NASA Astrophysics Data System (ADS)
Kim, Tae-Jeong; Kim, Ki-Young; Shin, Dong-Hoon; Kwon, Hyun-Han
2015-04-01
It has been widely acknowledged that the appropriate simulation of natural streamflow at ungauged sites is one of the fundamental challenges to hydrology community. In particular, the key to reliable runoff simulation in ungauged basins is a reliable rainfall-runoff model and a parameter estimation. In general, parameter estimation in rainfall-runoff models is a complex issue due to an insufficient hydrologic data. This study aims to regionalize the parameters of the continuous rainfall-runoff model in conjunction with Bayesian statistical techniques to facilitate uncertainty analysis. First, this study uses the Bayesian Markov Chain Monte Carlo scheme for the Sacramento rainfall-runoff model that has been widely used around the world. The Sacramento model is calibrated against daily runoff observation, and thirteen parameters of the model are optimized as well as posterior distributor distributions for each parameter are derived. Second, we applied Bayesian generalized linear regression model to set of the parameters with basin characteristics (e.g. area and slope), to obtain a functional relationship between pairs of variables. The proposed model was validated in two gauged watersheds in accordance with the efficiency criteria such as the Nash-Sutcliffe efficiency, coefficient of efficiency, index of agreement and coefficient of correlation. The future study will be further focused on uncertainty analysis to fully incorporate propagation of the uncertainty into the regionalization framework. KEYWORDS: Ungauge, Parameter, Sacramento, Generalized linear model, Regionalization Acknowledgement This research was supported by a Grant (13SCIPA01) from Smart Civil Infrastructure Research Program funded by the Ministry of Land, Infrastructure and Transport (MOLIT) of Korea government and the Korea Agency for Infrastructure Technology Advancement (KAIA).
NOTE: Estimation of renal scintigraphy parameters using a linear piecewise-continuous model
NASA Astrophysics Data System (ADS)
Zhang, Jeff L.; Zhang, L.; Koh, T. S.; Shuter, B.
2003-06-01
Instead of performing a numerical deconvolution, we propose to use a linear piecewise-continuous model of the renal impulse response function for parametric fitting of renal scintigraphy data, to obtain clinically useful renal parameters. The strengths of the present model are its simplicity and speed of computation, while not compromising on accuracy. Preliminary patient case studies show that the estimated parameters are in good agreement with a more elaborate model.
Bayesian recursive mixed linear model for gene expression analyses with continuous covariates.
Casellas, J; Ibáñez-Escriche, N
2012-01-01
The analysis of microarray gene expression data has experienced a remarkable growth in scientific research over the last few years and is helping to decipher the genetic background of several productive traits. Nevertheless, most analytical approaches have relied on the comparison of 2 (or a few) well-defined groups of biological conditions where the continuous covariates have no sense (e.g., healthy vs. cancerous cells). Continuous effects could be of special interest when analyzing gene expression in animal production-oriented studies (e.g., birth weight), although very few studies address this peculiarity in the animal science framework. Within this context, we have developed a recursive linear mixed model where not only are linear covariates accounted for during gene expression analyses but also hierarchized and the effects of their genetic, environmental, and residual components on differential gene expression inferred independently. This parameterization allows a step forward in the inference of differential gene expression linked to a given quantitative trait such as birth weight. The statistical performance of this recursive model was exemplified under simulation by accounting for different sample sizes (n), heritabilities for the quantitative trait (h(2)), and magnitudes of differential gene expression (λ). It is important to highlight that statistical power increased with n, h(2), and λ, and the recursive model exceeded the standard linear mixed model with linear (nonrecursive) covariates in the majority of scenarios. This new parameterization would provide new insights about gene expression in the animal science framework, opening a new research scenario where within-covariate sources of differential gene expression could be individualized and estimated. The source code of the program accommodating these analytical developments and additional information about practical aspects on running the program are freely available by request to the corresponding
NASA Technical Reports Server (NTRS)
Guo, Tong-Yi; Hwang, Chyi; Shieh, Leang-San
1994-01-01
This paper deals with the multipoint Cauer matrix continued-fraction expansion (MCFE) for model reduction of linear multi-input multi-output (MIMO) systems with various numbers of inputs and outputs. A salient feature of the proposed MCFE approach to model reduction of MIMO systems with square transfer matrices is its equivalence to the matrix Pade approximation approach. The Cauer second form of the ordinary MCFE for a square transfer function matrix is generalized in this paper to a multipoint and nonsquare-matrix version. An interesting connection of the multipoint Cauer MCFE method to the multipoint matrix Pade approximation method is established. Also, algorithms for obtaining the reduced-degree matrix-fraction descriptions and reduced-dimensional state-space models from a transfer function matrix via the multipoint Cauer MCFE algorithm are presented. Practical advantages of using the multipoint Cauer MCFE are discussed and a numerical example is provided to illustrate the algorithms.
ERIC Educational Resources Information Center
Ferrando, Pere J.
2004-01-01
This study used kernel-smoothing procedures to estimate the item characteristic functions (ICFs) of a set of continuous personality items. The nonparametric ICFs were compared with the ICFs estimated (a) by the linear model and (b) by Samejima's continuous-response model. The study was based on a conditioned approach and used an error-in-variables…
Hernández-Lloreda, María Victoria; Colmenares, Fernando; Martínez-Arias, Rosario
2004-09-01
In behavioral science, developmental discontinuities are thought to arise when the association between an outcome measure and the underlying process changes over time. Sudden changes in behavior across time are often taken to indicate that a reorganization in the outcome-process relationship may have occurred. The authors proposed in this article the use of piecewise hierarchical linear growth modeling as a statistical methodology to search for discontinuities in behavioral development and illustrated its possibilities by applying 2-piece hierarchical linear models to the study of developmental trajectories of baboon (Papio hamadryas) mothers' behavior during their infants' 1st year of life. The authors provided empirical evidence that piecewise growth modeling can be used to determine whether abrupt changes in development trajectories are tied to changes in the underlying process. PMID:15482059
Raabe, Joshua K.; Gardner, Beth; Hightower, Joseph E.
2013-01-01
We developed a spatial capture–recapture model to evaluate survival and activity centres (i.e., mean locations) of tagged individuals detected along a linear array. Our spatially explicit version of the Cormack–Jolly–Seber model, analyzed using a Bayesian framework, correlates movement between periods and can incorporate environmental or other covariates. We demonstrate the model using 2010 data for anadromous American shad (Alosa sapidissima) tagged with passive integrated transponders (PIT) at a weir near the mouth of a North Carolina river and passively monitored with an upstream array of PIT antennas. The river channel constrained migrations, resulting in linear, one-dimensional encounter histories that included both weir captures and antenna detections. Individual activity centres in a given time period were a function of the individual’s previous estimated location and the river conditions (i.e., gage height). Model results indicate high within-river spawning mortality (mean weekly survival = 0.80) and more extensive movements during elevated river conditions. This model is applicable for any linear array (e.g., rivers, shorelines, and corridors), opening new opportunities to study demographic parameters, movement or migration, and habitat use.
Wang, Ching-Yun; Dieu Tapsoba, Jean De; Duggan, Catherine; Campbell, Kristin L; McTiernan, Anne
2016-05-10
In many biomedical studies, covariates of interest may be measured with errors. However, frequently in a regression analysis, the quantiles of the exposure variable are often used as the covariates in the regression analysis. Because of measurement errors in the continuous exposure variable, there could be misclassification in the quantiles for the exposure variable. Misclassification in the quantiles could lead to bias estimation in the association between the exposure variable and the outcome variable. Adjustment for misclassification will be challenging when the gold standard variables are not available. In this paper, we develop two regression calibration estimators to reduce bias in effect estimation. The first estimator is normal likelihood-based. The second estimator is linearization-based, and it provides a simple and practical correction. Finite sample performance is examined via a simulation study. We apply the methods to a four-arm randomized clinical trial that tested exercise and weight loss interventions in women aged 50-75years. Copyright © 2015 John Wiley & Sons, Ltd. PMID:26593772
Gonçalves, Nuno R; Whelan, Robert; Foxe, John J; Lalor, Edmund C
2014-08-15
Noninvasive investigation of human sensory processing with high temporal resolution typically involves repeatedly presenting discrete stimuli and extracting an average event-related response from scalp recorded neuroelectric or neuromagnetic signals. While this approach is and has been extremely useful, it suffers from two drawbacks: a lack of naturalness in terms of the stimulus and a lack of precision in terms of the cortical response generators. Here we show that a linear modeling approach that exploits functional specialization in sensory systems can be used to rapidly obtain spatiotemporally precise responses to complex sensory stimuli using electroencephalography (EEG). We demonstrate the method by example through the controlled modulation of the contrast and coherent motion of visual stimuli. Regressing the data against these modulation signals produces spatially focal, highly temporally resolved response measures that are suggestive of specific activation of visual areas V1 and V6, respectively, based on their onset latency, their topographic distribution and the estimated location of their sources. We discuss our approach by comparing it with fMRI/MRI informed source analysis methods and, in doing so, we provide novel information on the timing of coherent motion processing in human V6. Generalizing such an approach has the potential to facilitate the rapid, inexpensive spatiotemporal localization of higher perceptual functions in behaving humans. PMID:24736185
Linear models: permutation methods
Cade, B.S.
2005-01-01
Permutation tests (see Permutation Based Inference) for the linear model have applications in behavioral studies when traditional parametric assumptions about the error term in a linear model are not tenable. Improved validity of Type I error rates can be achieved with properly constructed permutation tests. Perhaps more importantly, increased statistical power, improved robustness to effects of outliers, and detection of alternative distributional differences can be achieved by coupling permutation inference with alternative linear model estimators. For example, it is well-known that estimates of the mean in linear model are extremely sensitive to even a single outlying value of the dependent variable compared to estimates of the median [7, 19]. Traditionally, linear modeling focused on estimating changes in the center of distributions (means or medians). However, quantile regression allows distributional changes to be estimated in all or any selected part of a distribution or responses, providing a more complete statistical picture that has relevance to many biological questions [6]...
Continuous-mode operation of a noiseless linear amplifier
NASA Astrophysics Data System (ADS)
Li, Yi; Carvalho, André R. R.; James, Matthew R.
2016-05-01
We develop a dynamical model to describe the operation of the nondeterministic noiseless linear amplifier (NLA) in the regime of continuous-mode inputs. We analyze the dynamics conditioned on the detection of photons and show that the amplification gain depends on detection times and on the temporal profile of the input state and the auxiliary single-photon state required by the NLA. We also show that the output amplified state inherits the pulse shape of the ancilla photon.
Generalized Linear Models in Family Studies
ERIC Educational Resources Information Center
Wu, Zheng
2005-01-01
Generalized linear models (GLMs), as defined by J. A. Nelder and R. W. M. Wedderburn (1972), unify a class of regression models for categorical, discrete, and continuous response variables. As an extension of classical linear models, GLMs provide a common body of theory and methodology for some seemingly unrelated models and procedures, such as…
Villante, F. L.; Ricci, B.
2010-05-01
We present a new approach to studying the properties of the Sun. We consider small variations of the physical and chemical properties of the Sun with respect to standard solar model predictions and we linearize the structure equations to relate them to the properties of the solar plasma. By assuming that the (variation of) present solar composition can be estimated from the (variation of) nuclear reaction rates and elemental diffusion efficiency in the present Sun, we obtain a linear system of ordinary differential equations which can be used to calculate the response of the Sun to an arbitrary modification of the input parameters (opacity, cross sections, etc.). This new approach is intended to be a complement to the traditional methods for solar model (SM) calculation and allows us to investigate in a more efficient and transparent way the role of parameters and assumptions in SM construction. We verify that these linear solar models recover the predictions of the traditional SMs with a high level of accuracy.
NASA Technical Reports Server (NTRS)
Cellier, Francois E.
1991-01-01
A comprehensive and systematic introduction is presented for the concepts associated with 'modeling', involving the transition from a physical system down to an abstract description of that system in the form of a set of differential and/or difference equations, and basing its treatment of modeling on the mathematics of dynamical systems. Attention is given to the principles of passive electrical circuit modeling, planar mechanical systems modeling, hierarchical modular modeling of continuous systems, and bond-graph modeling. Also discussed are modeling in equilibrium thermodynamics, population dynamics, and system dynamics, inductive reasoning, artificial neural networks, and automated model synthesis.
Non-linear Models for Longitudinal Data
Serroyen, Jan; Molenberghs, Geert; Verbeke, Geert; Davidian, Marie
2009-01-01
While marginal models, random-effects models, and conditional models are routinely considered to be the three main modeling families for continuous and discrete repeated measures with linear and generalized linear mean structures, respectively, it is less common to consider non-linear models, let alone frame them within the above taxonomy. In the latter situation, indeed, when considered at all, the focus is often exclusively on random-effects models. In this paper, we consider all three families, exemplify their great flexibility and relative ease of use, and apply them to a simple but illustrative set of data on tree circumference growth of orange trees. PMID:20160890
Some estimation formulae for continuous time-invariant linear systems
NASA Technical Reports Server (NTRS)
Bierman, G. J.; Sidhu, G. S.
1975-01-01
In this brief paper we examine a Riccati equation decomposition due to Reid and Lainiotis and apply the result to the continuous time-invariant linear filtering problem. Exploitation of the time-invariant structure leads to integration-free covariance recursions which are of use in covariance analyses and in filter implementations. A super-linearly convergent iterative solution to the algebraic Riccati equation (ARE) is developed. The resulting algorithm, arranged in a square-root form, is thought to be numerically stable and competitive with other ARE solution methods. Certain covariance relations that are relevant to the fixed-point and fixed-lag smoothing problems are also discussed.
Parameterized Linear Longitudinal Airship Model
NASA Technical Reports Server (NTRS)
Kulczycki, Eric; Elfes, Alberto; Bayard, David; Quadrelli, Marco; Johnson, Joseph
2010-01-01
A parameterized linear mathematical model of the longitudinal dynamics of an airship is undergoing development. This model is intended to be used in designing control systems for future airships that would operate in the atmospheres of Earth and remote planets. Heretofore, the development of linearized models of the longitudinal dynamics of airships has been costly in that it has been necessary to perform extensive flight testing and to use system-identification techniques to construct models that fit the flight-test data. The present model is a generic one that can be relatively easily specialized to approximate the dynamics of specific airships at specific operating points, without need for further system identification, and with significantly less flight testing. The approach taken in the present development is to merge the linearized dynamical equations of an airship with techniques for estimation of aircraft stability derivatives, and to thereby make it possible to construct a linearized dynamical model of the longitudinal dynamics of a specific airship from geometric and aerodynamic data pertaining to that airship. (It is also planned to develop a model of the lateral dynamics by use of the same methods.) All of the aerodynamic data needed to construct the model of a specific airship can be obtained from wind-tunnel testing and computational fluid dynamics
LINEAR - DERIVATION AND DEFINITION OF A LINEAR AIRCRAFT MODEL
NASA Technical Reports Server (NTRS)
Duke, E. L.
1994-01-01
The Derivation and Definition of a Linear Model program, LINEAR, provides the user with a powerful and flexible tool for the linearization of aircraft aerodynamic models. LINEAR was developed to provide a standard, documented, and verified tool to derive linear models for aircraft stability analysis and control law design. Linear system models define the aircraft system in the neighborhood of an analysis point and are determined by the linearization of the nonlinear equations defining vehicle dynamics and sensors. LINEAR numerically determines a linear system model using nonlinear equations of motion and a user supplied linear or nonlinear aerodynamic model. The nonlinear equations of motion used are six-degree-of-freedom equations with stationary atmosphere and flat, nonrotating earth assumptions. LINEAR is capable of extracting both linearized engine effects, such as net thrust, torque, and gyroscopic effects and including these effects in the linear system model. The point at which this linear model is defined is determined either by completely specifying the state and control variables, or by specifying an analysis point on a trajectory and directing the program to determine the control variables and the remaining state variables. The system model determined by LINEAR consists of matrices for both the state and observation equations. The program has been designed to provide easy selection of state, control, and observation variables to be used in a particular model. Thus, the order of the system model is completely under user control. Further, the program provides the flexibility of allowing alternate formulations of both the state and observation equations. Data describing the aircraft and the test case is input to the program through a terminal or formatted data files. All data can be modified interactively from case to case. The aerodynamic model can be defined in two ways: a set of nondimensional stability and control derivatives for the flight point of
Foster, Guy M.; Graham, Jennifer L.
2016-01-01
The Kansas River is a primary source of drinking water for about 800,000 people in northeastern Kansas. Source-water supplies are treated by a combination of chemical and physical processes to remove contaminants before distribution. Advanced notification of changing water-quality conditions and cyanobacteria and associated toxin and taste-and-odor compounds provides drinking-water treatment facilities time to develop and implement adequate treatment strategies. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office (funded in part through the Kansas State Water Plan Fund), and the City of Lawrence, the City of Topeka, the City of Olathe, and Johnson County Water One, began a study in July 2012 to develop statistical models at two Kansas River sites located upstream from drinking-water intakes. Continuous water-quality monitors have been operated and discrete-water quality samples have been collected on the Kansas River at Wamego (USGS site number 06887500) and De Soto (USGS site number 06892350) since July 2012. Continuous and discrete water-quality data collected during July 2012 through June 2015 were used to develop statistical models for constituents of interest at the Wamego and De Soto sites. Logistic models to continuously estimate the probability of occurrence above selected thresholds were developed for cyanobacteria, microcystin, and geosmin. Linear regression models to continuously estimate constituent concentrations were developed for major ions, dissolved solids, alkalinity, nutrients (nitrogen and phosphorus species), suspended sediment, indicator bacteria (Escherichia coli, fecal coliform, and enterococci), and actinomycetes bacteria. These models will be used to provide real-time estimates of the probability that cyanobacteria and associated compounds exceed thresholds and of the concentrations of other water-quality constituents in the Kansas River. The models documented in this report are useful for characterizing changes
Inverse Modeling Via Linearized Functional Minimization
NASA Astrophysics Data System (ADS)
Barajas-Solano, D. A.; Wohlberg, B.; Vesselinov, V. V.; Tartakovsky, D. M.
2014-12-01
We present a novel parameter estimation methodology for transient models of geophysical systems with uncertain, spatially distributed, heterogeneous and piece-wise continuous parameters.The methodology employs a bayesian approach to propose an inverse modeling problem for the spatial configuration of the model parameters.The likelihood of the configuration is formulated using sparse measurements of both model parameters and transient states.We propose using total variation regularization (TV) as the prior reflecting the heterogeneous, piece-wise continuity assumption on the parameter distribution.The maximum a posteriori (MAP) estimator of the parameter configuration is then computed by minimizing the negative bayesian log-posterior using a linearized functional minimization approach. The computation of the MAP estimator is a large-dimensional nonlinear minimization problem with two sources of nonlinearity: (1) the TV operator, and (2) the nonlinear relation between states and parameters provided by the model's governing equations.We propose a a hybrid linearized functional minimization (LFM) algorithm in two stages to efficiently treat both sources of nonlinearity.The relation between states and parameters is linearized, resulting in a linear minimization sub-problem equipped with the TV operator; this sub-problem is then minimized using the Alternating Direction Method of Multipliers (ADMM). The methodology is illustrated with a transient saturated groundwater flow application in a synthetic domain, stimulated by external point-wise loadings representing aquifer pumping, together with an array of discrete measurements of hydraulic conductivity and transient measurements of hydraulic head.We show that our inversion strategy is able to recover the overall large-scale features of the parameter configuration, and that the reconstruction is improved by the addition of transient information of the state variable.
Computing Linear Mathematical Models Of Aircraft
NASA Technical Reports Server (NTRS)
Duke, Eugene L.; Antoniewicz, Robert F.; Krambeer, Keith D.
1991-01-01
Derivation and Definition of Linear Aircraft Model (LINEAR) computer program provides user with powerful, and flexible, standard, documented, and verified software tool for linearization of mathematical models of aerodynamics of aircraft. Intended for use in software tool to drive linear analysis of stability and design of control laws for aircraft. Capable of both extracting such linearized engine effects as net thrust, torque, and gyroscopic effects, and including these effects in linear model of system. Designed to provide easy selection of state, control, and observation variables used in particular model. Also provides flexibility of allowing alternate formulations of both state and observation equations. Written in FORTRAN.
On high-continuity transfinite element formulations for linear-nonlinear transient thermal problems
NASA Technical Reports Server (NTRS)
Tamma, Kumar K.; Railkar, Sudhir B.
1987-01-01
This paper describes recent developments in the applicability of a hybrid transfinite element methodology with emphasis on high-continuity formulations for linear/nonlinear transient thermal problems. The proposed concepts furnish accurate temperature distributions and temperature gradients making use of a relatively smaller number of degrees of freedom; and the methodology is applicable to linear/nonlinear thermal problems. Characteristic features of the formulations are described in technical detail as the proposed hybrid approach combines the major advantages and modeling features of high-continuity thermal finite elements in conjunction with transform methods and classical Galerkin schemes. Several numerical test problems are evaluated and the results obtained validate the proposed concepts for linear/nonlinear thermal problems.
Wealth redistribution in conservative linear kinetic models
NASA Astrophysics Data System (ADS)
Toscani, G.
2009-10-01
We introduce and discuss kinetic models for wealth distribution which include both taxation and uniform redistribution. The evolution of the continuous density of wealth obeys a linear Boltzmann equation where the background density represents the action of an external subject on the taxation mechanism. The case in which the mean wealth is conserved is analyzed in full details, by recovering the analytical form of the steady states. These states are probability distributions of convergent random series of a special structure, called perpetuities. Among others, Gibbs distribution appears as steady state in case of total taxation and uniform redistribution.
Nonlinear Modeling by Assembling Piecewise Linear Models
NASA Technical Reports Server (NTRS)
Yao, Weigang; Liou, Meng-Sing
2013-01-01
To preserve nonlinearity of a full order system over a parameters range of interest, we propose a simple modeling approach by assembling a set of piecewise local solutions, including the first-order Taylor series terms expanded about some sampling states. The work by Rewienski and White inspired our use of piecewise linear local solutions. The assembly of these local approximations is accomplished by assigning nonlinear weights, through radial basis functions in this study. The efficacy of the proposed procedure is validated for a two-dimensional airfoil moving at different Mach numbers and pitching motions, under which the flow exhibits prominent nonlinear behaviors. All results confirm that our nonlinear model is accurate and stable for predicting not only aerodynamic forces but also detailed flowfields. Moreover, the model is robustness-accurate for inputs considerably different from the base trajectory in form and magnitude. This modeling preserves nonlinearity of the problems considered in a rather simple and accurate manner.
Linear Logistic Test Modeling with R
ERIC Educational Resources Information Center
Baghaei, Purya; Kubinger, Klaus D.
2015-01-01
The present paper gives a general introduction to the linear logistic test model (Fischer, 1973), an extension of the Rasch model with linear constraints on item parameters, along with eRm (an R package to estimate different types of Rasch models; Mair, Hatzinger, & Mair, 2014) functions to estimate the model and interpret its parameters. The…
A spatially continuous magnetization model for Mars
NASA Astrophysics Data System (ADS)
Whaler, K. A.; Purucker, M. E.
2005-09-01
Using a three-component magnetic field data set at over 100,000 satellite points previously compiled for spherical harmonic analysis, we have produced a continuously varying magnetization model for Mars. The magnetized layer was assumed to be 40 km thick, an average value based on previous studies of the topography and gravity field. The severe nonuniqueness in magnetization modeling is addressed by seeking the model with minimum root-mean-square (RMS) magnetization for a given fit to the data, with the trade-off between RMS magnetization and fit controlled by a damping parameter. Our preferred model has magnetization amplitudes up to 20 A/m. It is expressed as a linear combination of the Green's functions relating each observation to magnetization at the point of interest within the crust, leading to a linear system of equations of dimension the number of data points. Although this is impractically large for direct solution, most of the matrix elements relating data to model parameters are negligibly small. We therefore apply methods applicable to sparse systems, allowing us to preserve the resolution of the original data set. Thus we produce more detailed models than any previously published, although they share many similarities. We find that tectonism in the Valles Marineris region has a magnetic signature, and we show that volcanism south of the dichotomy boundary has both a magnetic and gravity signature. The method can also be used to downward continue magnetic data, and a comparison with other leveling techniques at Mars' surface is favorable.
Continuous Quantitative Measurements on a Linear Air Track
ERIC Educational Resources Information Center
Vogel, Eric
1973-01-01
Describes the construction and operational procedures of a spark-timing apparatus which is designed to record the back and forth motion of one or two carts on linear air tracks. Applications to measurements of velocity, acceleration, simple harmonic motion, and collision problems are illustrated. (CC)
NASA Astrophysics Data System (ADS)
Peeling, S. M.; Ponting, K. M.
1991-12-01
Linear discriminant analysis is used to generate speech data transformations. This transformed data is then used within the Airborne Reconnaissance Mission (ARM) continuous speech recognition system. The aim of the ARM project is accurate recognition of continuously spoken airborne reconnaissance reports using a speech recognition system based on phoneme level hidden Markov models. A fuller description of a linear discriminant analysis, which is applied to speaker dependent data in the ARM system, is given. Preliminary results are presented from experiments using transformed data alone and also in conjunction with one, or both, of the word transition penalties and variable frame rate analysis. Speaker dependent results are reported which are significantly better then the best obtained previously.
Generalization of continuous-variable quantum cloning with linear optics
NASA Astrophysics Data System (ADS)
Zhai, Zehui; Guo, Juan; Gao, Jiangrui
2006-05-01
We propose an asymmetric quantum cloning scheme. Based on the proposal and experiment by Andersen [Phys. Rev. Lett. 94, 240503 (2005)], we generalize it to two asymmetric cases: quantum cloning with asymmetry between output clones and between quadrature variables. These optical implementations also employ linear elements and homodyne detection only. Finally, we also compare the utility of symmetric and asymmetric cloning in an analysis of a squeezed-state quantum key distribution protocol and find that the asymmetric one is more advantageous.
Composite Linear Models | Division of Cancer Prevention
By Stuart G. Baker The composite linear models software is a matrix approach to compute maximum likelihood estimates and asymptotic standard errors for models for incomplete multinomial data. It implements the method described in Baker SG. Composite linear models for incomplete multinomial data. Statistics in Medicine 1994;13:609-622. The software includes a library of thirty examples from the literature. |
Generalization of continuous-variable quantum cloning with linear optics
Zhai Zehui; Guo Juan; Gao Jiangrui
2006-05-15
We propose an asymmetric quantum cloning scheme. Based on the proposal and experiment by Andersen et al. [Phys. Rev. Lett. 94, 240503 (2005)], we generalize it to two asymmetric cases: quantum cloning with asymmetry between output clones and between quadrature variables. These optical implementations also employ linear elements and homodyne detection only. Finally, we also compare the utility of symmetric and asymmetric cloning in an analysis of a squeezed-state quantum key distribution protocol and find that the asymmetric one is more advantageous.
Quantifying and visualizing variations in sets of images using continuous linear optimal transport
NASA Astrophysics Data System (ADS)
Kolouri, Soheil; Rohde, Gustavo K.
2014-03-01
Modern advancements in imaging devices have enabled us to explore the subcellular structure of living organisms and extract vast amounts of information. However, interpreting the biological information mined in the captured images is not a trivial task. Utilizing predetermined numerical features is usually the only hope for quantifying this information. Nonetheless, direct visual or biological interpretation of results obtained from these selected features is non-intuitive and difficult. In this paper, we describe an automatic method for modeling visual variations in a set of images, which allows for direct visual interpretation of the most significant differences, without the need for predefined features. The method is based on a linearized version of the continuous optimal transport (OT) metric, which provides a natural linear embedding for the image data set, in which linear combination of images leads to a visually meaningful image. This enables us to apply linear geometric data analysis techniques such as principal component analysis and linear discriminant analysis in the linearly embedded space and visualize the most prominent modes, as well as the most discriminant modes of variations, in the dataset. Using the continuous OT framework, we are able to analyze variations in shape and texture in a set of images utilizing each image at full resolution, that otherwise cannot be done by existing methods. The proposed method is applied to a set of nuclei images segmented from Feulgen stained liver tissues in order to investigate the major visual differences in chromatin distribution of Fetal-Type Hepatoblastoma (FHB) cells compared to the normal cells.
Dissipative Continuous Spontaneous Localization (CSL) model
NASA Astrophysics Data System (ADS)
Smirne, Andrea; Bassi, Angelo
2015-08-01
Collapse models explain the absence of quantum superpositions at the macroscopic scale, while giving practically the same predictions as quantum mechanics for microscopic systems. The Continuous Spontaneous Localization (CSL) model is the most refined and studied among collapse models. A well-known problem of this model, and of similar ones, is the steady and unlimited increase of the energy induced by the collapse noise. Here we present the dissipative version of the CSL model, which guarantees a finite energy during the entire system’s evolution, thus making a crucial step toward a realistic energy-conserving collapse model. This is achieved by introducing a non-linear stochastic modification of the Schrödinger equation, which represents the action of a dissipative finite-temperature collapse noise. The possibility to introduce dissipation within collapse models in a consistent way will have relevant impact on the experimental investigations of the CSL model, and therefore also on the testability of the quantum superposition principle.
Dissipative Continuous Spontaneous Localization (CSL) model.
Smirne, Andrea; Bassi, Angelo
2015-01-01
Collapse models explain the absence of quantum superpositions at the macroscopic scale, while giving practically the same predictions as quantum mechanics for microscopic systems. The Continuous Spontaneous Localization (CSL) model is the most refined and studied among collapse models. A well-known problem of this model, and of similar ones, is the steady and unlimited increase of the energy induced by the collapse noise. Here we present the dissipative version of the CSL model, which guarantees a finite energy during the entire system's evolution, thus making a crucial step toward a realistic energy-conserving collapse model. This is achieved by introducing a non-linear stochastic modification of the Schrödinger equation, which represents the action of a dissipative finite-temperature collapse noise. The possibility to introduce dissipation within collapse models in a consistent way will have relevant impact on the experimental investigations of the CSL model, and therefore also on the testability of the quantum superposition principle. PMID:26243034
Dissipative Continuous Spontaneous Localization (CSL) model
Smirne, Andrea; Bassi, Angelo
2015-01-01
Collapse models explain the absence of quantum superpositions at the macroscopic scale, while giving practically the same predictions as quantum mechanics for microscopic systems. The Continuous Spontaneous Localization (CSL) model is the most refined and studied among collapse models. A well-known problem of this model, and of similar ones, is the steady and unlimited increase of the energy induced by the collapse noise. Here we present the dissipative version of the CSL model, which guarantees a finite energy during the entire system’s evolution, thus making a crucial step toward a realistic energy-conserving collapse model. This is achieved by introducing a non-linear stochastic modification of the Schrödinger equation, which represents the action of a dissipative finite-temperature collapse noise. The possibility to introduce dissipation within collapse models in a consistent way will have relevant impact on the experimental investigations of the CSL model, and therefore also on the testability of the quantum superposition principle. PMID:26243034
Aircraft engine mathematical model - linear system approach
NASA Astrophysics Data System (ADS)
Rotaru, Constantin; Roateşi, Simona; Cîrciu, Ionicǎ
2016-06-01
This paper examines a simplified mathematical model of the aircraft engine, based on the theory of linear and nonlinear systems. The dynamics of the engine was represented by a linear, time variant model, near a nominal operating point within a finite time interval. The linearized equations were expressed in a matrix form, suitable for the incorporation in the MAPLE program solver. The behavior of the engine was included in terms of variation of the rotational speed following a deflection of the throttle. The engine inlet parameters can cover a wide range of altitude and Mach numbers.
Theoretical and Empirical Comparisons between Two Models for Continuous Item Responses.
ERIC Educational Resources Information Center
Ferrando, Pere J.
2002-01-01
Analyzed the relations between two continuous response models intended for typical response items: the linear congeneric model and Samejima's continuous response model (CRM). Illustrated the relations described using an empirical example and assessed the relations through a simulation study. (SLD)
Continuing evaluation of bipolar linear devices for total dose bias dependency and ELDRS effects
NASA Technical Reports Server (NTRS)
McClure, Steven S.; Gorelick, Jerry L.; Yui, Candice; Rax, Bernard G.; Wiedeman, Michael D.
2003-01-01
We present results of continuing efforts to evaluate total dose bias dependency and ELDRS effects in bipolar linear microcircuits. Several devices were evaluated, each exhibiting moderate to significant bias and/or dose rate dependency.
On Estimation of Partially Linear Transformation Models
Lu, Wenbin; Zhang, Hao Helen
2010-01-01
We study a general class of partially linear transformation models, which extend linear transformation models by incorporating nonlinear covariate effects in survival data analysis. A new martingale-based estimating equation approach, consisting of both global and kernel-weighted local estimation equations, is developed for estimating the parametric and nonparametric covariate effects in a unified manner. We show that with a proper choice of the kernel bandwidth parameter, one can obtain the consistent and asymptotically normal parameter estimates for the linear effects. Asymptotic properties of the estimated nonlinear effects are established as well. We further suggest a simple resampling method to estimate the asymptotic variance of the linear estimates and show its effectiveness. To facilitate the implementation of the new procedure, an iterative algorithm is developed. Numerical examples are given to illustrate the finite-sample performance of the procedure. PMID:20802823
On Estimation of Partially Linear Transformation Models.
Lu, Wenbin; Zhang, Hao Helen
2010-06-01
We study a general class of partially linear transformation models, which extend linear transformation models by incorporating nonlinear covariate effects in survival data analysis. A new martingale-based estimating equation approach, consisting of both global and kernel-weighted local estimation equations, is developed for estimating the parametric and nonparametric covariate effects in a unified manner. We show that with a proper choice of the kernel bandwidth parameter, one can obtain the consistent and asymptotically normal parameter estimates for the linear effects. Asymptotic properties of the estimated nonlinear effects are established as well. We further suggest a simple resampling method to estimate the asymptotic variance of the linear estimates and show its effectiveness. To facilitate the implementation of the new procedure, an iterative algorithm is developed. Numerical examples are given to illustrate the finite-sample performance of the procedure. PMID:20802823
Numerical Based Linear Model for Dipole Magnets
Li,Y.; Krinsky, S.; Rehak, M.
2009-05-04
In this paper, we discuss an algorithm for constructing a numerical linear optics model for dipole magnets from a 3D field map. The difference between the numerical model and K. Brown's analytic approach is investigated and clarified. It was found that the optics distortion due to the dipoles' fringe focusing must be properly taken into account to accurately determine the chromaticities. In NSLS-II, there are normal dipoles with 35-mm gap and dipoles for infrared sources with 90-mm gap. This linear model of the dipole magnets is applied to the NSLS-II lattice design to match optics parameters between the DBA cells having dipoles with different gaps.
Congeneric Models and Levine's Linear Equating Procedures.
ERIC Educational Resources Information Center
Brennan, Robert L.
In 1955, R. Levine introduced two linear equating procedures for the common-item non-equivalent populations design. His procedures make the same assumptions about true scores; they differ in terms of the nature of the equating function used. In this paper, two parameterizations of a classical congeneric model are introduced to model the variables…
ERIC Educational Resources Information Center
Ker, H. W.
2014-01-01
Multilevel data are very common in educational research. Hierarchical linear models/linear mixed-effects models (HLMs/LMEs) are often utilized to analyze multilevel data nowadays. This paper discusses the problems of utilizing ordinary regressions for modeling multilevel educational data, compare the data analytic results from three regression…
NASA Astrophysics Data System (ADS)
Brake, M. R.
2011-06-01
The analysis of continuous systems with piecewise-linear constraints in their domains have previously been limited to either numerical approaches, or analytical methods that are constrained in the parameter space, boundary conditions, or order of the system. The present analysis develops a robust method for studying continuous systems with arbitrary boundary conditions and discrete piecewise-linear constraints. A superposition method is used to generate homogeneous boundary conditions, and modal analysis is used to find the displacement of the system in each state of the piecewise-linear constraint. In order to develop a mapping across each slope discontinuity in the piecewise-linear force-deflection profile, a variational calculus approach is taken that minimizes the L 2 energy norm between the previous and current states. An approach for calculating the finite-time Lyapunov exponents is presented in order to determine chaotic regimes. To illustrate this method, two examples are presented: a pinned-pinned beam with a deadband constraint, and a leaf spring coupled with a connector pin immersed in a viscous fluid. The pinned-pinned beam example illustrates the method for a non-operator based analysis. Results are used to show that the present method does not necessitate the need of a large number of basis functions to adequately map the displacement and velocity of the system across states. In the second example, the leaf spring is modeled as a clamped-free beam. The interaction between the beam and the connector pin is modeled with a preload and a penalty stiffness. Several experiments are conducted in order to validate aspects of the leaf spring model. From the results of the convergence and parameter studies, a high correlation between the finite-time Lyapunov exponents and the contact time per period of the excitation is observed. The parameter studies also indicate that when the system's parameters are changed in order to reduce the magnitude of the impact
Orthogonal nilpotent superfields from linear models
NASA Astrophysics Data System (ADS)
Kallosh, Renata; Karlsson, Anna; Mosk, Benjamin; Murli, Divyanshu
2016-05-01
We derive supersymmetry/supergravity models with constrained orthogonal nilpotent superfields from the linear models in the formal limit where the masses of the sgoldstino, inflatino and sinflaton tend to infinity. The case where the sinflaton mass remains finite leads to a model with a `relaxed' constraint, where the sinflaton remains an independent field. Our procedure is equivalent to a requirement that some of the components of the curvature of the moduli space tend to infinity.
Managing Clustered Data Using Hierarchical Linear Modeling
ERIC Educational Resources Information Center
Warne, Russell T.; Li, Yan; McKyer, E. Lisako J.; Condie, Rachel; Diep, Cassandra S.; Murano, Peter S.
2012-01-01
Researchers in nutrition research often use cluster or multistage sampling to gather participants for their studies. These sampling methods often produce violations of the assumption of data independence that most traditional statistics share. Hierarchical linear modeling is a statistical method that can overcome violations of the independence…
Oliver-Rodríguez, B; Zafra-Gómez, A; Reis, M S; Duarte, B P M; Verge, C; de Ferrer, J A; Pérez-Pascual, M; Vílchez, J L
2015-07-01
The behaviour of Linear Alkylbenzene Sulfonate (LAS) in agricultural soil is investigated in the laboratory using continuous-flow soil column studies in order to simultaneously analyze the three main underlying phenomena (adsorption/desorption, degradation and transport). The continuous-flow soil column experiments generated the breakthrough curves for each LAS homologue, C10, C11, C12 and C13, and by adding them up, for total LAS, from which the relevant retention, degradation and transport parameters could be estimated, after proposing adequate models. Several transport equations were considered, including the degradation of the sorbate in solution and its retention by soil, under equilibrium and non-equilibrium conditions between the sorbent and the sorbate. In general, the results obtained for the estimates of those parameters that were common to the various models studied (such as the isotherm slope, first order degradation rate coefficient and the hydrodynamic dispersion coefficient) were rather consistent, meaning that mass transfer limitations are not playing a major role in the experiments. These three parameters increase with the length of the LAS homologue chain. The study will provide the underlying conceptual framework and fundamental parameters to understand, simulate and predict the environmental behaviour of LAS compounds in agricultural soils. PMID:25765258
NASA Astrophysics Data System (ADS)
Schmitt, F. G.
2014-12-01
Multiplicative cascade models, when densified (continuous scale invariance) correspond to the exponential of a linear process. Hence this cannot generate zero values. Such framework is not complete and not purely multiplicative. We present here a stochastic framework which stays in the multiplicative realm and can be used to generate zero values. The multiplicative continuous model for multifractal fields with zero values is built using infinitely multiplicative random variables, the multiplicative analog to infinitely divisible distributions for addition. It also needs stochastic multiplicative measures and multiplicative stochastic integrals. The model hence generates continuous multiplicative cascades. The model produced possesses as special case a continuous generalization of the classical discrete beta-model. Applications are numerous in many fields of applied sciences, including smallscale rainfall, soil sciences. The theory is first proposed, then simulation algorithm is presented and simulations are shown in 1D and in 2D. Figure: a continuous lognormal multifractal with zero values (512x512).
Linear Mixed Models: Gum and Beyond
NASA Astrophysics Data System (ADS)
Arendacká, Barbora; Täubner, Angelika; Eichstädt, Sascha; Bruns, Thomas; Elster, Clemens
2014-04-01
In Annex H.5, the Guide to the Evaluation of Uncertainty in Measurement (GUM) [1] recognizes the necessity to analyze certain types of experiments by applying random effects ANOVA models. These belong to the more general family of linear mixed models that we focus on in the current paper. Extending the short introduction provided by the GUM, our aim is to show that the more general, linear mixed models cover a wider range of situations occurring in practice and can be beneficial when employed in data analysis of long-term repeated experiments. Namely, we point out their potential as an aid in establishing an uncertainty budget and as means for gaining more insight into the measurement process. We also comment on computational issues and to make the explanations less abstract, we illustrate all the concepts with the help of a measurement campaign conducted in order to challenge the uncertainty budget in calibration of accelerometers.
On the Limit Cycles for a Class of Continuous Piecewise Linear Differential Systems with Three Zones
NASA Astrophysics Data System (ADS)
Lima, Maurício Firmino Silva; Pessoa, Claudio; Pereira, Weber F.
Lima and Llibre [2012] have studied a class of planar continuous piecewise linear vector fields with three zones. Using the Poincaré map, they proved that this class admits always a unique limit cycle, which is hyperbolic. The class studied in [Lima & Llibre, 2012] belongs to a larger set of planar continuous piecewise linear vector fields with three zones that can be separated into four other classes. Here, we consider some of these classes and we prove that some of them always admit a unique limit cycle, which is hyperbolic. However we find a class that does not have limit cycles.
User's manual for LINEAR, a FORTRAN program to derive linear aircraft models
NASA Technical Reports Server (NTRS)
Duke, Eugene L.; Patterson, Brian P.; Antoniewicz, Robert F.
1987-01-01
This report documents a FORTRAN program that provides a powerful and flexible tool for the linearization of aircraft models. The program LINEAR numerically determines a linear system model using nonlinear equations of motion and a user-supplied nonlinear aerodynamic model. The system model determined by LINEAR consists of matrices for both state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model.
Synaptic dynamics: linear model and adaptation algorithm.
Yousefi, Ali; Dibazar, Alireza A; Berger, Theodore W
2014-08-01
In this research, temporal processing in brain neural circuitries is addressed by a dynamic model of synaptic connections in which the synapse model accounts for both pre- and post-synaptic processes determining its temporal dynamics and strength. Neurons, which are excited by the post-synaptic potentials of hundred of the synapses, build the computational engine capable of processing dynamic neural stimuli. Temporal dynamics in neural models with dynamic synapses will be analyzed, and learning algorithms for synaptic adaptation of neural networks with hundreds of synaptic connections are proposed. The paper starts by introducing a linear approximate model for the temporal dynamics of synaptic transmission. The proposed linear model substantially simplifies the analysis and training of spiking neural networks. Furthermore, it is capable of replicating the synaptic response of the non-linear facilitation-depression model with an accuracy better than 92.5%. In the second part of the paper, a supervised spike-in-spike-out learning rule for synaptic adaptation in dynamic synapse neural networks (DSNN) is proposed. The proposed learning rule is a biologically plausible process, and it is capable of simultaneously adjusting both pre- and post-synaptic components of individual synapses. The last section of the paper starts with presenting the rigorous analysis of the learning algorithm in a system identification task with hundreds of synaptic connections which confirms the learning algorithm's accuracy, repeatability and scalability. The DSNN is utilized to predict the spiking activity of cortical neurons and pattern recognition tasks. The DSNN model is demonstrated to be a generative model capable of producing different cortical neuron spiking patterns and CA1 Pyramidal neurons recordings. A single-layer DSNN classifier on a benchmark pattern recognition task outperforms a 2-Layer Neural Network and GMM classifiers while having fewer numbers of free parameters and
Comparing the Discrete and Continuous Logistic Models
ERIC Educational Resources Information Center
Gordon, Sheldon P.
2008-01-01
The solutions of the discrete logistic growth model based on a difference equation and the continuous logistic growth model based on a differential equation are compared and contrasted. The investigation is conducted using a dynamic interactive spreadsheet. (Contains 5 figures.)
Linear transport models for adsorbing solutes
NASA Astrophysics Data System (ADS)
Roth, K.; Jury, W. A.
1993-04-01
A unified linear theory for the transport of adsorbing solutes through soils is presented and applied to analyze movement of napropamide through undisturbed soil columns. The transport characteristics of the soil are expressed in terms of the travel time distribution of the mobile phase which is then used to incorporate local interaction processes. This approach permits the analysis of all linear transport processes, not only the small subset for which a differential description is known. From a practical point of view, it allows the direct use of measured concentrations or fluxes of conservative solutes to characterize the mobile phase without first subjecting them to any model. For complicated flow regimes, this may vastly improve the identification of models and estimation of their parameters for the local adsorption processes.
Nonlinear damping and quasi-linear modelling.
Elliott, S J; Ghandchi Tehrani, M; Langley, R S
2015-09-28
The mechanism of energy dissipation in mechanical systems is often nonlinear. Even though there may be other forms of nonlinearity in the dynamics, nonlinear damping is the dominant source of nonlinearity in a number of practical systems. The analysis of such systems is simplified by the fact that they show no jump or bifurcation behaviour, and indeed can often be well represented by an equivalent linear system, whose damping parameters depend on the form and amplitude of the excitation, in a 'quasi-linear' model. The diverse sources of nonlinear damping are first reviewed in this paper, before some example systems are analysed, initially for sinusoidal and then for random excitation. For simplicity, it is assumed that the system is stable and that the nonlinear damping force depends on the nth power of the velocity. For sinusoidal excitation, it is shown that the response is often also almost sinusoidal, and methods for calculating the amplitude are described based on the harmonic balance method, which is closely related to the describing function method used in control engineering. For random excitation, several methods of analysis are shown to be equivalent. In general, iterative methods need to be used to calculate the equivalent linear damper, since its value depends on the system's response, which itself depends on the value of the equivalent linear damper. The power dissipation of the equivalent linear damper, for both sinusoidal and random cases, matches that dissipated by the nonlinear damper, providing both a firm theoretical basis for this modelling approach and clear physical insight. Finally, practical examples of nonlinear damping are discussed: in microspeakers, vibration isolation, energy harvesting and the mechanical response of the cochlea. PMID:26303921
B-737 Linear Autoland Simulink Model
NASA Technical Reports Server (NTRS)
Belcastro, Celeste (Technical Monitor); Hogge, Edward F.
2004-01-01
The Linear Autoland Simulink model was created to be a modular test environment for testing of control system components in commercial aircraft. The input variables, physical laws, and referenced frames used are summarized. The state space theory underlying the model is surveyed and the location of the control actuators described. The equations used to realize the Dryden gust model to simulate winds and gusts are derived. A description of the pseudo-random number generation method used in the wind gust model is included. The longitudinal autopilot, lateral autopilot, automatic throttle autopilot, engine model and automatic trim devices are considered as subsystems. The experience in converting the Airlabs FORTRAN aircraft control system simulation to a graphical simulation tool (Matlab/Simulink) is described.
Drawbacks of using linear mixture modeling on hyperspectral images
NASA Astrophysics Data System (ADS)
Rodricks, Neena; Kirkland, Laurel E.
2004-10-01
Hyperspectral spectroscopy can be used remotely to measure emitted radiation from minerals and rocks at a series of narrow and continuous wavelength bands resulting in a continuous spectrum for each pixel, thereby providing ample spectral information to identify and distinguish spectrally unique materials. Linear mixture modeling ("spectral unmixing"), a commonly used method, is based on the theory that the radiance in the thermal infrared region (8-12 μm) from a multi-mineral surface can be modeled as a linear combination of the endmembers. A linear mixture model can thus potentially model the minerals present on planetary surfaces. It works by scaling the endmember spectra so that the sum of the scaled endmember spectra matches the measured spectrum with the smallest "error" (difference). But one of the drawbacks of this established method is that mathematically, a fit with an inverted spectrum is valid, which effectively returns a negative abundance of a material. Current models usually address the problem by elimination of endmembers that have negative scale factors. Eliminating the negative abundance problem is not a major issue when the endmembers are known. However, identifying unknown target composition (like on Mars) can be a problem. The goal of this study is to improve the understanding and find a subsequent solution of the negative abundance problem for Mars analog field data obtained from airborne and ground spectrometers. We are using a well-defined library of spectra to test the accuracy of hyperspectral analysis for the identification of minerals on planetary surfaces.
Reduced Order ODE Model for Linear Contrails
NASA Astrophysics Data System (ADS)
Inamdar, A. R.; Lele, S. K.; Jacobson, M. Z.
2015-12-01
It is widely acknowledged that the large uncertainties in predictions of climate impact of linear contrails stem from inadequate parametrization of contrails in GCMs. But, the parameter space on which contrail dynamics and optical properties depend is very large and spanning it using high fidelity LES is prohibitively expensive. This study leverages the large dataset of LES done so far to understand the most important physical process that governs the evolution of contrails in different stages of its life and proposes a simple, low-cost and robust ODE model to capture the evolution of quantities of interest such as ice mass, vortex downwash and contrail cross-sectional dimensions. A direct consequence of modeling the contrail using parameters impacting the most important physical process is the reduction of the original parameter space to only those groupings of parameters that impact linear contrails independently. We are able to capture the most prominent features of the contrail at every stage of the life of the contrail - the induction of the jet exhaust by the trailing vortex pair, the vortex downwash and eventual destruction and the subsequent spreading of the contrail by ambient turbulence. A simplified version of GATOR-GCMOM - a GCM - is initialized using inputs from the new ODE model to test if the inclusion of the impact of the aforementioned parameter groups has significant persistent effects. Results from the GATOR-GCMOM box model calculations show which parameter groupings show persistent effects.
ATOPS B-737 inner-loop control system linear model construction and verification
NASA Technical Reports Server (NTRS)
Broussard, J. R.
1983-01-01
Nonlinear models and block diagrams of an inner-loop control system for the ATOPS B-737 Research Aircraft are presented. Continuous time linear model representations of the nonlinear inner-loop control systems are derived. Closed-loop aircraft simulations comparing nonlinear and linear dynamic responses to step inputs are used to verify the inner-loop control system models.
User's manual for interactive LINEAR: A FORTRAN program to derive linear aircraft models
NASA Technical Reports Server (NTRS)
Antoniewicz, Robert F.; Duke, Eugene L.; Patterson, Brian P.
1988-01-01
An interactive FORTRAN program that provides the user with a powerful and flexible tool for the linearization of aircraft aerodynamic models is documented in this report. The program LINEAR numerically determines a linear system model using nonlinear equations of motion and a user-supplied linear or nonlinear aerodynamic model. The nonlinear equations of motion used are six-degree-of-freedom equations with stationary atmosphere and flat, nonrotating earth assumptions. The system model determined by LINEAR consists of matrices for both the state and observation equations. The program has been designed to allow easy selection and definition of the state, control, and observation variables to be used in a particular model.
Estimating population trends with a linear model
Bart, J.; Collins, B.; Morrison, R.I.G.
2003-01-01
We describe a simple and robust method for estimating trends in population size. The method may be used with Breeding Bird Survey data, aerial surveys, point counts, or any other program of repeated surveys at permanent locations. Surveys need not be made at each location during each survey period. The method differs from most existing methods in being design based, rather than model based. The only assumptions are that the nominal sampling plan is followed and that sample size is large enough for use of the t-distribution. Simulations based on two bird data sets from natural populations showed that the point estimate produced by the linear model was essentially unbiased even when counts varied substantially and 25% of the complete data set was missing. The estimating-equation approach, often used to analyze Breeding Bird Survey data, performed similarly on one data set but had substantial bias on the second data set, in which counts were highly variable. The advantages of the linear model are its simplicity, flexibility, and that it is self-weighting. A user-friendly computer program to carry out the calculations is available from the senior author.
Linear modelling of attentional resource allocation
NASA Technical Reports Server (NTRS)
Pierce, B.
1978-01-01
Eight subjects time-shared performance of two compensatory tracking tasks under conditions when both were of constant difficulty, and when the control order of one task (designated primary) was varied over time within a trial. On line performance feedback was presented on half of the trials. The data are interpreted in terms of a linear model of the operator's attention allocation system, and suggest that this allocation is strongly suboptimal. Furthermore, the limitations in reallocating attentional resources between tasks, in response to difficulty fluctuations were not reduced by augmented performance feedback. Some characteristics of the allocation system are described, and reasons for its limitations suggested.
The Piece Wise Linear Reactive Flow Model
Vitello, P; Souers, P C
2005-08-18
For non-ideal explosives a wide range of behavior is observed in experiments dealing with differing sizes and geometries. A predictive detonation model must be able to reproduce many phenomena including such effects as: variations in the detonation velocity with the radial diameter of rate sticks; slowing of the detonation velocity around gentle corners; production of dead zones for abrupt corner turning; failure of small diameter rate sticks; and failure for rate sticks with sufficiently wide cracks. Most models have been developed to explain one effect at a time. Often, changes are made in the input parameters used to fit each succeeding case with the implication that this is sufficient for the model to be valid over differing regimes. We feel that it is important to develop a model that is able to fit experiments with one set of parameters. To address this we are creating a new generation of models that are able to produce better fitting to individual data sets than prior models and to simultaneous fit distinctly different regimes of experiments. Presented here are details of our new Piece Wise Linear reactive flow model applied to LX-17.
Continuous representation for shell models of turbulence
NASA Astrophysics Data System (ADS)
Mailybaev, Alexei A.
2015-07-01
In this work we construct and analyze continuous hydrodynamic models in one space dimension, which are induced by shell models of turbulence. After Fourier transformation, such continuous models split into an infinite number of uncoupled subsystems, which are all identical to the same shell model. The two shell models, which allow such a construction, are considered: the dyadic (Desnyansky-Novikov) model with the intershell ratio λ = 23/2 and the Sabra model of turbulence with λ = \\sqrt{2+\\sqrt{5}} ≈ 2.058 . The continuous models allow for understanding of various properties of shell model solutions and provide their interpretation in physical space. We show that the asymptotic solutions of the dyadic model with Kolmogorov scaling correspond to the shocks (discontinuities) for the induced continuous solutions in physical space, and the finite-time blowup together with its viscous regularization follow the scenario similar to the Burgers equation. For the Sabra model, we provide the physical space representation for blowup solutions and intermittent turbulent dynamics.
Model Selection with the Linear Mixed Model for Longitudinal Data
ERIC Educational Resources Information Center
Ryoo, Ji Hoon
2011-01-01
Model building or model selection with linear mixed models (LMMs) is complicated by the presence of both fixed effects and random effects. The fixed effects structure and random effects structure are codependent, so selection of one influences the other. Most presentations of LMM in psychology and education are based on a multilevel or…
Information metric from a linear sigma model.
Miyamoto, U; Yahikozawa, S
2012-05-01
The idea that a space-time metric emerges as a Fisher-Rao "information metric" of instanton moduli space has been examined in several field theories, such as the Yang-Mills theories and nonlinear σ models. In this paper, we report that the flat Euclidean or Minkowskian metric, rather than an anti-de Sitter metric that generically emerges from instanton moduli spaces, can be obtained as the Fisher-Rao metric from a nontrivial solution of the massive Klein-Gordon field (a linear σ model). This realization of the flat space from the simple field theory would be useful to investigate the ideas that relate the space-time geometry with the information geometry. PMID:23004729
NASA Astrophysics Data System (ADS)
Zhang, Yichen; Yu, Song; Guo, Hong
2015-11-01
We propose a modified no-switching continuous-variable quantum key distribution protocol by employing a practical noiseless linear amplifier at the receiver to increase the maximal transmission distance and tolerable excess noise. A security analysis is presented to derive the secure bound of the protocol in presence of a Gaussian noisy lossy channel. Simulation results show that the modified protocol can not only transmit longer distance and tolerate more channel excess noise than the original protocol, but also distribute more secure keys in the enhanced region where we define a critical point to separate the enhanced and degenerative region. This critical point presents the condition of using a practical noiseless linear amplifier in the no-switching continuous-variable quantum cryptography, which is meaningful and instructive to implement a practical experiment.
Meshless analysis of shear deformable shells: the linear model
NASA Astrophysics Data System (ADS)
Costa, Jorge C.; Tiago, Carlos M.; Pimenta, Paulo M.
2013-10-01
This work develops a kinematically linear shell model departing from a consistent nonlinear theory. The initial geometry is mapped from a flat reference configuration by a stress-free finite deformation, after which, the actual shell motion takes place. The model maintains the features of a complete stress-resultant theory with Reissner-Mindlin kinematics based on an inextensible director. A hybrid displacement variational formulation is presented, where the domain displacements and kinematic boundary reactions are independently approximated. The resort to a flat reference configuration allows the discretization using 2-D Multiple Fixed Least-Squares (MFLS) on the domain. The consistent definition of stress resultants and consequent plane stress assumption led to a neat formulation for the analysis of shells. The consistent linear approximation, combined with MFLS, made possible efficient computations with a desired continuity degree, leading to smooth results for the displacement, strain and stress fields, as shown by several numerical examples.
Modeling patterns in data using linear and related models
Engelhardt, M.E.
1996-06-01
This report considers the use of linear models for analyzing data related to reliability and safety issues of the type usually associated with nuclear power plants. The report discusses some of the general results of linear regression analysis, such as the model assumptions and properties of the estimators of the parameters. The results are motivated with examples of operational data. Results about the important case of a linear regression model with one covariate are covered in detail. This case includes analysis of time trends. The analysis is applied with two different sets of time trend data. Diagnostic procedures and tests for the adequacy of the model are discussed. Some related methods such as weighted regression and nonlinear models are also considered. A discussion of the general linear model is also included. Appendix A gives some basic SAS programs and outputs for some of the analyses discussed in the body of the report. Appendix B is a review of some of the matrix theoretic results which are useful in the development of linear models.
A unifying review of linear gaussian models.
Roweis, S; Ghahramani, Z
1999-02-15
Factor analysis, principal component analysis, mixtures of gaussian clusters, vector quantization, Kalman filter models, and hidden Markov models can all be unified as variations of unsupervised learning under a single basic generative model. This is achieved by collecting together disparate observations and derivations made by many previous authors and introducing a new way of linking discrete and continuous state models using a simple nonlinearity. Through the use of other nonlinearities, we show how independent component analysis is also a variation of the same basic generative model. We show that factor analysis and mixtures of gaussians can be implemented in autoencoder neural networks and learned using squared error plus the same regularization term. We introduce a new model for static data, known as sensible principal component analysis, as well as a novel concept of spatially adaptive observation noise. We also review some of the literature involving global and local mixtures of the basic models and provide pseudocode for inference and learning for all the basic models. PMID:9950734
Averaging models for linear piezostructural systems
NASA Astrophysics Data System (ADS)
Kim, W.; Kurdila, A. J.; Stepanyan, V.; Inman, D. J.; Vignola, J.
2009-03-01
In this paper, we consider a linear piezoelectric structure which employs a fast-switched, capacitively shunted subsystem to yield a tunable vibration absorber or energy harvester. The dynamics of the system is modeled as a hybrid system, where the switching law is considered as a control input and the ambient vibration is regarded as an external disturbance. It is shown that under mild assumptions of existence and uniqueness of the solution of this hybrid system, averaging theory can be applied, provided that the original system dynamics is periodic. The resulting averaged system is controlled by the duty cycle of a driven pulse-width modulated signal. The response of the averaged system approximates the performance of the original fast-switched linear piezoelectric system. It is analytically shown that the averaging approximation can be used to predict the electromechanically coupled system modal response as a function of the duty cycle of the input switching signal. This prediction is experimentally validated for the system consisting of a piezoelectric bimorph connected to an electromagnetic exciter. Experimental results show that the analytical predictions are observed in practice over a fixed "effective range" of switching frequencies. The same experiments show that the response of the switched system is insensitive to an increase in switching frequency above the effective frequency range.
Numerical linearized MHD model of flapping oscillations
NASA Astrophysics Data System (ADS)
Korovinskiy, D. B.; Ivanov, I. B.; Semenov, V. S.; Erkaev, N. V.; Kiehas, S. A.
2016-06-01
Kink-like magnetotail flapping oscillations in a Harris-like current sheet with earthward growing normal magnetic field component Bz are studied by means of time-dependent 2D linearized MHD numerical simulations. The dispersion relation and two-dimensional eigenfunctions are obtained. The results are compared with analytical estimates of the double-gradient model, which are found to be reliable for configurations with small Bz up to values ˜ 0.05 of the lobe magnetic field. Coupled with previous results, present simulations confirm that the earthward/tailward growth direction of the Bz component acts as a switch between stable/unstable regimes of the flapping mode, while the mode dispersion curve is the same in both cases. It is confirmed that flapping oscillations may be triggered by a simple Gaussian initial perturbation of the Vz velocity.
Testing Linear Models for Ability Parameters in Item Response Models
ERIC Educational Resources Information Center
Glas, Cees A. W.; Hendrawan, Irene
2005-01-01
Methods for testing hypotheses concerning the regression parameters in linear models for the latent person parameters in item response models are presented. Three tests are outlined: A likelihood ratio test, a Lagrange multiplier test and a Wald test. The tests are derived in a marginal maximum likelihood framework. They are explicitly formulated…
ERIC Educational Resources Information Center
Kane, Michael T.; Mroch, Andrew A.; Suh, Youngsuk; Ripkey, Douglas R.
2009-01-01
This paper analyzes five linear equating models for the "nonequivalent groups with anchor test" (NEAT) design with internal anchors (i.e., the anchor test is part of the full test). The analysis employs a two-dimensional framework. The first dimension contrasts two general approaches to developing the equating relationship. Under a "parameter…
Robust coarticulatory modeling for continuous speech recognition
NASA Astrophysics Data System (ADS)
Schwartz, R.; Chow, Y. L.; Dunham, M. O.; Kimball, O.; Krasner, M.; Kubala, F.; Makhoul, J.; Price, P.; Roucos, S.
1986-10-01
The purpose of this project is to perform research into algorithms for the automatic recognition of individual sounds or phonemes in continuous speech. The algorithms developed should be appropriate for understanding large-vocabulary continuous speech input and are to be made available to the Strategic Computing Program for incorporation in a complete word recognition system. This report describes process to date in developing phonetic models that are appropriate for continuous speech recognition. In continuous speech, the acoustic realization of each phoneme depends heavily on the preceding and following phonemes: a process known as coarticulation. Thus, while there are relatively few phonemes in English (on the order of fifty or so), the number of possible different accoustic realizations is in the thousands. Therefore, to develop high-accuracy recognition algorithms, one may need to develop literally thousands of relatively distance phonetic models to represent the various phonetic context adequately. Developing a large number of models usually necessitates having a large amount of speech to provide reliable estimates of the model parameters. The major contributions of this work are the development of: (1) A simple but powerful formalism for modeling phonemes in context; (2) Robust training methods for the reliable estimation of model parameters by utilizing the available speech training data in a maximally effective way; and (3) Efficient search strategies for phonetic recognition while maintaining high recognition accuracy.
Piecewise Linear-Linear Latent Growth Mixture Models with Unknown Knots
ERIC Educational Resources Information Center
Kohli, Nidhi; Harring, Jeffrey R.; Hancock, Gregory R.
2013-01-01
Latent growth curve models with piecewise functions are flexible and useful analytic models for investigating individual behaviors that exhibit distinct phases of development in observed variables. As an extension of this framework, this study considers a piecewise linear-linear latent growth mixture model (LGMM) for describing segmented change of…
Downward continuation methods for gravimetric geoid modelling
NASA Astrophysics Data System (ADS)
Huang, J.; Véronneau, M.
2003-04-01
The determination of a gravimetric geoid model based on the Stokes integral requires that gravity anomalies must be on the geoid and that the anomalous potential must be harmonic above the geoid. To fulfill these requirements, gravity observations (or gravity anomalies) collected on the surface of the Earth need to be reduced to the geoid by a) removing the masses above the geoid and compensating for this removal; and b) continuing the gravity anomalies downward to the geoid. A well-known case is the determination of the Helmert gravity anomalies on the geoid in terms of Helmert's 2nd condensation method (e.g. Martinec et al. 1993). There are two procedures to follow for the evaluation of the Helmert gravity anomalies on the geoid: a) the Helmert gravity anomalies are evaluated on the irregular Earth surface, then are continued downward to the geoid, i.e., masses above the geoid are removed and restored as a condensed layer on the geoid prior to the downward continuation; b) alternatively the refined Bouguer anomalies on the surface of the Earth are downward-continued to the geoid, then the Helmert gravity anomalies are evaluated on the geoid, i.e., the condensed masses are restored after the downward continuation. Both procedures are theoretically equivalent (Huang et al. 2002a). In theory, the inclusion of the downward continuation should improve the geoid regardless of the approach chosen. However, different authors arrive at contradictory conclusions pertaining to its applications (e.g. Pavlis 1998; Ardalan 2000; Jekili and Serpas 2002; Véronneau and Huang 2002). This raises an open question as to how researchers should evaluate the downward continuation in order to improve geoid modeling. In this research, the two procedures described above are used to determine the geoid in Canada. The downward continuations are evaluated using the Poisson and Moritz methods (e.g. Moritz 1980; Sideris 1988; Vanícek et al. 1996; Martinec 1996; Sjöberg 1998; Nahavandchi 2000
Linear functional minimization for inverse modeling
NASA Astrophysics Data System (ADS)
Barajas-Solano, D. A.; Wohlberg, B. E.; Vesselinov, V. V.; Tartakovsky, D. M.
2015-06-01
We present a novel inverse modeling strategy to estimate spatially distributed parameters of nonlinear models. The maximum a posteriori (MAP) estimators of these parameters are based on a likelihood functional, which contains spatially discrete measurements of the system parameters and spatiotemporally discrete measurements of the transient system states. The piecewise continuity prior for the parameters is expressed via Total Variation (TV) regularization. The MAP estimator is computed by minimizing a nonquadratic objective equipped with the TV operator. We apply this inversion algorithm to estimate hydraulic conductivity of a synthetic confined aquifer from measurements of conductivity and hydraulic head. The synthetic conductivity field is composed of a low-conductivity heterogeneous intrusion into a high-conductivity heterogeneous medium. Our algorithm accurately reconstructs the location, orientation, and extent of the intrusion from the steady-state data only. Addition of transient measurements of hydraulic head improves the parameter estimation, accurately reconstructing the conductivity field in the vicinity of observation locations.
Non linear behaviour of cell tensegrity models
NASA Astrophysics Data System (ADS)
Alippi, A.; Bettucci, A.; Biagioni, A.; Conclusio, D.; D'Orazio, A.; Germano, M.; Passeri, D.
2012-05-01
Tensegrity models for the cytoskeleton structure of living cells is largely used nowadays for interpreting the biochemical response of living tissues to mechanical stresses. Microtubules, microfilaments and filaments are the microscopic cell counterparts of struts (microtubules) and cables (microfilaments and filaments) in the macroscopic world: the formers oppose to compression, the latters to tension, thus yielding an overall structure, light and highly deformable. Specific cell surface receptors, such as integrins, act as the coupling elements that transmit the outside mechanical stress state into the cell body. Reversible finite deformations of tensegrity structures have been widely demonstrated experimentally and in a number of living cell simulations. In the present paper, the bistability behaviour of two general models, the linear bar oscillator and the icosahedron, is studied, as they are both obtained from mathematical simulation, the former, and from larger scale experiments, the latter. The discontinuity in the frequency response of the oscillation amplitude and the lateral bending of the resonance curves are put in evidence, as it grows larger as the driving amplitude increases, respectively.
NASA Astrophysics Data System (ADS)
Guo, Ying; Lv, Geli; Zeng, Guihua
2015-11-01
We show that the tolerable excess noise can be dynamically balanced in source preparation while inserting a tunable linear optics cloning machine (LOCM) for balancing the secret key rate and the maximal transmission distance of continuous-variable quantum key distribution (CVQKD). The intensities of source noise are sensitive to the tunable LOCM and can be stabilized to the suitable values to eliminate the impact of channel noise and defeat the potential attacks even in the case of the degenerated linear optics amplifier (LOA). The LOCM-additional noise can be elegantly employed by the reference partner of reconciliation to regulate the secret key rate and the transmission distance. Simulation results show that there is a considerable improvement in the secret key rate of the LOCM-based CVQKD while providing a tunable LOCM for source preparation with the specified parameters in suitable ranges.
NASA Astrophysics Data System (ADS)
You, Dae-Joon; Lee, Sung-Ho; Jang, Seok-Myeong
2008-04-01
In the case of the manufactured linear permanent magnet synchronous machines (PMLSMs), dynamic range evaluation for system efficiency and performance limits is difficult to accomplish because of the moving length restriction with mover and the absence of interface between the design field and control field. To solve this problem, this paper presents a dynamic analysis based on design parameters by magnetic field analysis of the linear PM machine. And then, maximum operating range of the system is estimated considering the control method of a fixed dc-link voltage of the inverter. This analysis is verified from the dynamic experiments through continuous progressive motion of the manufactured disk-type PMLSM by current control.
Two fusion predictors for continuous-time linear systems with different types of observations
NASA Astrophysics Data System (ADS)
Song, Haryong; Lee, Kyung Min; Shin, Vladimir
2012-01-01
This article proposes new fusion predictors for continuous-time linear systems with different types of observations. The fusion predictors are formed by the summation of the local Kalman estimators (filters and predictors) with matrix weights depending only on time instants. Both fusion predictors represent the optimal linear combination of an arbitrary number of local Kalman estimators and each is fused by the minimum mean square error criterion. As a consequence of the parallel structure of the proposed predictors, parallel computers can be used for their design. This article also establishes the relationship between fusion predictors. High accuracy and computational efficiency of the fusion predictors are demonstrated through several examples, including the damper harmonic oscillator motion with a multisensory environment.
NASA Astrophysics Data System (ADS)
Benavides, A.; Everett, M. E.
2007-03-01
This work adopts a continuation approach, based on path tracking in model space, to solve the non-linear least-squares problem for discrimination of unexploded ordnance (UXO) using multi-receiver electromagnetic induction (EMI) data. The forward model corresponds to a stretched-exponential decay of eddy currents induced in a magnetic spheroid. We formulate an over-determined, or under-parameterized, inverse problem. An example using synthetic multi-receiver EMI responses illustrates the efficiency of the method. The fast inversion of actual field multi-receiver EMI responses of inert, buried ordnances is also shown. Software based on the continuation method could be installed within a multi-receiver EMI sensor and used for near-real-time UXO decision-making purposes without the need for a highly-trained operator.
Controlling Continuous-Variable Quantum Key Distribution with Tuned Linear Optics Cloning Machines
NASA Astrophysics Data System (ADS)
Guo, Ying; Qiu, Deli; Huang, Peng; Zeng, Guihua
2015-09-01
We show that the tolerable excess noise can be elegantly controlled while inserting a tunable linear optics cloning machine (LOCM) for continuous-variable key distribution (CVQKD). The LOCM-tuned noise can be stabilized to an optimal value by the reference partner of reconciliation to guarantee the high secret key rate. Simulation results show that there is a considerable improvement of the performance for the LOCM-based CVQKD protocol in terms of the secret rate while making a fine balance between the secret key rate and the transmission distance with the dynamically tuned parameters in suitable ranges.
A FORTRAN program for the analysis of linear continuous and sample-data systems
NASA Technical Reports Server (NTRS)
Edwards, J. W.
1976-01-01
A FORTRAN digital computer program which performs the general analysis of linearized control systems is described. State variable techniques are used to analyze continuous, discrete, and sampled data systems. Analysis options include the calculation of system eigenvalues, transfer functions, root loci, root contours, frequency responses, power spectra, and transient responses for open- and closed-loop systems. A flexible data input format allows the user to define systems in a variety of representations. Data may be entered by inputing explicit data matrices or matrices constructed in user written subroutines, by specifying transfer function block diagrams, or by using a combination of these methods.
Linearized Functional Minimization for Inverse Modeling
Wohlberg, Brendt; Tartakovsky, Daniel M.; Dentz, Marco
2012-06-21
Heterogeneous aquifers typically consist of multiple lithofacies, whose spatial arrangement significantly affects flow and transport. The estimation of these lithofacies is complicated by the scarcity of data and by the lack of a clear correlation between identifiable geologic indicators and attributes. We introduce a new inverse-modeling approach to estimate both the spatial extent of hydrofacies and their properties from sparse measurements of hydraulic conductivity and hydraulic head. Our approach is to minimize a functional defined on the vectors of values of hydraulic conductivity and hydraulic head fields defined on regular grids at a user-determined resolution. This functional is constructed to (i) enforce the relationship between conductivity and heads provided by the groundwater flow equation, (ii) penalize deviations of the reconstructed fields from measurements where they are available, and (iii) penalize reconstructed fields that are not piece-wise smooth. We develop an iterative solver for this functional that exploits a local linearization of the mapping from conductivity to head. This approach provides a computationally efficient algorithm that rapidly converges to a solution. A series of numerical experiments demonstrates the robustness of our approach.
Continuous utility factor in segregation models
NASA Astrophysics Data System (ADS)
Roy, Parna; Sen, Parongama
2016-02-01
We consider the constrained Schelling model of social segregation in which the utility factor of agents strictly increases and nonlocal jumps of the agents are allowed. In the present study, the utility factor u is defined in a way such that it can take continuous values and depends on the tolerance threshold as well as the fraction of unlike neighbors. Two models are proposed: in model A the jump probability is determined by the sign of u only, which makes it equivalent to the discrete model. In model B the actual values of u are considered. Model A and model B are shown to differ drastically as far as segregation behavior and phase transitions are concerned. In model A, although segregation can be achieved, the cluster sizes are rather small. Also, a frozen state is obtained in which steady states comprise many unsatisfied agents. In model B, segregated states with much larger cluster sizes are obtained. The correlation function is calculated to show quantitatively that larger clusters occur in model B. Moreover for model B, no frozen states exist even for very low dilution and small tolerance parameter. This is in contrast to the unconstrained discrete model considered earlier where agents can move even when utility remains the same. In addition, we also consider a few other dynamical aspects which have not been studied in segregation models earlier.
Stochastic string models with continuous semimartingales
NASA Astrophysics Data System (ADS)
Bueno-Guerrero, Alberto; Moreno, Manuel; Navas, Javier F.
2015-09-01
This paper reformulates the stochastic string model of Santa-Clara and Sornette using stochastic calculus with continuous semimartingales. We present some new results, such as: (a) the dynamics of the short-term interest rate, (b) the PDE that must be satisfied by the bond price, and (c) an analytic expression for the price of a European bond call option. Additionally, we clarify some important features of the stochastic string model and show its relevance to price derivatives and the equivalence with an infinite dimensional HJM model to price European options.
Modeling of continuous strip production by rheocasting
Matsumiya, T.; Flemings, M.C.
1981-03-01
A process was experimentally and mathematically modeled for continuous and direct production of metal strip from its molten state by the use of Rheocasting. The process comprises 1) continuous production of a Rheocast semisolid alloy, and 2) direct shaping of the semisolid into strip. Sn-15 pct Pb was used as the modeling alloy. Crack formation and surface quality of the strip produced depend on fraction solid and deformation force. Continuous, sound strip could be obtained with good surface quality when fraction solid was between 0.50 and 0.70 and deformation force did not exceed a given maximum. Sheet thickness depends on deformation force, fraction solid, rotor rate of Rheocaster and production line speed. At constant deformation force, sheet thickness increases as fraction solid increases, rotor rate decreases and line speed is reduced. Sheet thickness is larger in the center than in the edge, but the difference is reduced by applying edgers. Some segregation of lead toward the edges is observed, ad the segregation increases as amount of deformation is increased. A mathematical model for heat flow, solidification and deformation was constructed. The model predicts the point of completion of solidification in the strip and sheet thickness as a function of deformation force and line speed. Calculations are in good agreement with experimental results.
Continuous multifractal models with zero values: a continuous \\beta -multifractal model
NASA Astrophysics Data System (ADS)
Schmitt, F. G.
2014-02-01
In this paper we propose for the first time a multiplicative continuous model for generating multifractal fields with zero values, as a continuous generalization of the intermittent lognormal \\beta -model proposed by Over and Gupta (1996). It is built using infinitely multiplicative random variables, the multiplicative analog to infinitely divisible distributions for addition. The model also needs stochastic multiplicative measures and multiplicative stochastic integrals. It possesses as a special case a continuous generalization of the classical discrete \\beta -model. Applications are numerous in many fields of applied science, including small-scale rainfall and soil science.
Continuous-time discrete-space models for animal movement
Hanks, Ephraim M.; Hooten, Mevin B.; Alldredge, Mat W.
2015-01-01
The processes influencing animal movement and resource selection are complex and varied. Past efforts to model behavioral changes over time used Bayesian statistical models with variable parameter space, such as reversible-jump Markov chain Monte Carlo approaches, which are computationally demanding and inaccessible to many practitioners. We present a continuous-time discrete-space (CTDS) model of animal movement that can be fit using standard generalized linear modeling (GLM) methods. This CTDS approach allows for the joint modeling of location-based as well as directional drivers of movement. Changing behavior over time is modeled using a varying-coefficient framework which maintains the computational simplicity of a GLM approach, and variable selection is accomplished using a group lasso penalty. We apply our approach to a study of two mountain lions (Puma concolor) in Colorado, USA.
NASA Astrophysics Data System (ADS)
Batt, Gregory S.; Gibert, James M.; Daqaq, Mohammed
2015-08-01
In this paper, the free and forced vibration response of a linearized, distributed-parameter model of a viscoelastic rod with an applied tip-mass is investigated. A nonlinear model is developed from constitutive relations and is linearized about a static equilibrium position for analysis. A classical Maxwell-Weichert model, represented via a Prony series, is used to model the viscoelastic system. The exact solution to both the free and forced vibration problem is derived and used to study the behavior of an idealized packaging system containing Nova Chemicals' Arcel® foam. It is observed that, although three Prony series terms are deemed sufficient to fit the static test data, convergence of the dynamic response and study of the storage and loss modulii necessitate the use of additional Prony series terms. It is also shown that the model is able to predict the modal frequencies and the primary resonance response at low acceleration excitation, both with reasonable accuracy given the non-homogeneity and density variation observed in the specimens. Higher acceleration inputs result in softening nonlinear responses highlighting the need for a nonlinear elastic model that extends beyond the scope of this work. Solution analysis and experimental data indicate little material vibration energy dissipation close to the first modal frequency of the mass/rod system.
Fault diagnosis based on continuous simulation models
NASA Technical Reports Server (NTRS)
Feyock, Stefan
1987-01-01
The results are described of an investigation of techniques for using continuous simulation models as basis for reasoning about physical systems, with emphasis on the diagnosis of system faults. It is assumed that a continuous simulation model of the properly operating system is available. Malfunctions are diagnosed by posing the question: how can we make the model behave like that. The adjustments that must be made to the model to produce the observed behavior usually provide definitive clues to the nature of the malfunction. A novel application of Dijkstra's weakest precondition predicate transformer is used to derive the preconditions for producing the required model behavior. To minimize the size of the search space, an envisionment generator based on interval mathematics was developed. In addition to its intended application, the ability to generate qualitative state spaces automatically from quantitative simulations proved to be a fruitful avenue of investigation in its own right. Implementations of the Dijkstra transform and the envisionment generator are reproduced in the Appendix.
Mathematical Models of Continuous Flow Electrophoresis
NASA Technical Reports Server (NTRS)
Saville, D. A.; Snyder, R. S.
1985-01-01
Development of high resolution continuous flow electrophoresis devices ultimately requires comprehensive understanding of the ways various phenomena and processes facilitate or hinder separation. A comprehensive model of the actual three dimensional flow, temperature and electric fields was developed to provide guidance in the design of electrophoresis chambers for specific tasks and means of interpreting test data on a given chamber. Part of the process of model development includes experimental and theoretical studies of hydrodynamic stability. This is necessary to understand the origin of mixing flows observed with wide gap gravitational effects. To insure that the model accurately reflects the flow field and particle motion requires extensive experimental work. Another part of the investigation is concerned with the behavior of concentrated sample suspensions with regard to sample stream stability particle-particle interactions which might affect separation in an electric field, especially at high field strengths. Mathematical models will be developed and tested to establish the roles of the various interactions.
Equivalent linear damping characterization in linear and nonlinear force-stiffness muscle models.
Ovesy, Marzieh; Nazari, Mohammad Ali; Mahdavian, Mohammad
2016-02-01
In the current research, the muscle equivalent linear damping coefficient which is introduced as the force-velocity relation in a muscle model and the corresponding time constant are investigated. In order to reach this goal, a 1D skeletal muscle model was used. Two characterizations of this model using a linear force-stiffness relationship (Hill-type model) and a nonlinear one have been implemented. The OpenSim platform was used for verification of the model. The isometric activation has been used for the simulation. The equivalent linear damping and the time constant of each model were extracted by using the results obtained from the simulation. The results provide a better insight into the characteristics of each model. It is found that the nonlinear models had a response rate closer to the reality compared to the Hill-type models. PMID:26837750
Modeling Pan Evaporation for Kuwait by Multiple Linear Regression
Almedeij, Jaber
2012-01-01
Evaporation is an important parameter for many projects related to hydrology and water resources systems. This paper constitutes the first study conducted in Kuwait to obtain empirical relations for the estimation of daily and monthly pan evaporation as functions of available meteorological data of temperature, relative humidity, and wind speed. The data used here for the modeling are daily measurements of substantial continuity coverage, within a period of 17 years between January 1993 and December 2009, which can be considered representative of the desert climate of the urban zone of the country. Multiple linear regression technique is used with a procedure of variable selection for fitting the best model forms. The correlations of evaporation with temperature and relative humidity are also transformed in order to linearize the existing curvilinear patterns of the data by using power and exponential functions, respectively. The evaporation models suggested with the best variable combinations were shown to produce results that are in a reasonable agreement with observation values. PMID:23226984
Solidification modeling of continuous casting process
NASA Astrophysics Data System (ADS)
Lerner, V. S.; Lerner, Y. S.
2005-04-01
The aim of the present work was to utilize a new systematic mathematical-informational approach based on informational macrodynamics (IMD) to model and optimize the casting process, taking as an example horizontal continuous casting (HCC). The IMD model takes into account the interrelated thermal, diffusion, kinetic, hydrodynamic, and mechanical effects that are essential for the given casting process. The optimum technological process parameters are determined by the simultaneous solution of problems of identification and optimal control. The control functions of the synthesized optimal model are found from the extremum of the entropy functional having a particular sense of an integrated assessment of the continuous cast bar physicochemical properties. For the physical system considered, the IMD structures of the optimal model are connected with controllable equations of nonequilibrium thermodynamics. This approach was applied to the HCC of ductile iron, and the results were compared with experimental data and numerical simulation. Good agreement was confirmed between the predicted and practical data, as well as between new and traditional methods.
Recent Updates to the GEOS-5 Linear Model
NASA Technical Reports Server (NTRS)
Holdaway, Dan; Kim, Jong G.; Errico, Ron; Gelaro, Ronald; Mahajan, Rahul
2014-01-01
Global Modeling and Assimilation Office (GMAO) is close to having a working 4DVAR system and has developed a linearized version of GEOS-5.This talk outlines a series of improvements made to the linearized dynamics, physics and trajectory.Of particular interest is the development of linearized cloud microphysics, which provides the framework for 'all-sky' data assimilation.
NASA Astrophysics Data System (ADS)
Zhou, Jun; Lu, Xinbiao; Qian, Huimin
2016-09-01
The paper reports interesting but unnoticed facts about irreducibility (resp., reducibility) of Flouqet factorisations and their harmonic implication in term of controllability in finite-dimensional linear continuous-time periodic (FDLCP) systems. Reducibility and irreducibility are attributed to matrix logarithm algorithms during computing Floquet factorisations in FDLCP systems, which are a pair of essential features but remain unnoticed in the Floquet theory so far. The study reveals that reducible Floquet factorisations may bring in harmonic waves variance into the Fourier analysis of FDLCP systems that in turn may alter our interpretation of controllability when the Floquet factors are used separately during controllability testing; namely, controllability interpretation discrepancy (or simply, controllability discrepancy) may occur and must be examined whenever reducible Floquet factorisations are involved. On the contrary, when irreducible Floquet factorisations are employed, controllability interpretation discrepancy can be avoided. Examples are included to illustrate such observations.
Rakheja, S; Gurram, R; Gouw, G J
1993-10-01
Hand-arm vibration (HAV) models serve as an effective tool to assess the vibration characteristics of the hand-tool system and to evaluate the attenuation performance of vibration isolation mechanisms. This paper describes a methodology to identify the parameters of HAV models, whether linear or nonlinear, using mechanical impedance data and a nonlinear programming based optimization technique. Three- and four-degrees-of-freedom (DOF) linear, piecewise linear and nonlinear HAV models are formulated and analyzed to yield impedance characteristics in the 5-1000 Hz frequency range. A local equivalent linearization algorithm, based upon the principle of energy similarity, is implemented to simulate the nonlinear HAV models. Optimization methods are employed to identify the model parameters, such that the magnitude and phase errors between the computed and measured impedance characteristics are minimum in the entire frequency range. The effectiveness of the proposed method is demonstrated through derivations of models that correlate with the measured X-axis impedance characteristics of the hand-arm system, proposed by ISO. The results of the study show that a linear model cannot predict the impedance characteristics in the entire frequency range, while a piecewise linear model yields an accurate estimation. PMID:8253830
Liu, Jian; Miller, William H.
2008-08-01
The maximum entropy analytic continuation (MEAC) method is used to extend the range of accuracy of the linearized semiclassical initial value representation (LSC-IVR)/classical Wigner approximation for real time correlation functions. The LSC-IVR provides a very effective 'prior' for the MEAC procedure since it is very good for short times, exact for all time and temperature for harmonic potentials (even for correlation functions of nonlinear operators), and becomes exact in the classical high temperature limit. This combined MEAC+LSC/IVR approach is applied here to two highly nonlinear dynamical systems, a pure quartic potential in one dimensional and liquid para-hydrogen at two thermal state points (25K and 14K under nearly zero external pressure). The former example shows the MEAC procedure to be a very significant enhancement of the LSC-IVR, for correlation functions of both linear and nonlinear operators, and especially at low temperature where semiclassical approximations are least accurate. For liquid para-hydrogen, the LSC-IVR is seen already to be excellent at T = 25K, but the MEAC procedure produces a significant correction at the lower temperature (T = 14K). Comparisons are also made to how the MEAC procedure is able to provide corrections for other trajectory-based dynamical approximations when used as priors.
Linear motor drive system for continuous-path closed-loop position control of an object
Barkman, William E.
1980-01-01
A precision numerical controlled servo-positioning system is provided for continuous closed-loop position control of a machine slide or platform driven by a linear-induction motor. The system utilizes filtered velocity feedback to provide system stability required to operate with a system gain of 100 inches/minute/0.001 inch of following error. The filtered velocity feedback signal is derived from the position output signals of a laser interferometer utilized to monitor the movement of the slide. Air-bearing slides mounted to a stable support are utilized to minimize friction and small irregularities in the slideway which would tend to introduce positioning errors. A microprocessor is programmed to read command and feedback information and converts this information into the system following error signal. This error signal is summed with the negative filtered velocity feedback signal at the input of a servo amplifier whose output serves as the drive power signal to the linear motor position control coil.
Linear and Nonlinear Models of Agenda Setting in Television.
ERIC Educational Resources Information Center
Brosius, Hans-Bernd; Kepplinger, Hans Mathias
1992-01-01
A content analysis of major German television news shows and 53 weekly surveys on 16 issues were used to compare linear and nonlinear models as ways to describe the relationship between media coverage and the public agenda. Results indicate that nonlinear models are in some cases superior to linear models in terms of explained variance. (34…
Tried and True: Springing into Linear Models
ERIC Educational Resources Information Center
Darling, Gerald
2012-01-01
In eighth grade, students usually learn about forces in science class and linear relationships in math class, crucial topics that form the foundation for further study in science and engineering. An activity that links these two fundamental concepts involves measuring the distance a spring stretches as a function of how much weight is suspended…
Three-Dimensional Modeling in Linear Regression.
ERIC Educational Resources Information Center
Herman, James D.
Linear regression examines the relationship between one or more independent (predictor) variables and a dependent variable. By using a particular formula, regression determines the weights needed to minimize the error term for a given set of predictors. With one predictor variable, the relationship between the predictor and the dependent variable…
An analytically linearized helicopter model with improved modeling accuracy
NASA Technical Reports Server (NTRS)
Jensen, Patrick T.; Curtiss, H. C., Jr.; Mckillip, Robert M., Jr.
1991-01-01
An analytically linearized model for helicopter flight response including rotor blade dynamics and dynamic inflow, that was recently developed, was studied with the objective of increasing the understanding, the ease of use, and the accuracy of the model. The mathematical model is described along with a description of the UH-60A Black Hawk helicopter and flight test used to validate the model. To aid in utilization of the model for sensitivity analysis, a new, faster, and more efficient implementation of the model was developed. It is shown that several errors in the mathematical modeling of the system caused a reduction in accuracy. These errors in rotor force resolution, trim force and moment calculation, and rotor inertia terms were corrected along with improvements to the programming style and documentation. Use of a trim input file to drive the model is examined. Trim file errors in blade twist, control input phase angle, coning and lag angles, main and tail rotor pitch, and uniform induced velocity, were corrected. Finally, through direct comparison of the original and corrected model responses to flight test data, the effect of the corrections on overall model output is shown.
Development of a Linear Stirling Model with Varying Heat Inputs
NASA Technical Reports Server (NTRS)
Regan, Timothy F.; Lewandowski, Edward J.
2007-01-01
The linear model of the Stirling system developed by NASA Glenn Research Center (GRC) has been extended to include a user-specified heat input. Previously developed linear models were limited to the Stirling convertor and electrical load. They represented the thermodynamic cycle with pressure factors that remained constant. The numerical values of the pressure factors were generated by linearizing GRC s non-linear System Dynamic Model (SDM) of the convertor at a chosen operating point. The pressure factors were fixed for that operating point, thus, the model lost accuracy if a transition to a different operating point were simulated. Although the previous linear model was used in developing controllers that manipulated current, voltage, and piston position, it could not be used in the development of control algorithms that regulated hot-end temperature. This basic model was extended to include the thermal dynamics associated with a hot-end temperature that varies over time in response to external changes as well as to changes in the Stirling cycle. The linear model described herein includes not only dynamics of the piston, displacer, gas, and electrical circuit, but also the transient effects of the heater head thermal inertia. The linear version algebraically couples two separate linear dynamic models, one model of the Stirling convertor and one model of the thermal system, through the pressure factors. The thermal system model includes heat flow of heat transfer fluid, insulation loss, and temperature drops from the heat source to the Stirling convertor expansion space. The linear model was compared to a nonlinear model, and performance was very similar. The resulting linear model can be implemented in a variety of computing environments, and is suitable for analysis with classical and state space controls analysis techniques.
Descriptive Linear modeling of steady-state visual evoked response
NASA Technical Reports Server (NTRS)
Levison, W. H.; Junker, A. M.; Kenner, K.
1986-01-01
A study is being conducted to explore use of the steady state visual-evoke electrocortical response as an indicator of cognitive task loading. Application of linear descriptive modeling to steady state Visual Evoked Response (VER) data is summarized. Two aspects of linear modeling are reviewed: (1) unwrapping the phase-shift portion of the frequency response, and (2) parsimonious characterization of task-loading effects in terms of changes in model parameters. Model-based phase unwrapping appears to be most reliable in applications, such as manual control, where theoretical models are available. Linear descriptive modeling of the VER has not yet been shown to provide consistent and readily interpretable results.
Modeling interdependent animal movement in continuous time.
Niu, Mu; Blackwell, Paul G; Skarin, Anna
2016-06-01
This article presents a new approach to modeling group animal movement in continuous time. The movement of a group of animals is modeled as a multivariate Ornstein Uhlenbeck diffusion process in a high-dimensional space. Each individual of the group is attracted to a leading point which is generally unobserved, and the movement of the leading point is also an Ornstein Uhlenbeck process attracted to an unknown attractor. The Ornstein Uhlenbeck bridge is applied to reconstruct the location of the leading point. All movement parameters are estimated using Markov chain Monte Carlo sampling, specifically a Metropolis Hastings algorithm. We apply the method to a small group of simultaneously tracked reindeer, Rangifer tarandus tarandus, showing that the method detects dependency in movement between individuals. PMID:26812666
Rabbit models for continuous curvilinear capsulorhexis instruction
Ruggiero, Jason; Keller, Christopher; Porco, Travis; Naseri, Ayman; Sretavan, David W.
2012-01-01
PURPOSE To develop a rabbit model for continuous curvilinear capsulorhexis (CCC) instruction. SETTING University of California San Francisco, San Francisco, California, USA. DESIGN Experimental study. METHODS Isolated rabbit lenses were immersed in 2% to 8% paraformaldehyde (PFA) fixative from 15 minutes to 6 hours. Rabbit eyes were treated by substituting aqueous with 2% to 4% PFA for 30 minutes to 6 hours, followed by washes with a balanced salt solution. Treated lenses and eyes were held in purpose-designed holders using vacuum. A panel of 6 cataract surgeons with 5 to 15 years of experience performed CCC on treated lenses and eyes and responded to a questionnaire regarding the utility of these models for resident teaching using a 5-item Likert scale. RESULTS The expert panel found that rabbit lenses treated with increasing amounts of fixative simulated CCC on human lens capsules from the third to the seventh decade of life. The panel also found fixative-treated rabbit eyes to simulate some of the experience of CCC within the human anterior chamber but noted a shallower anterior chamber depth, variation in pupil size, and corneal clouding under some treatment conditions. CONCLUSIONS Experienced cataract surgeons who performed CCC on these rabbit models strongly agreed that isolated rabbit lenses treated with fixative provide a realistic simulation of CCC in human patients and that both models were useful tools for capsulorhexis instruction. Results indicate that rabbit lenses treated with 8% PFA for 15 minutes is a model with good fidelity for CCC training. PMID:22727296
ERIC Educational Resources Information Center
Wang, Tianyou
2008-01-01
Von Davier, Holland, and Thayer (2004) laid out a five-step framework of test equating that can be applied to various data collection designs and equating methods. In the continuization step, they presented an adjusted Gaussian kernel method that preserves the first two moments. This article proposes an alternative continuization method that…
Topology changing transitions in supersymmetric linear σ-models
NASA Astrophysics Data System (ADS)
Ryang, Shijong
1995-02-01
We analyze the two-dimensional supersymmetric linear σ-model with U(1) gauge symmetries that includes a Calabi-Yau phase and a possible Landau-Ginzburg phase. We demonstrate the topology changing transitions among the generic vacua of various linear σ-models. In the supersymmetric transition the determinantal contraction naturally arises.
Response of a rotorcraft model with damping non-linearities
NASA Astrophysics Data System (ADS)
Tongue, B. H.
1985-11-01
The linearized equations of motion of a helicopter in contact with the ground have solutions which can be linearly stable or unstable, depending on the system parameters. The present study includes physical non-linearities in the helicopter model. This allows one to determine if a steady-state response exists and, if so, what the frequency and amplitude of the oscillations will be. In this way, one can determine how serious the linearly unstable operating regime is and whether destructive oscillations are possible when the system is in the linearly stable regime. The present analysis applies to helicopters having fully articulated rotors.
A linear model of population dynamics
NASA Astrophysics Data System (ADS)
Lushnikov, A. A.; Kagan, A. I.
2016-08-01
The Malthus process of population growth is reformulated in terms of the probability w(n,t) to find exactly n individuals at time t assuming that both the birth and the death rates are linear functions of the population size. The master equation for w(n,t) is solved exactly. It is shown that w(n,t) strongly deviates from the Poisson distribution and is expressed in terms either of Laguerre’s polynomials or a modified Bessel function. The latter expression allows for considerable simplifications of the asymptotic analysis of w(n,t).
Employment of CB models for non-linear dynamic analysis
NASA Technical Reports Server (NTRS)
Klein, M. R. M.; Deloo, P.; Fournier-Sicre, A.
1990-01-01
The non-linear dynamic analysis of large structures is always very time, effort and CPU consuming. Whenever possible the reduction of the size of the mathematical model involved is of main importance to speed up the computational procedures. Such reduction can be performed for the part of the structure which perform linearly. Most of the time, the classical Guyan reduction process is used. For non-linear dynamic process where the non-linearity is present at interfaces between different structures, Craig-Bampton models can provide a very rich information, and allow easy selection of the relevant modes with respect to the phenomenon driving the non-linearity. The paper presents the employment of Craig-Bampton models combined with Newmark direct integration for solving non-linear friction problems appearing at the interface between the Hubble Space Telescope and its solar arrays during in-orbit maneuvers. Theory, implementation in the FEM code ASKA, and practical results are shown.
Rost, D; Assaad, F; Blümer, N
2013-05-01
We present an algorithm for solving the self-consistency equations of the dynamical mean-field theory (DMFT) with high precision and efficiency at low temperatures. In each DMFT iteration, the impurity problem is mapped to an auxiliary Hamiltonian, for which the Green function is computed by combining determinantal quantum Monte Carlo (BSS-QMC) calculations with a multigrid extrapolation procedure. The method is numerically exact, i.e., yields results which are free of significant Trotter errors, but retains the BSS advantage, compared to direct QMC impurity solvers, of linear (instead of cubic) scaling with the inverse temperature. The new algorithm is applied to the half-filled Hubbard model close to the Mott transition; detailed comparisons with exact diagonalization, Hirsch-Fye QMC, and continuous-time QMC are provided. PMID:23767655
NASA Astrophysics Data System (ADS)
De la sen, M.
2006-03-01
This paper deals with the pole-placement type robust adaptive control of continuous linear systems in the presence of bounded noise and a common class of unmodeled dynamics with the use of multiple estimation schemes working in parallel. The multiestimation scheme consisting of the above set of various single estimation schemes is a tool used to minimize the plant identification error by building an estimate which is a convex combination of the estimates at all time. The weighting functions of the individual estimates are provided at each time by a suboptimization scheme for a quadratic loss function of a possibly filtered tracking error and/or control input. The robust stability of the overall adaptive scheme is ensured by an adaptation relative dead zone which takes into account the contribution of the unmodeled dynamics and bounded noise. The basic results are derived for two different estimation strategies which have either a shared regressor with the plant or individual regressors for the input contribution and its relevant time-derivatives. In this second case, the plant input is obtained through a similar convex combination rule as the one used for the estimators in the first approach. An extension of the basic strategies is also pointed out including a combined use of the suboptimization scheme with a supervisor of past measures for the on-line calculation of the estimator weights in the convex combination.
Humans use internal models to estimate gravity and linear acceleration.
Merfeld, D M; Zupan, L; Peterka, R J
1999-04-15
Because sensory systems often provide ambiguous information, neural processes must exist to resolve these ambiguities. It is likely that similar neural processes are used by different sensory systems. For example, many tasks require neural processing to distinguish linear acceleration from gravity, but Einstein's equivalence principle states that all linear accelerometers must measure both linear acceleration and gravity. Here we investigate whether the brain uses internal models, defined as neural systems that mimic physical principles, to help estimate linear acceleration and gravity. Internal models may be used in motor contro, sensorimotor integration and sensory processing, but direct experimental evidence for such models is limited. To determine how humans process ambiguous gravity and linear acceleration cues, subjects were tilted after being rotated at a constant velocity about an Earth-vertical axis. We show that the eye movements evoked by this post-rotational tilt include a response component that compensates for the estimated linear acceleration even when no actual linear acceleration occurs. These measured responses are consistent with our internal model predictions that the nervous system can develop a non-zero estimate of linear acceleration even when no true linear acceleration is present. PMID:10217143
Linear radiation model for phase of thermal emission spectroscopy
NASA Astrophysics Data System (ADS)
Bennett, Ted D.; Yu, Fengling
2005-11-01
A linear radiation model is developed that overcomes the analytical complexity in phase of thermal emission spectroscopy. It is shown that the linear radiation model can result in a simple algebraic relation between the phase of thermal emission and four coating properties, enabling these properties to be determined by nonlinear regression analysis of experimental measurements. Suitability of the linear radiation model to various measurement conditions is explored, and the model is applied to the phase of thermal emission measurements performed on a thermal barrier coating.
Non-linear transformer modeling and simulation
Archer, W.E.; Deveney, M.F.; Nagel, R.L.
1994-08-01
Transformers models for simulation with Pspice and Analogy`s Saber are being developed using experimental B-H Loop and network analyzer measurements. The models are evaluated for accuracy and convergence using several test circuits. Results are presented which demonstrate the effects on circuit performance from magnetic core losses eddy currents and mechanical stress on the magnetic cores.
A Second-Order Conditionally Linear Mixed Effects Model with Observed and Latent Variable Covariates
ERIC Educational Resources Information Center
Harring, Jeffrey R.; Kohli, Nidhi; Silverman, Rebecca D.; Speece, Deborah L.
2012-01-01
A conditionally linear mixed effects model is an appropriate framework for investigating nonlinear change in a continuous latent variable that is repeatedly measured over time. The efficacy of the model is that it allows parameters that enter the specified nonlinear time-response function to be stochastic, whereas those parameters that enter in a…
On-line control models for the Stanford Linear Collider
Sheppard, J.C.; Helm, R.H.; Lee, M.J.; Woodley, M.D.
1983-03-01
Models for computer control of the SLAC three-kilometer linear accelerator and damping rings have been developed as part of the control system for the Stanford Linear Collider. Some of these models have been tested experimentally and implemented in the control program for routine linac operations. This paper will describe the development and implementation of these models, as well as some of the operational results.
Neural network modelling of non-linear hydrological relationships
NASA Astrophysics Data System (ADS)
Abrahart, R. J.; See, L. M.
2007-09-01
Two recent studies have suggested that neural network modelling offers no worthwhile improvements in comparison to the application of weighted linear transfer functions for capturing the non-linear nature of hydrological relationships. The potential of an artificial neural network to perform simple non-linear hydrological transformations under controlled conditions is examined in this paper. Eight neural network models were developed: four full or partial emulations of a recognised non-linear hydrological rainfall-runoff model; four solutions developed on an identical set of inputs and a calculated runoff coefficient output. The use of different input combinations enabled the competencies of solutions developed on a reduced number of parameters to be assessed. The selected hydrological model had a limited number of inputs and contained no temporal component. The modelling process was based on a set of random inputs that had a uniform distribution and spanned a modest range of possibilities. The initial cloning operations permitted a direct comparison to be performed with the equation-based relationship. It also provided more general information about the power of a neural network to replicate mathematical equations and model modest non-linear relationships. The second group of experiments explored a different relationship that is of hydrological interest; the target surface contained a stronger set of non-linear properties and was more challenging. Linear modelling comparisons were performed against traditional least squares multiple linear regression solutions developed on identical datasets. The reported results demonstrate that neural networks are capable of modelling non-linear hydrological processes and are therefore appropriate tools for hydrological modelling.
Non-linear protocell models: synchronization and chaos
NASA Astrophysics Data System (ADS)
Filisetti, A.; Serra, R.; Carletti, T.; Villani, M.; Poli, I.
2010-09-01
We consider generic protocells models allowing linear and non-linear kinetics for the main involved chemical reactions. We are interested in understanding if and how the protocell division and the metabolism do synchronise to give rise to sustainable evolution of the protocell.
Linear and Nonlinear Thinking: A Multidimensional Model and Measure
ERIC Educational Resources Information Center
Groves, Kevin S.; Vance, Charles M.
2015-01-01
Building upon previously developed and more general dual-process models, this paper provides empirical support for a multidimensional thinking style construct comprised of linear thinking and multiple dimensions of nonlinear thinking. A self-report assessment instrument (Linear/Nonlinear Thinking Style Profile; LNTSP) is presented and…
Derivation and definition of a linear aircraft model
NASA Technical Reports Server (NTRS)
Duke, Eugene L.; Antoniewicz, Robert F.; Krambeer, Keith D.
1988-01-01
A linear aircraft model for a rigid aircraft of constant mass flying over a flat, nonrotating earth is derived and defined. The derivation makes no assumptions of reference trajectory or vehicle symmetry. The linear system equations are derived and evaluated along a general trajectory and include both aircraft dynamics and observation variables.
Recent History Functional Linear Models for Sparse Longitudinal Data
Kim, Kion; Şentürk, Damla; Li, Runze
2011-01-01
We consider the recent history functional linear models, relating a longitudinal response to a longitudinal predictor where the predictor process only in a sliding window into the recent past has an effect on the response value at the current time. We propose an estimation procedure for recent history functional linear models that is geared towards sparse longitudinal data, where the observation times across subjects are irregular and total number of measurements per subject is small. The proposed estimation procedure builds upon recent developments in literature for estimation of functional linear models with sparse data and utilizes connections between the recent history functional linear models and varying coefficient models. We establish uniform consistency of the proposed estimators, propose prediction of the response trajectories and derive their asymptotic distribution leading to asymptotic point-wise confidence bands. We include a real data application and simulation studies to demonstrate the efficacy of the proposed methodology. PMID:21691421
Nonlinear Submodels Of Orthogonal Linear Models
ERIC Educational Resources Information Center
Bechtel, Gordon G.
1973-01-01
It is the purpose of this paper to suggest the orthogonal analysis of variance as a device for simplifying either the analytic or iterative problem of finding LS (least squares) estimates for the parameters of particular nonlinear models. (Author/RK)
Genetic parameters for racing records in trotters using linear and generalized linear models.
Suontama, M; van der Werf, J H J; Juga, J; Ojala, M
2012-09-01
Heritability and repeatability and genetic and phenotypic correlations were estimated for trotting race records with linear and generalized linear models using 510,519 records on 17,792 Finnhorses and 513,161 records on 25,536 Standardbred trotters. Heritability and repeatability were estimated for single racing time and earnings traits with linear models, and logarithmic scale was used for racing time and fourth-root scale for earnings to correct for nonnormality. Generalized linear models with a gamma distribution were applied for single racing time and with a multinomial distribution for single earnings traits. In addition, genetic parameters for annual earnings were estimated with linear models on the observed and fourth-root scales. Racing success traits of single placings, winnings, breaking stride, and disqualifications were analyzed using generalized linear models with a binomial distribution. Estimates of heritability were greatest for racing time, which ranged from 0.32 to 0.34. Estimates of heritability were low for single earnings with all distributions, ranging from 0.01 to 0.09. Annual earnings were closer to normal distribution than single earnings. Heritability estimates were moderate for annual earnings on the fourth-root scale, 0.19 for Finnhorses and 0.27 for Standardbred trotters. Heritability estimates for binomial racing success variables ranged from 0.04 to 0.12, being greatest for winnings and least for breaking stride. Genetic correlations among racing traits were high, whereas phenotypic correlations were mainly low to moderate, except correlations between racing time and earnings were high. On the basis of a moderate heritability and moderate to high repeatability for racing time and annual earnings, selection of horses for these traits is effective when based on a few repeated records. Because of high genetic correlations, direct selection for racing time and annual earnings would also result in good genetic response in racing success
Bond models in linear and nonlinear optics
NASA Astrophysics Data System (ADS)
Aspnes, D. E.
2015-08-01
Bond models, also known as polarizable-point or mechanical models, have a long history in optics, starting with the Clausius-Mossotti relation but more accurately originating with Ewald's largely forgotten work in 1912. These models describe macroscopic phenomena such as dielectric functions and nonlinear-optical (NLO) susceptibilities in terms of the physics that takes place in real space, in real time, on the atomic scale. Their strengths lie in the insights that they provide and the questions that they raise, aspects that are often obscured by quantum-mechanical treatments. Statics versions were used extensively in the late 1960's and early 1970's to correlate NLO susceptibilities among bulk materials. Interest in NLO applications revived with the 2002 work of Powell et al., who showed that a fully anisotropic version reduced by more than a factor of 2 the relatively large number of parameters necessary to describe secondharmonic- generation (SHG) data for Si(111)/SiO2 interfaces. Attention now is focused on the exact physical meaning of these parameters, and to the extent that they represent actual physical quantities.
Failure of Tube Models to Predict the Linear Rheology of Star/Linear Blends
NASA Astrophysics Data System (ADS)
Hall, Ryan; Desai, Priyanka; Kang, Beomgoo; Katzarova, Maria; Huang, Qifan; Lee, Sanghoon; Chang, Taihyun; Venerus, David; Mays, Jimmy; Schieber, Jay; Larson, Ronald
We compare predictions of two of the most advanced versions of the tube model, namely the Hierarchical model by Wang et al. (J. Rheol. 54:223, 2010) and the BOB (branch-on-branch) model by Das et al. (J. Rheol. 50:207-234, 2006), against linear viscoelastic data on blends of monodisperse star and monodisperse linear polybutadiene polymers. The star was carefully synthesized/characterized by temperature gradient interaction chromatography, and rheological data in the high frequency region were obtained through time-temperature superposition. We found massive failures of both the Hierarchical and BOB models to predict the terminal relaxation behavior of the star/linear blends, despite their success in predicting the rheology of the pure star and pure linear. This failure occurred regardless of the choices made concerning constraint release, such as assuming arm retraction in fat or skinny tubes, or allowing for disentanglement relaxation to cut off the constraint release Rouse process at long times. The failures call into question whether constraint release can be described as a combination of constraint release Rouse processes and dynamic tube dilation within a canonical tube model of entanglement interactions.
Dilatonic non-linear sigma models and Ricci flow extensions
NASA Astrophysics Data System (ADS)
Carfora, M.; Marzuoli, A.
2016-09-01
We review our recent work describing, in terms of the Wasserstein geometry over the space of probability measures, the embedding of the Ricci flow in the renormalization group flow for dilatonic non-linear sigma models.
Model checking for linear temporal logic: An efficient implementation
NASA Technical Reports Server (NTRS)
Sherman, Rivi; Pnueli, Amir
1990-01-01
This report provides evidence to support the claim that model checking for linear temporal logic (LTL) is practically efficient. Two implementations of a linear temporal logic model checker is described. One is based on transforming the model checking problem into a satisfiability problem; the other checks an LTL formula for a finite model by computing the cross-product of the finite state transition graph of the program with a structure containing all possible models for the property. An experiment was done with a set of mutual exclusion algorithms and tested safety and liveness under fairness for these algorithms.
Optimization Research of Generation Investment Based on Linear Programming Model
NASA Astrophysics Data System (ADS)
Wu, Juan; Ge, Xueqian
Linear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments.
ERIC Educational Resources Information Center
Esteley, Cristina; Villarreal, Monica; Alagia, Humberto
2004-01-01
This research report presents a study of the work of agronomy majors in which an extension of linear models to non-linear contexts can be observed. By linear models we mean the model y=a.x+b, some particular representations of direct proportionality and the diagram for the rule of three. Its presence and persistence in different types of problems…
Modelling Childhood Growth Using Fractional Polynomials and Linear Splines
Tilling, Kate; Macdonald-Wallis, Corrie; Lawlor, Debbie A.; Hughes, Rachael A.; Howe, Laura D.
2014-01-01
Background There is increasing emphasis in medical research on modelling growth across the life course and identifying factors associated with growth. Here, we demonstrate multilevel models for childhood growth either as a smooth function (using fractional polynomials) or a set of connected linear phases (using linear splines). Methods We related parental social class to height from birth to 10 years of age in 5,588 girls from the Avon Longitudinal Study of Parents and Children (ALSPAC). Multilevel fractional polynomial modelling identified the best-fitting model as being of degree 2 with powers of the square root of age, and the square root of age multiplied by the log of age. The multilevel linear spline model identified knot points at 3, 12 and 36 months of age. Results Both the fractional polynomial and linear spline models show an initially fast rate of growth, which slowed over time. Both models also showed that there was a disparity in length between manual and non-manual social class infants at birth, which decreased in magnitude until approximately 1 year of age and then increased. Conclusions Multilevel fractional polynomials give a more realistic smooth function, and linear spline models are easily interpretable. Each can be used to summarise individual growth trajectories and their relationships with individual-level exposures. PMID:25413651
Phase II monitoring of auto-correlated linear profiles using linear mixed model
NASA Astrophysics Data System (ADS)
Narvand, A.; Soleimani, P.; Raissi, Sadigh
2013-05-01
In many circumstances, the quality of a process or product is best characterized by a given mathematical function between a response variable and one or more explanatory variables that is typically referred to as profile. There are some investigations to monitor auto-correlated linear and nonlinear profiles in recent years. In the present paper, we use the linear mixed models to account autocorrelation within observations which is gathered on phase II of the monitoring process. We undertake that the structure of correlated linear profiles simultaneously has both random and fixed effects. The work enhanced a Hotelling's T 2 statistic, a multivariate exponential weighted moving average (MEWMA), and a multivariate cumulative sum (MCUSUM) control charts to monitor process. We also compared their performances, in terms of average run length criterion, and designated that the proposed control charts schemes could effectively act in detecting shifts in process parameters. Finally, the results are applied on a real case study in an agricultural field.
Generation of linear dynamic models from a digital nonlinear simulation
NASA Technical Reports Server (NTRS)
Daniele, C. J.; Krosel, S. M.
1979-01-01
The results and methodology used to derive linear models from a nonlinear simulation are presented. It is shown that averaged positive and negative perturbations in the state variables can reduce numerical errors in finite difference, partial derivative approximations and, in the control inputs, can better approximate the system response in both directions about the operating point. Both explicit and implicit formulations are addressed. Linear models are derived for the F 100 engine, and comparisons of transients are made with the nonlinear simulation. The problem of startup transients in the nonlinear simulation in making these comparisons is addressed. Also, reduction of the linear models is investigated using the modal and normal techniques. Reduced-order models of the F 100 are derived and compared with the full-state models.
Complex dynamics in the Oregonator model with linear delayed feedback
NASA Astrophysics Data System (ADS)
Sriram, K.; Bernard, S.
2008-06-01
The Belousov-Zhabotinsky (BZ) reaction can display a rich dynamics when a delayed feedback is applied. We used the Oregonator model of the oscillating BZ reaction to explore the dynamics brought about by a linear delayed feedback. The time-delayed feedback can generate a succession of complex dynamics: period-doubling bifurcation route to chaos; amplitude death; fat, wrinkled, fractal, and broken tori; and mixed-mode oscillations. We observed that this dynamics arises due to a delay-driven transition, or toggling of the system between large and small amplitude oscillations, through a canard bifurcation. We used a combination of numerical bifurcation continuation techniques and other numerical methods to explore the dynamics in the strength of feedback-delay space. We observed that the period-doubling and quasiperiodic route to chaos span a low-dimensional subspace, perhaps due to the trapping of the trajectories in the small amplitude regime near the canard; and the trapped chaotic trajectories get ejected from the small amplitude regime due to a crowding effect to generate chaotic-excitable spikes. We also qualitatively explained the observed dynamics by projecting a three-dimensional phase portrait of the delayed dynamics on the two-dimensional nullclines. This is the first instance in which it is shown that the interaction of delay and canard can bring about complex dynamics.
Computer modeling of batteries from non-linear circuit elements
NASA Technical Reports Server (NTRS)
Waaben, S.; Federico, J.; Moskowitz, I.
1983-01-01
A simple non-linear circuit model for battery behavior is given. It is based on time-dependent features of the well-known PIN change storage diode, whose behavior is described by equations similar to those associated with electrochemical cells. The circuit simulation computer program ADVICE was used to predict non-linear response from a topological description of the battery analog built from advice components. By a reasonable choice of one set of parameters, the circuit accurately simulates a wide spectrum of measured non-linear battery responses to within a few millivolts.
Confirming the Lanchestrian linear-logarithmic model of attrition
Hartley, D.S. III.
1990-12-01
This paper is the fourth in a series of reports on the breakthrough research in historical validation of attrition in conflict. Significant defense policy decisions, including weapons acquisition and arms reduction, are based in part on models of conflict. Most of these models are driven by their attrition algorithms, usually forms of the Lanchester square and linear laws. None of these algorithms have been validated. The results of this paper confirm the results of earlier papers, using a large database of historical results. The homogeneous linear-logarithmic Lanchestrian attrition model is validated to the extent possible with current initial and final force size data and is consistent with the Iwo Jima data. A particular differential linear-logarithmic model is described that fits the data very well. A version of Helmbold's victory predicting parameter is also confirmed, with an associated probability function. 37 refs., 73 figs., 68 tabs.
Non-Linear Finite Element Modeling of THUNDER Piezoelectric Actuators
NASA Technical Reports Server (NTRS)
Taleghani, Barmac K.; Campbell, Joel F.
1999-01-01
A NASTRAN non-linear finite element model has been developed for predicting the dome heights of THUNDER (THin Layer UNimorph Ferroelectric DrivER) piezoelectric actuators. To analytically validate the finite element model, a comparison was made with a non-linear plate solution using Von Karmen's approximation. A 500 volt input was used to examine the actuator deformation. The NASTRAN finite element model was also compared with experimental results. Four groups of specimens were fabricated and tested. Four different input voltages, which included 120, 160, 200, and 240 Vp-p with a 0 volts offset, were used for this comparison.
A Model for Continuing Pharmacy Education
Newlon, Carey; Dickerhofe, Jeannine
2009-01-01
Objective To develop and implement a continuing pharmacy education (CPE) program at Kaiser Permanente Colorado (KPCO) Design To address the continuing education needs of its diverse pharmacy staff, an internal continuing pharmacy education (CPE) program was developed. The pharmacy department became an accredited provider by the Accreditation Council for Pharmacy Education (ACPE). Live, interactive, and evidence-based CPE programs, presented by highly qualified internal staff members, utilized videoconferencing and a Web-based learning management system. Cross-accreditation of medical and pharmacy educational programs was offered to KPCO staff members. Assessment Annual needs assessments were conducted to ensure the provision of relevant educational topics and to assess learning needs. To demonstrate outcomes of the CPE programs, 2 methods were utilized: objective effectiveness assessment and knowledge acquisition assessment. This program met the objectives for CPE activities a large majority of the time (usually over 90%), demonstrated statistically significant (p < 0.05) improvement in knowledge from before to after the CPE activity in 11 of 13 questions asked, and minimized the cost to acquire CPE credit for both the pharmacy department and its staff members. Conclusion The KPCO continuing pharmacy education program has developed a high quality and cost-favorable system that has resulted in significant improvements in attendee knowledge. PMID:19777102
Dynamic modeling of electrochemical systems using linear graph theory
NASA Astrophysics Data System (ADS)
Dao, Thanh-Son; McPhee, John
An electrochemical cell is a multidisciplinary system which involves complex chemical, electrical, and thermodynamical processes. The primary objective of this paper is to develop a linear graph-theoretical modeling for the dynamic description of electrochemical systems through the representation of the system topologies. After a brief introduction to the topic and a review of linear graphs, an approach to develop linear graphs for electrochemical systems using a circuitry representation is discussed, followed in turn by the use of the branch and chord transformation techniques to generate final dynamic equations governing the system. As an example, the application of linear graph theory to modeling a nickel metal hydride (NiMH) battery will be presented. Results show that not only the number of equations are reduced significantly, but also the linear graph model simulates faster compared to the original lumped parameter model. The approach presented in this paper can be extended to modeling complex systems such as an electric or hybrid electric vehicle where a battery pack is interconnected with other components in many different domains.
ASSESSING THE ACCURACY OF THE LINEARIZED LANGMUIR MODEL
Technology Transfer Automated Retrieval System (TEKTRAN)
One of the most commonly used models for describing phosphorus (P) sorption to soils is the nonlinear Langmuir model. To avoid the difficulties in fitting the nonlinear Langmuir equation to sorption data, linearized versions are commonly used. Although concerns have been raised in the past regarding...
Inverse Modelling Problems in Linear Algebra Undergraduate Courses
ERIC Educational Resources Information Center
Martinez-Luaces, Victor E.
2013-01-01
This paper will offer an analysis from a theoretical point of view of mathematical modelling, applications and inverse problems of both causation and specification types. Inverse modelling problems give the opportunity to establish connections between theory and practice and to show this fact, a simple linear algebra example in two different…
Optical linear algebra processors - Noise and error-source modeling
NASA Technical Reports Server (NTRS)
Casasent, D.; Ghosh, A.
1985-01-01
The modeling of system and component noise and error sources in optical linear algebra processors (OLAPs) are considered, with attention to the frequency-multiplexed OLAP. General expressions are obtained for the output produced as a function of various component errors and noise. A digital simulator for this model is discussed.
MULTIVARIATE LINEAR MIXED MODELS FOR MULTIPLE OUTCOMES. (R824757)
We propose a multivariate linear mixed (MLMM) for the analysis of multiple outcomes, which generalizes the latent variable model of Sammel and Ryan. The proposed model assumes a flexible correlation structure among the multiple outcomes, and allows a global test of the impact of ...
PID controller design for trailer suspension based on linear model
NASA Astrophysics Data System (ADS)
Kushairi, S.; Omar, A. R.; Schmidt, R.; Isa, A. A. Mat; Hudha, K.; Azizan, M. A.
2015-05-01
A quarter of an active trailer suspension system having the characteristics of a double wishbone type was modeled as a complex multi-body dynamic system in MSC.ADAMS. Due to the complexity of the model, a linearized version is considered in this paper. A model reduction technique is applied to the linear model, resulting in a reduced-order model. Based on this simplified model, a Proportional-Integral-Derivative (PID) controller was designed in MATLAB/Simulink environment; primarily to reduce excessive roll motions and thus improving the ride comfort. Simulation results show that the output signal closely imitates the input signal in multiple cases - demonstrating the effectiveness of the controller.
Functional linear models for association analysis of quantitative traits.
Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao
2013-11-01
Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. PMID:24130119
Confirming the Lanchestrian linear-logarithmic model of attrition
Hartley, D.S. III.
1990-12-01
This paper is the fourth in a series of reports on the breakthrough research in historical validation of attrition in conflict. Significant defense policy decisions, including weapons acquisition and arms reduction, are based in part on models of conflict. Most of these models are driven by their attrition algorithms, usually forms of the Lanchester square and linear laws. None of these algorithms have been validated. The results of this paper confirm the results of earlier papers, using a large database of historical results. The homogeneous linear-logarithmic Lanchestrian attrition model is validated to the extent possible with current initial and final force size data and is consistent with the Iwo Jima data. A particular differential linear-logarithmic model is described that fits the data very well. A version of Helmbold's victory predicting parameter is also confirmed, with an associated probability function. The implications of these findings are potentially far-reaching. Two-sided daily attrition data on a large number of battles is needed to absolutely confirm these results. Such a confirmation will require that numerous computer conflict models containing square and linear law based attrition algorithms be reexamined. It is conceivable that complex mixed, heterogeneous, square plus linear law algorithms may produce the same results as a homogeneous mixed linear-logarithmic law algorithm; however, such an occurrence is by no means assured. Even without such absolute confirmation, the results of this research allow the analysis of combat data for the effects of training, weather, leadership, and other human factors, unencumbered by the force size effects.
NASA Astrophysics Data System (ADS)
Lee, Dong-Jin; Lee, Sun-Kyu
2015-01-01
This paper presents a design and control system for an XY stage driven by an ultrasonic linear motor. In this study, a hybrid bolt-clamped Langevin-type ultrasonic linear motor was manufactured and then operated at the resonance frequency of the third longitudinal and the sixth lateral modes. These two modes were matched through the preload adjustment and precisely tuned by the frequency matching method based on the impedance matching method with consideration of the different moving weights. The XY stage was evaluated in terms of position and circular motion. To achieve both fine and stable motion, the controller consisted of a nominal characteristics trajectory following (NCTF) control for continuous motion, dead zone compensation, and a switching controller based on the different NCTFs for the macro- and micro-dynamics regimes. The experimental results showed that the developed stage enables positioning and continuous motion with nanometer-level accuracy.
Chen, Haixia; Zhang, Jing
2007-02-15
We propose a scheme for continuous-variable quantum cloning of coherent states with phase-conjugate input modes using linear optics. The quantum cloning machine yields M identical optimal clones from N replicas of a coherent state and N replicas of its phase conjugate. This scheme can be straightforwardly implemented with the setups accessible at present since its optical implementation only employs simple linear optical elements and homodyne detection. Compared with the original scheme for continuous-variable quantum cloning with phase-conjugate input modes proposed by Cerf and Iblisdir [Phys. Rev. Lett. 87, 247903 (2001)], which utilized a nondegenerate optical parametric amplifier, our scheme loses the output of phase-conjugate clones and is regarded as irreversible quantum cloning.
Lee, Dong-Jin; Lee, Sun-Kyu
2015-01-15
This paper presents a design and control system for an XY stage driven by an ultrasonic linear motor. In this study, a hybrid bolt-clamped Langevin-type ultrasonic linear motor was manufactured and then operated at the resonance frequency of the third longitudinal and the sixth lateral modes. These two modes were matched through the preload adjustment and precisely tuned by the frequency matching method based on the impedance matching method with consideration of the different moving weights. The XY stage was evaluated in terms of position and circular motion. To achieve both fine and stable motion, the controller consisted of a nominal characteristics trajectory following (NCTF) control for continuous motion, dead zone compensation, and a switching controller based on the different NCTFs for the macro- and micro-dynamics regimes. The experimental results showed that the developed stage enables positioning and continuous motion with nanometer-level accuracy.
Multikernel linear mixed models for complex phenotype prediction.
Weissbrod, Omer; Geiger, Dan; Rosset, Saharon
2016-07-01
Linear mixed models (LMMs) and their extensions have recently become the method of choice in phenotype prediction for complex traits. However, LMM use to date has typically been limited by assuming simple genetic architectures. Here, we present multikernel linear mixed model (MKLMM), a predictive modeling framework that extends the standard LMM using multiple-kernel machine learning approaches. MKLMM can model genetic interactions and is particularly suitable for modeling complex local interactions between nearby variants. We additionally present MKLMM-Adapt, which automatically infers interaction types across multiple genomic regions. In an analysis of eight case-control data sets from the Wellcome Trust Case Control Consortium and more than a hundred mouse phenotypes, MKLMM-Adapt consistently outperforms competing methods in phenotype prediction. MKLMM is as computationally efficient as standard LMMs and does not require storage of genotypes, thus achieving state-of-the-art predictive power without compromising computational feasibility or genomic privacy. PMID:27302636
Parallel, iterative solution of sparse linear systems: Models and architectures
NASA Technical Reports Server (NTRS)
Reed, D. A.; Patrick, M. L.
1984-01-01
A model of a general class of asynchronous, iterative solution methods for linear systems is developed. In the model, the system is solved by creating several cooperating tasks that each compute a portion of the solution vector. A data transfer model predicting both the probability that data must be transferred between two tasks and the amount of data to be transferred is presented. This model is used to derive an execution time model for predicting parallel execution time and an optimal number of tasks given the dimension and sparsity of the coefficient matrix and the costs of computation, synchronization, and communication. The suitability of different parallel architectures for solving randomly sparse linear systems is discussed. Based on the complexity of task scheduling, one parallel architecture, based on a broadcast bus, is presented and analyzed.
A linear model of stationary elevator traveling and compensation cables
NASA Astrophysics Data System (ADS)
Zhu, W. D.; Ren, H.
2013-06-01
Based on a recent asymptotic analysis of a nonlinear model of a slack cable, a computationally efficient, linear model is developed for calculating the natural frequencies, mode shapes, and dynamic responses of stationary elevator traveling and compensation cables. The linear cable model consists of two vertical cable segments connected by a half-circular lower loop. The two vertical cable segments are modeled as a string with a variable tension due to the weight of the cable. The horizontal displacements of the cable segments consist of boundary-induced displacements and relative elastic displacements, where the boundary-induced displacements are interpolated from the displacements of the two lower ends of the cable segments, and the relative elastic displacements satisfy the corresponding homogeneous boundary conditions of the cable segments. The horizontal displacement of the lower loop is interpolated from those of the two lower ends of the two cable segments, and the bending stiffness of the lower loop is modeled by a spring with a constant stiffness, which can be calculated from the nonlinear model. Given a car position, the natural frequencies and mode shapes of an elevator traveling or compensation cable are calculated using the linear model and compared with those from the nonlinear model. The calculated natural frequencies are also compared with those from a full-scale experiment. In addition, the dynamic responses of a cable under a boundary excitation are calculated and compared with those from the nonlinear model. There is a good agreement between the predictions from the linear and nonlinear models and between the measured natural frequencies from the full-scale experiment and the corresponding calculated ones.
The determination of third order linear models from a seventh order nonlinear jet engine model
NASA Technical Reports Server (NTRS)
Lalonde, Rick J.; Hartley, Tom T.; De Abreu-Garcia, J. Alex
1989-01-01
Results are presented that demonstrate how good reduced-order models can be obtained directly by recursive parameter identification using input/output (I/O) data of high-order nonlinear systems. Three different methods of obtaining a third-order linear model from a seventh-order nonlinear turbojet engine model are compared. The first method is to obtain a linear model from the original model and then reduce the linear model by standard reduction techniques such as residualization and balancing. The second method is to identify directly a third-order linear model by recursive least-squares parameter estimation using I/O data of the original model. The third method is to obtain a reduced-order model from the original model and then linearize the reduced model. Frequency responses are used as the performance measure to evaluate the reduced models. The reduced-order models along with their Bode plots are presented for comparison purposes.
A QUANTITATIVE PEDOLOGY APPROACH TO CONTINUOUS SOIL LANDSCAPE MODELS
Technology Transfer Automated Retrieval System (TEKTRAN)
Continuous representations of soil profiles and landscapes are needed to provide input into process based models and to move beyond the categorical paradigm of horizons and map-units. Continuous models of soil landscapes should be driven by the factors and processes of the soil genetic model. Parame...
Continuous-Discontinuous Model for Ductile Fracture
Seabra, Mariana R. R.; Cesar de Sa, Jose M. A.
2010-06-15
In this contribution, a continuum-dicontinuum model for ductile failure is presented. The degradation of material properties trough deformation is described by Continuum Damage Mechanics in a non-local integral formulation to avoid mesh dependence. In the final stage of failure, the damaged zone is replaced by a cohesive macro crack and subsequent traction-free macro crack for a more realistic representation of the phenomenon. The inclusion of the discontinuity surfaces is performed by the XFEM and Level Set Method and avoids the spurious damage growth typical of this class of models.
Identification of parameters of discrete-continuous models
Cekus, Dawid Warys, Pawel
2015-03-10
In the paper, the parameters of a discrete-continuous model have been identified on the basis of experimental investigations and formulation of optimization problem. The discrete-continuous model represents a cantilever stepped Timoshenko beam. The mathematical model has been formulated and solved according to the Lagrange multiplier formalism. Optimization has been based on the genetic algorithm. The presented proceeding’s stages make the identification of any parameters of discrete-continuous systems possible.
Dust grain coagulation modelling : From discrete to continuous
NASA Astrophysics Data System (ADS)
Paruta, P.; Hendrix, T.; Keppens, R.
2016-07-01
In molecular clouds, stars are formed from a mixture of gas, plasma and dust particles. The dynamics of this formation is still actively investigated and a study of dust coagulation can help to shed light on this process. Starting from a pre-existing discrete coagulation model, this work aims to mathematically explore its properties and its suitability for numerical validation. The crucial step is in our reinterpretation from its original discrete to a well-defined continuous form, which results in the well-known Smoluchowski coagulation equation. This opens up the possibility of exploiting previous results in order to prove the existence and uniqueness of a mass conserving solution for the evolution of dust grain size distribution. Ultimately, to allow for a more flexible numerical implementation, the problem is rewritten as a non-linear hyperbolic integro-differential equation and solved using a finite volume discretisation. It is demonstrated that there is an exact numerical agreement with the initial discrete model, with improved accuracy. This is of interest for further work on dynamically coupled gas with dust simulations.
Current Density and Continuity in Discretized Models
ERIC Educational Resources Information Center
Boykin, Timothy B.; Luisier, Mathieu; Klimeck, Gerhard
2010-01-01
Discrete approaches have long been used in numerical modelling of physical systems in both research and teaching. Discrete versions of the Schrodinger equation employing either one or several basis functions per mesh point are often used by senior undergraduates and beginning graduate students in computational physics projects. In studying…
Mathematical Modelling of Continuous Biotechnological Processes
ERIC Educational Resources Information Center
Pencheva, T.; Hristozov, I.; Shannon, A. G.
2003-01-01
Biotechnological processes (BTP) are characterized by a complicated structure of organization and interdependent characteristics. Partial differential equations or systems of partial differential equations are used for their behavioural description as objects with distributed parameters. Modelling of substrate without regard to dispersion…
Use of Linear Models for Thermal Processing Acidified Foods
Technology Transfer Automated Retrieval System (TEKTRAN)
Acidified vegetable products with a pH above 3.3 must be pasteurized to assure the destruction of acid resistant pathogenic bacteria. The times and temperatures needed to assure a five log reduction by pasteurization have previously been determined using a non-linear (Weibull) model. Recently, the F...
Mathematical modelling and linear stability analysis of laser fusion cutting
NASA Astrophysics Data System (ADS)
Hermanns, Torsten; Schulz, Wolfgang; Vossen, Georg; Thombansen, Ulrich
2016-06-01
A model for laser fusion cutting is presented and investigated by linear stability analysis in order to study the tendency for dynamic behavior and subsequent ripple formation. The result is a so called stability function that describes the correlation of the setting values of the process and the process' amount of dynamic behavior.
Evaluating Faculty Salary Equity Using Hierarchical Linear Modeling.
ERIC Educational Resources Information Center
Stapleton, Laura M.; Lissitz, Robert W.
This paper presents results from a comparison of the multiple regression (MR) approach to examining faculty salary equity (with clusters for the various disciplines) and hierarchical linear modeling (HLM) for the same problem. The comparison was done in two steps. First, a practical example of applying both techniques, using empirical data, is…
Confidence Intervals for Assessing Heterogeneity in Generalized Linear Mixed Models
ERIC Educational Resources Information Center
Wagler, Amy E.
2014-01-01
Generalized linear mixed models are frequently applied to data with clustered categorical outcomes. The effect of clustering on the response is often difficult to practically assess partly because it is reported on a scale on which comparisons with regression parameters are difficult to make. This article proposes confidence intervals for…
A General Linear Model Approach to Adjusting the Cumulative GPA.
ERIC Educational Resources Information Center
Young, John W.
A general linear model (GLM), using least-squares techniques, was used to develop a criterion measure to replace freshman year grade point average (GPA) in college admission predictive validity studies. Problems with the use of GPA include those associated with the combination of grades from different courses and disciplines into a single measure,…
Identification of linear system models and state estimators for controls
NASA Technical Reports Server (NTRS)
Chen, Chung-Wen
1992-01-01
The following paper is presented in viewgraph format and covers topics including: (1) linear state feedback control system; (2) Kalman filter state estimation; (3) relation between residual and stochastic part of output; (4) obtaining Kalman filter gain; (5) state estimation under unknown system model and unknown noises; and (6) relationship between filter Markov parameters and system Markov parameters.
Asymptotic behavior of coupled linear systems modeling suspension bridges
NASA Astrophysics Data System (ADS)
Dell'Oro, Filippo; Giorgi, Claudio; Pata, Vittorino
2015-06-01
We consider the coupled linear system describing the vibrations of a string-beam system related to the well-known Lazer-McKenna suspension bridge model. For ɛ > 0 and k > 0, the decay properties of the solution semigroup are discussed in dependence of the nonnegative parameters γ and h, which are responsible for the damping effects.
BF Models in Dual Formulations of Linearized Gravity
Bizdadea, Constantin; Cioroianu, Eugen M.; Danehkar, Ashbiz; Iordache, Marius; Saliu, Solange O.; Sararu, Silviu C.
2009-05-22
The case of couplings in D = 5 between a simple, maximal BF model and the dual formulation of linearized gravity is considered. All the possible interactions are exhausted by means of computing the 'free' local BRST cohomology in ghost number zero.
Linear network representation of multistate models of transport.
Sandblom, J; Ring, A; Eisenman, G
1982-05-01
By introducing external driving forces in rate-theory models of transport we show how the Eyring rate equations can be transformed into Ohm's law with potentials that obey Kirchhoff's second law. From such a formalism the state diagram of a multioccupancy multicomponent system can be directly converted into linear network with resistors connecting nodal (branch) points and with capacitances connecting each nodal point with a reference point. The external forces appear as emf or current generators in the network. This theory allows the algebraic methods of linear network theory to be used in solving the flux equations for multistate models and is particularly useful for making proper simplifying approximation in models of complex membrane structure. Some general properties of linear network representation are also deduced. It is shown, for instance, that Maxwell's reciprocity relationships of linear networks lead directly to Onsager's relationships in the near equilibrium region. Finally, as an example of the procedure, the equivalent circuit method is used to solve the equations for a few transport models. PMID:7093425
A SEMIPARAMETRIC BAYESIAN MODEL FOR CIRCULAR-LINEAR REGRESSION
We present a Bayesian approach to regress a circular variable on a linear predictor. The regression coefficients are assumed to have a nonparametric distribution with a Dirichlet process prior. The semiparametric Bayesian approach gives added flexibility to the model and is usefu...
Linearity of Quantum Probability Measure and Hardy's Model
NASA Astrophysics Data System (ADS)
Fujikawa, Kazuo; Oh, C. H.; Zhang, Chengjie
2014-01-01
We re-examine d = 4 hidden-variables model for a system of two spin-1/2 particles in view of the concrete model of Hardy, who analyzed the criterion of entanglement without referring to inequality. The basis of our analysis is the linearity of the probability measure related to the Born probability interpretation, which excludes noncontextual hidden-variables model in d≥3. To be specific, we note the inconsistency of the noncontextual hidden-variables model in d = 4 with the linearity of the quantum mechanical probability measure in the sense <ψ|aṡσ ⊗b ṡσ|ψ>+ <ψ|a ṡσ ⊗b‧ ṡσ|ψ> = <ψ|aṡσ⊗(b + b‧)ṡσ|ψ> for noncollinear b and b‧. It is then shown that Hardy's model in d = 4 does not lead to a unique mathematical expression in the demonstration of the discrepancy of local realism (hidden-variables model) with entanglement and thus his proof is incomplete. We identify the origin of this nonuniqueness with the nonuniqueness of translating quantum mechanical expressions into expressions in hidden-variables model, which results from the failure of the above linearity of the probability measure. In contrast, if the linearity of the probability measure is strictly imposed, which tantamounts to asking that the noncontextual hidden-variables model in d = 4 gives the Clauser-Horne-Shimony-Holt (CHSH) inequality ||≤2 uniquely, it is shown that the hidden-variables model can describe only separable quantum mechanical states; this conclusion is in perfect agreement with the so-called Gisin's theorem which states that ||≤2 implies separable states.
Identifiability Results for Several Classes of Linear Compartment Models.
Meshkat, Nicolette; Sullivant, Seth; Eisenberg, Marisa
2015-08-01
Identifiability concerns finding which unknown parameters of a model can be estimated, uniquely or otherwise, from given input-output data. If some subset of the parameters of a model cannot be determined given input-output data, then we say the model is unidentifiable. In this work, we study linear compartment models, which are a class of biological models commonly used in pharmacokinetics, physiology, and ecology. In past work, we used commutative algebra and graph theory to identify a class of linear compartment models that we call identifiable cycle models, which are unidentifiable but have the simplest possible identifiable functions (so-called monomial cycles). Here we show how to modify identifiable cycle models by adding inputs, adding outputs, or removing leaks, in such a way that we obtain an identifiable model. We also prove a constructive result on how to combine identifiable models, each corresponding to strongly connected graphs, into a larger identifiable model. We apply these theoretical results to several real-world biological models from physiology, cell biology, and ecology. PMID:26337290
STATISTICAL BASED NON-LINEAR MODEL UPDATING USING FEATURE EXTRACTION
Schultz, J.F.; Hemez, F.M.
2000-10-01
This research presents a new method to improve analytical model fidelity for non-linear systems. The approach investigates several mechanisms to assist the analyst in updating an analytical model based on experimental data and statistical analysis of parameter effects. The first is a new approach at data reduction called feature extraction. This is an expansion of the update metrics to include specific phenomena or character of the response that is critical to model application. This is an extension of the classical linear updating paradigm of utilizing the eigen-parameters or FRFs to include such devices as peak acceleration, time of arrival or standard deviation of model error. The next expansion of the updating process is the inclusion of statistical based parameter analysis to quantify the effects of uncertain or significant effect parameters in the construction of a meta-model. This provides indicators of the statistical variation associated with parameters as well as confidence intervals on the coefficients of the resulting meta-model, Also included in this method is the investigation of linear parameter effect screening using a partial factorial variable array for simulation. This is intended to aid the analyst in eliminating from the investigation the parameters that do not have a significant variation effect on the feature metric, Finally an investigation of the model to replicate the measured response variation is examined.
Linear parameter varying battery model identification using subspace methods
NASA Astrophysics Data System (ADS)
Hu, Y.; Yurkovich, S.
2011-03-01
The advent of hybrid and plug-in hybrid electric vehicles has created a demand for more precise battery pack management systems (BMS). Among methods used to design various components of a BMS, such as state-of-charge (SoC) estimators, model based approaches offer a good balance between accuracy, calibration effort and implementability. Because models used for these approaches are typically low in order and complexity, the traditional approach is to identify linear (or slightly nonlinear) models that are scheduled based on operating conditions. These models, formally known as linear parameter varying (LPV) models, tend to be difficult to identify because they contain a large amount of coefficients that require calibration. Consequently, the model identification process can be very laborious and time-intensive. This paper describes a comprehensive identification algorithm that uses linear-algebra-based subspace methods to identify a parameter varying state variable model that can describe the input-to-output dynamics of a battery under various operating conditions. Compared with previous methods, this approach is much faster and provides the user with information on the order of the system without placing an a priori structure on the system matrices. The entire process and various nuances are demonstrated using data collected from a lithium ion battery, and the focus is on applications for energy storage in automotive applications.
Linear Sigma Model Toolshed for D-brane Physics
Hellerman, Simeon
2001-08-23
Building on earlier work, we construct linear sigma models for strings on curved spaces in the presence of branes. Our models include an extremely general class of brane-worldvolume gauge field configurations. We explain in an accessible manner the mathematical ideas which suggest appropriate worldsheet interactions for generating a given open string background. This construction provides an explanation for the appearance of the derived category in D-brane physic complementary to that of recent work of Douglas.
Skills Diagnosis Using IRT-Based Continuous Latent Trait Models
ERIC Educational Resources Information Center
Stout, William
2007-01-01
This article summarizes the continuous latent trait IRT approach to skills diagnosis as particularized by a representative variety of continuous latent trait models using item response functions (IRFs). First, several basic IRT-based continuous latent trait approaches are presented in some detail. Then a brief summary of estimation, model…
Linear Time Invariant Models for Integrated Flight and Rotor Control
NASA Astrophysics Data System (ADS)
Olcer, Fahri Ersel
2011-12-01
Recent developments on individual blade control (IBC) and physics based reduced order models of various on-blade control (OBC) actuation concepts are opening up opportunities to explore innovative rotor control strategies for improved rotor aerodynamic performance, reduced vibration and BVI noise, and improved rotor stability, etc. Further, recent developments in computationally efficient algorithms for the extraction of Linear Time Invariant (LTI) models are providing a convenient framework for exploring integrated flight and rotor control, while accounting for the important couplings that exist between body and low frequency rotor response and high frequency rotor response. Formulation of linear time invariant (LTI) models of a nonlinear system about a periodic equilibrium using the harmonic domain representation of LTI model states has been studied in the literature. This thesis presents an alternative method and a computationally efficient scheme for implementation of the developed method for extraction of linear time invariant (LTI) models from a helicopter nonlinear model in forward flight. The fidelity of the extracted LTI models is evaluated using response comparisons between the extracted LTI models and the nonlinear model in both time and frequency domains. Moreover, the fidelity of stability properties is studied through the eigenvalue and eigenvector comparisons between LTI and LTP models by making use of the Floquet Transition Matrix. For time domain evaluations, individual blade control (IBC) and On-Blade Control (OBC) inputs that have been tried in the literature for vibration and noise control studies are used. For frequency domain evaluations, frequency sweep inputs are used to obtain frequency responses of fixed system hub loads to a single blade IBC input. The evaluation results demonstrate the fidelity of the extracted LTI models, and thus, establish the validity of the LTI model extraction process for use in integrated flight and rotor control
Linear modeling of steady-state behavioral dynamics.
Palya, William L; Walter, Donald; Kessel, Robert; Lucke, Robert
2002-01-01
The observed steady-state behavioral dynamics supported by unsignaled periods of reinforcement within repeating 2,000-s trials were modeled with a linear transfer function. These experiments employed improved schedule forms and analytical methods to improve the precision of the measured transfer function, compared to previous work. The refinements include both the use of multiple reinforcement periods that improve spectral coverage and averaging of independently determined transfer functions. A linear analysis was then used to predict behavior observed for three different test schedules. The fidelity of these predictions was determined. PMID:11831782
Gene Golub; Kwok Ko
2009-03-30
The solutions of sparse eigenvalue problems and linear systems constitute one of the key computational kernels in the discretization of partial differential equations for the modeling of linear accelerators. The computational challenges faced by existing techniques for solving those sparse eigenvalue problems and linear systems call for continuing research to improve on the algorithms so that ever increasing problem size as required by the physics application can be tackled. Under the support of this award, the filter algorithm for solving large sparse eigenvalue problems was developed at Stanford to address the computational difficulties in the previous methods with the goal to enable accelerator simulations on then the world largest unclassified supercomputer at NERSC for this class of problems. Specifically, a new method, the Hemitian skew-Hemitian splitting method, was proposed and researched as an improved method for solving linear systems with non-Hermitian positive definite and semidefinite matrices.
Can the Non-linear Ballooning Model describe ELMs?
NASA Astrophysics Data System (ADS)
Henneberg, S. A.; Cowley, S. C.; Wilson, H. R.
2015-11-01
The explosive, filamentary plasma eruptions described by the non-linear ideal MHD ballooning model is tested quantitatively against experimental observations of ELMs in MAST. The equations describing this model were derived by Wilson and Cowley for tokamak-like geometry which includes two differential equations: the linear ballooning equation which describes the spatial distribution along the field lines and the non-linear ballooning mode envelope equation, which is a two-dimensional, non-linear differential equation which can involve fractional temporal-derivatives, but is often second-order in time and space. To employ the second differential equation for a specific geometry one has to evaluate the coefficients of the equation which is non-trivial as it involves field line averaging of slowly converging functions. We have solved this system for MAST, superimposing the solutions of both differential equations and mapping them onto a MAST plasma. Comparisons with the evolution of ELM filaments in MAST will be reported in order to test the model. The support of the EPSRC for the FCDT (Grant EP/K504178/1), of Euratom research and training programme 2014-2018 (No 633053) and of the RCUK Energy Programme [grant number EP/I501045] is gratefully acknowledged.
Models for total dose degradation of linear integrated circuits
Johnston, A.H.; Plaag, R.E.
1987-12-01
Mechanisms for total dose degradation of linear circuits are discussed, including bulk effects, oxide charge buildup and recombination at the Si-SiO/sub 2/ interface. The dependence of damage on bias, dose, particle type and energy is used in conjunction with two-dimensional modeling to identify the failure mechanism in a specific linear device type. The importance of surface recombination is demonstrated along with the absence of bias dependence. Bulk damage is shown to be important for high energy electron irradiation because of wide-base pnp transistors. This causes substantial differences in device failure between electron and cobalt-60 environments that need to be taken into account for test standards and data bases that include commercial bipolar integrated circuits. Valid test methodologies for linear device must consider the energy and particle type present in the actual environment.
General mirror pairs for gauged linear sigma models
NASA Astrophysics Data System (ADS)
Aspinwall, Paul S.; Plesser, M. Ronen
2015-11-01
We carefully analyze the conditions for an abelian gauged linear σ-model to exhibit nontrivial IR behavior described by a nonsingular superconformal field theory determining a superstring vacuum. This is done without reference to a geometric phase, by associating singular behavior to a noncompact space of (semi-)classical vacua. We find that models determined by reflexive combinatorial data are nonsingular for generic values of their parameters. This condition has the pleasant feature that the mirror of a nonsingular gauged linear σ-model is another such model, but it is clearly too strong and we provide an example of a non-reflexive mirror pair. We discuss a weaker condition inspired by considering extremal transitions, which is also mirror symmetric and which we conjecture to be sufficient. We apply these ideas to extremal transitions and to understanding the way in which both Berglund-Hübsch mirror symmetry and the Vafa-Witten mirror orbifold with discrete torsion can be seen as special cases of the general combinatorial duality of gauged linear σ-models. In the former case we encounter an example showing that our weaker condition is still not necessary.
Yang, Xiaowei; Nie, Kun
2008-03-15
Longitudinal data sets in biomedical research often consist of large numbers of repeated measures. In many cases, the trajectories do not look globally linear or polynomial, making it difficult to summarize the data or test hypotheses using standard longitudinal data analysis based on various linear models. An alternative approach is to apply the approaches of functional data analysis, which directly target the continuous nonlinear curves underlying discretely sampled repeated measures. For the purposes of data exploration, many functional data analysis strategies have been developed based on various schemes of smoothing, but fewer options are available for making causal inferences regarding predictor-outcome relationships, a common task seen in hypothesis-driven medical studies. To compare groups of curves, two testing strategies with good power have been proposed for high-dimensional analysis of variance: the Fourier-based adaptive Neyman test and the wavelet-based thresholding test. Using a smoking cessation clinical trial data set, this paper demonstrates how to extend the strategies for hypothesis testing into the framework of functional linear regression models (FLRMs) with continuous functional responses and categorical or continuous scalar predictors. The analysis procedure consists of three steps: first, apply the Fourier or wavelet transform to the original repeated measures; then fit a multivariate linear model in the transformed domain; and finally, test the regression coefficients using either adaptive Neyman or thresholding statistics. Since a FLRM can be viewed as a natural extension of the traditional multiple linear regression model, the development of this model and computational tools should enhance the capacity of medical statistics for longitudinal data. PMID:17610294
Linear models for joint association and linkage QTL mapping
2009-01-01
Background Populational linkage disequilibrium and within-family linkage are commonly used for QTL mapping and marker assisted selection. The combination of both results in more robust and accurate locations of the QTL, but models proposed so far have been either single marker, complex in practice or well fit to a particular family structure. Results We herein present linear model theory to come up with additive effects of the QTL alleles in any member of a general pedigree, conditional to observed markers and pedigree, accounting for possible linkage disequilibrium among QTLs and markers. The model is based on association analysis in the founders; further, the additive effect of the QTLs transmitted to the descendants is a weighted (by the probabilities of transmission) average of the substitution effects of founders' haplotypes. The model allows for non-complete linkage disequilibrium QTL-markers in the founders. Two submodels are presented: a simple and easy to implement Haley-Knott type regression for half-sib families, and a general mixed (variance component) model for general pedigrees. The model can use information from all markers. The performance of the regression method is compared by simulation with a more complex IBD method by Meuwissen and Goddard. Numerical examples are provided. Conclusion The linear model theory provides a useful framework for QTL mapping with dense marker maps. Results show similar accuracies but a bias of the IBD method towards the center of the region. Computations for the linear regression model are extremely simple, in contrast with IBD methods. Extensions of the model to genomic selection and multi-QTL mapping are straightforward. PMID:19788745
Classifying linearly shielded modified gravity models in effective field theory.
Lombriser, Lucas; Taylor, Andy
2015-01-23
We study the model space generated by the time-dependent operator coefficients in the effective field theory of the cosmological background evolution and perturbations of modified gravity and dark energy models. We identify three classes of modified gravity models that reduce to Newtonian gravity on the small scales of linear theory. These general classes contain enough freedom to simultaneously admit a matching of the concordance model background expansion history. In particular, there exists a large model space that mimics the concordance model on all linear quasistatic subhorizon scales as well as in the background evolution. Such models also exist when restricting the theory space to operators introduced in Horndeski scalar-tensor gravity. We emphasize that whereas the partially shielded scenarios might be of interest to study in connection with tensions between large and small scale data, with conventional cosmological probes, the ability to distinguish the fully shielded scenarios from the concordance model on near-horizon scales will remain limited by cosmic variance. Novel tests of the large-scale structure remedying this deficiency and accounting for the full covariant nature of the alternative gravitational theories, however, might yield further insights on gravity in this regime. PMID:25658988
A non-linear model of economic production processes
NASA Astrophysics Data System (ADS)
Ponzi, A.; Yasutomi, A.; Kaneko, K.
2003-06-01
We present a new two phase model of economic production processes which is a non-linear dynamical version of von Neumann's neoclassical model of production, including a market price-setting phase as well as a production phase. The rate of an economic production process is observed, for the first time, to depend on the minimum of its input supplies. This creates highly non-linear supply and demand dynamics. By numerical simulation, production networks are shown to become unstable when the ratio of different products to total processes increases. This provides some insight into observed stability of competitive capitalist economies in comparison to monopolistic economies. Capitalist economies are also shown to have low unemployment.
Flood Nowcasting With Linear Catchment Models, Radar and Kalman Filters
NASA Astrophysics Data System (ADS)
Pegram, Geoff; Sinclair, Scott
A pilot study using real time rainfall data as input to a parsimonious linear distributed flood forecasting model is presented. The aim of the study is to deliver an operational system capable of producing flood forecasts, in real time, for the Mgeni and Mlazi catchments near the city of Durban in South Africa. The forecasts can be made at time steps which are of the order of a fraction of the catchment response time. To this end, the model is formulated in Finite Difference form in an equation similar to an Auto Regressive Moving Average (ARMA) model; it is this formulation which provides the required computational efficiency. The ARMA equation is a discretely coincident form of the State-Space equations that govern the response of an arrangement of linear reservoirs. This results in a functional relationship between the reservoir response con- stants and the ARMA coefficients, which guarantees stationarity of the ARMA model. Input to the model is a combined "Best Estimate" spatial rainfall field, derived from a combination of weather RADAR and Satellite rainfield estimates with point rain- fall given by a network of telemetering raingauges. Several strategies are employed to overcome the uncertainties associated with forecasting. Principle among these are the use of optimal (double Kalman) filtering techniques to update the model states and parameters in response to current streamflow observations and the application of short term forecasting techniques to provide future estimates of the rainfield as input to the model.
LINEAR MODELS FOR MANAGING SOURCES OF GROUNDWATER POLLUTION.
Gorelick, Steven M.; Gustafson, Sven-Ake
1984-01-01
Mathematical models for the problem of maintaining a specified groundwater quality while permitting solute waste disposal at various facilities distributed over space are discussed. The pollutants are assumed to be chemically inert and their concentrations in the groundwater are governed by linear equations for advection and diffusion. The aim is to determine a disposal policy which maximises the total amount of pollutants released during a fixed time T while meeting the condition that the concentration everywhere is below prescribed levels.
Using Quartile-Quartile Lines as Linear Models
ERIC Educational Resources Information Center
Gordon, Sheldon P.
2015-01-01
This article introduces the notion of the quartile-quartile line as an alternative to the regression line and the median-median line to produce a linear model based on a set of data. It is based on using the first and third quartiles of a set of (x, y) data. Dynamic spreadsheets are used as exploratory tools to compare the different approaches and…
Credibility analysis of risk classes by generalized linear model
NASA Astrophysics Data System (ADS)
Erdemir, Ovgucan Karadag; Sucu, Meral
2016-06-01
In this paper generalized linear model (GLM) and credibility theory which are frequently used in nonlife insurance pricing are combined for reliability analysis. Using full credibility standard, GLM is associated with limited fluctuation credibility approach. Comparison criteria such as asymptotic variance and credibility probability are used to analyze the credibility of risk classes. An application is performed by using one-year claim frequency data of a Turkish insurance company and results of credible risk classes are interpreted.
Granita; Bahar, A.
2015-03-09
This paper discusses on linear birth and death with immigration and emigration (BIDE) process to stochastic differential equation (SDE) model. Forward Kolmogorov equation in continuous time Markov chain (CTMC) with a central-difference approximation was used to find Fokker-Planckequation corresponding to a diffusion process having the stochastic differential equation of BIDE process. The exact solution, mean and variance function of BIDE process was found.
NASA Astrophysics Data System (ADS)
Granita, Bahar, A.
2015-03-01
This paper discusses on linear birth and death with immigration and emigration (BIDE) process to stochastic differential equation (SDE) model. Forward Kolmogorov equation in continuous time Markov chain (CTMC) with a central-difference approximation was used to find Fokker-Planckequation corresponding to a diffusion process having the stochastic differential equation of BIDE process. The exact solution, mean and variance function of BIDE process was found.
A general linear model for MEG beamformer imaging.
Brookes, Matthew J; Gibson, Andrew M; Hall, Stephen D; Furlong, Paul L; Barnes, Gareth R; Hillebrand, Arjan; Singh, Krish D; Holliday, Ian E; Francis, Sue T; Morris, Peter G
2004-11-01
A new general linear model (GLM) beamformer method is described for processing magnetoencephalography (MEG) data. A standard nonlinear beamformer is used to determine the time course of neuronal activation for each point in a predefined source space. A Hilbert transform gives the envelope of oscillatory activity at each location in any chosen frequency band (not necessary in the case of sustained (DC) fields), enabling the general linear model to be applied and a volumetric T statistic image to be determined. The new method is illustrated by a two-source simulation (sustained field and 20 Hz) and is shown to provide accurate localization. The method is also shown to locate accurately the increasing and decreasing gamma activities to the temporal and frontal lobes, respectively, in the case of a scintillating scotoma. The new method brings the advantages of the general linear model to the analysis of MEG data and should prove useful for the localization of changing patterns of activity across all frequency ranges including DC (sustained fields). PMID:15528094
ERIC Educational Resources Information Center
Esteley, Cristina B.; Villarreal, Monica E.; Alagia, Humberto R.
2010-01-01
Over the past several years, we have been exploring and researching a phenomenon that occurs among undergraduate students that we called extension of linear models to non-linear contexts or overgeneralization of linear models. This phenomenon appears when some students use linear representations in situations that are non-linear. In a first phase,…
CANFIS: A non-linear regression procedure to produce statistical air-quality forecast models
Burrows, W.R.; Montpetit, J.; Pudykiewicz, J.
1997-12-31
Statistical models for forecasts of environmental variables can provide a good trade-off between significance and precision in return for substantial saving of computer execution time. Recent non-linear regression techniques give significantly increased accuracy compared to traditional linear regression methods. Two are Classification and Regression Trees (CART) and the Neuro-Fuzzy Inference System (NFIS). Both can model predict and distributions, including the tails, with much better accuracy than linear regression. Given a learning data set of matched predict and predictors, CART regression produces a non-linear, tree-based, piecewise-continuous model of the predict and data. Its variance-minimizing procedure optimizes the task of predictor selection, often greatly reducing initial data dimensionality. NFIS reduces dimensionality by a procedure known as subtractive clustering but it does not of itself eliminate predictors. Over-lapping coverage in predictor space is enhanced by NFIS with a Gaussian membership function for each cluster component. Coefficients for a continuous response model based on the fuzzified cluster centers are obtained by a least-squares estimation procedure. CANFIS is a two-stage data-modeling technique that combines the strength of CART to optimize the process of selecting predictors from a large pool of potential predictors with the modeling strength of NFIS. A CANFIS model requires negligible computer time to run. CANFIS models for ground-level O{sub 3}, particulates, and other pollutants will be produced for each of about 100 Canadian sites. The air-quality models will run twice daily using a small number of predictors isolated from a large pool of upstream and local Lagrangian potential predictors.
Sahin, Rubina; Tapadia, Kavita
2015-01-01
The three widely used isotherms Langmuir, Freundlich and Temkin were examined in an experiment using fluoride (F⁻) ion adsorption on a geo-material (limonite) at four different temperatures by linear and non-linear models. Comparison of linear and non-linear regression models were given in selecting the optimum isotherm for the experimental results. The coefficient of determination, r², was used to select the best theoretical isotherm. The four Langmuir linear equations (1, 2, 3, and 4) are discussed. Langmuir isotherm parameters obtained from the four Langmuir linear equations using the linear model differed but they were the same when using the nonlinear model. Langmuir-2 isotherm is one of the linear forms, and it had the highest coefficient of determination (r² = 0.99) compared to the other Langmuir linear equations (1, 3 and 4) in linear form, whereas, for non-linear, Langmuir-4 fitted best among all the isotherms because it had the highest coefficient of determination (r² = 0.99). The results showed that the non-linear model may be a better way to obtain the parameters. In the present work, the thermodynamic parameters show that the absorption of fluoride onto limonite is both spontaneous (ΔG < 0) and endothermic (ΔH > 0). Scanning electron microscope and X-ray diffraction images also confirm the adsorption of F⁻ ion onto limonite. The isotherm and kinetic study reveals that limonite can be used as an adsorbent for fluoride removal. In future we can develop new technology for fluoride removal in large scale by using limonite which is cost-effective, eco-friendly and is easily available in the study area. PMID:26676015
A new pore-scale model for linear and non-linear heterogeneous dissolution and precipitation
NASA Astrophysics Data System (ADS)
Huber, Christian; Shafei, Babak; Parmigiani, Andrea
2014-01-01
Pore-scale processes exert a strong control on the transport of reactants in porous media at the continuum scale. As such, pore-scale numerical models can offer a more quantitative understanding of the coupling between transport and reaction and yield parameterized constitutive equations to introduce pore-scale corrections into macroscopic (continuum) reactive transport models. In the present study, we present a new pore-scale model for the advection and diffusion of reactants in porous media with complex topologies. The model is based on the lattice Boltzmann method and couples a fluid flow solver to an optimal advection-diffusion transport model. Internal solid-fluid boundaries (grain boundaries) are explicitly part of the numerical domain, which allows the algorithm to solve for surface reactions independently from the surface shape and orientation of the grains. Thus, the approach is well suited for the treatment of heterogeneous reactions in complex pore structures. We present single and multispecies reactive transport applications of the model. In the first application we study the permeability change of a porous medium associated with a given porosity change during dissolution and precipitation using linear reaction kinetics. We show that, for a given porous medium, the correlation between porosity and permeability changes depends on the transport regime (the ratio of advective to diffusive transport) and the reaction rate. Finally, we carry out simulations of multispecies reactive transport, focusing on the case of calcium carbonate dissolution/precipitation. Our results highlight the difference between pH dependent and independent reaction rates for heterogeneous reactions in complex geometries at the pore scale.
NASA Technical Reports Server (NTRS)
Rosen, I. G.; Wang, C.
1990-01-01
The convergence of solutions to the discrete or sampled time linear quadratic regulator problem and associated Riccati equation for infinite dimensional systems to the solutions to the corresponding continuous time problem and equation, as the length of the sampling interval (the sampling rate) tends toward zero (infinity) is established. Both the finite and infinite time horizon problems are studied. In the finite time horizon case, strong continuity of the operators which define the control system and performance index together with a stability and consistency condition on the sampling scheme are required. For the infinite time horizon problem, in addition, the sampled systems must be stabilizable and detectable, uniformly with respect to the sampling rate. Classes of systems for which this condition can be verified are discussed. Results of numerical studies involving the control of a heat/diffusion equation, a hereditary of delay system, and a flexible beam are presented and discussed.
NASA Technical Reports Server (NTRS)
Rosen, I. G.; Wang, C.
1992-01-01
The convergence of solutions to the discrete- or sampled-time linear quadratic regulator problem and associated Riccati equation for infinite-dimensional systems to the solutions to the corresponding continuous time problem and equation, as the length of the sampling interval (the sampling rate) tends toward zero(infinity) is established. Both the finite-and infinite-time horizon problems are studied. In the finite-time horizon case, strong continuity of the operators that define the control system and performance index, together with a stability and consistency condition on the sampling scheme are required. For the infinite-time horizon problem, in addition, the sampled systems must be stabilizable and detectable, uniformly with respect to the sampling rate. Classes of systems for which this condition can be verified are discussed. Results of numerical studies involving the control of a heat/diffusion equation, a hereditary or delay system, and a flexible beam are presented and discussed.
On the Development of Parameterized Linear Analytical Longitudinal Airship Models
NASA Technical Reports Server (NTRS)
Kulczycki, Eric A.; Johnson, Joseph R.; Bayard, David S.; Elfes, Alberto; Quadrelli, Marco B.
2008-01-01
In order to explore Titan, a moon of Saturn, airships must be able to traverse the atmosphere autonomously. To achieve this, an accurate model and accurate control of the vehicle must be developed so that it is understood how the airship will react to specific sets of control inputs. This paper explains how longitudinal aircraft stability derivatives can be used with airship parameters to create a linear model of the airship solely by combining geometric and aerodynamic airship data. This method does not require system identification of the vehicle. All of the required data can be derived from computational fluid dynamics and wind tunnel testing. This alternate method of developing dynamic airship models will reduce time and cost. Results are compared to other stable airship dynamic models to validate the methods. Future work will address a lateral airship model using the same methods.
Bayesian partial linear model for skewed longitudinal data.
Tang, Yuanyuan; Sinha, Debajyoti; Pati, Debdeep; Lipsitz, Stuart; Lipshultz, Steven
2015-07-01
Unlike majority of current statistical models and methods focusing on mean response for highly skewed longitudinal data, we present a novel model for such data accommodating a partially linear median regression function, a skewed error distribution and within subject association structures. We provide theoretical justifications for our methods including asymptotic properties of the posterior and associated semiparametric Bayesian estimators. We also provide simulation studies to investigate the finite sample properties of our methods. Several advantages of our method compared with existing methods are demonstrated via analysis of a cardiotoxicity study of children of HIV-infected mothers. PMID:25792623
Modelling human balance using switched systems with linear feedback control.
Kowalczyk, Piotr; Glendinning, Paul; Brown, Martin; Medrano-Cerda, Gustavo; Dallali, Houman; Shapiro, Jonathan
2012-02-01
We are interested in understanding the mechanisms behind and the character of the sway motion of healthy human subjects during quiet standing. We assume that a human body can be modelled as a single-link inverted pendulum, and the balance is achieved using linear feedback control. Using these assumptions, we derive a switched model which we then investigate. Stable periodic motions (limit cycles) about an upright position are found. The existence of these limit cycles is studied as a function of system parameters. The exploration of the parameter space leads to the detection of multi-stability and homoclinic bifurcations. PMID:21697168
NASA Astrophysics Data System (ADS)
Łuczko, J.
2002-08-01
A geometrically non-linear model of the rotating shaft is introduced, which includes Kárman non-linearity, non-linear curvature effects, large displacements and rotations as well as gyroscopic effects. Through applying Timoshenko-type assumptions, the shear effects are also included in the model. Convenient matrix descriptions are used in order to facilitate the analysis based on Galerkin and continuation methods. The model is used to analyze the phenomenon of internal resonance. The influence of some of the system's parameters on the amplitude and frequency of self-excited vibration is investigated.
First class models from linear and nonlinear second class constraints
NASA Astrophysics Data System (ADS)
Dehghani, Mehdi; Mardaani, Maryam; Monemzadeh, Majid; Nejad, Salman Abarghouei
2015-10-01
Two models with linear and nonlinear second class constraints are considered and gauged by embedding in an extended phase space. These models are studied by considering a free non-relativistic particle on the hyperplane and hypersphere in the configuration space. The gauged theory of the first model is obtained by converting the very second class system to the first class one directly. In contrast, the first class system related to the free particle on the hypersphere is derived with the help of the infinite Batalin-Fradkin-Tyutin (BFT) embedding procedure. We propose a practical formula, based on the simplified BFT method, which is practical in gauging linear and some nonlinear second class systems. As a result of gauging these two models, we show that in the conversion of second class constraints to the first class ones, the minimum number of phase space degrees of freedom for both systems is a pair of phase space coordinates. This pair is made up of a coordinate and its conjugate momentum for the first model, but the corresponding Poisson structure of the embedded non-relativistic particle on hypersphere is a nontrivial one. We derive infinite correction terms for the Hamiltonian of the nonlinear constraints and an interacting gauged Hamiltonian is constructed by summing over them. At the end, we find an open algebra for three first class objects of the embedded nonlinear system.
Linear stability analysis of swirling turbulent flows with turbulence models
NASA Astrophysics Data System (ADS)
Gupta, Vikrant; Juniper, Matthew
2013-11-01
In this paper, we consider the growth of large scale coherent structures in turbulent flows by performing linear stability analysis around a mean flow. Turbulent flows are characterized by fine-scale stochastic perturbations. The momentum transfer caused by these perturbations affects the development of larger structures. Therefore, in a linear stability analysis, it is important to include the perturbations' influence. One way to do this is to include a turbulence model in the stability analysis. This is done in the literature by using eddy viscosity models (EVMs), which are first order turbulence models. We extend this approach by using second order turbulence models, in this case explicit algebraic Reynolds stress models (EARSMs). EARSMs are more versatile than EVMs, in that they can be applied to a wider range of flows, and could also be more accurate. We verify our EARSM-based analysis by applying it to a channel flow and then comparing the results with those from an EVM-based analysis. We then apply the EARSM-based stability analysis to swirling pipe flows and Taylor-Couette flows, which demonstrates the main benefit of EARSM-based analysis. This project is supported by EPSRC and Rolls-Royce through a Dorothy Hodgkin Research Fellowship.
Wavefront Sensing for WFIRST with a Linear Optical Model
NASA Technical Reports Server (NTRS)
Jurling, Alden S.; Content, David A.
2012-01-01
In this paper we develop methods to use a linear optical model to capture the field dependence of wavefront aberrations in a nonlinear optimization-based phase retrieval algorithm for image-based wavefront sensing. The linear optical model is generated from a ray trace model of the system and allows the system state to be described in terms of mechanical alignment parameters rather than wavefront coefficients. This approach allows joint optimization over images taken at different field points and does not require separate convergence of phase retrieval at individual field points. Because the algorithm exploits field diversity, multiple defocused images per field point are not required for robustness. Furthermore, because it is possible to simultaneously fit images of many stars over the field, it is not necessary to use a fixed defocus to achieve adequate signal-to-noise ratio despite having images with high dynamic range. This allows high performance wavefront sensing using in-focus science data. We applied this technique in a simulation model based on the Wide Field Infrared Survey Telescope (WFIRST) Intermediate Design Reference Mission (IDRM) imager using a linear optical model with 25 field points. We demonstrate sub-thousandth-wave wavefront sensing accuracy in the presence of noise and moderate undersampling for both monochromatic and polychromatic images using 25 high-SNR target stars. Using these high-quality wavefront sensing results, we are able to generate upsampled point-spread functions (PSFs) and use them to determine PSF ellipticity to high accuracy in order to reduce the systematic impact of aberrations on the accuracy of galactic ellipticity determination for weak-lensing science.
NASA Astrophysics Data System (ADS)
Reagor, Matthew; Pfaff, Wolfgang; Heeres, Reinier; Ofek, Nissim; Chou, Kevin; Blumoff, Jacob; Leghtas, Zaki; Touzard, Steven; Sliwa, Katrina; Holland, Eric; Albert, Victor V.; Frunzio, Luigi; Devoret, Michel H.; Jiang, Liang; Schoelkopf, Robert J.
2015-03-01
Recent advances in circuit QED have shown great potential for using microwave resonators as quantum memories. In particular, it is possible to encode the state of a quantum bit in non-classical photonic states inside a high-Q linear resonator. An outstanding challenge is to perform controlled operations on such a photonic state. We demonstrate experimentally how a continuous drive on a transmon qubit coupled to a high-Q storage resonator can be used to induce non-linear dynamics of the resonator. Tailoring the drive properties allows us to cancel or enhance non-linearities in the system such that we can manipulate the state stored in the cavity. This approach can be used to either counteract undesirable evolution due to the bare Hamiltonian of the system or, ultimately, to perform logical operations on the state encoded in the cavity field. Our method provides a promising pathway towards performing universal control for quantum states stored in high-coherence resonators in the circuit QED platform.
NASA Astrophysics Data System (ADS)
Zander, C.; Plastino, A. R.; Díaz-Alonso, J.
2015-11-01
We investigate time-dependent solutions for a non-linear Schrödinger equation recently proposed by Nassar and Miret-Artés (NM) to describe the continuous measurement of the position of a quantum particle (Nassar, 2013; Nassar and Miret-Artés, 2013). Here we extend these previous studies in two different directions. On the one hand, we incorporate a potential energy term in the NM equation and explore the corresponding wave packet dynamics, while in the previous works the analysis was restricted to the free-particle case. On the other hand, we investigate time-dependent solutions while previous studies focused on a stationary one. We obtain exact wave packet solutions for linear and quadratic potentials, and approximate solutions for the Morse potential. The free-particle case is also revisited from a time-dependent point of view. Our analysis of time-dependent solutions allows us to determine the stability properties of the stationary solution considered in Nassar (2013), Nassar and Miret-Artés (2013). On the basis of these results we reconsider the Bohmian approach to the NM equation, taking into account the fact that the evolution equation for the probability density ρ =| ψ | 2 is not a continuity equation. We show that the effect of the source term appearing in the evolution equation for ρ has to be explicitly taken into account when interpreting the NM equation from a Bohmian point of view.
Prediction of mean arterial blood pressure with linear stochastic models.
Genc, Sahika
2011-01-01
A model-based approach that integrates known portion of the cardiovascular system and unknown portion through a parameter estimation to predict evolution of the mean arterial pressure is considered. The unknown portion corresponds to the neural portion that acts like a controller that takes corrective actions to regulate the arterial blood pressure at a constant level. The input to the neural part is the arterial pressure and output is the sympathetic nerve activity. In this model, heart rate is considered a proxy for sympathetic nerve activity. The neural portion is modeled as a linear discrete-time system with random coefficients. The performance of the model is tested on a case study of acute hypotensive episodes (AHEs) on PhysioNet data. TPRs and FPRs improve as more data becomes available during estimation period. PMID:22254409
Optimizing the Teaching-Learning Process Through a Linear Programming Model--Stage Increment Model.
ERIC Educational Resources Information Center
Belgard, Maria R.; Min, Leo Yoon-Gee
An operations research method to optimize the teaching-learning process is introduced in this paper. In particular, a linear programing model is proposed which, unlike dynamic or control theory models, allows the computer to react to the responses of a learner in seconds or less. To satisfy the assumptions of linearity, the seemingly complicated…
Rethinking the linear regression model for spatial ecological data.
Wagner, Helene H
2013-11-01
The linear regression model, with its numerous extensions including multivariate ordination, is fundamental to quantitative research in many disciplines. However, spatial or temporal structure in the data may invalidate the regression assumption of independent residuals. Spatial structure at any spatial scale can be modeled flexibly based on a set of uncorrelated component patterns (e.g., Moran's eigenvector maps, MEM) that is derived from the spatial relationships between sampling locations as defined in a spatial weight matrix. Spatial filtering thus addresses spatial autocorrelation in the residuals by adding such component patterns (spatial eigenvectors) as predictors to the regression model. However, space is not an ecologically meaningful predictor, and commonly used tests for selecting significant component patterns do not take into account the specific nature of these variables. This paper proposes "spatial component regression" (SCR) as a new way of integrating the linear regression model with Moran's eigenvector maps. In its unconditioned form, SCR decomposes the relationship between response and predictors by component patterns, whereas conditioned SCR provides an alternative method of spatial filtering, taking into account the statistical properties of component patterns in the design of statistical hypothesis tests. Application to the well-known multivariate mite data set illustrates how SCR may be used to condition for significant residual spatial structure and to identify additional predictors associated with residual spatial structure. Finally, I argue that all variance is spatially structured, hence spatial independence is best characterized by a lack of excess variance at any spatial scale, i.e., spatial white noise. PMID:24400490
Marginally specified generalized linear mixed models: a robust approach.
Mills, J E; Field, C A; Dupuis, D J
2002-12-01
Longitudinal data modeling is complicated by the necessity to deal appropriately with the correlation between observations made on the same individual. Building on an earlier nonrobust version proposed by Heagerty (1999, Biometrics 55, 688-698), our robust marginally specified generalized linear mixed model (ROBMS-GLMM) provides an effective method for dealing with such data. This model is one of the first to allow both population-averaged and individual-specific inference. As well, it adopts the flexibility and interpretability of generalized linear mixed models for introducing dependence but builds a regression structure for the marginal mean, allowing valid application with time-dependent (exogenous) and time-independent covariates. These new estimators are obtained as solutions of a robustified likelihood equation involving Huber's least favorable distribution and a collection of weights. Huber's least favorable distribution produces estimates that are resistant to certain deviations from the random effects distributional assumptions. Innovative weighting strategies enable the ROBMS-GLMM to perform well when faced with outlying observations both in the response and covariates. We illustrate the methodology with an analysis of a prospective longitudinal study of laryngoscopic endotracheal intubation, a skill that numerous health-care professionals are expected to acquire. The principal goal of our research is to achieve robust inference in longitudinal analyses. PMID:12495126
Monthly pan evaporation modeling using linear genetic programming
NASA Astrophysics Data System (ADS)
Guven, Aytac; Kisi, Ozgur
2013-10-01
This study compares the accuracy of linear genetic programming (LGP), fuzzy genetic (FG), adaptive neuro-fuzzy inference system (ANFIS), artificial neural networks (ANN) and Stephens-Stewart (SS) methods in modeling pan evaporations. Monthly climatic data including solar radiation, air temperature, relative humidity, wind speed and pan evaporation from Antalya and Mersin stations, in Turkey are used in the study. The study composed of two parts. First part of the study focuses the comparison of LGP models with those of the FG, ANFIS, ANN and SS models in estimating pan evaporations of Antalya and Mersin stations, separately. From the comparison results, the LGP models are found to be better than the other models. Comparison of LGP models with the other models in estimating pan evaporations of the Mersin Station by using both stations' inputs is focused in the second part of the study. The results indicate that the LGP models better accuracy than the FG, ANFIS, ANN and SS models. It is seen that the pan evaporations can be successfully estimated by the LGP method.
ERIC Educational Resources Information Center
Cheong, Yuk Fai; Kamata, Akihito
2013-01-01
In this article, we discuss and illustrate two centering and anchoring options available in differential item functioning (DIF) detection studies based on the hierarchical generalized linear and generalized linear mixed modeling frameworks. We compared and contrasted the assumptions of the two options, and examined the properties of their DIF…
Comparison of linear and nonlinear subgrid scale model for hybrid RANS/LES modelling
NASA Astrophysics Data System (ADS)
Straka, Petr
2016-06-01
The contribution deals with application of the hybrid RANS/LES model for calculation of flow around the circular cylinder. Used hybrid RANS/LES model is based on transport equation for the kinetic energy which is shared in both RANS and LES modes. The linear and the nonlinear closure formulas are described in the paper. Numerical results are compared with the experimental data. Results show that the nonlinear model predicts development of the wake behind the cylinder better than the linear model.
Tommasi, C.; May, C.
2010-09-30
The DKL-optimality criterion has been recently proposed for the dual problem of model discrimination and parameter estimation, for the case of two rival models. A sequential version of the DKL-optimality criterion is herein proposed in order to discriminate and efficiently estimate more than two nested non-linear models. Our sequential method is inspired by the procedure of Biswas and Chaudhuri (2002), which is however useful only in the set up of nested linear models.
Tangent linear analysis of the Mosaic land surface model
NASA Astrophysics Data System (ADS)
Yang, Runhua; Cohn, Stephen E.; da Silva, Arlindo; Joiner, Joanna; Houser, Paul R.
2003-01-01
In this study, a tangent linear eigenanalysis is applied to the Mosaic land surface model (LSM) [, 1992] to examine the impacts of the model internal dynamics and physics on the land surface state variability. The tangent linear model (TLM) of the Mosaic LSM is derived numerically for two sets of basic states and two tile types of land condition, grass and bare soil. An additional TLM, for the soil moisture subsystem of this LSM, is derived analytically for the same cases to obtain explicit expressions for the eigenvalues. An eigenvalue of the TLM determines a characteristic timescale, and the corresponding eigenvector, or mode, describes a particular coupling among the perturbed states. The results show that (1) errors in initial conditions tend to decay with e-folding times given by the characteristic timescales; (2) the LSM exhibits a wide range of internal variability, modes mainly representing surface temperature and surface moisture perturbations exhibit short timescales, whereas modes mainly representing deep soil temperature perturbations and moisture transfer throughout the entire soil column exhibit much longer timescales; (3) the modes of soil moisture tend to be weakly coupled with other perturbed variables, and the mode representing the deep soil temperature perturbation has a consistent e-folding time across the experiments; (4) the key parameters include soil moisture, soil layer depth, and soil hydraulic parameters. The results agree qualitatively with previous findings. However, tangent linear eigenanalysis provides a new approach to the quantitative substantiation of those findings. Also, it reveals the evolution and the coupling of the perturbed land states that are useful for the development of land surface data assimilation schemes. One must be careful when generalizing the quantitative results since they are obtained with respect to two specific basic states and two simple land conditions. Also, the methodology employed here does not apply
Linear system identification via backward-time observer models
NASA Technical Reports Server (NTRS)
Juang, Jer-Nan; Phan, Minh
1993-01-01
This paper presents an algorithm to identify a state-space model of a linear system using a backward-time approach. The procedure consists of three basic steps. First, the Markov parameters of a backward-time observer are computed from experimental input-output data. Second, the backward-time observer Markov parameters are decomposed to obtain the backward-time system Markov parameters (backward-time pulse response samples) from which a backward-time state-space model is realized using the Eigensystem Realization Algorithm. Third, the obtained backward-time state space model is converted to the usual forward-time representation. Stochastic properties of this approach will be discussed. Experimental results are given to illustrate when and to what extent this concept works.
Adaptive Error Estimation in Linearized Ocean General Circulation Models
NASA Technical Reports Server (NTRS)
Chechelnitsky, Michael Y.
1999-01-01
Data assimilation methods are routinely used in oceanography. The statistics of the model and measurement errors need to be specified a priori. This study addresses the problem of estimating model and measurement error statistics from observations. We start by testing innovation based methods of adaptive error estimation with low-dimensional models in the North Pacific (5-60 deg N, 132-252 deg E) to TOPEX/POSEIDON (TIP) sea level anomaly data, acoustic tomography data from the ATOC project, and the MIT General Circulation Model (GCM). A reduced state linear model that describes large scale internal (baroclinic) error dynamics is used. The methods are shown to be sensitive to the initial guess for the error statistics and the type of observations. A new off-line approach is developed, the covariance matching approach (CMA), where covariance matrices of model-data residuals are "matched" to their theoretical expectations using familiar least squares methods. This method uses observations directly instead of the innovations sequence and is shown to be related to the MT method and the method of Fu et al. (1993). Twin experiments using the same linearized MIT GCM suggest that altimetric data are ill-suited to the estimation of internal GCM errors, but that such estimates can in theory be obtained using acoustic data. The CMA is then applied to T/P sea level anomaly data and a linearization of a global GFDL GCM which uses two vertical modes. We show that the CMA method can be used with a global model and a global data set, and that the estimates of the error statistics are robust. We show that the fraction of the GCM-T/P residual variance explained by the model error is larger than that derived in Fukumori et al.(1999) with the method of Fu et al.(1993). Most of the model error is explained by the barotropic mode. However, we find that impact of the change in the error statistics on the data assimilation estimates is very small. This is explained by the large
Linear mixing model applied to AVHRR LAC data
NASA Technical Reports Server (NTRS)
Holben, Brent N.; Shimabukuro, Yosio E.
1993-01-01
A linear mixing model was applied to coarse spatial resolution data from the NOAA Advanced Very High Resolution Radiometer. The reflective component of the 3.55 - 3.93 microns channel was extracted and used with the two reflective channels 0.58 - 0.68 microns and 0.725 - 1.1 microns to run a Constraine Least Squares model to generate vegetation, soil, and shade fraction images for an area in the Western region of Brazil. The Landsat Thematic Mapper data covering the Emas National park region was used for estimating the spectral response of the mixture components and for evaluating the mixing model results. The fraction images were compared with an unsupervised classification derived from Landsat TM data acquired on the same day. The relationship between the fraction images and normalized difference vegetation index images show the potential of the unmixing techniques when using coarse resolution data for global studies.
Accelerating transient simulation of linear reduced order models.
Thornquist, Heidi K.; Mei, Ting; Keiter, Eric Richard; Bond, Brad
2011-10-01
Model order reduction (MOR) techniques have been used to facilitate the analysis of dynamical systems for many years. Although existing model reduction techniques are capable of providing huge speedups in the frequency domain analysis (i.e. AC response) of linear systems, such speedups are often not obtained when performing transient analysis on the systems, particularly when coupled with other circuit components. Reduced system size, which is the ostensible goal of MOR methods, is often insufficient to improve transient simulation speed on realistic circuit problems. It can be shown that making the correct reduced order model (ROM) implementation choices is crucial to the practical application of MOR methods. In this report we investigate methods for accelerating the simulation of circuits containing ROM blocks using the circuit simulator Xyce.
Spatial temporal disaggregation of daily rainfall from a generalized linear model
NASA Astrophysics Data System (ADS)
Segond, M.-L.; Onof, C.; Wheater, H. S.
2006-12-01
SummaryThis paper describes a methodology for continuous simulation of spatially-distributed hourly rainfall, based on observed data from a daily raingauge network. Generalized linear models (GLMs), which can represent the spatial and temporal non-stationarities of multi-site daily rainfall (Chandler, R.E., Wheater, H.S., 2002. Analysis of rainfall variability using generalised linear models: a case study from the west of Ireland. Water Resources Research, 38 (10), 1192. doi:10.1029/2001WR000906), are combined with a single-site disaggregation model based on Poisson cluster processes (Koutsoyiannis, D., Onof, C., 2001. Rainfall disaggregation using adjusting procedures on a Poisson cluster model. Journal of Hydrology 246, 109-122). The resulting sub-daily temporal profile is then applied linearly to all sites over the catchment to reproduce the spatially-varying daily totals. The method is tested for the River Lee catchment, UK, a tributary of the Thames covering an area of 1400 km 2. Twenty simulations of 12 years of hourly rainfall are generated at 20 sites and compared with the historical series. The proposed model preserves most standard statistics but has some limitations in the representation of extreme rainfall and the correlation structure. The method can be extended to sites within the modelled region not used in the model calibration.
Decoding coalescent hidden Markov models in linear time
Harris, Kelley; Sheehan, Sara; Kamm, John A.; Song, Yun S.
2014-01-01
In many areas of computational biology, hidden Markov models (HMMs) have been used to model local genomic features. In particular, coalescent HMMs have been used to infer ancient population sizes, migration rates, divergence times, and other parameters such as mutation and recombination rates. As more loci, sequences, and hidden states are added to the model, however, the runtime of coalescent HMMs can quickly become prohibitive. Here we present a new algorithm for reducing the runtime of coalescent HMMs from quadratic in the number of hidden time states to linear, without making any additional approximations. Our algorithm can be incorporated into various coalescent HMMs, including the popular method PSMC for inferring variable effective population sizes. Here we implement this algorithm to speed up our demographic inference method diCal, which is equivalent to PSMC when applied to a sample of two haplotypes. We demonstrate that the linear-time method can reconstruct a population size change history more accurately than the quadratic-time method, given similar computation resources. We also apply the method to data from the 1000 Genomes project, inferring a high-resolution history of size changes in the European population. PMID:25340178
Modeling of Linear Gas Tungsten Arc Welding of Stainless Steel
NASA Astrophysics Data System (ADS)
Maran, P.; Sornakumar, T.; Sundararajan, T.
2008-08-01
A heat and fluid flow model has been developed to solve the gas tungsten arc (GTA) linear welding problem for austenitic stainless steel. The moving heat source problem associated with the electrode traverse has been simplified into an equivalent two-dimensional (2-D) transient problem. The torch residence time has been calculated from the arc diameter and torch speed. The mathematical formulation considers buoyancy, electromagnetic induction, and surface tension forces. The governing equations have been solved by the finite volume method. The temperature and velocity fields have been determined. The theoretical predictions for weld bead geometry are in good agreement with experimental measurements.
Markov-random-field modeling for linear seismic tomography.
Kuwatani, Tatsu; Nagata, Kenji; Okada, Masato; Toriumi, Mitsuhiro
2014-10-01
We apply the Markov-random-field model to linear seismic tomography and propose a method to estimate the hyperparameters for the smoothness and the magnitude of the noise. Optimal hyperparameters can be determined analytically by minimizing the free energy function, which is defined by marginalizing the evaluation function. In synthetic inversion tests under various settings, the assumed velocity structures are successfully reconstructed, which shows the effectiveness and robustness of the proposed method. The proposed mathematical framework can be applied to inversion problems in various fields in the natural sciences. PMID:25375468
The linear interaction model of personality effects in health communication.
Dutta-Bergman, Mohan Jyoti
2003-01-01
The recent growth of research in message tailoring has opened up new avenues for researchers to use personality variables for message delivery. This article builds on research on idiocentrism and self-monitoring to propose a framework for message appeal construction. Based on a scheme for appeal categorization borrowed from commercial marketing, the article suggests that low and high idiocentrics differ from each other in the way they respond to appeal types. Similarly, significant differences are demonstrated between low and high self-monitors in the realm of their response to message appeals. A linear interaction model is proposed to document the combined effects of self-monitoring and idiocentrism. PMID:12553779
Linear and generalized linear models for the detection of QTL effects on within-subject variability
Wittenburg, Dörte; Guiard, Volker; Liese, Friedrich; Reinsch, Norbert
2007-01-01
Summary Quantitative trait loci (QTLs) may affect not only the mean of a trait but also its variability. A special aspect is the variability between multiple measured traits of genotyped animals, such as the within-litter variance of piglet birth weights. The sample variance of repeated measurements is assigned as an observation for every genotyped individual. It is shown that the conditional distribution of the non-normally distributed trait can be approximated by a gamma distribution. To detect QTL effects in the daughter design, a generalized linear model with the identity link function is applied. Suitable test statistics are constructed to test the null hypothesis H0: No QTL with effect on the within-litter variance is segregating versus HA: There is a QTL with effect on the variability of birth weight within litter. Furthermore, estimates of the QTL effect and the QTL position are introduced and discussed. The efficiency of the presented tests is compared with a test based on weighted regression. The error probability of the first type as well as the power of QTL detection are discussed and compared for the different tests. PMID:18208630
A wavelet-linear genetic programming model for sodium (Na+) concentration forecasting in rivers
NASA Astrophysics Data System (ADS)
Ravansalar, Masoud; Rajaee, Taher; Zounemat-Kermani, Mohammad
2016-06-01
The prediction of water quality parameters in water resources such as rivers is of importance issue that needs to be considered in better management of irrigation systems and water supplies. In this respect, this study proposes a new hybrid wavelet-linear genetic programming (WLGP) model for prediction of monthly sodium (Na+) concentration. The 23-year monthly data used in this study, were measured from the Asi River at the Demirköprü gauging station located in Antakya, Turkey. At first, the measured discharge (Q) and Na+ datasets are initially decomposed into several sub-series using discrete wavelet transform (DWT). Then, these new sub-series are imposed to the ad hoc linear genetic programming (LGP) model as input patterns to predict monthly Na+ one month ahead. The results of the new proposed WLGP model are compared with LGP, WANN and ANN models. Comparison of the models represents the superiority of the WLGP model over the LGP, WANN and ANN models such that the Nash-Sutcliffe efficiencies (NSE) for WLGP, WANN, LGP and ANN models were 0.984, 0.904, 0.484 and 0.351, respectively. The achieved results even points to the superiority of the single LGP model than the ANN model. Continuously, the capability of the proposed WLGP model in terms of prediction of the Na+ peak values is also presented in this study.
Stratospheric ozone time series analysis using dynamical linear models
NASA Astrophysics Data System (ADS)
Laine, Marko; Kyrölä, Erkki
2013-04-01
We describe a hierarchical statistical state space model for ozone profile time series. The time series are from satellite measurements by the SAGE II and GOMOS instruments spanning years 1984-2012. The original data sets are combined and gridded monthly using 10 degree latitude bands, and covering 20-60 km with 1 km vertical spacing. Model components include level, trend, seasonal effect with solar activity, and quasi biennial oscillations as proxy variables. A typical feature of an atmospheric time series is that they are not stationary but exhibit both slowly varying and abrupt changes in the distributional properties. These are caused by external forcing such as changes in the solar activity or volcanic eruptions. Further, the data sampling is often nonuniform, there are data gaps, and the uncertainty of the observations can vary. When observations are combined from various sources there will be instrument and retrieval method related biases. The differences in sampling lead also to uncertainties. Standard classical ARIMA type of statistical time series methods are mostly useless for atmospheric data. A more general approach makes use of dynamical linear models and Kalman filter type of sequential algorithms. These state space models assume a linear relationship between the unknown state of the system and the observations and for the process evolution of the hidden states. They are still flexible enough to model both smooth trends and sudden changes. The above mentioned methodological challenges are discussed, together with analysis of change points in trends related to recovery of stratospheric ozone. This work is part of the ESA SPIN and ozone CCI projects.
Non-Linear Slosh Damping Model Development and Validation
NASA Technical Reports Server (NTRS)
Yang, H. Q.; West, Jeff
2015-01-01
Propellant tank slosh dynamics are typically represented by a mechanical model of spring mass damper. This mechanical model is then included in the equation of motion of the entire vehicle for Guidance, Navigation and Control (GN&C) analysis. For a partially-filled smooth wall propellant tank, the critical damping based on classical empirical correlation is as low as 0.05%. Due to this low value of damping, propellant slosh is potential sources of disturbance critical to the stability of launch and space vehicles. It is postulated that the commonly quoted slosh damping is valid only under the linear regime where the slosh amplitude is small. With the increase of slosh amplitude, the critical damping value should also increase. If this nonlinearity can be verified and validated, the slosh stability margin can be significantly improved, and the level of conservatism maintained in the GN&C analysis can be lessened. The purpose of this study is to explore and to quantify the dependence of slosh damping with slosh amplitude. Accurately predicting the extremely low damping value of a smooth wall tank is very challenging for any Computational Fluid Dynamics (CFD) tool. One must resolve thin boundary layers near the wall and limit numerical damping to minimum. This computational study demonstrates that with proper grid resolution, CFD can indeed accurately predict the low damping physics from smooth walls under the linear regime. Comparisons of extracted damping values with experimental data for different tank sizes show very good agreements. Numerical simulations confirm that slosh damping is indeed a function of slosh amplitude. When slosh amplitude is low, the damping ratio is essentially constant, which is consistent with the empirical correlation. Once the amplitude reaches a critical value, the damping ratio becomes a linearly increasing function of the slosh amplitude. A follow-on experiment validated the developed nonlinear damping relationship. This discovery can
NASA Astrophysics Data System (ADS)
Liang, Jianwu; Zhou, Jian; Shi, Jinjing; He, Guangqiang; Guo, Ying
2016-02-01
We characterize the efficiency of the practical continuous-variable quantum key distribution (CVQKD) while inserting the heralded noiseless linear amplifier (NLA) before detectors to increase the secret key rate and the maximum transmission distance in Gaussian channels. In the heralded NLA-based CVQKD system, the entanglement source is only placed in the middle while the two participants are unnecessary to trust their source. The intensities of source noise are sensitive to the tunable NLA with the parameter g in a suitable range and can be stabilized to the suitable constant values to eliminate the impact of channel noise and defeat the potential attacks. Simulation results show that there is a well balance between the secret key rate and the maximum transmission distance with the tunable NLA.
Feedbacks, climate sensitivity and the limits of linear models.
Knutti, Reto; Rugenstein, Maria A A
2015-11-13
The term 'feedback' is used ubiquitously in climate research, but implies varied meanings in different contexts. From a specific process that locally affects a quantity, to a formal framework that attempts to determine a global response to a forcing, researchers use this term to separate, simplify and quantify parts of the complex Earth system. We combine new model results with a historical and educational perspective to organize existing ideas around feedbacks and linear models. Our results suggest that the state- and forcing-dependency of feedbacks are probably not appreciated enough, and not considered appropriately in many studies. A non-constant feedback parameter likely explains some of the differences in estimates of equilibrium climate sensitivity from different methods and types of data. Clarifying the value and applicability of the linear forcing feedback framework and a better quantification of feedbacks on various timescales and spatial scales remains a high priority in order to better understand past and predict future changes in the climate system. PMID:26438287
Linear versus quadratic portfolio optimization model with transaction cost
NASA Astrophysics Data System (ADS)
Razak, Norhidayah Bt Ab; Kamil, Karmila Hanim; Elias, Siti Masitah
2014-06-01
Optimization model is introduced to become one of the decision making tools in investment. Hence, it is always a big challenge for investors to select the best model that could fulfill their goal in investment with respect to risk and return. In this paper we aims to discuss and compare the portfolio allocation and performance generated by quadratic and linear portfolio optimization models namely of Markowitz and Maximin model respectively. The application of these models has been proven to be significant and popular among others. However transaction cost has been debated as one of the important aspects that should be considered for portfolio reallocation as portfolio return could be significantly reduced when transaction cost is taken into consideration. Therefore, recognizing the importance to consider transaction cost value when calculating portfolio' return, we formulate this paper by using data from Shariah compliant securities listed in Bursa Malaysia. It is expected that, results from this paper will effectively justify the advantage of one model to another and shed some lights in quest to find the best decision making tools in investment for individual investors.
Revisiting "Discrepancy Analysis in Continuing Medical Education: A Conceptual Model"
ERIC Educational Resources Information Center
Fox, Robert D.
2011-01-01
Based upon a review and analysis of selected literature, the author presents a conceptual model of discrepancy analysis evaluation for planning, implementing, and assessing the impact of continuing medical education (CME). The model is described in terms of its value as a means of diagnosing errors in the development and implementation of CME. The…
A MCMC-Method for Models with Continuous Latent Responses.
ERIC Educational Resources Information Center
Maris, Gunter; Maris, Eric
2002-01-01
Introduces a new technique for estimating the parameters of models with continuous latent data. To streamline presentation of this Markov Chain Monte Carlo (MCMC) method, the Rasch model is used. Also introduces a new sampling-based Bayesian technique, the DA-T-Gibbs sampler. (SLD)
A Quasispecies Continuous Contact Model in a Critical Regime
NASA Astrophysics Data System (ADS)
Kondratiev, Yuri; Pirogov, Sergey; Zhizhina, Elena
2016-04-01
We study a new non-equilibrium dynamical model: a marked continuous contact model in d-dimensional space (d ge 3). We prove that for certain values of rates (the critical regime) this system has the one-parameter family of invariant measures labelled by the spatial density of particles. Then we prove that the process starting from the marked Poisson measure converges to one of these invariant measures. In contrast with the continuous contact model studied earlier in Kondratiev (Infin Dimens Anal Quantum Probab Relat Top 11(2):231-258, 2008), now the spatial particle density is not a conserved quantity.
Pointwise Description for the Linearized Fokker-Planck-Boltzmann Model
NASA Astrophysics Data System (ADS)
Wu, Kung-Chien
2015-09-01
In this paper, we study the pointwise (in the space variable) behavior of the linearized Fokker-Planck-Boltzmann model for nonsmooth initial perturbations. The result reveals both the fluid and kinetic aspects of this model. The fluid-like waves are constructed as the long-wave expansion in the spectrum of the Fourier modes for the space variable, and it has polynomial time decay rate. We design a Picard-type iteration for constructing the increasingly regular kinetic-like waves, which are carried by the transport equations and have exponential time decay rate. The Mixture Lemma plays an important role in constructing the kinetic-like waves, this lemma was originally introduced by Liu-Yu (Commun Pure Appl Math 57:1543-1608, 2004) for Boltzmann equation, but the Fokker-Planck term in this paper creates some technical difficulties.
Linear mixing model applied to coarse resolution satellite data
NASA Technical Reports Server (NTRS)
Holben, Brent N.; Shimabukuro, Yosio E.
1992-01-01
A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fraction images and the well known NDVI images are presented. The results show the great potential of the unmixing techniques for applying to coarse resolution data for global studies.
Relating Cohesive Zone Model to Linear Elastic Fracture Mechanics
NASA Technical Reports Server (NTRS)
Wang, John T.
2010-01-01
The conditions required for a cohesive zone model (CZM) to predict a failure load of a cracked structure similar to that obtained by a linear elastic fracture mechanics (LEFM) analysis are investigated in this paper. This study clarifies why many different phenomenological cohesive laws can produce similar fracture predictions. Analytical results for five cohesive zone models are obtained, using five different cohesive laws that have the same cohesive work rate (CWR-area under the traction-separation curve) but different maximum tractions. The effect of the maximum traction on the predicted cohesive zone length and the remote applied load at fracture is presented. Similar to the small scale yielding condition for an LEFM analysis to be valid. the cohesive zone length also needs to be much smaller than the crack length. This is a necessary condition for a CZM to obtain a fracture prediction equivalent to an LEFM result.
Measuring and modeling continuous quality distributions of soil organic matter
NASA Astrophysics Data System (ADS)
Bruun, S.; Gren, G. I. Ã.; Christensen, B. T.; Jensen, L. S.
2010-01-01
An understanding of the dynamics of soil organic matter (SOM) is important for our ability to develop management practices that preserve soil quality and sequester carbon. Most SOM decomposition models represent the heterogeneity of organic matter by a few discrete compartments with different turnover rates, while other models employ a continuous quality distribution. To make the multi-compartment models more mechanistic in nature, it has been argued that the compartments should be related to soil fractions actually occurring and having a functional role in the soil. In this paper, we make the case that fractionation methods that can measure continuous quality distributions should be developed, and that the temporal development of these distributions should be incorporated into SOM models. The measured continuous SOM quality distributions should hold valuable information not only for model development, but also for direct interpretation. Measuring continuous distributions requires that the measurements along the quality variable are so frequent that the distribution approaches the underlying continuum. Continuous distributions lead to possible simplifications of the model formulations, which considerably reduce the number of parameters needed to describe SOM turnover. A general framework for SOM models representing SOM across measurable quality distributions is presented and simplifications for specific situations are discussed. Finally, methods that have been used or have the potential to be used to measure continuous quality SOM distributions are reviewed. Generally, existing fractionation methods will have to be modified to allow measurement of distributions or new fractionation techniques will have to be developed. Developing the distributional models in concert with the fractionation methods to measure the distributions will be a major task. We hope the current paper will help generate the interest needed to accommodate this.
Measuring and modelling continuous quality distributions of soil organic matter
NASA Astrophysics Data System (ADS)
Bruun, S.; Gren, G. I.; Christensen, B. T.; Jensen, L. S.
2009-09-01
An understanding of the dynamics of soil organic matter (SOM) is important for our ability to develop management practices that preserve soil quality and sequester carbon. Most SOM decomposition models represent the heterogeneity of organic matter by a few discrete compartments with different turnover rates, while other models employ a continuous quality distribution. To make the multi-compartment models more mechanistic in nature, it has been argued that the compartments should be related to soil fractions actually occurring and having a functional role in the soil. In this paper, we make the case that fractionation methods that can measure continuous quality distributions should be developed, and that the temporal development of these distributions should be incorporated into SOM models. The measured continuous SOM quality distributions should hold valuable information not only for model development, but also for direct interpretation. Measuring continuous distributions requires that the measurements along the quality variable are so frequent that the distribution is approaching the underlying continuum. Continuous distributions leads to possible simplifications of the model formulations, which considerably reduce the number of parameters needed to describe SOM turnover. A general framework for SOM models representing SOM across measurable quality distributions is presented and simplifications for specific situations are discussed. Finally, methods that have been used or have the potential to be used to measure continuous quality SOM distributions are reviewed. Generally, existing fractionation methods have to be modified to allow measurement of distributions or new fractionation techniques will have to be developed. Developing the distributional models in concert with the fractionation methods to measure the distributions will be a major task. We hope the current paper will help spawning the interest needed to accommodate this.
Vazquez-Leal, H.; Jimenez-Fernandez, V. M.; Benhammouda, B.; Filobello-Nino, U.; Sarmiento-Reyes, A.; Ramirez-Pinero, A.; Marin-Hernandez, A.; Huerta-Chua, J.
2014-01-01
We present a homotopy continuation method (HCM) for finding multiple operating points of nonlinear circuits composed of devices modelled by using piecewise linear (PWL) representations. We propose an adaptation of the modified spheres path tracking algorithm to trace the homotopy trajectories of PWL circuits. In order to assess the benefits of this proposal, four nonlinear circuits composed of piecewise linear modelled devices are analysed to determine their multiple operating points. The results show that HCM can find multiple solutions within a single homotopy trajectory. Furthermore, we take advantage of the fact that homotopy trajectories are PWL curves meant to replace the multidimensional interpolation and fine tuning stages of the path tracking algorithm with a simple and highly accurate procedure based on the parametric straight line equation. PMID:25184157
Vazquez-Leal, H; Jimenez-Fernandez, V M; Benhammouda, B; Filobello-Nino, U; Sarmiento-Reyes, A; Ramirez-Pinero, A; Marin-Hernandez, A; Huerta-Chua, J
2014-01-01
We present a homotopy continuation method (HCM) for finding multiple operating points of nonlinear circuits composed of devices modelled by using piecewise linear (PWL) representations. We propose an adaptation of the modified spheres path tracking algorithm to trace the homotopy trajectories of PWL circuits. In order to assess the benefits of this proposal, four nonlinear circuits composed of piecewise linear modelled devices are analysed to determine their multiple operating points. The results show that HCM can find multiple solutions within a single homotopy trajectory. Furthermore, we take advantage of the fact that homotopy trajectories are PWL curves meant to replace the multidimensional interpolation and fine tuning stages of the path tracking algorithm with a simple and highly accurate procedure based on the parametric straight line equation. PMID:25184157
Application of fractional derivative models in linear viscoelastic problems
NASA Astrophysics Data System (ADS)
Sasso, M.; Palmieri, G.; Amodio, D.
2011-11-01
Appropriate knowledge of viscoelastic properties of polymers and elastomers is of fundamental importance for a correct modelization and analysis of structures where such materials are present, especially when dealing with dynamic and vibration problems. In this paper experimental results of a series of compression and tension tests on specimens of styrene-butadiene rubber and polypropylene plastic are presented; tests consist of creep and relaxation tests, as well as cyclic loading at different frequencies. Experimental data are then used to calibrate some linear viscoelastic models; besides the classical approach based on a combination in series or parallel of standard mechanical elements as springs and dashpots, particular emphasis is given to the application of models whose constitutive equations are based on differential equations of fractional order (Fractional Derivative Model). The two approaches are compared analyzing their capability to reproduce all the experimental data for given materials; also, the main computational issues related with these models are addressed, and the advantage of using a limited number of parameters is demonstrated.
Electroweak corrections and unitarity in linear moose models
Chivukula, R. Sekhar; Simmons, Elizabeth H.; He, H.-J.; Kurachi, Masafumi; Tanabashi, Masaharu
2005-02-01
We calculate the form of the corrections to the electroweak interactions in the class of Higgsless models which can be deconstructed to a chain of SU(2) gauge groups adjacent to a chain of U(1) gauge groups, and with the fermions coupled to any single SU(2) group and to any single U(1) group along the chain. The primary advantage of our technique is that the size of corrections to electroweak processes can be directly related to the spectrum of vector bosons ('KK modes'). In Higgsless models, this spectrum is constrained by unitarity. Our methods also allow for arbitrary background 5D geometry, spatially dependent gauge-couplings, and brane kinetic energy terms. We find that, due to the size of corrections to electroweak processes in any unitary theory, Higgsless models with localized fermions are disfavored by precision electroweak data. Although we stress our results as they apply to continuum Higgsless 5D models, they apply to any linear moose model including those with only a few extra vector bosons. Our calculations of electroweak corrections also apply directly to the electroweak gauge sector of 5D theories with a bulk scalar Higgs boson; the constraints arising from unitarity do not apply in this case.
The Dantzig Selector for Censored Linear Regression Models
Li, Yi; Dicker, Lee; Zhao, Sihai Dave
2013-01-01
The Dantzig variable selector has recently emerged as a powerful tool for fitting regularized regression models. To our knowledge, most work involving the Dantzig selector has been performed with fully-observed response variables. This paper proposes a new class of adaptive Dantzig variable selectors for linear regression models when the response variable is subject to right censoring. This is motivated by a clinical study to identify genes predictive of event-free survival in newly diagnosed multiple myeloma patients. Under some mild conditions, we establish the theoretical properties of our procedures, including consistency in model selection (i.e. the right subset model will be identified with a probability tending to 1) and the optimal efficiency of estimation (i.e. the asymptotic distribution of the estimates is the same as that when the true subset model is known a priori). The practical utility of the proposed adaptive Dantzig selectors is verified via extensive simulations. We apply our new methods to the aforementioned myeloma clinical trial and identify important predictive genes. PMID:24478569