our approximations of the statistical outputs. Based on these error estimates, we propose an algorithm for optimally choosing both the dimensions of the reduced basis approximations and the sizes of Monte Carlo samples to achieve a given error tolerance. We provide numerical examples to demonstrate the performance of the proposed method.
Adewunmi, Adrian; Byrne, Mike
2008-01-01
This paper investigates the reduction of variance associated with a simulation output performance measure, using the Sequential Sampling method while applying minimum simulation replications, for a class of JIT (Just in Time) warehousing system called crossdocking. We initially used the Sequential Sampling method to attain a desired 95% confidence interval half width of plus/minus 0.5 for our chosen performance measure (Total usage cost, given the mean maximum level of 157,000 pounds and a mean minimum level of 149,000 pounds). From our results, we achieved a 95% confidence interval half width of plus/minus 2.8 for our chosen performance measure (Total usage cost, with an average mean value of 115,000 pounds). However, the Sequential Sampling method requires a huge number of simulation replications to reduce variance for our simulation output value to the target level. Arena (version 11) simulation software was used to conduct this study.
Vincenza Di Stefano
2009-11-01
Full Text Available The Multicomb variance reduction technique has been introduced in the Direct Monte Carlo Simulation for submicrometric semiconductor devices. The method has been implemented in bulk silicon. The simulations show that the statistical variance of hot electrons is reduced with some computational cost. The method is efficient and easy to implement in existing device simulators.
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.
Importance Sampling Variance Reduction for the Fokker-Planck Rarefied Gas Particle Method
Collyer, Benjamin; Lockerby, Duncan
2015-01-01
Models and methods that are able to accurately and efficiently predict the flows of low-speed rarefied gases are in high demand, due to the increasing ability to manufacture devices at micro and nano scales. One such model and method is a Fokker-Planck approximation to the Boltzmann equation, which can be solved numerically by a stochastic particle method. The stochastic nature of this method leads to noisy estimates of the thermodynamic quantities one wishes to sample when the signal is small in comparison to the thermal velocity of the gas. Recently, Gorji et al have proposed a method which is able to greatly reduce the variance of the estimators, by creating a correlated stochastic process which acts as a control variate for the noisy estimates. However, there are potential difficulties involved when the geometry of the problem is complex, as the method requires the density to be solved for independently. Importance sampling is a variance reduction technique that has already been shown to successfully redu...
Variance reduction techniques for 14 MeV neutron streaming problem in rectangular annular bent duct
Ueki, Kotaro [Ship Research Inst., Mitaka, Tokyo (Japan)
1998-03-01
Monte Carlo method is the powerful technique for solving wide range of radiation transport problems. Its features are that it can solve the Boltzmann`s transport equation almost without approximation, and that the complexity of the systems to be treated rarely becomes a problem. However, the Monte Carlo calculation is always accompanied by statistical errors called variance. In shielding calculation, standard deviation or fractional standard deviation (FSD) is used frequently. The expression of the FSD is shown. Radiation shielding problems are roughly divided into transmission through deep layer and streaming problem. In the streaming problem, the large difference in the weight depending on the history of particles makes the FSD of Monte Carlo calculation worse. The streaming experiment in the 14 MeV neutron rectangular annular bent duct, which is the typical streaming bench mark experiment carried out of the OKTAVIAN of Osaka University, was analyzed by MCNP 4B, and the reduction of variance or FSD was attempted. The experimental system is shown. The analysis model by MCNP 4B, the input data and the results of analysis are reported, and the comparison with the experimental results was examined. (K.I.)
Improving computational efficiency of Monte-Carlo simulations with variance reduction
Turner, A
2013-01-01
CCFE perform Monte-Carlo transport simulations on large and complex tokamak models such as ITER. Such simulations are challenging since streaming and deep penetration effects are equally important. In order to make such simulations tractable, both variance reduction (VR) techniques and parallel computing are used. It has been found that the application of VR techniques in such models significantly reduces the efficiency of parallel computation due to 'long histories'. VR in MCNP can be accomplished using energy-dependent weight windows. The weight window represents an 'average behaviour' of particles, and large deviations in the arriving weight of a particle give rise to extreme amounts of splitting being performed and a long history. When running on parallel clusters, a long history can have a detrimental effect on the parallel efficiency - if one process is computing the long history, the other CPUs complete their batch of histories and wait idle. Furthermore some long histories have been found to be effect...
Application of variance reduction technique to nuclear transmutation system driven by accelerator
Sasa, Toshinobu [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment
1998-03-01
In Japan, it is the basic policy to dispose the high level radioactive waste arising from spent nuclear fuel in stable deep strata after glass solidification. If the useful elements in the waste can be separated and utilized, resources are effectively used, and it can be expected to guarantee high economical efficiency and safety in the disposal in strata. Japan Atomic Energy Research Institute proposed the hybrid type transmutation system, in which high intensity proton accelerator and subcritical fast core are combined, or the nuclear reactor which is optimized for the exclusive use for transmutation. The tungsten target, minor actinide nitride fuel transmutation system and the melted minor actinide chloride salt target fuel transmutation system are outlined. The conceptual figures of both systems are shown. As the method of analysis, Version 2.70 of Lahet Code System which was developed by Los Alamos National Laboratory in USA was adopted. In case of carrying out the analysis of accelerator-driven subcritical core in the energy range below 20 MeV, variance reduction technique must be applied. (K.I.)
Variance reduction techniques for a quantitative understanding of the \\Delta I = 1/2 rule
Endress, Eric
2012-01-01
The role of the charm quark in the dynamics underlying the \\Delta I = 1/2 rule for kaon decays can be understood by studying the dependence of kaon decay amplitudes on the charm quark mass using an effective \\Delta S = 1 weak Hamiltonian in which the charm is kept as an active degree of freedom. Overlap fermions are employed in order to avoid renormalization problems, as well as to allow access to the deep chiral regime. Quenched results in the GIM limit have shown that a significant part of the enhancement is purely due to low-energy QCD effects; variance reduction techniques based on low-mode averaging were instrumental in determining the relevant weak effective lowenergy couplings in this case. Moving away from the GIM limit requires the computation of diagrams containing closed quark loops. We report on our progress to employ a combination of low-mode averaging and stochastic volume sources in order to control these contributions. Results showing a significant improvement in the statistical signal are pre...
Advanced digital signal processing and noise reduction
Vaseghi, Saeed V
2008-01-01
Digital signal processing plays a central role in the development of modern communication and information processing systems. The theory and application of signal processing is concerned with the identification, modelling and utilisation of patterns and structures in a signal process. The observation signals are often distorted, incomplete and noisy and therefore noise reduction, the removal of channel distortion, and replacement of lost samples are important parts of a signal processing system. The fourth edition of Advanced Digital Signal Processing and Noise Reduction updates an
Advanced Data Reduction Techniques for MUSE
Weilbacher, Peter M; Roth, Martin M; Boehm, Petra; Pecontal-Rousset, Arlette
2009-01-01
MUSE, a 2nd generation VLT instrument, will become the world's largest integral field spectrograph. It will be an AO assisted instrument which, in a single exposure, covers the wavelength range from 465 to 930 nm with an average resolution of 3000 over a field of view of 1'x1' with 0.2'' spatial sampling. Both the complexity and the rate of the data are a challenge for the data processing of this instrument. We will give an overview of the data processing scheme that has been designed for MUSE. Specifically, we will use only a single resampling step from the raw data to the reduced data product. This allows us to improve data quality, accurately propagate variance, and minimize spreading of artifacts and correlated noise. This approach necessitates changes to the standard way in which reduction steps like wavelength calibration and sky subtraction are carried out, but can be expanded to include combination of multiple exposures.
Ramos-Méndez, José; Schuemann, Jan; Incerti, Sebastien; Paganetti, Harald; Schulte, Reinhard; Faddegon, Bruce
2017-08-01
deviations) for endpoints (1) and (2), within 2% (1 standard deviation) for endpoint (3). In conclusion, standard particle splitting variance reduction techniques can be successfully implemented in Monte Carlo track structure codes.
Wang, Zhen; Cui, Shengcheng; Yang, Jun; Gao, Haiyang; Liu, Chao; Zhang, Zhibo
2017-03-01
We present a novel hybrid scattering order-dependent variance reduction method to accelerate the convergence rate in both forward and backward Monte Carlo radiative transfer simulations involving highly forward-peaked scattering phase function. This method is built upon a newly developed theoretical framework that not only unifies both forward and backward radiative transfer in scattering-order-dependent integral equation, but also generalizes the variance reduction formalism in a wide range of simulation scenarios. In previous studies, variance reduction is achieved either by using the scattering phase function forward truncation technique or the target directional importance sampling technique. Our method combines both of them. A novel feature of our method is that all the tuning parameters used for phase function truncation and importance sampling techniques at each order of scattering are automatically optimized by the scattering order-dependent numerical evaluation experiments. To make such experiments feasible, we present a new scattering order sampling algorithm by remodeling integral radiative transfer kernel for the phase function truncation method. The presented method has been implemented in our Multiple-Scaling-based Cloudy Atmospheric Radiative Transfer (MSCART) model for validation and evaluation. The main advantage of the method is that it greatly improves the trade-off between numerical efficiency and accuracy order by order.
Milias-Argeitis, Andreas; Lygeros, John; Khammash, Mustafa
2014-07-01
We address the problem of estimating steady-state quantities associated to systems of stochastic chemical kinetics. In most cases of interest, these systems are analytically intractable, and one has to resort to computational methods to estimate stationary values of cost functions. In this work, we introduce a novel variance reduction algorithm for stochastic chemical kinetics, inspired by related methods in queueing theory, in particular the use of shadow functions. Using two numerical examples, we demonstrate the efficiency of the method for the calculation of steady-state parametric sensitivities and evaluate its performance in comparison to other estimation methods.
Golzari, Fahimeh; Jalili, Saeed
2015-07-21
In protein function prediction (PFP) problem, the goal is to predict function of numerous well-sequenced known proteins whose function is not still known precisely. PFP is one of the special and complex problems in machine learning domain in which a protein (regarded as instance) may have more than one function simultaneously. Furthermore, the functions (regarded as classes) are dependent and also are organized in a hierarchical structure in the form of a tree or directed acyclic graph. One of the common learning methods proposed for solving this problem is decision trees in which, by partitioning data into sharp boundaries sets, small changes in the attribute values of a new instance may cause incorrect change in predicted label of the instance and finally misclassification. In this paper, a Variance Reduction based Binary Fuzzy Decision Tree (VR-BFDT) algorithm is proposed to predict functions of the proteins. This algorithm just fuzzifies the decision boundaries instead of converting the numeric attributes into fuzzy linguistic terms. It has the ability of assigning multiple functions to each protein simultaneously and preserves the hierarchy consistency between functional classes. It uses the label variance reduction as splitting criterion to select the best "attribute-value" at each node of the decision tree. The experimental results show that the overall performance of the proposed algorithm is promising. Copyright © 2015 Elsevier Ltd. All rights reserved.
Sampson, Andrew; Le Yi; Williamson, Jeffrey F. [Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia 23298 (United States)
2012-02-15
heterogeneous doses. On an AMD 1090T processor, computing times of 38 and 21 sec were required to achieve an average statistical uncertainty of 2% within the prostate (1 x 1 x 1 mm{sup 3}) and breast (0.67 x 0.67 x 0.8 mm{sup 3}) CTVs, respectively. Conclusions: CMC supports an additional average 38-60 fold improvement in average efficiency relative to conventional uncorrelated MC techniques, although some voxels experience no gain or even efficiency losses. However, for the two investigated case studies, the maximum variance within clinically significant structures was always reduced (on average by a factor of 6) in the therapeutic dose range generally. CMC takes only seconds to produce an accurate, high-resolution, low-uncertainly dose distribution for the low-energy PSB implants investigated in this study.
无
2010-01-01
A new noise reduction method for nonlinear signal based on maximum variance unfolding(MVU)is proposed.The noisy sig- nal is firstly embedded into a high-dimensional phase space based on phase space reconstruction theory,and then the manifold learning algorithm MVU is used to perform nonlinear dimensionality reduction on the data of phase space in order to separate low-dimensional manifold representing the attractor from noise subspace.Finally,the noise-reduced signal is obtained through reconstructing the low-dimensional manifold.The simulation results of Lorenz system show that the proposed MVU-based noise reduction method outperforms the KPCA-based method and has the advantages of simple parameter estimation and low parameter sensitivity.The proposed method is applied to fault detection of a vibration signal from rotor-stator of aero engine with slight rubbing fault.The denoised results show that the slight rubbing features overwhelmed by noise can be effectively extracted by the proposed noise reduction method.
Doi, Suhail A R; Barendregt, Jan J; Khan, Shahjahan; Thalib, Lukman; Williams, Gail M
2015-11-01
This article examines an improved alternative to the random effects (RE) model for meta-analysis of heterogeneous studies. It is shown that the known issues of underestimation of the statistical error and spuriously overconfident estimates with the RE model can be resolved by the use of an estimator under the fixed effect model assumption with a quasi-likelihood based variance structure - the IVhet model. Extensive simulations confirm that this estimator retains a correct coverage probability and a lower observed variance than the RE model estimator, regardless of heterogeneity. When the proposed IVhet method is applied to the controversial meta-analysis of intravenous magnesium for the prevention of mortality after myocardial infarction, the pooled OR is 1.01 (95% CI 0.71-1.46) which not only favors the larger studies but also indicates more uncertainty around the point estimate. In comparison, under the RE model the pooled OR is 0.71 (95% CI 0.57-0.89) which, given the simulation results, reflects underestimation of the statistical error. Given the compelling evidence generated, we recommend that the IVhet model replace both the FE and RE models. To facilitate this, it has been implemented into free meta-analysis software called MetaXL which can be downloaded from www.epigear.com.
Evaluation of the Advanced Subsonic Technology Program Noise Reduction Benefits
Golub, Robert A.; Rawls, John W., Jr.; Russell, James W.
2005-01-01
This report presents a detailed evaluation of the aircraft noise reduction technology concepts developed during the course of the NASA/FAA Advanced Subsonic Technology (AST) Noise Reduction Program. In 1992, NASA and the FAA initiated a cosponsored, multi-year program with the U.S. aircraft industry focused on achieving significant advances in aircraft noise reduction. The program achieved success through a systematic development and validation of noise reduction technology. Using the NASA Aircraft Noise Prediction Program, the noise reduction benefit of the technologies that reached a NASA technology readiness level of 5 or 6 were applied to each of four classes of aircraft which included a large four engine aircraft, a large twin engine aircraft, a small twin engine aircraft and a business jet. Total aircraft noise reductions resulting from the implementation of the appropriate technologies for each class of aircraft are presented and compared to the AST program goals.
Wagner, John C [ORNL; Peplow, Douglas E. [ORNL; Mosher, Scott W [ORNL
2014-01-01
This paper presents a new hybrid (Monte Carlo/deterministic) method for increasing the efficiency of Monte Carlo calculations of distributions, such as flux or dose rate distributions (e.g., mesh tallies), as well as responses at multiple localized detectors and spectra. This method, referred to as Forward-Weighted CADIS (FW-CADIS), is an extension of the Consistent Adjoint Driven Importance Sampling (CADIS) method, which has been used for more than a decade to very effectively improve the efficiency of Monte Carlo calculations of localized quantities, e.g., flux, dose, or reaction rate at a specific location. The basis of this method is the development of an importance function that represents the importance of particles to the objective of uniform Monte Carlo particle density in the desired tally regions. Implementation of this method utilizes the results from a forward deterministic calculation to develop a forward-weighted source for a deterministic adjoint calculation. The resulting adjoint function is then used to generate consistent space- and energy-dependent source biasing parameters and weight windows that are used in a forward Monte Carlo calculation to obtain more uniform statistical uncertainties in the desired tally regions. The FW-CADIS method has been implemented and demonstrated within the MAVRIC sequence of SCALE and the ADVANTG/MCNP framework. Application of the method to representative, real-world problems, including calculation of dose rate and energy dependent flux throughout the problem space, dose rates in specific areas, and energy spectra at multiple detectors, is presented and discussed. Results of the FW-CADIS method and other recently developed global variance reduction approaches are also compared, and the FW-CADIS method outperformed the other methods in all cases considered.
Golosio, Bruno; Schoonjans, Tom; Brunetti, Antonio; Oliva, Piernicola; Masala, Giovanni Luca
2014-03-01
The simulation of X-ray imaging experiments is often performed using deterministic codes, which can be relatively fast and easy to use. However, such codes are generally not suitable for the simulation of even slightly more complex experimental conditions, involving, for instance, first-order or higher-order scattering, X-ray fluorescence emissions, or more complex geometries, particularly for experiments that combine spatial resolution with spectral information. In such cases, simulations are often performed using codes based on the Monte Carlo method. In a simple Monte Carlo approach, the interaction position of an X-ray photon and the state of the photon after an interaction are obtained simply according to the theoretical probability distributions. This approach may be quite inefficient because the final channels of interest may include only a limited region of space or photons produced by a rare interaction, e.g., fluorescent emission from elements with very low concentrations. In the field of X-ray fluorescence spectroscopy, this problem has been solved by combining the Monte Carlo method with variance reduction techniques, which can reduce the computation time by several orders of magnitude. In this work, we present a C++ code for the general simulation of X-ray imaging and spectroscopy experiments, based on the application of the Monte Carlo method in combination with variance reduction techniques, with a description of sample geometry based on quadric surfaces. We describe the benefits of the object-oriented approach in terms of code maintenance, the flexibility of the program for the simulation of different experimental conditions and the possibility of easily adding new modules. Sample applications in the fields of X-ray imaging and X-ray spectroscopy are discussed. Catalogue identifier: AERO_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERO_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland
Lim, Sanghyeok; Kim, Seung Hyun; Kim, Yongsoo; Cho, Young Seo; Kim, Tae Yeob; Jeong, Woo Kyoung; Sohn, Joo Hyun
2017-08-14
To compare the diagnostic performance for advanced hepatic fibrosis measured by 2D shear-wave elastography (SWE), using either the coefficient of variance (CV) or the interquartile range divided by the median value (IQR/M) as quality criteria. In this retrospective study, from January 2011 to December 2013, 96 patients, who underwent both liver stiffness measurement by 2D SWE and liver biopsy for hepatic fibrosis grading, were enrolled. The diagnostic performances of the CV and the IQR/M were analyzed using receiver operating characteristic curves with areas under the curves (AUCs) and were compared by Fisher's Z test, based on matching the cutoff points in an interactive dot diagram. All P values less than 0.05 were considered significant. When using the cutoff value IQR/M of 0.21, the matched cutoff point of CV was 20%. When a cutoff value of CV of 20% was used, the diagnostic performance for advanced hepatic fibrosis ( ≥ F3 grade) with CV of less than 20% was better than that in the group with CV greater than or equal to 20% (AUC 0.967 versus 0.786, z statistic = 2.23, P = .025), whereas when the matched cutoff value IQR/M of 0.21 showed no difference (AUC 0.918 versus 0.927, z statistic = -0.178, P = .859). The validity of liver stiffness measurements made by 2D SWE for assessing advanced hepatic fibrosis may be judged using CVs, and when the CV is less than 20% it can be considered "more reliable" than using IQR/M of less than 0.21. © 2017 by the American Institute of Ultrasound in Medicine.
Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W.; Müller, Klaus-Robert; Lemm, Steven
2013-01-01
Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation. PMID:23844016
Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W; Müller, Klaus-Robert; Lemm, Steven
2013-01-01
Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation.
Daniel Bartz
Full Text Available Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation.
Mendenhall, Marcus H
2011-01-01
In Monte-Carlo codes such as Geant4, it is often important to adjust reaction cross sections to reduce the variance of calculations of relatively rare events, in a technique known as non-analogous Monte-Carlo. We present the theory and sample code for a Geant4 process which allows the cross section of a G4VDiscreteProcess to be scaled, while adjusting track weights so as to mitigate the effects of altered primary beam depletion induced by the cross section change. This allows us to increase the cross section of nuclear reactions by factors exceeding 10^{4} (in appropriate cases), without distorting the results of energy deposition calculations or coincidence rates. The procedure is also valid for bias factors less than unity, which is useful, for example, in problems which involve computation of particle penetration deep into a target, such as occurs in atmospheric showers or in shielding.
Mendenhall, Marcus H., E-mail: marcus.h.mendenhall@vanderbilt.edu [Vanderbilt University, Department of Electrical Engineering, P.O. Box 351824B, Nashville, TN 37235 (United States); Weller, Robert A., E-mail: robert.a.weller@vanderbilt.edu [Vanderbilt University, Department of Electrical Engineering, P.O. Box 351824B, Nashville, TN 37235 (United States)
2012-03-01
In Monte Carlo particle transport codes, it is often important to adjust reaction cross-sections to reduce the variance of calculations of relatively rare events, in a technique known as non-analog Monte Carlo. We present the theory and sample code for a Geant4 process which allows the cross-section of a G4VDiscreteProcess to be scaled, while adjusting track weights so as to mitigate the effects of altered primary beam depletion induced by the cross-section change. This makes it possible to increase the cross-section of nuclear reactions by factors exceeding 10{sup 4} (in appropriate cases), without distorting the results of energy deposition calculations or coincidence rates. The procedure is also valid for bias factors less than unity, which is useful in problems that involve the computation of particle penetration deep into a target (e.g. atmospheric showers or shielding studies).
Fluid Mechanics, Drag Reduction and Advanced Configuration Aeronautics
Bushnell, Dennis M.
2000-01-01
This paper discusses Advanced Aircraft configurational approaches across the speed range, which are either enabled, or greatly enhanced, by clever Flow Control. Configurations considered include Channel Wings with circulation control for VTOL (but non-hovering) operation with high cruise speed, strut-braced CTOL transports with wingtip engines and extensive ('natural') laminar flow control, a midwing double fuselage CTOL approach utilizing several synergistic methods for drag-due-to-lift reduction, a supersonic strut-braced configuration with order of twice the L/D of current approaches and a very advanced, highly engine flow-path-integrated hypersonic cruise machine. This paper indicates both the promise of synergistic flow control approaches as enablers for 'Revolutions' in aircraft performance and fluid mechanic 'areas of ignorance' which impede their realization and provide 'target-rich' opportunities for Fluids Research.
Cycle update : advanced fuels and technologies for emissions reduction
Smallwood, G. [National Research Council of Canada, Ottawa, ON (Canada)
2009-07-01
This paper provided a summary of key achievements of the Program of Energy Research and Development advanced fuels and technologies for emissions reduction (AFTER) program over the funding cycle from fiscal year 2005/2006 to 2008/2009. The purpose of the paper was to inform interested parties of recent advances in knowledge and in science and technology capacities in a concise manner. The paper discussed the high level research and development themes of the AFTER program through the following 4 overarching questions: how could advanced fuels and internal combustion engine designs influence emissions; how could emissions be reduced through the use of engine hardware including aftertreatment devices; how do real-world duty cycles and advanced technology vehicles operating on Canadian fuels compare with existing technologies, models and estimates; and what are the health risks associated with transportation-related emissions. It was concluded that the main issues regarding the use of biodiesel blends in current technology diesel engines are the lack of consistency in product quality; shorter shelf life of biodiesel due to poorer oxidative stability; and a need to develop characterization methods for the final oxygenated product because most standard methods are developed for hydrocarbons and are therefore inadequate. 2 tabs., 13 figs.
Advanced MMIS Toward Substantial Reduction in Human Errors in NPPs
Seong, Poong Hyun; Kang, Hyun Gook [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Na, Man Gyun [Chosun Univ., Gwangju (Korea, Republic of); Kim, Jong Hyun [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of); Heo, Gyunyoung [Kyung Hee Univ., Yongin (Korea, Republic of); Jung, Yoensub [Korea Hydro and Nuclear Power Co., Ltd., Daejeon (Korea, Republic of)
2013-04-15
This paper aims to give an overview of the methods to inherently prevent human errors and to effectively mitigate the consequences of such errors by securing defense-in-depth during plant management through the advanced man-machine interface system (MMIS). It is needless to stress the significance of human error reduction during an accident in nuclear power plants (NPPs). Unexpected shutdowns caused by human errors not only threaten nuclear safety but also make public acceptance of nuclear power extremely lower. We have to recognize there must be the possibility of human errors occurring since humans are not essentially perfect particularly under stressful conditions. However, we have the opportunity to improve such a situation through advanced information and communication technologies on the basis of lessons learned from our experiences. As important lessons, authors explained key issues associated with automation, man-machine interface, operator support systems, and procedures. Upon this investigation, we outlined the concept and technical factors to develop advanced automation, operation and maintenance support systems, and computer-based procedures using wired/wireless technology. It should be noted that the ultimate responsibility of nuclear safety obviously belongs to humans not to machines. Therefore, safety culture including education and training, which is a kind of organizational factor, should be emphasized as well. In regard to safety culture for human error reduction, several issues that we are facing these days were described. We expect the ideas of the advanced MMIS proposed in this paper to lead in the future direction of related researches and finally supplement the safety of NPPs.
ADVANCED MMIS TOWARD SUBSTANTIAL REDUCTION IN HUMAN ERRORS IN NPPS
POONG HYUN SEONG
2013-04-01
Full Text Available This paper aims to give an overview of the methods to inherently prevent human errors and to effectively mitigate the consequences of such errors by securing defense-in-depth during plant management through the advanced man-machine interface system (MMIS. It is needless to stress the significance of human error reduction during an accident in nuclear power plants (NPPs. Unexpected shutdowns caused by human errors not only threaten nuclear safety but also make public acceptance of nuclear power extremely lower. We have to recognize there must be the possibility of human errors occurring since humans are not essentially perfect particularly under stressful conditions. However, we have the opportunity to improve such a situation through advanced information and communication technologies on the basis of lessons learned from our experiences. As important lessons, authors explained key issues associated with automation, man-machine interface, operator support systems, and procedures. Upon this investigation, we outlined the concept and technical factors to develop advanced automation, operation and maintenance support systems, and computer-based procedures using wired/wireless technology. It should be noted that the ultimate responsibility of nuclear safety obviously belongs to humans not to machines. Therefore, safety culture including education and training, which is a kind of organizational factor, should be emphasized as well. In regard to safety culture for human error reduction, several issues that we are facing these days were described. We expect the ideas of the advanced MMIS proposed in this paper to lead in the future direction of related researches and finally supplement the safety of NPPs.
Recent advances in the kinetics of oxygen reduction
Adzic, R.
1996-07-01
Oxygen reduction is considered an important electrocatalytic reaction; the most notable need remains improvement of the catalytic activity of existing metal electrocatalysts and development of new ones. A review is given of new advances in the understanding of reaction kinetics and improvements of the electrocatalytic properties of some surfaces, with focus on recent studies of relationship of the surface properties to its activity and reaction kinetics. The urgent need is to improve catalytic activity of Pt and synthesize new, possibly non- noble metal catalysts. New experimental techniques for obtaining new level of information include various {ital in situ} spectroscopies and scanning probes, some involving synchrotron radiation. 138 refs, 18 figs, 2 tabs.
Active Vibration Reduction of the Advanced Stirling Convertor
Wilson, Scott D.; Metscher, Jonathan F.; Schifer, Nicholas A.
2016-01-01
Stirling Radioisotope Power Systems (RPS) are being developed as an option to provide power on future space science missions where robotic spacecraft will orbit, flyby, land or rove. A Stirling Radioisotope Generator (SRG) could offer space missions a more efficient power system that uses one fourth of the nuclear fuel and decreases the thermal footprint compared to the current state of the art. The Stirling Cycle Technology Development (SCTD) Project is funded by the RPS Program to developing Stirling-based subsystems, including convertors and controller maturation efforts that have resulted in high fidelity hardware like the Advanced Stirling Radioisotope Generator (ASRG), Advanced Stirling Convertor (ASC), and ASC Controller Unit (ACU). The SCTD Project also performs research to develop less mature technologies with a wide variety of objectives, including increasing temperature capability to enable new environments, improving system reliability or fault tolerance, reducing mass or size, and developing advanced concepts that are mission enabling. Active vibration reduction systems (AVRS), or "balancers", have historically been developed and characterized to provide fault tolerance for generator designs that incorporate dual-opposed Stirling convertors or enable single convertor, or small RPS, missions. Balancers reduce the dynamic disturbance forces created by the power piston and displacer internal moving components of a single operating convertor to meet spacecraft requirements for induced disturbance force. To improve fault tolerance for dual-opposed configurations and enable single convertor configurations, a breadboard AVRS was implemented on the Advanced Stirling Convertor (ASC). The AVRS included a linear motor, a motor mount, and a closed-loop controller able to balance out the transmitted peak dynamic disturbance using acceleration feedback. Test objectives included quantifying power and mass penalty and reduction in transmitted force over a range of ASC
Perchlorate reduction by the sulfite/ultraviolet light advanced reduction process
Vellanki, Bhanu Prakash, E-mail: bhanuprakashvellanki@gmail.com [Zachry Department of Civil Engineering, 3136 TAMU, Texas A and M University, College Station, TX 77803-3136 (United States); Batchelor, Bill, E-mail: bill-batchelor@neo.tamu.edu [Zachry Department of Civil Engineering, 3136 TAMU, Texas A and M University, College Station, TX 77803-3136 (United States)
2013-11-15
Highlights: • Perchlorate removal by sulfite/UV-L advanced reduction process documented. • Perchlorate removal efficiency increases with increasing pH and temperature. • Increasing pH results in decreasing quantum yield for sulfite loss. • An optimal sulfite concentration exists for maximum perchlorate degradation. • Satisfactory chlorine recovery was obtained with chlorate and chloride the major products. • Oxygen abstraction mechanism to reduce perchlorate proposed. -- Abstract: Advanced reduction processes (ARPs) are a new class of water treatment processes that combine activation methods and reducing agents to form highly reactive reducing radicals that degrade oxidized contaminants. The combination of sulfite with low-pressure ultraviolet light (UV-L) is the most effective ARP tested to date. In this study, batch kinetic experiments were conducted to characterize the kinetics of perchlorate destruction by the sulfite/UV-L ARP. Experimental variables were pH, sulfite concentration, temperature and UV-L irradiance. The rate of perchlorate degradation by sulfite/UV-L increases with increasing pH and temperature and increases with increasing sulfite concentration to a maximum and then decreases due to lack of mixing within the reactor system used. Efficiency of perchlorate degradation was measured as a quantum yield and was observed to decrease with increasing sulfite concentration. The ultimate product of perchlorate degradation by the sulfite/UV-L ARP is chloride, but chlorate was detected as an intermediate.
Low cost biological lung volume reduction therapy for advanced emphysema
Bakeer M
2016-08-01
Full Text Available Mostafa Bakeer,1 Taha Taha Abdelgawad,1 Raed El-Metwaly,1 Ahmed El-Morsi,1 Mohammad Khairy El-Badrawy,1 Solafa El-Sharawy2 1Chest Medicine Department, 2Clinical Pathology Department, Faculty of Medicine, Mansoura University, Mansoura, Egypt Background: Bronchoscopic lung volume reduction (BLVR, using biological agents, is one of the new alternatives to lung volume reduction surgery.Objectives: To evaluate efficacy and safety of biological BLVR using low cost agents including autologous blood and fibrin glue.Methods: Enrolled patients were divided into two groups: group A (seven patients in which autologous blood was used and group B (eight patients in which fibrin glue was used. The agents were injected through a triple lumen balloon catheter via fiberoptic bronchoscope. Changes in high resolution computerized tomography (HRCT volumetry, pulmonary function tests, symptoms, and exercise capacity were evaluated at 12 weeks postprocedure as well as for complications.Results: In group A, at 12 weeks postprocedure, there was significant improvement in the mean value of HRCT volumetry and residual volume/total lung capacity (% predicted (P-value: <0.001 and 0.038, respectively. In group B, there was significant improvement in the mean value of HRCT volumetry and (residual volume/total lung capacity % predicted (P-value: 0.005 and 0.004, respectively. All patients tolerated the procedure with no mortality.Conclusion: BLVR using autologous blood and locally prepared fibrin glue is a promising method for therapy of advanced emphysema in term of efficacy, safety as well as cost effectiveness. Keywords: BLVR, bronchoscopy, COPD, interventional pulmonology
Wenner, Michael T.
Obtaining the solution to the linear Boltzmann equation is often is often a daunting task. The time-independent form is an equation of six independent variables which cannot be solved analytically in all but some special problems. Instead, numerical approaches have been devised. This work focuses on improving Monte Carlo methods for its solution in eigenvalue form. First, a statistical method of stationarity detection called the KPSS test adapted as a Monte Carlo eigenvalue source convergence test. The KPSS test analyzes the source center of mass series which was chosen since it should be indicative of overall source behavior, and is physically easy to understand. A source center of mass plot alone serves as a good visual source convergence diagnostic. The KPSS test and three different information theoretic diagnostics were implemented into the well known KENOV.a code inside of the SCALE (version 5) code package from Oak Ridge National Laboratory and compared through analysis of a simple problem and several difficult source convergence benchmarks. Results showed that the KPSS test can add to the overall confidence by identifying more problematic simulations than without its usage. Not only this, the source center of mass information on hand visually aids in the understanding of the problem physics. The second major focus of this dissertation concerned variance reduction methodologies for Monte Carlo eigenvalue problems. The CADIS methodology, based on importance sampling, was adapted to the eigenvalue problems. It was shown that the straight adaption of importance sampling can provide a significant variance reduction in determination of keff (in cases studied up to 30%?). A modified version of this methodology was developed which utilizes independent deterministic importance simulations. In this new methodology, each particle is simulated multiple times, once to every other discretized source region utilizing the importance for that region only. Since each particle
Advanced Acoustic Blankets for Improved Aircraft Interior Noise Reduction Project
National Aeronautics and Space Administration — In this project advanced acoustic blankets for improved low frequency interior noise control in aircraft will be developed and demonstrated. The improved performance...
Advanced Acoustic Blankets for Improved Aircraft Interior Noise Reduction Project
National Aeronautics and Space Administration — The objective of the proposed Phase II research effort is to develop heterogeneous (HG) blankets for improved sound reduction in aircraft structures. Phase I...
Advances in reduction techniques for tire contact problems
Noor, Ahmed K.
1995-08-01
Some recent developments in reduction techniques, as applied to predicting the tire contact response and evaluating the sensitivity coefficients of the different response quantities, are reviewed. The sensitivity coefficients measure the sensitivity of the contact response to variations in the geometric and material parameters of the tire. The tire is modeled using a two-dimensional laminated anisotropic shell theory with the effects of variation in geometric and material parameters, transverse shear deformation, and geometric nonlinearities included. The contact conditions are incorporated into the formulation by using a perturbed Lagrangian approach with the fundamental unknowns consisting of the stress resultants, the generalized displacements, and the Lagrange multipliers associated with the contact conditions. The elemental arrays are obtained by using a modified two-field, mixed variational principle. For the application of reduction techniques, the tire finite element model is partitioned into two regions. The first region consists of the nodes that are likely to come in contact with the pavement, and the second region includes all the remaining nodes. The reduction technique is used to significantly reduce the degrees of freedom in the second region. The effectiveness of the computational procedure is demonstrated by a numerical example of the frictionless contact response of the space shuttle nose-gear tire, inflated and pressed against a rigid flat surface. Also, the research topics which have high potential for enhancing the effectiveness of reduction techniques are outlined.
Sampson, Andrew Joseph
This dissertation describes the application of two principled variance reduction strategies to increase the efficiency for two applications within medical physics. The first, called correlated Monte Carlo (CMC) applies to patient-specific, permanent-seed brachytherapy (PSB) dose calculations. The second, called adjoint-biased forward Monte Carlo (ABFMC), is used to compute cone-beam computed tomography (CBCT) scatter projections. CMC was applied for two PSB cases: a clinical post-implant prostate, and a breast with a simulated lumpectomy cavity. CMC computes the dose difference, DeltaD, between the highly correlated dose computing homogeneous and heterogeneous geometries. The particle transport in the heterogeneous geometry assumed a purely homogeneous environment, and altered particle weights accounted for bias. Average gains of 37 to 60 are reported from using CMC, relative to un-correlated Monte Carlo (UMC) calculations, for the prostate and breast CTV's, respectively. To further increase the efficiency up to 1500 fold above UMC, an approximation called interpolated correlated Monte Carlo (ICMC) was applied. ICMC computes DeltaD using CMC on a low-resolution (LR) spatial grid followed by interpolation to a high-resolution (HR) voxel grid followed. The interpolated, HR DeltaD is then summed with a HR, pre-computed, homogeneous dose map. ICMC computes an approximate, but accurate, HR heterogeneous dose distribution from LR MC calculations achieving an average 2% standard deviation within the prostate and breast CTV's in 1.1 sec and 0.39 sec, respectively. Accuracy for 80% of the voxels using ICMC is within 3% for anatomically realistic geometries. Second, for CBCT scatter projections, ABFMC was implemented via weight windowing using a solution to the adjoint Boltzmann transport equation computed either via the discrete ordinates method (DOM), or a MC implemented forward-adjoint importance generator (FAIG). ABFMC, implemented via DOM or FAIG, was tested for a
Targeted reduction of advanced glycation improves renal function in obesity
Harcourt, Brooke E; Sourris, Karly C; Coughlan, Melinda T
2011-01-01
Obesity is highly prevalent in Western populations and is considered a risk factor for the development of renal impairment. Interventions that reduce the tissue burden of advanced glycation end-products (AGEs) have shown promise in stemming the progression of chronic disease. Here we tested...... function and an inflammatory profile (monocyte chemoattractant protein-1 (MCP-1) and macrophage migration inhibitory factor (MIF)) were improved following the low-AGE diet. Mechanisms of advanced glycation-related renal damage were investigated in a mouse model of obesity using the AGE...... if treatments that lower tissue AGE burden in patients and mice would improve obesity-related renal dysfunction. Overweight and obese individuals (body mass index (BMI) 26-39¿kg/m(2)) were recruited to a randomized, crossover clinical trial involving 2 weeks each on a low- and a high-AGE-containing diet. Renal...
Recent advancements in mechanical reduction methods: particulate systems.
Leleux, Jardin; Williams, Robert O
2014-03-01
The screening of new active pharmaceutical ingredients (APIs) has become more streamlined and as a result the number of new drugs in the pipeline is steadily increasing. However, a major limiting factor of new API approval and market introduction is the low solubility associated with a large percentage of these new drugs. While many modification strategies have been studied to improve solubility such as salt formation and addition of cosolvents, most provide only marginal success and have severe disadvantages. One of the most successful methods to date is the mechanical reduction of drug particle size, inherently increasing the surface area of the particles and, as described by the Noyes-Whitney equation, the dissolution rate. Drug micronization has been the gold standard to achieve these improvements; however, the extremely low solubility of some new chemical entities is not significantly affected by size reduction in this range. A reduction in size to the nanometric scale is necessary. Bottom-up and top-down techniques are utilized to produce drug crystals in this size range; however, as discussed in this review, top-down approaches have provided greater enhancements in drug usability on the industrial scale. The six FDA approved products that all exploit top-down approaches confirm this. In this review, the advantages and disadvantages of both approaches will be discussed in addition to specific top-down techniques and the improvements they contribute to the pharmaceutical field.
Recent Advances in Electrical Resistance Preheating of Aluminum Reduction Cells
Ali, Mohamed Mahmoud; Kvande, Halvor
2017-02-01
There are two mainpreheating methods that are used nowadays for aluminum reduction cells. One is based on electrical resistance preheating with a thin bed of small coke and/or graphite particles between the anodes and the cathode carbon blocks. The other is flame preheating, where two or more gas or oil burners are used. Electrical resistance preheating is the oldest method, but is still frequently used by different aluminum producers. Many improvements have been made to this method by different companies over the last decade. In this paper, important points pertaining to the preparation and preheating of these cells, as well as measurements made during the preheating process and evaluation of the performance of the preheating, are illustrated. The preheating times of these cells were found to be between 36 h and 96 h for cell currents between 176 kA and 406 kA, while the resistance bed thickness was between 13 mm and 60 mm. The average cathode surface temperature at the end of the preheating was usually between 800°C and 950°C. The effect of the preheating methods on cell life is unclear and no quantifiable conclusions can be drawn. Some works carried out in the mathematical modeling area are also discussed. It is concluded that there is a need for more studies with real situations for preheated cells on the basis of actual measurements. The expected development in electrical resistance preheating of aluminum reduction cells is also summarized.
Update on Risk Reduction Activities for a Liquid Advanced Booster for NASA's Space Launch System
Crocker, Andy; Greene, William D.
2017-01-01
Goals of NASA's Advanced Booster Engineering Demonstration and/or Risk Reduction (ABEDRR) are to: (1) Reduce risks leading to an affordable Advanced Booster that meets the evolved capabilities of SLS. (2) Enable competition by mitigating targeted Advanced Booster risks to enhance SLS affordability. SLS Block 1 vehicle is being designed to carry 70 mT to LEO: (1) Uses two five-segment solid rocket boosters (SRBs) similar to the boosters that helped power the space shuttle to orbit. Evolved 130 mT payload class rocket requires an advanced booster with more thrust than any existing U.S. liquid-or solid-fueled boosters
Blazquez, J.; Montalvo, C.; Balbas, M.; Garcia-Berrocal, A.
2011-07-01
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.
Byrne, Vicky; Orndoff, Evelyne; Poritz, Darwin; Schlesinger, Thilini
2013-01-01
All human space missions require significant logistical mass and volume that will become an excessive burden for long duration missions beyond low Earth orbit. The goal of the Advanced Exploration Systems (AES) Logistics Reduction & Repurposing (LRR) project is to bring new ideas and technologies that will enable human presence in farther regions of space. The LRR project has five tasks: 1) Advanced Clothing System (ACS) to reduce clothing mass and volume, 2) Logistics to Living (L2L) to repurpose existing cargo, 3) Heat Melt Compactor (HMC) to reprocess materials in space, 4) Trash to Gas (TTG) to extract useful gases from trash, and 5) Systems Engineering and Integration (SE&I) to integrate these logistical components. The current International Space Station (ISS) crew wardrobe has already evolved not only to reduce some of the logistical burden but also to address crew preference. The ACS task is to find ways to further reduce this logistical burden while examining human response to different types of clothes. The ACS task has been broken into a series of studies on length of wear of various garments: 1) three small studies conducted through other NASA projects (MMSEV, DSH, HI-SEAS) focusing on length of wear of garments treated with an antimicrobial finish; 2) a ground study, which is the subject of this report, addressing both length of wear and subject perception of various types of garments worn during aerobic exercise; and 3) an ISS study replicating the ground study, and including every day clothing to collect information on perception in reduced gravity in which humans experience physiological changes. The goal of the ground study is first to measure how long people can wear the same exercise garment, depending on the type of fabric and the presence of antimicrobial treatment, and second to learn why. Human factors considerations included in the study consist of the Institutional Review Board approval, test protocol and participants' training, and a web
Downside Variance Risk Premium
Feunou, Bruno; Jahan-Parvar, Mohammad R.; Okou, Cédric
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...
WANG Zhi-hua; ZHOU Jun-hu; ZHANG Yan-wei; LU Zhi-min; FAN Jian-ren; CEN Ke-fa
2005-01-01
Pulverized coal reburning, ammonia injection and advanced reburning in a pilot scale drop tube furnace were investigated. Premix of petroleum gas, air and NH3 were burned in a porous gas burner to generate the needed flue gas. Four kinds of pulverized coal were fed as reburning fuel at constant rate of 1g/min. The coal reburning process parameters including 15%～25% reburn heat input, temperature range from 1100 ℃ to 1400 ℃ and also the carbon in fly ash, coal fineness, reburn zone stoichiometric ratio, etc. were investigated. On the condition of 25% reburn heat input, maximum of 47% NO reduction with Yanzhou coal was obtained by pure coal reburning. Optimal temperature for reburning is about 1300 ℃ and fuel-rich stoichiometric ratio is essential; coal fineness can slightly enhance the reburning ability. The temperature window for ammonia injection is about 700 ℃～1100 ℃. CO can improve the NH3 ability at lower temperature. During advanced reburning, 72.9% NO reduction was measured. To achieve more than 70% NO reduction, Selective Non-catalytic NOx Reduction (SNCR) should need NH3/NO stoichiometric ratio larger than 5, while advanced reburning only uses common dose of ammonia as in conventional SNCR technology. Mechanism study shows the oxidization of CO can improve the decomposition of H2O, which will rich the radical pools igniting the whole reactions at lower temperatures.
王宏健; 王晶; 曲丽萍; 刘振业
2013-01-01
The FastSLAM algorithm based on variance reduction of particle weight was presented in order to solve the decrease of estimated accuracy of AUV ( autonomous underwater vehicle) , location due to particles degeneracy and the sample impoverishment as a result of resampling in standard FastSLAM. The variance of particle weight was decreased by generating an adaptive exponential fading factor, which came from the thought of cooling function in simulated annealing. The effective particle number was increased by application of FastSLAM based on simulated annealing variance reduction in navigation and localization of AUV. Resampling in standard FastSLAM was replaced with it. Establish the kinematic model of AUV, feature model and measurement models of sensors, and make feature extraction with Hough transform. The experiment of AUV's simultaneous localization and mapping u-sing simulated annealing variance reduction FastSLAM was based on trial data. The results indicate that the method described in this paper maintains the diversity of the particles, however, weakens the degeneracy, while at the same time enhances the accuracy stability of AUV's navigation and localization system.%由于标准FastSLAM中存在粒子退化及重采样引起的粒子贫化,导致自主水下航行器(AUV)位置估计精度严重下降的问题,提出了一种基于粒子权值方差缩减的FastSLAM算法.利用模拟退火的降温函数产生自适应指数渐消因子来降低粒子权值的方差,进而增加有效粒子数,以此取代标准FastSLAM中的重采样步骤.建立AUV的运动学模型、特征模型及传感器的测量模型,通过霍夫变换进行特征提取.利用方差缩减FastSLAM算法,基于海试数据进行了AUV同步定位与构图仿真试验,结果表明所提方法能够保证粒子的多样性,并且降低粒子的退化程度,提高了AUV定位与地图构建系统的准确性及稳定性.
ZAYAS Pérez Teresa; GEISSLER Gunther; HERNANDEZ Fernando
2007-01-01
The removal of the natural organic matter present in coffee processing wastewater through chemical coagulation-flocculatio and advanced oxidation processes(AOP)had been studied.The effectiveness of the removal of natural organic matter using commercial flocculants and UV/H202,UVO3 and UV/H-H202/O3 processes was determined under acidic conditions.For each of these processes,different operational conditions were explored to optimize the treatment efficiency of the coffee wastewater.Coffee wastewater is characterized by a high chemical oxygen demand(COD)and low total suspended solids.The outcomes of coffee wastewater reeatment using coagulation-flocculation and photodegradation processes were assessed in terms of reduction of COD,color,and turbidity.It was found that a reductiOn in COD of 67%could be realized when the coffee wastewater was treated by chemical coagulation-flocculatlon witll lime and coagulant T-1.When coffee wastewater was treated by coagulation-flocculation in combination with UV/H202,a COD reduction of 86%was achieved,although only after prolonged UV irradiation.Of the three advanced oxidation processes considered,UV/H202,uv/03 and UV/H202/03,we found that the treatment with UV/H2O2/O3 was the most effective,with an efficiency of color,turbidity and further COD removal of 87%,when applied to the flocculated coffee wastewater.
Regulatory Risk Reduction for Advanced Reactor Technologies – FY2016 Status and Work Plan Summary
Moe, Wayne Leland [Idaho National Lab. (INL), Idaho Falls, ID (United States)
2016-08-01
Millions of public and private sector dollars have been invested over recent decades to realize greater efficiency, reliability, and the inherent and passive safety offered by advanced nuclear reactor technologies. However, a major challenge in experiencing those benefits resides in the existing U.S. regulatory framework. This framework governs all commercial nuclear plant construction, operations, and safety issues and is highly large light water reactor (LWR) technology centric. The framework must be modernized to effectively deal with non-LWR advanced designs if those designs are to become part of the U.S energy supply. The U.S. Department of Energy’s (DOE) Advanced Reactor Technologies (ART) Regulatory Risk Reduction (RRR) initiative, managed by the Regulatory Affairs Department at the Idaho National Laboratory (INL), is establishing a capability that can systematically retire extraneous licensing risks associated with regulatory framework incompatibilities. This capability proposes to rely heavily on the perspectives of the affected regulated community (i.e., commercial advanced reactor designers/vendors and prospective owner/operators) yet remain tuned to assuring public safety and acceptability by regulators responsible for license issuance. The extent to which broad industry perspectives are being incorporated into the proposed framework makes this initiative unique and of potential benefit to all future domestic non-LWR applicants
Rybnikova, V; Usman, M; Hanna, K
2016-09-01
Although the chemical reduction and advanced oxidation processes have been widely used individually, very few studies have assessed the combined reduction/oxidation approach for soil remediation. In the present study, experiments were performed in spiked sand and historically contaminated soil by using four synthetic nanoparticles (Fe(0), Fe/Ni, Fe3O4, Fe3 - x Ni x O4). These nanoparticles were tested firstly for reductive transformation of polychlorinated biphenyls (PCBs) and then employed as catalysts to promote chemical oxidation reactions (H2O2 or persulfate). Obtained results indicated that bimetallic nanoparticles Fe/Ni showed the highest efficiency in reduction of PCB28 and PCB118 in spiked sand (97 and 79 %, respectively), whereas magnetite (Fe3O4) exhibited a high catalytic stability during the combined reduction/oxidation approach. In chemical oxidation, persulfate showed higher PCB degradation extent than hydrogen peroxide. As expected, the degradation efficiency was found to be limited in historically contaminated soil, where only Fe(0) and Fe/Ni particles exhibited reductive capability towards PCBs (13 and 18 %). In oxidation step, the highest degradation extents were obtained in presence of Fe(0) and Fe/Ni (18-19 %). The increase in particle and oxidant doses improved the efficiency of treatment, but overall degradation extents did not exceed 30 %, suggesting that only a small part of PCBs in soil was available for reaction with catalyst and/or oxidant. The use of organic solvent or cyclodextrin to improve the PCB availability in soil did not enhance degradation efficiency, underscoring the strong impact of soil matrix. Moreover, a better PCB degradation was observed in sand spiked with extractable organic matter separated from contaminated soil. In contrast to fractions with higher particle size (250-500 and oxidation reactions in soils and understand the impact of soil properties on remediation performance.
Moussavi, Gholamreza, E-mail: moussavi@modares.ac.ir; Shekoohiyan, Sakine
2016-11-15
Highlights: • Simultaneous advanced oxidation and reduction processes were explored in VUV system. • Complete reduction of nitrate to N{sub 2} was achieved at the presence of acetaminophen. • Complete degradation of acetaminophen was achieved at the presence of nitrate. • Over 95% of acetaminophen was mineralized in the VUV photoreactor. • VUV is a chemical-less advanced process for treating water emerging contaminants. - Abstract: This work was aimed at investigating the performance of the continuous-flow VUV photoreactor as a novel chemical-less advanced process for simultaneously oxidizing acetaminophen (ACT) as a model of pharmaceuticals and reducing nitrate in a single reactor. Solution pH was an important parameter affecting the performance of VUV; the highest ACT oxidation and nitrate reduction attained at solution pH between 6 and 8. The ACT was oxidized mainly by HO· while the aqueous electrons were the main working agents in the reduction of nitrate. The performance of VUV photoreactor improved with the increase of hydraulic retention time (HRT); the complete degradation of ACT and ∼99% reduction of nitrate with 100% N{sub 2} selectivity achieved at HRT of 80 min. The VUV effluent concentrations of nitrite and ammonium at HRT of 80 min were below the drinking water standards. The real water sample contaminated with the ACT and nitrate was efficiently treated in the VUV photoreactor. Therefore, the VUV photoreactor is a chemical-less advanced process in which both advanced oxidation and advanced reduction reactions are accomplished. This unique feature possesses VUV photoreactor as a promising method of treating water contaminated with both pharmaceutical and nitrate.
Yeo, Seung-Gu [Center for Colorectal Cancer, Research Institute and Hospital, National Cancer Center, Goyang (Korea, Republic of); Department of Radiation Oncology, Soonchunhyang University College of Medicine, Cheonan (Korea, Republic of); Kim, Dae Yong, E-mail: radiopiakim@hanmail.net [Center for Colorectal Cancer, Research Institute and Hospital, National Cancer Center, Goyang (Korea, Republic of); Park, Ji Won; Oh, Jae Hwan; Kim, Sun Young; Chang, Hee Jin; Kim, Tae Hyun; Kim, Byung Chang; Sohn, Dae Kyung; Kim, Min Ju [Center for Colorectal Cancer, Research Institute and Hospital, National Cancer Center, Goyang (Korea, Republic of)
2012-02-01
Purpose: To investigate the prognostic significance of tumor volume reduction rate (TVRR) after preoperative chemoradiotherapy (CRT) in locally advanced rectal cancer (LARC). Methods and Materials: In total, 430 primary LARC (cT3-4) patients who were treated with preoperative CRT and curative radical surgery between May 2002 and March 2008 were analyzed retrospectively. Pre- and post-CRT tumor volumes were measured using three-dimensional region-of-interest MR volumetry. Tumor volume reduction rate was determined using the equation TVRR (%) = (pre-CRT tumor volume - post-CRT tumor volume) Multiplication-Sign 100/pre-CRT tumor volume. The median follow-up period was 64 months (range, 27-99 months) for survivors. Endpoints were disease-free survival (DFS) and overall survival (OS). Results: The median TVRR was 70.2% (mean, 64.7% {+-} 22.6%; range, 0-100%). Downstaging (ypT0-2N0M0) occurred in 183 patients (42.6%). The 5-year DFS and OS rates were 77.7% and 86.3%, respectively. In the analysis that included pre-CRT and post-CRT tumor volumes and TVRR as continuous variables, only TVRR was an independent prognostic factor. Tumor volume reduction rate was categorized according to a cutoff value of 45% and included with clinicopathologic factors in the multivariate analysis; ypN status, circumferential resection margin, and TVRR were significant prognostic factors for both DFS and OS. Conclusions: Tumor volume reduction rate was a significant prognostic factor in LARC patients receiving preoperative CRT. Tumor volume reduction rate data may be useful for tailoring surgery and postoperative adjuvant therapy after preoperative CRT.
Update on Risk Reduction Activities for a Liquid Advanced Booster for NASA's Space Launch System
Crocker, Andrew M.; Doering, Kimberly B; Meadows, Robert G.; Lariviere, Brian W.; Graham, Jerry B.
2015-01-01
The stated goals of NASA's Research Announcement for the Space Launch System (SLS) Advanced Booster Engineering Demonstration and/or Risk Reduction (ABEDRR) are to reduce risks leading to an affordable Advanced Booster that meets the evolved capabilities of SLS; and enable competition by mitigating targeted Advanced Booster risks to enhance SLS affordability. Dynetics, Inc. and Aerojet Rocketdyne (AR) formed a team to offer a wide-ranging set of risk reduction activities and full-scale, system-level demonstrations that support NASA's ABEDRR goals. For NASA's SLS ABEDRR procurement, Dynetics and AR formed a team to offer a series of full-scale risk mitigation hardware demonstrations for an affordable booster approach that meets the evolved capabilities of the SLS. To establish a basis for the risk reduction activities, the Dynetics Team developed a booster design that takes advantage of the flight-proven Apollo-Saturn F-1. Using NASA's vehicle assumptions for the SLS Block 2, a two-engine, F-1-based booster design delivers 150 mT (331 klbm) payload to LEO, 20 mT (44 klbm) above NASA's requirements. This enables a low-cost, robust approach to structural design. During the ABEDRR effort, the Dynetics Team has modified proven Apollo-Saturn components and subsystems to improve affordability and reliability (e.g., reduce parts counts, touch labor, or use lower cost manufacturing processes and materials). The team has built hardware to validate production costs and completed tests to demonstrate it can meet performance requirements. State-of-the-art manufacturing and processing techniques have been applied to the heritage F-1, resulting in a low recurring cost engine while retaining the benefits of Apollo-era experience. NASA test facilities have been used to perform low-cost risk-reduction engine testing. In early 2014, NASA and the Dynetics Team agreed to move additional large liquid oxygen/kerosene engine work under Dynetics' ABEDRR contract. Also led by AR, the
Briggs, J. L.; Younger, A. F.
1980-06-02
A materials selection test program was conducted to characterize optimum interior surface coatings for an advanced size reduction facility. The equipment to be processed by this facility consists of stainless steel apparatus (e.g., glove boxes, piping, and tanks) used for the chemical recovery of plutonium. Test results showed that a primary requirement for a satisfactory coating is ease of decontamination. A closely related concern is the resistance of paint films to nitric acid - plutonium environments. A vinyl copolymer base paint was the only coating, of eight paints tested, with properties that permitted satisfactory decontamination of plutonium and also performed equal to or better than the other paints in the chemical resistance, radiation stability, and impact tests.
DEMONSTRATION OF AN ADVANCED INTEGRATED CONTROL SYSTEM FOR SIMULTANEOUS EMISSIONS REDUCTION
Suzanne Shea; Randhir Sehgal; Ilga Celmins; Andrew Maxson
2002-02-01
The primary objective of the project titled ''Demonstration of an Advanced Integrated Control System for Simultaneous Emissions Reduction'' was to demonstrate at proof-of-concept scale the use of an online software package, the ''Plant Environmental and Cost Optimization System'' (PECOS), to optimize the operation of coal-fired power plants by economically controlling all emissions simultaneously. It combines physical models, neural networks, and fuzzy logic control to provide both optimal least-cost boiler setpoints to the boiler operators in the control room, as well as optimal coal blending recommendations designed to reduce fuel costs and fuel-related derates. The goal of the project was to demonstrate that use of PECOS would enable coal-fired power plants to make more economic use of U.S. coals while reducing emissions.
Advancing Development and Greenhouse Gas Reductions in Vietnam's Wind Sector
Bilello, D.; Katz, J.; Esterly, S.; Ogonowski, M.
2014-09-01
Clean energy development is a key component of Vietnam's Green Growth Strategy, which establishes a target to reduce greenhouse gas (GHG) emissions from domestic energy activities by 20-30 percent by 2030 relative to a business-as-usual scenario. Vietnam has significant wind energy resources, which, if developed, could help the country reach this target while providing ancillary economic, social, and environmental benefits. Given Vietnam's ambitious clean energy goals and the relatively nascent state of wind energy development in the country, this paper seeks to fulfill two primary objectives: to distill timely and useful information to provincial-level planners, analysts, and project developers as they evaluate opportunities to develop local wind resources; and, to provide insights to policymakers on how coordinated efforts may help advance large-scale wind development, deliver near-term GHG emission reductions, and promote national objectives in the context of a low emission development framework.
Conversations across Meaning Variance
Cordero, Alberto
2013-01-01
Progressive interpretations of scientific theories have long been denounced as naive, because of the inescapability of meaning variance. The charge reportedly applies to recent realist moves that focus on theory-parts rather than whole theories. This paper considers the question of what "theory-parts" of epistemic significance (if any) relevantly…
Treatment of Aqueous Bromate by Superparamagnetic BiOCl-Mediated Advanced Reduction Process
Xiaowei Liu
2017-05-01
Full Text Available Bromate ( BrO 3 − contamination in drinking water is a growing concern. Advanced reduction processes (ARPs are reportedly promising in relieving this concern. In this work, UV/superparamagnetic BiOCl (BiOCl loaded onto superparamagnetic hydroxyapatite assisted with small molecule carboxylic acid (formate, citrate, and acetate, a carboxyl anion radical ( CO 2 • − -based ARP, was proposed to eliminate aqueous BrO 3 − . Formate and citrate were found to be ideal CO 2 • − precursor, and the latter was found to be safe for practical use. BrO 3 − (10 μg·L−1, WHO guideline for drinking water can be completely degraded within 3 min under oxygen-free conditions. In this process, BrO 3 − degradation was realized by the reduction of CO 2 • − (major role and formyloxyl radical (minor role in bulk solution. The formation mechanism of radicals and the transformation pathway of BrO 3 − were proposed based on data on electron paramagnetic resonance monitoring, competitive kinetics, and degradation product analysis. The process provided a sustainable decontamination performance (<5% deterioration for 10 cycles and appeared to be more resistant to common electron acceptors (O2, NO 3 − , and Fe3+ than hydrated electron based-ARPs. Phosphate based-superparamagnetic hydroxyapatite, used to support BiOCl in this work, was believed to be applicable for resolving the recycling problem of other metal-containing catalyst.
Christelle Pau Ping Wong
2015-10-01
Full Text Available Textile industries consume large volumes of water for dye processing, leading to undesirable toxic dyes in water bodies. Dyestuffs are harmful to human health and aquatic life, and such illnesses as cholera, dysentery, hepatitis A, and hinder the photosynthetic activity of aquatic plants. To overcome this environmental problem, the advanced oxidation process is a promising technique to mineralize a wide range of dyes in water systems. In this work, reduced graphene oxide (rGO was prepared via an advanced chemical reduction route, and its photocatalytic activity was tested by photodegrading Reactive Black 5 (RB5 dye in aqueous solution. rGO was synthesized by dispersing the graphite oxide into the water to form a graphene oxide (GO solution followed by the addition of hydrazine. Graphite oxide was prepared using a modified Hummers’ method by using potassium permanganate and concentrated sulphuric acid. The resulted rGO nanoparticles were characterized using ultraviolet-visible spectrophotometry (UV-Vis, X-ray powder diffraction (XRD, Raman, and Scanning Electron Microscopy (SEM to further investigate their chemical properties. A characteristic peak of rGO-48 h (275 cm−1 was observed in the UV spectrum. Further, the appearance of a broad peak (002, centred at 2θ = 24.1°, in XRD showing that graphene oxide was reduced to rGO. Based on our results, it was found that the resulted rGO-48 h nanoparticles achieved 49% photodecolorization of RB5 under UV irradiation at pH 3 in 60 min. This was attributed to the high and efficient electron transport behaviors of rGO between aromatic regions of rGO and RB5 molecules.
Zhang, Yingying; Zhuang, Yao; Geng, Jinju; Ren, Hongqiang; Xu, Ke; Ding, Lili
2016-04-15
This study investigated the reduction of antibiotic resistance genes (ARGs), intI1 and 16S rRNA genes, by advanced oxidation processes (AOPs), namely Fenton oxidation (Fe(2+)/H2O2) and UV/H2O2 process. The ARGs include sul1, tetX, and tetG from municipal wastewater effluent. The results indicated that the Fenton oxidation and UV/H2O2 process could reduce selected ARGs effectively. Oxidation by the Fenton process was slightly better than that of the UV/H2O2 method. Particularly, for the Fenton oxidation, under the optimal condition wherein Fe(2+)/H2O2 had a molar ratio of 0.1 and a H2O2 concentration of 0.01molL(-1) with a pH of 3.0 and reaction time of 2h, 2.58-3.79 logs of target genes were removed. Under the initial effluent pH condition (pH=7.0), the removal was 2.26-3.35 logs. For the UV/H2O2 process, when the pH was 3.5 with a H2O2 concentration of 0.01molL(-1) accompanied by 30min of UV irradiation, all ARGs could achieve a reduction of 2.8-3.5 logs, and 1.55-2.32 logs at a pH of 7.0. The Fenton oxidation and UV/H2O2 process followed the first-order reaction kinetic model. The removal of target genes was affected by many parameters, including initial Fe(2+)/H2O2 molar ratios, H2O2 concentration, solution pH, and reaction time. Among these factors, reagent concentrations and pH values are the most important factors during AOPs.
储真真; 陈历宏; 陈信义
2013-01-01
笔者依据原发性肝癌不同治疗阶段(即肝癌中晚期、肝癌介入治疗后、肝癌放疗后)的不同证候特点,运用六味地黄丸变方(柴芍地黄丸、知柏地黄丸、杞菊地黄丸、芪麦地黄丸、归芍地黄丸等),分别对其进行治疗.阐述了不同治疗阶段的证候特点和治疗方法,并以“案例”形式,通过“按语”对不同阶段的治疗用药思路进行解释,介绍六味地黄丸变方在中晚期原发性肝癌治疗中的应用、治疗经验,并概括介绍了中药治疗肝癌的配伍要点和体会.其自拟方芪麦地黄丸治疗中晚期原发性肝癌的临床应用,为临床治疗该病提供了新的思路.%The author is flexibility in the use of Liuwei Dihuang Wan variance (Chalshao Dihuang Wan,Zhibal Dihuang Wan,Qiju Dihuang Wan,Qimai Dihuang Wan,Guishao Dihuang Wan),according to the different syndrome characteristics of different treatment stages of primary liver cancer (that are advanced stage of liver cancer,liver cancer after interventional therapy,liver cancer after radiotherapy),to carry on the treatment respectively.The writer expounds the syndrome characteristics and therapeutic methods of different treatment stages,and explains in detail the thought of treatment and medication of different treatment stages through the ‘note' in the form of ‘disease record'.The author also explains profound theories in simple language in the application and treatment experience of Liuwei Dihuang Wan variance in the treatment of advanced primary liver cancer,and briefly introduces the key points of compatibility and experience of Chinese herbal medicine in treating liver cancer.The clinical application of Qimai Dihuang Wan in the treatment of primary liver cancer provides a new approach for the clinical treatment of the disease.
Goodall, R. G.; Painter, G. W.
1975-01-01
Conceptual nacelle designs for wide-bodied and for advanced-technology transports were studied with the objective of achieving significant reductions in community noise with minimum penalties in airplane weight, cost, and in operating expense by the application of advanced composite materials to nacelle structure and sound suppression elements. Nacelle concepts using advanced liners, annular splitters, radial splitters, translating centerbody inlets, and mixed-flow nozzles were evaluated and a preferred concept selected. A preliminary design study of the selected concept, a mixed flow nacelle with extended inlet and no splitters, was conducted and the effects on noise, direct operating cost, and return on investment determined.
Zhang, Yingying; Zhuang, Yao; Geng, Jinju, E-mail: jjgeng@nju.edu.cn; Ren, Hongqiang; Xu, Ke; Ding, Lili
2016-04-15
This study investigated the reduction of antibiotic resistance genes (ARGs), intI1 and 16S rRNA genes, by advanced oxidation processes (AOPs), namely Fenton oxidation (Fe{sup 2+}/H{sub 2}O{sub 2}) and UV/H{sub 2}O{sub 2} process. The ARGs include sul1, tetX, and tetG from municipal wastewater effluent. The results indicated that the Fenton oxidation and UV/H{sub 2}O{sub 2} process could reduce selected ARGs effectively. Oxidation by the Fenton process was slightly better than that of the UV/H{sub 2}O{sub 2} method. Particularly, for the Fenton oxidation, under the optimal condition wherein Fe{sup 2+}/H{sub 2}O{sub 2} had a molar ratio of 0.1 and a H{sub 2}O{sub 2} concentration of 0.01 mol L{sup −1} with a pH of 3.0 and reaction time of 2 h, 2.58–3.79 logs of target genes were removed. Under the initial effluent pH condition (pH = 7.0), the removal was 2.26–3.35 logs. For the UV/H{sub 2}O{sub 2} process, when the pH was 3.5 with a H{sub 2}O{sub 2} concentration of 0.01 mol L{sup −1} accompanied by 30 min of UV irradiation, all ARGs could achieve a reduction of 2.8–3.5 logs, and 1.55–2.32 logs at a pH of 7.0. The Fenton oxidation and UV/H{sub 2}O{sub 2} process followed the first-order reaction kinetic model. The removal of target genes was affected by many parameters, including initial Fe{sup 2+}/H{sub 2}O{sub 2} molar ratios, H{sub 2}O{sub 2} concentration, solution pH, and reaction time. Among these factors, reagent concentrations and pH values are the most important factors during AOPs. - Highlights: • AOPs including Fenton oxidation and UV/H{sub 2}O{sub 2} process could reduce ARGs effectively. • Fenton oxidation is slightly more effective than UV/H{sub 2}O{sub 2} process in ARG reduction. • Removal of ARGs by AOPs follows the first-order reaction kinetic model. • Selected ARGs and 16S rRNA genes exhibit similar change trends during AOPs.
Kim, Min-Suk; Won, Hwa-Yeon; Jeong, Jong-Mun; Böcker, Paul; Vergaij-Huizer, Lydia; Kupers, Michiel; Jovanović, Milenko; Sochal, Inez; Ryan, Kevin; Sun, Kyu-Tae; Lim, Young-Wan; Byun, Jin-Moo; Kim, Gwang-Gon; Suh, Jung-Joon
2016-03-01
In order to optimize yield in DRAM semiconductor manufacturing for 2x nodes and beyond, the (processing induced) overlay fingerprint towards the edge of the wafer needs to be reduced. Traditionally, this is achieved by acquiring denser overlay metrology at the edge of the wafer, to feed field-by-field corrections. Although field-by-field corrections can be effective in reducing localized overlay errors, the requirement for dense metrology to determine the corrections can become a limiting factor due to a significant increase of metrology time and cost. In this study, a more cost-effective solution has been found in extending the regular correction model with an edge-specific component. This new overlay correction model can be driven by an optimized, sparser sampling especially at the wafer edge area, and also allows for a reduction of noise propagation. Lithography correction potential has been maximized, with significantly less metrology needs. Evaluations have been performed, demonstrating the benefit of edge models in terms of on-product overlay performance, as well as cell based overlay performance based on metrology-to-cell matching improvements. Performance can be increased compared to POR modeling and sampling, which can contribute to (overlay based) yield improvement. Based on advanced modeling including edge components, metrology requirements have been optimized, enabling integrated metrology which drives down overall metrology fab footprint and lithography cycle time.
Nominal analysis of "variance".
Weiss, David J
2009-08-01
Nominal responses are the natural way for people to report actions or opinions. Because nominal responses do not generate numerical data, they have been underutilized in behavioral research. On those occasions in which nominal responses are elicited, the responses are customarily aggregated over people or trials so that large-sample statistics can be employed. A new analysis is proposed that directly associates differences among responses with particular sources in factorial designs. A pair of nominal responses either matches or does not; when responses do not match, they vary. That analogue to variance is incorporated in the nominal analysis of "variance" (NANOVA) procedure, wherein the proportions of matches associated with sources play the same role as do sums of squares in an ANOVA. The NANOVA table is structured like an ANOVA table. The significance levels of the N ratios formed by comparing proportions are determined by resampling. Fictitious behavioral examples featuring independent groups and repeated measures designs are presented. A Windows program for the analysis is available.
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...
Maximum Variance Hashing via Column Generation
Lei Luo
2013-01-01
item search. Recently, a number of data-dependent methods have been developed, reflecting the great potential of learning for hashing. Inspired by the classic nonlinear dimensionality reduction algorithm—maximum variance unfolding, we propose a novel unsupervised hashing method, named maximum variance hashing, in this work. The idea is to maximize the total variance of the hash codes while preserving the local structure of the training data. To solve the derived optimization problem, we propose a column generation algorithm, which directly learns the binary-valued hash functions. We then extend it using anchor graphs to reduce the computational cost. Experiments on large-scale image datasets demonstrate that the proposed method outperforms state-of-the-art hashing methods in many cases.
Park TS
2015-07-01
Full Text Available Tai Sun Park,1 Yoonki Hong,2 Jae Seung Lee,1 Sang Young Oh,3 Sang Min Lee,3 Namkug Kim,3 Joon Beom Seo,3 Yeon-Mok Oh,1 Sang-Do Lee,1 Sei Won Lee1 1Department of Pulmonary and Critical Care Medicine and Clinical Research Center for Chronic Obstructive Airway Diseases, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea; 2Department of Internal Medicine, College of Medicine, Kangwon National University, Chuncheon, Korea; 3Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea Purpose: Endobronchial valve (EBV therapy is increasingly being seen as a therapeutic option for advanced emphysema, but its clinical utility in Asian populations, who may have different phenotypes to other ethnic populations, has not been assessed.Patients and methods: This prospective open-label single-arm clinical trial examined the clinical efficacy and the safety of EBV in 43 consecutive patients (mean age 68.4±7.5, forced expiratory volume in 1 second [FEV1] 24.5%±10.7% predicted, residual volume 208.7%±47.9% predicted with severe emphysema with complete fissure and no collateral ventilation in a tertiary referral hospital in Korea.Results: Compared to baseline, the patients exhibited significant improvements 6 months after EBV therapy in terms of FEV1 (from 0.68±0.26 L to 0.92±0.40 L; P<0.001, 6-minute walk distance (from 233.5±114.8 m to 299.6±87.5 m; P=0.012, modified Medical Research Council dyspnea scale (from 3.7±0.6 to 2.4±1.2; P<0.001, and St George’s Respiratory Questionnaire (from 65.59±13.07 to 53.76±11.40; P=0.028. Nine patients (20.9% had a tuberculosis scar, but these scars did not affect target lobe volume reduction or pneumothorax frequency. Thirteen patients had adverse events, ten (23.3% developed pneumothorax, which included one death due to tension pneumothorax.Conclusion: EBV therapy was as effective and safe in Korean
Propulsion Noise Reduction Research in the NASA Advanced Air Transport Technology Project
Van Zante, Dale; Nark, Douglas; Fernandez, Hamilton
2017-01-01
The Aircraft Noise Reduction (ANR) sub-project is focused on the generation, development, and testing of component noise reduction technologies progressing toward the NASA far term noise goals while providing associated near and mid-term benefits. The ANR sub-project has efforts in airframe noise reduction, propulsion (including fan and core) noise reduction, acoustic liner technology, and propulsion airframe aeroacoustics for candidate conventional and unconventional aircraft configurations. The current suite of propulsion specific noise research areas is reviewed along with emerging facility and measurement capabilities. In the longer term, the changes in engine and aircraft configuration will influence the suite of technologies necessary to reduce noise in next generation systems.
A Broadband Beamformer Using Controllable Constraints and Minimum Variance
Karimian-Azari, Sam; Benesty, Jacob; Jensen, Jesper Rindom
2014-01-01
The minimum variance distortionless response (MVDR) and the linearly constrained minimum variance (LCMV) beamformers are two optimal approaches in the sense of noise reduction. The LCMV beamformer can also reject interferers using linear constraints at the expense of reducing the degree of freedom...
Fixed effects analysis of variance
Fisher, Lloyd; Birnbaum, Z W; Lukacs, E
1978-01-01
Fixed Effects Analysis of Variance covers the mathematical theory of the fixed effects analysis of variance. The book discusses the theoretical ideas and some applications of the analysis of variance. The text then describes topics such as the t-test; two-sample t-test; the k-sample comparison of means (one-way analysis of variance); the balanced two-way factorial design without interaction; estimation and factorial designs; and the Latin square. Confidence sets, simultaneous confidence intervals, and multiple comparisons; orthogonal and nonorthologonal designs; and multiple regression analysi
Siemund, Roger; Loeve, A.; Westen, D. van; Stenberg, L.; Petersen, C. (Dept. of Radiology, Lund Univ., Lund (Sweden); Center for Medical Imaging and Physiology, Skaane Univ. Hospital, Lund (Sweden)), email: roger.siemund@med.lu.se; Bjoerkman-Burtscher, I. M. (Dept. of Radiology, Lund Univ., Lund (Sweden); Center for Medical Imaging and Physiology, Skaane Univ. Hospital, Lund (Sweden); Lund Univ. Bioimaging Center, Lund (Sweden))
2012-05-15
Background: Computed tomography (CT) of the brain is performed with high local doses due to high demands on low contrast resolution. Advanced algorithms for noise reduction might be able to preserve critical image information when reducing radiation dose. Purpose: To evaluate the effect of advanced noise filtering on image quality in brain CT acquired with reduced radiation dose. Material and Methods: Thirty patients referred for non-enhanced CT of the brain were examined with two helical protocols: normal dose (ND, CTDIvol 57 mGy) and low dose (LD, CTDIvol 40 mGy) implying a 30% radiation dose reduction. Images from the LD examinations were also post processed with a noise reduction software with non-linear filters (SharpView CT), creating filtered low dose images (FLD) for each patient. The three image stacks for each patient were presented side by side in randomized order. Five radiologists, blinded for dose level and filtering, ranked these three axial image stacks (ND, LD, FLD) as best to poorest (1 to 3) regarding three image quality criteria. Measurements of mean Hounsfield units (HU) and standard deviation (SD) of the HU were calculated for large region of interest in the centrum semiovale as a measure for noise. Results: Ranking results in pooled data showed that the advanced noise filtering significantly improved the image quality in FLD as compared to LD images for all tested criteria. No significant differences in image quality were found between ND examinations and FLD. However, there was a notable inter-reader spread of the ranking. SD values were 15% higher for LD as compared to ND and FLD. Conclusion: The advanced noise filtering clearly improves image quality of CT examinations of the brain. This effect can be used to significantly lower radiation dose.
Advanced airflow distribution methods for reduction of personal exposure to indoor pollutants
Cao, Guangyu; Kosonen, Risto; Melikov, Arsen
2016-01-01
The main objective of this study is to recognize possible airflow distribution methods to protect the occupants from exposure to various indoor pollutants. The fact of the increasing exposure of occupants to various indoor pollutants shows that there is an urgent need to develop advanced airflow ...... distribution methods to reduce indoor exposure to various indoor pollutants. This article presents some of the latest development of advanced airflow distribution methods to reduce indoor exposure in various types of buildings.......The main objective of this study is to recognize possible airflow distribution methods to protect the occupants from exposure to various indoor pollutants. The fact of the increasing exposure of occupants to various indoor pollutants shows that there is an urgent need to develop advanced airflow...
Statistical inference on variance components
Verdooren, L.R.
1988-01-01
In several sciences but especially in animal and plant breeding, the general mixed model with fixed and random effects plays a great role. Statistical inference on variance components means tests of hypotheses about variance components, constructing confidence intervals for them, estimating them,
Advanced RF-KO slow-extraction method for the reduction of spill ripple
Noda, K; Shibuya, S; Uesugi, T; Muramatsu, M; Kanazawa, M; Takada, E; Yamada, S
2002-01-01
Two advanced RF-knockout (RF-KO) slow-extraction methods have been developed at HIMAC in order to reduce the spill ripple for accurate heavy-ion cancer therapy: the dual frequency modulation (FM) method and the separated function method. As a result of simulations and experiments, it was verified that the spill ripple could be considerably reduced using these advanced methods, compared with the ordinary RF-KO method. The dual FM method and the separated function method bring about a low spill ripple within standard deviations of around 25% and of 15% during beam extraction within around 2 s, respectively, which are in good agreement with the simulation results.
Advanced RF-KO slow-extraction method for the reduction of spill ripple
Noda, K.; Furukawa, T.; Shibuya, S.; Uesugi, T.; Muramatsu, M.; Kanazawa, M.; Takada, E.; Yamada, S.
2002-10-01
Two advanced RF-knockout (RF-KO) slow-extraction methods have been developed at HIMAC in order to reduce the spill ripple for accurate heavy-ion cancer therapy: the dual frequency modulation (FM) method and the separated function method. As a result of simulations and experiments, it was verified that the spill ripple could be considerably reduced using these advanced methods, compared with the ordinary RF-KO method. The dual FM method and the separated function method bring about a low spill ripple within standard deviations of around 25% and of 15% during beam extraction within around 2 s, respectively, which are in good agreement with the simulation results.
Roden, E.E.; Urrutia, M.M.
1997-07-01
'The authors have made considerable progress toward a number of project objectives during the first several months of activity on the project. An exhaustive analysis was made of the growth rate and biomass yield (both derived from measurements of cell protein production) of two representative strains of Fe(III)-reducing bacteria (Shewanellaalga strain BrY and Geobactermetallireducens) growing with different forms of Fe(III) as an electron acceptor. These two fundamentally different types of Fe(III)-reducing bacteria (FeRB) showed comparable rates of Fe(III) reduction, cell growth, and biomass yield during reduction of soluble Fe(III)-citrate and solid-phase amorphous hydrous ferric oxide (HFO). Intrinsic growth rates of the two FeRB were strongly influenced by whether a soluble or a solid-phase source of Fe(III) was provided: growth rates on soluble Fe(III) were 10--20 times higher than those on solid-phase Fe(III) oxide. Intrinsic FeRB growth rates were comparable during reduction of HF0 and a synthetic crystalline Fe(III) oxide (goethite). A distinct lag phase for protein production was observed during the first several days of incubation in solid-phase Fe(III) oxide medium, even though Fe(III) reduction proceeded without any lag. No such lag between protein production and Fe(III) reduction was observed during growth with soluble Fe(III). This result suggested that protein synthesis coupled to solid-phase Fe(III) oxide reduction in batch culture requires an initial investment of energy (generated by Fe(III) reduction), which is probably needed for synthesis of materials (e.g. extracellular polysaccharides) required for attachment of the cells to oxide surfaces. This phenomenon may have important implications for modeling the growth of FeRB in subsurface sedimentary environments, where attachment and continued adhesion to solid-phase materials will be required for maintenance of Fe(III) reduction activity. Despite considerable differences in the rate and
Chandrashekar, Anand; Chen, Feng; Lin, Jasmine; Humayun, Raashina; Wongsenakhum, Panya; Chang, Sean; Danek, Michal; Itou, Takamasa; Nakayama, Tomoo; Kariya, Atsushi; Kawaguchi, Masazumi; Hizume, Shunichi
2010-09-01
This paper describes electrical testing results of new tungsten chemical vapor deposition (CVD-W) process concepts that were developed to address the W contact and bitline scaling issues on 55 nm node devices. Contact resistance (Rc) measurements in complementary metal oxide semiconductor (CMOS) devices indicate that the new CVD-W process for sub-32 nm and beyond - consisting of an advanced pulsed nucleation layer (PNL) combined with low resistivity tungsten (LRW) initiation - produces a 20-30% drop in Rc for diffused NiSi contacts. From cross-sectional bright field and dark field transmission electron microscopy (TEM) analysis, such Rc improvement can be attributed to improved plugfill and larger in-feature W grain size with the advanced PNL+LRW process. More experiments that measured contact resistance for different feature sizes point to favorable Rc scaling with the advanced PNL+LRW process. Finally, 40% improvement in line resistance was observed with this process as tested on 55 nm embedded dynamic random access memory (DRAM) devices, confirming that the advanced PNL+LRW process can be an effective metallization solution for sub-32 nm devices.
Sorge, J.N. [Southern Co. Services, Inc., Birmingham, AL (United States); Menzies, B. [Radian Corp., Austin, TX (United States); Smouse, S.M. [USDOE Pittsburgh Energy Technology Center, PA (United States); Stallings, J.W. [Electric Power Research Inst., Palo Alto, CA (United States)
1995-09-01
Technology project demonstrating advanced wall-fired combustion techniques for the reduction of nitrogen oxide NOx emissions from coal-fired boilers. The primary objective of the demonstration is to determine the long-term NOx reduction performance of advanced overfire air (AOFA), low NOx burners (LNB), and advanced digital control/optimization methodologies applied in a stepwise fashion to a 500 MW boiler. The focus of this paper is to report (1) on the installation of three on-line carbon-in-ash monitors and (2) the design and results to date from the advanced digital control/optimization phase of the project.
Marincean, Simona; Smith, Sheila R.; Fritz, Michael; Lee, Byung Joo; Rizk, Zeinab
2012-01-01
An upper-division laboratory project has been developed as a collaborative investigation of a reaction routinely taught in organic chemistry courses: the reduction of carbonyl compounds by borohydride reagents. Determination of several trends regarding structure-activity relationship was possible because each student contributed his or her results…
Marincean, Simona; Smith, Sheila R.; Fritz, Michael; Lee, Byung Joo; Rizk, Zeinab
2012-01-01
An upper-division laboratory project has been developed as a collaborative investigation of a reaction routinely taught in organic chemistry courses: the reduction of carbonyl compounds by borohydride reagents. Determination of several trends regarding structure-activity relationship was possible because each student contributed his or her results…
New advanced BARC and gap fill materials based on sublimate reduction for 193nm lithography
Takei, Satoshi; Shinjo, Tetsuya; Sakaida, Yasushi; Horiguchi, Yusuke; Nakajima, Yasuyuki
2006-03-01
Innovative technologies are required by integrated circuit manufacturers to create smaller feature sizes on chips. According to the semiconductor roadmap, feature sizes are slated to be as small as 45nm in 2007, and sizes will be continued to decrease in the following years. Suitable absorbance, Lower etch resistance, straight photoresist profiles, wider D.O.F., thinner film thickness, more effective barrier properties to reduce resist poisoning, and sublimate reduction for defect free coating are the major concerns to be taken into consideration for new BARC and gap fill materials. In this paper, the study of sublimate reduction in the new BARC and gap fill materials was investigated. The effect of sublimate reduction from BARC in bake process is related to decrease defect number. We will introduce new BARC and gap fill material consisted of the polymers with self crosslink-reaction system. In addition of sublimate reduction data, resist profiles and 130 nm via fill performance in via- first dual damascene process presented here would show clearly these materials are ready to be investigated into mass production of 90 nm node IC devices and beyond.
Hughes, Christoper E.; Gazzaniga, John A.
2013-01-01
A wind tunnel experiment was conducted in the NASA Glenn Research Center anechoic 9- by 15-Foot Low-Speed Wind Tunnel to investigate two new advanced noise reduction technologies in support of the NASA Fundamental Aeronautics Program Subsonic Fixed Wing Project. The goal of the experiment was to demonstrate the noise reduction potential and effect on fan model performance of the two noise reduction technologies in a scale model Ultra-High Bypass turbofan at simulated takeoff and approach aircraft flight speeds. The two novel noise reduction technologies are called Over-the-Rotor acoustic treatment and Soft Vanes. Both technologies were aimed at modifying the local noise source mechanisms of the fan tip vortex/fan case interaction and the rotor wake-stator interaction. For the Over-the-Rotor acoustic treatment, two noise reduction configurations were investigated. The results showed that the two noise reduction technologies, Over-the-Rotor and Soft Vanes, were able to reduce the noise level of the fan model, but the Over-the-Rotor configurations had a significant negative impact on the fan aerodynamic performance; the loss in fan aerodynamic efficiency was between 2.75 to 8.75 percent, depending on configuration, compared to the conventional solid baseline fan case rubstrip also tested. Performance results with the Soft Vanes showed that there was no measurable change in the corrected fan thrust and a 1.8 percent loss in corrected stator vane thrust, which resulted in a total net thrust loss of approximately 0.5 percent compared with the baseline reference stator vane set.
Littleton, Harry; Griffin, John
2011-07-31
This project was a subtask of Energy Saving Melting and Revert Reduction Technology (Energy SMARRT) Program. Through this project, technologies, such as computer modeling, pattern quality control, casting quality control and marketing tools, were developed to advance the Lost Foam Casting process application and provide greater energy savings. These technologies have improved (1) production efficiency, (2) mechanical properties, and (3) marketability of lost foam castings. All three reduce energy consumption in the metals casting industry. This report summarizes the work done on all tasks in the period of January 1, 2004 through June 30, 2011. Current (2011) annual energy saving estimates based on commercial introduction in 2011 and a market penetration of 97% by 2020 is 5.02 trillion BTU's/year and 6.46 trillion BTU's/year with 100% market penetration by 2023. Along with these energy savings, reduction of scrap and improvement in casting yield will result in a reduction of the environmental emissions associated with the melting and pouring of the metal which will be saved as a result of this technology. The average annual estimate of CO2 reduction per year through 2020 is 0.03 Million Metric Tons of Carbon Equivalent (MM TCE).
Development of Head-end Pyrochemical Reduction Process for Advanced Oxide Fuels
Park, B. H.; Seo, C. S.; Hur, J. M.; Jeong, S. M.; Hong, S. S.; Choi, I. K.; Choung, W. M.; Kwon, K. C.; Lee, I. W. [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2008-12-15
The development of an electrolytic reduction technology for spent fuels in the form of oxide is of essence to introduce LWR SFs to a pyroprocessing. In this research, the technology was investigated to scale a reactor up, the electrochemical behaviors of FPs were studied to understand the process and a reaction rate data by using U{sub 3}O{sub 8} was obtained with a bench scale reactor. In a scale of 20 kgHM/batch reactor, U{sub 3}O{sub 8} and Simfuel were successfully reduced into metals. Electrochemical characteristics of LiBr, LiI and Li{sub 2}Se were measured in a bench scale reactor and an electrolytic reduction cell was modeled by a computational tool.
ADVANCEMENT OF NUCLEIC ACID-BASED TOOLS FOR MONITORING IN SITU REDUCTIVE DECHLORINATION
Vangelas, K; ELIZABETH EDWARDS, E; FRANK LOFFLER, F; Brian02 Looney, B
2006-11-17
Regulatory protocols generally recognize that destructive processes are the most effective mechanisms that support natural attenuation of chlorinated solvents. In many cases, these destructive processes will be biological processes and, for chlorinated compounds, will often be reductive processes that occur under anaerobic conditions. The existing EPA guidance (EPA, 1998) provides a list of parameters that provide indirect evidence of reductive dechlorination processes. In an effort to gather direct evidence of these processes, scientists have identified key microorganisms and are currently developing tools to measure the abundance and activity of these organisms in subsurface systems. Drs. Edwards and Luffler are two recognized leaders in this field. The research described herein continues their development efforts to provide a suite of tools to enable direct measures of biological processes related to the reductive dechlorination of TCE and PCE. This study investigated the strengths and weaknesses of the 16S rRNA gene-based approach to characterizing the natural attenuation capabilities in samples. The results suggested that an approach based solely on 16S rRNA may not provide sufficient information to document the natural attenuation capabilities in a system because it does not distinguish between strains of organisms that have different biodegradation capabilities. The results of the investigations provided evidence that tools focusing on relevant enzymes for functionally desired characteristics may be useful adjuncts to the 16SrRNA methods.
Sarhadi, Ali; Burn, Donald H.; Yang, Ge; Ghodsi, Ali
2017-02-01
One of the main challenges in climate change studies is accurate projection of the global warming impacts on the probabilistic behaviour of hydro-climate processes. Due to the complexity of climate-associated processes, identification of predictor variables from high dimensional atmospheric variables is considered a key factor for improvement of climate change projections in statistical downscaling approaches. For this purpose, the present paper adopts a new approach of supervised dimensionality reduction, which is called "Supervised Principal Component Analysis (Supervised PCA)" to regression-based statistical downscaling. This method is a generalization of PCA, extracting a sequence of principal components of atmospheric variables, which have maximal dependence on the response hydro-climate variable. To capture the nonlinear variability between hydro-climatic response variables and projectors, a kernelized version of Supervised PCA is also applied for nonlinear dimensionality reduction. The effectiveness of the Supervised PCA methods in comparison with some state-of-the-art algorithms for dimensionality reduction is evaluated in relation to the statistical downscaling process of precipitation in a specific site using two soft computing nonlinear machine learning methods, Support Vector Regression and Relevance Vector Machine. The results demonstrate a significant improvement over Supervised PCA methods in terms of performance accuracy.
Armor Possibilities and Radiographic Blur Reduction for The Advanced Hydrotest Facility
Hackett, M
2001-09-01
Currently at Lawrence Livermore National Laboratory (LLNL) a composite firing vessel is under development for the Advanced Hydrotest Facility (AHF) to study high explosives. This vessel requires a shrapnel mitigating layer to protect the vessel during experiments. The primary purpose of this layer is to protect the vessel, yet the material must be transparent to proton radiographs. Presented here are methods available to collect data needed before selection, along with a comparison tool developed to aid in choosing a material that offers the best of ballistic protection while allowing for clear radiographs.
Armor Possibilities and Radiographic Blur Reduction for The Advanced Hydrotest Facility
Hackett, M
2001-09-01
Currently at Lawrence Livermore National Laboratory (LLNL) a composite firing vessel is under development for the Advanced Hydrotest Facility (AHF) to study high explosives. This vessel requires a shrapnel mitigating layer to protect the vessel during experiments. The primary purpose of this layer is to protect the vessel, yet the material must be transparent to proton radiographs. Presented here are methods available to collect data needed before selection, along with a comparison tool developed to aid in choosing a material that offers the best of ballistic protection while allowing for clear radiographs.
Satake, Kenji
2014-12-01
The December 2004 Indian Ocean tsunami was the worst tsunami disaster in the world's history with more than 200,000 casualties. This disaster was attributed to giant size (magnitude M ~ 9, source length >1000 km) of the earthquake, lacks of expectation of such an earthquake, tsunami warning system, knowledge and preparedness for tsunamis in the Indian Ocean countries. In the last ten years, seismology and tsunami sciences as well as tsunami disaster risk reduction have significantly developed. Progress in seismology includes implementation of earthquake early warning, real-time estimation of earthquake source parameters and tsunami potential, paleoseismological studies on past earthquakes and tsunamis, studies of probable maximum size, recurrence variability, and long-term forecast of large earthquakes in subduction zones. Progress in tsunami science includes accurate modeling of tsunami source such as contribution of horizontal components or "tsunami earthquakes", development of new types of offshore and deep ocean tsunami observation systems such as GPS buoys or bottom pressure gauges, deployments of DART gauges in the Pacific and other oceans, improvements in tsunami propagation modeling, and real-time inversion or data assimilation for the tsunami warning. These developments have been utilized for tsunami disaster reduction in the forms of tsunami early warning systems, tsunami hazard maps, and probabilistic tsunami hazard assessments. Some of the above scientific developments helped to reveal the source characteristics of the 2011 Tohoku earthquake, which caused devastating tsunami damage in Japan and Fukushima Dai-ichi Nuclear Power Station accident. Toward tsunami disaster risk reduction, interdisciplinary and trans-disciplinary approaches are needed for scientists with other stakeholders.
Advances of Model Order Reduction Research in Large-scale System Simulation
无
2002-01-01
Model Order Reduction (MOR) plays more and more imp or tant role in complex system simulation, design and control recently. For example , for the large-size space structures, VLSI and MEMS (Micro-ElectroMechanical Systems) etc., in order to shorten the development cost, increase the system co ntrolling accuracy and reduce the complexity of controllers, the reduced order model must be constructed. Even in Virtual Reality (VR), the simulation and d isplay must be in real-time, the model order must be red...
López-Gatius, F; Hunter, R H F
2005-01-01
Twin pregnancies represent a management problem in dairy cattle since the risk of pregnancy loss increases, and the profitability of the herd diminishes drastically as the frequency of twin births increases. The aim of this study was to monitor the development of 211 twin pregnancies in high producing dairy cows in order to determine the best time for an embryo reduction approach. Pregnancy was diagnosed by transrectal ultrasonography between 36 and 42 days after insemination. Animals were then subjected to weekly ultrasound examination until Day 90 of gestation or until pregnancy loss. Viability was determined by monitoring the embryonic/fetal heartbeat until Day 50 of pregnancy, and then by heartbeat or fetal movement detection. Eighty-six cows (40.8%) bore bilateral and 125 (59.2%) unilateral twin pregnancies. Embryo death was registered in one of the two embryos in 35 cows (16.6%), 33 of them at pregnancy diagnosis. Pregnancy loss occurred in 22 of these cows between 1 and 4 weeks later. Thus, 13 (6.2% of the total animals) cows, carrying one dead of the two embryos, maintained gestation. Total pregnancy loss before Day 90 of pregnancy (mean 69 +/- 14 days) was registered in 51 (24.2%) cows: 7 (8%) of bilateral pregnancies and 44 (35.2%) of unilateral pregnancies, and it was higher (P = 0.0001) for both right (32.4%, 24/74) and left (39.2%, 20/51) unilateral than for bilateral (8.1%, 7/86) twin pregnancies. The single embryo death rate was significantly (P = 0.02) lower for cows with bilateral twins (9.3%, 8/86) than for total cows with unilateral twins (21.6%, 27/125). By way of overall conclusion, embryo reduction can occur in dairy cattle, and the practical perspective remains that most embryonic mortality in twins (one of the two embryos) occurs around Days 35-40 of gestation, the period when pregnancy diagnosis is generally performed and when embryo reduction could be tried.
Wu, Renbing; Xue, Yanhong; Liu, Bo; Zhou, Kun; Wei, Jun; Chan, Siew Hwa
2016-10-01
Highly efficient and cost-effective electrocatalyst for the oxygen reduction reaction (ORR) is crucial for a variety of renewable energy applications. Herein, strongly coupled hybrid composites composed of cobalt diselenide (CoSe2) nanoparticles embedded within graphitic carbon polyhedra (GCP) as high-performance ORR catalyst have been rationally designed and synthesized. The catalyst is fabricated by a convenient method, which involves the simultaneous pyrolysis and selenization of preformed Co-based zeolitic imidazolate framework (ZIF-67). Benefiting from the unique structural features, the resulting CoSe2/GCP hybrid catalyst shows high stability and excellent electrocatalytic activity towards ORR (the onset and half-wave potentials are 0.935 and 0.806 V vs. RHE, respectively), which is superior to the state-of-the-art commercial Pt/C catalyst (0.912 and 0.781 V vs. RHE, respectively).
Gate Leakage Current Reduction With Advancement of Graded Barrier AlGaN/GaN HEMT
Palash Das
2011-01-01
Full Text Available The gate leakage current reduction solution of AlGaN/GaN HEMT device issue has been addressed in this paper with compositional grading of AlGaN barrier layer. This work is also conjugated with the critical thickness limitation of heterostructure material growth. Hence, critical thickness calculation of AlGaN over GaN has been kept in special view. 1D Schrodinger and Poisson solver was used to calculate the 2DEG concentration and effective location to use it in the ATLAS device simulator for the predictions. The proposed Al0.50Ga0.50N/Al0.35Ga0.65N/Al0.20Ga0.80N/GaN HEMT structure exhibits the leakage current of the order of around 15 nA/mm at gate voltage of 1 V.
2014 U.S. Offshore Wind Market Report: Industry Trends, Technology Advancement, and Cost Reduction
Smith, Aaron; Stehly, Tyler; Walter Musial
2015-09-29
2015 has been an exciting year for the U.S. offshore wind market. After more than 15 years of development work, the U.S. has finally hit a crucial milestone; Deepwater Wind began construction on the 30 MW Block Island Wind Farm (BIWF) in April. A number of other promising projects, however, have run into economic, legal, and political headwinds, generating much speculation about the future of the industry. This slow, and somewhat painful, start to the industry is not without precedent; each country in northern Europe began with pilot-scale, proof-of-concept projects before eventually moving to larger commercial scale installations. Now, after more than a decade of commercial experience, the European industry is set to achieve a new deployment record, with more than 4 GW expected to be commissioned in 2015, with demonstrable progress towards industry-wide cost reduction goals. DWW is leveraging 25 years of European deployment experience; the BIWF combines state-of-the-art technologies such as the Alstom 6 MW turbine with U.S. fabrication and installation competencies. The successful deployment of the BIWF will provide a concrete showcase that will illustrate the potential of offshore wind to contribute to state, regional, and federal goals for clean, reliable power and lasting economic development. It is expected that this initial project will launch the U.S. industry into a phase of commercial development that will position offshore wind to contribute significantly to the electric systems in coastal states by 2030.
Luo, Yuehao; Yuan, Lu; Li, Jianhua; Wang, Jianshe
2015-12-01
Nature has supplied the inexhaustible resources for mankind, and at the same time, it has also progressively developed into the school for scientists and engineers. Through more than four billions years of rigorous and stringent evolution, different creatures in nature gradually exhibit their own special and fascinating biological functional surfaces. For example, sharkskin has the potential drag-reducing effect in turbulence, lotus leaf possesses the self-cleaning and anti-foiling function, gecko feet have the controllable super-adhesion surfaces, the flexible skin of dolphin can accelerate its swimming velocity. Great profits of applying biological functional surfaces in daily life, industry, transportation and agriculture have been achieved so far, and much attention from all over the world has been attracted and focused on this field. In this overview, the bio-inspired drag-reducing mechanism derived from sharkskin is explained and explored comprehensively from different aspects, and then the main applications in different fluid engineering are demonstrated in brief. This overview will inevitably improve the comprehension of the drag reduction mechanism of sharkskin surface and better understand the recent applications in fluid engineering.
Modelling volatility by variance decomposition
Amado, Cristina; Teräsvirta, Timo
on the multiplicative decomposition of the variance is developed. It is heavily dependent on Lagrange multiplier type misspecification tests. Finite-sample properties of the strategy and tests are examined by simulation. An empirical application to daily stock returns and another one to daily exchange rate returns...... illustrate the functioning and properties of our modelling strategy in practice. The results show that the long memory type behaviour of the sample autocorrelation functions of the absolute returns can also be explained by deterministic changes in the unconditional variance....
Revision: Variance Inflation in Regression
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.
Analysis of variance: Comfortless questions
L.V. Nedorezov
2017-01-01
In this paper the simplest variant of analysis of variance is under consideration. Three examples from textbooks by Lakin (1990) and Rokitsky (1973) were re-considered. It was obtained that traditional one-way ANOVA and Kruskal - Wallis criterion can lead to unreal results about factor's influence on value of characteristics. Alternative way to solution of the same problem is under consideration too.
Analysis of Variance: Variably Complex
Drummond, Gordon B.; Vowler, Sarah L.
2012-01-01
These authors have previously described how to use the "t" test to compare two groups. In this article, they describe the use of a different test, analysis of variance (ANOVA) to compare more than two groups. ANOVA is a test of group differences: do at least two of the means differ from each other? ANOVA assumes (1) normal distribution of…
Xiao, Qian; Yu, Shuili; Li, Lei; Wang, Ting; Liao, Xinlei; Ye, Yubing
2017-02-15
Bromate (BrO3(-)) is a possible human carcinogen regulated at a strict standard of 10μg/L in drinking water. Various techniques to eliminate BrO3(-) usually fall into three main categories: reducing bromide (Br(-)) prior to formation of BrO3(-), minimizing BrO3(-) formation during the ozonation process, and removing BrO3(-) from post-ozonation waters. However, the first two approaches exhibit low degradation efficiency and high treatment cost. The third workaround has obvious advantages, such as high reduction efficiency, more stable performance and easier combination with UV disinfection, and has therefore been widely implemented in water treatment. Recently, advanced reduction processes (ARPs), the photocatalysis of BrO3(-), have attracted much attention due to improved performance. To increase the feasibility of photocatalytic systems, the focus of this work concerns new technological developments, followed by a summary of reducing agents, activation methods, operational parameters, and applications. The reaction mechanisms of two typical processes involving UV/sulfite homogeneous photocatalysis and UV/titanium dioxide heterogeneous photocatalysis are further summarized. The future research needs for ARPs to reach full-scale potential in drinking water treatment are suggested accordingly. Copyright © 2016. Published by Elsevier B.V.
Comprehensive Study on the Estimation of the Variance Components of Traverse Nets
无
2003-01-01
This paper advances a new simplified formula for estimating variance components ,sums up the basic law to calculate the weights of observed values and a circulation method using the increaments of weights when estimating the variance components of traverse nets,advances the charicteristic roots method to estimate the variance components of traveres nets and presents a practical method to make two real and symmetric matrices two diagonal ones.
Sorge, J.N.; Larrimore, C.L.; Slatsky, M.D.; Menzies, W.R.; Smouse, S.M.; Stallings, J.W.
1997-12-31
This paper discusses the technical progress of a US Department of Energy Innovative Clean Coal Technology project demonstrating advanced wall-fired combustion techniques for the reduction of nitrogen oxide (NOx) emissions from coal-fired boilers. The primary objectives of the demonstration is to determine the long-term NOx reduction performance of advanced overfire air (AOFA), low NOx burners (LNB), and advanced digital control optimization methodologies applied in a stepwise fashion to a 500 MW boiler. The focus of this paper is to report (1) on the installation of three on-line carbon-in-ash monitors and (2) the design and results to date from the advanced digital control/optimization phase of the project.
Variance based OFDM frame synchronization
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.
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
2015-06-28
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.
Pesenson, Meyer; Pesenson, I. Z.; McCollum, B.
2009-05-01
The complexity of multitemporal/multispectral astronomical data sets together with the approaching petascale of such datasets and large astronomical surveys require automated or semi-automated methods for knowledge discovery. Traditional statistical methods of analysis may break down not only because of the amount of data, but mostly because of the increase of the dimensionality of data. Image fusion (combining information from multiple sensors in order to create a composite enhanced image) and dimension reduction (finding lower-dimensional representation of high-dimensional data) are effective approaches to "the curse of dimensionality,” thus facilitating automated feature selection, classification and data segmentation. Dimension reduction methods greatly increase computational efficiency of machine learning algorithms, improve statistical inference and together with image fusion enable effective scientific visualization (as opposed to mere illustrative visualization). The main approach of this work utilizes recent advances in multidimensional image processing, as well as representation of essential structure of a data set in terms of its fundamental eigenfunctions, which are used as an orthonormal basis for the data visualization and analysis. We consider multidimensional data sets and images as manifolds or combinatorial graphs and construct variational splines that minimize certain Sobolev norms. These splines allow us to reconstruct the eigenfunctions of the combinatorial Laplace operator by using only a small portion of the graph. We use the first two or three eigenfunctions for embedding large data sets into two- or three-dimensional Euclidean space. Such reduced data sets allow efficient data organization, retrieval, analysis and visualization. We demonstrate applications of the algorithms to test cases from the Spitzer Space Telescope. This work was carried out with funding from the National Geospatial-Intelligence Agency University Research Initiative
Mei, S; Tonry, J L; Jordan, A; Peng, E W; Côté, P; Ferrarese, L; Merritt, D; Milosavljevic, M; West, M J; Mei, Simona; Blakeslee, John P.; Tonry, John L.; Jordan, Andres; Peng, Eric W.; Cote, Patrick; Ferrarese, Laura; Merritt, David; Milosavljevic, Milos; West, Michael J.
2005-01-01
The Advanced Camera for Surveys (ACS) Virgo Cluster Survey is a large program to image 100 early-type Virgo galaxies using the F475W and F850LP bandpasses of the Wide Field Channel of the ACS instrument on the Hubble Space Telescope (HST). The scientific goals of this survey include an exploration of the three-dimensional structure of the Virgo Cluster and a critical examination of the usefulness of the globular cluster luminosity function as a distance indicator. Both of these issues require accurate distances for the full sample of 100 program galaxies. In this paper, we describe our data reduction procedures and examine the feasibility of accurate distance measurements using the method of surface brightness fluctuations (SBF) applied to the ACS Virgo Cluster Survey F850LP imaging. The ACS exhibits significant geometrical distortions due to its off-axis location in the HST focal plane; correcting for these distortions by resampling the pixel values onto an undistorted frame results in pixel correlations tha...
Variance-based uncertainty relations
Huang, Yichen
2010-01-01
It is hard to overestimate the fundamental importance of uncertainty relations in quantum mechanics. In this work, I propose state-independent variance-based uncertainty relations for arbitrary observables in both finite and infinite dimensional spaces. We recover the Heisenberg uncertainty principle as a special case. By studying examples, we find that the lower bounds provided by our new uncertainty relations are optimal or near-optimal. I illustrate the uses of our new uncertainty relations by showing that they eliminate one common obstacle in a sequence of well-known works in entanglement detection, and thus make these works much easier to access in applications.
Vertical velocity variances and Reynold stresses at Brookhaven
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...... velocity component....
Neutrino mass without cosmic variance
LoVerde, Marilena
2016-01-01
Measuring the absolute scale of the neutrino masses is one of the most exciting opportunities available with near-term cosmological datasets. Two quantities that are sensitive to neutrino mass, scale-dependent halo bias $b(k)$ and the linear growth parameter $f(k)$ inferred from redshift-space distortions, can be measured without cosmic variance. Unlike the amplitude of the matter power spectrum, which always has a finite error, the error on $b(k)$ and $f(k)$ continues to decrease as the number density of tracers increases. This paper presents forecasts for statistics of galaxy and lensing fields that are sensitive to neutrino mass via $b(k)$ and $f(k)$. The constraints on neutrino mass from the auto- and cross-power spectra of spectroscopic and photometric galaxy samples are weakened by scale-dependent bias unless a very high density of tracers is available. In the high density limit, using multiple tracers allows cosmic-variance to be beaten and the forecasted errors on neutrino mass shrink dramatically. In...
The phenome-wide distribution of genetic variance.
Blows, Mark W; Allen, Scott L; Collet, Julie M; Chenoweth, Stephen F; McGuigan, Katrina
2015-07-01
A general observation emerging from estimates of additive genetic variance in sets of functionally or developmentally related traits is that much of the genetic variance is restricted to few trait combinations as a consequence of genetic covariance among traits. While this biased distribution of genetic variance among functionally related traits is now well documented, how it translates to the broader phenome and therefore any trait combination under selection in a given environment is unknown. We show that 8,750 gene expression traits measured in adult male Drosophila serrata exhibit widespread genetic covariance among random sets of five traits, implying that pleiotropy is common. Ultimately, to understand the phenome-wide distribution of genetic variance, very large additive genetic variance-covariance matrices (G) are required to be estimated. We draw upon recent advances in matrix theory for completing high-dimensional matrices to estimate the 8,750-trait G and show that large numbers of gene expression traits genetically covary as a consequence of a single genetic factor. Using gene ontology term enrichment analysis, we show that the major axis of genetic variance among expression traits successfully identified genetic covariance among genes involved in multiple modes of transcriptional regulation. Our approach provides a practical empirical framework for the genetic analysis of high-dimensional phenome-wide trait sets and for the investigation of the extent of high-dimensional genetic constraint.
ADVANTG An Automated Variance Reduction Parameter Generator, Rev. 1
Mosher, Scott W. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Johnson, Seth R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Bevill, Aaron M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Ibrahim, Ahmad M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Daily, Charles R. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Evans, Thomas M. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wagner, John C. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Johnson, Jeffrey O. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Grove, Robert E. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
2015-08-01
The primary objective of ADVANTG is to reduce both the user effort and the computational time required to obtain accurate and precise tally estimates across a broad range of challenging transport applications. ADVANTG has been applied to simulations of real-world radiation shielding, detection, and neutron activation problems. Examples of shielding applications include material damage and dose rate analyses of the Oak Ridge National Laboratory (ORNL) Spallation Neutron Source and High Flux Isotope Reactor (Risner and Blakeman 2013) and the ITER Tokamak (Ibrahim et al. 2011). ADVANTG has been applied to a suite of radiation detection, safeguards, and special nuclear material movement detection test problems (Shaver et al. 2011). ADVANTG has also been used in the prediction of activation rates within light water reactor facilities (Pantelias and Mosher 2013). In these projects, ADVANTG was demonstrated to significantly increase the tally figure of merit (FOM) relative to an analog MCNP simulation. The ADVANTG-generated parameters were also shown to be more effective than manually generated geometry splitting parameters.
Mathieu R Brodeur
Full Text Available Advanced-glycation end products (AGEs were recently implicated in vascular calcification, through a process mediated by RAGE (receptor for AGEs. Although a correlation between AGEs levels and vascular calcification was established, there is no evidence that reducing in vivo AGEs deposition or inhibiting AGEs-RAGE signaling pathways can decrease medial calcification. We evaluated the impact of inhibiting AGEs formation by pyridoxamine or elimination of AGEs by alagebrium on diabetic medial calcification. We also evaluated if the inhibition of AGEs-RAGE signaling pathways can prevent calcification. Rats were fed a high fat diet during 2 months before receiving a low dose of streptozotocin. Then, calcification was induced with warfarin. Pyridoxamine was administered at the beginning of warfarin treatment while alagebrium was administered 3 weeks after the beginning of warfarin treatment. Results demonstrate that AGEs inhibitors prevent the time-dependent accumulation of AGEs in femoral arteries of diabetic rats. This effect was accompanied by a reduced diabetes-accelerated calcification. Ex vivo experiments showed that N-methylpyridinium, an agonist of RAGE, induced calcification of diabetic femoral arteries, a process inhibited by antioxidants and different inhibitors of signaling pathways associated to RAGE activation. The physiological importance of oxidative stress was demonstrated by the reduction of femoral artery calcification in diabetic rats treated with apocynin, an inhibitor of reactive oxygen species production. We demonstrated that AGE inhibitors prevent or limit medial calcification. We also showed that diabetes-accelerated calcification is prevented by antioxidants. Thus, inhibiting the association of AGE-RAGE or the downstream signaling reduced medial calcification in diabetes.
Variance estimation for systematic designs in spatial surveys.
Fewster, R M
2011-12-01
In spatial surveys for estimating the density of objects in a survey region, systematic designs will generally yield lower variance than random designs. However, estimating the systematic variance is well known to be a difficult problem. Existing methods tend to overestimate the variance, so although the variance is genuinely reduced, it is over-reported, and the gain from the more efficient design is lost. The current approaches to estimating a systematic variance for spatial surveys are to approximate the systematic design by a random design, or approximate it by a stratified design. Previous work has shown that approximation by a random design can perform very poorly, while approximation by a stratified design is an improvement but can still be severely biased in some situations. We develop a new estimator based on modeling the encounter process over space. The new "striplet" estimator has negligible bias and excellent precision in a wide range of simulation scenarios, including strip-sampling, distance-sampling, and quadrat-sampling surveys, and including populations that are highly trended or have strong aggregation of objects. We apply the new estimator to survey data for the spotted hyena (Crocuta crocuta) in the Serengeti National Park, Tanzania, and find that the reported coefficient of variation for estimated density is 20% using approximation by a random design, 17% using approximation by a stratified design, and 11% using the new striplet estimator. This large reduction in reported variance is verified by simulation. © 2011, The International Biometric Society.
Analytic variance estimates of Swank and Fano factors.
Gutierrez, Benjamin; Badano, Aldo; Samuelson, Frank
2014-07-01
Variance estimates for detector energy resolution metrics can be used as stopping criteria in Monte Carlo simulations for the purpose of ensuring a small uncertainty of those metrics and for the design of variance reduction techniques. The authors derive an estimate for the variance of two energy resolution metrics, the Swank factor and the Fano factor, in terms of statistical moments that can be accumulated without significant computational overhead. The authors examine the accuracy of these two estimators and demonstrate how the estimates of the coefficient of variation of the Swank and Fano factors behave with data from a Monte Carlo simulation of an indirect x-ray imaging detector. The authors' analyses suggest that the accuracy of their variance estimators is appropriate for estimating the actual variances of the Swank and Fano factors for a variety of distributions of detector outputs. The variance estimators derived in this work provide a computationally convenient way to estimate the error or coefficient of variation of the Swank and Fano factors during Monte Carlo simulations of radiation imaging systems.
Analytic variance estimates of Swank and Fano factors
Gutierrez, Benjamin; Badano, Aldo; Samuelson, Frank, E-mail: frank.samuelson@fda.hhs.gov [US Food and Drug Administration, Silver Spring, Maryland 20993 (United States)
2014-07-15
Purpose: Variance estimates for detector energy resolution metrics can be used as stopping criteria in Monte Carlo simulations for the purpose of ensuring a small uncertainty of those metrics and for the design of variance reduction techniques. Methods: The authors derive an estimate for the variance of two energy resolution metrics, the Swank factor and the Fano factor, in terms of statistical moments that can be accumulated without significant computational overhead. The authors examine the accuracy of these two estimators and demonstrate how the estimates of the coefficient of variation of the Swank and Fano factors behave with data from a Monte Carlo simulation of an indirect x-ray imaging detector. Results: The authors' analyses suggest that the accuracy of their variance estimators is appropriate for estimating the actual variances of the Swank and Fano factors for a variety of distributions of detector outputs. Conclusions: The variance estimators derived in this work provide a computationally convenient way to estimate the error or coefficient of variation of the Swank and Fano factors during Monte Carlo simulations of radiation imaging systems.
Warped functional analysis of variance.
Gervini, Daniel; Carter, Patrick A
2014-09-01
This article presents an Analysis of Variance model for functional data that explicitly incorporates phase variability through a time-warping component, allowing for a unified approach to estimation and inference in presence of amplitude and time variability. The focus is on single-random-factor models but the approach can be easily generalized to more complex ANOVA models. The behavior of the estimators is studied by simulation, and an application to the analysis of growth curves of flour beetles is presented. Although the model assumes a smooth latent process behind the observed trajectories, smootheness of the observed data is not required; the method can be applied to irregular time grids, which are common in longitudinal studies.
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
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 optimal stopping for geometric Levy processes
Gad, Kamille Sofie Tågholt; Pedersen, Jesper Lund
2015-01-01
The main result of this paper is the solution to the optimal stopping problem of maximizing the variance of a geometric Lévy process. We call this problem the variance problem. We show that, for some geometric Lévy processes, we achieve higher variances by allowing randomized stopping. Furthermore...
Linear Minimum variance estimation fusion
ZHU Yunmin; LI Xianrong; ZHAO Juan
2004-01-01
This paper shows that a general mulitisensor unbiased linearly weighted estimation fusion essentially is the linear minimum variance (LMV) estimation with linear equality constraint, and the general estimation fusion formula is developed by extending the Gauss-Markov estimation to the random paramem of distributed estimation fusion in the LMV setting.In this setting ,the fused estimator is a weighted sum of local estimatess with a matrix quadratic optimization problem subject to a convex linear equality constraint. Second, we present a unique solution to the above optimization problem, which depends only on the covariance matrixCK. Third, if a priori information, the expectation and covariance, of the estimated quantity is unknown, a necessary and sufficient condition for the above LMV fusion becoming the best unbiased LMV estimation with dnown prior information as the above is presented. We also discuss the generality and usefulness of the LMV fusion formulas developed. Finally, we provied and off-line recursion of Ck for a class of multisensor linear systems with coupled measurement noises.
Pillard, Paul; Livet, Veronique; Cabon, Quentin; Bismuth, Camille; Sonet, Juliette; Remy, Denise; Fau, Didier; Carozzo, Claude; Viguier, Eric; Cachon, Thibaut
2016-12-01
OBJECTIVE To evaluate the validity of 2 radiographic methods for measurement of the tibial tuberosity advancement distance required to achieve a reduction in patellar tendon-tibial plateau angle (PTA) to the ideal 90° in dogs by use of the modified Maquet technique (MMT). SAMPLE 24 stifle joints harvested from 12 canine cadavers. PROCEDURES Radiographs of stifle joints placed at 135° in the true lateral position were used to measure the required tibial tuberosity advancement distance with the conventional (A(M)) and correction (A(E)) methods. The MMT was used to successively advance the tibial crest to A(M) and A(E). Postoperative PTA was measured on a mediolateral radiograph for each advancement measurement method. If none of the measurements were close to 90°, the advancement distance was modified until the PTA was equal to 90° within 0.1°, and the true advancement distance (TA) was measured. Results were used to determine the optimal commercially available size of cage implant that would be used in a clinical situation. RESULTS Median A(M) and A(E) were 10.6 mm and 11.5 mm, respectively. Mean PTAs for the conventional and correction methods were 93.4° and 92.3°, respectively, and differed significantly from 90°. Median TA was 13.5 mm. The A(M) and A(E) led to the same cage size recommendations as for TA for only 1 and 4 stifle joints, respectively. CONCLUSIONS AND CLINICAL RELEVANCE Both radiographic methods of measuring the distance required to advance the tibial tuberosity in dogs led to an under-reduction in postoperative PTA when the MMT was used. A new, more accurate radiographic method needs to be developed.
Generalized analysis of molecular variance.
Caroline M Nievergelt
2007-04-01
Full Text Available Many studies in the fields of genetic epidemiology and applied population genetics are predicated on, or require, an assessment of the genetic background diversity of the individuals chosen for study. A number of strategies have been developed for assessing genetic background diversity. These strategies typically focus on genotype data collected on the individuals in the study, based on a panel of DNA markers. However, many of these strategies are either rooted in cluster analysis techniques, and hence suffer from problems inherent to the assignment of the biological and statistical meaning to resulting clusters, or have formulations that do not permit easy and intuitive extensions. We describe a very general approach to the problem of assessing genetic background diversity that extends the analysis of molecular variance (AMOVA strategy introduced by Excoffier and colleagues some time ago. As in the original AMOVA strategy, the proposed approach, termed generalized AMOVA (GAMOVA, requires a genetic similarity matrix constructed from the allelic profiles of individuals under study and/or allele frequency summaries of the populations from which the individuals have been sampled. The proposed strategy can be used to either estimate the fraction of genetic variation explained by grouping factors such as country of origin, race, or ethnicity, or to quantify the strength of the relationship of the observed genetic background variation to quantitative measures collected on the subjects, such as blood pressure levels or anthropometric measures. Since the formulation of our test statistic is rooted in multivariate linear models, sets of variables can be related to genetic background in multiple regression-like contexts. GAMOVA can also be used to complement graphical representations of genetic diversity such as tree diagrams (dendrograms or heatmaps. We examine features, advantages, and power of the proposed procedure and showcase its flexibility by
Analysis of Variance Components for Genetic Markers with Unphased Genotypes.
Wang, Tao
2016-01-01
An ANOVA type general multi-allele (GMA) model was proposed in Wang (2014) on analysis of variance components for quantitative trait loci or genetic markers with phased or unphased genotypes. In this study, by applying the GMA model, we further examine estimation of the genetic variance components for genetic markers with unphased genotypes based on a random sample from a study population. In one locus and two loci cases, we first derive the least square estimates (LSE) of model parameters in fitting the GMA model. Then we construct estimators of the genetic variance components for one marker locus in a Hardy-Weinberg disequilibrium population and two marker loci in an equilibrium population. Meanwhile, we explore the difference between the classical general linear model (GLM) and GMA based approaches in association analysis of genetic markers with quantitative traits. We show that the GMA model can retain the same partition on the genetic variance components as the traditional Fisher's ANOVA model, while the GLM cannot. We clarify that the standard F-statistics based on the partial reductions in sums of squares from GLM for testing the fixed allelic effects could be inadequate for testing the existence of the variance component when allelic interactions are present. We point out that the GMA model can reduce the confounding between the allelic effects and allelic interactions at least for independent alleles. As a result, the GMA model could be more beneficial than GLM for detecting allelic interactions.
Seasonal variance in P system models for metapopulations
Daniela Besozzi; Paolo Cazzaniga; Dario Pescini; Giancarlo Mauri
2007-01-01
Metapopulations are ecological models describing the interactions and the behavior of populations living in fragmented habitats. In this paper, metapopulations are modelled by means of dynamical probabilistic P systems, where additional structural features have been defined (e. g., a weighted graph associated with the membrane structure and the reduction of maximal parallelism). In particular, we investigate the influence of stochastic and periodic resource feeding processes, owing to seasonal variance, on emergent metapopulation dynamics.
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.
Expected Stock Returns and Variance Risk Premia
Bollerslev, Tim; Zhou, Hao
predicting high (low) future returns. The magnitude of the return predictability of the variance risk premium easily dominates that afforded by standard predictor variables like the P/E ratio, the dividend yield, the default spread, and the consumption-wealth ratio (CAY). Moreover, combining the variance...... 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...
Bierbaum, S; Öller, H-J; Kersten, A; Klemenčič, A Krivograd
2014-01-01
Ozone (O(3)) has been used successfully in advanced wastewater treatment in paper mills, other sectors and municipalities. To solve the water problems of regions lacking fresh water, wastewater treated by advanced oxidation processes (AOPs) can substitute fresh water in highly water-consuming industries. Results of this study have shown that paper strength properties are not impaired and whiteness is slightly impaired only when reusing paper mill wastewater. Furthermore, organic trace compounds are becoming an issue in the German paper industry. The results of this study have shown that AOPs are capable of improving wastewater quality by reducing organic load, colour and organic trace compounds.
Barlas, A.; Van Kuik, G.A.M.
2009-01-01
A newly developed comprehensive aeroelastic model is used to investigate active flap concepts on the Upwind 5MW reference wind turbine. The model is specially designed to facilitate distributed control concepts and advanced controller design. Different concepts of centralized and distributed control
Barlas, A.; van Kuik, G.A.M.
2009-01-01
A newly developed comprehensive aeroelastic model is used to investigate active flap concepts on the Upwind 5MW reference wind turbine. The model is specially designed to facilitate distributed control concepts and advanced controller design. Different concepts of centralized and distributed control
Influence of Family Structure on Variance Decomposition
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...
2010-04-01
... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Variances. 1010.4 Section 1010.4 Food and Drugs... PERFORMANCE STANDARDS FOR ELECTRONIC PRODUCTS: GENERAL General Provisions § 1010.4 Variances. (a) Criteria for... shall modify the tag, label, or other certification required by § 1010.2 to state: (1) That the...
Analysis of variance for model output
Jansen, M.J.W.
1999-01-01
A scalar model output Y is assumed to depend deterministically on a set of stochastically independent input vectors of different dimensions. The composition of the variance of Y is considered; variance components of particular relevance for uncertainty analysis are identified. Several analysis of va
The Correct Kriging Variance Estimated by Bootstrapping
den Hertog, D.; Kleijnen, J.P.C.; Siem, A.Y.D.
2004-01-01
The classic Kriging variance formula is widely used in geostatistics and in the design and analysis of computer experiments.This paper proves that this formula is wrong.Furthermore, it shows that the formula underestimates the Kriging variance in expectation.The paper develops parametric bootstrappi
Influence of Family Structure on Variance Decomposition
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...
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 Risk Premia on Stocks and Bonds
Mueller, Philippe; Sabtchevsky, Petar; Vedolin, Andrea
is different from the equity variance risk premium. Third, the conditional correlation between stock and bond market variance risk premium switches sign often and ranges between -60% and +90%. We then show that these stylized facts pose a challenge to standard consumption-based asset pricing models....
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.
Expected Stock Returns and Variance Risk Premia
Bollerslev, Tim; Zhou, Hao
We find that the difference between implied and realized variation, or the variance risk premium, is able to explain more than fifteen percent of the ex-post time series variation in quarterly excess returns on the market portfolio over the 1990 to 2005 sample period, with high (low) premia...... predicting high (low) future returns. The magnitude of the return predictability of the variance risk premium easily dominates that afforded by standard predictor variables like the P/E ratio, the dividend yield, the default spread, and the consumption-wealth ratio (CAY). Moreover, combining the variance...... 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...
Wang, Lei; Yin, Jie; Zhao, Lu; Tian, Chungui; Yu, Peng; Wang, Jianqiang; Fu, Honggang
2013-04-14
Fe2N nanoparticles and nitrogen-doped graphitic nanosheet composites (Fe2N-NGC) have been synthesized by an ion-exchanged route, which can serve as an efficient non-precious metal electrocatalyst with a 4e(-) reaction pathway for oxygen reduction reactions (ORR).
Functional analysis of variance for association studies.
Olga A Vsevolozhskaya
Full Text Available While progress has been made in identifying common genetic variants associated with human diseases, for most of common complex diseases, the identified genetic variants only account for a small proportion of heritability. Challenges remain in finding additional unknown genetic variants predisposing to complex diseases. With the advance in next-generation sequencing technologies, sequencing studies have become commonplace in genetic research. The ongoing exome-sequencing and whole-genome-sequencing studies generate a massive amount of sequencing variants and allow researchers to comprehensively investigate their role in human diseases. The discovery of new disease-associated variants can be enhanced by utilizing powerful and computationally efficient statistical methods. In this paper, we propose a functional analysis of variance (FANOVA method for testing an association of sequence variants in a genomic region with a qualitative trait. The FANOVA has a number of advantages: (1 it tests for a joint effect of gene variants, including both common and rare; (2 it fully utilizes linkage disequilibrium and genetic position information; and (3 allows for either protective or risk-increasing causal variants. Through simulations, we show that FANOVA outperform two popularly used methods - SKAT and a previously proposed method based on functional linear models (FLM, - especially if a sample size of a study is small and/or sequence variants have low to moderate effects. We conduct an empirical study by applying three methods (FANOVA, SKAT and FLM to sequencing data from Dallas Heart Study. While SKAT and FLM respectively detected ANGPTL 4 and ANGPTL 3 associated with obesity, FANOVA was able to identify both genes associated with obesity.
Russell, Matthew R; Lilley, Kathryn S
2012-12-21
The biological variance in protein expression of interest to biologists can only be accessed if the technical variance of the protein quantification method is low compared with the biological variance. Technical variance is dependent on the protocol employed within a quantitative proteomics experiment and accumulated with every additional step. The magnitude of additional variance incurred by each step of a protocol should be determined to enable design of experiments maximally sensitive to differential protein expression. Metabolic labelling techniques for MS based quantitative proteomics enable labelled and unlabelled samples to be combined at the tissue level. It has been widely assumed, although not yet empirically verified, that early combination of samples minimises technical variance in relative quantification. This study presents a pipeline to determine the variance incurred at each stage of a common quantitative proteomics protocol involving metabolic labelling. We apply this pipeline to determine whether early combination of samples in a protocol leads to significant reduction in experimental variance. We also identify which stage within the protocol is associated with maximum variance. This provides a blueprint by which the variance associated with each stage of any protocol can be dissected and utilised to influence optimal experimental design.
Variance components for body weight in Japanese quails (Coturnix japonica
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.
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.
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...
Reducing variance in batch partitioning measurements
Mariner, Paul E.
2010-08-11
The partitioning experiment is commonly performed with little or no attention to reducing measurement variance. Batch test procedures such as those used to measure K{sub d} values (e.g., ASTM D 4646 and EPA402 -R-99-004A) do not explain how to evaluate measurement uncertainty nor how to minimize measurement variance. In fact, ASTM D 4646 prescribes a sorbent:water ratio that prevents variance minimization. Consequently, the variance of a set of partitioning measurements can be extreme and even absurd. Such data sets, which are commonplace, hamper probabilistic modeling efforts. An error-savvy design requires adjustment of the solution:sorbent ratio so that approximately half of the sorbate partitions to the sorbent. Results of Monte Carlo simulations indicate that this simple step can markedly improve the precision and statistical characterization of partitioning uncertainty.
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.
78 FR 14122 - Revocation of Permanent Variances
2013-03-04
... Occupational Safety and Health Administration Revocation of Permanent Variances AGENCY: Occupational Safety and Health Administration (OSHA), Labor. ACTION: Notice of revocation. SUMMARY: With this notice, OSHA is... into consideration these newly corrected cross references. DATES: The effective date of the...
2010-01-01
... 13 Business Credit and Assistance 1 2010-01-01 2010-01-01 false Variances. 307.22 Section 307.22 Business Credit and Assistance ECONOMIC DEVELOPMENT ADMINISTRATION, DEPARTMENT OF COMMERCE ECONOMIC... Federal, State and local law....
Variance components in discrete force production tasks.
Varadhan, S K M; Zatsiorsky, Vladimir M; Latash, Mark L
2010-09-01
The study addresses the relationships between task parameters and two components of variance, "good" and "bad", during multi-finger accurate force production. The variance components are defined in the space of commands to the fingers (finger modes) and refer to variance that does ("bad") and does not ("good") affect total force. Based on an earlier study of cyclic force production, we hypothesized that speeding-up an accurate force production task would be accompanied by a drop in the regression coefficient linking the "bad" variance and force rate such that variance of the total force remains largely unaffected. We also explored changes in parameters of anticipatory synergy adjustments with speeding-up the task. The subjects produced accurate ramps of total force over different times and in different directions (force-up and force-down) while pressing with the four fingers of the right hand on individual force sensors. The two variance components were quantified, and their normalized difference was used as an index of a total force stabilizing synergy. "Good" variance scaled linearly with force magnitude and did not depend on force rate. "Bad" variance scaled linearly with force rate within each task, and the scaling coefficient did not change across tasks with different ramp times. As a result, a drop in force ramp time was associated with an increase in total force variance, unlike the results of the study of cyclic tasks. The synergy index dropped 100-200 ms prior to the first visible signs of force change. The timing and magnitude of these anticipatory synergy adjustments did not depend on the ramp time. Analysis of the data within an earlier model has shown adjustments in the variance of a timing parameter, although these adjustments were not as pronounced as in the earlier study of cyclic force production. Overall, we observed qualitative differences between the discrete and cyclic force production tasks: Speeding-up the cyclic tasks was associated with
Discrimination of frequency variance for tonal sequencesa)
Byrne, Andrew J.; Viemeister, Neal F.; Stellmack, Mark A.
2014-01-01
Real-world auditory stimuli are highly variable across occurrences and sources. The present study examined the sensitivity of human listeners to differences in global stimulus variability. In a two-interval, forced-choice task, variance discrimination was measured using sequences of five 100-ms tone pulses. The frequency of each pulse was sampled randomly from a distribution that was Gaussian in logarithmic frequency. In the non-signal interval, the sampled distribution had a variance of σSTA...
Variational bayesian method of estimating variance components.
Arakawa, Aisaku; Taniguchi, Masaaki; Hayashi, Takeshi; Mikawa, Satoshi
2016-07-01
We developed a Bayesian analysis approach by using a variational inference method, a so-called variational Bayesian method, to determine the posterior distributions of variance components. This variational Bayesian method and an alternative Bayesian method using Gibbs sampling were compared in estimating genetic and residual variance components from both simulated data and publically available real pig data. In the simulated data set, we observed strong bias toward overestimation of genetic variance for the variational Bayesian method in the case of low heritability and low population size, and less bias was detected with larger population sizes in both methods examined. The differences in the estimates of variance components between the variational Bayesian and the Gibbs sampling were not found in the real pig data. However, the posterior distributions of the variance components obtained with the variational Bayesian method had shorter tails than those obtained with the Gibbs sampling. Consequently, the posterior standard deviations of the genetic and residual variances of the variational Bayesian method were lower than those of the method using Gibbs sampling. The computing time required was much shorter with the variational Bayesian method than with the method using Gibbs sampling.
The Variance Composition of Firm Growth Rates
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.
Shao, Charles Y; Mirra, Suzanne S; Sait, Hameetha B R; Sacktor, Todd C; Sigurdsson, Einar M
2011-09-01
Impairment of synaptic plasticity underlies memory dysfunction in Alzheimer's disease (AD). Molecules involved in this plasticity such as PSD-95, a major postsynaptic scaffold protein at excitatory synapses, may play an important role in AD pathogenesis. We examined the distribution of PSD-95 in transgenic mice of amyloidopathy (5XFAD) and tauopathy (JNPL3) as well as in AD brains using double-labeling immunofluorescence and confocal microscopy. In wild type control mice, PSD-95 primarily labeled neuropil with distinct distribution in hippocampal apical dendrites. In 3-month-old 5XFAD mice, PSD-95 distribution was similar to that of wild type mice despite significant Aβ deposition. However, in 6-month-old 5XFAD mice, PSD-95 immunoreactivity in apical dendrites markedly decreased and prominent immunoreactivity was noted in neuronal soma in CA1 neurons. Similarly, PSD-95 immunoreactivity disappeared from apical dendrites and accumulated in neuronal soma in 14-month-old, but not in 3-month-old, JNPL3 mice. In AD brains, PSD-95 accumulated in Hirano bodies in hippocampal neurons. Our findings support the notion that either Aβ or tau can induce reduction of PSD-95 in excitatory synapses in hippocampus. Furthermore, this PSD-95 reduction is not an early event but occurs as the pathologies advance. Thus, the time-dependent PSD-95 reduction from synapses and accumulation in neuronal soma in transgenic mice and Hirano bodies in AD may mark postsynaptic degeneration that underlies long-term functional deficits.
Guimarães, José Roberto; Franco, Regina Maura Bueno; Guadagnini, Regiane Aparecida; dos Santos, Luciana Urbano
2014-01-01
This study evaluated the effect of peroxidation assisted by ultraviolet radiation (H2O2/UV), which is an advanced oxidation process (AOP), on Giardia duodenalis cysts. The cysts were inoculated in synthetic and surface water using a concentration of 12 g H2O2 L−1 and a UV dose (λ = 254 nm) of 5,480 mJcm−2. The aqueous solutions were concentrated using membrane filtration, and the organisms were observed using a direct immunofluorescence assay (IFA). The AOP was effective in reducing the number of G. duodenalis cysts in synthetic and surface water and was most effective in reducing the fluorescence of the cyst walls that were present in the surface water. The AOP showed a higher deleterious potential for G. duodenalis cysts than either peroxidation (H2O2) or photolysis (UV) processes alone. PMID:27379301
Brausch, J. F.; Motsinger, R. E.; Hoerst, D. J.
1986-01-01
Ten scale-model nozzles were tested in an anechoic free-jet facility to evaluate the acoustic characteristics of a mechanically suppressed inverted-velocity-profile coannular nozzle with an accoustically treated ejector system. The nozzle system used was developed from aerodynamic flow lines evolved in a previous contract, defined to incorporate the restraints imposed by the aerodynamic performance requirements of an Advanced Supersonic Technology/Variable Cycle Engine system through all its mission phases. Accoustic data of 188 test points were obtained, 87 under static and 101 under simulated flight conditions. The tests investigated variables of hardwall ejector application to a coannular nozzle with 20-chute outer annular suppressor, ejector axial positioning, treatment application to ejector and plug surfaces, and treatment design. Laser velocimeter, shadowgraph photograph, aerodynamic static pressure, and temperature measurement were acquired on select models to yield diagnositc information regarding the flow field and aerodynamic performance characteristics of the nozzles.
O' Connor, Patrick [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Rugani, Kelsey [Kearns & West, Inc., San Francisco, CA (United States); West, Anna [Kearns & West, Inc., San Francisco, CA (United States)
2016-03-01
On behalf of the U.S. Department of Energy (DOE) Wind and Water Power Technology Office (WWPTO), Oak Ridge National Laboratory (ORNL), hosted a day and half long workshop on November 5 and 6, 2015 in the Washington, D.C. metro area to discuss cost reduction opportunities in the development of hydropower projects. The workshop had a further targeted focus on the costs of small, low-head1 facilities at both non-powered dams (NPDs) and along undeveloped stream reaches (also known as New Stream-Reach Development or “NSD”). Workshop participants included a cross-section of seasoned experts, including project owners and developers, engineering and construction experts, conventional and next-generation equipment manufacturers, and others to identify the most promising ways to reduce costs and achieve improvements for hydropower projects.
Hasegawa, Ken R.
2000-12-01
MSMP and BAMM were commissioned by the Air Force Space Division (AFSD) in the late seventies to generate data in support of the Advanced Warning System (AWS), a development activity to replace the space-based surveillance satellites of the Defense Support Program (DSP). These programs were carried out by the Air Force Geophysics Laboratory with planning and mentoring by Irving Spiro of The Aerospace Corporation, acting on behalf of the program managers, 1st Lt. Todd Frantz, 1st Lt. Gordon Frantom, and 1st Lt. Ken Hasegawa of the technology program office at AFSD. The motivation of MSMP was the need for characterizing the exhaust plumes of the thrusters aboard post-boost vehicles, a primary target for the infrared sensors of the proposed AWS system. To that end, the experiments consisted of a series of Aries rocket launches from White Sands Missile Range in which dual payloads were carried aloft and separately deployed at altitudes above 100 km. One module contained an ensemble of sensors spanning the spectrum from the vacuum ultraviolet to the long wave infrared, all slaved to an rf tracker locked onto a beacon on the target module. The target was a small pressure-fed liquid-propellant rocket engine, a modified Atlas vernier, programmed for a series of maneuvers in the vicinity of the instrument module. As part of this program, diagnostic measurements of the target engine exhaust were made at Rocketdyne, and shock tube experiments on excitation processes were carried out by staff members of Calspan.
NONE
1997-01-01
The team of Arthur D. Little, Tufts University and Engelhard Corporation are conducting Phase 1 of a four and a half year, two-phase effort to develop and scale-up an advanced byproduct recovery technology that is a direct, single-stage, catalytic process for converting sulfur dioxide to elemental sulfur. This catalytic process reduces SO{sub 2} over a fluorite-type oxide (such as ceria and zirconia). The catalytic activity can be significantly promoted by active transition metals, such as copper. More than 95% elemental sulfur yield, corresponding to almost complete sulfur dioxide conversion, was obtained over a Cu-Ce-O oxide catalyst as part of an on-going DOE-sponsored, University Coal Research Program. This type of mixed metal oxide catalyst has stable activity, high selectivity for sulfur production, and is resistant to water and carbon dioxide poisoning. Tests with CO and CH{sub 4} reducing gases indicate that the catalyst has the potential for flexibility with regard to the composition of the reducing gas, making it attractive for utility use. The performance of the catalyst is consistently good over a range of SO{sub 2} inlet concentration (0.1 to 10%) indicating its flexibility in treating SO{sub 2} tail gases as well as high concentration streams.
Derk-Jan Dijk
Full Text Available BACKGROUND: The phase and amplitude of rhythms in physiology and behavior are generated by circadian oscillators and entrained to the 24-h day by exposure to the light-dark cycle and feedback from the sleep-wake cycle. The extent to which the phase and amplitude of multiple rhythms are similarly affected during altered timing of light exposure and the sleep-wake cycle has not been fully characterized. METHODOLOGY/PRINCIPAL FINDINGS: We assessed the phase and amplitude of the rhythms of melatonin, core body temperature, cortisol, alertness, performance and sleep after a perturbation of entrainment by a gradual advance of the sleep-wake schedule (10 h in 5 days and associated light-dark cycle in 14 healthy men. The light-dark cycle consisted either of moderate intensity 'room' light (∼90-150 lux or moderate light supplemented with bright light (∼10,000 lux for 5 to 8 hours following sleep. After the advance of the sleep-wake schedule in moderate light, no significant advance of the melatonin rhythm was observed whereas, after bright light supplementation the phase advance was 8.1 h (SEM 0.7 h. Individual differences in phase shifts correlated across variables. The amplitude of the melatonin rhythm assessed under constant conditions was reduced after moderate light by 54% (17-94% and after bright light by 52% (range 12-84%, as compared to the amplitude at baseline in the presence of a sleep-wake cycle. Individual differences in amplitude reduction of the melatonin rhythm correlated with the amplitude of body temperature, cortisol and alertness. CONCLUSIONS/SIGNIFICANCE: Alterations in the timing of the sleep-wake cycle and associated bright or moderate light exposure can lead to changes in phase and reduction of circadian amplitude which are consistent across multiple variables but differ between individuals. These data have implications for our understanding of circadian organization and the negative health outcomes associated with shift
Estimating Predictive Variance for Statistical Gas Distribution Modelling
Lilienthal, Achim J.; Asadi, Sahar; Reggente, Matteo
2009-05-01
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.
Modality-Driven Classification and Visualization of Ensemble Variance
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.
Discrimination of frequency variance for tonal sequences.
Byrne, Andrew J; Viemeister, Neal F; Stellmack, Mark A
2014-12-01
Real-world auditory stimuli are highly variable across occurrences and sources. The present study examined the sensitivity of human listeners to differences in global stimulus variability. In a two-interval, forced-choice task, variance discrimination was measured using sequences of five 100-ms tone pulses. The frequency of each pulse was sampled randomly from a distribution that was Gaussian in logarithmic frequency. In the non-signal interval, the sampled distribution had a variance of σSTAN (2), while in the signal interval, the variance of the sequence was σSIG (2) (with σSIG (2) > σSTAN (2)). The listener's task was to choose the interval with the larger variance. To constrain possible decision strategies, the mean frequency of the sampling distribution of each interval was randomly chosen for each presentation. Psychometric functions were measured for various values of σSTAN (2). Although the performance was remarkably similar across listeners, overall performance was poorer than that of an ideal observer (IO) which perfectly compares interval variances. However, like the IO, Weber's Law behavior was observed, with a constant ratio of ( σSIG (2)- σSTAN (2)) to σSTAN (2) yielding similar performance. A model which degraded the IO with a frequency-resolution noise and a computational noise provided a reasonable fit to the real data.
NiCo2O4/N-doped graphene as an advanced electrocatalyst for oxygen reduction reaction
Zhang, Hui; Li, Huiyong; Wang, Haiyan; He, Kejian; Wang, Shuangyin; Tang, Yougen; Chen, Jiajie
2015-04-01
Developing low-cost catalyst for high-performance oxygen reduction reaction (ORR) is highly desirable. Herein, NiCo2O4/N-doped reduced graphene oxide (NiCo2O4/N-rGO) hybrid is proposed as a high-performance catalyst for ORR for the first time. The well-formed NiCo2O4/N-rGO hybrid is studied by cyclic voltammetry (CV) curves and linear-sweep voltammetry (LSV) performed on the rotating-ring-disk-electrode (RDE) in comparison with N-rGO-free NiCo2O4 and the bare N-rGO. Due to the synergistic effect, the NiCo2O4/N-rGO hybrid exhibits significant improvement of catalytic performance with an onset potential of -0.12 V, which mainly favors a direct four electron pathway in ORR process, close to the behavior of commercial carbon-supported Pt. Also, the benefits of N-incorporation are investigated by comparing NiCo2O4/N-rGO with NiCo2O4/rGO, where higher cathodic currents, much more positive half-wave potential and more electron transfer numbers are observed for the N-doping one, which should be ascribed to the new highly efficient active sites created by N incorporation into graphene. The NiCo2O4/N-rGO hybrid could be used as a promising catalyst for high power metal/air battery.
Estimating quadratic variation using realized variance
Barndorff-Nielsen, Ole Eiler; Shephard, N.
2002-01-01
This paper looks at some recent work on estimating quadratic variation using realized variance (RV) - that is, sums of M squared returns. This econometrics has been motivated by the advent of the common availability of high-frequency financial return data. When the underlying process is a semimar......This paper looks at some recent work on estimating quadratic variation using realized variance (RV) - that is, sums of M squared returns. This econometrics has been motivated by the advent of the common availability of high-frequency financial return data. When the underlying process...... 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....
Fritz, Jan; Thawait, Gaurav K. [Johns Hopkins University School of Medicine, Russell H. Morgan Department of Radiology and Radiological Science, Section of Musculoskeletal Radiology, Baltimore, MD (United States); Fritz, Benjamin [University of Freiburg, Department of Radiology, Freiburg im Breisgau (Germany); Raithel, Esther; Nittka, Mathias [Siemens Healthcare GmbH, Erlangen (Germany); Gilson, Wesley D. [Siemens Healthcare USA, Inc., Baltimore, MD (United States); Mont, Michael A. [Cleveland Clinic Foundation, Department of Orthopedic Surgery, Cleveland, OH (United States)
2016-10-15
Compressed sensing (CS) acceleration has been theorized for slice encoding for metal artifact correction (SEMAC), but has not been shown to be feasible. Therefore, we tested the hypothesis that CS-SEMAC is feasible for MRI of metal-on-metal hip resurfacing implants. Following prospective institutional review board approval, 22 subjects with metal-on-metal hip resurfacing implants underwent 1.5 T MRI. We compared CS-SEMAC prototype, high-bandwidth TSE, and SEMAC sequences with acquisition times of 4-5, 4-5 and 10-12 min, respectively. Outcome measures included bone-implant interfaces, image quality, periprosthetic structures, artifact size, and signal- and contrast-to-noise ratios (SNR and CNR). Using Friedman, repeated measures analysis of variances, and Cohen's weighted kappa tests, Bonferroni-corrected p-values of 0.005 and less were considered statistically significant. There was no statistical difference of outcomes measures of SEMAC and CS-SEMAC images. Visibility of implant-bone interfaces and pseudocapsule as well as fat suppression and metal reduction were ''adequate'' to ''good'' on CS-SEMAC and ''non-diagnostic'' to ''adequate'' on high-BW TSE (p < 0.001, respectively). SEMAC and CS-SEMAC showed mild blur and ripple artifacts. The metal artifact size was 63 % larger for high-BW TSE as compared to SEMAC and CS-SEMAC (p < 0.0001, respectively). CNRs were sufficiently high and statistically similar, with the exception of CNR of fluid and muscle and CNR of fluid and tendon, which were higher on intermediate-weighted high-BW TSE (p < 0.005, respectively). Compressed sensing acceleration enables the time-neutral use of SEMAC for MRI of metal-on-metal hip resurfacing implants when compared to high-BW TSE and image quality similar to conventional SEMAC. (orig.)
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.
Kalman filtering techniques for reducing variance of digital speckle displacement measurement noise
Donghui Li; Li Guo
2006-01-01
@@ Target dynamics are assumed to be known in measuring digital speckle displacement. Use is made of a simple measurement equation, where measurement noise represents the effect of disturbances introduced in measurement process. From these assumptions, Kalman filter can be designed to reduce variance of measurement noise. An optical and analysis system was set up, by which object motion with constant displacement and constant velocity is experimented with to verify validity of Kalman filtering techniques for reduction of measurement noise variance.
Sources of variance in ocular microtremor.
Sheahan, N F; Coakley, D; Bolger, C; O'Neill, D; Fry, G; Phillips, J; Malone, J F
1994-02-01
This study presents a preliminary investigation of the sources of variance in the measurement of ocular microtremor frequency in a normal population. When the results from both experienced and relatively inexperienced operators are pooled, factors that contribute significantly to the total variance include the measurement procedure (p < 0.001), day-to-day variations within subjects (p < 0.001), and inter-subject differences (p < 0.01). Operator experience plays a role in determining the measurement precision: the intra-subject coefficient of variation is about 5% for a very experienced operator, and about 14% for a relatively inexperienced operator.
Managing product inherent variance during treatment
Verdenius, F.
1996-01-01
The natural variance of agricultural product parameters complicates recipe planning for product treatment, i.e. the process of transforming a product batch from its initial state to a prespecified final state. For a specific product P, recipes are currently composed by human experts on the basis of
The Variance of Language in Different Contexts
申一宁
2012-01-01
language can be quite different (here referring to the meaning) in different contexts. And there are 3 categories of context: the culture, the situation and the cotext. In this article, we will analysis the variance of language in each of the 3 aspects. This article is written for the purpose of making people understand the meaning of a language under specific better.
Regression calibration with heteroscedastic error variance.
Spiegelman, Donna; Logan, Roger; Grove, Douglas
2011-01-01
The problem of covariate measurement error with heteroscedastic measurement error variance is considered. Standard regression calibration assumes that the measurement error has a homoscedastic measurement error variance. An estimator is proposed to correct regression coefficients for covariate measurement error with heteroscedastic variance. Point and interval estimates are derived. Validation data containing the gold standard must be available. This estimator is a closed-form correction of the uncorrected primary regression coefficients, which may be of logistic or Cox proportional hazards model form, and is closely related to the version of regression calibration developed by Rosner et al. (1990). The primary regression model can include multiple covariates measured without error. The use of these estimators is illustrated in two data sets, one taken from occupational epidemiology (the ACE study) and one taken from nutritional epidemiology (the Nurses' Health Study). In both cases, although there was evidence of moderate heteroscedasticity, there was little difference in estimation or inference using this new procedure compared to standard regression calibration. It is shown theoretically that unless the relative risk is large or measurement error severe, standard regression calibration approximations will typically be adequate, even with moderate heteroscedasticity in the measurement error model variance. In a detailed simulation study, standard regression calibration performed either as well as or better than the new estimator. When the disease is rare and the errors normally distributed, or when measurement error is moderate, standard regression calibration remains the method of choice.
Formative Use of Intuitive Analysis of Variance
Trumpower, David L.
2013-01-01
Students' informal inferential reasoning (IIR) is often inconsistent with the normative logic underlying formal statistical methods such as Analysis of Variance (ANOVA), even after instruction. In two experiments reported here, student's IIR was assessed using an intuitive ANOVA task at the beginning and end of a statistics course. In…
Linear transformations of variance/covariance matrices
Parois, P.J.A.; Lutz, M.
2011-01-01
Many applications in crystallography require the use of linear transformations on parameters and their standard uncertainties. While the transformation of the parameters is textbook knowledge, the transformation of the standard uncertainties is more complicated and needs the full variance/covariance
Decomposition of variance for spatial Cox processes
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
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...
Decomposition of variance for spatial Cox processes
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...
40 CFR 142.43 - Disposition of a variance request.
2010-07-01
... during the period of variance shall specify interim treatment techniques, methods and equipment, and... the specified treatment technique for which the variance was granted is necessary to protect...
Thomas, Reju George; Moon, Myeong Ju; Kim, Jo Heon; Lee, Jae Hyuk; Jeong, Yong Yeon
2015-01-01
Advanced hepatic fibrosis therapy using drug-delivering nanoparticles is a relatively unexplored area. Angiotensin type 1 (AT1) receptor blockers such as losartan can be delivered to hepatic stellate cells (HSC), blocking their activation and thereby reducing fibrosis progression in the liver. In our study, we analyzed the possibility of utilizing drug-loaded vehicles such as hyaluronic acid (HA) micelles carrying losartan to attenuate HSC activation. Losartan, which exhibits inherent lipophilicity, was loaded into the hydrophobic core of HA micelles with a 19.5% drug loading efficiency. An advanced liver fibrosis model was developed using C3H/HeN mice subjected to 20 weeks of prolonged TAA/ethanol weight-adapted treatment. The cytocompatibility and cell uptake profile of losartan-HA micelles were studied in murine fibroblast cells (NIH3T3), human hepatic stellate cells (hHSC) and FL83B cells (hepatocyte cell line). The ability of these nanoparticles to attenuate HSC activation was studied in activated HSC cells based on alpha smooth muscle actin (α-sma) expression. Mice treated with oral losartan or losartan-HA micelles were analyzed for serum enzyme levels (ALT/AST, CK and LDH) and collagen deposition (hydroxyproline levels) in the liver. The accumulation of HA micelles was observed in fibrotic livers, which suggests increased delivery of losartan compared to normal livers and specific uptake by HSC. Active reduction of α-sma was observed in hHSC and the liver sections of losartan-HA micelle-treated mice. The serum enzyme levels and collagen deposition of losartan-HA micelle-treated mice was reduced significantly compared to the oral losartan group. Losartan-HA micelles demonstrated significant attenuation of hepatic fibrosis via an HSC-targeting mechanism in our in vitro and in vivo studies. These nanoparticles can be considered as an alternative therapy for liver fibrosis.
Bias-variance decomposition in Genetic Programming
Kowaliw Taras
2016-01-01
Full Text Available We study properties of Linear Genetic Programming (LGP through several regression and classification benchmarks. In each problem, we decompose the results into bias and variance components, and explore the effect of varying certain key parameters on the overall error and its decomposed contributions. These parameters are the maximum program size, the initial population, and the function set used. We confirm and quantify several insights into the practical usage of GP, most notably that (a the variance between runs is primarily due to initialization rather than the selection of training samples, (b parameters can be reasonably optimized to obtain gains in efficacy, and (c functions detrimental to evolvability are easily eliminated, while functions well-suited to the problem can greatly improve performance—therefore, larger and more diverse function sets are always preferable.
Realized Variance and Market Microstructure Noise
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...
Linear transformations of variance/covariance matrices.
Parois, Pascal; Lutz, Martin
2011-07-01
Many applications in crystallography require the use of linear transformations on parameters and their standard uncertainties. While the transformation of the parameters is textbook knowledge, the transformation of the standard uncertainties is more complicated and needs the full variance/covariance matrix. For the transformation of second-rank tensors it is suggested that the 3 × 3 matrix is re-written into a 9 × 1 vector. The transformation of the corresponding variance/covariance matrix is then straightforward and easily implemented into computer software. This method is applied in the transformation of anisotropic displacement parameters, the calculation of equivalent isotropic displacement parameters, the comparison of refinements in different space-group settings and the calculation of standard uncertainties of eigenvalues.
Variance and covariance of accumulated displacement estimates.
Bayer, Matthew; Hall, Timothy J
2013-04-01
Tracking large deformations in tissue using ultrasound can enable the reconstruction of nonlinear elastic parameters, but poses a challenge to displacement estimation algorithms. Such large deformations have to be broken up into steps, each of which contributes an estimation error to the final accumulated displacement map. The work reported here measured the error variance for single-step and accumulated displacement estimates using one-dimensional numerical simulations of ultrasound echo signals, subjected to tissue strain and electronic noise. The covariance between accumulation steps was also computed. These simulations show that errors due to electronic noise are negatively correlated between steps, and therefore accumulate slowly, whereas errors due to tissue deformation are positively correlated and accumulate quickly. For reasonably low electronic noise levels, the error variance in the accumulated displacement estimates is remarkably constant as a function of step size, but increases with the length of the tracking kernel.
Realized Variance and Market Microstructure Noise
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
Zakharov, Leonid E.; Lewandowski, Jerome; Foley, Elizabeth L.; Levinton, Fred M.; Yuh, Howard Y.; Drozdov, Vladimir; McDonald, Darren
2008-01-14
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.
Eigenvalue variance bounds for covariance matrices
Dallaporta, Sandrine
2013-01-01
This work is concerned with finite range bounds on the variance of individual eigenvalues of random covariance matrices, both in the bulk and at the edge of the spectrum. In a preceding paper, the author established analogous results for Wigner matrices and stated the results for covariance matrices. They are proved in the present paper. Relying on the LUE example, which needs to be investigated first, the main bounds are extended to complex covariance matrices by means of the Tao, Vu and Wan...
High-dimensional regression with unknown variance
Giraud, Christophe; Verzelen, Nicolas
2011-01-01
We review recent results for high-dimensional sparse linear regression in the practical case of unknown variance. Different sparsity settings are covered, including coordinate-sparsity, group-sparsity and variation-sparsity. The emphasize is put on non-asymptotic analyses and feasible procedures. In addition, a small numerical study compares the practical performance of three schemes for tuning the Lasso esti- mator and some references are collected for some more general models, including multivariate regression and nonparametric regression.
Fractional constant elasticity of variance model
Ngai Hang Chan; Chi Tim Ng
2007-01-01
This paper develops a European option pricing formula for fractional market models. Although there exist option pricing results for a fractional Black-Scholes model, they are established without accounting for stochastic volatility. In this paper, a fractional version of the Constant Elasticity of Variance (CEV) model is developed. European option pricing formula similar to that of the classical CEV model is obtained and a volatility skew pattern is revealed.
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.
Applications of non-parametric statistics and analysis of variance on sample variances
Myers, R. H.
1981-01-01
Nonparametric methods that are available for NASA-type applications are discussed. An attempt will be made here to survey what can be used, to attempt recommendations as to when each would be applicable, and to compare the methods, when possible, with the usual normal-theory procedures that are avavilable for the Gaussion analog. It is important here to point out the hypotheses that are being tested, the assumptions that are being made, and limitations of the nonparametric procedures. The appropriateness of doing analysis of variance on sample variances are also discussed and studied. This procedure is followed in several NASA simulation projects. On the surface this would appear to be reasonably sound procedure. However, difficulties involved center around the normality problem and the basic homogeneous variance assumption that is mase in usual analysis of variance problems. These difficulties discussed and guidelines given for using the methods.
Williams, Hants; Simmons, Leigh Ann; Tanabe, Paula
2015-09-01
The aim of this article is to discuss how advanced practice nurses (APNs) can incorporate mindfulness-based stress reduction (MBSR) as a nonpharmacologic clinical tool in their practice. Over the last 30 years, patients and providers have increasingly used complementary and holistic therapies for the nonpharmacologic management of acute and chronic diseases. Mindfulness-based interventions, specifically MBSR, have been tested and applied within a variety of patient populations. There is strong evidence to support that the use of MBSR can improve a range of biological and psychological outcomes in a variety of medical illnesses, including acute and chronic pain, hypertension, and disease prevention. This article will review the many ways APNs can incorporate MBSR approaches for health promotion and disease/symptom management into their practice. We conclude with a discussion of how nurses can obtain training and certification in MBSR. Given the significant and growing literature supporting the use of MBSR in the prevention and treatment of chronic disease, increased attention on how APNs can incorporate MBSR into clinical practice is necessary. © The Author(s) 2015.
The Parabolic variance (PVAR), a wavelet variance based on least-square fit
Vernotte, F; Bourgeois, P -Y; Rubiola, E
2015-01-01
The Allan variance (AVAR) is one option among the wavelet variances. However a milestone in the analysis of frequency fluctuations and in the long-term stability of clocks, and certainly the most widely used one, AVAR is not suitable when fast noise processes show up, chiefly because of the poor rejection of white phase noise. The modified Allan variance (MVAR) features high resolution in the presence of white PM noise, but it is poorer for slow phenomena because the wavelet spans over 50% longer time. This article introduces the Parabolic Variance (PVAR), a wavelet variance similar to the Allan variance, based on the Linear Regression (LR) of phase data. The PVAR relates to the Omega frequency counter, which is the topics of a companion article [the reference to the article, or to the ArXiv manuscript, will be provided later]. The PVAR wavelet spans over 2 tau, the same of the AVAR wavelet. After setting the theoretical framework, we analyze the degrees of freedom and the detection of weak noise processes in...
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
Variance of gene expression identifies altered network constraints in neurological disease.
Jessica C Mar
2011-08-01
Full Text Available Gene expression analysis has become a ubiquitous tool for studying a wide range of human diseases. In a typical analysis we compare distinct phenotypic groups and attempt to identify genes that are, on average, significantly different between them. Here we describe an innovative approach to the analysis of gene expression data, one that identifies differences in expression variance between groups as an informative metric of the group phenotype. We find that genes with different expression variance profiles are not randomly distributed across cell signaling networks. Genes with low-expression variance, or higher constraint, are significantly more connected to other network members and tend to function as core members of signal transduction pathways. Genes with higher expression variance have fewer network connections and also tend to sit on the periphery of the cell. Using neural stem cells derived from patients suffering from Schizophrenia (SZ, Parkinson's disease (PD, and a healthy control group, we find marked differences in expression variance in cell signaling pathways that shed new light on potential mechanisms associated with these diverse neurological disorders. In particular, we find that expression variance of core networks in the SZ patient group was considerably constrained, while in contrast the PD patient group demonstrated much greater variance than expected. One hypothesis is that diminished variance in SZ patients corresponds to an increased degree of constraint in these pathways and a corresponding reduction in robustness of the stem cell networks. These results underscore the role that variation plays in biological systems and suggest that analysis of expression variance is far more important in disease than previously recognized. Furthermore, modeling patterns of variability in gene expression could fundamentally alter the way in which we think about how cellular networks are affected by disease processes.
A relation between information entropy and variance
Pandey, Biswajit
2016-01-01
We obtain an analytic relation between the information entropy and the variance of a distribution in the regime of small fluctuations. We use a set of Monte Carlo simulations of different homogeneous and inhomogeneous distributions to verify the relation and also test it in a set of cosmological N-body simulations. We find that the relation is in excellent agreement with the simulations and is independent of number density and the nature of the distributions. The relation would help us to relate entropy to other conventional measures and widen its scope.
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...
EXPLANATORY VARIANCE IN MAXIMAL OXYGEN UPTAKE
Jacalyn J. Robert McComb
2006-06-01
Full Text Available The purpose of this study was to develop a prediction equation that could be used to estimate maximal oxygen uptake (VO2max from a submaximal water running protocol. Thirty-two volunteers (n =19 males, n = 13 females, ages 18 - 24 years, underwent the following testing procedures: (a a 7-site skin fold assessment; (b a land VO2max running treadmill test; and (c a 6 min water running test. For the water running submaximal protocol, the participants were fitted with an Aqua Jogger Classic Uni-Sex Belt and a Polar Heart Rate Monitor; the participants' head, shoulders, hips and feet were vertically aligned, using a modified running/bicycle motion. A regression model was used to predict VO2max. The criterion variable, VO2max, was measured using open-circuit calorimetry utilizing the Bruce Treadmill Protocol. Predictor variables included in the model were percent body fat (% BF, height, weight, gender, and heart rate following a 6 min water running protocol. Percent body fat accounted for 76% (r = -0.87, SEE = 3.27 of the variance in VO2max. No other variables significantly contributed to the explained variance in VO2max. The equation for the estimation of VO2max is as follows: VO2max ml.kg-1·min-1 = 56.14 - 0.92 (% BF.
A Mean-variance Problem in the Constant Elasticity of Variance (CEV) Mo del
Hou Ying-li; Liu Guo-xin; Jiang Chun-lan
2015-01-01
In this paper, we focus on a constant elasticity of variance (CEV) model and want to find its optimal strategies for a mean-variance problem under two con-strained controls: reinsurance/new business and investment (no-shorting). First, a Lagrange multiplier is introduced to simplify the mean-variance problem and the corresponding Hamilton-Jacobi-Bellman (HJB) equation is established. Via a power transformation technique and variable change method, the optimal strategies with the Lagrange multiplier are obtained. Final, based on the Lagrange duality theorem, the optimal strategies and optimal value for the original problem (i.e., the eﬃcient strategies and eﬃcient frontier) are derived explicitly.
Dynamics of Variance Risk Premia, Investors' Sentiment and Return Predictability
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 realized variances, our model allows to infer the occurrence and size of extreme variance events, and construct indicators signalling agents sentiment towards future market conditions. Our results show that excess returns are to a large extent explained by fear or optimism towards future extreme variance...
The value of travel time variance
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....
Power Estimation in Multivariate Analysis of Variance
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.
Expected Stock Returns and Variance Risk Premia
Bollerslev, Tim; Tauchen, George; Zhou, Hao
Motivated by the implications from a stylized self-contained general equilibrium model incorporating the effects of time-varying economic uncertainty, we show that the difference between implied and realized variation, or the variance risk premium, is able to explain a non-trivial fraction...... of the time series variation in post 1990 aggregate stock market returns, with high (low) premia predicting high (low) future returns. Our empirical results depend crucially on the use of "model-free," as opposed to Black- Scholes, options implied volatilities, along with accurate realized variation measures...... constructed from high-frequency intraday, as opposed to daily, data. The magnitude of the predictability is particularly strong at the intermediate quarterly return horizon, where it dominates that afforded by other popular predictor variables, like the P/E ratio, the default spread, and the consumption...
The Parabolic Variance (PVAR): A Wavelet Variance Based on the Least-Square Fit.
Vernotte, Francois; Lenczner, Michel; Bourgeois, Pierre-Yves; Rubiola, Enrico
2016-04-01
This paper introduces the parabolic variance (PVAR), a wavelet variance similar to the Allan variance (AVAR), based on the linear regression (LR) of phase data. The companion article arXiv:1506.05009 [physics.ins-det] details the Ω frequency counter, which implements the LR estimate. The PVAR combines the advantages of AVAR and modified AVAR (MVAR). PVAR is good for long-term analysis because the wavelet spans over 2τ, the same as the AVAR wavelet, and good for short-term analysis because the response to white and flicker PM is 1/τ(3) and 1/τ(2), the same as the MVAR. After setting the theoretical framework, we study the degrees of freedom and the confidence interval for the most common noise types. Then, we focus on the detection of a weak noise process at the transition-or corner-where a faster process rolls off. This new perspective raises the question of which variance detects the weak process with the shortest data record. Our simulations show that PVAR is a fortunate tradeoff. PVAR is superior to MVAR in all cases, exhibits the best ability to divide between fast noise phenomena (up to flicker FM), and is almost as good as AVAR for the detection of random walk and drift.
Genomic variance estimates: With or without disequilibrium covariances?
Lehermeier, C; de Los Campos, G; Wimmer, V; Schön, C-C
2017-06-01
Whole-genome regression methods are often used for estimating genomic heritability: the proportion of phenotypic variance that can be explained by regression on marker genotypes. Recently, there has been an intensive debate on whether and how to account for the contribution of linkage disequilibrium (LD) to genomic variance. Here, we investigate two different methods for genomic variance estimation that differ in their ability to account for LD. By analysing flowering time in a data set on 1,057 fully sequenced Arabidopsis lines with strong evidence for diversifying selection, we observed a large contribution of covariances between quantitative trait loci (QTL) to the genomic variance. The classical estimate of genomic variance that ignores covariances underestimated the genomic variance in the data. The second method accounts for LD explicitly and leads to genomic variance estimates that when added to error variance estimates match the sample variance of phenotypes. This method also allows estimating the covariance between sets of markers when partitioning the genome into subunits. Large covariance estimates between the five Arabidopsis chromosomes indicated that the population structure in the data led to strong LD also between physically unlinked QTL. By consecutively removing population structure from the phenotypic variance using principal component analysis, we show how population structure affects the magnitude of LD contribution and the genomic variance estimates obtained with the two methods. © 2017 Blackwell Verlag GmbH.
Characterizing nonconstant instrumental variance in emerging miniaturized analytical techniques.
Noblitt, Scott D; Berg, Kathleen E; Cate, David M; Henry, Charles S
2016-04-01
Measurement variance is a crucial aspect of quantitative chemical analysis. Variance directly affects important analytical figures of merit, including detection limit, quantitation limit, and confidence intervals. Most reported analyses for emerging analytical techniques implicitly assume constant variance (homoskedasticity) by using unweighted regression calibrations. Despite the assumption of constant variance, it is known that most instruments exhibit heteroskedasticity, where variance changes with signal intensity. Ignoring nonconstant variance results in suboptimal calibrations, invalid uncertainty estimates, and incorrect detection limits. Three techniques where homoskedasticity is often assumed were covered in this work to evaluate if heteroskedasticity had a significant quantitative impact-naked-eye, distance-based detection using paper-based analytical devices (PADs), cathodic stripping voltammetry (CSV) with disposable carbon-ink electrode devices, and microchip electrophoresis (MCE) with conductivity detection. Despite these techniques representing a wide range of chemistries and precision, heteroskedastic behavior was confirmed for each. The general variance forms were analyzed, and recommendations for accounting for nonconstant variance discussed. Monte Carlo simulations of instrument responses were performed to quantify the benefits of weighted regression, and the sensitivity to uncertainty in the variance function was tested. Results show that heteroskedasticity should be considered during development of new techniques; even moderate uncertainty (30%) in the variance function still results in weighted regression outperforming unweighted regressions. We recommend utilizing the power model of variance because it is easy to apply, requires little additional experimentation, and produces higher-precision results and more reliable uncertainty estimates than assuming homoskedasticity.
NONE
1996-07-01
This Public Design Report presents the design criteria of a DOE Innovative Clean Coal Technology (ICCT) project demonstrating advanced wall-fired combustion techniques for the reduction of NO{sub x} emissions from coal-fired boilers. The project is being conducted at Georgia Power Company`s Plant Hammond Unit 4 (500 MW) near Rome, Georgia. The technologies being demonstrated at this site include Foster Wheeler Energy Corporation`s advanced overfire air system and Controlled Flow/Split Flame low NO{sub x} burner. This report provides documentation on the design criteria used in the performance of this project as it pertains to the scope involved with the low NO{sub x} burners, advanced overfire systems, and digital control system.
1992-12-31
This quarterly report discusses the technical progress of an Innovative Clean Coal Technology (ICCT) demonstration of advanced wall-fired combustion techniques for the reduction of nitrogen oxide (NO{sub x}) emissions from coal-fired boilers. The project is being conducted at Georgia Power Company`s Plant Hammond Unit 4 located near Rome, Georgia. The primary goal of this project is the characterization of the low NO{sub x} combustion equipment through the collection and analysis of long-term emissions data. A target of achieving fifty percent NO{sub x} reduction using combustion modifications has been established for the project. The project provides a stepwise retrofit of an advanced overfire air (AOFA) system followed by low NO{sub x} burners (LNB). During each test phase of the project, diagnostic, performance, long-term, and verification testing will be performed. These tests are used to quantify the NO{sub x} reductions of each technology and evaluate the effects of those reductions on other combustion parameters such as particulate characteristics and boiler efficiency.
Gene set analysis using variance component tests
2013-01-01
Background 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. Results 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). Conclusion 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. PMID:23806107
Measuring past changes in ENSO variance using Mg/Ca measurements on individual planktic foraminifera
Marchitto, T. M.; Grist, H. R.; van Geen, A.
2013-12-01
Previous work in Soledad Basin, located off Baja California Sur in the eastern subtropical Pacific, supports a La Niña-like mean-state response to enhanced radiative forcing at both orbital and millennial (solar) timescales during the Holocene. Mg/Ca measurements on the planktic foraminifer Globigerina bulloides indicate cooling when insolation is higher, consistent with an ';ocean dynamical thermostat' response that shoals the thermocline and cools the surface in the eastern tropical Pacific. Some, but not all, numerical models simulate reduced ENSO variance (less frequent and/or less intense events) when the Pacific is driven into a La Niña-like mean state by radiative forcing. Hypothetically the question of ENSO variance can be examined by measuring individual planktic foraminiferal tests from within a sample interval. Koutavas et al. (2006) used d18O on single specimens of Globigerinoides ruber from the eastern equatorial Pacific to demonstrate a 50% reduction in variance at ~6 ka compared to ~2 ka, consistent with the sense of the model predictions at the orbital scale. Here we adapt this approach to Mg/Ca and apply it to the millennial-scale question. We present Mg/Ca measured on single specimens of G. bulloides (cold season) and G. ruber (warm season) from three time slices in Soledad Basin: the 20th century, the warm interval (and solar low) at 9.3 ka, and the cold interval (and solar high) at 9.8 ka. Each interval is uniformly sampled over a ~100-yr (~10-cm or more) window to ensure that our variance estimate is not biased by decadal-scale stochastic variability. Theoretically we can distinguish between changing ENSO variability and changing seasonality: a reduction in ENSO variance would result in narrowing of both the G. bulloides and G. ruber temperature distributions without necessarily changing the distance between their two medians; while a reduction in seasonality would cause the two species' distributions to move closer together.
Variance Estimation Using Refitted Cross-validation in Ultrahigh Dimensional Regression
Fan, Jianqing; Hao, Ning
2010-01-01
Variance estimation is a fundamental problem in statistical modeling. In ultrahigh dimensional linear regressions where the dimensionality is much larger than sample size, traditional variance estimation techniques are not applicable. Recent advances on variable selection in ultrahigh dimensional linear regressions make this problem accessible. One of the major problems in ultrahigh dimensional regression is the high spurious correlation between the unobserved realized noise and some of the predictors. As a result, the realized noises are actually predicted when extra irrelevant variables are selected, leading to serious underestimate of the noise level. In this paper, we propose a two-stage refitted procedure via a data splitting technique, called refitted cross-validation (RCV), to attenuate the influence of irrelevant variables with high spurious correlations. Our asymptotic results show that the resulting procedure performs as well as the oracle estimator, which knows in advance the mean regression functi...
Anatomic variance of the iliopsoas tendon.
Philippon, Marc J; Devitt, Brian M; Campbell, Kevin J; Michalski, Max P; Espinoza, Chris; Wijdicks, Coen A; Laprade, Robert F
2014-04-01
The iliopsoas tendon has been implicated as a generator of hip pain and a cause of labral injury due to impingement. Arthroscopic release of the iliopsoas tendon has become a preferred treatment for internal snapping hips. Traditionally, the iliopsoas tendon has been considered the conjoint tendon of the psoas major and iliacus muscles, although anatomic variance has been reported. The iliopsoas tendon consists of 2 discrete tendons in the majority of cases, arising from both the psoas major and iliacus muscles. Descriptive laboratory study. Fifty-three nonmatched, fresh-frozen, cadaveric hemipelvis specimens (average age, 62 years; range, 47-70 years; 29 male and 24 female) were used in this study. The iliopsoas muscle was exposed via a Smith-Petersen approach. A transverse incision across the entire iliopsoas musculotendinous unit was made at the level of the hip joint. Each distinctly identifiable tendon was recorded, and the distance from the lesser trochanter was recorded. The prevalence of a single-, double-, and triple-banded iliopsoas tendon was 28.3%, 64.2%, and 7.5%, respectively. The psoas major tendon was consistently the most medial tendinous structure, and the primary iliacus tendon was found immediately lateral to the psoas major tendon within the belly of the iliacus muscle. When present, an accessory iliacus tendon was located adjacent to the primary iliacus tendon, lateral to the primary iliacus tendon. Once considered a rare anatomic variant, the finding of ≥2 distinct tendinous components to the iliacus and psoas major muscle groups is an important discovery. It is essential to be cognizant of the possibility that more than 1 tendon may exist to ensure complete release during endoscopy. Arthroscopic release of the iliopsoas tendon is a well-accepted surgical treatment for iliopsoas impingement. The most widely used site for tendon release is at the level of the anterior hip joint. The findings of this novel cadaveric anatomy study suggest that
40 CFR 190.11 - Variances for unusual operations.
2010-07-01
... PROTECTION PROGRAMS ENVIRONMENTAL RADIATION PROTECTION STANDARDS FOR NUCLEAR POWER OPERATIONS Environmental Standards for the Uranium Fuel Cycle § 190.11 Variances for unusual operations. The standards specified...
Simulations of the Hadamard Variance: Probability Distributions and Confidence Intervals.
Ashby, Neil; Patla, Bijunath
2016-04-01
Power-law noise in clocks and oscillators can be simulated by Fourier transforming a modified spectrum of white phase noise. This approach has been applied successfully to simulation of the Allan variance and the modified Allan variance in both overlapping and nonoverlapping forms. When significant frequency drift is present in an oscillator, at large sampling times the Allan variance overestimates the intrinsic noise, while the Hadamard variance is insensitive to frequency drift. The simulation method is extended in this paper to predict the Hadamard variance for the common types of power-law noise. Symmetric real matrices are introduced whose traces-the sums of their eigenvalues-are equal to the Hadamard variances, in overlapping or nonoverlapping forms, as well as for the corresponding forms of the modified Hadamard variance. We show that the standard relations between spectral densities and Hadamard variance are obtained with this method. The matrix eigenvalues determine probability distributions for observing a variance at an arbitrary value of the sampling interval τ, and hence for estimating confidence in the measurements.
Network Structure and Biased Variance Estimation in Respondent Driven Sampling.
Ashton M Verdery
Full Text Available 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
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.
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.
Sinha, Neeraj
2014-01-01
This Phase II project validated a state-of-the-art LES model, coupled with a Ffowcs Williams-Hawkings (FW-H) far-field acoustic solver, to support the development of advanced engine concepts. These concepts include innovative flow control strategies to attenuate jet noise emissions. The end-to-end LES/ FW-H noise prediction model was demonstrated and validated by applying it to rectangular nozzle designs with a high aspect ratio. The model also was validated against acoustic and flow-field data from a realistic jet-pylon experiment, thereby significantly advancing the state of the art for LES.
Marini, Federico; de Beer, Dalene; Joubert, Elizabeth; Walczak, Beata
2015-07-31
Direct application of popular approaches, e.g., Principal Component Analysis (PCA) or Partial Least Squares (PLS) to chromatographic data originating from a well-designed experimental study including more than one factor is not recommended. In the case of a well-designed experiment involving two or more factors (crossed or nested), data are usually decomposed into the contributions associated with the studied factors (and with their interactions), and the individual effect matrices are then analyzed using, e.g., PCA, as in the case of ASCA (analysis of variance combined with simultaneous component analysis). As an alternative to the ASCA method, we propose the application of PLS followed by target projection (TP), which allows a one-factor representation of the model for each column in the design dummy matrix. PLS application follows after proper deflation of the experimental matrix, i.e., to what are called the residuals under the reduced ANOVA model. The proposed approach (ANOVA-TP) is well suited for the study of designed chromatographic data of complex samples. It allows testing of statistical significance of the studied effects, 'biomarker' identification, and enables straightforward visualization and accurate estimation of between- and within-class variance. The proposed approach has been successfully applied to a case study aimed at evaluating the effect of pasteurization on the concentrations of various phenolic constituents of rooibos tea of different quality grades and its outcomes have been compared to those of ASCA.
Accounting for Variance in Hyperspectral Data Coming from Limitations of the Imaging System
Shurygin, B.; Shestakova, M.; Nikolenko, A.; Badasen, E.; Strakhov, P.
2016-06-01
Over the course of the past few years, a number of methods was developed to incorporate hyperspectral imaging specifics into generic data mining techniques, traditionally used for hyperspectral data processing. Projection pursuit methods embody the largest class of methods empoyed for hyperspectral image data reduction, however, they all have certain drawbacks making them either hard to use or inefficient. It has been shown that hyperspectral image (HSI) statistics tend to display "heavy tails" (Manolakis2003)(Theiler2005), rendering most of the projection pursuit methods hard to use. Taking into consideration the magnitude of described deviations of observed data PDFs from normal distribution, it is apparent that a priori knowledge of variance in data caused by the imaging system is to be employed in order to efficiently classify objects on HSIs (Kerr, 2015), especially in cases of wildly varying SNR. A number of attempts to describe this variance and compensating techniques has been made (Aiazzi2006), however, new data quality standards are not yet set and accounting for the detector response is made under large set of assumptions. Current paper addresses the issue of hyperspectral image classification in the context of different variance sources based on the knowledge of calibration curves (both spectral and radiometric) obtained for each pixel of imaging camera. A camera produced by ZAO NPO Lepton (Russia) was calibrated and used to obtain a test image. A priori known values of SNR and spectral channel cross-correlation were incorporated into calculating test statistics used in dimensionality reduction and feature extraction. Expectation-Maximization classification algorithm modification for non-Gaussian model as described by (Veracini2010) was further employed. The impact of calibration data coarsening by ignoring non-uniformities on false alarm rate was studied. Case study shows both regions of scene-dominated variance and sensor-dominated variance, leading
An Analysis of Variance Framework for Matrix Sampling.
Sirotnik, Kenneth
Significant cost savings can be achieved with the use of matrix sampling in estimating population parameters from psychometric data. The statistical design is intuitively simple, using the framework of the two-way classification analysis of variance technique. For example, the mean and variance are derived from the performance of a certain grade…
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…
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…
Error Variance of Rasch Measurement with Logistic Ability Distributions.
Dimitrov, Dimiter M.
Exact formulas for classical error variance are provided for Rasch measurement with logistic distributions. An approximation formula with the normal ability distribution is also provided. With the proposed formulas, the additive contribution of individual items to the population error variance can be determined without knowledge of the other test…
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…
The asymptotic variance of departures in critically loaded queues
A. Al Hanbali; M.R.H. Mandjes (Michel); Y. Nazarathy (Yoni); W. Whitt
2010-01-01
htmlabstractWe 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 that the system load rho equals 1, and prove that the asymptotic variance rate satisfies lim_t Var D(t)/t = lambda
76 FR 78698 - Proposed Revocation of Permanent Variances
2011-12-19
... Occupational Safety and Health Administration Proposed Revocation of Permanent Variances AGENCY: Occupational... short and plain statement detailing (1) how the proposed revocation would affect the requesting party..., subpart L. The following table provides information about the variances proposed for revocation by...
Adjustment for heterogeneous variances due to days in milk and ...
ARC-IRENE
Adjustment of heterogeneous variances and a calving year effect in test-day ... Regression Test-Day Model (FRTDM), which assumes equal variances of the response variable at different .... random residual error .... records were included in the selection, while in the unadjusted data set, lactations consisting of six and more.
Characterizing the evolution of genetic variance using genetic covariance tensors.
Hine, Emma; Chenoweth, Stephen F; Rundle, Howard D; Blows, Mark W
2009-06-12
Determining how genetic variance changes under selection in natural populations has proved to be a very resilient problem in evolutionary genetics. In the same way that understanding the availability of genetic variance within populations requires the simultaneous consideration of genetic variance in sets of functionally related traits, determining how genetic variance changes under selection in natural populations will require ascertaining how genetic variance-covariance (G) matrices evolve. Here, we develop a geometric framework using higher-order tensors, which enables the empirical characterization of how G matrices have diverged among populations. We then show how divergence among populations in genetic covariance structure can then be associated with divergence in selection acting on those traits using key equations from evolutionary theory. Using estimates of G matrices of eight male sexually selected traits from nine geographical populations of Drosophila serrata, we show that much of the divergence in genetic variance occurred in a single trait combination, a conclusion that could not have been reached by examining variation among the individual elements of the nine G matrices. Divergence in G was primarily in the direction of the major axes of genetic variance within populations, suggesting that genetic drift may be a major cause of divergence in genetic variance among these populations.
Productive Failure in Learning the Concept of Variance
Kapur, Manu
2012-01-01
In a study with ninth-grade mathematics students on learning the concept of variance, students experienced either direct instruction (DI) or productive failure (PF), wherein they were first asked to generate a quantitative index for variance without any guidance before receiving DI on the concept. Whereas DI students relied only on the canonical…
Time variance effects and measurement error indications for MLS measurements
Liu, Jiyuan
1999-01-01
Mathematical characteristics of Maximum-Length-Sequences are discussed, and effects of measuring on slightly time-varying systems with the MLS method are examined with computer simulations with MATLAB. A new coherence measure is suggested for the indication of time-variance effects. The results...... of the simulations show that the proposed MLS coherence can give an indication of time-variance effects....
Confidence Intervals of Variance Functions in Generalized Linear Model
Yong Zhou; Dao-ji Li
2006-01-01
In this paper we introduce an appealing nonparametric method for estimating variance and conditional variance functions in generalized linear models (GLMs), when designs are fixed points and random variables respectively. Bias-corrected confidence bands are proposed for the (conditional) variance by local linear smoothers. Nonparametric techniques are developed in deriving the bias-corrected confidence intervals of the (conditional) variance. The asymptotic distribution of the proposed estimator is established and show that the bias-corrected confidence bands asymptotically have the correct coverage properties. A small simulation is performed when unknown regression parameter is estimated by nonparametric quasi-likelihood. The results are also applicable to nonparametric autoregressive times series model with heteroscedastic conditional variance.
Research on variance of subnets in network sampling
Qi Gao; Xiaoting Li; Feng Pan
2014-01-01
In the recent research of network sampling, some sam-pling concepts are misunderstood, and the variance of subnets is not taken into account. We propose the correct definition of the sample and sampling rate in network sampling, as wel as the formula for calculating the variance of subnets. Then, three commonly used sampling strategies are applied to databases of the connecting nearest-neighbor (CNN) model, random network and smal-world network to explore the variance in network sam-pling. As proved by the results, snowbal sampling obtains the most variance of subnets, but does wel in capturing the network struc-ture. The variance of networks sampled by the hub and random strategy are much smal er. The hub strategy performs wel in re-flecting the property of the whole network, while random sampling obtains more accurate results in evaluating clustering coefficient.
Minimum Variance Portfolios in the Brazilian Equity Market
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.
How Well Can We Estimate Error Variance of Satellite Precipitation Data Around the World?
Gebregiorgis, A. S.; Hossain, F.
2014-12-01
The traditional approach to measuring precipitation by placing a probe on the ground will likely never be adequate or affordable in most parts of the world. Fortunately, satellites today provide a continuous global bird's-eye view (above ground) at any given location. However, the usefulness of such precipitation products for hydrological applications depends on their error characteristics. Thus, providing error information associated with existing satellite precipitation estimates is crucial to advancing applications in hydrologic modeling. In this study, we present a method of estimating satellite precipitation error variance using regression model for three satellite precipitation products (3B42RT, CMORPH, and PERSIANN-CCS) using easily available geophysical features and satellite precipitation rate. The goal of this work is to explore how well the method works around the world in diverse geophysical settings. Topography, climate, and seasons are considered as the governing factors to segregate the satellite precipitation uncertainty and fit a nonlinear regression equation as function of satellite precipitation rate. The error variance models were tested on USA, Asia, Middle East, and Mediterranean region. Rain-gauge based precipitation product was used to validate the errors variance of satellite precipitation products. Our study attests that transferability of model estimators (which help to estimate the error variance) from one region to another is practically possible by leveraging the similarity in geophysical features. Therefore, the quantitative picture of satellite precipitation error over ungauged regions can be discerned even in the absence of ground truth data.
Utility functions predict variance and skewness risk preferences in monkeys.
Genest, Wilfried; Stauffer, William R; Schultz, Wolfram
2016-07-26
Utility is the fundamental variable thought to underlie economic choices. In particular, utility functions are believed to reflect preferences toward risk, a key decision variable in many real-life situations. To assess the validity of utility representations, it is therefore important to examine risk preferences. In turn, this approach requires formal definitions of risk. A standard approach is to focus on the variance of reward distributions (variance-risk). In this study, we also examined a form of risk related to the skewness of reward distributions (skewness-risk). Thus, we tested the extent to which empirically derived utility functions predicted preferences for variance-risk and skewness-risk in macaques. The expected utilities calculated for various symmetrical and skewed gambles served to define formally the direction of stochastic dominance between gambles. In direct choices, the animals' preferences followed both second-order (variance) and third-order (skewness) stochastic dominance. Specifically, for gambles with different variance but identical expected values (EVs), the monkeys preferred high-variance gambles at low EVs and low-variance gambles at high EVs; in gambles with different skewness but identical EVs and variances, the animals preferred positively over symmetrical and negatively skewed gambles in a strongly transitive fashion. Thus, the utility functions predicted the animals' preferences for variance-risk and skewness-risk. Using these well-defined forms of risk, this study shows that monkeys' choices conform to the internal reward valuations suggested by their utility functions. This result implies a representation of utility in monkeys that accounts for both variance-risk and skewness-risk preferences.
Hickey, J.M.; Veerkamp, R.F.; Calus, M.P.L.; Mulder, H.A.; Thompson, R.
2009-01-01
Calculation of the exact prediction error variance covariance matrix is often computationally too demanding, which limits its application in REML algorithms, the calculation of accuracies of estimated breeding values and the control of variance of response to selection. Alternatively Monte Carlo
Hickey, J.M.; Veerkamp, R.F.; Calus, M.P.L.; Mulder, H.A.; Thompson, R.
2009-01-01
Calculation of the exact prediction error variance covariance matrix is often computationally too demanding, which limits its application in REML algorithms, the calculation of accuracies of estimated breeding values and the control of variance of response to selection. Alternatively Monte Carlo sam
Capturing Option Anomalies with a Variance-Dependent Pricing Kernel
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 ...... 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....... 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......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...
Filtered kriging for spatial data with heterogeneous measurement error variances.
Christensen, William F
2011-09-01
When predicting values for the measurement-error-free component of an observed spatial process, it is generally assumed that the process has a common measurement error variance. However, it is often the case that each measurement in a spatial data set has a known, site-specific measurement error variance, rendering the observed process nonstationary. We present a simple approach for estimating the semivariogram of the unobservable measurement-error-free process using a bias adjustment of the classical semivariogram formula. We then develop a new kriging predictor that filters the measurement errors. For scenarios where each site's measurement error variance is a function of the process of interest, we recommend an approach that also uses a variance-stabilizing transformation. The properties of the heterogeneous variance measurement-error-filtered kriging (HFK) predictor and variance-stabilized HFK predictor, and the improvement of these approaches over standard measurement-error-filtered kriging are demonstrated using simulation. The approach is illustrated with climate model output from the Hudson Strait area in northern Canada. In the illustration, locations with high or low measurement error variances are appropriately down- or upweighted in the prediction of the underlying process, yielding a realistically smooth picture of the phenomenon of interest.
Meta-analysis of ratios of sample variances.
Prendergast, Luke A; Staudte, Robert G
2016-05-20
When conducting a meta-analysis of standardized mean differences (SMDs), it is common to use Cohen's d, or its variants, that require equal variances in the two arms of each study. While interpretation of these SMDs is simple, this alone should not be used as a justification for assuming equal variances. Until now, researchers have either used an F-test for each individual study or perhaps even conveniently ignored such tools altogether. In this paper, we propose a meta-analysis of ratios of sample variances to assess whether the equality of variances assumptions is justified prior to a meta-analysis of SMDs. Quantile-quantile plots, an omnibus test for equal variances or an overall meta-estimate of the ratio of variances can all be used to formally justify the use of less common methods when evidence of unequal variances is found. The methods in this paper are simple to implement and the validity of the approaches are reinforced by simulation studies and an application to a real data set.
Cawthorn, J. M.; Brown, C. G.
1974-01-01
A study has been conducted of the future noise environment of Patric Henry Airport and its neighboring communities projected for the year 1990. An assessment was made of the impact of advanced noise reduction technologies which are currently being considered. These advanced technologies include a two-segment landing approach procedure and aircraft hardware modifications or retrofits which would add sound absorbent material in the nacelles of the engines or which would replace the present two- and three-stage fans with a single-stage fan of larger diameter. Noise Exposure Forecast (NEF) contours were computed for the baseline (nonretrofitted) aircraft for the projected traffic volume and fleet mix for the year 1990. These NEF contours are presented along with contours for a variety of retrofit options. Comparisons of the baseline with the noise reduction options are given in terms of total land area exposed to 30 and 40 NEF levels. Results are also presented of the effects on noise exposure area of the total number of daily operations.
Comparison of multiplicative heterogeneous variance adjustment models for genetic evaluations.
Márkus, Sz; Mäntysaari, E A; Strandén, I; Eriksson, J-Å; Lidauer, M H
2014-06-01
Two heterogeneous variance adjustment methods and two variance models were compared in a simulation study. The method used for heterogeneous variance adjustment in the Nordic test-day model, which is a multiplicative method based on Meuwissen (J. Dairy Sci., 79, 1996, 310), was compared with a restricted multiplicative method where the fixed effects were not scaled. Both methods were tested with two different variance models, one with a herd-year and the other with a herd-year-month random effect. The simulation study was built on two field data sets from Swedish Red dairy cattle herds. For both data sets, 200 herds with test-day observations over a 12-year period were sampled. For one data set, herds were sampled randomly, while for the other, each herd was required to have at least 10 first-calving cows per year. The simulations supported the applicability of both methods and models, but the multiplicative mixed model was more sensitive in the case of small strata sizes. Estimation of variance components for the variance models resulted in different parameter estimates, depending on the applied heterogeneous variance adjustment method and variance model combination. Our analyses showed that the assumption of a first-order autoregressive correlation structure between random-effect levels is reasonable when within-herd heterogeneity is modelled by year classes, but less appropriate for within-herd heterogeneity by month classes. Of the studied alternatives, the multiplicative method and a variance model with a random herd-year effect were found most suitable for the Nordic test-day model for dairy cattle evaluation.
Global Gravity Wave Variances from Aura MLS: Characteristics and Interpretation
Wu, Dong L.; Eckermann, Stephen D.
2008-01-01
The gravity wave (GW)-resolving capabilities of 118-GHz saturated thermal radiances acquired throughout the stratosphere by the Microwave Limb Sounder (MLS) on the Aura satellite are investigated and initial results presented. Because the saturated (optically thick) radiances resolve GW perturbations from a given altitude at different horizontal locations, variances are evaluated at 12 pressure altitudes between 21 and 51 km using the 40 saturated radiances found at the bottom of each limb scan. Forward modeling simulations show that these variances are controlled mostly by GWs with vertical wavelengths z 5 km and horizontal along-track wavelengths of y 100-200 km. The tilted cigar-shaped three-dimensional weighting functions yield highly selective responses to GWs of high intrinsic frequency that propagate toward the instrument. The latter property is used to infer the net meridional component of GW propagation by differencing the variances acquired from ascending (A) and descending (D) orbits. Because of improved vertical resolution and sensitivity, Aura MLS GW variances are 5?8 times larger than those from the Upper Atmosphere Research Satellite (UARS) MLS. Like UARS MLS variances, monthly-mean Aura MLS variances in January and July 2005 are enhanced when local background wind speeds are large, due largely to GW visibility effects. Zonal asymmetries in variance maps reveal enhanced GW activity at high latitudes due to forcing by flow over major mountain ranges and at tropical and subtropical latitudes due to enhanced deep convective generation as inferred from contemporaneous MLS cloud-ice data. At 21-28-km altitude (heights not measured by the UARS MLS), GW variance in the tropics is systematically enhanced and shows clear variations with the phase of the quasi-biennial oscillation, in general agreement with GW temperature variances derived from radiosonde, rocketsonde, and limb-scan vertical profiles.
Variance decomposition of apolipoproteins and lipids in Danish twins
Fenger, Mogens; Schousboe, Karoline; Sørensen, Thorkild I A
2007-01-01
OBJECTIVE: Twin studies are used extensively to decompose the variance of a trait, mainly to estimate the heritability of the trait. A second purpose of such studies is to estimate to what extent the non-genetic variance is shared or specific to individuals. To a lesser extent the twin studies have...... been used in bivariate or multivariate analysis to elucidate common genetic factors to two or more traits. METHODS AND RESULTS: In the present study the variances of traits related to lipid metabolism is decomposed in a relatively large Danish twin population, including bivariate analysis to detect...
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.
Capturing Option Anomalies with a Variance-Dependent Pricing Kernel
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...
Pricing Volatility Derivatives Under the Modified Constant Elasticity of Variance Model
Leunglung Chan; Eckhard Platen
2015-01-01
This paper studies volatility derivatives such as variance and volatility swaps, options on variance in the modified constant elasticity of variance model using the benchmark approach. The analytical expressions of pricing formulas for variance swaps are presented. In addition, the numerical solutions for variance swaps, volatility swaps and options on variance are demonstrated.
NONE
1998-01-01
This report presents the results of a U.S. Department of Energy (DOE) Innovative Clean Coal Technology (ICCT) project demonstrating advanced wall-fired combustion techniques for the reduction of nitrogen oxide (NOx) emissions from coal-fired boilers. The project was conducted at Georgia Power Company`s Plant Hammond Unit 4 located near Rome, Georgia. The technologies demonstrated at this site include Foster Wheeler Energy Corporation`s advanced overfire air system and Controlled Flow/Split Flame low NOx burner. The primary objective of the demonstration at Hammond Unit 4 was to determine the long-term effects of commercially available wall-fired low NOx combustion technologies on NOx emissions and boiler performance. Short-term tests of each technology were also performed to provide engineering information about emissions and performance trends. A target of achieving fifty percent NOx reduction using combustion modifications was established for the project. Short-term and long-term baseline testing was conducted in an {open_quotes}as-found{close_quotes} condition from November 1989 through March 1990. Following retrofit of the AOFA system during a four-week outage in spring 1990, the AOFA configuration was tested from August 1990 through March 1991. The FWEC CF/SF low NOx burners were then installed during a seven-week outage starting on March 8, 1991 and continuing to May 5, 1991. Following optimization of the LNBs and ancillary combustion equipment by FWEC personnel, LNB testing commenced during July 1991 and continued until January 1992. Testing in the LNB+AOFA configuration was completed during August 1993. This report provides documentation on the design criteria used in the performance of this project as it pertains to the scope involved with the low NOx burners and advanced overfire systems.
Buls, Nico; Gompel, Gert van; Nieboer, Koenraad; Willekens, Inneke; Mey, Johan de [Universitair Ziekenhuis Brussel (UZ Brussel), Department of Radiology, Brussels (Belgium); Vrije Universiteit Brussel (VUB), Research group LABO, Brussel (Belgium); Cauteren, Toon van [Vrije Universiteit Brussel (VUB), Research group LABO, Brussel (Belgium); Verfaillie, Guy [Universitair Ziekenhuis Brussel (UZ Brussel), Department of Radiology, Brussels (Belgium); Evans, Paul; Macholl, Sven; Newton, Ben [GE Healthcare, Department of Medical Diagnostics, Amersham, Buckinghamshire (United Kingdom)
2015-04-01
To assess image quality in abdominal CT at low tube voltage combined with two types of iterative reconstruction (IR) at four reduced contrast agent dose levels. Minipigs were scanned with standard 320 mg I/mL contrast concentration at 120 kVp, and with reduced formulations of 120, 170, 220 and 270 mg I/mL at 80 kVp with IR. Image quality was assessed by CT value, dose normalized contrast and signal to noise ratio (CNRD and SNRD) in the arterial and venous phases. Qualitative analysis was included by expert reading. Protocols with 170 mg I/mL or higher showed equal or superior CT values: aorta (278-468 HU versus 314 HU); portal vein (205-273 HU versus 208 HU); liver parenchyma (122-146 HU versus 115 HU). In the aorta, all 170 mg I/mL protocols or higher yielded equal or superior CNRD (15.0-28.0 versus 13.7). In liver parenchyma, all study protocols resulted in higher SNRDs. Radiation dose could be reduced from standard CTDI{sub vol} = 7.8 mGy (6.2 mSv) to 7.6 mGy (5.2 mSv) with 170 mg I/mL. Combining 80 kVp with IR allows at least a 47 % contrast agent dose reduction and 16 % radiation dose reduction for images of comparable quality. (orig.)
1993-12-31
This quarterly report discusses the technical progress of an Innovative Clean Coal Technology (ICCT) demonstration of advanced wall-fired combustion techniques for the reduction of nitrogen oxide (NO{sub x}) emissions from coal-fired boilers. The project provides a stepwise retrofit of an advanced overfire air (AOFA) system followed by low NO{sub x} burners (LNB). During each test phase of the project, diagnostic, performance, long-term, and verification testing will be performed. These tests are used to quantify the NO{sub x} reductions of each technology and evaluate the effects of those reductions on other combustion parameters such as particulate characteristics and boiler efficiency. Baseline, AOFA, LNB, and LNB plus AOFA test segments have been completed. Analysis of the 94 days of LNB long-term data collected show the full-load NO{sub x} emission levels to be approximately 0.65 lb/MBtu with fly ash LOI values of approximately 8 percent. Corresponding values for the AOFA configuration are 0.94 lb/MBtu and approximately 10 percent. For comparison, the long-term full-load, baseline NO{sub x} emission level was approximately 1.24 lb/MBtu at 5.2 percent LOI. Comprehensive testing in the LNB+AOFA configuration indicate that at full-load, NO{sub x} emissions and fly ash LOI are near 0.40 lb/MBtu and 8 percent, respectively. However, it is believed that a substantial portion of the incremental change in NO{sub x} emissions between the LNB and LNB+AOFA configurations is the result of additional burner tuning and other operational adjustments and is not the result of the AOFA system. During this quarter, LNB+AOFA testing was concluded. Testing performed during this quarter included long-term and verification testing in the LNB+AOFA configuration.
Hickey, John M; Veerkamp, Roel F; Calus, Mario P L; Mulder, Han A; Thompson, Robin
2009-02-09
Calculation of the exact prediction error variance covariance matrix is often computationally too demanding, which limits its application in REML algorithms, the calculation of accuracies of estimated breeding values and the control of variance of response to selection. Alternatively Monte Carlo sampling can be used to calculate approximations of the prediction error variance, which converge to the true values if enough samples are used. However, in practical situations the number of samples, which are computationally feasible, is limited. The objective of this study was to compare the convergence rate of different formulations of the prediction error variance calculated using Monte Carlo sampling. Four of these formulations were published, four were corresponding alternative versions, and two were derived as part of this study. The different formulations had different convergence rates and these were shown to depend on the number of samples and on the level of prediction error variance. Four formulations were competitive and these made use of information on either the variance of the estimated breeding value and on the variance of the true breeding value minus the estimated breeding value or on the covariance between the true and estimated breeding values.
minimum variance estimation of yield parameters of rubber tree with ...
2013-03-01
Mar 1, 2013 ... STAMP, an OxMetric modular software system for time series analysis, was used to estimate the yield ... derlying regression techniques. .... Kalman Filter Minimum Variance Estimation of Rubber Tree Yield Parameters. 83.
Detecting Pulsars with Interstellar Scintillation in Variance Images
Dai, S; Bell, M E; Coles, W A; Hobbs, G; Ekers, R D; Lenc, E
2016-01-01
Pulsars are the only cosmic radio sources known to be sufficiently compact to show diffractive interstellar scintillations. Images of the variance of radio signals in both time and frequency can be used to detect pulsars in large-scale continuum surveys using the next generation of synthesis radio telescopes. This technique allows a search over the full field of view while avoiding the need for expensive pixel-by-pixel high time resolution searches. We investigate the sensitivity of detecting pulsars in variance images. We show that variance images are most sensitive to pulsars whose scintillation time-scales and bandwidths are close to the subintegration time and channel bandwidth. Therefore, in order to maximise the detection of pulsars for a given radio continuum survey, it is essential to retain a high time and frequency resolution, allowing us to make variance images sensitive to pulsars with different scintillation properties. We demonstrate the technique with Murchision Widefield Array data and show th...
40 CFR 141.4 - Variances and exemptions.
2010-07-01
... Section 141.4 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) WATER PROGRAMS (CONTINUED) NATIONAL PRIMARY DRINKING WATER REGULATIONS General § 141.4 Variances and exemptions. (a... maintenance of the distribution system. ...
Fundamental Indexes As Proxies For Mean-Variance Efficient Portfolios
Kathleen Hodnett; Gearé Botes; Khumbudzo Daswa; Kimberly Davids; Emmanuel Che Fongwa; Candice Fortuin
2014-01-01
Mean-variance efficiency was first explained by Markowitz (1952) who derived an efficient frontier comprised of portfolios with the highest expected returns for a given level of risk borne by the investor...
TESTS FOR VARIANCE COMPONENTS IN VARYING COEFFICIENT MIXED MODELS
Zaixing Li; Yuedong Wang; Ping Wu; Wangli Xu; Lixing Zhu
2012-01-01
.... To address the question of whether a varying coefficient mixed model can be reduced to a simpler varying coefficient model, we develop one-sided tests for the null hypothesis that all the variance components are zero...
Estimating the generalized concordance correlation coefficient through variance components.
Carrasco, Josep L; Jover, Lluís
2003-12-01
The intraclass correlation coefficient (ICC) and the concordance correlation coefficient (CCC) are two of the most popular measures of agreement for variables measured on a continuous scale. Here, we demonstrate that ICC and CCC are the same measure of agreement estimated in two ways: by the variance components procedure and by the moment method. We propose estimating the CCC using variance components of a mixed effects model, instead of the common method of moments. With the variance components approach, the CCC can easily be extended to more than two observers, and adjusted using confounding covariates, by incorporating them in the mixed model. A simulation study is carried out to compare the variance components approach with the moment method. The importance of adjusting by confounding covariates is illustrated with a case example.
Variance estimation in neutron coincidence counting using the bootstrap method
Dubi, C., E-mail: chendb331@gmail.com [Physics Department, Nuclear Research Center of the Negev, P.O.B. 9001 Beer Sheva (Israel); Ocherashvilli, A.; Ettegui, H. [Physics Department, Nuclear Research Center of the Negev, P.O.B. 9001 Beer Sheva (Israel); Pedersen, B. [Nuclear Security Unit, Institute for Transuranium Elements, Via E. Fermi, 2749 JRC, Ispra (Italy)
2015-09-11
In the study, we demonstrate the implementation of the “bootstrap” method for a reliable estimation of the statistical error in Neutron Multiplicity Counting (NMC) on plutonium samples. The “bootstrap” method estimates the variance of a measurement through a re-sampling process, in which a large number of pseudo-samples are generated, from which the so-called bootstrap distribution is generated. The outline of the present study is to give a full description of the bootstrapping procedure, and to validate, through experimental results, the reliability of the estimated variance. Results indicate both a very good agreement between the measured variance and the variance obtained through the bootstrap method, and a robustness of the method with respect to the duration of the measurement and the bootstrap parameters.
Dimension free and infinite variance tail estimates on Poisson space
Breton, J. C.; Houdré, C.; Privault, N.
2004-01-01
Concentration inequalities are obtained on Poisson space, for random functionals with finite or infinite variance. In particular, dimension free tail estimates and exponential integrability results are given for the Euclidean norm of vectors of independent functionals. In the finite variance case these results are applied to infinitely divisible random variables such as quadratic Wiener functionals, including L\\'evy's stochastic area and the square norm of Brownian paths. In the infinite vari...
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 +
Wavelet Variance Analysis of EEG Based on Window Function
ZHENG Yuan-zhuang; YOU Rong-yi
2014-01-01
A new wavelet variance analysis method based on window function is proposed to investigate the dynamical features of electroencephalogram (EEG).The ex-prienmental results show that the wavelet energy of epileptic EEGs are more discrete than normal EEGs, and the variation of wavelet variance is different between epileptic and normal EEGs with the increase of time-window width. Furthermore, it is found that the wavelet subband entropy (WSE) of the epileptic EEGs are lower than the normal EEGs.
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 ...
Multiperiod mean-variance efficient portfolios with endogenous liabilities
Markus LEIPPOLD; Trojani, Fabio; Vanini, Paolo
2011-01-01
We study the optimal policies and mean-variance frontiers (MVF) of a multiperiod mean-variance optimization of assets and liabilities (AL). This makes the analysis more challenging than for a setting based on purely exogenous liabilities, in which the optimization is only performed on the assets while keeping liabilities fixed. We show that, under general conditions for the joint AL dynamics, the optimal policies and the MVF can be decomposed into an orthogonal set of basis returns using exte...
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 ...
Estimating Income Variances by Probability Sampling: A Case Study
Akbar Ali Shah
2010-08-01
Full Text Available The main focus of the study is to estimate variability in income distribution of households by conducting a survey. The variances in income distribution have been calculated by probability sampling techniques. The variances are compared and relative gains are also obtained. It is concluded that the income distribution has been better as compared to first Household Income and Expenditure Survey (HIES conducted in Pakistan 1993-94.
Testing for Causality in Variance Usinf Multivariate GARCH Models
Christian M. Hafner; Herwartz, Helmut
2008-01-01
Tests of causality in variance in multiple time series have been proposed recently, based on residuals of estimated univariate models. Although such tests are applied frequently, little is known about their power properties. In this paper we show that a convenient alternative to residual based testing is to specify a multivariate volatility model, such as multivariate GARCH (or BEKK), and construct a Wald test on noncausality in variance. We compare both approaches to testing causality in var...
Testing for causality in variance using multivariate GARCH models
Hafner, Christian; Herwartz, H.
2004-01-01
textabstractTests of causality in variance in multiple time series have been proposed recently, based on residuals of estimated univariate models. Although such tests are applied frequently little is known about their power properties. In this paper we show that a convenient alternative to residual based testing is to specify a multivariate volatility model, such as multivariate GARCH (or BEKK), and construct a Wald test on noncausality in variance. We compare both approaches to testing causa...
The evolution and consequences of sex-specific reproductive variance.
Mullon, Charles; Reuter, Max; Lehmann, Laurent
2014-01-01
Natural selection favors alleles that increase the number of offspring produced by their carriers. But in a world that is inherently uncertain within generations, selection also favors alleles that reduce the variance in the number of offspring produced. If previous studies have established this principle, they have largely ignored fundamental aspects of sexual reproduction and therefore how selection on sex-specific reproductive variance operates. To study the evolution and consequences of sex-specific reproductive variance, we present a population-genetic model of phenotypic evolution in a dioecious population that incorporates previously neglected components of reproductive variance. First, we derive the probability of fixation for mutations that affect male and/or female reproductive phenotypes under sex-specific selection. We find that even in the simplest scenarios, the direction of selection is altered when reproductive variance is taken into account. In particular, previously unaccounted for covariances between the reproductive outputs of different individuals are expected to play a significant role in determining the direction of selection. Then, the probability of fixation is used to develop a stochastic model of joint male and female phenotypic evolution. We find that sex-specific reproductive variance can be responsible for changes in the course of long-term evolution. Finally, the model is applied to an example of parental-care evolution. Overall, our model allows for the evolutionary analysis of social traits in finite and dioecious populations, where interactions can occur within and between sexes under a realistic scenario of reproduction.
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.
Genetic heterogeneity of residual variance in broiler chickens
Hill William G
2006-11-01
Full Text Available Abstract Aims were to estimate the extent of genetic heterogeneity in environmental variance. Data comprised 99 535 records of 35-day body weights from broiler chickens reared in a controlled environment. Residual variance within dam families was estimated using ASREML, after fitting fixed effects such as genetic groups and hatches, for each of 377 genetically contemporary sires with a large number of progeny (> 100 males or females each. Residual variance was computed separately for male and female offspring, and after correction for sampling, strong evidence for heterogeneity was found, the standard deviation between sires in within variance amounting to 15–18% of its mean. Reanalysis using log-transformed data gave similar results, and elimination of 2–3% of outlier data reduced the heterogeneity but it was still over 10%. The correlation between estimates for males and females was low, however. The correlation between sire effects on progeny mean and residual variance for body weight was small and negative (-0.1. Using a data set bigger than any yet presented and on a trait measurable in both sexes, this study has shown evidence for heterogeneity in the residual variance, which could not be explained by segregation of major genes unless very few determined the trait.
1992-11-25
This quarterly report discusses the technical progress of a US Department of Energy (DOE) Innovative Clean Coal Technology (ICCT) Project demonstrating advanced tangentially-fired combustion techniques for the reduction of nitrogen oxide (NO[sub x]) emissions from a coal-fired boiler. The project is being conducted at Gulf Power Company's Plant Lansing Smith Unit 2 located near Panama City, Florida. The primary objective of this demonstration is to determine the long-term effects of commercially available tangentially-fired low NO[sub x] combustion technologies on NO[sub x] emissions and boiler performance. A target of achieving fifty percent NO[sub x] reduction using combustion modifications has been established for the project. The stepwise approach that is being used to evaluate the NO[sub x] control technologies requires three plant outages to successively install the test instrumentation and the different levels of the low NO[sub x] concentric firing system (LNCFS). Following each outage, a series of four groups of tests are performed. These are (1) diagnostic, (2) performance, (3) long-term, and (4) verification. These tests are used to quantify the NO[sub x] reductions of each technology and evaluate the effects of those reductions on other combustion parameters such as particulate characteristics and boiler efficiency. This technical progress report presents the LNCFS Level I short-term data collected during this quarter. In addition, a comparison of all the long-term emissions data that have been collected to date is included.
1992-11-25
This quarterly report discusses the technical progress of a US Department of Energy (DOE) Innovative Clean Coal Technology (ICCT) Project demonstrating advanced tangentially-fired combustion techniques for the reduction of nitrogen oxide (NO{sub x}) emissions from a coal-fired boiler. The project is being conducted at Gulf Power Company`s Plant Lansing Smith Unit 2 located near Panama City, Florida. The primary objective of this demonstration is to determine the long-term effects of commercially available tangentially-fired low NO{sub x} combustion technologies on NO{sub x} emissions and boiler performance. A target of achieving fifty percent NO{sub x} reduction using combustion modifications has been established for the project. The stepwise approach that is being used to evaluate the NO{sub x} control technologies requires three plant outages to successively install the test instrumentation and the different levels of the low NO{sub x} concentric firing system (LNCFS). Following each outage, a series of four groups of tests are performed. These are (1) diagnostic, (2) performance, (3) long-term, and (4) verification. These tests are used to quantify the NO{sub x} reductions of each technology and evaluate the effects of those reductions on other combustion parameters such as particulate characteristics and boiler efficiency. This technical progress report presents the LNCFS Level I short-term data collected during this quarter. In addition, a comparison of all the long-term emissions data that have been collected to date is included.
Chen, Jiangyao; Huang, Yong; Li, Guiying; An, Taicheng; Hu, Yunkun; Li, Yunlu
2016-01-25
Volatile organic compounds (VOCs) emitted during the electronic waste dismantling process (EWDP) were treated at a pilot scale, using integrated electrostatic precipitation (EP)-advanced oxidation technologies (AOTs, subsequent photocatalysis (PC) and ozonation). Although no obvious alteration was seen in VOC concentration and composition, EP technology removed 47.2% of total suspended particles, greatly reducing the negative effect of particles on subsequent AOTs. After the AOT treatment, average removal efficiencies of 95.7%, 95.4%, 87.4%, and 97.5% were achieved for aromatic hydrocarbons, aliphatic hydrocarbons, halogenated hydrocarbons, as well as nitrogen- and oxygen-containing compounds, respectively, over 60-day treatment period. Furthermore, high elimination capacities were also seen using hybrid technique of PC with ozonation; this was due to the PC unit's high loading rates and excellent pre-treatment abilities, and the ozonation unit's high elimination capacity. In addition, the non-cancer and cancer risks, as well as the occupational exposure cancer risk, for workers exposed to emitted VOCs in workshop were reduced dramatically after the integrated technique treatment. Results demonstrated that the integrated technique led to highly efficient and stable VOC removal from EWDP emissions at a pilot scale. This study points to an efficient approach for atmospheric purification and improving human health in e-waste recycling regions.
Bobrowska Alicja
2015-09-01
Full Text Available In constructions, the usefulness of modern technical diagnostics of stone as a raw material requires predicting the effects of long-term environmental impact of its qualities and geomechanical properties. The paper presents geomechanical research enabling presentation of the factors for strength loss of the stone and forecasting the rate of development of destructive phenomena on the stone structure on a long-time basis. As research material Turkish travertines were selected from the Denizli-Kaklık Basin (Pamukkale and Hierapolis quarries, which have been commonly used for centuries in global architecture. The rock material was subjected to testing of the impact of various environmental factors, as well as European standards recommended by the author of the research program. Their resistance to the crystallization of salts from aqueous solutions and the effects of SO2, as well as the effect of frost and high temperatures are presented. The studies allowed establishing the following quantitative indicators: the ultrasonic waves index (IVp and the strength reduction index (IRc. Reflections on the assessment of deterioration effects indicate that the most active factors decreasing travertine resistance in the aging process include frost and sulphur dioxide (SO2. Their negative influence is particularly intense when the stone material is already strongly weathered.
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.
Rompel, Oliver; Janka, Rolf; Lell, Michael M.; Uder, Michael; Hammon, Matthias [University Hospital Erlangen, Department of Radiology, Erlangen (Germany); Gloeckler, Martin; Dittrich, Sven [University Hospital Erlangen, Department of Pediatric Cardiology, Erlangen (Germany); Cesnjevar, Robert [University Hospital Erlangen, Department of Pediatric Cardiac Surgery, Erlangen (Germany)
2016-04-15
Many technical updates have been made in multi-detector CT. To evaluate image quality and radiation dose of high-pitch second- and third-generation dual-source chest CT angiography and to assess the effects of different levels of advanced modeled iterative reconstruction (ADMIRE) in newborns and children. Chest CT angiography (70 kVp) was performed in 42 children (age 158 ± 267 days, range 1-1,194 days). We evaluated subjective and objective image quality, and radiation dose with filtered back projection (FBP) and different strength levels of ADMIRE. For comparison were 42 matched controls examined with a second-generation 128-slice dual-source CT-scanner (80 kVp). ADMIRE demonstrated improved objective and subjective image quality (P <.01). Mean signal/noise, contrast/noise and subjective image quality were 11.9, 10.0 and 1.9, respectively, for the 80 kVp mode and 11.2, 10.0 and 1.9 for the 70 kVp mode. With ADMIRE, the corresponding values for the 70 kVp mode were 13.7, 12.1 and 1.4 at strength level 2 and 17.6, 15.6 and 1.2 at strength level 4. Mean CTDI{sub vol}, DLP and effective dose were significantly lower with the 70-kVp mode (0.31 mGy, 5.33 mGy*cm, 0.36 mSv) compared to the 80-kVp mode (0.46 mGy, 9.17 mGy*cm, 0.62 mSv; P <.01). The third-generation dual-source CT at 70 kVp provided good objective and subjective image quality at lower radiation exposure. ADMIRE improved objective and subjective image quality. (orig.)
Niebuhr, Oliver
2016-01-01
Managing and, ideally, explaining phonetic variation has ever since been a key issue in the speech sciences. In this context, the major contribution of Lindblom's H&H theory was to replace the futile search for invariance by an explainable variance based on the tug-of-war metaphor. Recent empirical...
Lei, Zhouyue; Xu, Shengjie; Wan, Jiaxun; Wu, Peiyi
2016-01-01
In this study, uniform nitrogen-doped carbon quantum dots (N-CDs) were synthesized through a one-step solvothermal process of cyclic and nitrogen-rich solvents, such as N-methyl-2-pyrrolidone (NMP) and dimethyl-imidazolidinone (DMEU), under mild conditions. The products exhibited strong light blue fluorescence, good cell permeability and low cytotoxicity. Moreover, after a facile post-thermal treatment, it developed a lotus seedpod surface-like structure of seed-like N-CDs decorating on the surface of carbon layers with a high proportion of quaternary nitrogen moieties that exhibited excellent electrocatalytic activity and long-term durability towards the oxygen reduction reaction (ORR). The peak potential was -160 mV, which was comparable to or even lower than commercial Pt/C catalysts. Therefore, this study provides an alternative facile approach to the synthesis of versatile carbon quantum dots (CDs) with widespread commercial application prospects, not only as bioimaging probes but also as promising electrocatalysts for the metal-free ORR.In this study, uniform nitrogen-doped carbon quantum dots (N-CDs) were synthesized through a one-step solvothermal process of cyclic and nitrogen-rich solvents, such as N-methyl-2-pyrrolidone (NMP) and dimethyl-imidazolidinone (DMEU), under mild conditions. The products exhibited strong light blue fluorescence, good cell permeability and low cytotoxicity. Moreover, after a facile post-thermal treatment, it developed a lotus seedpod surface-like structure of seed-like N-CDs decorating on the surface of carbon layers with a high proportion of quaternary nitrogen moieties that exhibited excellent electrocatalytic activity and long-term durability towards the oxygen reduction reaction (ORR). The peak potential was -160 mV, which was comparable to or even lower than commercial Pt/C catalysts. Therefore, this study provides an alternative facile approach to the synthesis of versatile carbon quantum dots (CDs) with widespread
肿瘤中Axin表达减少的机制及其研究进展%Advances in research on mechanisms of Axin reduction in tumor
周明祎
2011-01-01
a tumor inhibitor, Axin protein expression decreases in many malignant carcinoma. The mechanism of Axin reduction is still undear. It may be associated with gene mutation, promoter methylation, protein degradation, and various small molecules. This review mainly summarized the latest progress in research on mechanism of Axin reduction.
NONE
2002-07-01
Conferences on emission reduction have been held by the Kommission Reinhaltung der Luft im VDI and the DIN-Normenausschuss KRdL since 1960. Recent European regulations as well as the TA Luft 2002 set the current boundary conditions. They necessitate that primary measures, i.e. measures integrated in the production process, must be fully utilized. Examples are presented and discussed. As a rule, the exhaust purification systems must be improved as well. This colloquium presented improvements and new developments that were successfully tested in practice and have become an established state-of-the-art technology. This proceedings volume contains the papers read at the colloquium of 19/20 November 2002, in Fulda, as well as the long versions of the posters presented there. [German] Seit 1960 werden von der Kommission Reinhaltung der Luft im VDI und DIN - Normenausschuss KRdL regelmaessig Veranstaltungen durchgefuehrt, um ueber die Fortschritte in der Luftreinhaltetechnik, insbesondere bei Verfahren zur Emissionsminderung von Schadstoffen aus industriellen und gewerblichen Prozessen, zu berichten. Neben den europaeischen Rahmenbedingungen fuer den Umweltschutz stellt die TA Luft 2002 neue Anforderungen an emissionsmindernde Massnahmen. Um die geforderten verringerten Emissionswerte zu erreichen, muessen die Moeglichkeiten des produktionsintegrierten Umweltschutzes ('primaere Massnahmen') vorab ausgeschoepft werden. Beispiele fuer produktionsintegrierte Loesungen zur Emissionsminderung werden vorgestellt und diskutiert. In der Regel sind verfahrenstechnische Verbesserungen der Abgasreinigungsanlagen zusaetzlich unumgaenglich. Zentrales Anliegen des Kolloquiums ist es, die Verbesserungen und Neuentwicklungen des gesamten Spektrums der Emissionsminderung vorzustellen, die mit Erfolg in der Praxis eingefuehrt wurden und sich als Stand der Technik etabliert haben. Der vorliegende Tagungsband enthaelt die Vortraege, die anlaesslich des Kolloquiums &apos
Minimum variance system identification with application to digital adaptive flight control
Kotob, S.; Kaufman, H.
1975-01-01
A new on-line minimum variance filter for the identification of systems with additive and multiplicative noise is described which embodies both accuracy and computational efficiency. The resulting filter is shown to use both the covariance of the parameter vector itself and the covariance of the error in identification. A bias reduction scheme can be used to yield asymptotically unbiased estimates. Experimental results for simulated linearized lateral aircraft motion in a digital closed loop mode are presented, showing the utility of the identification schemes.
Variance-Constrained Multiobjective Control and Filtering for Nonlinear Stochastic Systems: A Survey
Lifeng Ma
2013-01-01
Full Text Available The multiobjective control and filtering problems for nonlinear stochastic systems with variance constraints are surveyed. First, the concepts of nonlinear stochastic systems are recalled along with the introduction of some recent advances. Then, the covariance control theory, which serves as a practical method for multi-objective control design as well as a foundation for linear system theory, is reviewed comprehensively. The multiple design requirements frequently applied in engineering practice for the use of evaluating system performances are introduced, including robustness, reliability, and dissipativity. Several design techniques suitable for the multi-objective variance-constrained control and filtering problems for nonlinear stochastic systems are discussed. In particular, as a special case for the multi-objective design problems, the mixed H2/H∞ control and filtering problems are reviewed in great detail. Subsequently, some latest results on the variance-constrained multi-objective control and filtering problems for the nonlinear stochastic systems are summarized. Finally, conclusions are drawn, and several possible future research directions are pointed out.
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).
Variance-based fingerprint distance adjustment algorithm for indoor localization
Xiaolong Xu; Yu Tang; Xinheng Wang; Yun Zhang
2015-01-01
The multipath effect and movements of people in in-door environments lead to inaccurate localization. Through the test, calculation and analysis on the received signal strength in-dication (RSSI) and the variance of RSSI, we propose a novel variance-based fingerprint distance adjustment algorithm (VFDA). Based on the rule that variance decreases with the increase of RSSI mean, VFDA calculates RSSI variance with the mean value of received RSSIs. Then, we can get the correction weight. VFDA adjusts the fingerprint distances with the correction weight based on the variance of RSSI, which is used to correct the fingerprint distance. Besides, a threshold value is applied to VFDA to im-prove its performance further. VFDA and VFDA with the threshold value are applied in two kinds of real typical indoor environments deployed with several Wi-Fi access points. One is a quadrate lab room, and the other is a long and narrow corridor of a building. Experimental results and performance analysis show that in in-door environments, both VFDA and VFDA with the threshold have better positioning accuracy and environmental adaptability than the current typical positioning methods based on the k-nearest neighbor algorithm and the weighted k-nearest neighbor algorithm with similar computational costs.
Estimating Variances of Horizontal Wind Fluctuations in Stable Conditions
Luhar, Ashok K.
2010-05-01
Information concerning the average wind speed and the variances of lateral and longitudinal wind velocity fluctuations is required by dispersion models to characterise turbulence in the atmospheric boundary layer. When the winds are weak, the scalar average wind speed and the vector average wind speed need to be clearly distinguished and both lateral and longitudinal wind velocity fluctuations assume equal importance in dispersion calculations. We examine commonly-used methods of estimating these variances from wind-speed and wind-direction statistics measured separately, for example, by a cup anemometer and a wind vane, and evaluate the implied relationship between the scalar and vector wind speeds, using measurements taken under low-wind stable conditions. We highlight several inconsistencies inherent in the existing formulations and show that the widely-used assumption that the lateral velocity variance is equal to the longitudinal velocity variance is not necessarily true. We derive improved relations for the two variances, and although data under stable stratification are considered for comparison, our analysis is applicable more generally.
Application of variance components estimation to calibrate geoid error models.
Guo, Dong-Mei; Xu, Hou-Ze
2015-01-01
The method of using Global Positioning System-leveling data to obtain orthometric heights has been well studied. A simple formulation for the weighted least squares problem has been presented in an earlier work. This formulation allows one directly employing the errors-in-variables models which completely descript the covariance matrices of the observables. However, an important question that what accuracy level can be achieved has not yet to be satisfactorily solved by this traditional formulation. One of the main reasons for this is the incorrectness of the stochastic models in the adjustment, which in turn allows improving the stochastic models of measurement noises. Therefore the issue of determining the stochastic modeling of observables in the combined adjustment with heterogeneous height types will be a main focus point in this paper. Firstly, the well-known method of variance component estimation is employed to calibrate the errors of heterogeneous height data in a combined least square adjustment of ellipsoidal, orthometric and gravimetric geoid. Specifically, the iterative algorithms of minimum norm quadratic unbiased estimation are used to estimate the variance components for each of heterogeneous observations. Secondly, two different statistical models are presented to illustrate the theory. The first method directly uses the errors-in-variables as a priori covariance matrices and the second method analyzes the biases of variance components and then proposes bias-corrected variance component estimators. Several numerical test results show the capability and effectiveness of the variance components estimation procedure in combined adjustment for calibrating geoid error model.
Noam Lior; Stuart W. Churchill
2003-10-01
the Gordon Conference on Modern Development in Thermodynamics. The results obtained are very encouraging for the development of the RCSC as a commercial burner for significant reduction of NO{sub x} emissions, and highly warrants further study and development.
Zinn Manfred
2011-04-01
Full Text Available Abstract Background The substitution of plastics based on fossil raw material by biodegradable plastics produced from renewable resources is of crucial importance in a context of oil scarcity and overflowing plastic landfills. One of the most promising organisms for the manufacturing of medium-chain-length polyhydroxyalkanoates (mcl-PHA is Pseudomonas putida KT2440 which can accumulate large amounts of polymer from cheap substrates such as glucose. Current research focuses on enhancing the strain production capacity and synthesizing polymers with novel material properties. Many of the corresponding protocols for strain engineering rely on the rifampicin-resistant variant, P. putida KT2442. However, it remains unclear whether these two strains can be treated as equivalent in terms of mcl-PHA production, as the underlying antibiotic resistance mechanism involves a modification in the RNA polymerase and thus has ample potential for interfering with global transcription. Results To assess PHA production in P. putida KT2440 and KT2442, we characterized the growth and PHA accumulation on three categories of substrate: PHA-related (octanoate, PHA-unrelated (gluconate and poor PHA substrate (citrate. The strains showed clear differences of growth rate on gluconate and citrate (reduction for KT2442 > 3-fold and > 1.5-fold, respectively but not on octanoate. In addition, P. putida KT2442 PHA-free biomass significantly decreased after nitrogen depletion on gluconate. In an attempt to narrow down the range of possible reasons for this different behavior, the uptake of gluconate and extracellular release of the oxidized product 2-ketogluconate were measured. The results suggested that the reason has to be an inefficient transport or metabolization of 2-ketogluconate while an alteration of gluconate uptake and conversion to 2-ketogluconate could be excluded. Conclusions The study illustrates that the recruitment of a pleiotropic mutation, whose effects might
苏清发; 刘亚敏; 陈杰; 潘华; 施耀
2009-01-01
The emission of nitrogen oxides (NOx) from stationary sources, primarily from power stations, industrial heaters and cogeneration plants, represents a major environmental problem. This paper intends to give a general review over the advances in non-thermal plasma assisted selective catalytic reduction (SCR) of NOx with lower hydrocarbon compounds. In the last decade, the non-thermal plasma induced SCR of nitrogen oxide with low hydrocarbon compounds has received much attention. The different hydrocarbons (≤C3) used in the research are discussed. As we know,methane is more difficultly activated than non-methane hydrocarbons, such as ethylene and propylene etc. The reduction mechanism is also discussed. In addition, aiming at the difficulties existed, the direction for future research is prospected.%综述了近年来低温等离子体诱导低碳烃选择性催化还原NOx的研究进展,详细介绍了难活化的甲烷及较易活化的非甲烷低碳烃气体如乙烯、丙烯及丙烷等的研究现状,探讨了低温等离子体诱导低碳烃选择性催化还原NOx的反应机理,并展望了低温等离子体诱导低碳烃选择性催化还原NOx今后研究方向.
Sensitivity to Estimation Errors in Mean-variance Models
Zhi-ping Chen; Cai-e Zhao
2003-01-01
In order to give a complete and accurate description about the sensitivity of efficient portfolios to changes in assets' expected returns, variances and covariances, the joint effect of estimation errors in means, variances and covariances on the efficient portfolio's weights is investigated in this paper. It is proved that the efficient portfolio's composition is a Lipschitz continuous, differentiable mapping of these parameters under suitable conditions. The change rate of the efficient portfolio's weights with respect to variations about riskreturn estimations is derived by estimating the Lipschitz constant. Our general quantitative results show thatthe efficient portfolio's weights are normally not so sensitive to estimation errors about means and variances .Moreover, we point out those extreme cases which might cause stability problems and how to avoid them in practice. Preliminary numerical results are also provided as an illustration to our theoretical results.
Expectation Values and Variance Based on Lp-Norms
George Livadiotis
2012-11-01
Full Text Available This analysis introduces a generalization of the basic statistical concepts of expectation values and variance for non-Euclidean metrics induced by Lp-norms. The non-Euclidean Lp means are defined by exploiting the fundamental property of minimizing the Lp deviations that compose the Lp variance. These Lp expectation values embody a generic formal scheme of means characterization. Having the p-norm as a free parameter, both the Lp-normed expectation values and their variance are flexible to analyze new phenomena that cannot be described under the notions of classical statistics based on Euclidean norms. The new statistical approach provides insights into regression theory and Statistical Physics. Several illuminating examples are examined.
CMB-S4 and the Hemispherical Variance Anomaly
O'Dwyer, Marcio; Knox, Lloyd; Starkman, Glenn D
2016-01-01
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. In this context, the northern hemisphere displays an anomalously low variance while the southern hemisphere appears unremarkable (consistent with expectations from the best-fitting theory, $\\Lambda$CDM). 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 ba...
Variance inflation in high dimensional Support Vector Machines
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...... is not the full input space. Hence, when applying the model to future data the model is effectively blind to the missed orthogonal subspace. This can lead to an inflated variance of hidden variables estimated in the training set and when the model is applied to test data we may find that the hidden variables...... 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...
Variance swap payoffs, risk premia and extreme market conditions
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...... constraint. Our approach, only requiring option implied volatilities and daily returns for the underlying, provides measurement error free estimates of the part of the VRP related to normal market conditions, and allows constructing variables indicating agents' expectations under extreme market conditions....... 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....
Saturation of number variance in embedded random-matrix ensembles.
Prakash, Ravi; Pandey, Akhilesh
2016-05-01
We study fluctuation properties of embedded random matrix ensembles of noninteracting particles. For ensemble of two noninteracting particle systems, we find that unlike the spectra of classical random matrices, correlation functions are nonstationary. In the locally stationary region of spectra, we study the number variance and the spacing distributions. The spacing distributions follow the Poisson statistics, which is a key behavior of uncorrelated spectra. The number variance varies linearly as in the Poisson case for short correlation lengths but a kind of regularization occurs for large correlation lengths, and the number variance approaches saturation values. These results are known in the study of integrable systems but are being demonstrated for the first time in random matrix theory. We conjecture that the interacting particle cases, which exhibit the characteristics of classical random matrices for short correlation lengths, will also show saturation effects for large correlation lengths.
The positioning algorithm based on feature variance of billet character
Yi, Jiansong; Hong, Hanyu; Shi, Yu; Chen, Hongyang
2015-12-01
In the process of steel billets recognition on the production line, the key problem is how to determine the position of the billet from complex scenes. To solve this problem, this paper presents a positioning algorithm based on the feature variance of billet character. Using the largest intra-cluster variance recursive method based on multilevel filtering, the billet characters are segmented completely from the complex scenes. There are three rows of characters on each steel billet, we are able to determine whether the connected regions, which satisfy the condition of the feature variance, are on a straight line. Then we can accurately locate the steel billet. The experimental results demonstrated that the proposed method in this paper is competitive to other methods in positioning the characters and it also reduce the running time. The algorithm can provide a better basis for the character recognition.
Saturation of number variance in embedded random-matrix ensembles
Prakash, Ravi; Pandey, Akhilesh
2016-05-01
We study fluctuation properties of embedded random matrix ensembles of noninteracting particles. For ensemble of two noninteracting particle systems, we find that unlike the spectra of classical random matrices, correlation functions are nonstationary. In the locally stationary region of spectra, we study the number variance and the spacing distributions. The spacing distributions follow the Poisson statistics, which is a key behavior of uncorrelated spectra. The number variance varies linearly as in the Poisson case for short correlation lengths but a kind of regularization occurs for large correlation lengths, and the number variance approaches saturation values. These results are known in the study of integrable systems but are being demonstrated for the first time in random matrix theory. We conjecture that the interacting particle cases, which exhibit the characteristics of classical random matrices for short correlation lengths, will also show saturation effects for large correlation lengths.
Logistics Reduction and Repurposing Project
National Aeronautics and Space Administration — The Advanced Exploration Systems (AES) Logistics Reduction and Repurposing (LRR) project will enable a mission-independent cradle-to-grave-to-cradle...
Variance squeezing and entanglement of the XX central spin model
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.
Recursive identification for multidimensional ARMA processes with increasing variances
CHEN Hanfu
2005-01-01
In time series analysis, almost all existing results are derived for the case where the driven noise {wn} in the MA part is with bounded variance (or conditional variance). In contrast to this, the paper discusses how to identify coefficients in a multidimensional ARMA process with fixed orders, but in its MA part the conditional moment E(‖wn‖β| Fn-1), β＞ 2 Is possible to grow up at a rate of a power of logn. The wellknown stochastic gradient (SG) algorithm is applied to estimating the matrix coefficients of the ARMA process, and the reasonable conditions are given to guarantee the estimate to be strongly consistent.
Asymptotic variance of grey-scale surface area estimators
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....
Precise Asymptotics of Error Variance Estimator in Partially Linear Models
Shao-jun Guo; Min Chen; Feng Liu
2008-01-01
In this paper, we focus our attention on the precise asymptoties of error variance estimator in partially linear regression models, yi = xTi β + g(ti) +εi, 1 ≤i≤n, {εi,i = 1,... ,n } are i.i.d random errors with mean 0 and positive finite variance q2. Following the ideas of Allan Gut and Aurel Spataru[7,8] and Zhang[21],on precise asymptotics in the Baum-Katz and Davis laws of large numbers and precise rate in laws of the iterated logarithm, respectively, and subject to some regular conditions, we obtain the corresponding results in partially linear regression models.
Least-squares variance component estimation: theory and GPS applications
Amiri-Simkooei, A.
2007-01-01
In this thesis we study the method of least-squares variance component estimation (LS-VCE) and elaborate on theoretical and practical aspects of the method. We show that LS-VCE is a simple, flexible, and attractive VCE-method. The LS-VCE method is simple because it is based on the well-known principle of least-squares. With this method the estimation of the (co)variance components is based on a linear model of observation equations. The method is flexible since it works with a user-defined we...
The dynamic Allan Variance IV: characterization of atomic clock anomalies.
Galleani, Lorenzo; Tavella, Patrizia
2015-05-01
The number of applications where precise clocks play a key role is steadily increasing, satellite navigation being the main example. Precise clock anomalies are hence critical events, and their characterization is a fundamental problem. When an anomaly occurs, the clock stability changes with time, and this variation can be characterized with the dynamic Allan variance (DAVAR). We obtain the DAVAR for a series of common clock anomalies, namely, a sinusoidal term, a phase jump, a frequency jump, and a sudden change in the clock noise variance. These anomalies are particularly common in space clocks. Our analytic results clarify how the clock stability changes during these anomalies.
On Variance and Covariance for Bounded Linear Operators
Chia Shiang LIN
2001-01-01
In this paper we initiate a study of covariance and variance for two operators on a Hilbert space, proving that the c-v (covariance-variance) inequality holds, which is equivalent to the CauchySchwarz inequality. As for applications of the c-v inequality we prove uniformly the Bernstein-type incqualities and equalities, and show the generalized Heinz-Kato-Furuta-type inequalities and equalities,from which a generalization and sharpening of Reid's inequality is obtained. We show that every operator can be expressed as a p-hyponormal-type, and a hyponornal-type operator. Finally, some new characterizations of the Furuta inequality are given.
赵吝加; 曾维华; 许乃中; 温宗国
2012-01-01
Currently, domestic environmental technologies evaluation methods are mainly based on experts' qualitative estimate and lack of comprehensive evaluation methods. By setting an indicator system of energy conservation and emissions reduction, determining the indicator weight, and constructing the evaluation factors set and its membership function based on AHP and Fuzzy comprehensive evaluation, an evaluation method of advanced and available technologies for energy conservation and emissions reduction of deinking process was established. U-sing this evaluation method, flotation method can be picked out as an advanced and appropriate technology for energy conservation and emissions reduction of deinking process from three technologies including washing, flotation-washing, and flotation. This evaluation method provides a basic method for decision making on deinking technologies evaluation and selection.%针对国内环境技术评估以定性判断为主,缺乏综合评估方法的状况,通过设置节能减排先进适用技术指标体系、确定指标权重、构建评估因素集及其隶属函数等过程,建立基于层次分析和模糊综合评估的定性与定量方法相结合的造纸行业废纸脱墨工艺节能减排先进适用技术评估方法.应用该方法,在洗涤法脱墨技术、浮选法脱墨技术、浮选-洗涤法脱墨技术3项技术中,筛选出浮选法脱墨技术作为废纸制浆脱墨工艺重点推广的节能减排先进适用技术,其余两项技术中,洗涤法脱墨技术优于浮选-洗涤法脱墨技术.
Ortiz, Isabel
2007-01-01
The paper reviews poverty trends and measurements, poverty reduction in historical perspective, the poverty-inequality-growth debate, national poverty reduction strategies, criticisms of the agenda and the need for redistribution, international policies for poverty reduction, and ultimately understanding poverty at a global scale. It belongs to a series of backgrounders developed at Joseph Stiglitz's Initiative for Policy Dialogue.
Models of Postural Control: Shared Variance in Joint and COM Motions.
Kilby, Melissa C; Molenaar, Peter C M; Newell, Karl M
2015-01-01
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.
Models of Postural Control: Shared Variance in Joint and COM Motions.
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.
Lourenco, Stella F; Bonny, Justin W; Fernandez, Edmund P; Rao, Sonia
2012-11-13
Humans and nonhuman animals share the capacity to estimate, without counting, the number of objects in a set by relying on an approximate number system (ANS). Only humans, however, learn the concepts and operations of symbolic mathematics. Despite vast differences between these two systems of quantification, neural and behavioral findings suggest functional connections. Another line of research suggests that the ANS is part of a larger, more general system of magnitude representation. Reports of cognitive interactions and common neural coding for number and other magnitudes such as spatial extent led us to ask whether, and how, nonnumerical magnitude interfaces with mathematical competence. On two magnitude comparison tasks, college students estimated (without counting or explicit calculation) which of two arrays was greater in number or cumulative area. They also completed a battery of standardized math tests. Individual differences in both number and cumulative area precision (measured by accuracy on the magnitude comparison tasks) correlated with interindividual variability in math competence, particularly advanced arithmetic and geometry, even after accounting for general aspects of intelligence. Moreover, analyses revealed that whereas number precision contributed unique variance to advanced arithmetic, cumulative area precision contributed unique variance to geometry. Taken together, these results provide evidence for shared and unique contributions of nonsymbolic number and cumulative area representations to formally taught mathematics. More broadly, they suggest that uniquely human branches of mathematics interface with an evolutionarily primitive general magnitude system, which includes partially overlapping representations of numerical and nonnumerical magnitude.
José Elidney Pinto Júnior
2011-03-01
recursos. A variabilidade genética presente foi representada pelos valores moderados obtidos de herdabilidade individual, no sentido restrito, para o crescimento em diâmetro à altura do peito (DAP, nos três locais estudados. A adoção de estratégias e critérios propostos à seleção permitirá compor uma População Selecionada com duzentos indivíduos de maiores valores genéticos, com número efetivo de progênies adequado, propiciando ganhos para DAP entre 12,89% a 24,33%, em relação à média experimental, no estabelecimento de um Pomar de Sementes por Mudas. A seleção dos vinte indivíduos com os maiores valores genéticos aditivos, para o estabelecimento de um Pomar Clonal de Sementes, poderá propiciar ganhos para DAP entre 17,18% e 50,95%, em relação à média experimental. Por sua vez, a seleção dos vinte melhores indivíduos, com os maiores valores genotípicos, para o estabelecimento de um Jardim Clonal, poderá propiciar ganhos para DAP entre 22,40% a 82,16%, em relação à média experimental, para as plantações clonais resultantes do material selecionado em questão.
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 si
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…
Gender variance in Asia: discursive contestations and legal implications
Wieringa, S.E.
2010-01-01
A recent court case in Indonesia in which a person diagnosed with an intersex condition was classified as a transsexual gives rise to a reflection on three discourses in which gender variance is discussed: the biomedical, the cultural, and the human rights discourse. This article discusses the
Permutation tests for multi-factorial analysis of variance
Anderson, M.J.; Braak, ter C.J.F.
2003-01-01
Several permutation strategies are often possible for tests of individual terms in analysis-of-variance (ANOVA) designs. These include restricted permutations, permutation of whole groups of units, permutation of some form of residuals or some combination of these. It is unclear, especially for
A Hold-out method to correct PCA variance inflation
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 was int...
Similarities Derived from 3-D Nonlinear Psychophysics: Variance Distributions.
Gregson, Robert A. M.
1994-01-01
The derivation of the variance of similarity judgments is made from the 3-D process in nonlinear psychophysics. The idea of separability of dimensions in metric space theories of similarity is replaced by one parameter that represents the degree of a form of interdimensional cross-sampling. (SLD)
Infinite variance in fermion quantum Monte Carlo calculations.
Shi, Hao; Zhang, Shiwei
2016-03-01
For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties without the sign problem. The list spans condensed matter, nuclear physics, and high-energy physics, including the half-filled repulsive Hubbard model, the spin-balanced atomic Fermi gas, and lattice quantum chromodynamics calculations at zero density with Wilson Fermions, and is growing rapidly as a number of problems have been discovered recently to be free of the sign problem. In these situations, QMC calculations are relied on to provide definitive answers. Their results are instrumental to our ability to understand and compute properties in fundamental models important to multiple subareas in quantum physics. It is shown, however, that the most commonly employed algorithms in such situations have an infinite variance problem. A diverging variance causes the estimated Monte Carlo statistical error bar to be incorrect, which can render the results of the calculation unreliable or meaningless. We discuss how to identify the infinite variance problem. An approach is then proposed to solve the problem. The solution does not require major modifications to standard algorithms, adding a "bridge link" to the imaginary-time path integral. The general idea is applicable to a variety of situations where the infinite variance problem may be present. Illustrative results are presented for the ground state of the Hubbard model at half-filling.
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
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
20 CFR 901.40 - Proof; variance; amendment of pleadings.
2010-04-01
... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Proof; variance; amendment of pleadings. 901.40 Section 901.40 Employees' Benefits JOINT BOARD FOR THE ENROLLMENT OF ACTUARIES REGULATIONS GOVERNING THE PERFORMANCE OF ACTUARIAL SERVICES UNDER THE EMPLOYEE RETIREMENT INCOME SECURITY ACT OF...
Multivariate Variance Targeting in the BEKK-GARCH Model
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...
Estimation of dominance variance in purebred Yorkshire swine.
Culbertson, M S; Mabry, J W; Misztal, I; Gengler, N; Bertrand, J K; Varona, L
1998-02-01
We used 179,485 Yorkshire reproductive and 239,354 Yorkshire growth records to estimate additive and dominance variances by Method Fraktur R. Estimates were obtained for number born alive (NBA), 21-d litter weight (LWT), days to 104.5 kg (DAYS), and backfat at 104.5 kg (BF). The single-trait models for NBA and LWT included the fixed effects of contemporary group and regression on inbreeding percentage and the random effects mate within contemporary group, animal permanent environment, animal additive, and parental dominance. The single-trait models for DAYS and BF included the fixed effects of contemporary group, sex, and regression on inbreeding percentage and the random effects litter of birth, dam permanent environment, animal additive, and parental dominance. Final estimates were obtained from six samples for each trait. Regression coefficients for 10% inbreeding were found to be -.23 for NBA, -.52 kg for LWT, 2.1 d for DAYS, and 0 mm for BF. Estimates of additive and dominance variances expressed as a percentage of phenotypic variances were, respectively, 8.8 +/- .5 and 2.2 +/- .7 for NBA, 8.1 +/- 1.1 and 6.3 +/- .9 for LWT, 33.2 +/- .4 and 10.3 +/- 1.5 for DAYS, and 43.6 +/- .9 and 4.8 +/- .7 for BF. The ratio of dominance to additive variances ranged from .78 to .11.
Common Persistence and Error-Correction Mode in Conditional Variance
LI Han-dong; ZHANG Shi-ying
2001-01-01
We firstly define the persistence and common persistence of vector GARCH process from the point of view of the integration, and then discuss the sufficient and necessary condition of the copersistence in variance. In the end of this paper, we give the properties and the error correction model of vector GARCH process under the condition of the co-persistence.
Bounds for Tail Probabilities of the Sample Variance
V. Bentkus
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.
Variance Ranklets : Orientation-selective rank features for contrast modulations
Azzopardi, George; Smeraldi, Fabrizio
2009-01-01
We introduce a novel type of orientation–selective rank features that are sensitive to contrast modulations (second–order stimuli). Variance Ranklets are designed in close analogy with the standard Ranklets, but use the Siegel–Tukey statistics for dispersion instead of the Wilcoxon statistics. Their
A note on minimum-variance theory and beyond
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.
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 s
Average local values and local variances in quantum mechanics
Muga, J G; Sala, P R
1998-01-01
Several definitions for the average local value and local variance of a quantum observable are examined and compared with their classical counterparts. An explicit way to construct an infinite number of these quantities is provided. It is found that different classical conditions may be satisfied by different definitions, but none of the quantum definitions examined is entirely consistent with all classical requirements.
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 Fis
Least-squares variance component estimation: theory and GPS applications
Amiri-Simkooei, A.
2007-01-01
In this thesis we study the method of least-squares variance component estimation (LS-VCE) and elaborate on theoretical and practical aspects of the method. We show that LS-VCE is a simple, flexible, and attractive VCE-method. The LS-VCE method is simple because it is based on the well-known
Multivariate Variance Targeting in the BEKK-GARCH Model
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
Pedersen, Rasmus S.; Rahbæk, 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...
A comparison between temporal and subband minimum variance adaptive beamforming
Diamantis, Konstantinos; Voxen, Iben Holfort; Greenaway, Alan H.
2014-01-01
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...
CAIXA. II. AGNs from excess variance analysis (Ponti+, 2012) [Dataset
Ponti, G.; Papadakis, I.E.; Bianchi, S.; Guainazzi, M.; Matt, G.; Uttley, P.; Bonilla, N.F.
2012-01-01
We report on the results of the first XMM-Newton systematic "excess variance" study of all the radio quiet, X-ray unobscured AGN. The entire sample consist of 161 sources observed by XMM-Newton for more than 10ks in pointed observations, which is the largest sample used so far to study AGN X-ray var
Gender variance in Asia: discursive contestations and legal implications
Wieringa, S.E.
2010-01-01
A recent court case in Indonesia in which a person diagnosed with an intersex condition was classified as a transsexual gives rise to a reflection on three discourses in which gender variance is discussed: the biomedical, the cultural, and the human rights discourse. This article discusses the impli
CAIXA. II. AGNs from excess variance analysis (Ponti+, 2012) [Dataset
Ponti, G.; Papadakis, I.E.; Bianchi, S.; Guainazzi, M.; Matt, G.; Uttley, P.; Bonilla, N.F.
2012-01-01
We report on the results of the first XMM-Newton systematic "excess variance" study of all the radio quiet, X-ray unobscured AGN. The entire sample consist of 161 sources observed by XMM-Newton for more than 10ks in pointed observations, which is the largest sample used so far to study AGN X-ray var
Infinite variance in fermion quantum Monte Carlo calculations
Shi, Hao; Zhang, Shiwei
2016-03-01
For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties without the sign problem. The list spans condensed matter, nuclear physics, and high-energy physics, including the half-filled repulsive Hubbard model, the spin-balanced atomic Fermi gas, and lattice quantum chromodynamics calculations at zero density with Wilson Fermions, and is growing rapidly as a number of problems have been discovered recently to be free of the sign problem. In these situations, QMC calculations are relied on to provide definitive answers. Their results are instrumental to our ability to understand and compute properties in fundamental models important to multiple subareas in quantum physics. It is shown, however, that the most commonly employed algorithms in such situations have an infinite variance problem. A diverging variance causes the estimated Monte Carlo statistical error bar to be incorrect, which can render the results of the calculation unreliable or meaningless. We discuss how to identify the infinite variance problem. An approach is then proposed to solve the problem. The solution does not require major modifications to standard algorithms, adding a "bridge link" to the imaginary-time path integral. The general idea is applicable to a variety of situations where the infinite variance problem may be present. Illustrative results are presented for the ground state of the Hubbard model at half-filling.
Testing for causality in variance using multivariate GARCH models
C.M. Hafner (Christian); H. Herwartz
2004-01-01
textabstractTests of causality in variance in multiple time series have been proposed recently, based on residuals of estimated univariate models. Although such tests are applied frequently little is known about their power properties. In this paper we show that a convenient alternative to residual
Variance Components for NLS: Partitioning the Design Effect.
Folsom, Ralph E., Jr.
This memorandum demonstrates a variance components methodology for partitioning the overall design effect (D) for a ratio mean into stratification (S), unequal weighting (W), and clustering (C) effects, so that D = WSC. In section 2, a sample selection scheme modeled after the National Longitudinal Study of the High School Class of 1972 (NKS)…
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.
Maginnis, P. A.; West, M.; Dullerud, G. E.
2016-10-01
We propose an algorithm to accelerate Monte Carlo simulation for a broad class of stochastic processes. Specifically, the class of countable-state, discrete-time Markov chains driven by additive Poisson noise, or lattice discrete-time Markov chains. In particular, this class includes simulation of reaction networks via the tau-leaping algorithm. To produce the speedup, we simulate pairs of fair-draw trajectories that are negatively correlated. Thus, when averaged, these paths produce an unbiased Monte Carlo estimator that has reduced variance and, therefore, reduced error. Numerical results for three example systems included in this work demonstrate two to four orders of magnitude reduction of mean-square error. The numerical examples were chosen to illustrate different application areas and levels of system complexity. The areas are: gene expression (affine state-dependent rates), aerosol particle coagulation with emission and human immunodeficiency virus infection (both with nonlinear state-dependent rates). Our algorithm views the system dynamics as a "black-box", i.e., we only require control of pseudorandom number generator inputs. As a result, typical codes can be retrofitted with our algorithm using only minor changes. We prove several analytical results. Among these, we characterize the relationship of covariances between paths in the general nonlinear state-dependent intensity rates case, and we prove variance reduction of mean estimators in the special case of affine intensity rates.
Heterogeneity of variances for carcass traits by percentage Brahman inheritance.
Crews, D H; Franke, D E
1998-07-01
Heterogeneity of carcass trait variances due to level of Brahman inheritance was investigated using records from straightbred and crossbred steers produced from 1970 to 1988 (n = 1,530). Angus, Brahman, Charolais, and Hereford sires were mated to straightbred and crossbred cows to produce straightbred, F1, back-cross, three-breed cross, and two-, three-, and four-breed rotational crossbred steers in four non-overlapping generations. At weaning (mean age = 220 d), steers were randomly assigned within breed group directly to the feedlot for 200 d, or to a backgrounding and stocker phase before feeding. Stocker steers were fed from 70 to 100 d in generations 1 and 2 and from 60 to 120 d in generations 3 and 4. Carcass traits included hot carcass weight, subcutaneous fat thickness and longissimus muscle area at the 12-13th rib interface, carcass weight-adjusted longissimus muscle area, USDA yield grade, estimated total lean yield, marbling score, and Warner-Bratzler shear force. Steers were classified as either high Brahman (50 to 100% Brahman), moderate Brahman (25 to 49% Brahman), or low Brahman (0 to 24% Brahman) inheritance. Two types of animal models were fit with regard to level of Brahman inheritance. One model assumed similar variances between pairs of Brahman inheritance groups, and the second model assumed different variances between pairs of Brahman inheritance groups. Fixed sources of variation in both models included direct and maternal additive and nonadditive breed effects, year of birth, and slaughter age. Variances were estimated using derivative free REML procedures. Likelihood ratio tests were used to compare models. The model accounting for heterogeneous variances had a greater likelihood (P carcass weight, longissimus muscle area, weight-adjusted longissimus muscle area, total lean yield, and Warner-Bratzler shear force, indicating improved fit with percentage Brahman inheritance considered as a source of heterogeneity of variance. Genetic
Advances in pediatric anesthesia.
Burns, L S
1997-03-01
Advances in many aspects of pediatric anesthesia have resulted in a significant reduction in morbidity and mortality in children. Research and development have created vast improvements in pharmacology. Sophisticated monitoring and improvements in equipment evolved from advances made in scientific technology. Recognition of the psychological needs of children of all ages likely has reduced the incidence of lasting psychological effects after hospitalization. Finally, these important advances have made pediatric anesthesia a safer and more compassionate specialty.
Simultaneous optimal estimates of fixed effects and variance components in the mixed model
WU Mixia; WANG Songgui
2004-01-01
For a general linear mixed model with two variance components, a set of simple conditions is obtained, under which, (i) the least squares estimate of the fixed effects and the analysis of variance (ANOVA) estimates of variance components are proved to be uniformly minimum variance unbiased estimates simultaneously; (ii) the exact confidence intervals of the fixed effects and uniformly optimal unbiased tests on variance components are given; (iii) the exact probability expression of ANOVA estimates of variance components taking negative value is obtained.
1978-12-01
AD-A041/70 ,4 Poperty of US Air .For, AAIWZ L1 brary AFFDLTR 78-179 ’Wrlght.Peatt Orson AF’B, EFFECT OF VARIANCES AND MANUFACTURING TOLERANCES ON...Degradation For Advanced Composites", Lockheed-California F33615-77-C-3084, Quar- terlies 1977 to Present. Phillips, D. C. and Scott , J. M., "The Shear
Variance in brain volume with advancing age: implications for defining the limits of normality.
David Alexander Dickie
Full Text Available Statistical models of normal ageing brain tissue volumes may support earlier diagnosis of increasingly common, yet still fatal, neurodegenerative diseases. For example, the statistically defined distribution of normal ageing brain tissue volumes may be used as a reference to assess patient volumes. To date, such models were often derived from mean values which were assumed to represent the distributions and boundaries, i.e. percentile ranks, of brain tissue volume. Since it was previously unknown, the objective of the present study was to determine if this assumption was robust, i.e. whether regression models derived from mean values accurately represented the distributions and boundaries of brain tissue volume at older ages.We acquired T1-w magnetic resonance (MR brain images of 227 normal and 219 Alzheimer's disease (AD subjects (aged 55-89 years from publicly available databanks. Using nonlinear regression within both samples, we compared mean and percentile rank estimates of whole brain tissue volume by age.In both the normal and AD sample, mean regression estimates of brain tissue volume often did not accurately represent percentile rank estimates (errors=-74% to 75%. In the normal sample, mean estimates generally underestimated differences in brain volume at percentile ranks below the mean. Conversely, in the AD sample, mean estimates generally underestimated differences in brain volume at percentile ranks above the mean. Differences between ages at the 5(th percentile rank of normal subjects were ~39% greater than mean differences in the AD subjects.While more data are required to make true population inferences, our results indicate that mean regression estimates may not accurately represent the distributions of ageing brain tissue volumes. This suggests that percentile rank estimates will be required to robustly define the limits of brain tissue volume in normal ageing and neurodegenerative disease.
The Reduction of Advanced Military Aircraft Noise
2011-12-01
enterline s ingularity. A non -matching bl ock i nterface c ondition i s de veloped t o a llow t he grids t o be g reatly r efined a round t he c hevrons...T his i s ne eded t o t rigger t he uns teadiness of t he j et flow. T he gr ids a re r efined significantly around the jet potential core. The...dvanced C FD t echnologies a nd t he a coustic a nalogy. T he i mmersed boundary method with local grid r efinement i s used to avoid the di fficulty in
Convergence of Recursive Identification for ARMAX Process with Increasing Variances
JIN Ya; LUO Guiming
2007-01-01
The autoregressive moving average exogenous (ARMAX) model is commonly adopted for describing linear stochastic systems driven by colored noise. The model is a finite mixture with the ARMA component and external inputs. In this paper we focus on a paramete estimate of the ARMAX model. Classical modeling methods are usually based on the assumption that the driven noise in the moving average (MA) part has bounded variances, while in the model considered here the variances of noise may increase by a power of log n. The plant parameters are identified by the recursive stochastic gradient algorithm. The diminishing excitation technique and some results of martingale difference theory are adopted in order to prove the convergence of the identification. Finally, some simulations are given to show the theoretical results.
PORTFOLIO COMPOSITION WITH MINIMUM VARIANCE: COMPARISON WITH MARKET BENCHMARKS
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.
Climate variance influence on the non-stationary plankton dynamics.
Molinero, Juan Carlos; Reygondeau, Gabriel; Bonnet, Delphine
2013-08-01
We examined plankton responses to climate variance by using high temporal resolution data from 1988 to 2007 in the Western English Channel. Climate variability modified both the magnitude and length of the seasonal signal of sea surface temperature, as well as the timing and depth of the thermocline. These changes permeated the pelagic system yielding conspicuous modifications in the phenology of autotroph communities and zooplankton. The climate variance envelope, thus far little considered in climate-plankton studies, is closely coupled with the non-stationary dynamics of plankton, and sheds light on impending ecological shifts and plankton structural changes. Our study calls for the integration of the non-stationary relationship between climate and plankton in prognostic models on the productivity of marine ecosystems.
Multivariate Variance Targeting in the BEKK-GARCH Model
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 to these ......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...... to these two steps. Strong consistency is established under weak moment conditions, while sixth order moment restrictions are imposed to establish asymptotic normality. Included simulations indicate that the multivariately induced higher-order moment constraints are indeed necessary....
Response variance in functional maps: neural darwinism revisited.
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.
Validation technique using mean and variance of kriging model
Kim, Ho Sung; Jung, Jae Jun; Lee, Tae Hee [Hanyang Univ., Seoul (Korea, Republic of)
2007-07-01
To validate rigorously the accuracy of metamodel is an important research area in metamodel techniques. A leave-k-out cross-validation technique not only requires considerable computational cost but also cannot measure quantitatively the fidelity of metamodel. Recently, the average validation technique has been proposed. However the average validation criterion may stop a sampling process prematurely even if kriging model is inaccurate yet. In this research, we propose a new validation technique using an average and a variance of response during a sequential sampling method, such as maximum entropy sampling. The proposed validation technique becomes more efficient and accurate than cross-validation technique, because it integrates explicitly kriging model to achieve an accurate average and variance, rather than numerical integration. The proposed validation technique shows similar trend to root mean squared error such that it can be used as a strop criterion for sequential sampling.
Explaining the Prevalence, Scaling and Variance of Urban Phenomena
Gomez-Lievano, Andres; Hausmann, Ricardo
2016-01-01
The prevalence of many urban phenomena changes systematically with population size. We propose a theory that unifies models of economic complexity and cultural evolution to derive urban scaling. The theory accounts for the difference in scaling exponents and average prevalence across phenomena, as well as the difference in the variance within phenomena across cities of similar size. The central ideas are that a number of necessary complementary factors must be simultaneously present for a phenomenon to occur, and that the diversity of factors is logarithmically related to population size. The model reveals that phenomena that require more factors will be less prevalent, scale more superlinearly and show larger variance across cities of similar size. The theory applies to data on education, employment, innovation, disease and crime, and it entails the ability to predict the prevalence of a phenomenon across cities, given information about the prevalence in a single city.
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.
Sample variance and Lyman-alpha forest transmission statistics
Rollinde, Emmanuel; Schaye, Joop; Pâris, Isabelle; Petitjean, Patrick
2012-01-01
We compare the observed probability distribution function of the transmission in the \\HI\\ Lyman-alpha forest, measured from the UVES 'Large Programme' sample at redshifts z=[2,2.5,3], to results from the GIMIC cosmological simulations. Our measured values for the mean transmission and its PDF are in good agreement with published results. Errors on statistics measured from high-resolution data are typically estimated using bootstrap or jack-knife resampling techniques after splitting the spectra into chunks. We demonstrate that these methods tend to underestimate the sample variance unless the chunk size is much larger than is commonly the case. We therefore estimate the sample variance from the simulations. We conclude that observed and simulated transmission statistics are in good agreement, in particular, we do not require the temperature-density relation to be 'inverted'.
Automated Extraction of Archaeological Traces by a Modified Variance Analysis
Tiziana D'Orazio
2015-03-01
Full Text Available This paper considers the problem of detecting archaeological traces in digital aerial images by analyzing the pixel variance over regions around selected points. In order to decide if a point belongs to an archaeological trace or not, its surrounding regions are considered. The one-way ANalysis Of VAriance (ANOVA is applied several times to detect the differences among these regions; in particular the expected shape of the mark to be detected is used in each region. Furthermore, an effect size parameter is defined by comparing the statistics of these regions with the statistics of the entire population in order to measure how strongly the trace is appreciable. Experiments on synthetic and real images demonstrate the effectiveness of the proposed approach with respect to some state-of-the-art methodologies.
Variable variance Preisach model for multilayers with perpendicular magnetic anisotropy
Franco, A. F.; Gonzalez-Fuentes, C.; Morales, R.; Ross, C. A.; Dumas, R.; Åkerman, J.; Garcia, C.
2016-08-01
We present a variable variance Preisach model that fully accounts for the different magnetization processes of a multilayer structure with perpendicular magnetic anisotropy by adjusting the evolution of the interaction variance as the magnetization changes. We successfully compare in a quantitative manner the results obtained with this model to experimental hysteresis loops of several [CoFeB/Pd ] n multilayers. The effect of the number of repetitions and the thicknesses of the CoFeB and Pd layers on the magnetization reversal of the multilayer structure is studied, and it is found that many of the observed phenomena can be attributed to an increase of the magnetostatic interactions and subsequent decrease of the size of the magnetic domains. Increasing the CoFeB thickness leads to the disappearance of the perpendicular anisotropy, and such a minimum thickness of the Pd layer is necessary to achieve an out-of-plane magnetization.
Analysis of variance in spectroscopic imaging data from human tissues.
Kwak, Jin Tae; Reddy, Rohith; Sinha, Saurabh; Bhargava, Rohit
2012-01-17
The analysis of cell types and disease using Fourier transform infrared (FT-IR) spectroscopic imaging is promising. The approach lacks an appreciation of the limits of performance for the technology, however, which limits both researcher efforts in improving the approach and acceptance by practitioners. One factor limiting performance is the variance in data arising from biological diversity, measurement noise or from other sources. Here we identify the sources of variation by first employing a high throughout sampling platform of tissue microarrays (TMAs) to record a sufficiently large and diverse set data. Next, a comprehensive set of analysis of variance (ANOVA) models is employed to analyze the data. Estimating the portions of explained variation, we quantify the primary sources of variation, find the most discriminating spectral metrics, and recognize the aspects of the technology to improve. The study provides a framework for the development of protocols for clinical translation and provides guidelines to design statistically valid studies in the spectroscopic analysis of tissue.
The return of the variance: intraspecific variability in community ecology.
Violle, Cyrille; Enquist, Brian J; McGill, Brian J; Jiang, Lin; Albert, Cécile H; Hulshof, Catherine; Jung, Vincent; Messier, Julie
2012-04-01
Despite being recognized as a promoter of diversity and a condition for local coexistence decades ago, the importance of intraspecific variance has been neglected over time in community ecology. Recently, there has been a new emphasis on intraspecific variability. Indeed, recent developments in trait-based community ecology have underlined the need to integrate variation at both the intraspecific as well as interspecific level. We introduce new T-statistics ('T' for trait), based on the comparison of intraspecific and interspecific variances of functional traits across organizational levels, to operationally incorporate intraspecific variability into community ecology theory. We show that a focus on the distribution of traits at local and regional scales combined with original analytical tools can provide unique insights into the primary forces structuring communities.
Analysis of Variance in the Modern Design of Experiments
Deloach, Richard
2010-01-01
This paper is a tutorial introduction to the analysis of variance (ANOVA), intended as a reference for aerospace researchers who are being introduced to the analytical methods of the Modern Design of Experiments (MDOE), or who may have other opportunities to apply this method. One-way and two-way fixed-effects ANOVA, as well as random effects ANOVA, are illustrated in practical terms that will be familiar to most practicing aerospace researchers.
Estimating High-Frequency Based (Co-) Variances: A Unified Approach
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...... frequency derived in Bandi & Russell (2005a) and Bandi & Russell (2005b). For a realistic trading scenario, the efficiency gains resulting from our approach are in the range of 35% to 50%....
VARIANCE OF NONLINEAR PHASE NOISE IN FIBER-OPTIC SYSTEM
RANJU KANWAR; SAMEKSHA BHASKAR
2013-01-01
In communication system, the noise process must be known, in order to compute the system performance. The nonlinear effects act as strong perturbation in long- haul system. This perturbation effects the signal, when interact with amplitude noise, and results in random motion of the phase of the signal. Based on the perturbation theory, the variance of nonlinear phase noise contaminated by both self- and cross-phase modulation, is derived analytically for phase-shift- keying system. Through th...
Recombining binomial tree for constant elasticity of variance process
Hi Jun Choe; Jeong Ho Chu; So Jeong Shin
2014-01-01
The theme in this paper is the recombining binomial tree to price American put option when the underlying stock follows constant elasticity of variance(CEV) process. Recombining nodes of binomial tree are decided from finite difference scheme to emulate CEV process and the tree has a linear complexity. Also it is derived from the differential equation the asymptotic envelope of the boundary of tree. Conducting numerical experiments, we confirm the convergence and accuracy of the pricing by ou...
PARAMETER-ESTIMATION FOR ARMA MODELS WITH INFINITE VARIANCE INNOVATIONS
MIKOSCH, T; GADRICH, T; KLUPPELBERG, C; ADLER, RJ
We consider a standard ARMA process of the form phi(B)X(t) = B(B)Z(t), where the innovations Z(t) belong to the domain of attraction of a stable law, so that neither the Z(t) nor the X(t) have a finite variance. Our aim is to estimate the coefficients of phi and theta. Since maximum likelihood
Relationship between Allan variances and Kalman Filter parameters
Vandierendonck, A. J.; Mcgraw, J. B.; Brown, R. G.
1984-01-01
A relationship was constructed between the Allan variance parameters (H sub z, H sub 1, H sub 0, H sub -1 and H sub -2) and a Kalman Filter model that would be used to estimate and predict clock phase, frequency and frequency drift. To start with the meaning of those Allan Variance parameters and how they are arrived at for a given frequency source is reviewed. Although a subset of these parameters is arrived at by measuring phase as a function of time rather than as a spectral density, they all represent phase noise spectral density coefficients, though not necessarily that of a rational spectral density. The phase noise spectral density is then transformed into a time domain covariance model which can then be used to derive the Kalman Filter model parameters. Simulation results of that covariance model are presented and compared to clock uncertainties predicted by Allan variance parameters. A two state Kalman Filter model is then derived and the significance of each state is explained.
Dynamic Programming Using Polar Variance for Image Segmentation.
Rosado-Toro, Jose A; Altbach, Maria I; Rodriguez, Jeffrey J
2016-10-06
When using polar dynamic programming (PDP) for image segmentation, the object size is one of the main features used. This is because if size is left unconstrained the final segmentation may include high-gradient regions that are not associated with the object. In this paper, we propose a new feature, polar variance, which allows the algorithm to segment objects of different sizes without the need for training data. The polar variance is the variance in a polar region between a user-selected origin and a pixel we want to analyze. We also incorporate a new technique that allows PDP to segment complex shapes by finding low-gradient regions and growing them. The experimental analysis consisted on comparing our technique with different active contour segmentation techniques on a series of tests. The tests consisted on robustness to additive Gaussian noise, segmentation accuracy with different grayscale images and finally robustness to algorithm-specific parameters. Experimental results show that our technique performs favorably when compared to other segmentation techniques.
Variance Analysis and Adaptive Sampling for Indirect Light Path Reuse
Hao Qin; Xin Sun; Jun Yan; Qi-Ming Hou; Zhong Ren; Kun Zhou
2016-01-01
In this paper, we study the estimation variance of a set of global illumination algorithms based on indirect light path reuse. These algorithms usually contain two passes — in the first pass, a small number of indirect light samples are generated and evaluated, and they are then reused by a large number of reconstruction samples in the second pass. Our analysis shows that the covariance of the reconstruction samples dominates the estimation variance under high reconstruction rates and increasing the reconstruction rate cannot effectively reduce the covariance. We also find that the covariance represents to what degree the indirect light samples are reused during reconstruction. This analysis motivates us to design a heuristic approximating the covariance as well as an adaptive sampling scheme based on this heuristic to reduce the rendering variance. We validate our analysis and adaptive sampling scheme in the indirect light field reconstruction algorithm and the axis-aligned filtering algorithm for indirect lighting. Experiments are in accordance with our analysis and show that rendering artifacts can be greatly reduced at a similar computational cost.
Variance optimal sampling based estimation of subset sums
Cohen, Edith; Kaplan, Haim; Lund, Carsten; Thorup, Mikkel
2008-01-01
From a high volume stream of weighted items, we want to maintain a generic sample of a certain limited size $k$ that we can later use to estimate the total weight of arbitrary subsets. This is the classic context of on-line reservoir sampling, thinking of the generic sample as a reservoir. We present a reservoir sampling scheme providing variance optimal estimation of subset sums. More precisely, if we have seen $n$ items of the stream, then for any subset size $m$, our scheme based on $k$ samples minimizes the average variance over all subsets of size $m$. In fact, the optimality is against any off-line sampling scheme tailored for the concrete set of items seen: no off-line scheme based on $k$ samples can perform better than our on-line scheme when it comes to average variance over any subset size. Our scheme has no positive covariances between any pair of item estimates. Also, our scheme can handle each new item of the stream in $O(\\log k)$ time, which is optimal even on the word RAM.
Genetic variance of tolerance and the toxicant threshold model.
Tanaka, Yoshinari; Mano, Hiroyuki; Tatsuta, Haruki
2012-04-01
A statistical genetics method is presented for estimating the genetic variance (heritability) of tolerance to pollutants on the basis of a standard acute toxicity test conducted on several isofemale lines of cladoceran species. To analyze the genetic variance of tolerance in the case when the response is measured as a few discrete states (quantal endpoints), the authors attempted to apply the threshold character model in quantitative genetics to the threshold model separately developed in ecotoxicology. The integrated threshold model (toxicant threshold model) assumes that the response of a particular individual occurs at a threshold toxicant concentration and that the individual tolerance characterized by the individual's threshold value is determined by genetic and environmental factors. As a case study, the heritability of tolerance to p-nonylphenol in the cladoceran species Daphnia galeata was estimated by using the maximum likelihood method and nested analysis of variance (ANOVA). Broad-sense heritability was estimated to be 0.199 ± 0.112 by the maximum likelihood method and 0.184 ± 0.089 by ANOVA; both results implied that the species examined had the potential to acquire tolerance to this substance by evolutionary change.
Measuring primordial non-gaussianity without cosmic variance
Seljak, Uros
2008-01-01
Non-gaussianity in the initial conditions of the universe is one of the most powerful mechanisms to discriminate among the competing theories of the early universe. Measurements using bispectrum of cosmic microwave background anisotropies are limited by the cosmic variance, i.e. available number of modes. Recent work has emphasized the possibility to probe non-gaussianity of local type using the scale dependence of large scale bias from highly biased tracers of large scale structure. However, this power spectrum method is also limited by cosmic variance, finite number of structures on the largest scales, and by the partial degeneracy with other cosmological parameters that can mimic the same effect. Here we propose an alternative method that solves both of these problems. It is based on the idea that on large scales halos are biased, but not stochastic, tracers of dark matter: by correlating a highly biased tracer of large scale structure against an unbiased tracer one eliminates the cosmic variance error, wh...
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.
Winkler, Tilo; Melo, Marcos F Vidal; Degani-Costa, Luiza H; Harris, R Scott; Correia, John A; Musch, Guido; Venegas, Jose G
2015-01-01
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(r)2. Additional evaluations were conducted on 38 PET scans of pulmonary perfusion using (13)NN-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.
Litzow, Michael A.; Piatt, J.F.
2003-01-01
We use data on pigeon guillemots Cepphus columba to test the hypothesis that discretionary time in breeding seabirds is correlated with variance in prey abundance. We measured the amount of time that guillemots spent at the colony before delivering fish to chicks ("resting time") in relation to fish abundance as measured by beach seines and bottom trawls. Radio telemetry showed that resting time was inversely correlated with time spent diving for fish during foraging trips (r = -0.95). Pigeon guillemots fed their chicks either Pacific sand lance Ammodytes hexapterus, a schooling midwater fish, which exhibited high interannual variance in abundance (CV = 181%), or a variety of non-schooling demersal fishes, which were less variable in abundance (average CV = 111%). Average resting times were 46% higher at colonies where schooling prey dominated the diet. Individuals at these colonies reduced resting times 32% during years of low food abundance, but did not reduce meal delivery rates. In contrast, individuals feeding on non-schooling fishes did not reduce resting times during low food years, but did reduce meal delivery rates by 27%. Interannual variance in resting times was greater for the schooling group than for the non-schooling group. We conclude from these differences that time allocation in pigeon guillemots is more flexible when variable schooling prey dominate diets. Resting times were also 27% lower for individuals feeding two-chick rather than one-chick broods. The combined effects of diet and brood size on adult time budgets may help to explain higher rates of brood reduction for pigeon guillemot chicks fed non-schooling fishes.
Female Scarcity Reduces Women's Marital Ages and Increases Variance in Men's Marital Ages
Daniel J. Kruger
2010-07-01
Full Text Available When women are scarce in a population relative to men, they have greater bargaining power in romantic relationships and thus may be able to secure male commitment at earlier ages. Male motivation for long-term relationship commitment may also be higher, in conjunction with the motivation to secure a prospective partner before another male retains her. However, men may also need to acquire greater social status and resources to be considered marriageable. This could increase the variance in male marital age, as well as the average male marital age. We calculated the Operational Sex Ratio, and means, medians, and standard deviations in marital ages for women and men for the 50 largest Metropolitan Statistical Areas in the United States with 2000 U.S Census data. As predicted, where women are scarce they marry earlier on average. However, there was no significant relationship with mean male marital ages. The variance in male marital age increased with higher female scarcity, contrasting with a non-significant inverse trend for female marital age variation. These findings advance the understanding of the relationship between the OSR and marital patterns. We believe that these results are best accounted for by sex specific attributes of reproductive value and associated mate selection criteria, demonstrating the power of an evolutionary framework for understanding human relationships and demographic patterns.
Sørensen, Anders Christian; Kristensen, Torsten Nygård; Loeschcke, Volker
2007-01-01
quantitative genetics model based on the infinitesimal model, and an extension of this model. In the extended model it is assumed that each individual has its own environmental variance and that this heterogeneity of variance has a genetic component. The heterogeneous variance model was favoured by the data......, indicating that the environmental variance is partly under genetic control. If this heterogeneous variance model also applies to livestock, it would be possible to select for animals with a higher uniformity of products across environmental regimes. Also for evolutionary biology the results are of interest...
Variance as a Leading Indicator of Regime Shift in Ecosystem Services
William A. Brock
2006-12-01
Full Text Available Many environmental conflicts involve pollutants such as greenhouse gas emissions that are dispersed through space and cause losses of ecosystem services. As pollutant emissions rise in one place, a spatial cascade of declining ecosystem services can spread across a larger landscape because of the dispersion of the pollutant. This paper considers the problem of anticipating such spatial regime shifts by monitoring time series of the pollutant or associated ecosystem services. Using such data, it is possible to construct indicators that rise sharply in advance of regime shifts. Specifically, the maximum eigenvalue of the variance-covariance matrix of the multivariate time series of pollutants and ecosystem services rises prior to the regime shift. No specific knowledge of the mechanisms underlying the regime shift is needed to construct the indicator. Such leading indicators of regime shifts could provide useful signals to management agencies or to investors in ecosystem service markets.
Loberg, A; Dürr, J W; Fikse, W F; Jorjani, H; Crooks, L
2015-10-01
The amount of variance captured in genetic estimations may depend on whether a pedigree-based or genomic relationship matrix is used. The purpose of this study was to investigate the genetic variance as well as the variance of predicted genetic merits (PGM) using pedigree-based or genomic relationship matrices in Brown Swiss cattle. We examined a range of traits in six populations amounting to 173 population-trait combinations. A main aim was to determine how using different relationship matrices affect variance estimation. We calculated ratios between different types of estimates and analysed the impact of trait heritability and population size. The genetic variances estimated by REML using a genomic relationship matrix were always smaller than the variances that were similarly estimated using a pedigree-based relationship matrix. The variances from the genomic relationship matrix became closer to estimates from a pedigree relationship matrix as heritability and population size increased. In contrast, variances of predicted genetic merits obtained using a genomic relationship matrix were mostly larger than variances of genetic merit predicted using pedigree-based relationship matrix. The ratio of the genomic to pedigree-based PGM variances decreased as heritability and population size rose. The increased variance among predicted genetic merits is important for animal breeding because this is one of the factors influencing genetic progress. © 2015 Blackwell Verlag GmbH.
Dominance Genetic Variance for Traits Under Directional Selection in Drosophila serrata
Sztepanacz, Jacqueline L.; Blows, Mark W.
2015-01-01
In contrast to our growing understanding of patterns of additive genetic variance in single- and multi-trait combinations, the relative contribution of nonadditive genetic variance, particularly dominance variance, to multivariate phenotypes is largely unknown. While mechanisms for the evolution of dominance genetic variance have been, and to some degree remain, subject to debate, the pervasiveness of dominance is widely recognized and may play a key role in several evolutionary processes. Theoretical and empirical evidence suggests that the contribution of dominance variance to phenotypic variance may increase with the correlation between a trait and fitness; however, direct tests of this hypothesis are few. Using a multigenerational breeding design in an unmanipulated population of Drosophila serrata, we estimated additive and dominance genetic covariance matrices for multivariate wing-shape phenotypes, together with a comprehensive measure of fitness, to determine whether there is an association between directional selection and dominance variance. Fitness, a trait unequivocally under directional selection, had no detectable additive genetic variance, but significant dominance genetic variance contributing 32% of the phenotypic variance. For single and multivariate morphological traits, however, no relationship was observed between trait–fitness correlations and dominance variance. A similar proportion of additive and dominance variance was found to contribute to phenotypic variance for single traits, and double the amount of additive compared to dominance variance was found for the multivariate trait combination under directional selection. These data suggest that for many fitness components a positive association between directional selection and dominance genetic variance may not be expected. PMID:25783700
Regression between earthquake magnitudes having errors with known variances
Pujol, Jose
2016-07-01
Recent publications on the regression between earthquake magnitudes assume that both magnitudes are affected by error and that only the ratio of error variances is known. If X and Y represent observed magnitudes, and x and y represent the corresponding theoretical values, the problem is to find the a and b of the best-fit line y = a x + b. This problem has a closed solution only for homoscedastic errors (their variances are all equal for each of the two variables). The published solution was derived using a method that cannot provide a sum of squares of residuals. Therefore, it is not possible to compare the goodness of fit for different pairs of magnitudes. Furthermore, the method does not provide expressions for the x and y. The least-squares method introduced here does not have these drawbacks. The two methods of solution result in the same equations for a and b. General properties of a discussed in the literature but not proved, or proved for particular cases, are derived here. A comparison of different expressions for the variances of a and b is provided. The paper also considers the statistical aspects of the ongoing debate regarding the prediction of y given X. Analysis of actual data from the literature shows that a new approach produces an average improvement of less than 0.1 magnitude units over the standard approach when applied to Mw vs. mb and Mw vs. MS regressions. This improvement is minor, within the typical error of Mw. Moreover, a test subset of 100 predicted magnitudes shows that the new approach results in magnitudes closer to the theoretically true magnitudes for only 65 % of them. For the remaining 35 %, the standard approach produces closer values. Therefore, the new approach does not always give the most accurate magnitude estimates.
Critical points of multidimensional random Fourier series: Variance estimates
Nicolaescu, Liviu I.
2016-08-01
We investigate the number of critical points of a Gaussian random smooth function uɛ on the m-torus Tm ≔ ℝm/ℤm approximating the Gaussian white noise as ɛ → 0. Let N(uɛ) denote the number of critical points of uɛ. We prove the existence of constants C, C' such that as ɛ goes to zero, the expectation of the random variable ɛmN(uɛ) converges to C, while its variance is extremely small and behaves like C'ɛm.
Generalized Minimum Variance Control for MDOF Structures under Earthquake Excitation
Lakhdar Guenfaf
2016-01-01
Full Text Available Control of a multi-degree-of-freedom structural system under earthquake excitation is investigated in this paper. The control approach based on the Generalized Minimum Variance (GMV algorithm is developed and presented. Our approach is a generalization to multivariable systems of the GMV strategy designed initially for single-input-single-output (SISO systems. Kanai-Tajimi and Clough-Penzien models are used to generate the seismic excitations. Those models are calculated using the specific soil parameters. Simulation tests using a 3DOF structure are performed and show the effectiveness of the control method.
Stable limits for sums of dependent infinite variance random variables
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 results are qualitative in the sense that the parameters of the limit distribution are expressed in terms of some limiting point process. In this paper we will be able to determine the parameters of the limiting stable distribution in terms of some tail characteristics of the underlying stationary...
Minimum Variance Beamforming for High Frame-Rate Ultrasound Imaging
Holfort, Iben Kraglund; Gran, Fredrik; Jensen, Jørgen Arendt
2007-01-01
This paper investigates the application of adaptive beamforming in medical ultrasound imaging. A minimum variance (MV) approach for near-field beamforming of broadband data is proposed. The approach is implemented in the frequency domain, and it provides a set of adapted, complex apodization...... 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...
Computing the Expected Value and Variance of Geometric Measures
Staals, Frank; Tsirogiannis, Constantinos
2017-01-01
points in P. This problem is a crucial part of modern ecological analyses; each point in P represents a species in d-dimensional trait space, and the goal is to compute the statistics of a geometric measure on this trait space, when subsets of species are selected under random processes. We present...... efficient exact algorithms for computing the mean and variance of several geometric measures when point sets are selected under one of the described random distributions. More specifically, we provide algorithms for the following measures: the bounding box volume, the convex hull volume, the mean pairwise...
Multivariate variance targeting in the BEKK-GARCH model
Pedersen, Rasmus S.; Rahbæk, 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...... to these two steps. Strong consis-tency is established under weak moment conditions, while sixth-order moment restrictions are imposed to establish asymptotic normality. Included simulations indicate that the multivariately induced higher-order moment constraints are necessary...
A guide to SPSS for analysis of variance
Levine, Gustav
2013-01-01
This book offers examples of programs designed for analysis of variance and related statistical tests of significance that can be run with SPSS. The reader may copy these programs directly, changing only the names or numbers of levels of factors according to individual needs. Ways of altering command specifications to fit situations with larger numbers of factors are discussed and illustrated, as are ways of combining program statements to request a variety of analyses in the same program. The first two chapters provide an introduction to the use of SPSS, Versions 3 and 4. General rules conce
Variance-optimal hedging for processes with stationary independent increments
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...... show that for this class of processes the optimal endowment and strategy can be expressed more explicitly. The corresponding formulas involve the moment resp. cumulant generating function of the underlying process and a Laplace- or Fourier-type representation of the contingent claim. An example...
Two-dimensional finite-element temperature variance analysis
Heuser, J. S.
1972-01-01
The finite element method is extended to thermal analysis by forming a variance analysis of temperature results so that the sensitivity of predicted temperatures to uncertainties in input variables is determined. The temperature fields within a finite number of elements are described in terms of the temperatures of vertices and the variational principle is used to minimize the integral equation describing thermal potential energy. A computer calculation yields the desired solution matrix of predicted temperatures and provides information about initial thermal parameters and their associated errors. Sample calculations show that all predicted temperatures are most effected by temperature values along fixed boundaries; more accurate specifications of these temperatures reduce errors in thermal calculations.
Local orbitals by minimizing powers of the orbital variance
Jansik, Branislav; Høst, Stinne; Kristensen, Kasper;
2011-01-01
It is demonstrated that a set of local orthonormal Hartree–Fock (HF) molecular orbitals can be obtained for both the occupied and virtual orbital spaces by minimizing powers of the orbital variance using the trust-region algorithm. For a power exponent equal to one, the Boys localization function...... is obtained. For increasing power exponents, the penalty for delocalized orbitals is increased and smaller maximum orbital spreads are encountered. Calculations on superbenzene, C60, and a fragment of the titin protein show that for a power exponent equal to one, delocalized outlier orbitals may...
A Mean-Variance Portfolio Optimal Under Utility Pricing
HÃ¼rlimann Werner
2006-01-01
Full Text Available An expected utility model of asset choice, which takes into account asset pricing, is considered. The obtained portfolio selection problem under utility pricing is solved under several assumptions including quadratic utility, exponential utility and multivariate symmetric elliptical returns. The obtained unique solution, called optimal utility portfolio, is shown mean-variance efficient in the classical sense. Various questions, including conditions for complete diversification and the behavior of the optimal portfolio under univariate and multivariate ordering of risks as well as risk-adjusted performance measurement, are discussed.
Budde, M.E.; Tappan, G.; Rowland, J.; Lewis, J.; Tieszen, L.L.
2004-01-01
The researchers calculated seasonal integrated normalized difference vegetation index (NDVI) for each of 7 years using a time-series of 1-km data from the Advanced Very High Resolution Radiometer (AVHRR) (1992-93, 1995) and SPOT Vegetation (1998-2001) sensors. We used a local variance technique to identify each pixel as normal or either positively or negatively anomalous when compared to its surroundings. We then summarized the number of years that a given pixel was identified as an anomaly. The resulting anomaly maps were analysed using Landsat TM imagery and extensive ground knowledge to assess the results. This technique identified anomalies that can be linked to numerous anthropogenic impacts including agricultural and urban expansion, maintenance of protected areas and increased fallow. Local variance analysis is a reliable method for assessing vegetation degradation resulting from human pressures or increased land productivity from natural resource management practices. ?? 2004 Published by Elsevier Ltd.
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 portfolio and T the length of the time series used to estimate the covariance matrix. At the critical point r = 1 a phase transition is taking place. The out of sample estimation error blows up at this point as 1/(1 - r), independently of the covariance matrix or the expected return, displaying the universality not only of the critical exponent, but also the critical point. As a conspicuous illustration of the dangers of in-sample estimates, the optimal in-sample variance is found to vanish at the critical point inversely proportional to the divergent estimation error.
MENENTUKAN PORTOFOLIO OPTIMAL MENGGUNAKAN MODEL CONDITIONAL MEAN VARIANCE
I GEDE ERY NISCAHYANA
2016-08-01
Full Text Available When the returns of stock prices show the existence of autocorrelation and heteroscedasticity, then conditional mean variance models are suitable method to model the behavior of the stocks. In this thesis, the implementation of the conditional mean variance model to the autocorrelated and heteroscedastic return was discussed. The aim of this thesis was to assess the effect of the autocorrelated and heteroscedastic returns to the optimal solution of a portfolio. The margin of four stocks, Fortune Mate Indonesia Tbk (FMII.JK, Bank Permata Tbk (BNLI.JK, Suryamas Dutamakmur Tbk (SMDM.JK dan Semen Gresik Indonesia Tbk (SMGR.JK were estimated by GARCH(1,1 model with standard innovations following the standard normal distribution and the t-distribution. The estimations were used to construct a portfolio. The portfolio optimal was found when the standard innovation used was t-distribution with the standard deviation of 1.4532 and the mean of 0.8023 consisting of 0.9429 (94% of FMII stock, 0.0473 (5% of BNLI stock, 0% of SMDM stock, 1% of SMGR stock.
Facial Feature Extraction Method Based on Coefficients of Variances
Feng-Xi Song; David Zhang; Cai-Kou Chen; Jing-Yu Yang
2007-01-01
Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are two popular feature ex- traction techniques in statistical pattern recognition field. Due to small sample size problem LDA cannot be directly applied to appearance-based face recognition tasks. As a consequence, a lot of LDA-based facial feature extraction techniques are proposed to deal with the problem one after the other. Nullspace Method is one of the most effective methods among them. The Nullspace Method tries to find a set of discriminant vectors which maximize the between-class scatter in the null space of the within-class scatter matrix. The calculation of its discriminant vectors will involve performing singular value decomposition on a high-dimensional matrix. It is generally memory- and time-consuming. Borrowing the key idea in Nullspace method and the concept of coefficient of variance in statistical analysis we present a novel facial feature extraction method, i.e., Discriminant based on Coefficient of Variance (DCV) in this paper. Experimental results performed on the FERET and AR face image databases demonstrate that DCV is a promising technique in comparison with Eigenfaces, Nullspace Method, and other state-of-the-art facial feature extraction methods.
Cosmic variance of the galaxy cluster weak lensing signal
Gruen, D; Becker, M R; Friedrich, O; Mana, A
2015-01-01
Intrinsic variations of the projected density profiles of clusters of galaxies at fixed mass are a source of uncertainty for cluster weak lensing. We present a semi-analytical model to account for this effect, based on a combination of variations in halo concentration, ellipticity and orientation, and the presence of correlated haloes. We calibrate the parameters of our model at the 10 per cent level to match the empirical cosmic variance of cluster profiles at M_200m=10^14...10^15 h^-1 M_sol, z=0.25...0.5 in a cosmological simulation. We show that weak lensing measurements of clusters significantly underestimate mass uncertainties if intrinsic profile variations are ignored, and that our model can be used to provide correct mass likelihoods. Effects on the achievable accuracy of weak lensing cluster mass measurements are particularly strong for the most massive clusters and deep observations (with ~20 per cent uncertainty from cosmic variance alone at M_200m=10^15 h^-1 M_sol and z=0.25), but significant also...
Mean-Variance-Validation Technique for Sequential Kriging Metamodels
Lee, Tae Hee; Kim, Ho Sung [Hanyang University, Seoul (Korea, Republic of)
2010-05-15
The rigorous validation of the accuracy of metamodels is an important topic in research on metamodel techniques. Although a leave-k-out cross-validation technique involves a considerably high computational cost, it cannot be used to measure the fidelity of metamodels. Recently, the mean{sub 0} validation technique has been proposed to quantitatively determine the accuracy of metamodels. However, the use of mean{sub 0} validation criterion may lead to premature termination of a sampling process even if the kriging model is inaccurate. In this study, we propose a new validation technique based on the mean and variance of the response evaluated when sequential sampling method, such as maximum entropy sampling, is used. The proposed validation technique is more efficient and accurate than the leave-k-out cross-validation technique, because instead of performing numerical integration, the kriging model is explicitly integrated to accurately evaluate the mean and variance of the response evaluated. The error in the proposed validation technique resembles a root mean squared error, thus it can be used to determine a stop criterion for sequential sampling of metamodels.
Infinite Variance in Fermion Quantum Monte Carlo Calculations
Shi, Hao
2015-01-01
For important classes of many-fermion problems, quantum Monte Carlo (QMC) methods allow exact calculations of ground-state and finite-temperature properties, without the sign problem. The list spans condensed matter, nuclear physics, and high-energy physics, including the half-filled repulsive Hubbard model, the spin-balanced atomic Fermi gas, lattice QCD calculations at zero density with Wilson Fermions, and is growing rapidly as a number of problems have been discovered recently to be free of the sign problem. In these situations, QMC calculations are relied upon to provide definitive answers. Their results are instrumental to our ability to understand and compute properties in fundamental models important to multiple sub-areas in quantum physics. It is shown, however, that the most commonly employed algorithms in such situations turn out to have an infinite variance problem. A diverging variance causes the estimated Monte Carlo statistical error bar to be incorrect, which can render the results of the calc...
Deterministic mean-variance-optimal consumption and investment
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...
The Variance of Energy Estimates for the Product Model
David Smallwood
2003-01-01
, is the product of a slowly varying random window, {w(t}, and a stationary random process, {g(t}, is defined. A single realization of the process will be defined as x(t. This is slightly different from the usual definition of the product model where the window is typically defined as deterministic. An estimate of the energy (the zero order temporal moment, only in special cases is this physical energy of the random process, {x(t}, is defined as m0=∫∞∞|x(t|2dt=∫−∞∞|w(tg(t|2dt Relationships for the mean and variance of the energy estimates, m0, are then developed. It is shown that for many cases the uncertainty (4π times the product of rms duration, Dt, and rms bandwidth, Df is approximately the inverse of the normalized variance of the energy. The uncertainty is a quantitative measure of the expected error in the energy estimate. If a transient has a significant random component, a small uncertainty parameter implies large error in the energy estimate. Attempts to resolve a time/frequency spectrum near the uncertainty limits of a transient with a significant random component will result in large errors in the spectral estimates.
Cosmic variance in the nanohertz gravitational wave background
Roebber, Elinore; Holz, Daniel; Warren, Michael
2015-01-01
We use large N-body simulations and empirical scaling relations between dark matter halos, galaxies, and supermassive black holes to estimate the formation rates of supermassive black hole binaries and the resulting low-frequency stochastic gravitational wave background (GWB). We find this GWB to be relatively insensitive ($\\lesssim10\\%$) to cosmological parameters, with only slight variation between WMAP5 and Planck cosmologies. We find that uncertainty in the astrophysical scaling relations changes the amplitude of the GWB by a factor of $\\sim 2$. Current observational limits are already constraining this predicted range of models. We investigate the Poisson variance in the amplitude of the GWB for randomly-generated populations of supermassive black holes, finding a scatter of order unity per frequency bin below 10 nHz, and increasing to a factor of $\\sim 10$ near 100 nHz. This variance is a result of the rarity of the most massive binaries, which dominate the signal, and acts as a fundamental uncertainty ...
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
Worldwide variance in the potential utilization of Gamma Knife radiosurgery.
Hamilton, Travis; Dade Lunsford, L
2016-12-01
OBJECTIVE The role of Gamma Knife radiosurgery (GKRS) has expanded worldwide during the past 3 decades. The authors sought to evaluate whether experienced users vary in their estimate of its potential use. METHODS Sixty-six current Gamma Knife users from 24 countries responded to an electronic survey. They estimated the potential role of GKRS for benign and malignant tumors, vascular malformations, and functional disorders. These estimates were compared with published disease epidemiological statistics and the 2014 use reports provided by the Leksell Gamma Knife Society (16,750 cases). RESULTS Respondents reported no significant variation in the estimated use in many conditions for which GKRS is performed: meningiomas, vestibular schwannomas, and arteriovenous malformations. Significant variance in the estimated use of GKRS was noted for pituitary tumors, craniopharyngiomas, and cavernous malformations. For many current indications, the authors found significant variance in GKRS users based in the Americas, Europe, and Asia. Experts estimated that GKRS was used in only 8.5% of the 196,000 eligible cases in 2014. CONCLUSIONS Although there was a general worldwide consensus regarding many major indications for GKRS, significant variability was noted for several more controversial roles. This expert opinion survey also suggested that GKRS is significantly underutilized for many current diagnoses, especially in the Americas. Future studies should be conducted to investigate health care barriers to GKRS for many patients.
VARIANCE OF NONLINEAR PHASE NOISE IN FIBER-OPTIC SYSTEM
RANJU KANWAR
2013-04-01
Full Text Available In communication system, the noise process must be known, in order to compute the system performance. The nonlinear effects act as strong perturbation in long- haul system. This perturbation effects the signal, when interact with amplitude noise, and results in random motion of the phase of the signal. Based on the perturbation theory, the variance of nonlinear phase noise contaminated by both self- and cross-phase modulation, is derived analytically for phase-shift- keying system. Through this work, it is investigated that for longer transmission distance, 40-Gb/s systems are more sensitive to nonlinear phase noise as compared to 50-Gb/s systems. Also, when transmitting the data through the fiber optic link, bit errors are produced due to various effects such as noise from optical amplifiers and nonlinearity occurring in fiber. On the basis of the simulation results , we have compared the bit error rate based on 8-PSK with theoretical results, and result shows that in real time approach, the bit error rate is high for the same signal to noise ratio. MATLAB software is used to validate the analytical expressions for the variance of nonlinear phase noise.
Hidden temporal order unveiled in stock market volatility variance
Y. Shapira
2011-06-01
Full Text Available When analyzed by standard statistical methods, the time series of the daily return of financial indices appear to behave as Markov random series with no apparent temporal order or memory. This empirical result seems to be counter intuitive since investor are influenced by both short and long term past market behaviors. Consequently much effort has been devoted to unveil hidden temporal order in the market dynamics. Here we show that temporal order is hidden in the series of the variance of the stocks volatility. First we show that the correlation between the variances of the daily returns and means of segments of these time series is very large and thus cannot be the output of random series, unless it has some temporal order in it. Next we show that while the temporal order does not show in the series of the daily return, rather in the variation of the corresponding volatility series. More specifically, we found that the behavior of the shuffled time series is equivalent to that of a random time series, while that of the original time series have large deviations from the expected random behavior, which is the result of temporal structure. We found the same generic behavior in 10 different stock markets from 7 different countries. We also present analysis of specially constructed sequences in order to better understand the origin of the observed temporal order in the market sequences. Each sequence was constructed from segments with equal number of elements taken from algebraic distributions of three different slopes.
Shrivastava, Manish [Pacific Northwest National Laboratory, Richland Washington USA; Zhao, Chun [Pacific Northwest National Laboratory, Richland Washington USA; Easter, Richard C. [Pacific Northwest National Laboratory, Richland Washington USA; Qian, Yun [Pacific Northwest National Laboratory, Richland Washington USA; Zelenyuk, Alla [Pacific Northwest National Laboratory, Richland Washington USA; Fast, Jerome D. [Pacific Northwest National Laboratory, Richland Washington USA; Liu, Ying [Pacific Northwest National Laboratory, Richland Washington USA; Zhang, Qi [Department of Environmental Toxicology, University of California Davis, California USA; Guenther, Alex [Department of Earth System Science, University of California, Irvine California USA
2016-04-08
We investigate the sensitivity of secondary organic aerosol (SOA) loadings simulated by a regional chemical transport model to 7 selected tunable model parameters: 4 involving emissions of anthropogenic and biogenic volatile organic compounds, anthropogenic semi-volatile and intermediate volatility organics (SIVOCs), and NOx, 2 involving dry deposition of SOA precursor gases, and one involving particle-phase transformation of SOA to low volatility. We adopt a quasi-Monte Carlo sampling approach to effectively sample the high-dimensional parameter space, and perform a 250 member ensemble of simulations using a regional model, accounting for some of the latest advances in SOA treatments based on our recent work. We then conduct a variance-based sensitivity analysis using the generalized linear model method to study the responses of simulated SOA loadings to the tunable parameters. Analysis of SOA variance from all 250 simulations shows that the volatility transformation parameter, which controls whether particle-phase transformation of SOA from semi-volatile SOA to non-volatile is on or off, is the dominant contributor to variance of simulated surface-level daytime SOA (65% domain average contribution). We also split the simulations into 2 subsets of 125 each, depending on whether the volatility transformation is turned on/off. For each subset, the SOA variances are dominated by the parameters involving biogenic VOC and anthropogenic SIVOC emissions. Furthermore, biogenic VOC emissions have a larger contribution to SOA variance when the SOA transformation to non-volatile is on, while anthropogenic SIVOC emissions have a larger contribution when the transformation is off. NOx contributes less than 4.3% to SOA variance, and this low contribution is mainly attributed to dominance of intermediate to high NOx conditions throughout the simulated domain. The two parameters related to dry deposition of SOA precursor gases also have very low contributions to SOA variance
Kriging with Unknown Variance Components for Regional Ionospheric Reconstruction
Ling Huang
2017-02-01
Full Text Available Ionospheric delay effect is a critical issue that limits the accuracy of precise Global Navigation Satellite System (GNSS positioning and navigation for single-frequency users, especially in mid- and low-latitude regions where variations in the ionosphere are larger. Kriging spatial interpolation techniques have been recently introduced to model the spatial correlation and variability of ionosphere, which intrinsically assume that the ionosphere field is stochastically stationary but does not take the random observational errors into account. In this paper, by treating the spatial statistical information on ionosphere as prior knowledge and based on Total Electron Content (TEC semivariogram analysis, we use Kriging techniques to spatially interpolate TEC values. By assuming that the stochastic models of both the ionospheric signals and measurement errors are only known up to some unknown factors, we propose a new Kriging spatial interpolation method with unknown variance components for both the signals of ionosphere and TEC measurements. Variance component estimation has been integrated with Kriging to reconstruct regional ionospheric delays. The method has been applied to data from the Crustal Movement Observation Network of China (CMONOC and compared with the ordinary Kriging and polynomial interpolations with spherical cap harmonic functions, polynomial functions and low-degree spherical harmonic functions. The statistics of results indicate that the daily ionospheric variations during the experimental period characterized by the proposed approach have good agreement with the other methods, ranging from 10 to 80 TEC Unit (TECU, 1 TECU = 1 × 1016 electrons/m2 with an overall mean of 28.2 TECU. The proposed method can produce more appropriate estimations whose general TEC level is as smooth as the ordinary Kriging but with a smaller standard deviation around 3 TECU than others. The residual results show that the interpolation precision of the
Kriging with Unknown Variance Components for Regional Ionospheric Reconstruction.
Huang, Ling; Zhang, Hongping; Xu, Peiliang; Geng, Jianghui; Wang, Cheng; Liu, Jingnan
2017-02-27
Ionospheric delay effect is a critical issue that limits the accuracy of precise Global Navigation Satellite System (GNSS) positioning and navigation for single-frequency users, especially in mid- and low-latitude regions where variations in the ionosphere are larger. Kriging spatial interpolation techniques have been recently introduced to model the spatial correlation and variability of ionosphere, which intrinsically assume that the ionosphere field is stochastically stationary but does not take the random observational errors into account. In this paper, by treating the spatial statistical information on ionosphere as prior knowledge and based on Total Electron Content (TEC) semivariogram analysis, we use Kriging techniques to spatially interpolate TEC values. By assuming that the stochastic models of both the ionospheric signals and measurement errors are only known up to some unknown factors, we propose a new Kriging spatial interpolation method with unknown variance components for both the signals of ionosphere and TEC measurements. Variance component estimation has been integrated with Kriging to reconstruct regional ionospheric delays. The method has been applied to data from the Crustal Movement Observation Network of China (CMONOC) and compared with the ordinary Kriging and polynomial interpolations with spherical cap harmonic functions, polynomial functions and low-degree spherical harmonic functions. The statistics of results indicate that the daily ionospheric variations during the experimental period characterized by the proposed approach have good agreement with the other methods, ranging from 10 to 80 TEC Unit (TECU, 1 TECU = 1 × 10(16) electrons/m²) with an overall mean of 28.2 TECU. The proposed method can produce more appropriate estimations whose general TEC level is as smooth as the ordinary Kriging but with a smaller standard deviation around 3 TECU than others. The residual results show that the interpolation precision of the new proposed
Interdependence of NAFTA capital markets: A minimum variance portfolio approach
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.
Estimation of measurement variance in the context of environment statistics
Maiti, Pulakesh
2015-02-01
The object of environment statistics is for providing information on the environment, on its most important changes over time, across locations and identifying the main factors that influence them. Ultimately environment statistics would be required to produce higher quality statistical information. For this timely, reliable and comparable data are needed. Lack of proper and uniform definitions, unambiguous classifications pose serious problems to procure qualitative data. These cause measurement errors. We consider the problem of estimating measurement variance so that some measures may be adopted to improve upon the quality of data on environmental goods and services and on value statement in economic terms. The measurement technique considered here is that of employing personal interviewers and the sampling considered here is that of two-stage sampling.
Diffusion-Based Trajectory Observers with Variance Constraints
Alcocer, Alex; Jouffroy, Jerome; Oliveira, Paulo
Diffusion-based trajectory observers have been recently proposed as a simple and efficient framework to solve diverse smoothing problems in underwater navigation. For instance, to obtain estimates of the trajectories of an underwater vehicle given position fixes from an acoustic positioning system...... and velocity measurements from a DVL. The observers are conceptually simple and can easily deal with the problems brought about by the occurrence of asynchronous measurements and dropouts. In its original formulation, the trajectory observers depend on a user-defined constant gain that controls the level...... of smoothing and is determined by resorting to trial and error. This paper presents a methodology to choose the observer gain by taking into account a priori information on the variance of the position measurement errors. Experimental results with data from an acoustic positioning system are presented...
Static models, recursive estimators and the zero-variance approach
Rubino, Gerardo
2016-01-07
When evaluating dependability aspects of complex systems, most models belong to the static world, where time is not an explicit variable. These models suffer from the same problems than dynamic ones (stochastic processes), such as the frequent combinatorial explosion of the state spaces. In the Monte Carlo domain, on of the most significant difficulties is the rare event situation. In this talk, we describe this context and a recent technique that appears to be at the top performance level in the area, where we combined ideas that lead to very fast estimation procedures with another approach called zero-variance approximation. Both ideas produced a very efficient method that has the right theoretical property concerning robustness, the Bounded Relative Error one. Some examples illustrate the results.
INTERPRETING MAGNETIC VARIANCE ANISOTROPY MEASUREMENTS IN THE SOLAR WIND
TenBarge, J. M.; Klein, K. G.; Howes, G. G. [Department of Physics and Astronomy, University of Iowa, Iowa City, IA (United States); Podesta, J. J., E-mail: jason-tenbarge@uiowa.edu [Space Science Institute, Boulder, CO (United States)
2012-07-10
The magnetic variance anisotropy (A{sub m}) of the solar wind has been used widely as a method to identify the nature of solar wind turbulent fluctuations; however, a thorough discussion of the meaning and interpretation of the A{sub m} has not appeared in the literature. This paper explores the implications and limitations of using the A{sub m} as a method for constraining the solar wind fluctuation mode composition and presents a more informative method for interpreting spacecraft data. The paper also compares predictions of the A{sub m} from linear theory to nonlinear turbulence simulations and solar wind measurements. In both cases, linear theory compares well and suggests that the solar wind for the interval studied is dominantly Alfvenic in the inertial and dissipation ranges to scales of k{rho}{sub i} {approx_equal} 5.
Estimating discharge measurement uncertainty using the interpolated variance estimator
Cohn, T.; Kiang, J.; Mason, R.
2012-01-01
Methods for quantifying the uncertainty in discharge measurements typically identify various sources of uncertainty and then estimate the uncertainty from each of these sources by applying the results of empirical or laboratory studies. If actual measurement conditions are not consistent with those encountered in the empirical or laboratory studies, these methods may give poor estimates of discharge uncertainty. This paper presents an alternative method for estimating discharge measurement uncertainty that uses statistical techniques and at-site observations. This Interpolated Variance Estimator (IVE) estimates uncertainty based on the data collected during the streamflow measurement and therefore reflects the conditions encountered at the site. The IVE has the additional advantage of capturing all sources of random uncertainty in the velocity and depth measurements. It can be applied to velocity-area discharge measurements that use a velocity meter to measure point velocities at multiple vertical sections in a channel cross section.
MARKOV-MODULATED MEAN-VARIANCE PROBLEM FOR AN INSURER
Wang Wei; Bi Junna
2011-01-01
In this paper, we consider an insurance company which has the option of investing in a risky asset and a risk-free asset, whose price parameters are driven by a finite state Markov chain. The risk process of the insurance company is modeled as a diffusion process whose diffusion and drift parameters switch over time according to the same Markov chain. We study the Markov-modulated mean-variance problem for the insurer and derive explicitly the closed form of the efficient strategy and efficient frontier. In the case of no regime switching, we can see that the efficient frontier in our paper coincides with that of [10] when there is no pure jump.
Variance component estimates for alternative litter size traits in swine.
Putz, A M; Tiezzi, F; Maltecca, C; Gray, K A; Knauer, M T
2015-11-01
Litter size at d 5 (LS5) has been shown to be an effective trait to increase total number born (TNB) while simultaneously decreasing preweaning mortality. The objective of this study was to determine the optimal litter size day for selection (i.e., other than d 5). Traits included TNB, number born alive (NBA), litter size at d 2, 5, 10, 30 (LS2, LS5, LS10, LS30, respectively), litter size at weaning (LSW), number weaned (NW), piglet mortality at d 30 (MortD30), and average piglet birth weight (BirthWt). Litter size traits were assigned to biological litters and treated as a trait of the sow. In contrast, NW was the number of piglets weaned by the nurse dam. Bivariate animal models included farm, year-season, and parity as fixed effects. Number born alive was fit as a covariate for BirthWt. Random effects included additive genetics and the permanent environment of the sow. Variance components were plotted for TNB, NBA, and LS2 to LS30 using univariate animal models to determine how variances changed over time. Additive genetic variance was minimized at d 7 in Large White and at d 14 in Landrace pigs. Total phenotypic variance for litter size traits decreased over the first 10 d and then stabilized. Heritability estimates increased between TNB and LS30. Genetic correlations between TNB, NBA, and LS2 to LS29 with LS30 plateaued within the first 10 d. A genetic correlation with LS30 of 0.95 was reached at d 4 for Large White and at d 8 for Landrace pigs. Heritability estimates ranged from 0.07 to 0.13 for litter size traits and MortD30. Birth weight had an h of 0.24 and 0.26 for Large White and Landrace pigs, respectively. Genetic correlations among LS30, LSW, and NW ranged from 0.97 to 1.00. In the Large White breed, genetic correlations between MortD30 with TNB and LS30 were 0.23 and -0.64, respectively. These correlations were 0.10 and -0.61 in the Landrace breed. A high genetic correlation of 0.98 and 0.97 was observed between LS10 and NW for Large White and
From Means and Variances to Persons and Patterns
James W Grice
2015-07-01
Full Text Available A novel approach for conceptualizing and analyzing data from psychological studies is presented and discussed. This approach is centered on model building in an effort to explicate the structures and processes believed to generate a set of observations. These models therefore go beyond the variable-based, path models in use today which are limiting with regard to the types of inferences psychologists can draw from their research. In terms of analysis, the newer approach replaces traditional aggregate statistics such as means, variances, and covariances with methods of pattern detection and analysis. While these methods are person-centered and do not require parametric assumptions, they are both demanding and rigorous. They also provide psychologists with the information needed to draw the primary inference they often wish to make from their research; namely, the inference to best explanation.
Mean and variance of coincidence counting with deadtime
Yu, D F
2002-01-01
We analyze the first and second moments of the coincidence-counting process for a system affected by paralyzable (extendable) deadtime with (possibly unequal) deadtimes in each singles channel. We consider both 'accidental' and 'genuine' coincidences, and derive exact analytical expressions for the first and second moments of the number of recorded coincidence events under various scenarios. The results include an exact form for the coincidence rate under the combined effects of decay, background, and deadtime. The analysis confirms that coincidence counts are not exactly Poisson, but suggests that the Poisson statistical model that is used for positron emission tomography image reconstruction is a reasonable approximation since the mean and variance are nearly equal.
Variance of indoor radon concentration: Major influencing factors.
Yarmoshenko, I; Vasilyev, A; Malinovsky, G; Bossew, P; Žunić, Z S; Onischenko, A; Zhukovsky, M
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.
Risk Management - Variance Minimization or Lower Tail Outcome Elimination
Aabo, Tom
2002-01-01
This paper illustrates the profound difference between a risk management strategy of variance minimization and a risk management strategy of lower tail outcome elimination. Risk managers concerned about the variability of cash flows will tend to center their hedge decisions on their best guess...... on future cash flows (the budget), while risk managers concerned about costly lower tail outcomes will hedge (considerably) less depending on the level of uncertainty. A risk management strategy of lower tail outcome elimination is in line with theoretical recommendations in a corporate value......-adding perspective. A cross-case study of blue-chip industrial companies partly supports the empirical use of a risk management strategy of lower tail outcome elimination but does not exclude other factors from (co-)driving the observations....
Analysis of variance of an underdetermined geodetic displacement problem
Darby, D.
1982-06-01
It has been suggested recently that point displacements in a free geodetic network traversing a strike-slip fault may be estimated from repeated surveys by minimizing only those displacement components normal to the strike. It is desirable to justify this procedure. We construct, from estimable quantities, a deformation parameter which is an F-statistic of the type occurring in the analysis of variance of linear models not of full rank. A test of its significance provides the criterion to justify the displacement solution. It is also interesting to study its behaviour as one varies the supposed strike of the fault. Justification of a displacement solution using data from a strike-slip fault is found, but not for data from a rift valley. The technique can be generalized to more complex patterns of deformation such as those expected near the end-zone of a fault in a dislocation model.
Objective Bayesian Comparison of Constrained Analysis of Variance Models.
Consonni, Guido; Paroli, Roberta
2016-10-04
In the social sciences we are often interested in comparing models specified by parametric equality or inequality constraints. For instance, when examining three group means [Formula: see text] through an analysis of variance (ANOVA), a model may specify that [Formula: see text], while another one may state that [Formula: see text], and finally a third model may instead suggest that all means are unrestricted. This is a challenging problem, because it involves a combination of nonnested models, as well as nested models having the same dimension. We adopt an objective Bayesian approach, requiring no prior specification from the user, and derive the posterior probability of each model under consideration. Our method is based on the intrinsic prior methodology, suitably modified to accommodate equality and inequality constraints. Focussing on normal ANOVA models, a comparative assessment is carried out through simulation studies. We also present an application to real data collected in a psychological experiment.
Batch variation between branchial cell cultures: An analysis of variance
Hansen, Heinz Johs. Max; Grosell, M.; Kristensen, L.
2003-01-01
We present in detail how a statistical analysis of variance (ANOVA) is used to sort out the effect of an unexpected batch-to-batch variation between cell cultures. Two separate cultures of rainbow trout branchial cells were grown on permeable filtersupports ("inserts"). They were supposed...... and introducing the observed difference between batches as one of the factors in an expanded three-dimensional ANOVA, we were able to overcome an otherwisecrucial lack of sufficiently reproducible duplicate values. We could thereby show that the effect of changing the apical medium was much more marked when...... the radioactive lipid precursors were added on the apical, rather than on the basolateral, side. Theinsert cell cultures were obviously polarized. We argue that it is not reasonable to reject troublesome experimental results, when we do not know a priori that something went wrong. The ANOVA is a very useful...
Correct use of repeated measures analysis of variance.
Park, Eunsik; Cho, Meehye; Ki, Chang-Seok
2009-02-01
In biomedical research, researchers frequently use statistical procedures such as the t-test, standard analysis of variance (ANOVA), or the repeated measures ANOVA to compare means between the groups of interest. There are frequently some misuses in applying these procedures since the conditions of the experiments or statistical assumptions necessary to apply these procedures are not fully taken into consideration. In this paper, we demonstrate the correct use of repeated measures ANOVA to prevent or minimize ethical or scientific problems due to its misuse. We also describe the appropriate use of multiple comparison tests for follow-up analysis in repeated measures ANOVA. Finally, we demonstrate the use of repeated measures ANOVA by using real data and the statistical software package SPSS (SPSS Inc., USA).
Hodological resonance, hodological variance, psychosis and schizophrenia: A hypothetical model
Paul Brian eLawrie Birkett
2011-07-01
Full Text Available Schizophrenia is a disorder with a large number of clinical, neurobiological, and cognitive manifestations, none of which is invariably present. However it appears to be a single nosological entity. This article considers the likely characteristics of a pathology capable of such diverse consequences. It is argued that both deficit and psychotic symptoms can be manifestations of a single pathology. A general model of psychosis is proposed in which the informational sensitivity or responsivity of a network ("hodological resonance" becomes so high that it activates spontaneously, to produce a hallucination, if it is in sensory cortex, or another psychotic symptom if it is elsewhere. It is argued that this can come about because of high levels of modulation such as those assumed present in affective psychosis, or because of high levels of baseline resonance, such as those expected in deafferentation syndromes associated with hallucinations, for example, Charles Bonnet. It is further proposed that schizophrenia results from a process (probably neurodevelopmental causing widespread increases of variance in baseline resonance; consequently some networks possess high baseline resonance and become susceptible to spontaneous activation. Deficit symptoms might result from the presence of networks with increased activation thresholds. This hodological variance model is explored in terms of schizo-affective disorder, transient psychotic symptoms, diathesis-stress models, mechanisms of antipsychotic pharmacotherapy and persistence of genes predisposing to schizophrenia. Predictions and implications of the model are discussed. In particular it suggests a need for more research into psychotic states and for more single case-based studies in schizophrenia.
Teeth size reduction in the prehistoric populations in Serbia
Pajević Tina
2012-01-01
Full Text Available Introduction. Anthropological studies show craniofacial changes with a reduction in teeth size during evolution of the human population. Objective. The objective was to measure and compare the sizes of teeth in the population of the Mesolithic-Neolithic sites in the Iron Gate Gorge and the population from the Early Bronze Age site of Mokrin. Methods. The study included teeth without advanced wear near the pulp. The material was divided according to the site of the skeletal population in two groups. Group 1 comprised 107 teeth from the Mesolithic-Neolithic sites Lepenski Vir and Vlasac. Group 2 included 158 teeth from the Mokrin graveyard dated in the Early Bronze Age. The mesio-distal diameter was measured in all teeth, while the vestibulo-oral diameter was measured in the molars only. Using the two-factor analysis of variance, the influence of sex, site and their interaction on the size of the teeth were investigated. Results. The vestibulo-oral diameter of the upper third molar was significantly higher in males compared to females. The comparison between the groups showed that the vestibulooral diameter of the lower first molar was significantly higher in group 1. Conclusion. The present difference in teeth size indicates the existence of reduction during the prehistoric times. However, the time period between the populations studied is probably too short to be manifested on a large number of teeth.
Continuous-Time Mean-Variance Portfolio Selection under the CEV Process
Hui-qiang Ma
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...
Understanding the influence of watershed storage caused by human interferences on ET variance
Zeng, R.; Cai, X.
2014-12-01
Understanding the temporal variance of evapotranspiration (ET) at the watershed scale remains a challenging task, because it is affected by complex climate conditions, soil properties, vegetation, groundwater and human activities. In a changing environment with extensive and intensive human interferences, understanding ET variance and its factors is important for sustainable water resources management. This study presents an analysis of the effect of storage change caused by human activities on ET variance Irrigation usually filters ET variance through the use of surface and groundwater; however, over-amount irrigation may cause the depletion of watershed storage, which changes the coincidence of water availability and energy supply for ET. This study develops a framework by incorporating the water balance and the Budyko Hypothesis. It decomposes the ET variance to the variances of precipitation, potential ET, catchment storage change, and their covariances. The contributions of ET variance from the various components are scaled by some weighting functions, expressed as long-term climate conditions and catchment properties. ET variance is assessed by records from 32 major river basins across the world. It is found that ET variance is dominated by precipitation variance under hot-dry condition and by evaporative demand variance under cool-wet condition; while the coincidence of water and energy supply controls ET variance under moderate climate condition. Watershed storage change plays an increasing important role in determining ET variance with relatively shorter time scale. By incorporating storage change caused by human interferences, this framework corrects the over-estimation of ET variance in hot-dry climate and under-estimation of ET variance in cool-wet climate. Furthermore, classification of dominant factors on ET variance shows similar patterns as geographic zonation.
Kiviet, J.F.; Phillips, G.D.A.
2014-01-01
In dynamic regression models conditional maximum likelihood (least-squares) coefficient and variance estimators are biased. Using expansion techniques an approximation is obtained to the bias in variance estimation yielding a bias corrected variance estimator. This is achieved for both the standard
A New Approach for Predicting the Variance of Random Decrement Functions
Asmussen, J. C.; Brincker, Rune
1998-01-01
technique is that no consistent approach to estimate the variance of the RD functions is known. Only approximate relations are available, which can only be used under special conditions. The variance of teh RD functions contains valuable information about accuracy of the estimates. Furthermore, the variance...
The pricing of long and short run variance and correlation risk in stock returns
Cosemans, M.
2011-01-01
This paper studies the pricing of long and short run variance and correlation risk. The predictive power of the market variance risk premium for returns is driven by the correlation risk premium and the systematic part of individual variance premia. Furthermore, I find that aggregate volatility risk
Modeling Heterogeneous Variance-Covariance Components in Two-Level Models
Leckie, George; French, Robert; Charlton, Chris; Browne, William
2014-01-01
Applications of multilevel models to continuous outcomes nearly always assume constant residual variance and constant random effects variances and covariances. However, modeling heterogeneity of variance can prove a useful indicator of model misspecification, and in some educational and behavioral studies, it may even be of direct substantive…
The pricing of long and short run variance and correlation risk in stock returns
Cosemans, M.
2011-01-01
This paper studies the pricing of long and short run variance and correlation risk. The predictive power of the market variance risk premium for returns is driven by the correlation risk premium and the systematic part of individual variance premia. Furthermore, I find that aggregate volatility risk
Estimation of genetic variation in residual variance in female and male broiler chickens
Mulder, H.A.; Hill, W.G.; Vereijken, A.; Veerkamp, R.F.
2009-01-01
In breeding programs, robustness of animals and uniformity of end product can be improved by exploiting genetic variation in residual variance. Residual variance can be defined as environmental variance after accounting for all identifiable effects. The aims of this study were to estimate genetic va
Wang, Lu; Zhang, Chunxi; Gao, Shuang; Wang, Tao; Lin, Tie; Li, Xianmu
2016-01-01
The stability of a fiber optic gyroscope (FOG) in measurement while drilling (MWD) could vary with time because of changing temperature, high vibration, and sudden power failure. The dynamic Allan variance (DAVAR) is a sliding version of the Allan variance. It is a practical tool that could represent the non-stationary behavior of the gyroscope signal. Since the normal DAVAR takes too long to deal with long time series, a fast DAVAR algorithm has been developed to accelerate the computation speed. However, both the normal DAVAR algorithm and the fast algorithm become invalid for discontinuous time series. What is worse, the FOG-based MWD underground often keeps working for several days; the gyro data collected aboveground is not only very time-consuming, but also sometimes discontinuous in the timeline. In this article, on the basis of the fast algorithm for DAVAR, we make a further advance in the fast algorithm (improved fast DAVAR) to extend the fast DAVAR to discontinuous time series. The improved fast DAVAR and the normal DAVAR are used to responsively characterize two sets of simulation data. The simulation results show that when the length of the time series is short, the improved fast DAVAR saves 78.93% of calculation time. When the length of the time series is long (6×105 samples), the improved fast DAVAR reduces calculation time by 97.09%. Another set of simulation data with missing data is characterized by the improved fast DAVAR. Its simulation results prove that the improved fast DAVAR could successfully deal with discontinuous data. In the end, a vibration experiment with FOGs-based MWD has been implemented to validate the good performance of the improved fast DAVAR. The results of the experience testify that the improved fast DAVAR not only shortens computation time, but could also analyze discontinuous time series. PMID:27941600
Lu Wang
2016-12-01
Full Text Available The stability of a fiber optic gyroscope (FOG in measurement while drilling (MWD could vary with time because of changing temperature, high vibration, and sudden power failure. The dynamic Allan variance (DAVAR is a sliding version of the Allan variance. It is a practical tool that could represent the non-stationary behavior of the gyroscope signal. Since the normal DAVAR takes too long to deal with long time series, a fast DAVAR algorithm has been developed to accelerate the computation speed. However, both the normal DAVAR algorithm and the fast algorithm become invalid for discontinuous time series. What is worse, the FOG-based MWD underground often keeps working for several days; the gyro data collected aboveground is not only very time-consuming, but also sometimes discontinuous in the timeline. In this article, on the basis of the fast algorithm for DAVAR, we make a further advance in the fast algorithm (improved fast DAVAR to extend the fast DAVAR to discontinuous time series. The improved fast DAVAR and the normal DAVAR are used to responsively characterize two sets of simulation data. The simulation results show that when the length of the time series is short, the improved fast DAVAR saves 78.93% of calculation time. When the length of the time series is long ( 6 × 10 5 samples, the improved fast DAVAR reduces calculation time by 97.09%. Another set of simulation data with missing data is characterized by the improved fast DAVAR. Its simulation results prove that the improved fast DAVAR could successfully deal with discontinuous data. In the end, a vibration experiment with FOGs-based MWD has been implemented to validate the good performance of the improved fast DAVAR. The results of the experience testify that the improved fast DAVAR not only shortens computation time, but could also analyze discontinuous time series.
Estimation models of variance components for farrowing interval in swine
Aderbal Cavalcante Neto
2009-02-01
Full Text Available The main objective of this study was to evaluate the importance of including maternal genetic, common litter environmental and permanent environmental effects in estimation models of variance components for the farrowing interval trait in swine. Data consisting of 1,013 farrowing intervals of Dalland (C-40 sows recorded in two herds were analyzed. Variance components were obtained by the derivative-free restricted maximum likelihood method. Eight models were tested which contained the fixed effects(contemporary group and covariables and the direct genetic additive and residual effects, and varied regarding the inclusion of the maternal genetic, common litter environmental, and/or permanent environmental random effects. The likelihood-ratio test indicated that the inclusion of these effects in the model was unnecessary, but the inclusion of the permanent environmental effect caused changes in the estimates of heritability, which varied from 0.00 to 0.03. In conclusion, the heritability values obtained indicated that this trait appears to present no genetic gain as response to selection. The common litter environmental and the maternal genetic effects did not present any influence on this trait. The permanent environmental effect, however, should be considered in the genetic models for this trait in swine, because its presence caused changes in the additive genetic variance estimates.Este trabalho teve como objetivo principal avaliar a importância da inclusão dos efeitos genético materno, comum de leitegada e de ambiente permanente no modelo de estimação de componentes de variância para a característica intervalo de parto em fêmeas suínas. Foram utilizados dados que consistiam de 1.013 observações de fêmeas Dalland (C-40, registradas em dois rebanhos. As estimativas dos componentes de variância foram realizadas pelo método da máxima verossimilhança restrita livre de derivadas. Foram testados oito modelos, que continham os efeitos
Adenomyosis and Its Variance: Adenomyoma and Female Fertility
Peng-Hui Wang
2009-09-01
Full Text Available Extensive adenomyosis (adenomyosis or its variance, localized adenomyosis (adenomyoma of the uterus, is often described as scattered, widely-distributed endometrial glands or stromal tissue found throughout the myometrium layer of the uterus. By definition, adenomyosis consists of epithelial as well as stromal elements, and is situated at least 2.5 mm below the endometrial–myometrial junction. However, the diagnosis and clinical significance of uterine adenomyosis and/or adenomyoma remain somewhat enigmatic. The relationship between infertility and uterine adenomyosis and/or adenomyoma is still uncertain, but severe endometriosis impairs the chances of successful pregnancy when using artificial reproductive techniques. To date, there is no uniform agreement on the most appropriate therapeutic methods for managing women with uterine adenomyosis and/or adenomyoma who want to preserve their fertility. Fertility has been restored after successful treatment of adenomyosis using multiple modalities, including hormonal therapy and conservative surgical therapy via laparoscopy or exploratory laparotomy, uterine artery embolization, and other methods, including a potential but under- investigated procedure, magnetic resonance-guided focused ultrasound. This review will explore recent publications that have addressed the use of different approaches in the management of subfertile women with uterine adenomyosis and adenomyoma.
Cosmic variance and the measurement of the local Hubble parameter.
Marra, Valerio; Amendola, Luca; Sawicki, Ignacy; Valkenburg, Wessel
2013-06-14
There is an approximately 9% discrepancy, corresponding to 2.4 σ, between two independent constraints on the expansion rate of the Universe: one indirectly arising from the cosmic microwave background and baryon acoustic oscillations and one more directly obtained from local measurements of the relation between redshifts and distances to sources. We argue that by taking into account the local gravitational potential at the position of the observer this tension--strengthened by the recent Planck results--is partially relieved and the concordance of the Standard Model of cosmology increased. We estimate that measurements of the local Hubble constant are subject to a cosmic variance of about 2.4% (limiting the local sample to redshifts z > 0.010) or 1.3% (limiting it to z > 0.023), a more significant correction than that taken into account already. Nonetheless, we show that one would need a very rare fluctuation to fully explain the offset in the Hubble rates. If this tension is further strengthened, a cosmology beyond the Standard Model may prove necessary.
Sparse recovery with unknown variance: a LASSO-type approach
Chretien, Stephane
2011-01-01
We address the issue of estimating the regression vector $\\beta$ and the variance $\\sg^{2}$ in the generic s-sparse linear model $y = X\\beta+z$, with $\\beta\\in\\R^{p}$, $y\\in\\R^{n}$, $z\\sim\\mathcal N(0,\\sg^2 I)$ and $p> n$. We propose a new LASSO-type method that jointly estimates $\\beta$, $\\sg^{2}$ and the relaxation parameter $\\lb$ by imposing an explicit trade-off constraint between the $\\log$-likelihood and $\\ell_1$-penalization terms. We prove that exact recovery of the support and sign pattern of $\\beta$ holds with probability at least $1-O(p^{-\\alpha})$. Our assumptions, parametrized by $\\alpha$, are similar to the ones proposed in \\cite{CandesPlan:AnnStat09} for $\\sg^{2}$ known. The proof relies on a tail decoupling argument with explicit constants and a recent version of the Non-Commutative Bernstein inequality \\cite{Tropp:ArXiv10}. Our result is then derived from the optimality conditions for the estimators of $\\beta$ and $\\lb$. Finally, a thorough analysis of the standard LASSO estimator as a functi...
Analysis of variance in neuroreceptor ligand imaging studies.
Ji Hyun Ko
Full Text Available Radioligand positron emission tomography (PET with dual scan paradigms can provide valuable insight into changes in synaptic neurotransmitter concentration due to experimental manipulation. The residual t-test has been utilized to improve the sensitivity of the t-test in PET studies. However, no further development of statistical tests using residuals has been proposed so far to be applied in cases when there are more than two conditions. Here, we propose the residual f-test, a one-way analysis of variance (ANOVA, and examine its feasibility using simulated [(11C]raclopride PET data. We also re-visit data from our previously published [(11C]raclopride PET study, in which 10 individuals underwent three PET scans under different conditions. We found that the residual f-test is superior in terms of sensitivity than the conventional f-test while still controlling for type 1 error. The test will therefore allow us to reliably test hypotheses in the smaller sample sizes often used in explorative PET studies.
Chromatic visualization of reflectivity variance within hybridized directional OCT images
Makhijani, Vikram S.; Roorda, Austin; Bayabo, Jan Kristine; Tong, Kevin K.; Rivera-Carpio, Carlos A.; Lujan, Brandon J.
2013-03-01
This study presents a new method of visualizing hybridized images of retinal spectral domain optical coherence tomography (SDOCT) data comprised of varied directional reflectivity. Due to the varying reflectivity of certain retinal structures relative to angle of incident light, SDOCT images obtained with differing entry positions result in nonequivalent images of corresponding cellular and extracellular structures, especially within layers containing photoreceptor components. Harnessing this property, cross-sectional pathologic and non-pathologic macular images were obtained from multiple pupil entry positions using commercially-available OCT systems, and custom segmentation, alignment, and hybridization algorithms were developed to chromatically visualize the composite variance of reflectivity effects. In these images, strong relative reflectivity from any given direction visualizes as relative intensity of its corresponding color channel. Evident in non-pathologic images was marked enhancement of Henle's fiber layer (HFL) visualization and varying reflectivity patterns of the inner limiting membrane (ILM) and photoreceptor inner/outer segment junctions (IS/OS). Pathologic images displayed similar and additional patterns. Such visualization may allow a more intuitive understanding of structural and physiologic processes in retinal pathologies.
Analysis of variance (ANOVA) models in lower extremity wounds.
Reed, James F
2003-06-01
Consider a study in which 2 new treatments are being compared with a control group. One way to compare outcomes would simply be to compare the 2 treatments with the control and the 2 treatments against each using 3 Student t tests (t test). If we were to compare 4 treatment groups, then we would need to use 6 t tests. The difficulty with using multiple t tests is that as the number of groups increases, so will the likelihood of finding a difference between any pair of groups simply by change when no real difference exists by definition a Type I error. If we were to perform 3 separate t tests each at alpha = .05, the experimental error rate increases to .14. As the number of multiple t tests increases, the experiment-wise error rate increases rather rapidly. The solution to the experimental error rate problem is to use analysis of variance (ANOVA) methods. Three basic ANOVA designs are reviewed that give hypothetical examples drawn from the literature to illustrate single-factor ANOVA, repeated measures ANOVA, and randomized block ANOVA. "No frills" SPSS or SAS code for each of these designs and examples used are available from the author on request.
Variance in Dominant Grain Size Across the Mississippi River Delta
Miller, K. L.; Chamberlain, E. L.; Esposito, C. R.; Wagner, R. W.; Mohrig, D. C.
2016-02-01
Proposals to restore coastal Louisiana often center on Mississippi River diversion projects wherein water and sediment are routed into wetlands and shallow waters in an effort to build land. Successful design and implementation of diversions will include consideration of behavior and characteristics of sediment, both in the river and in the receiving basin. The Mississippi River sediment load is primarily mud (roughly 75%), with the remainder being very-fine to medium sand or organic detritus. The dominance of muds leads many to suggest that diversions should focus on capturing the mud fraction despite the smaller size and longer settling times required for these particles compared to sand; others believe that sand should be the focus. We present a systemic analysis of the texture of land-building sediment in the Mississippi Delta using borehole data from various depositional environments representing a range of spatial scales, system ages, and fluvial and basin characteristics. We include subdelta-scale data from the incipient Wax Lake Delta and from the distal plain of the abandoned Lafourche subdelta, as well as crevasse-scale data from modern Cubit's Gap and the Attakapas splay, an inland Lafourche crevasse. Comparison of these sites demonstrates a large variance in the volumetric mud to sand ratios across the system. We consider the differences to be emblematic of the various forcings on each lobe as it formed and suggest that the most efficient building block for a diversion is a function of the receiving basin and is not uniform across the entire delta.
On Eliminating The Scrambling Variance In Scrambled Response Models
Zawar Hussain
2012-06-01
Full Text Available To circumvent the response bias in sensitive surveys randomized response models are being used. To add into it we propose an improved response model utilizing both the additive and multiplicative scrambling method. The proposed model provides greater flexibility in terms of fixing the constantKdepending upon the guessed distribution of sensitive variable and nature of the population. The proposed model yields an unbiased estimator and is anticipated as more protective against the privacy of the respondents. The relative efficiency comparison of the proposed estimator is made relative to Hussain and Shabbir (2007 RRM. Furthermore, the proposed model itself is improved by taking the two responses from each respondent and suggesting a weighted estimator yielding an unbiased estimator having the minimum possible sampling variance. The suggested weighted estimator is unconditionally more efficient than all of the suggested estimators until now. Future research may be focused on privacy protection provided by the scrambling models. More scrambling models may be identified and improved by taking the two responses from each respondent in such a way that the scrambling effect is balanced out.
Mean-Variance Portfolio Selection with Margin Requirements
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.
Identifiability of Gaussian Structural Equation Models with Same Error Variances
Peters, Jonas
2012-01-01
We consider structural equation models (SEMs) in which variables can be written as a function of their parents and noise terms (the latter are assumed to be jointly independent). Corresponding to each SEM, there is a directed acyclic graph (DAG) G_0 describing the relationships between the variables. In Gaussian SEMs with linear functions, the graph can be identified from the joint distribution only up to Markov equivalence classes (assuming faithfulness). It has been shown, however, that this constitutes an exceptional case. In the case of linear functions and non-Gaussian noise, the DAG becomes identifiable. Apart from few exceptions the same is true for non-linear functions and arbitrarily distributed additive noise. In this work, we prove identifiability for a third modification: if we require all noise variables to have the same variances, again, the DAG can be recovered from the joint Gaussian distribution. Our result can be applied to the problem of causal inference. If the data follow a Gaussian SEM w...
Cosmic variance in [O/Fe] in the Galactic disk
de Lis, S Bertran; Majewski, S R; Schiavon, R P; Holtzman, J A; Shetrone, M; Carrera, R; Pérez, A E García; Mészáros, Sz; Frinchaboy, P M; Hearty, F R; Nidever, D L; Zasowski, G; Ge, J
2016-01-01
We examine the distribution of the [O/Fe] abundance ratio in stars across the Galactic disk using H-band spectra from the Apache Point Galactic Evolution Experiment (APOGEE). We minimized systematic errors by considering groups of stars with similar atmospheric parameters. The APOGEE measurements in the Sloan Digital Sky Survey Data Release 12 reveal that the square root of the star-to-star cosmic variance in oxygen at a given metallicity is about 0.03-0.04 dex in both the thin and thick disk. This is about twice as high as the spread found for solar twins in the immediate solar neighborhood and is probably caused by the wider range of galactocentric distances spanned by APOGEE stars. We quantified measurement uncertainties by examining the spread among stars with the same parameters in clusters; these errors are a function of effective temperature and metallicity, ranging between 0.005 dex at 4000 K and solar metallicity, to about 0.03 dex at 4500 K and [Fe/H]= -0.6. We argue that measuring the spread in [O/...
Cosmic variance in [O/Fe] in the Galactic disk
Bertran de Lis, S.; Allende Prieto, C.; Majewski, S. R.; Schiavon, R. P.; Holtzman, J. A.; Shetrone, M.; Carrera, R.; García Pérez, A. E.; Mészáros, Sz.; Frinchaboy, P. M.; Hearty, F. R.; Nidever, D. L.; Zasowski, G.; Ge, J.
2016-05-01
We examine the distribution of the [O/Fe] abundance ratio in stars across the Galactic disk using H-band spectra from the Apache Point Galactic Evolution Experiment (APOGEE). We minimize systematic errors by considering groups of stars with similar atmospheric parameters. The APOGEE measurements in the Sloan Digital Sky Survey data release 12 reveal that the square root of the star-to-star cosmic variance in the oxygen-to-iron ratio at a given metallicity is about 0.03-0.04 dex in both the thin and thick disk. This is about twice as high as the spread found for solar twins in the immediate solar neighborhood and the difference is probably associated to the wider range of galactocentric distances spanned by APOGEE stars. We quantify the uncertainties by examining the spread among stars with the same parameters in clusters; these errors are a function of effective temperature and metallicity, ranging between 0.005 dex at 4000 K and solar metallicity, to about 0.03 dex at 4500 K and [Fe/H] ≃ -0.6. We argue that measuring the spread in [O/Fe] and other abundance ratios provides strong constraints for models of Galactic chemical evolution.
Designing electricity generation portfolios using the mean-variance approach
Jorge Cunha
2014-06-01
Full Text Available The use of the mean-variance approach (MVA is well demonstrated in the financial literature for the optimal design of financial assets portfolios. The electricity sector portfolios are also guided by similar objectives, namely maximizing return and minimizing risk. As such, this paper proposes two possible MVA for the design of optimal renewable electricity production portfolios. The first approach is directed to portfolio output maximization and the second one is directed to portfolio cost optimization. The models implementation was achieved from data obtained for each quarter of an hour for a time period close to four years for the Portuguese electricity system. A set of renewable energy sources (RES portfolios was obtained, mixing three RES technologies, namely hydro power, wind power and photovoltaic. This allowed to recognize the seasonality of the resources demonstrating that hydro power output is positively correlated with wind and that photovoltaic is negatively correlated with both hydro and wind. The results showed that for both models the less risky solutions are characterised by a mix of RES technologies, taking advantage of the diversification benefits. As for the highest return solutions, as expected those were the ones with higher risk but the portfolio composition largely depends on the assumed costs of each technology.
A model selection approach to analysis of variance and covariance.
Alber, Susan A; Weiss, Robert E
2009-06-15
An alternative to analysis of variance is a model selection approach where every partition of the treatment means into clusters with equal value is treated as a separate model. The null hypothesis that all treatments are equal corresponds to the partition with all means in a single cluster. The alternative hypothesis correspond to the set of all other partitions of treatment means. A model selection approach can also be used for a treatment by covariate interaction, where the null hypothesis and each alternative correspond to a partition of treatments into clusters with equal covariate effects. We extend the partition-as-model approach to simultaneous inference for both treatment main effect and treatment interaction with a continuous covariate with separate partitions for the intercepts and treatment-specific slopes. The model space is the Cartesian product of the intercept partition and the slope partition, and we develop five joint priors for this model space. In four of these priors the intercept and slope partition are dependent. We advise on setting priors over models, and we use the model to analyze an orthodontic data set that compares the frictional resistance created by orthodontic fixtures. Copyright (c) 2009 John Wiley & Sons, Ltd.
Analysis of variance in neuroreceptor ligand imaging studies.
Ko, Ji Hyun; Reilhac, Anthonin; Ray, Nicola; Rusjan, Pablo; Bloomfield, Peter; Pellecchia, Giovanna; Houle, Sylvain; Strafella, Antonio P
2011-01-01
Radioligand positron emission tomography (PET) with dual scan paradigms can provide valuable insight into changes in synaptic neurotransmitter concentration due to experimental manipulation. The residual t-test has been utilized to improve the sensitivity of the t-test in PET studies. However, no further development of statistical tests using residuals has been proposed so far to be applied in cases when there are more than two conditions. Here, we propose the residual f-test, a one-way analysis of variance (ANOVA), and examine its feasibility using simulated [(11)C]raclopride PET data. We also re-visit data from our previously published [(11)C]raclopride PET study, in which 10 individuals underwent three PET scans under different conditions. We found that the residual f-test is superior in terms of sensitivity than the conventional f-test while still controlling for type 1 error. The test will therefore allow us to reliably test hypotheses in the smaller sample sizes often used in explorative PET studies.
Cosmological N-body simulations with suppressed variance
Angulo, Raul E.; Pontzen, Andrew
2016-10-01
We present and test a method that dramatically reduces variance arising from the sparse sampling of wavemodes in cosmological simulations. The method uses two simulations which are fixed (the initial Fourier mode amplitudes are fixed to the ensemble average power spectrum) and paired (with initial modes exactly out of phase). We measure the power spectrum, monopole and quadrupole redshift-space correlation functions, halo mass function and reduced bispectrum at z = 1. By these measures, predictions from a fixed pair can be as precise on non-linear scales as an average over 50 traditional simulations. The fixing procedure introduces a non-Gaussian correction to the initial conditions; we give an analytic argument showing why the simulations are still able to predict the mean properties of the Gaussian ensemble. We anticipate that the method will drive down the computational time requirements for accurate large-scale explorations of galaxy bias and clustering statistics, and facilitating the use of numerical simulations in cosmological data interpretation.
Variance Swaps in BM&F: Pricing and Viability of Hedge
Richard John Brostowicz Junior
2010-07-01
Full Text Available A variance swap can theoretically be priced with an infinite set of vanilla calls and puts options considering that the realized variance follows a purely diffusive process with continuous monitoring. In this article we willanalyze the possible differences in pricing considering discrete monitoring of realized variance. It will analyze the pricing of variance swaps with payoff in dollars, since there is a OTC market that works this way and thatpotentially serve as a hedge for the variance swaps traded in BM&F. Additionally, will be tested the feasibility of hedge of variance swaps when there is liquidity in just a few exercise prices, as is the case of FX optionstraded in BM&F. Thus be assembled portfolios containing variance swaps and their replicating portfolios using the available exercise prices as proposed in (DEMETERFI et al., 1999. With these portfolios, the effectiveness of the hedge was not robust in mostly of tests conducted in this work.
Asanuma, Jun
Variances of the velocity components and scalars are important as indicators of the turbulence intensity. They also can be utilized to estimate surface fluxes in several types of "variance methods", and the estimated fluxes can be regional values if the variances from which they are calculated are regionally representative measurements. On these motivations, variances measured by an aircraft in the unstable ABL over a flat pine forest during HAPEX-Mobilhy were analyzed within the context of the similarity scaling arguments. The variances of temperature and vertical velocity within the atmospheric surface layer were found to follow closely the Monin-Obukhov similarity theory, and to yield reasonable estimates of the surface sensible heat fluxes when they are used in variance methods. This gives a validation to the variance methods with aircraft measurements. On the other hand, the specific humidity variances were influenced by the surface heterogeneity and clearly fail to obey MOS. A simple analysis based on the similarity law for free convection produced a comprehensible and quantitative picture regarding the effect of the surface flux heterogeneity on the statistical moments, and revealed that variances of the active and passive scalars become dissimilar because of their different roles in turbulence. The analysis also indicated that the mean quantities are also affected by the heterogeneity but to a less extent than the variances. The temperature variances in the mixed layer (ML) were examined by using a generalized top-down bottom-up diffusion model with some combinations of velocity scales and inversion flux models. The results showed that the surface shear stress exerts considerable influence on the lower ML. Also with the temperature and vertical velocity variances ML variance methods were tested, and their feasibility was investigated. Finally, the variances in the ML were analyzed in terms of the local similarity concept; the results confirmed the original
Marrani, Alessio; Riccioni, Fabio
2011-01-01
Starting from basic identities of the group E8, we perform progressive reductions, namely decompositions with respect to the maximal and symmetric embeddings of E7xSU(2) and then of E6xU(1). This procedure provides a systematic approach to the basic identities involving invariant primitive tensor structures of various irreprs. of finite-dimensional exceptional Lie groups. We derive novel identities for E7 and E6, highlighting the E8 origin of some well known ones. In order to elucidate the connections of this formalism to four-dimensional Maxwell-Einstein supergravity theories based on symmetric scalar manifolds (and related to irreducible Euclidean Jordan algebras, the unique exception being the triality-symmetric N = 2 stu model), we then derive a fundamental identity involving the unique rank-4 symmetric invariant tensor of the 0-brane charge symplectic irrepr. of U-duality groups, with potential applications in the quantization of the charge orbits of supergravity theories, as well as in the study of mult...
A Mean-Variance Diagnosis of the Financial Crisis: International Diversification and Safe Havens
Alexander Eptas
2010-12-01
Full Text Available We use mean-variance analysis with short selling constraints to diagnose the effects of the recent global financial crisis by evaluating the potential benefits of international diversification in the search for ‘safe havens’. We use stock index data for a sample of developed, advanced-emerging and emerging countries. ‘Text-book’ results are obtained for the pre-crisis analysis with the optimal portfolio for any risk-averse investor being obtained as the tangency portfolio of the All-Country portfolio frontier. During the crisis there is a disjunction between bank lending and stock markets revealed by negative average returns and an absence of any empirical Capital Market Line. Israel and Colombia emerge as the safest havens for any investor during the crisis. For Israel this may reflect the protection afforded by special trade links and diaspora support, while for Colombia we speculate that this reveals the impact on world financial markets of the demand for cocaine.
Lee, Kenneth K. C.; Mariampillai, Adrian; Yu, Joe X. Z.; Cadotte, David W.; Wilson, Brian C.; Standish, Beau A.; Yang, Victor X. D.
2012-01-01
Abstract: Advances in swept source laser technology continues to increase the imaging speed of swept-source optical coherence tomography (SS-OCT) systems. These fast imaging speeds are ideal for microvascular detection schemes, such as speckle variance (SV), where interframe motion can cause severe imaging artifacts and loss of vascular contrast. However, full utilization of the laser scan speed has been hindered by the computationally intensive signal processing required by SS-OCT and SV calculations. Using a commercial graphics processing unit that has been optimized for parallel data processing, we report a complete high-speed SS-OCT platform capable of real-time data acquisition, processing, display, and saving at 108,000 lines per second. Subpixel image registration of structural images was performed in real-time prior to SV calculations in order to reduce decorrelation from stationary structures induced by the bulk tissue motion. The viability of the system was successfully demonstrated in a high bulk tissue motion scenario of human fingernail root imaging where SV images (512 × 512 pixels, n = 4) were displayed at 54 frames per second. PMID:22808428
On the stability and spatiotemporal variance distribution of salinity in the upper ocean
O'Kane, Terence J.; Monselesan, Didier P.; Maes, Christophe
2016-06-01
Despite recent advances in ocean observing arrays and satellite sensors, there remains great uncertainty in the large-scale spatial variations of upper ocean salinity on the interannual to decadal timescales. Consonant with both broad-scale surface warming and the amplification of the global hydrological cycle, observed global multidecadal salinity changes typically have focussed on the linear response to anthropogenic forcing but not on salinity variations due to changes in the static stability and or variability due to the intrinsic ocean or internal climate processes. Here, we examine the static stability and spatiotemporal variability of upper ocean salinity across a hierarchy of models and reanalyses. In particular, we partition the variance into time bands via application of singular spectral analysis, considering sea surface salinity (SSS), the Brunt Väisälä frequency (N2), and the ocean salinity stratification in terms of the stabilizing effect due to the haline part of N2 over the upper 500m. We identify regions of significant coherent SSS variability, either intrinsic to the ocean or in response to the interannually varying atmosphere. Based on consistency across models (CMIP5 and forced experiments) and reanalyses, we identify the stabilizing role of salinity in the tropics—typically associated with heavy precipitation and barrier layer formation, and the role of salinity in destabilizing upper ocean stratification in the subtropical regions where large-scale density compensation typically occurs.
Continuous-Time Mean-Variance Portfolio Selection under the CEV Process
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.
Westner, Guenther, E-mail: guenther.westner@eon-energie.co [E.ON Energy Projects GmbH, Arnulfstrasse 56, 80335 Munich (Germany); Madlener, Reinhard, E-mail: rmadlener@eonerc.rwth-aachen.d [Institute for Future Energy Consumer Needs and Behavior (FCN), Faculty of Business and Economics/E.ON Energy Research Center, RWTH Aachen University, Mathieustrasse 6, 52074 Aachen (Germany)
2010-12-15
The EU Directive 2004/8/EC, concerning the promotion of cogeneration, established principles on how EU member states can support combined heat and power generation (CHP). Up to now, the implementation of these principles into national law has not been uniform, and has led to the adoption of different promotion schemes for CHP across the EU member states. In this paper, we first give an overview of the promotion schemes for CHP in various European countries. In a next step, we take two standard CHP technologies, combined-cycle gas turbines (CCGT-CHP) and engine-CHP, and apply exemplarily four selected support mechanisms used in the four largest European energy markets: feed-in tariffs in Germany; energy efficiency certificates in Italy; benefits through tax reduction in the UK; and purchase obligations for power from CHP generation in France. For contracting companies, it could be of interest to diversify their investment in new CHP facilities regionally over several countries in order to reduce country and regulatory risk. By applying the Mean-Variance Portfolio (MVP) theory, we derive characteristic return-risk profiles of the selected CHP technologies in different countries. The results show that the returns on CHP investments differ significantly depending on the country, the support scheme, and the selected technology studied. While a regional diversification of investments in CCGT-CHP does not contribute to reducing portfolio risks, a diversification of investments in engine-CHP can decrease the risk exposure. - Research highlights: {yields}Preconditions for CHP investments differ significantly between the EU member states. {yields}Regional diversification of CHP investments can reduce the total portfolio risk. {yields}Risk reduction depends on the chosen CHP technology.
Bush, B.; Jenkin, T.; Lipowicz, D.; Arent, D. J.; Cooke, R.
2012-01-01
Does large scale penetration of renewable generation such as wind and solar power pose economic and operational burdens on the electricity system? A number of studies have pointed to the potential benefits of renewable generation as a hedge against the volatility and potential escalation of fossil fuel prices. Research also suggests that the lack of correlation of renewable energy costs with fossil fuel prices means that adding large amounts of wind or solar generation may also reduce the volatility of system-wide electricity costs. Such variance reduction of system costs may be of significant value to consumers due to risk aversion. The analysis in this report recognizes that the potential value of risk mitigation associated with wind generation and natural gas generation may depend on whether one considers the consumer's perspective or the investor's perspective and whether the market is regulated or deregulated. We analyze the risk and return trade-offs for wind and natural gas generation for deregulated markets based on hourly prices and load over a 10-year period using historical data in the PJM Interconnection (PJM) from 1999 to 2008. Similar analysis is then simulated and evaluated for regulated markets under certain assumptions.
Westner, Guenther; Madlener, Reinhard [E.ON Energy Projects GmbH, Arnulfstrasse 56, 80335 Munich (Germany)
2010-12-15
The EU Directive 2004/8/EC, concerning the promotion of cogeneration, established principles on how EU member states can support combined heat and power generation (CHP). Up to now, the implementation of these principles into national law has not been uniform, and has led to the adoption of different promotion schemes for CHP across the EU member states. In this paper, we first give an overview of the promotion schemes for CHP in various European countries. In a next step, we take two standard CHP technologies, combined-cycle gas turbines (CCGT-CHP) and engine-CHP, and apply exemplarily four selected support mechanisms used in the four largest European energy markets: feed-in tariffs in Germany; energy efficiency certificates in Italy; benefits through tax reduction in the UK; and purchase obligations for power from CHP generation in France. For contracting companies, it could be of interest to diversify their investment in new CHP facilities regionally over several countries in order to reduce country and regulatory risk. By applying the Mean-Variance Portfolio (MVP) theory, we derive characteristic return-risk profiles of the selected CHP technologies in different countries. The results show that the returns on CHP investments differ significantly depending on the country, the support scheme, and the selected technology studied. While a regional diversification of investments in CCGT-CHP does not contribute to reducing portfolio risks, a diversification of investments in engine-CHP can decrease the risk exposure. (author)
Simon K G Forsberg
2015-11-01
Full Text Available Genome-wide association (GWA analyses have generally been used to detect individual loci contributing to the phenotypic diversity in a population by the effects of these loci on the trait mean. More rarely, loci have also been detected based on variance differences between genotypes. Several hypotheses have been proposed to explain the possible genetic mechanisms leading to such variance signals. However, little is known about what causes these signals, or whether this genetic variance-heterogeneity reflects mechanisms of importance in natural populations. Previously, we identified a variance-heterogeneity GWA (vGWA signal for leaf molybdenum concentrations in Arabidopsis thaliana. Here, fine-mapping of this association reveals that the vGWA emerges from the effects of three independent genetic polymorphisms that all are in strong LD with the markers displaying the genetic variance-heterogeneity. By revealing the genetic architecture underlying this vGWA signal, we uncovered the molecular source of a significant amount of hidden additive genetic variation or "missing heritability". Two of the three polymorphisms underlying the genetic variance-heterogeneity are promoter variants for Molybdate transporter 1 (MOT1, and the third a variant located ~25 kb downstream of this gene. A fourth independent association was also detected ~600 kb upstream of MOT1. Use of a T-DNA knockout allele highlights Copper Transporter 6; COPT6 (AT2G26975 as a strong candidate gene for this association. Our results show that an extended LD across a complex locus including multiple functional alleles can lead to a variance-heterogeneity between genotypes in natural populations. Further, they provide novel insights into the genetic regulation of ion homeostasis in A. thaliana, and empirically confirm that variance-heterogeneity based GWA methods are a valuable tool to detect novel associations of biological importance in natural populations.
Inferring changes in ENSO amplitude from the variance of proxy records
Russon, Tom; Tudhope, Alexander; Collins, Mat; Hegerl, Gabi
2015-01-01
One common approach to investigating past changes in ENSO amplitude is through quantifying the variance of ENSO-influenced proxy records. However, a component of the variance of all such proxies will reflect influences that are unrelated to the instrumental climatic indices from which modern ENSO amplitudes are defined. The unrelated component of proxy variance introduces a fundamental source of uncertainty to all such constraints on past ENSO amplitudes. Based on a simple parametric approach...
Second order pseudo-maximum likelihood estimation and conditional variance misspecification
Lejeune, Bernard
1997-01-01
In this paper, we study the behavior of second order pseudo-maximum likelihood estimators under conditional variance misspecification. We determine sufficient and essentially necessary conditions for such a estimator to be, regardless of the conditional variance (mis)specification, consistent for the mean parameters when the conditional mean is correctly specified. These conditions implie that, even if mean and variance parameters vary independently, standard PML2 estimators are generally not...
How the Weak Variance of Momentum Can Turn Out to be Negative
2015-01-01
Weak values are average quantities, therefore investigating their associated variance is crucial in understanding their place in quantum mechanics. We develop the concept of a position-postselected weak variance of momentum as cohesively as possible, building primarily on material from Moyal (Mathematical Proceedings of the Cambridge Philosophical Society, Cambridge University Press, Cambridge, 1949) and Sonego (Found Phys 21(10):1135, 1991) . The weak variance is defined in terms of the Wign...
Kaneko, Kunihiko
2013-01-01
The characterization of plasticity, robustness, and evolvability, an important issue in biology, is studied in terms of phenotypic fluctuations. By numerically evolving gene regulatory networks, the proportionality between the phenotypic variances of epigenetic and genetic origins is confirmed. The former is given by the variance of the phenotypic fluctuation due to noise in the developmental process; and the latter, by the variance of the phenotypic fluctuation due to genetic mutation. The r...
The Impact of Jump Distributions on the Implied Volatility of Variance
Nicolato, Elisa; Pedersen, David Sloth; Pisani, Camilla
2016-01-01
of jumps on the associated implied volatility smile. We provide sufficient conditions for the asymptotic behavior of the implied volatility of variance for small and large strikes. In particular, by selecting alternative jump distributions, we show that one can obtain fundamentally different shapes...... of the implied volatility of variance smile -- some clearly at odds with the upward-sloping volatility skew observed in variance markets....