Modeling and Simulation of Linear and Nonlinear MEMS Scale Electromagnetic Energy Harvesters for Random Vibration Environments

PubMed Central

Sassani, Farrokh

2014-01-01

The simulation results for electromagnetic energy harvesters (EMEHs) under broad band stationary Gaussian random excitations indicate the importance of both a high transformation factor and a high mechanical quality factor to achieve favourable mean power, mean square load voltage, and output spectral density. The optimum load is different for random vibrations and for sinusoidal vibration. Reducing the total damping ratio under band-limited random excitation yields a higher mean square load voltage. Reduced bandwidth resulting from decreased mechanical damping can be compensated by increasing the electrical damping (transformation factor) leading to a higher mean square load voltage and power. Nonlinear EMEHs with a Duffing spring and with linear plus cubic damping are modeled using the method of statistical linearization. These nonlinear EMEHs exhibit approximately linear behaviour under low levels of broadband stationary Gaussian random vibration; however, at higher levels of such excitation the central (resonant) frequency of the spectral density of the output voltage shifts due to the increased nonlinear stiffness and the bandwidth broadens slightly. Nonlinear EMEHs exhibit lower maximum output voltage and central frequency of the spectral density with nonlinear damping compared to linear damping. Stronger nonlinear damping yields broader bandwidths at stable resonant frequency. PMID:24605063

A new look at the robust control of discrete-time Markov jump linear systems

NASA Astrophysics Data System (ADS)

Todorov, M. G.; Fragoso, M. D.

2016-03-01

In this paper, we make a foray in the role played by a set of four operators on the study of robust H2 and mixed H2/H∞ control problems for discrete-time Markov jump linear systems. These operators appear in the study of mean square stability for this class of systems. By means of new linear matrix inequality (LMI) characterisations of controllers, which include slack variables that, to some extent, separate the robustness and performance objectives, we introduce four alternative approaches to the design of controllers which are robustly stabilising and at the same time provide a guaranteed level of H2 performance. Since each operator provides a different degree of conservatism, the results are unified in the form of an iterative LMI technique for designing robust H2 controllers, whose convergence is attained in a finite number of steps. The method yields a new way of computing mixed H2/H∞ controllers, whose conservatism decreases with iteration. Two numerical examples illustrate the applicability of the proposed results for the control of a small unmanned aerial vehicle, and for an underactuated robotic arm.

Primary Stability Recognition of the Newly Designed Cementless Femoral Stem Using Digital Signal Processing

PubMed Central

Salleh, Sh-Hussain; Hamedi, Mahyar; Zulkifly, Ahmad Hafiz; Lee, Muhammad Hisyam; Mohd Noor, Alias; Harris, Arief Ruhullah A.; Abdul Majid, Norazman

2014-01-01

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing. PMID:24800230

Primary stability recognition of the newly designed cementless femoral stem using digital signal processing.

PubMed

Baharuddin, Mohd Yusof; Salleh, Sh-Hussain; Hamedi, Mahyar; Zulkifly, Ahmad Hafiz; Lee, Muhammad Hisyam; Mohd Noor, Alias; Harris, Arief Ruhullah A; Abdul Majid, Norazman

2014-01-01

Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing.

Stability of Capillary Surfaces in Rectangular Containers: The Right Square Cylinder

NASA Technical Reports Server (NTRS)

Weislogel, M. M.; Hsieh, K. C.

1998-01-01

The linearized governing equations for an ideal fluid are presented for numerical analysis for the stability of free capillary surfaces in rectangular containers against unfavorable disturbances (accelerations,i.e. Rayleigh-Taylor instability). The equations are solved for the case of the right square cylinder. The results are expressed graphically in term of a critical Bond number as a function of system contact angle. A critical wetting phenomena in the corners is shown to significantly alter the region of stability for such containers in contrast to simpler geometries such as the right circular cylinder or the infinite rectangular slot. Such computational results provide additional constraints for the design of fluids systems for space-based applications.

Prediction of atmospheric degradation data for POPs by gene expression programming.

PubMed

Luan, F; Si, H Z; Liu, H T; Wen, Y Y; Zhang, X Y

2008-01-01

Quantitative structure-activity relationship models for the prediction of the mean and the maximum atmospheric degradation half-life values of persistent organic pollutants were developed based on the linear heuristic method (HM) and non-linear gene expression programming (GEP). Molecular descriptors, calculated from the structures alone, were used to represent the characteristics of the compounds. HM was used both to pre-select the whole descriptor sets and to build the linear model. GEP yielded satisfactory prediction results: the square of the correlation coefficient r(2) was 0.80 and 0.81 for the mean and maximum half-life values of the test set, and the root mean square errors were 0.448 and 0.426, respectively. The results of this work indicate that the GEP is a very promising tool for non-linear approximations.

A Stochastic Total Least Squares Solution of Adaptive Filtering Problem

PubMed Central

Ahmad, Noor Atinah

2014-01-01

An efficient and computationally linear algorithm is derived for total least squares solution of adaptive filtering problem, when both input and output signals are contaminated by noise. The proposed total least mean squares (TLMS) algorithm is designed by recursively computing an optimal solution of adaptive TLS problem by minimizing instantaneous value of weighted cost function. Convergence analysis of the algorithm is given to show the global convergence of the proposed algorithm, provided that the stepsize parameter is appropriately chosen. The TLMS algorithm is computationally simpler than the other TLS algorithms and demonstrates a better performance as compared with the least mean square (LMS) and normalized least mean square (NLMS) algorithms. It provides minimum mean square deviation by exhibiting better convergence in misalignment for unknown system identification under noisy inputs. PMID:24688412

Composite Robust $$H_\\infty$$ Control for Uncertain Stochastic Nonlinear Systems with State Delay via Disturbance Observer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yunlong; Wang, Hong; Guo, Lei

Here in this note, the robust stochastic stabilization and robust H_infinity control problems are investigated for uncertain stochastic time-delay systems with nonlinearity and multiple disturbances. By estimating the disturbance, which can be described by an exogenous model, a composite hierarchical control scheme is proposed that integrates the output of the disturbance observer with state feedback control law. Sufficient conditions for the existence of the disturbance observer and composite hierarchical controller are established in terms of linear matrix inequalities, which ensure the mean-square asymptotic stability of the resulting closed-loop system and the disturbance attenuation. It has been shown that the disturbancemore » rejection performance can also be achieved. A numerical example is provided to show the potential of the proposed techniques and encouraging results have been obtained.« less

Composite Robust $$H_\\infty$$ Control for Uncertain Stochastic Nonlinear Systems with State Delay via Disturbance Observer

DOE PAGES

Liu, Yunlong; Wang, Hong; Guo, Lei

2018-03-26

Here in this note, the robust stochastic stabilization and robust H_infinity control problems are investigated for uncertain stochastic time-delay systems with nonlinearity and multiple disturbances. By estimating the disturbance, which can be described by an exogenous model, a composite hierarchical control scheme is proposed that integrates the output of the disturbance observer with state feedback control law. Sufficient conditions for the existence of the disturbance observer and composite hierarchical controller are established in terms of linear matrix inequalities, which ensure the mean-square asymptotic stability of the resulting closed-loop system and the disturbance attenuation. It has been shown that the disturbancemore » rejection performance can also be achieved. A numerical example is provided to show the potential of the proposed techniques and encouraging results have been obtained.« less

Myopia Stabilization and Associated Factors Among Participants in the Correction of Myopia Evaluation Trial (COMET)

PubMed Central

2013-01-01

Purpose. To use the Gompertz function to estimate the age and the amount of myopia at stabilization and to evaluate associated factors in the Correction of Myopia Evaluation Trial (COMET) cohort, a large ethnically diverse group of myopic children. Methods. The COMET enrolled 469 ethnically diverse children aged 6 to younger than 12 years with spherical equivalent refraction between −1.25 and −4.50 diopters (D). Noncycloplegic refraction was measured semiannually for 4 years and annually thereafter. Right eye data were fit to individual Gompertz functions in participants with at least 6 years of follow-up and at least seven refraction measurements over 11 years. Function parameters were estimated using a nonlinear least squares procedure. Associated factors were evaluated using linear regression. Results. In total, 426 participants (91%) had valid Gompertz curve fits. The mean (SD) age at myopia stabilization was 15.61 (4.17) years, and the mean (SD) amount of myopia at stabilization was −4.87 (2.01) D. Ethnicity (P < 0.0001) but not sex or the number of myopic parents was associated with the age at stabilization. Ethnicity (P = 0.02) and the number of myopic parents (P = 0.01) but not sex were associated with myopia magnitude at stabilization. At stabilization, African Americans were youngest (mean age, 13.82 years) and had the least myopia (mean, −4.36 D). Participants with two versus no myopic parents had approximately 1.00 D more myopia at stabilization. The age and the amount of myopia at stabilization were correlated (r = −0.60, P < 0.0001). Conclusions. The Gompertz function provides estimates of the age and the amount of myopia at stabilization in an ethnically diverse cohort. These findings should provide guidance on the time course of myopia and on decisions regarding the type and timing of interventions. PMID:24159085

Applying the methodology of Design of Experiments to stability studies: a Partial Least Squares approach for evaluation of drug stability.

PubMed

Jordan, Nika; Zakrajšek, Jure; Bohanec, Simona; Roškar, Robert; Grabnar, Iztok

2018-05-01

The aim of the present research is to show that the methodology of Design of Experiments can be applied to stability data evaluation, as they can be seen as multi-factor and multi-level experimental designs. Linear regression analysis is usually an approach for analyzing stability data, but multivariate statistical methods could also be used to assess drug stability during the development phase. Data from a stability study for a pharmaceutical product with hydrochlorothiazide (HCTZ) as an unstable drug substance was used as a case example in this paper. The design space of the stability study was modeled using Umetrics MODDE 10.1 software. We showed that a Partial Least Squares model could be used for a multi-dimensional presentation of all data generated in a stability study and for determination of the relationship among factors that influence drug stability. It might also be used for stability predictions and potentially for the optimization of the extent of stability testing needed to determine shelf life and storage conditions, which would be time and cost-effective for the pharmaceutical industry.

Chemical library subset selection algorithms: a unified derivation using spatial statistics.

PubMed

Hamprecht, Fred A; Thiel, Walter; van Gunsteren, Wilfred F

2002-01-01

If similar compounds have similar activity, rational subset selection becomes superior to random selection in screening for pharmacological lead discovery programs. Traditional approaches to this experimental design problem fall into two classes: (i) a linear or quadratic response function is assumed (ii) some space filling criterion is optimized. The assumptions underlying the first approach are clear but not always defendable; the second approach yields more intuitive designs but lacks a clear theoretical foundation. We model activity in a bioassay as realization of a stochastic process and use the best linear unbiased estimator to construct spatial sampling designs that optimize the integrated mean square prediction error, the maximum mean square prediction error, or the entropy. We argue that our approach constitutes a unifying framework encompassing most proposed techniques as limiting cases and sheds light on their underlying assumptions. In particular, vector quantization is obtained, in dimensions up to eight, in the limiting case of very smooth response surfaces for the integrated mean square error criterion. Closest packing is obtained for very rough surfaces under the integrated mean square error and entropy criteria. We suggest to use either the integrated mean square prediction error or the entropy as optimization criteria rather than approximations thereof and propose a scheme for direct iterative minimization of the integrated mean square prediction error. Finally, we discuss how the quality of chemical descriptors manifests itself and clarify the assumptions underlying the selection of diverse or representative subsets.

The influence of a prediction display on the quasi-linear describing function and remnant measured with an adaptive analog-pilot in a closed loop

NASA Technical Reports Server (NTRS)

Dey, D.

1972-01-01

The effect of a prediction display on the human transfer characteristics is explained with the aid of a quasi-linear model. The prediction display causes an increase of the gain factor and the lead factor, a diminishing of the lag factor and a decrease of the remnant. Altogether, these factors yield a smaller mean square value of the control deviation and a simultaneous decrease of the mean square value of the stick signal.

Finite-time synchronization of stochastic coupled neural networks subject to Markovian switching and input saturation.

PubMed

Selvaraj, P; Sakthivel, R; Kwon, O M

2018-06-07

This paper addresses the problem of finite-time synchronization of stochastic coupled neural networks (SCNNs) subject to Markovian switching, mixed time delay, and actuator saturation. In addition, coupling strengths of the SCNNs are characterized by mutually independent random variables. By utilizing a simple linear transformation, the problem of stochastic finite-time synchronization of SCNNs is converted into a mean-square finite-time stabilization problem of an error system. By choosing a suitable mode dependent switched Lyapunov-Krasovskii functional, a new set of sufficient conditions is derived to guarantee the finite-time stability of the error system. Subsequently, with the help of anti-windup control scheme, the actuator saturation risks could be mitigated. Moreover, the derived conditions help to optimize estimation of the domain of attraction by enlarging the contractively invariant set. Furthermore, simulations are conducted to exhibit the efficiency of proposed control scheme. Copyright © 2018 Elsevier Ltd. All rights reserved.

Non-fragile ?-? control for discrete-time stochastic nonlinear systems under event-triggered protocols

NASA Astrophysics Data System (ADS)

Sun, Ying; Ding, Derui; Zhang, Sunjie; Wei, Guoliang; Liu, Hongjian

2018-07-01

In this paper, the non-fragile ?-? control problem is investigated for a class of discrete-time stochastic nonlinear systems under event-triggered communication protocols, which determine whether the measurement output should be transmitted to the controller or not. The main purpose of the addressed problem is to design an event-based output feedback controller subject to gain variations guaranteeing the prescribed disturbance attenuation level described by the ?-? performance index. By utilizing the Lyapunov stability theory combined with S-procedure, a sufficient condition is established to guarantee both the exponential mean-square stability and the ?-? performance for the closed-loop system. In addition, with the help of the orthogonal decomposition, the desired controller parameter is obtained in terms of the solution to certain linear matrix inequalities. Finally, a simulation example is exploited to demonstrate the effectiveness of the proposed event-based controller design scheme.

Consensus seeking in a network of discrete-time linear agents with communication noises

NASA Astrophysics Data System (ADS)

Wang, Yunpeng; Cheng, Long; Hou, Zeng-Guang; Tan, Min; Zhou, Chao; Wang, Ming

2015-07-01

This paper studies the mean square consensus of discrete-time linear time-invariant multi-agent systems with communication noises. A distributed consensus protocol, which is composed of the agent's own state feedback and the relative states between the agent and its neighbours, is proposed. A time-varying consensus gain a[k] is applied to attenuate the effect of noises which inherits in the inaccurate measurement of relative states with neighbours. A polynomial, namely 'parameter polynomial', is constructed. And its coefficients are the parameters in the feedback gain vector of the proposed protocol. It turns out that the parameter polynomial plays an important role in guaranteeing the consensus of linear multi-agent systems. By the proposed protocol, necessary and sufficient conditions for mean square consensus are presented under different topology conditions: (1) if the communication topology graph has a spanning tree and every node in the graph has at least one parent node, then the mean square consensus can be achieved if and only if ∑∞k = 0a[k] = ∞, ∑∞k = 0a2[k] < ∞ and all roots of the parameter polynomial are in the unit circle; (2) if the communication topology graph has a spanning tree and there exits one node without any parent node (the leader-follower case), then the mean square consensus can be achieved if and only if ∑∞k = 0a[k] = ∞, limk → ∞a[k] = 0 and all roots of the parameter polynomial are in the unit circle; (3) if the communication topology graph does not have a spanning tree, then the mean square consensus can never be achieved. Finally, one simulation example on the multiple aircrafts system is provided to validate the theoretical analysis.

Application of quadratic optimization to supersonic inlet control.

NASA Technical Reports Server (NTRS)

Lehtinen, B.; Zeller, J. R.

1972-01-01

This paper describes the application of linear stochastic optimal control theory to the design of the control system for the air intake, the inlet, of a supersonic air-breathing propulsion system. The controls must maintain a stable inlet shock position in the presence of random airflow disturbances and prevent inlet unstart. Two different linear time invariant controllers are developed. One is designed to minimize a nonquadratic index, the expected frequency of inlet unstart, and the other is designed to minimize the mean square value of inlet shock motion. The quadratic equivalence principle is used to obtain a linear controller that minimizes the nonquadratic index. The two controllers are compared on the basis of unstart prevention, control effort requirements, and frequency response. It is concluded that while controls designed to minimize unstarts are desirable in that the index minimized is physically meaningful, computation time required is longer than for the minimum mean square shock position approach. The simpler minimum mean square shock position solution produced expected unstart frequency values which were not significantly larger than those of the nonquadratic solution.

EKF-Based Enhanced Performance Controller Design for Nonlinear Stochastic Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Yuyang; Zhang, Qichun; Wang, Hong

In this paper, a novel control algorithm is presented to enhance the performance of tracking property for a class of non-linear dynamic stochastic systems with unmeasurable variables. To minimize the entropy of tracking errors without changing the existing closed loop with PI controller, the enhanced performance loop is constructed based on the state estimation by extended Kalman Filter and the new controller is designed by full state feedback following this presented control algorithm. Besides, the conditions are obtained for the stability analysis in the mean square sense. In the end, the comparative simulation results are given to illustrate the effectivenessmore » of proposed control algorithm.« less

Two-dimensional motion of Brownian swimmers in linear flows.

PubMed

Sandoval, Mario; Jimenez, Alonso

2016-03-01

The motion of viruses and bacteria and even synthetic microswimmers can be affected by thermal fluctuations and by external flows. In this work, we study the effect of linear external flows and thermal fluctuations on the diffusion of those swimmers modeled as spherical active (self-propelled) particles moving in two dimensions. General formulae for their mean-square displacement under a general linear flow are presented. We also provide, at short and long times, explicit expressions for the mean-square displacement of a swimmer immersed in three canonical flows, namely, solid-body rotation, shear and extensional flows. These expressions can now be used to estimate the effect of external flows on the displacement of Brownian microswimmers. Finally, our theoretical results are validated by using Brownian dynamics simulations.

Sum-of-Squares-Based Region of Attraction Analysis for Gain-Scheduled Three-Loop Autopilot

NASA Astrophysics Data System (ADS)

Seo, Min-Won; Kwon, Hyuck-Hoon; Choi, Han-Lim

2018-04-01

A conventional method of designing a missile autopilot is to linearize the original nonlinear dynamics at several trim points, then to determine linear controllers for each linearized model, and finally implement gain-scheduling technique. The validation of such a controller is often based on linear system analysis for the linear closed-loop system at the trim conditions. Although this type of gain-scheduled linear autopilot works well in practice, validation based solely on linear analysis may not be sufficient to fully characterize the closed-loop system especially when the aerodynamic coefficients exhibit substantial nonlinearity with respect to the flight condition. The purpose of this paper is to present a methodology for analyzing the stability of a gain-scheduled controller in a setting close to the original nonlinear setting. The method is based on sum-of-squares (SOS) optimization that can be used to characterize the region of attraction of a polynomial system by solving convex optimization problems. The applicability of the proposed SOS-based methodology is verified on a short-period autopilot of a skid-to-turn missile.

An iterative technique to stabilize a linear time invariant multivariable system with output feedback

NASA Technical Reports Server (NTRS)

Sankaran, V.

1974-01-01

An iterative procedure for determining the constant gain matrix that will stabilize a linear constant multivariable system using output feedback is described. The use of this procedure avoids the transformation of variables which is required in other procedures. For the case in which the product of the output and input vector dimensions is greater than the number of states of the plant, general solution is given. In the case in which the states exceed the product of input and output vector dimensions, a least square solution which may not be stable in all cases is presented. The results are illustrated with examples.

Techniques for the Enhancement of Linear Predictive Speech Coding in Adverse Conditions

NASA Astrophysics Data System (ADS)

Wrench, Alan A.

Available from UMI in association with The British Library. Requires signed TDF. The Linear Prediction model was first applied to speech two and a half decades ago. Since then it has been the subject of intense research and continues to be one of the principal tools in the analysis of speech. Its mathematical tractability makes it a suitable subject for study and its proven success in practical applications makes the study worthwhile. The model is known to be unsuited to speech corrupted by background noise. This has led many researchers to investigate ways of enhancing the speech signal prior to Linear Predictive analysis. In this thesis this body of work is extended. The chosen application is low bit-rate (2.4 kbits/sec) speech coding. For this task the performance of the Linear Prediction algorithm is crucial because there is insufficient bandwidth to encode the error between the modelled speech and the original input. A review of the fundamentals of Linear Prediction and an independent assessment of the relative performance of methods of Linear Prediction modelling are presented. A new method is proposed which is fast and facilitates stability checking, however, its stability is shown to be unacceptably poorer than existing methods. A novel supposition governing the positioning of the analysis frame relative to a voiced speech signal is proposed and supported by observation. The problem of coding noisy speech is examined. Four frequency domain speech processing techniques are developed and tested. These are: (i) Combined Order Linear Prediction Spectral Estimation; (ii) Frequency Scaling According to an Aural Model; (iii) Amplitude Weighting Based on Perceived Loudness; (iv) Power Spectrum Squaring. These methods are compared with the Recursive Linearised Maximum a Posteriori method. Following on from work done in the frequency domain, a time domain implementation of spectrum squaring is developed. In addition, a new method of power spectrum estimation is developed based on the Minimum Variance approach. This new algorithm is shown to be closely related to Linear Prediction but produces slightly broader spectral peaks. Spectrum squaring is applied to both the new algorithm and standard Linear Prediction and their relative performance is assessed. (Abstract shortened by UMI.).

Determination of suitable drying curve model for bread moisture loss during baking

NASA Astrophysics Data System (ADS)

Soleimani Pour-Damanab, A. R.; Jafary, A.; Rafiee, S.

2013-03-01

This study presents mathematical modelling of bread moisture loss or drying during baking in a conventional bread baking process. In order to estimate and select the appropriate moisture loss curve equation, 11 different models, semi-theoretical and empirical, were applied to the experimental data and compared according to their correlation coefficients, chi-squared test and root mean square error which were predicted by nonlinear regression analysis. Consequently, of all the drying models, a Page model was selected as the best one, according to the correlation coefficients, chi-squared test, and root mean square error values and its simplicity. Mean absolute estimation error of the proposed model by linear regression analysis for natural and forced convection modes was 2.43, 4.74%, respectively.

A new finite element formulation for computational fluid dynamics. IX - Fourier analysis of space-time Galerkin/least-squares algorithms

NASA Technical Reports Server (NTRS)

Shakib, Farzin; Hughes, Thomas J. R.

1991-01-01

A Fourier stability and accuracy analysis of the space-time Galerkin/least-squares method as applied to a time-dependent advective-diffusive model problem is presented. Two time discretizations are studied: a constant-in-time approximation and a linear-in-time approximation. Corresponding space-time predictor multi-corrector algorithms are also derived and studied. The behavior of the space-time algorithms is compared to algorithms based on semidiscrete formulations.

Study of Interpolated Timing Recovery Phase-Locked Loop with Linearly Constrained Adaptive Prefilter for Higher-Density Optical Disc

NASA Astrophysics Data System (ADS)

Kajiwara, Yoshiyuki; Shiraishi, Junya; Kobayashi, Shoei; Yamagami, Tamotsu

2009-03-01

A digital phase-locked loop (PLL) with a linearly constrained adaptive filter (LCAF) has been studied for higher-linear-density optical discs. LCAF has been implemented before an interpolated timing recovery (ITR) PLL unit in order to improve the quality of phase error calculation by using an adaptively equalized partial response (PR) signal. Coefficient update of an asynchronous sampled adaptive FIR filter with a least-mean-square (LMS) algorithm has been constrained by a projection matrix in order to suppress the phase shift of the tap coefficients of the adaptive filter. We have developed projection matrices that are suitable for Blu-ray disc (BD) drive systems by numerical simulation. Results have shown the properties of the projection matrices. Then, we have designed the read channel system of the ITR PLL with an LCAF model on the FPGA board for experiments. Results have shown that the LCAF improves the tilt margins of 30 gigabytes (GB) recordable BD (BD-R) and 33 GB BD read-only memory (BD-ROM) with a sufficient LMS adaptation stability.

Enhanced Performance Controller Design for Stochastic Systems by Adding Extra State Estimation onto the Existing Closed Loop Control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Yuyang; Zhang, Qichun; Wang, Hong

To enhance the performance of the tracking property , this paper presents a novel control algorithm for a class of linear dynamic stochastic systems with unmeasurable states, where the performance enhancement loop is established based on Kalman filter. Without changing the existing closed loop with the PI controller, the compensative controller is designed to minimize the variances of the tracking errors using the estimated states and the propagation of state variances. Moreover, the stability of the closed-loop systems has been analyzed in the mean-square sense. A simulated example is included to show the effectiveness of the presented control algorithm, wheremore » encouraging results have been obtained.« less

Cross-flow vortex structure and transition measurements using multi-element hot films

NASA Technical Reports Server (NTRS)

Agarwal, Naval K.; Mangalam, Siva M.; Maddalon, Dal V.; Collier, Fayette S., Jr.

1991-01-01

An experiment on a 45-degree swept wing was conducted to study three-dimensional boundary-layer characteristics using surface-mounted, micro-thin, multi-element hot-film sensors. Cross-flow vortex structure and boundary-layer transition were measured from the simultaneously acquired signals of the hot films. Spanwise variation of the root-mean-square (RMS) hot-film signal show a local minima and maxima. The distance between two minima corresponds to the stationary cross-flow vortex wavelength and agrees with naphthalene flow-visualization results. The chordwise and spanwise variation of amplified traveling (nonstationary) cross-flow disturbance characteristics were measured as Reynolds number was varied. The frequency of the most amplified cross-flow disturbances agrees with linear stability theory.

The sampled-data consensus of multi-agent systems with probabilistic time-varying delays and packet losses

NASA Astrophysics Data System (ADS)

Sui, Xin; Yang, Yongqing; Xu, Xianyun; Zhang, Shuai; Zhang, Lingzhong

2018-02-01

This paper investigates the consensus of multi-agent systems with probabilistic time-varying delays and packet losses via sampled-data control. On the one hand, a Bernoulli-distributed white sequence is employed to model random packet losses among agents. On the other hand, a switched system is used to describe packet dropouts in a deterministic way. Based on the special property of the Laplacian matrix, the consensus problem can be converted into a stabilization problem of a switched system with lower dimensions. Some mean square consensus criteria are derived in terms of constructing an appropriate Lyapunov function and using linear matrix inequalities (LMIs). Finally, two numerical examples are given to show the effectiveness of the proposed method.

Relationships between digital signal processing and control and estimation theory

NASA Technical Reports Server (NTRS)

Willsky, A. S.

1978-01-01

Research areas associated with digital signal processing and control and estimation theory are identified. Particular attention is given to image processing, system identification problems (parameter identification, linear prediction, least squares, Kalman filtering), stability analyses (the use of the Liapunov theory, frequency domain criteria, passivity), and multiparameter systems, distributed processes, and random fields.

Postural stability in the elderly during sensory perturbations and dual tasking: the influence of refractive blur.

PubMed

Anand, Vijay; Buckley, John G; Scally, Andy; Elliott, David B

2003-07-01

To determine the influence of refractive blur on postural stability during somatosensory and vestibular system perturbation and dual tasking. Fifteen healthy, elderly subjects (mean age, 71 +/- 5 years), who had no history of falls and had normal vision, were recruited. Postural stability during standing was assessed using a force platform, and was determined as the root mean square (RMS) of the center of pressure (COP) signal in the anterior-posterior (A-P) and medial-lateral directions collected over a 30-second period. Data were collected under normal standing conditions and with somatosensory and vestibular system perturbations. Measurements were repeated with an additional physical and/or cognitive task. Postural stability was measured under conditions of binocular refractive blur of 0, 1, 2, 4, and 8 D and with eyes closed. The data were analyzed with a population-averaged linear model. The greatest increases in postural instability were due to disruptions of the somatosensory and vestibular systems. Increasing refractive blur caused increasing postural instability, and its effect was greater when the input from the other sensory systems was disrupted. Performing an additional cognitive and physical task increased A-P RMS COP further. All these detrimental effects on postural stability were cumulative. The findings highlight the multifactorial nature of postural stability and indicate why the elderly, many of whom have poor vision and musculoskeletal and central nervous system degeneration, are at greater risk of falling. The findings also highlight that standing instability in both normal and perturbed conditions was significantly increased with refractive blur. Correcting visual impairment caused by uncorrected refractive error could be a useful intervention strategy to help prevent falls and fall-related injuries in the elderly.

Functional Mixed Effects Model for Small Area Estimation.

PubMed

Maiti, Tapabrata; Sinha, Samiran; Zhong, Ping-Shou

2016-09-01

Functional data analysis has become an important area of research due to its ability of handling high dimensional and complex data structures. However, the development is limited in the context of linear mixed effect models, and in particular, for small area estimation. The linear mixed effect models are the backbone of small area estimation. In this article, we consider area level data, and fit a varying coefficient linear mixed effect model where the varying coefficients are semi-parametrically modeled via B-splines. We propose a method of estimating the fixed effect parameters and consider prediction of random effects that can be implemented using a standard software. For measuring prediction uncertainties, we derive an analytical expression for the mean squared errors, and propose a method of estimating the mean squared errors. The procedure is illustrated via a real data example, and operating characteristics of the method are judged using finite sample simulation studies.

Ball-morph: definition, implementation, and comparative evaluation.

PubMed

Whited, Brian; Rossignac, Jaroslaw Jarek

2011-06-01

We define b-compatibility for planar curves and propose three ball morphing techniques between pairs of b-compatible curves. Ball-morphs use the automatic ball-map correspondence, proposed by Chazal et al., from which we derive different vertex trajectories (linear, circular, and parabolic). All three morphs are symmetric, meeting both curves with the same angle, which is a right angle for the circular and parabolic. We provide simple constructions for these ball-morphs and compare them to each other and other simple morphs (linear-interpolation, closest-projection, curvature-interpolation, Laplace-blending, and heat-propagation) using six cost measures (travel-distance, distortion, stretch, local acceleration, average squared mean curvature, and maximum squared mean curvature). The results depend heavily on the input curves. Nevertheless, we found that the linear ball-morph has consistently the shortest travel-distance and the circular ball-morph has the least amount of distortion.

Quadcopter Path Following Control Design Using Output Feedback with Command Generator Tracker LOS Based At Square Path

NASA Astrophysics Data System (ADS)

Nugraha, A. T.; Agustinah, T.

2018-01-01

Quadcopter an unstable system, underactuated and nonlinear in quadcopter control research developments become an important focus of attention. In this study, following the path control method for position on the X and Y axis, used structure-Generator Tracker Command (CGT) is tested. Attitude control and position feedback quadcopter is compared using the optimal output. The addition of the H∞ performance optimal output feedback control is used to maintain the stability and robustness of quadcopter. Iterative numerical techniques Linear Matrix Inequality (LMI) is used to find the gain controller. The following path control problems is solved using the method of LQ regulators with output feedback. Simulations show that the control system can follow the paths that have been defined in the form of a reference signal square shape. The result of the simulation suggest that the method which used can bring the yaw angle at the expected value algorithm. Quadcopter can do automatically following path with cross track error mean X=0.5 m and Y=0.2 m.

Ratio manipulating spectrophotometry versus chemometry as stability indicating methods for cefquinome sulfate determination

NASA Astrophysics Data System (ADS)

Yehia, Ali M.; Arafa, Reham M.; Abbas, Samah S.; Amer, Sawsan M.

2016-01-01

Spectral resolution of cefquinome sulfate (CFQ) in the presence of its degradation products was studied. Three selective, accurate and rapid spectrophotometric methods were performed for the determination of CFQ in the presence of either its hydrolytic, oxidative or photo-degradation products. The proposed ratio difference, derivative ratio and mean centering are ratio manipulating spectrophotometric methods that were satisfactorily applied for selective determination of CFQ within linear range of 5.0-40.0 μg mL- 1. Concentration Residuals Augmented Classical Least Squares was applied and evaluated for the determination of the cited drug in the presence of its all degradation products. Traditional Partial Least Squares regression was also applied and benchmarked against the proposed advanced multivariate calibration. Experimentally designed 25 synthetic mixtures of three factors at five levels were used to calibrate and validate the multivariate models. Advanced chemometrics succeeded in quantitative and qualitative analyses of CFQ along with its hydrolytic, oxidative and photo-degradation products. The proposed methods were applied successfully for different pharmaceutical formulations analyses. These developed methods were simple and cost-effective compared with the manufacturer's RP-HPLC method.

Bivariate random-effects meta-analysis models for diagnostic test accuracy studies using arcsine-based transformations.

PubMed

Negeri, Zelalem F; Shaikh, Mateen; Beyene, Joseph

2018-05-11

Diagnostic or screening tests are widely used in medical fields to classify patients according to their disease status. Several statistical models for meta-analysis of diagnostic test accuracy studies have been developed to synthesize test sensitivity and specificity of a diagnostic test of interest. Because of the correlation between test sensitivity and specificity, modeling the two measures using a bivariate model is recommended. In this paper, we extend the current standard bivariate linear mixed model (LMM) by proposing two variance-stabilizing transformations: the arcsine square root and the Freeman-Tukey double arcsine transformation. We compared the performance of the proposed methods with the standard method through simulations using several performance measures. The simulation results showed that our proposed methods performed better than the standard LMM in terms of bias, root mean square error, and coverage probability in most of the scenarios, even when data were generated assuming the standard LMM. We also illustrated the methods using two real data sets. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Robust Bayesian linear regression with application to an analysis of the CODATA values for the Planck constant

NASA Astrophysics Data System (ADS)

Wübbeler, Gerd; Bodnar, Olha; Elster, Clemens

2018-02-01

Weighted least-squares estimation is commonly applied in metrology to fit models to measurements that are accompanied with quoted uncertainties. The weights are chosen in dependence on the quoted uncertainties. However, when data and model are inconsistent in view of the quoted uncertainties, this procedure does not yield adequate results. When it can be assumed that all uncertainties ought to be rescaled by a common factor, weighted least-squares estimation may still be used, provided that a simple correction of the uncertainty obtained for the estimated model is applied. We show that these uncertainties and credible intervals are robust, as they do not rely on the assumption of a Gaussian distribution of the data. Hence, common software for weighted least-squares estimation may still safely be employed in such a case, followed by a simple modification of the uncertainties obtained by that software. We also provide means of checking the assumptions of such an approach. The Bayesian regression procedure is applied to analyze the CODATA values for the Planck constant published over the past decades in terms of three different models: a constant model, a straight line model and a spline model. Our results indicate that the CODATA values may not have yet stabilized.

A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

NASA Astrophysics Data System (ADS)

Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

2018-04-01

In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

Anodic Oxidation of Etodolac and its Linear Sweep, Square Wave and Differential Pulse Voltammetric Determination in Pharmaceuticals

PubMed Central

Yilmaz, B.; Kaban, S.; Akcay, B. K.

2015-01-01

In this study, simple, fast and reliable cyclic voltammetry, linear sweep voltammetry, square wave voltammetry and differential pulse voltammetry methods were developed and validated for determination of etodolac in pharmaceutical preparations. The proposed methods were based on electrochemical oxidation of etodolac at platinum electrode in acetonitrile solution containing 0.1 M lithium perchlorate. The well-defined oxidation peak was observed at 1.03 V. The calibration curves were linear for etodolac at the concentration range of 2.5-50 μg/ml for linear sweep, square wave and differential pulse voltammetry methods, respectively. Intra- and inter-day precision values for etodolac were less than 4.69, and accuracy (relative error) was better than 2.00%. The mean recovery of etodolac was 100.6% for pharmaceutical preparations. No interference was found from three tablet excipients at the selected assay conditions. Developed methods in this study are accurate, precise and can be easily applied to Etol, Tadolak and Etodin tablets as pharmaceutical preparation. PMID:26664057

State Estimation for Linear Systems Driven Simultaneously by Wiener and Poisson Processes.

DTIC Science & Technology

1978-12-01

The state estimation problem of linear stochastic systems driven simultaneously by Wiener and Poisson processes is considered, especially the case...where the incident intensities of the Poisson processes are low and the system is observed in an additive white Gaussian noise. The minimum mean squared

The mean-square error optimal linear discriminant function and its application to incomplete data vectors

NASA Technical Reports Server (NTRS)

Walker, H. F.

1979-01-01

In many pattern recognition problems, data vectors are classified although one or more of the data vector elements are missing. This problem occurs in remote sensing when the ground is obscured by clouds. Optimal linear discrimination procedures for classifying imcomplete data vectors are discussed.

Sea surface mean square slope from Ku-band backscatter data

NASA Technical Reports Server (NTRS)

Jackson, F. C.; Walton, W. T.; Hines, D. E.; Walter, B. A.; Peng, C. Y.

1992-01-01

A surface mean-square-slope parameter analysis is conducted for 14-GHz airborne radar altimeter near-nadir, quasi-specular backscatter data, which in raw form obtained by least-squares fitting of an optical scattering model to the return waveform show an approximately linear dependence over the 7-15 m/sec wind speed range. Slope data are used to draw inferences on the structure of the high-wavenumber portion of the spectrum. A directionally-integrated model height spectrum that encompasses wind speed-dependent k exp -5/2 and classical Phillips k exp -3 power laws subranges in the range of gravity waves is supported by the data.

The modelling of lead removal from water by deep eutectic solvents functionalized CNTs: artificial neural network (ANN) approach.

PubMed

Fiyadh, Seef Saadi; AlSaadi, Mohammed Abdulhakim; AlOmar, Mohamed Khalid; Fayaed, Sabah Saadi; Hama, Ako R; Bee, Sharifah; El-Shafie, Ahmed

2017-11-01

The main challenge in the lead removal simulation is the behaviour of non-linearity relationships between the process parameters. The conventional modelling technique usually deals with this problem by a linear method. The substitute modelling technique is an artificial neural network (ANN) system, and it is selected to reflect the non-linearity in the interaction among the variables in the function. Herein, synthesized deep eutectic solvents were used as a functionalized agent with carbon nanotubes as adsorbents of Pb 2+ . Different parameters were used in the adsorption study including pH (2.7 to 7), adsorbent dosage (5 to 20 mg), contact time (3 to 900 min) and Pb 2+ initial concentration (3 to 60 mg/l). The number of experimental trials to feed and train the system was 158 runs conveyed in laboratory scale. Two ANN types were designed in this work, the feed-forward back-propagation and layer recurrent; both methods are compared based on their predictive proficiency in terms of the mean square error (MSE), root mean square error, relative root mean square error, mean absolute percentage error and determination coefficient (R 2 ) based on the testing dataset. The ANN model of lead removal was subjected to accuracy determination and the results showed R 2 of 0.9956 with MSE of 1.66 × 10 -4 . The maximum relative error is 14.93% for the feed-forward back-propagation neural network model.

A Simulation-Based Comparison of Several Stochastic Linear Regression Methods in the Presence of Outliers.

ERIC Educational Resources Information Center

Rule, David L.

Several regression methods were examined within the framework of weighted structural regression (WSR), comparing their regression weight stability and score estimation accuracy in the presence of outlier contamination. The methods compared are: (1) ordinary least squares; (2) WSR ridge regression; (3) minimum risk regression; (4) minimum risk 2;…

[Quantitative relationship between gas chromatographic retention time and structural parameters of alkylphenols].

PubMed

Ruan, Xiaofang; Zhang, Ruisheng; Yao, Xiaojun; Liu, Mancang; Fan, Botao

2007-03-01

Alkylphenols are a group of permanent pollutants in the environment and could adversely disturb the human endocrine system. It is therefore important to effectively separate and measure the alkylphenols. To guide the chromatographic analysis of these compounds in practice, the development of quantitative relationship between the molecular structure and the retention time of alkylphenols becomes necessary. In this study, topological, constitutional, geometrical, electrostatic and quantum-chemical descriptors of 44 alkylphenols were calculated using a software, CODESSA, and these descriptors were pre-selected using the heuristic method. As a result, three-descriptor linear model (LM) was developed to describe the relationship between the molecular structure and the retention time of alkylphenols. Meanwhile, the non-linear regression model was also developed based on support vector machine (SVM) using the same three descriptors. The correlation coefficient (R(2)) for the LM and SVM was 0.98 and 0. 92, and the corresponding root-mean-square error was 0. 99 and 2. 77, respectively. By comparing the stability and prediction ability of the two models, it was found that the linear model was a better method for describing the quantitative relationship between the retention time of alkylphenols and the molecular structure. The results obtained suggested that the linear model could be applied for the chromatographic analysis of alkylphenols with known molecular structural parameters.

Analysis and application of minimum variance discrete time system identification

NASA Technical Reports Server (NTRS)

Kaufman, H.; Kotob, S.

1975-01-01

An on-line minimum variance parameter identifier is developed which embodies both accuracy and computational efficiency. The formulation results in a linear estimation problem with both additive and multiplicative noise. The resulting filter which utilizes both the covariance of the parameter vector itself and the covariance of the error in identification is proven to be mean square convergent and mean square consistent. The MV parameter identification scheme is then used to construct a stable state and parameter estimation algorithm.

Squared ligament of the elbow: anatomy and contribution to forearm stability.

PubMed

Otayek, Salma; Tayeb, Abd-el-Kader Ait; Assabah, Bouchra; Viard, Brice; Dayan, Romain; Lazure, Thierry; Soubeyrand, Marc

2016-03-01

The present study describes the macroscopic and microscopic features of the squared ligament of the elbow (SLE). In addition, the SLE biomechanical behavior and contribution to the forearm stability were also examined. Ten forearms from freshly frozen cadavers were used for this work. Each forearm was mounted in an experimental frame for quantification of longitudinal and transverse stability. Macroscopic features and biomechanical behavior were analyzed on dynamic videos obtained during forearm rotation. Then, the SLE was harvested from the 10 forearms for microscopic analysis on histological slices stained with hematoxylin-eosin-saffron. Two main SLE configurations were identified. One in which the SLE had three distinct bundles (anterior, middle, posterior) and another in which it was homogeneous. The anterior part of the SLE had a mean length of 11.2 mm (±2.4 mm) and a mean width of 1.2 mm (±0.2 mm) while the posterior part had a mean length of 9.9 mm (±2.2 mm) and a mean width of 1 mm (±0.2 mm). Microscopic examination showed that the SLE is composed of a thin layer of arranged collagen fibers. During forearm rotation, the SLE progressively tightens upon pronation and supination by wrapping around the radial neck. Tightening of the SLE during forearm rotation provides transverse and longitudinal stability to the forearm, mainly in maximal pronation and supination. The SLE is a true ligament and provides forearm stability when it is stretched in pronation and supination.

An efficient method for model refinement in diffuse optical tomography

NASA Astrophysics Data System (ADS)

Zirak, A. R.; Khademi, M.

2007-11-01

Diffuse optical tomography (DOT) is a non-linear, ill-posed, boundary value and optimization problem which necessitates regularization. Also, Bayesian methods are suitable owing to measurements data are sparse and correlated. In such problems which are solved with iterative methods, for stabilization and better convergence, the solution space must be small. These constraints subject to extensive and overdetermined system of equations which model retrieving criteria specially total least squares (TLS) must to refine model error. Using TLS is limited to linear systems which is not achievable when applying traditional Bayesian methods. This paper presents an efficient method for model refinement using regularized total least squares (RTLS) for treating on linearized DOT problem, having maximum a posteriori (MAP) estimator and Tikhonov regulator. This is done with combination Bayesian and regularization tools as preconditioner matrices, applying them to equations and then using RTLS to the resulting linear equations. The preconditioning matrixes are guided by patient specific information as well as a priori knowledge gained from the training set. Simulation results illustrate that proposed method improves the image reconstruction performance and localize the abnormally well.

Stabilization of the Inverse Laplace Transform of Multiexponential Decay through Introduction of a Second Dimension

PubMed Central

Celik, Hasan; Bouhrara, Mustapha; Reiter, David A.; Fishbein, Kenneth W.; Spencer, Richard G.

2013-01-01

We propose a new approach to stabilizing the inverse Laplace transform of a multiexponential decay signal, a classically ill-posed problem, in the context of nuclear magnetic resonance relaxometry. The method is based on extension to a second, indirectly detected, dimension, that is, use of the established framework of two-dimensional relaxometry, followed by projection onto the desired axis. Numerical results for signals comprised of discrete T1 and T2 relaxation components and experiments performed on agarose gel phantoms are presented. We find markedly improved accuracy, and stability with respect to noise, as well as insensitivity to regularization in quantifying underlying relaxation components through use of the two-dimensional as compared to the one-dimensional inverse Laplace transform. This improvement is demonstrated separately for two different inversion algorithms, nonnegative least squares and non-linear least squares, to indicate the generalizability of this approach. These results may have wide applicability in approaches to the Fredholm integral equation of the first kind. PMID:24035004

Fourier transform infrared reflectance spectra of latent fingerprints: a biometric gauge for the age of an individual.

PubMed

Hemmila, April; McGill, Jim; Ritter, David

2008-03-01

To determine if changes in fingerprint infrared spectra linear with age can be found, partial least squares (PLS1) regression of 155 fingerprint infrared spectra against the person's age was constructed. The regression produced a linear model of age as a function of spectrum with a root mean square error of calibration of less than 4 years, showing an inflection at about 25 years of age. The spectral ranges emphasized by the regression do not correspond to the highest concentration constituents of the fingerprints. Separate linear regression models for old and young people can be constructed with even more statistical rigor. The success of the regression demonstrates that a combination of constituents can be found that changes linearly with age, with a significant shift around puberty.

Low-Temperature Crystal Structures of the Hard Core Square Shoulder Model.

PubMed

Gabriëlse, Alexander; Löwen, Hartmut; Smallenburg, Frank

2017-11-07

In many cases, the stability of complex structures in colloidal systems is enhanced by a competition between different length scales. Inspired by recent experiments on nanoparticles coated with polymers, we use Monte Carlo simulations to explore the types of crystal structures that can form in a simple hard-core square shoulder model that explicitly incorporates two favored distances between the particles. To this end, we combine Monte Carlo-based crystal structure finding algorithms with free energies obtained using a mean-field cell theory approach, and draw phase diagrams for two different values of the square shoulder width as a function of the density and temperature. Moreover, we map out the zero-temperature phase diagram for a broad range of shoulder widths. Our results show the stability of a rich variety of crystal phases, such as body-centered orthogonal (BCO) lattices not previously considered for the square shoulder model.

Design of adaptive control systems by means of self-adjusting transversal filters

NASA Technical Reports Server (NTRS)

Merhav, S. J.

1986-01-01

The design of closed-loop adaptive control systems based on nonparametric identification was addressed. Implementation is by self-adjusting Least Mean Square (LMS) transversal filters. The design concept is Model Reference Adaptive Control (MRAC). Major issues are to preserve the linearity of the error equations of each LMS filter, and to prevent estimation bias that is due to process or measurement noise, thus providing necessary conditions for the convergence and stability of the control system. The controlled element is assumed to be asymptotically stable and minimum phase. Because of the nonparametric Finite Impulse Response (FIR) estimates provided by the LMS filters, a-priori information on the plant model is needed only in broad terms. Following a survey of control system configurations and filter design considerations, system implementation is shown here in Single Input Single Output (SISO) format which is readily extendable to multivariable forms. In extensive computer simulation studies the controlled element is represented by a second-order system with widely varying damping, natural frequency, and relative degree.

Parameter estimation of Monod model by the Least-Squares method for microalgae Botryococcus Braunii sp

NASA Astrophysics Data System (ADS)

See, J. J.; Jamaian, S. S.; Salleh, R. M.; Nor, M. E.; Aman, F.

2018-04-01

This research aims to estimate the parameters of Monod model of microalgae Botryococcus Braunii sp growth by the Least-Squares method. Monod equation is a non-linear equation which can be transformed into a linear equation form and it is solved by implementing the Least-Squares linear regression method. Meanwhile, Gauss-Newton method is an alternative method to solve the non-linear Least-Squares problem with the aim to obtain the parameters value of Monod model by minimizing the sum of square error ( SSE). As the result, the parameters of the Monod model for microalgae Botryococcus Braunii sp can be estimated by the Least-Squares method. However, the estimated parameters value obtained by the non-linear Least-Squares method are more accurate compared to the linear Least-Squares method since the SSE of the non-linear Least-Squares method is less than the linear Least-Squares method.

Linear response to nonstationary random excitation.

NASA Technical Reports Server (NTRS)

Hasselman, T.

1972-01-01

Development of a method for computing the mean-square response of linear systems to nonstationary random excitation of the form given by y(t) = f(t) x(t), in which x(t) = a stationary process and f(t) is deterministic. The method is suitable for application to multidegree-of-freedom systems when the mean-square response at a point due to excitation applied at another point is desired. Both the stationary process, x(t), and the modulating function, f(t), may be arbitrary. The method utilizes a fundamental component of transient response dependent only on x(t) and the system, and independent of f(t) to synthesize the total response. The role played by this component is analogous to that played by the Green's function or impulse response function in the convolution integral.

On the null distribution of Bayes factors in linear regression

USDA-ARS?s Scientific Manuscript database

We show that under the null, the 2 log (Bayes factor) is asymptotically distributed as a weighted sum of chi-squared random variables with a shifted mean. This claim holds for Bayesian multi-linear regression with a family of conjugate priors, namely, the normal-inverse-gamma prior, the g-prior, and...

EVALUATING PREDICTIVE ERRORS OF A COMPLEX ENVIRONMENTAL MODEL USING A GENERAL LINEAR MODEL AND LEAST SQUARE MEANS

EPA Science Inventory

A General Linear Model (GLM) was used to evaluate the deviation of predicted values from expected values for a complex environmental model. For this demonstration, we used the default level interface of the Regional Mercury Cycling Model (R-MCM) to simulate epilimnetic total mer...

Stabilization of flow past a rounded cylinder

NASA Astrophysics Data System (ADS)

Samtaney, Ravi; Zhang, Wei

2016-11-01

We perform global linear stability analysis on low-Re flow past a rounded cylinder. The cylinder corners are rounded with a radius R, normalized as R+ = R / D where D is the cylinder diameter, and its effect on the flow stability characteristics is investigated. We compute the critical Reynolds number (Recr) for the onset of first instability, and quantify the perturbation growth rate for the super-critical flows. It is found that the flow can be stabilized by partially rounding the cylinder. Compared with the square and circular cylinders, the partially rounded cylinder has a higher Recr , attaining a maximum at around R+ = 0 . 30 , and the perturbation growth rate of the super-critical flows is reduced for Re <= 100 . We perform sensitivity analysis to explore the source of the stabilization. The growth rate sensitivity to base flow modification has two different spatial structures: the growth rate is sensitive to the wake backflow in a large region for square-like cylinders (R+ -> 0 . 00), while only the near-wake backflow is crucial for circular-like cylinders (R+ -> 0 . 50). The stability analysis results are also verified with those of the direct simulations and very good agreement is achieved. Supported by the KAUST Office of Competitive Research Funds under Award No. URF/1/1394-01. The supercomputer Shaheen at KAUST was utilized for the simulations.

Superresolution restoration of an image sequence: adaptive filtering approach.

PubMed

Elad, M; Feuer, A

1999-01-01

This paper presents a new method based on adaptive filtering theory for superresolution restoration of continuous image sequences. The proposed methodology suggests least squares (LS) estimators which adapt in time, based on adaptive filters, least mean squares (LMS) or recursive least squares (RLS). The adaptation enables the treatment of linear space and time-variant blurring and arbitrary motion, both of them assumed known. The proposed new approach is shown to be of relatively low computational requirements. Simulations demonstrating the superresolution restoration algorithms are presented.

Portent of Heine's Reciprocal Square Root Identity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cohl, H W

Precise efforts in theoretical astrophysics are needed to fully understand the mechanisms that govern the structure, stability, dynamics, formation, and evolution of differentially rotating stars. Direct computation of the physical attributes of a star can be facilitated by the use of highly compact azimuthal and separation angle Fourier formulations of the Green's functions for the linear partial differential equations of mathematical physics.

Vehicular traffic noise prediction using soft computing approach.

PubMed

Singh, Daljeet; Nigam, S P; Agrawal, V P; Kumar, Maneek

2016-12-01

A new approach for the development of vehicular traffic noise prediction models is presented. Four different soft computing methods, namely, Generalized Linear Model, Decision Trees, Random Forests and Neural Networks, have been used to develop models to predict the hourly equivalent continuous sound pressure level, Leq, at different locations in the Patiala city in India. The input variables include the traffic volume per hour, percentage of heavy vehicles and average speed of vehicles. The performance of the four models is compared on the basis of performance criteria of coefficient of determination, mean square error and accuracy. 10-fold cross validation is done to check the stability of the Random Forest model, which gave the best results. A t-test is performed to check the fit of the model with the field data. Copyright © 2016 Elsevier Ltd. All rights reserved.

Adaptive Neural Output Feedback Control for Nonstrict-Feedback Stochastic Nonlinear Systems With Unknown Backlash-Like Hysteresis and Unknown Control Directions.

PubMed

Yu, Zhaoxu; Li, Shugang; Yu, Zhaosheng; Li, Fangfei

2018-04-01

This paper investigates the problem of output feedback adaptive stabilization for a class of nonstrict-feedback stochastic nonlinear systems with both unknown backlashlike hysteresis and unknown control directions. A new linear state transformation is applied to the original system, and then, control design for the new system becomes feasible. By combining the neural network's (NN's) parameterization, variable separation technique, and Nussbaum gain function method, an input-driven observer-based adaptive NN control scheme, which involves only one parameter to be updated, is developed for such systems. All closed-loop signals are bounded in probability and the error signals remain semiglobally bounded in the fourth moment (or mean square). Finally, the effectiveness and the applicability of the proposed control design are verified by two simulation examples.

Subharmonic response of a single-degree-of-freedom nonlinear vibro-impact system to a narrow-band random excitation.

PubMed

Haiwu, Rong; Wang, Xiangdong; Xu, Wei; Fang, Tong

2009-08-01

The subharmonic response of single-degree-of-freedom nonlinear vibro-impact oscillator with a one-sided barrier to narrow-band random excitation is investigated. The narrow-band random excitation used here is a filtered Gaussian white noise. The analysis is based on a special Zhuravlev transformation, which reduces the system to one without impacts, or velocity jumps, thereby permitting the applications of asymptotic averaging over the "fast" variables. The averaged stochastic equations are solved exactly by the method of moments for the mean-square response amplitude for the case of linear system with zero offset. A perturbation-based moment closure scheme is proposed and the formula of the mean-square amplitude is obtained approximately for the case of linear system with nonzero offset. The perturbation-based moment closure scheme is used once again to obtain the algebra equation of the mean-square amplitude of the response for the case of nonlinear system. The effects of damping, detuning, nonlinear intensity, bandwidth, and magnitudes of random excitations are analyzed. The theoretical analyses are verified by numerical results. Theoretical analyses and numerical simulations show that the peak amplitudes may be strongly reduced at large detunings or large nonlinear intensity.

Role of assessment tests in the stability of intelligence scoring of pre-school children with uneven/delayed cognitive profile.

PubMed

Yang, P; Jong, Y-J; Hsu, H-Y; Lung, F-W

2011-05-01

As part of an ongoing clinical service programme for pre-school children with developmental delay in an Asian developing country, we analysed the effect of three assessment tests, that is, Bayley Scale of Infant Development-II, Leiter International Performance Scale - Revised and Wechsler Preschool and Primary Scale of Intelligence - Revised - Chinese, on the stability of intelligence quotient (IQ) of children from pre-school through early childhood. The participants were 313 Taiwanese pre-school children with uneven or delayed cognitive profile and they were followed through early childhood. IQ stability was explored by different tests and among children of different clinical diagnosis: 168 children with non-autistic intellectual disability, 73 children with autism spectrum disorder, 58 children with mixed receptive-expressive language disorder and 14 children of other heterogeneous diagnoses. Stability of scores was evaluated using the r-squared for Pearson's coefficients to see the correlation between initial IQ (IQ1) and follow-up IQ (IQ2). Multiple linear regressions were also applied to see whether IQ1 had predictive ability for IQ2 and test-test difference in the total 313 children and each diagnostic subgroup. Results revealed that mean IQ1 was 65.8 ± 15.4 while mean IQ2 was 73.2 ± 17.9 for the total 313 children. The IQs were stable across an average follow-up duration of 38.6 ± 22.1 month from pre-school into early childhood. Patterns of positive correlations between IQ1 and IQ2 were noted by all the tests (r-squared = 0.43-0.5, all P < 0.001) and in the majority of diagnostic subgroups. Multiple regressions analysis also revealed that IQ1 could predict IQ2 significantly in all the tests (all P < 0.001). After careful choice of appropriate initial test, stability of IQ in children with developmental delay was noted from pre-school through early childhood. In addition, the translated version of cognitive assessment was valid for the required context of an Asian developing country. With the current emphasis on early identification and intervention for pre-school children with developmental delay, this information bears merit in clinical practice. © 2011 The Authors. Journal of Intellectual Disability Research © 2011 Blackwell Publishing Ltd.

A method for obtaining reduced-order control laws for high-order systems using optimization techniques

NASA Technical Reports Server (NTRS)

Mukhopadhyay, V.; Newsom, J. R.; Abel, I.

1981-01-01

A method of synthesizing reduced-order optimal feedback control laws for a high-order system is developed. A nonlinear programming algorithm is employed to search for the control law design variables that minimize a performance index defined by a weighted sum of mean-square steady-state responses and control inputs. An analogy with the linear quadractic Gaussian solution is utilized to select a set of design variables and their initial values. To improve the stability margins of the system, an input-noise adjustment procedure is used in the design algorithm. The method is applied to the synthesis of an active flutter-suppression control law for a wind tunnel model of an aeroelastic wing. The reduced-order controller is compared with the corresponding full-order controller and found to provide nearly optimal performance. The performance of the present method appeared to be superior to that of two other control law order-reduction methods. It is concluded that by using the present algorithm, nearly optimal low-order control laws with good stability margins can be synthesized.

Quantum State Tomography via Linear Regression Estimation

PubMed Central

Qi, Bo; Hou, Zhibo; Li, Li; Dong, Daoyi; Xiang, Guoyong; Guo, Guangcan

2013-01-01

A simple yet efficient state reconstruction algorithm of linear regression estimation (LRE) is presented for quantum state tomography. In this method, quantum state reconstruction is converted into a parameter estimation problem of a linear regression model and the least-squares method is employed to estimate the unknown parameters. An asymptotic mean squared error (MSE) upper bound for all possible states to be estimated is given analytically, which depends explicitly upon the involved measurement bases. This analytical MSE upper bound can guide one to choose optimal measurement sets. The computational complexity of LRE is O(d4) where d is the dimension of the quantum state. Numerical examples show that LRE is much faster than maximum-likelihood estimation for quantum state tomography. PMID:24336519

Effective Surfactants Blend Concentration Determination for O/W Emulsion Stabilization by Two Nonionic Surfactants by Simple Linear Regression.

PubMed

Hassan, A K

2015-01-01

In this work, O/W emulsion sets were prepared by using different concentrations of two nonionic surfactants. The two surfactants, tween 80(HLB=15.0) and span 80(HLB=4.3) were used in a fixed proportions equal to 0.55:0.45 respectively. HLB value of the surfactants blends were fixed at 10.185. The surfactants blend concentration is starting from 3% up to 19%. For each O/W emulsion set the conductivity was measured at room temperature (25±2°), 40, 50, 60, 70 and 80°. Applying the simple linear regression least squares method statistical analysis to the temperature-conductivity obtained data determines the effective surfactants blend concentration required for preparing the most stable O/W emulsion. These results were confirmed by applying the physical stability centrifugation testing and the phase inversion temperature range measurements. The results indicated that, the relation which represents the most stable O/W emulsion has the strongest direct linear relationship between temperature and conductivity. This relationship is linear up to 80°. This work proves that, the most stable O/W emulsion is determined via the determination of the maximum R² value by applying of the simple linear regression least squares method to the temperature-conductivity obtained data up to 80°, in addition to, the true maximum slope is represented by the equation which has the maximum R² value. Because the conditions would be changed in a more complex formulation, the method of the determination of the effective surfactants blend concentration was verified by applying it for more complex formulations of 2% O/W miconazole nitrate cream and the results indicate its reproducibility.

A least-squares minimization approach for model parameters estimate by using a new magnetic anomaly formula

NASA Astrophysics Data System (ADS)

Abo-Ezz, E. R.; Essa, K. S.

2016-04-01

A new linear least-squares approach is proposed to interpret magnetic anomalies of the buried structures by using a new magnetic anomaly formula. This approach depends on solving different sets of algebraic linear equations in order to invert the depth ( z), amplitude coefficient ( K), and magnetization angle ( θ) of buried structures using magnetic data. The utility and validity of the new proposed approach has been demonstrated through various reliable synthetic data sets with and without noise. In addition, the method has been applied to field data sets from USA and India. The best-fitted anomaly has been delineated by estimating the root-mean squared (rms). Judging satisfaction of this approach is done by comparing the obtained results with other available geological or geophysical information.

Growth and Electronic Structure Characterization of (SrCoOx)n :(SrTiO3)1 Superlattices

NASA Astrophysics Data System (ADS)

Cook, Say Young; Andersen, Tassie; Rosenberg, Richard; Hong, Hawoong; Marks, Laurence; Fong, Dillon

We report on the synthesis of a (SrCoOx)1 :(SrTiO3)1 superlattice by oxide molecular beam epitaxy and the characterization of its electronic structure by soft x-ray spectroscopy. X-ray photoelectron and absorption spectroscopy reveal that Ti remains octahedrally coordinated with a 4 + oxidation state, while the Co oxidation state is intermediate of 3 + and 4 +. Despite having the same half an oxygen vacancy per Co atom found in brownmillerite SrCoO2.5, which consists of alternating tetrahedral and octahedral layers of Co, the confinement of oxygen vacancies to isolated single atomic layers of SrCoOx stabilizes square pyramidal coordination of Co, as observed by the linear dichroism in the Co 2p-3d x-ray absorption. The corresponding stabilization of Co4+ along with Co3 + within the square pyramidal SrCoO2.5 layers gives rise to a Fermi-edge step observed at strong Co 2p-3d resonance in the resonant photoemission spectroscopy of the valence band, and reveals a band gap of 1.7 eV. Comparisons with a Sr(Co,Ti)Ox alloy and a (SrCoOx)2 :(SrTiO3)1 superlattice also will also be presented. The obtained results demonstrate artificial superlattices as effective means to defect engineer complex oxides by harnessing the confinement of oxygen vacancies to control the oxygen coordination environment of the transition metal.

Stability analysis and wave dynamics of an extended hybrid traffic flow model

NASA Astrophysics Data System (ADS)

Wang, Yu-Qing; Zhou, Chao-Fan; Li, Wei-Kang; Yan, Bo-Wen; Jia, Bin; Wang, Ji-Xin

2018-02-01

The stability analysis and wave dynamic properties of an extended hybrid traffic flow model, WZY model, are intensively studied in this paper. The linear stable condition obtained by the linear stability analysis is presented. Besides, by means of analyzing Korteweg-de Vries equation, we present soliton waves in the metastable region. Moreover, the multiscale perturbation technique is applied to derive the traveling wave solution of the model. Furthermore, by means of performing Darboux transformation, the first-order and second-order doubly-periodic solutions and rational solutions are presented. It can be found that analytical solutions match well with numerical simulations.

The microcomputer scientific software series 3: general linear model--analysis of variance.

Treesearch

Harold M. Rauscher

1985-01-01

A BASIC language set of programs, designed for use on microcomputers, is presented. This set of programs will perform the analysis of variance for any statistical model describing either balanced or unbalanced designs. The program computes and displays the degrees of freedom, Type I sum of squares, and the mean square for the overall model, the error, and each factor...

Statistical linearization for multi-input/multi-output nonlinearities

NASA Technical Reports Server (NTRS)

Lin, Ching-An; Cheng, Victor H. L.

1991-01-01

Formulas are derived for the computation of the random input-describing functions for MIMO nonlinearities; these straightforward and rigorous derivations are based on the optimal mean square linear approximation. The computations involve evaluations of multiple integrals. It is shown that, for certain classes of nonlinearities, multiple-integral evaluations are obviated and the computations are significantly simplified.

A composite step conjugate gradients squared algorithm for solving nonsymmetric linear systems

NASA Astrophysics Data System (ADS)

Chan, Tony; Szeto, Tedd

1994-03-01

We propose a new and more stable variant of the CGS method [27] for solving nonsymmetric linear systems. The method is based on squaring the Composite Step BCG method, introduced recently by Bank and Chan [1,2], which itself is a stabilized variant of BCG in that it skips over steps for which the BCG iterate is not defined and causes one kind of breakdown in BCG. By doing this, we obtain a method (Composite Step CGS or CSCGS) which not only handles the breakdowns described above, but does so with the advantages of CGS, namely, no multiplications by the transpose matrix and a faster convergence rate than BCG. Our strategy for deciding whether to skip a step does not involve any machine dependent parameters and is designed to skip near breakdowns as well as produce smoother iterates. Numerical experiments show that the new method does produce improved performance over CGS on practical problems.

Effect of dietary phosphorus on intestinal phosphorus absorption in growing Holstein steers.

PubMed

Feng, X; Ronk, E; Hanigan, M D; Knowlton, K F; Schramm, H; McCann, M

2015-05-01

The effect of dietary P intake on intestinal P absorption was evaluated in growing Holstein steers. Diets varying in P content (0.15, 0.27, 0.36, and 0.45%, DM basis) were fed to 8 steers (174±10kg of BW) fitted with permanent duodenal and ileal cannulas in a replicated 4×4 Latin square with 14-d periods. Ytterbium-labeled corn silage and cobalt-EDTA were used as particulate and liquid phase markers, respectively, to measure digesta flow. Duodenal and ileal samples and spot urine samples were collected every 9 h from d 11 to 14. Total fecal collection was conducted on d 11 to 14 with fecal bags. Blood samples were collected from the coccygeal vessel on d 14. Feed, digesta, and fecal samples were analyzed for total P and inorganic P. Data were analyzed using PROC GLIMMIX in SAS with a model including treatment, square, period, and interaction of treatment and square. Preplanned contrasts were used to evaluate linear and quadratic treatment effects. Results were reported as least squares means. Dry matter intake (mean=4.90kg/d, 2.8% of BW) and apparent DM digestibility (mean=78.1%) were unaffected by treatment. Duodenal and ileal flow of total P increased linearly with increasing P intake (13.4, 18.5, 23.0, and 27.4g/d; 6.80, 7.87, 8.42, and 10.4g/d). Increasing P intake increased the quantity of P absorbed from the small intestine linearly (6.96, 11.1, 14.6, and 17.2g/d), but absorption efficiency was unchanged (mean=59.6%). Phosphorus was absorbed on a net basis from the large intestine, but this was not affected by treatment and was a small proportion of total P absorption. Blood inorganic P increased linearly with increased dietary P (4.36, 6.31, 7.68, and 8.5mg/dL) and salivary P secretion was unchanged (mean=5.79g/d), suggesting that rumen function was prioritized during short-term P deficiency. These data showing an absence of change in absorption efficiency and salivary P secretion in the face of short-term P deficiency may be used to improve published models of P digestion, absorption, and metabolism. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Ratio manipulating spectrophotometry versus chemometry as stability indicating methods for cefquinome sulfate determination.

PubMed

Yehia, Ali M; Arafa, Reham M; Abbas, Samah S; Amer, Sawsan M

2016-01-15

Spectral resolution of cefquinome sulfate (CFQ) in the presence of its degradation products was studied. Three selective, accurate and rapid spectrophotometric methods were performed for the determination of CFQ in the presence of either its hydrolytic, oxidative or photo-degradation products. The proposed ratio difference, derivative ratio and mean centering are ratio manipulating spectrophotometric methods that were satisfactorily applied for selective determination of CFQ within linear range of 5.0-40.0 μg mL(-1). Concentration Residuals Augmented Classical Least Squares was applied and evaluated for the determination of the cited drug in the presence of its all degradation products. Traditional Partial Least Squares regression was also applied and benchmarked against the proposed advanced multivariate calibration. Experimentally designed 25 synthetic mixtures of three factors at five levels were used to calibrate and validate the multivariate models. Advanced chemometrics succeeded in quantitative and qualitative analyses of CFQ along with its hydrolytic, oxidative and photo-degradation products. The proposed methods were applied successfully for different pharmaceutical formulations analyses. These developed methods were simple and cost-effective compared with the manufacturer's RP-HPLC method. Copyright © 2015 Elsevier B.V. All rights reserved.

Linear stability theory and three-dimensional boundary layer transition

NASA Technical Reports Server (NTRS)

Spall, Robert E.; Malik, Mujeeb R.

1992-01-01

The viewgraphs and discussion of linear stability theory and three dimensional boundary layer transition are provided. The ability to predict, using analytical tools, the location of boundary layer transition over aircraft-type configurations is of great importance to designers interested in laminar flow control (LFC). The e(sup N) method has proven to be fairly effective in predicting, in a consistent manner, the location of the onset of transition for simple geometries in low disturbance environments. This method provides a correlation between the most amplified single normal mode and the experimental location of the onset of transition. Studies indicate that values of N between 8 and 10 correlate well with the onset of transition. For most previous calculations, the mean flows were restricted to two-dimensional or axisymmetric cases, or have employed simple three-dimensional mean flows (e.g., rotating disk, infinite swept wing, or tapered swept wing with straight isobars). Unfortunately, for flows over general wing configurations, and for nearly all flows over fuselage-type bodies at incidence, the analysis of fully three-dimensional flow fields is required. Results obtained for the linear stability of fully three-dimensional boundary layers formed over both wing and fuselage-type geometries, and for both high and low speed flows are discussed. When possible, transition estimates form the e(sup N) method are compared to experimentally determined locations. The stability calculations are made using a modified version of the linear stability code COSAL. Mean flows were computed using both Navier Stokes and boundary-layer codes.

Proposing a new iterative learning control algorithm based on a non-linear least square formulation - Minimising draw-in errors

NASA Astrophysics Data System (ADS)

Endelt, B.

2017-09-01

Forming operation are subject to external disturbances and changing operating conditions e.g. new material batch, increasing tool temperature due to plastic work, material properties and lubrication is sensitive to tool temperature. It is generally accepted that forming operations are not stable over time and it is not uncommon to adjust the process parameters during the first half hour production, indicating that process instability is gradually developing over time. Thus, in-process feedback control scheme might not-be necessary to stabilize the process and an alternative approach is to apply an iterative learning algorithm, which can learn from previously produced parts i.e. a self learning system which gradually reduces error based on historical process information. What is proposed in the paper is a simple algorithm which can be applied to a wide range of sheet-metal forming processes. The input to the algorithm is the final flange edge geometry and the basic idea is to reduce the least-square error between the current flange geometry and a reference geometry using a non-linear least square algorithm. The ILC scheme is applied to a square deep-drawing and the Numisheet’08 S-rail benchmark problem, the numerical tests shows that the proposed control scheme is able control and stabilise both processes.

Linear and nonlinear pattern selection in Rayleigh-Benard stability problems

NASA Technical Reports Server (NTRS)

Davis, Sanford S.

1993-01-01

A new algorithm is introduced to compute finite-amplitude states using primitive variables for Rayleigh-Benard convection on relatively coarse meshes. The algorithm is based on a finite-difference matrix-splitting approach that separates all physical and dimensional effects into one-dimensional subsets. The nonlinear pattern selection process for steady convection in an air-filled square cavity with insulated side walls is investigated for Rayleigh numbers up to 20,000. The internalization of disturbances that evolve into coherent patterns is investigated and transient solutions from linear perturbation theory are compared with and contrasted to the full numerical simulations.

Congruence Approximations for Entrophy Endowed Hyperbolic Systems

NASA Technical Reports Server (NTRS)

Barth, Timothy J.; Saini, Subhash (Technical Monitor)

1998-01-01

Building upon the standard symmetrization theory for hyperbolic systems of conservation laws, congruence properties of the symmetrized system are explored. These congruence properties suggest variants of several stabilized numerical discretization procedures for hyperbolic equations (upwind finite-volume, Galerkin least-squares, discontinuous Galerkin) that benefit computationally from congruence approximation. Specifically, it becomes straightforward to construct the spatial discretization and Jacobian linearization for these schemes (given a small amount of derivative information) for possible use in Newton's method, discrete optimization, homotopy algorithms, etc. Some examples will be given for the compressible Euler equations and the nonrelativistic MHD equations using linear and quadratic spatial approximation.

Electrochemical detection of phenolic estrogenic compounds at clay modified carbon paste electrode

NASA Astrophysics Data System (ADS)

Belkamssa, N.; Ouattara, L.; Kawachi, A.; Tsujimura, M.; Isoda, H.; Chtaini, A.; Ksibi, M.

2015-04-01

A simple and sensitive electroanalytical method was developed to determine the Endocrine Disrupting chemical 4-tert-octylphenol on clay modified carbon paste electrode (Clay/CPE). The electrochemical response of the proposed electrode was studied by means of cyclic and square wave voltammetry. It has found that the oxidation of 4-tert-octylphenol on the clay/CPE displayed a well-defined oxidation peak. Under these optimal conditions, a linear relation between concentrations of 4-tert-octylphenol current response was obtained over range of 7.26×10-6 to 3.87×10-7 with a detection and quantification limit of 9.2×10-7 M and 3.06×10-6 M, respectively. The correlation coefficient is 0.9963. The modified electrode showed suitable sensitivity, high stability and an accurate detection of 4-tert-octylphenol. The modified electrode also relevant suitable selectivity for various phenolic estrogenic compounds.

Magnetohydrodynamic simulations of noninductive helicity injection in the reversed-field pinch and tokamak

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sovinec, Carl R.

1995-11-01

Numerical computation is used to investigate resistive magnetohydrodynamic (MHD) fluctuations in the reversed-field pinch (RFP) and in tokamak-like configurations driven solely by direct current (DC) helicity injection. A Lundquist number (S) scan of RFP turbulence without plasma pressure produces the weak scaling of S -0.18 for the root-mean-square magnetic fluctuation level for 2.5x10 3≤S≤4x10 4. The temporal behavior of fluctuations and the reversal parameter becomes more regular as S is increased, acquiring a "sawtooth" shape at the largest value of S. Simulations with plasma pressure and anisotropic thermal conduction demonstrate energy transport resulting from parallel heat fluctuations. To investigate meansmore » of improving RFP energy confinement, three forms of current profile modification are tested. Radio frequency (RF) current drive is modeled with an auxiliary electron force, and linear stability calculations are used.« less

Attenuation length measurements of a liquid scintillator with LabVIEW and reliability evaluation of the device

NASA Astrophysics Data System (ADS)

Gao, Long; Yu, Bo-Xiang; Ding, Ya-Yun; Zhou, Li; Wen, Liang-Jian; Xie, Yu-Guang; Wang, Zhi-Gang; Cai, Xiao; Sun, Xi-Lei; Fang, Jian; Xue, Zhen; Zhang, Ai-Wu; Lü, Qi-Wen; Sun, Li-Jun; Ge, Yong-Shuai; Liu, Ying-Biao; Niu, Shun-Li; Hu, Tao; Cao, Jun; Lü, Jun-Guang

2013-07-01

An attenuation length measurement device was constructed using an oscilloscope and LabVIEW for signal acquisition and processing. The performance of the device has been tested in a variety of ways. The test results show that the set-up has a good stability and high precision (sigma/mean reached 0.4 percent). Besides, the accuracy of the measurement system will decrease by about 17 percent if a filter is used. The attenuation length of a gadolinium-loaded liquid scintillator (Gd-LS) was measured as 15.10±0.35 m where Gd-LS was heavily used in the Daya Bay Neutrino Experiment. In addition, one method based on the Beer-Lambert law was proposed to investigate the reliability of the measurement device, the R-square reached 0.9995. Moreover, three purification methods for Linear Alkyl Benzene (LAB) production were compared in the experiment.

Synchronisation, electronic circuit implementation, and fractional-order analysis of 5D ordinary differential equations with hidden hyperchaotic attractors

NASA Astrophysics Data System (ADS)

Wei, Zhouchao; Rajagopal, Karthikeyan; Zhang, Wei; Kingni, Sifeu Takougang; Akgül, Akif

2018-04-01

Hidden hyperchaotic attractors can be generated with three positive Lyapunov exponents in the proposed 5D hyperchaotic Burke-Shaw system with only one stable equilibrium. To the best of our knowledge, this feature has rarely been previously reported in any other higher-dimensional systems. Unidirectional linear error feedback coupling scheme is used to achieve hyperchaos synchronisation, which will be estimated by using two indicators: the normalised average root-mean squared synchronisation error and the maximum cross-correlation coefficient. The 5D hyperchaotic system has been simulated using a specially designed electronic circuit and viewed on an oscilloscope, thereby confirming the results of the numerical integration. In addition, fractional-order hidden hyperchaotic system will be considered from the following three aspects: stability, bifurcation analysis and FPGA implementation. Such implementations in real time represent hidden hyperchaotic attractors with important consequences for engineering applications.

Antiretroviral drug costs and prescription patterns in British Columbia, Canada: 1996-2011.

PubMed

Nosyk, Bohdan; Montaner, Julio S G; Yip, Benita; Lima, Viviane D; Hogg, Robert S

2014-04-01

Treatment options and therapeutic guidelines have evolved substantially since highly active antiretroviral treatment (HAART) became the standard of HIV care in 1996. We conducted the present population-based analysis to characterize the determinants of direct costs of HAART over time in British Columbia, Canada. We considered individuals ever receiving HAART in British Columbia from 1996 to 2011. Linear mixed-effects regression models were constructed to determine the effects of demographic indicators, clinical stage, and treatment characteristics on quarterly costs of HAART (in 2010$CDN) among individuals initiating in different temporal periods. The least-square mean values were estimated by CD4 category and over time for each temporal cohort. Longitudinal data on HAART recipients (N = 9601, 17.6% female, mean age at initiation = 40.5) were analyzed. Multiple regression analyses identified demographics, treatment adherence, and pharmacological class to be independently associated with quarterly HAART costs. Higher CD4 cell counts were associated with modestly lower costs among pre-HAART initiators [least-square means (95% confidence interval), CD4 > 500: 4674 (4632-4716); CD4: 350-499: 4765 (4721-4809) CD4: 200-349: 4826 (4780-4871); CD4 <200: 4809 (4759-4859)]; however these differences were not significant among post-2003 HAART initiators. Population-level mean costs increased through 2006 and stabilized post-2003 HAART initiators incurred quarterly costs up to 23% lower than pre-2000 HAART initiators in 2010. Our results highlight the magnitude of the temporal changes in HAART costs, and disparities between recent and pre-HAART initiators. This methodology can improve the precision of economic modeling efforts by using detailed cost functions for annual, population-level medication costs according to the distribution of clients by clinical stage and era of treatment initiation.

Difference-based ridge-type estimator of parameters in restricted partial linear model with correlated errors.

PubMed

Wu, Jibo

2016-01-01

In this article, a generalized difference-based ridge estimator is proposed for the vector parameter in a partial linear model when the errors are dependent. It is supposed that some additional linear constraints may hold to the whole parameter space. Its mean-squared error matrix is compared with the generalized restricted difference-based estimator. Finally, the performance of the new estimator is explained by a simulation study and a numerical example.

Robust exponential stability of uncertain delayed neural networks with stochastic perturbation and impulse effects.

PubMed

Huang, Tingwen; Li, Chuandong; Duan, Shukai; Starzyk, Janusz A

2012-06-01

This paper focuses on the hybrid effects of parameter uncertainty, stochastic perturbation, and impulses on global stability of delayed neural networks. By using the Ito formula, Lyapunov function, and Halanay inequality, we established several mean-square stability criteria from which we can estimate the feasible bounds of impulses, provided that parameter uncertainty and stochastic perturbations are well-constrained. Moreover, the present method can also be applied to general differential systems with stochastic perturbation and impulses.

[Development of chlorophyll concentration nondestructive measurement instrument based on spectral analysis technology].

PubMed

Li, Qing-Bo; Xu, Yu-Po; Zhang, Chao-Hang; Zhang, Guang-Jun; Wu, Jin-Guang

2009-10-01

A portable nondestructive measuring instrument for plant chlorophyll was developed, which can perform real-time, quick and nondestructive measurement of chlorophyll. The instrument is mainly composed of four parts, including leaves clamp, driving circuit of light source, photoelectric detection and signal conditioning circuit and micro-control system. A new scheme of light source driving was proposed, which can not only achieve constant current, but also control the current by digital signal. The driving current can be changed depending on different light source and measurement situation by actual operation, which resolves the matching problem of output intensity of light source and input range of photoelectric detector. In addition, an integrative leaves clamp was designed, which simplified the optical structure, enhanced the stability of apparatus, decreased the loss of incident light and improved the signal-to-noise ratio and precision. The photoelectric detection and signal conditioning circuit achieve the conversion between optical signal and electrical signal, and make the electrical signal meet the requirement of AD conversion, and the photo detector is S1133-14 of Hamamatsu Company, with a high detection precision. The micro-control system mainly achieves control function, dealing with data, data storage and so on. As the most important component, microprocessor MSP430F149 of TI Company has many advantages, such as high processing speed, low power, high stability and so on. And it has an in-built 12 bit AD converter, so the data-acquisition circuit is simpler. MSP430F149 is suitable for portable instrument. In the calibration experiment of the instrument, the standard value was measured by chlorophyll meter SPAD-502, multiple linear calibration models were built, and the instrument performance was evaluated. The correlation coefficient between chlorophyll prediction value and standard value is 0.97, and the root mean square error of prediction is about 1.3 SPAD. In the evaluation experiment of the instrument repeatability, the root mean square error is 0.1 SPAD. Results of the calibration experiment show that the instrument has high measuring precision and high stability.

Dynamic stability of spinning pretwisted beams subjected to axial random forces

NASA Astrophysics Data System (ADS)

Young, T. H.; Gau, C. Y.

2003-11-01

This paper studies the dynamic stability of a pretwisted cantilever beam spinning along its longitudinal axis and subjected to an axial random force at the free end. The axial force is assumed as the sum of a constant force and a random process with a zero mean. Due to this axial force, the beam may experience parametric random instability. In this work, the finite element method is first applied to yield discretized system equations. The stochastic averaging method is then adopted to obtain Ito's equations for the response amplitudes of the system. Finally the mean-square stability criterion is utilized to determine the stability condition of the system. Numerical results show that the stability boundary of the system converges as the first three modes are taken into calculation. Before the convergence is reached, the stability condition predicted is not conservative enough.

Minimum mean squared error (MSE) adjustment and the optimal Tykhonov-Phillips regularization parameter via reproducing best invariant quadratic uniformly unbiased estimates (repro-BIQUUE)

NASA Astrophysics Data System (ADS)

Schaffrin, Burkhard

2008-02-01

In a linear Gauss-Markov model, the parameter estimates from BLUUE (Best Linear Uniformly Unbiased Estimate) are not robust against possible outliers in the observations. Moreover, by giving up the unbiasedness constraint, the mean squared error (MSE) risk may be further reduced, in particular when the problem is ill-posed. In this paper, the α-weighted S-homBLE (Best homogeneously Linear Estimate) is derived via formulas originally used for variance component estimation on the basis of the repro-BIQUUE (reproducing Best Invariant Quadratic Uniformly Unbiased Estimate) principle in a model with stochastic prior information. In the present model, however, such prior information is not included, which allows the comparison of the stochastic approach (α-weighted S-homBLE) with the well-established algebraic approach of Tykhonov-Phillips regularization, also known as R-HAPS (Hybrid APproximation Solution), whenever the inverse of the “substitute matrix” S exists and is chosen as the R matrix that defines the relative impact of the regularizing term on the final result.

Numerical studies on convective stability and flow pattern in three-dimensional spherical mantle of terrestrial planets

NASA Astrophysics Data System (ADS)

Yanagisawa, Takatoshi; Kameyama, Masanori; Ogawa, Masaki

2016-09-01

We explore thermal convection of a fluid with a temperature-dependent viscosity in a basally heated 3-D spherical shell using linear stability analyses and numerical experiments, while considering the application of our results to terrestrial planets. The inner to outer radius ratio of the shell f assumed in the linear stability analyses is in the range of 0.11-0.88. The critical Rayleigh number Rc for the onset of thermal convection decreases by two orders of magnitude as f increases from 0.11 to 0.88, when the viscosity depends sensitively on the temperature, as is the case for real mantle materials. Numerical simulations carried out in the range of f = 0.11-0.55 show that a thermal boundary layer (TBL) develops both along the surface and bottom boundaries to induce cold and hot plumes, respectively, when f is 0.33 or larger. However, for smaller f values, a TBL develops only on the bottom boundary. Convection occurs in the stagnant-lid regime where the root mean square velocity on the surface boundary is less than 1 per cent of its maximum at depth, when the ratio of the viscosity at the surface boundary to that at the bottom boundary exceeds a threshold that depends on f. The threshold decreases from 106.5 at f = 0.11 to 104 at f = 0.55. If the viscosity at the base of the convecting mantle is 1020-1021 Pa s, the Rayleigh number exceeds Rc for Mars, Venus and the Earth, but does not for the Moon and Mercury; convection is unlikely to occur in the latter planets unless the mantle viscosity is much lower than 1020 Pa s and/or the mantle contains a strong internal heat source.

The double nucleation model for sickle cell haemoglobin polymerization: full integration and comparison with experimental data.

PubMed

Medkour, Terkia; Ferrone, Frank; Galactéros, Frédéric; Hannaert, Patrick

2008-06-01

Sickle cell haemoglobin (HbS) polymerization reduces erythrocyte deformability, causing deleterous vaso-occlusions. The double-nucleation model states that polymers grow from HbS aggregates, the nuclei, (i) in solution (homogeneous nucleation), (ii) onto existing polymers (heterogeneous nucleation). When linearized at initial HbS concentration, this model predicts early polymerization and its characteristic delay-time (Ferrone et al. J Mol Biol 183(4):591-610, 611-631, 1985). Addressing its relevance for describing complete polymerization, we constructed the full, non-linearized model (Simulink), The MathWorks). Here, we compare the simulated outputs to experimental progress curves (n = 6-8 different [HbS], 3-6 mM range, from Ferrone's group). Within 10% from start, average root mean square (rms) deviation between simulated and experimental curves is 0.04 +/- 0.01 (25 degrees C, n = 8; mean +/- standard error). Conversely, for complete progress curves, averaged rms is 0.48 +/- 0.04. This figure is improved to 0.13 +/- 0.01 by adjusting heterogeneous pathway parameters (p < 0.01): the nucleus stability (sigma(2) micro( cc ): + 40%), and the fraction of polymer surface available for nucleation (phi), from 5e(-7), (3 mM) to 13 (6 mM). Similar results are obtained at 37 degrees C. We conclude that the physico-chemical description of heterogeneous nucleation warrants refinements in order to capture the whole HbS polymerization process.

Examining the Reliability of Interval Level Data Using Root Mean Square Differences and Concordance Correlation Coefficients

ERIC Educational Resources Information Center

Barchard, Kimberly A.

2012-01-01

This article introduces new statistics for evaluating score consistency. Psychologists usually use correlations to measure the degree of linear relationship between 2 sets of scores, ignoring differences in means and standard deviations. In medicine, biology, chemistry, and physics, a more stringent criterion is often used: the extent to which…

Analytic theory for the determination of velocity and stability of bubbles in a Hele-Shaw cell. I - Velocity selection. II - Stability

NASA Technical Reports Server (NTRS)

Tanveer, S.

1989-01-01

An asymptotic theory is presented for the determination of velocity and linear stability of a steady symmetric bubble in a Hele-Shaw cell for small surface tension. First the bubble velocity relative to the fluid velocity at infinity is determined for small surface tension by means of a transcendentally small correction to the asymptotic series solution. In addition, a linear stability analysis shows that only the solution branch corresponding to the largest possible bubble velocity for given surface tension is stable, while all the others are unstable.

Prediction of Moisture Content for Congou Black Tea Withering Leaves Using Image Features and Nonlinear Method.

PubMed

Liang, Gaozhen; Dong, Chunwang; Hu, Bin; Zhu, Hongkai; Yuan, Haibo; Jiang, Yongwen; Hao, Guoshuang

2018-05-18

Withering is the first step in the processing of congou black tea. With respect to the deficiency of traditional water content detection methods, a machine vision based NDT (Non Destructive Testing) method was established to detect the moisture content of withered leaves. First, according to the time sequences using computer visual system collected visible light images of tea leaf surfaces, and color and texture characteristics are extracted through the spatial changes of colors. Then quantitative prediction models for moisture content detection of withered tea leaves was established through linear PLS (Partial Least Squares) and non-linear SVM (Support Vector Machine). The results showed correlation coefficients higher than 0.8 between the water contents and green component mean value (G), lightness component mean value (L * ) and uniformity (U), which means that the extracted characteristics have great potential to predict the water contents. The performance parameters as correlation coefficient of prediction set (Rp), root-mean-square error of prediction (RMSEP), and relative standard deviation (RPD) of the SVM prediction model are 0.9314, 0.0411 and 1.8004, respectively. The non-linear modeling method can better describe the quantitative analytical relations between the image and water content. With superior generalization and robustness, the method would provide a new train of thought and theoretical basis for the online water content monitoring technology of automated production of black tea.

Testing concordance of instrumental variable effects in generalized linear models with application to Mendelian randomization

PubMed Central

Dai, James Y.; Chan, Kwun Chuen Gary; Hsu, Li

2014-01-01

Instrumental variable regression is one way to overcome unmeasured confounding and estimate causal effect in observational studies. Built on structural mean models, there has been considerale work recently developed for consistent estimation of causal relative risk and causal odds ratio. Such models can sometimes suffer from identification issues for weak instruments. This hampered the applicability of Mendelian randomization analysis in genetic epidemiology. When there are multiple genetic variants available as instrumental variables, and causal effect is defined in a generalized linear model in the presence of unmeasured confounders, we propose to test concordance between instrumental variable effects on the intermediate exposure and instrumental variable effects on the disease outcome, as a means to test the causal effect. We show that a class of generalized least squares estimators provide valid and consistent tests of causality. For causal effect of a continuous exposure on a dichotomous outcome in logistic models, the proposed estimators are shown to be asymptotically conservative. When the disease outcome is rare, such estimators are consistent due to the log-linear approximation of the logistic function. Optimality of such estimators relative to the well-known two-stage least squares estimator and the double-logistic structural mean model is further discussed. PMID:24863158

Numerical simulation and sensitivity analysis of a low-Reynolds-number flow around a square cylinder controlled using plasma actuators

NASA Astrophysics Data System (ADS)

Anzai, Yosuke; Fukagata, Koji; Meliga, Philippe; Boujo, Edouard; Gallaire, François

2017-04-01

Flow around a square cylinder controlled using plasma actuators (PAs) is numerically investigated by direct numerical simulation in order to clarify the most effective location of actuator installation and to elucidate the mechanism of control effect. The Reynolds number based on the cylinder diameter and the free-stream velocity is set to be 100 to study the fundamental effect of PAs on two-dimensional vortex shedding, and three different locations of PAs are considered. The mean drag and the root-mean-square of lift fluctuations are found to be reduced by 51% and 99% in the case where two opposing PAs are aligned vertically on the rear surface. In that case, a jet flow similar to a base jet is generated by the collision of the streaming flows induced by the two opposing PAs, and the vortex shedding is completely suppressed. The simulation results are ultimately revisited in the frame of linear sensitivity analysis, whose computational cost is much lower than that of performing the full simulation. A good agreement is reported for low control amplitudes, which allows further discussion of the linear optimal arrangement for any number of PAs.

Stable Numerical Approach for Fractional Delay Differential Equations

NASA Astrophysics Data System (ADS)

Singh, Harendra; Pandey, Rajesh K.; Baleanu, D.

2017-12-01

In this paper, we present a new stable numerical approach based on the operational matrix of integration of Jacobi polynomials for solving fractional delay differential equations (FDDEs). The operational matrix approach converts the FDDE into a system of linear equations, and hence the numerical solution is obtained by solving the linear system. The error analysis of the proposed method is also established. Further, a comparative study of the approximate solutions is provided for the test examples of the FDDE by varying the values of the parameters in the Jacobi polynomials. As in special case, the Jacobi polynomials reduce to the well-known polynomials such as (1) Legendre polynomial, (2) Chebyshev polynomial of second kind, (3) Chebyshev polynomial of third and (4) Chebyshev polynomial of fourth kind respectively. Maximum absolute error and root mean square error are calculated for the illustrated examples and presented in form of tables for the comparison purpose. Numerical stability of the presented method with respect to all four kind of polynomials are discussed. Further, the obtained numerical results are compared with some known methods from the literature and it is observed that obtained results from the proposed method is better than these methods.

Modular injector integrated linear apparatus with motion profile optimization for spatial atomic layer deposition.

PubMed

Wang, Xiaolei; Li, Yun; Lin, Jilong; Shan, Bin; Chen, Rong

2017-11-01

A spatial atomic layer deposition apparatus integrated with a modular injector and a linear motor has been designed. It consists of four parts: a precursor delivery manifold, a modular injector, a reaction zone, and a driving unit. An injector with multi-layer structured channels is designed to help improve precursor distribution homogeneity. During the back and forth movement of the substrate at high speed, the inertial impact caused by jerk and sudden changes of acceleration will degrade the film deposition quality. Such residual vibration caused by inertial impact will aggravate the fluctuation of the gap distance between the injector and the substrate in the deposition process. Thus, an S-curve motion profile is implemented to reduce the large inertial impact, and the maximum position error could be reduced by 84%. The microstructure of the film under the S-curve motion profile shows smaller root-mean-square and scanning voltage amplitude under an atomic force microscope, which verifies the effectiveness of the S-curve motion profile in reducing the residual vibration and stabilizing the gap distance between the injector and the substrate. The film deposition rate could reach 100 nm/min while maintaining good uniformity without obvious periodic patterns on the surface.

Modular injector integrated linear apparatus with motion profile optimization for spatial atomic layer deposition

NASA Astrophysics Data System (ADS)

Wang, Xiaolei; Li, Yun; Lin, Jilong; Shan, Bin; Chen, Rong

2017-11-01

A spatial atomic layer deposition apparatus integrated with a modular injector and a linear motor has been designed. It consists of four parts: a precursor delivery manifold, a modular injector, a reaction zone, and a driving unit. An injector with multi-layer structured channels is designed to help improve precursor distribution homogeneity. During the back and forth movement of the substrate at high speed, the inertial impact caused by jerk and sudden changes of acceleration will degrade the film deposition quality. Such residual vibration caused by inertial impact will aggravate the fluctuation of the gap distance between the injector and the substrate in the deposition process. Thus, an S-curve motion profile is implemented to reduce the large inertial impact, and the maximum position error could be reduced by 84%. The microstructure of the film under the S-curve motion profile shows smaller root-mean-square and scanning voltage amplitude under an atomic force microscope, which verifies the effectiveness of the S-curve motion profile in reducing the residual vibration and stabilizing the gap distance between the injector and the substrate. The film deposition rate could reach 100 nm/min while maintaining good uniformity without obvious periodic patterns on the surface.

Thermodynamic study of complex formation between Ce3+ and cryptand 222 in some binary mixed nonaqueous solvents

NASA Astrophysics Data System (ADS)

Rounaghi, G. H.; Dolatshahi, S.; Tarahomi, S.

2014-12-01

The stoichiometry, stability and the thermodynamic parameters of complex formation between cerium(III) cation and cryptand 222 (4,7,13,16,21,24-hexaoxa-1,10-diazabycyclo[8.8.8]-hexacosane) were studied by conductometric titration method in some binary solvent mixtures of dimethylformamide (DMF), 1,2-dichloroethane (DCE), ethyl acetate (EtOAc) and methyl acetate (MeOAc) with methanol (MeOH), at 288, 298, 308, and 318 K. A model based on 1: 1 stoichiometry has been used to analyze the conductivity data. The data have been fitted according to a non-linear least-squares analysis that provide the stability constant, K f, for the cation-ligand inclusion complex. The results revealed that the stability order of [Ce(cryptand 222)]3+ complex changes with the nature and composition of the solvent system. A non-linear relationship was observed between the stability constant (log K f) of [Ce(cryptand 222)]3+ complex versus the composition of the binary mixed solvent. Standard thermodynamic values were obtained from temperature dependence of the stability constant of the complex, show that the studied complexation process is mainly entropy governed and are influenced by the nature and composition of the binary mixed solvent solutions.

Combating speckle in SAR images - Vector filtering and sequential classification based on a multiplicative noise model

NASA Technical Reports Server (NTRS)

Lin, Qian; Allebach, Jan P.

1990-01-01

An adaptive vector linear minimum mean-squared error (LMMSE) filter for multichannel images with multiplicative noise is presented. It is shown theoretically that the mean-squared error in the filter output is reduced by making use of the correlation between image bands. The vector and conventional scalar LMMSE filters are applied to a three-band SIR-B SAR, and their performance is compared. Based on a mutliplicative noise model, the per-pel maximum likelihood classifier was derived. The authors extend this to the design of sequential and robust classifiers. These classifiers are also applied to the three-band SIR-B SAR image.

Brownian self-propelled particles on a sphere

NASA Astrophysics Data System (ADS)

Apaza-Pilco, Leonardo Felix; Sandoval, Mario

We present the dynamics of a Brownian self-propelled particle at low Reynolds number moving on the surface of a sphere. The effects of curvature and self-propulsion on the diffusion of the particle are elucidated by determining (numerically) the mean-square displacement of the particle's angular (azimuthal and polar) coordinates. The results show that the long time behavior of its angular mean-square displacement is linear in time. We also see that the slope of the angular MSD is proportional to the propulsion velocity and inverse to the curvature of the sphere. The angular probability distribution function (PDF) of the particle is also obtained by numerically solving its respective Smoluchowski equation.

Linear mixed-effects models to describe individual tree crown width for China-fir in Fujian Province, southeast China.

PubMed

Hao, Xu; Yujun, Sun; Xinjie, Wang; Jin, Wang; Yao, Fu

2015-01-01

A multiple linear model was developed for individual tree crown width of Cunninghamia lanceolata (Lamb.) Hook in Fujian province, southeast China. Data were obtained from 55 sample plots of pure China-fir plantation stands. An Ordinary Linear Least Squares (OLS) regression was used to establish the crown width model. To adjust for correlations between observations from the same sample plots, we developed one level linear mixed-effects (LME) models based on the multiple linear model, which take into account the random effects of plots. The best random effects combinations for the LME models were determined by the Akaike's information criterion, the Bayesian information criterion and the -2logarithm likelihood. Heteroscedasticity was reduced by three residual variance functions: the power function, the exponential function and the constant plus power function. The spatial correlation was modeled by three correlation structures: the first-order autoregressive structure [AR(1)], a combination of first-order autoregressive and moving average structures [ARMA(1,1)], and the compound symmetry structure (CS). Then, the LME model was compared to the multiple linear model using the absolute mean residual (AMR), the root mean square error (RMSE), and the adjusted coefficient of determination (adj-R2). For individual tree crown width models, the one level LME model showed the best performance. An independent dataset was used to test the performance of the models and to demonstrate the advantage of calibrating LME models.

Sum-of-squares-based fuzzy controller design using quantum-inspired evolutionary algorithm

NASA Astrophysics Data System (ADS)

Yu, Gwo-Ruey; Huang, Yu-Chia; Cheng, Chih-Yung

2016-07-01

In the field of fuzzy control, control gains are obtained by solving stabilisation conditions in linear-matrix-inequality-based Takagi-Sugeno fuzzy control method and sum-of-squares-based polynomial fuzzy control method. However, the optimal performance requirements are not considered under those stabilisation conditions. In order to handle specific performance problems, this paper proposes a novel design procedure with regard to polynomial fuzzy controllers using quantum-inspired evolutionary algorithms. The first contribution of this paper is a combination of polynomial fuzzy control and quantum-inspired evolutionary algorithms to undertake an optimal performance controller design. The second contribution is the proposed stability condition derived from the polynomial Lyapunov function. The proposed design approach is dissimilar to the traditional approach, in which control gains are obtained by solving the stabilisation conditions. The first step of the controller design uses the quantum-inspired evolutionary algorithms to determine the control gains with the best performance. Then, the stability of the closed-loop system is analysed under the proposed stability conditions. To illustrate effectiveness and validity, the problem of balancing and the up-swing of an inverted pendulum on a cart is used.

Ammonia-water mixtures at high pressures - Melting curves of ammonia dihydrate and ammonia monohydrate and a revised high-pressure phase diagram for the water-rich region. [in primordial solar system ices

NASA Technical Reports Server (NTRS)

Boone, S.; Nicol, M. F.

1991-01-01

The phase relations of some mixtures of ammonia and water are investigated to create a phase diagram in pressure-temperature-composition space relevant to the geophysical study of bodies in the outer solar system. The mixtures of NH3(x)H2O(1-x), where x is greater than 0.30 but less than 0.51, are examined at pressures and temperatures ranging from 0-6.5 GPa and 125-400 K, respectively. The ruby luminescence technique monitors the pressure and a diamond-anvil cell compresses the samples, and the phases are identified by means of normal- and polarized-light optical microscopy. The melting curve for NH3H2O(2) is described by the equation T = 176 + 60P - 8.5P squared for the ranges of 0.06-1.4 GPa and 179-243 K. The equation for NH3H2O is T = 194 + 37P - P squared, which represents a minor correction of a previous description by Johnson et al. (1985). Observed phase transitions are consistent with the high-pressure stability limit of NH3H2O(2), and the transition boundary is found to be linear.

Nonlinear dynamic systems identification using recurrent interval type-2 TSK fuzzy neural network - A novel structure.

PubMed

El-Nagar, Ahmad M

2018-01-01

In this study, a novel structure of a recurrent interval type-2 Takagi-Sugeno-Kang (TSK) fuzzy neural network (FNN) is introduced for nonlinear dynamic and time-varying systems identification. It combines the type-2 fuzzy sets (T2FSs) and a recurrent FNN to avoid the data uncertainties. The fuzzy firing strengths in the proposed structure are returned to the network input as internal variables. The interval type-2 fuzzy sets (IT2FSs) is used to describe the antecedent part for each rule while the consequent part is a TSK-type, which is a linear function of the internal variables and the external inputs with interval weights. All the type-2 fuzzy rules for the proposed RIT2TSKFNN are learned on-line based on structure and parameter learning, which are performed using the type-2 fuzzy clustering. The antecedent and consequent parameters of the proposed RIT2TSKFNN are updated based on the Lyapunov function to achieve network stability. The obtained results indicate that our proposed network has a small root mean square error (RMSE) and a small integral of square error (ISE) with a small number of rules and a small computation time compared with other type-2 FNNs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Estimation of perceptible water vapor of atmosphere using artificial neural network, support vector machine and multiple linear regression algorithm and their comparative study

NASA Astrophysics Data System (ADS)

Shastri, Niket; Pathak, Kamlesh

2018-05-01

The water vapor content in atmosphere plays very important role in climate. In this paper the application of GPS signal in meteorology is discussed, which is useful technique that is used to estimate the perceptible water vapor of atmosphere. In this paper various algorithms like artificial neural network, support vector machine and multiple linear regression are use to predict perceptible water vapor. The comparative studies in terms of root mean square error and mean absolute errors are also carried out for all the algorithms.

Selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays and impacts of using incorrect weighting factors on curve stability, data quality, and assay performance.

PubMed

Gu, Huidong; Liu, Guowen; Wang, Jian; Aubry, Anne-Françoise; Arnold, Mark E

2014-09-16

A simple procedure for selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays is reported. The correct weighting factor is determined by the relationship between the standard deviation of instrument responses (σ) and the concentrations (x). The weighting factor of 1, 1/x, or 1/x(2) should be selected if, over the entire concentration range, σ is a constant, σ(2) is proportional to x, or σ is proportional to x, respectively. For the first time, we demonstrated with detailed scientific reasoning, solid historical data, and convincing justification that 1/x(2) should always be used as the weighting factor for all bioanalytical LC-MS/MS assays. The impacts of using incorrect weighting factors on curve stability, data quality, and assay performance were thoroughly investigated. It was found that the most stable curve could be obtained when the correct weighting factor was used, whereas other curves using incorrect weighting factors were unstable. It was also found that there was a very insignificant impact on the concentrations reported with calibration curves using incorrect weighting factors as the concentrations were always reported with the passing curves which actually overlapped with or were very close to the curves using the correct weighting factor. However, the use of incorrect weighting factors did impact the assay performance significantly. Finally, the difference between the weighting factors of 1/x(2) and 1/y(2) was discussed. All of the findings can be generalized and applied into other quantitative analysis techniques using calibration curves with weighted least-squares regression algorithm.

Gompertzian stochastic model with delay effect to cervical cancer growth

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mazlan, Mazma Syahidatul Ayuni binti; Rosli, Norhayati binti; Bahar, Arifah

2015-02-03

In this paper, a Gompertzian stochastic model with time delay is introduced to describe the cervical cancer growth. The parameters values of the mathematical model are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic model numerically. The efficiency of mathematical model is measured by comparing the simulated result and the clinical data of cervical cancer growth. Low values of Mean-Square Error (MSE) of Gompertzian stochastic model with delay effect indicate good fits.

RVB signatures in the spin dynamics of the square-lattice Heisenberg antiferromagnet

NASA Astrophysics Data System (ADS)

Ghioldi, E. A.; Gonzalez, M. G.; Manuel, L. O.; Trumper, A. E.

2016-03-01

We investigate the spin dynamics of the square-lattice spin-\\frac{1}{2} Heisenberg antiferromagnet by means of an improved mean-field Schwinger boson calculation. By identifying both, the long-range Néel and the RVB-like components of the ground state, we propose an educated guess for the mean-field magnetic excitation consisting on a linear combination of local and bond spin flips to compute the dynamical structure factor. Our main result is that when this magnetic excitation is optimized in such a way that the corresponding sum rule is fulfilled, we recover the low- and high-energy spectral weight features of the experimental spectrum. In particular, the anomalous spectral weight depletion at (π,0) found in recent inelastic neutron scattering experiments can be attributed to the interference of the triplet bond excitations of the RVB component of the ground state. We conclude that the Schwinger boson theory seems to be a good candidate to adequately interpret the dynamic properties of the square-lattice Heisenberg antiferromagnet.

Super-linear Precision in Simple Neural Population Codes

NASA Astrophysics Data System (ADS)

Schwab, David; Fiete, Ila

2015-03-01

A widely used tool for quantifying the precision with which a population of noisy sensory neurons encodes the value of an external stimulus is the Fisher Information (FI). Maximizing the FI is also a commonly used objective for constructing optimal neural codes. The primary utility and importance of the FI arises because it gives, through the Cramer-Rao bound, the smallest mean-squared error achievable by any unbiased stimulus estimator. However, it is well-known that when neural firing is sparse, optimizing the FI can result in codes that perform very poorly when considering the resulting mean-squared error, a measure with direct biological relevance. Here we construct optimal population codes by minimizing mean-squared error directly and study the scaling properties of the resulting network, focusing on the optimal tuning curve width. We then extend our results to continuous attractor networks that maintain short-term memory of external stimuli in their dynamics. Here we find similar scaling properties in the structure of the interactions that minimize diffusive information loss.

Dynamical theory of stability for elastic rods with nonlinear curvature and twist

NASA Technical Reports Server (NTRS)

Wauer, J.

1977-01-01

Considering non-linear terms in the curvature as well as in the twist, the governing boundary value problem for lateral bending of elastic, transverse loaded rods is formulated by means of Hamilton's principle. Using the method of small vibrations, the associated linearized equations of stability are derived, which complete the currently accepted relations. The example of the simplest lateral bending problem illustrates the improved effect of the proposed equations.

Semiflexible polymer dynamics with a bead-spring model

NASA Astrophysics Data System (ADS)

Barkema, Gerard T.; Panja, Debabrata; van Leeuwen, J. M. J.

2014-11-01

We study the dynamical properties of semiflexible polymers with a recently introduced bead-spring model. We focus on double-stranded DNA (dsDNA). The two parameters of the model, T* and ν, are chosen to match its experimental force-extension curve. In comparison to its groundstate value, the bead-spring Hamiltonian is approximated in the first order by the Hessian that is quadratic in the bead positions. The eigenmodes of the Hessian provide the longitudinal (stretching) and transverse (bending) eigenmodes of the polymer, and the corresponding eigenvalues match well with the established phenomenology of semiflexible polymers. At the Hessian approximation of the Hamiltonian, the polymer dynamics is linear. Using the longitudinal and transverse eigenmodes, for the linearized problem, we obtain analytical expressions of (i) the autocorrelation function of the end-to-end vector, (ii) the autocorrelation function of a bond (i.e. a spring, or a tangent) vector at the middle of the chain, and (iii) the mean-square displacement of a tagged bead in the middle of the chain, as the sum over the contributions from the modes—the so-called ‘mode sums’. We also perform simulations with the full dynamics of the model. The simulations yield numerical values of the correlations functions (i-iii) that agree very well with the analytical expressions for the linearized dynamics. This does not however mean that the nonlinearities are not present. In fact, we also study the mean-square displacement of the longitudinal component of the end-to-end vector that showcases strong nonlinear effects in the polymer dynamics, and we identify at least an effective t7/8 power-law regime in its time-dependence. Nevertheless, in comparison to the full mean-square displacement of the end-to-end vector the nonlinear effects remain small at all times—it is in this sense we state that our results demonstrate that the linearized dynamics suffices for dsDNA fragments that are shorter than or comparable to the persistence length. Our results are consistent with those of the wormlike chain (WLC) model, the commonly used descriptive tool of semiflexible polymers.

A methodology based on reduced complexity algorithm for system applications using microprocessors

NASA Technical Reports Server (NTRS)

Yan, T. Y.; Yao, K.

1988-01-01

The paper considers a methodology on the analysis and design of a minimum mean-square error criterion linear system incorporating a tapped delay line (TDL) where all the full-precision multiplications in the TDL are constrained to be powers of two. A linear equalizer based on the dispersive and additive noise channel is presented. This microprocessor implementation with optimized power of two TDL coefficients achieves a system performance comparable to the optimum linear equalization with full-precision multiplications for an input data rate of 300 baud.

Adaptively combined FIR and functional link artificial neural network equalizer for nonlinear communication channel.

PubMed

Zhao, Haiquan; Zhang, Jiashu

2009-04-01

This paper proposes a novel computational efficient adaptive nonlinear equalizer based on combination of finite impulse response (FIR) filter and functional link artificial neural network (CFFLANN) to compensate linear and nonlinear distortions in nonlinear communication channel. This convex nonlinear combination results in improving the speed while retaining the lower steady-state error. In addition, since the CFFLANN needs not the hidden layers, which exist in conventional neural-network-based equalizers, it exhibits a simpler structure than the traditional neural networks (NNs) and can require less computational burden during the training mode. Moreover, appropriate adaptation algorithm for the proposed equalizer is derived by the modified least mean square (MLMS). Results obtained from the simulations clearly show that the proposed equalizer using the MLMS algorithm can availably eliminate various intensity linear and nonlinear distortions, and be provided with better anti-jamming performance. Furthermore, comparisons of the mean squared error (MSE), the bit error rate (BER), and the effect of eigenvalue ratio (EVR) of input correlation matrix are presented.

Fast smooth second-order sliding mode control for systems with additive colored noises.

PubMed

Yang, Pengfei; Fang, Yangwang; Wu, Youli; Liu, Yunxia; Zhang, Danxu

2017-01-01

In this paper, a fast smooth second-order sliding mode control is presented for a class of stochastic systems with enumerable Ornstein-Uhlenbeck colored noises. The finite-time mean-square practical stability and finite-time mean-square practical reachability are first introduced. Instead of treating the noise as bounded disturbance, the stochastic control techniques are incorporated into the design of the controller. The finite-time convergence of the prescribed sliding variable dynamics system is proved by using stochastic Lyapunov-like techniques. Then the proposed sliding mode controller is applied to a second-order nonlinear stochastic system. Simulation results are presented comparing with smooth second-order sliding mode control to validate the analysis.

Expected distributions of root-mean-square positional deviations in proteins.

PubMed

Pitera, Jed W

2014-06-19

The atom positional root-mean-square deviation (RMSD) is a standard tool for comparing the similarity of two molecular structures. It is used to characterize the quality of biomolecular simulations, to cluster conformations, and as a reaction coordinate for conformational changes. This work presents an approximate analytic form for the expected distribution of RMSD values for a protein or polymer fluctuating about a stable native structure. The mean and maximum of the expected distribution are independent of chain length for long chains and linearly proportional to the average atom positional root-mean-square fluctuations (RMSF). To approximate the RMSD distribution for random-coil or unfolded ensembles, numerical distributions of RMSD were generated for ensembles of self-avoiding and non-self-avoiding random walks. In both cases, for all reference structures tested for chains more than three monomers long, the distributions have a maximum distant from the origin with a power-law dependence on chain length. The purely entropic nature of this result implies that care must be taken when interpreting stable high-RMSD regions of the free-energy landscape as "intermediates" or well-defined stable states.

ORACLS: A system for linear-quadratic-Gaussian control law design

NASA Technical Reports Server (NTRS)

Armstrong, E. S.

1978-01-01

A modern control theory design package (ORACLS) for constructing controllers and optimal filters for systems modeled by linear time-invariant differential or difference equations is described. Numerical linear-algebra procedures are used to implement the linear-quadratic-Gaussian (LQG) methodology of modern control theory. Algorithms are included for computing eigensystems of real matrices, the relative stability of a matrix, factored forms for nonnegative definite matrices, the solutions and least squares approximations to the solutions of certain linear matrix algebraic equations, the controllability properties of a linear time-invariant system, and the steady state covariance matrix of an open-loop stable system forced by white noise. Subroutines are provided for solving both the continuous and discrete optimal linear regulator problems with noise free measurements and the sampled-data optimal linear regulator problem. For measurement noise, duality theory and the optimal regulator algorithms are used to solve the continuous and discrete Kalman-Bucy filter problems. Subroutines are also included which give control laws causing the output of a system to track the output of a prescribed model.

Nonlinear stability analysis of Darcy’s flow with viscous heating

PubMed Central

Alves, Leonardo S. de B.; Barletta, Antonio

2016-01-01

The nonlinear stability of a rectangular porous channel saturated by a fluid is here investigated. The aspect ratio of the channel is assumed to be variable. The channel walls are considered impermeable and adiabatic except for the horizontal top which is assumed to be isothermal. The viscous dissipation is acting inside the channel as internal heat generator. A basic throughflow is imposed, and the nonlinear convective stability is investigated by means of the generalized integral transform technique. The neutral stability curve is compared with the one obtained by the linear stability analysis already present in the literature. The growth rate analysis of different unstable modes is performed. The Nusselt number is investigated for several supercritical configurations in order to better understand how the system behaves when conditions far away from neutral stability are considered. The patterns of the neutrally stable convective cells are also reported. Nonlinear simulations support the results obtained by means of the linear stability analysis, confirming that viscous dissipation alone is indeed capable of inducing mixed convection. Low Gebhart or high Péclet numbers lead to a transient overheating of the originally motionless fluid before it settles in its convective steady state. PMID:27279772

Validation of a new modal performance measure for flexible controllers design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simo, J.B.; Tahan, S.A.; Kamwa, I.

1996-05-01

A new modal performance measure for power system stabilizer (PSS) optimization is proposed in this paper. The new method is based on modifying the square envelopes of oscillating modes, in order to take into account their damping ratios while minimizing the performance index. This criteria is applied to flexible controllers optimal design, on a multi-input-multi-output (MIMO) reduced-order model of a prototype power system. The multivariable model includes four generators, each having one input and one output. Linear time-response simulation and transient stability analysis with a nonlinear package confirm the superiority of the proposed criteria and illustrate its effectiveness in decentralizedmore » control.« less

Introducing linear functions: an alternative statistical approach

NASA Astrophysics Data System (ADS)

Nolan, Caroline; Herbert, Sandra

2015-12-01

The introduction of linear functions is the turning point where many students decide if mathematics is useful or not. This means the role of parameters and variables in linear functions could be considered to be `threshold concepts'. There is recognition that linear functions can be taught in context through the exploration of linear modelling examples, but this has its limitations. Currently, statistical data is easily attainable, and graphics or computer algebra system (CAS) calculators are common in many classrooms. The use of this technology provides ease of access to different representations of linear functions as well as the ability to fit a least-squares line for real-life data. This means these calculators could support a possible alternative approach to the introduction of linear functions. This study compares the results of an end-of-topic test for two classes of Australian middle secondary students at a regional school to determine if such an alternative approach is feasible. In this study, test questions were grouped by concept and subjected to concept by concept analysis of the means of test results of the two classes. This analysis revealed that the students following the alternative approach demonstrated greater competence with non-standard questions.

Weighted linear least squares estimation of diffusion MRI parameters: strengths, limitations, and pitfalls.

PubMed

Veraart, Jelle; Sijbers, Jan; Sunaert, Stefan; Leemans, Alexander; Jeurissen, Ben

2013-11-01

Linear least squares estimators are widely used in diffusion MRI for the estimation of diffusion parameters. Although adding proper weights is necessary to increase the precision of these linear estimators, there is no consensus on how to practically define them. In this study, the impact of the commonly used weighting strategies on the accuracy and precision of linear diffusion parameter estimators is evaluated and compared with the nonlinear least squares estimation approach. Simulation and real data experiments were done to study the performance of the weighted linear least squares estimators with weights defined by (a) the squares of the respective noisy diffusion-weighted signals; and (b) the squares of the predicted signals, which are reconstructed from a previous estimate of the diffusion model parameters. The negative effect of weighting strategy (a) on the accuracy of the estimator was surprisingly high. Multi-step weighting strategies yield better performance and, in some cases, even outperformed the nonlinear least squares estimator. If proper weighting strategies are applied, the weighted linear least squares approach shows high performance characteristics in terms of accuracy/precision and may even be preferred over nonlinear estimation methods. Copyright © 2013 Elsevier Inc. All rights reserved.

Variability simulations with a steady, linearized primitive equations model

NASA Technical Reports Server (NTRS)

Kinter, J. L., III; Nigam, S.

1985-01-01

Solutions of the steady, primitive equations on a sphere, linearized about a zonally symmetric basic state are computed for the purpose of simulating monthly mean variability in the troposphere. The basic states are observed, winter monthly mean, zonal means of zontal and meridional velocities, temperatures and surface pressures computed from the 15 year NMC time series. A least squares fit to a series of Legendre polynomials is used to compute the basic states between 20 H and the equator, and the hemispheres are assumed symmetric. The model is spectral in the zonal direction, and centered differences are employed in the meridional and vertical directions. Since the model is steady and linear, the solution is obtained by inversion of a block, pente-diagonal matrix. The model simulates the climatology of the GFDL nine level, spectral general circulation model quite closely, particularly in middle latitudes above the boundary layer. This experiment is an extension of that simulation to examine variability of the steady, linear solution.

Ion beam figuring of high-slope surfaces based on figure error compensation algorithm.

PubMed

Dai, Yifan; Liao, Wenlin; Zhou, Lin; Chen, Shanyong; Xie, Xuhui

2010-12-01

In a deterministic figuring process, it is critical to guarantee high stability of the removal function as well as the accuracy of the dwell time solution, which directly influence the convergence of the figuring process. Hence, when figuring steep optics, the ion beam is required to keep a perpendicular incidence, and a five-axis figuring machine is typically utilized. In this paper, however, a method for high-precision figuring of high-slope optics is proposed with a linear three-axis machine, allowing for inclined beam incidence. First, the changing rule of the removal function and the normal removal rate with the incidence angle is analyzed according to the removal characteristics of ion beam figuring (IBF). Then, we propose to reduce the influence of varying removal function and projection distortion on the dwell time solution by means of figure error compensation. Consequently, the incident ion beam is allowed to keep parallel to the optical axis. Simulations and experiments are given to verify the removal analysis. Finally, a figuring experiment is conducted on a linear three-axis IBF machine, which proves the validity of the method for high-slope surfaces. It takes two iterations and about 9 min to successfully figure a fused silica sample, whose aperture is 21.3 mm and radius of curvature is 16 mm. The root-mean-square figure error of the convex surface is reduced from 13.13 to 5.86 nm.

Postural stability changes in the elderly with cataract simulation and refractive blur.

PubMed

Anand, Vijay; Buckley, John G; Scally, Andy; Elliott, David B

2003-11-01

To determine the influence of cataractous and refractive blur on postural stability and limb-load asymmetry (LLA) and to establish how postural stability changes with the spatial frequency and contrast of the visual stimulus. Thirteen elderly subjects (mean age, 70.76 +/- 4.14 [SD] years) with no history of falls and normal vision were recruited. Postural stability was determined as the root mean square [RMS] of the center of pressure (COP) signal in the anterior-posterior (A-P) and medial-lateral directions and LLA was determined as the ratio of the average body weight placed on the more-loaded limb to the less-loaded limb, recorded during a 30-second period. Data were collected under normal standing conditions and with somatosensory system input disrupted. Measurements were repeated with four visual targets with high (8 cyc/deg) or low (2 cyc/deg) spatial frequency and high (Weber contrast, approximately 95%) or low (Weber contrast, approximately 25%) contrast. Postural stability was measured under conditions of binocular refractive blur of 0, 1, 2, 4, and 8 D and with cataract simulation. The data were analyzed in a population-averaged linear model. The cataract simulation caused significant increases in postural instability equivalent to that caused by 8-D blur conditions, and its effect was greater when the input from the somatosensory system was disrupted. High spatial frequency targets increased postural instability. Refractive blur, cataract simulation, or eye closure had no effect on LLA. Findings indicate that cataractous and refractive blur increase postural instability, and show why the elderly, many of whom have poor vision along with musculoskeletal and central nervous system degeneration, are at greater risk of falling. Findings also highlight that changes in contrast sensitivity rather than resolution changes are responsible for increasing postural instability. Providing low spatial frequency information in certain environments may be useful in maintaining postural stability. Correcting visual impairment caused by uncorrected refractive error and cataracts could be a useful intervention strategy to help prevent falls and fall-related injuries in the elderly.

Least-Squares Deconvolution of Compton Telescope Data with the Positivity Constraint

NASA Technical Reports Server (NTRS)

Wheaton, William A.; Dixon, David D.; Tumer, O. Tumay; Zych, Allen D.

1993-01-01

We describe a Direct Linear Algebraic Deconvolution (DLAD) approach to imaging of data from Compton gamma-ray telescopes. Imposition of the additional physical constraint, that all components of the model be non-negative, has been found to have a powerful effect in stabilizing the results, giving spatial resolution at or near the instrumental limit. A companion paper (Dixon et al. 1993) presents preliminary images of the Crab Nebula region using data from COMPTEL on the Compton Gamma-Ray Observatory.

Statistical Tutorial | Center for Cancer Research

Cancer.gov

Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data.  ST is designed as a follow up to Statistical Analysis of Research Data (SARD) held in April 2018.  The tutorial will apply the general principles of statistical analysis of research data including descriptive statistics, z- and t-tests of means and mean differences, simple and multiple linear regression, ANOVA tests, and Chi-Squared distribution.

New method for calculating a mathematical expression for streamflow recession

USGS Publications Warehouse

Rutledge, Albert T.

1991-01-01

An empirical method has been devised to calculate the master recession curve, which is a mathematical expression for streamflow recession during times of negligible direct runoff. The method is based on the assumption that the storage-delay factor, which is the time per log cycle of streamflow recession, varies linearly with the logarithm of streamflow. The resulting master recession curve can be nonlinear. The method can be executed by a computer program that reads a data file of daily mean streamflow, then allows the user to select several near-linear segments of streamflow recession. The storage-delay factor for each segment is one of the coefficients of the equation that results from linear least-squares regression. Using results for each recession segment, a mathematical expression of the storage-delay factor as a function of the log of streamflow is determined by linear least-squares regression. The master recession curve, which is a second-order polynomial expression for time as a function of log of streamflow, is then derived using the coefficients of this function.

Stabilization of Taylor-Couette flow due to time-periodic outer cylinder oscillation

NASA Technical Reports Server (NTRS)

Murray, B. T.; Mcfadden, G. B.; Coriell, S. R.

1990-01-01

The linear stability of circular Couette flow between concentric infinite cylinders is considered for the case when the inner cylinder is rotated at a constant angular velocity and the outer cylinder is driven sinusoidally in time with zero mean rotation. This configuration was studied experimentally by Walsh and Donnelly. The critical Reynolds numbers calculated from linear stability theory agree well with the experimental values, except at large modulation amplitudes and small frequencies. The theoretical values are obtained using Floquet theory implemented in two distinct approaches: a truncated Fourier series representation in time, and a fundamental solution matrix based on a Chebyshev pseudospectral representation in space. For large amplitude, low frequency modulation, the linear eigenfunctions are temporally complex, consisting of a quiescent region followed by rapid change in the perturbed flow velocities.

Tryptophan to Glycine mutation in the position 116 leads to protein aggregation and decreases the stability of the LITAF protein.

PubMed

Kumar, Chundi Vinay; Swetha, Rayapadi G; Ramaiah, Sudha; Anbarasu, Anand

2015-01-01

Mutations in the gene-encoding vesicle lipopolysaccharide-induced tumor necrosis factor (LITAF) protein cause Charcot-Marie-Tooth type 1C (CMT1C) disease, a neurological disorder. The LITAF gene is mapped to chromosome number 16 and can be found at cytogenetic location 16p13 of the chromosome. CMT1C-linked small integral membrane protein of lysosome/late endosome mutants are loss-of-function mutants that act in a dominant negative manner to impair endosomal trafficking, leading to prolonged extracellular signal-regulated kinases 1/2 signaling downstream of ErbB activation. Mutation W116G in the LITAF decreases the stability of the protein and also interrupts the functioning of gene. We have analyzed the single nucleotide polymorphism (SNP) results of 28 nsSNPs obtained from dbSNP. We also carried out multiple molecular dynamics simulations of 200 ns and obtained results of root-mean-square deviation, root-mean-square fluctuation, radius of gyration, solvent-accessible surface area, H-bond, and principal component analysis to check and prove the stability of both the wild type and the mutant. The protein was then checked for its aggregation and the results showed loss of helix. The loss of helix leads to the instability of the protein.

Fast smooth second-order sliding mode control for stochastic systems with enumerable coloured noises

NASA Astrophysics Data System (ADS)

Yang, Peng-fei; Fang, Yang-wang; Wu, You-li; Zhang, Dan-xu; Xu, Yang

2018-01-01

A fast smooth second-order sliding mode control is presented for a class of stochastic systems driven by enumerable Ornstein-Uhlenbeck coloured noises with time-varying coefficients. Instead of treating the noise as bounded disturbance, the stochastic control techniques are incorporated into the design of the control. The finite-time mean-square practical stability and finite-time mean-square practical reachability are first introduced. Then the prescribed sliding variable dynamic is presented. The sufficient condition guaranteeing its finite-time convergence is given and proved using stochastic Lyapunov-like techniques. The proposed sliding mode controller is applied to a second-order nonlinear stochastic system. Simulation results are given comparing with smooth second-order sliding mode control to validate the analysis.

A new adaptive multiple modelling approach for non-linear and non-stationary systems

NASA Astrophysics Data System (ADS)

Chen, Hao; Gong, Yu; Hong, Xia

2016-07-01

This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.

Non-linear Post Processing Image Enhancement

NASA Technical Reports Server (NTRS)

Hunt, Shawn; Lopez, Alex; Torres, Angel

1997-01-01

A non-linear filter for image post processing based on the feedforward Neural Network topology is presented. This study was undertaken to investigate the usefulness of "smart" filters in image post processing. The filter has shown to be useful in recovering high frequencies, such as those lost during the JPEG compression-decompression process. The filtered images have a higher signal to noise ratio, and a higher perceived image quality. Simulation studies comparing the proposed filter with the optimum mean square non-linear filter, showing examples of the high frequency recovery, and the statistical properties of the filter are given,

Optical pattern recognition architecture implementing the mean-square error correlation algorithm

DOEpatents

Molley, Perry A.

1991-01-01

An optical architecture implementing the mean-square error correlation algorithm, MSE=.SIGMA.[I-R].sup.2 for discriminating the presence of a reference image R in an input image scene I by computing the mean-square-error between a time-varying reference image signal s.sub.1 (t) and a time-varying input image signal s.sub.2 (t) includes a laser diode light source which is temporally modulated by a double-sideband suppressed-carrier source modulation signal I.sub.1 (t) having the form I.sub.1 (t)=A.sub.1 [1+.sqroot.2m.sub.1 s.sub.1 (t)cos (2.pi.f.sub.o t)] and the modulated light output from the laser diode source is diffracted by an acousto-optic deflector. The resultant intensity of the +1 diffracted order from the acousto-optic device is given by: I.sub.2 (t)=A.sub.2 [+2m.sub.2.sup.2 s.sub.2.sup.2 (t)-2.sqroot.2m.sub.2 (t) cos (2.pi.f.sub.o t] The time integration of the two signals I.sub.1 (t) and I.sub.2 (t) on the CCD deflector plane produces the result R(.tau.) of the mean-square error having the form: R(.tau.)=A.sub.1 A.sub.2 {[T]+[2m.sub.2.sup.2.multidot..intg.s.sub.2.sup.2 (t-.tau.)dt]-[2m.sub.1 m.sub.2 cos (2.tau.f.sub.o .tau.).multidot..intg.s.sub.1 (t)s.sub.2 (t-.tau.)dt]} where: s.sub.1 (t) is the signal input to the diode modulation source: s.sub.2 (t) is the signal input to the AOD modulation source; A.sub.1 is the light intensity; A.sub.2 is the diffraction efficiency; m.sub.1 and m.sub.2 are constants that determine the signal-to-bias ratio; f.sub.o is the frequency offset between the oscillator at f.sub.c and the modulation at f.sub.c +f.sub.o ; and a.sub.o and a.sub.1 are constant chosen to bias the diode source and the acousto-optic deflector into their respective linear operating regions so that the diode source exhibits a linear intensity characteristic and the AOD exhibits a linear amplitude characteristic.

Global synchronization of memristive neural networks subject to random disturbances via distributed pinning control.

PubMed

Guo, Zhenyuan; Yang, Shaofu; Wang, Jun

2016-12-01

This paper presents theoretical results on global exponential synchronization of multiple memristive neural networks in the presence of external noise by means of two types of distributed pinning control. The multiple memristive neural networks are coupled in a general structure via a nonlinear function, which consists of a linear diffusive term and a discontinuous sign term. A pinning impulsive control law is introduced in the coupled system to synchronize all neural networks. Sufficient conditions are derived for ascertaining global exponential synchronization in mean square. In addition, a pinning adaptive control law is developed to achieve global exponential synchronization in mean square. Both pinning control laws utilize only partial state information received from the neighborhood of the controlled neural network. Simulation results are presented to substantiate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nonergodic property of the space-time coupled CTRW: Dependence on the long-tailed property and correlation

NASA Astrophysics Data System (ADS)

Liu, Jian; Li, Baohe; Chen, Xiaosong

2018-02-01

The space-time coupled continuous time random walk model is a stochastic framework of anomalous diffusion with many applications in physics, geology and biology. In this manuscript the time averaged mean squared displacement and nonergodic property of a space-time coupled continuous time random walk model is studied, which is a prototype of the coupled continuous time random walk presented and researched intensively with various methods. The results in the present manuscript show that the time averaged mean squared displacements increase linearly with lag time which means ergodicity breaking occurs, besides, we find that the diffusion coefficient is intrinsically random which shows both aging and enhancement, the analysis indicates that the either aging or enhancement phenomena are determined by the competition between the correlation exponent γ and the waiting time's long-tailed index α.

Deciphering the Dynamics of Non-Covalent Interactions Affecting Thermal Stability of a Protein: Molecular Dynamics Study on Point Mutant of Thermus thermophilus Isopropylmalate Dehydrogenase.

PubMed

Sharma, Reetu; Sastry, G Narahari

2015-01-01

Thermus thermophilius isopropylmalate dehydrogenase catalyzes oxidative decarboxylation and dehydrogenation of isopropylmalate. Substitution of leucine to alanine at position 172 enhances the thermal stability among the known point mutants. Exploring the dynamic properties of non-covalent interactions such as saltbridges, hydrogen bonds and hydrophobic interactions to explain thermal stability of a protein is interesting in its own right. In this study dynamic changes in the non-covalent interactions are studied to decipher the deterministic features of thermal stability of a protein considering a case study of a point mutant in Thermus thermophilus isopropylmalate dehydrogenase. A total of four molecular dynamic simulations of 0.2 μs were carried out on wild type and mutant's functional dimers at 300 K and 337 K. Higher thermal stability of the mutant as compared to wild type is revealed by root mean square deviation, root mean square fluctuations and Cα-Cα distance with an increase in temperature from 300 K to 337 K. Most of the regions of wild type fluctuate higher than the corresponding regions of mutant with an increase in temperature. Cα-Cα distance analysis suggests that long distance networks are significantly affected in wild type as compared to the mutant. Short lived contacts are higher in wild type, while long lived contacts are lost at 337 K. The mutant forms less hydrogen bonds with water as compared to wild type at 337 K. In contrast to wild type, the mutant shows significant increase in unique saltbridges, hydrogen bonds and hydrophobic contacts at 337 K. The current study indicates that there is a strong inter-dependence of thermal stability on the way in which non-covalent interactions reorganize, and it is rewarding to explore this connection in single mutant studies.

Experimental evaluation of leaky least-mean-square algorithms for active noise reduction in communication headsets.

PubMed

Cartes, David A; Ray, Laura R; Collier, Robert D

2002-04-01

An adaptive leaky normalized least-mean-square (NLMS) algorithm has been developed to optimize stability and performance of active noise cancellation systems. The research addresses LMS filter performance issues related to insufficient excitation, nonstationary noise fields, and time-varying signal-to-noise ratio. The adaptive leaky NLMS algorithm is based on a Lyapunov tuning approach in which three candidate algorithms, each of which is a function of the instantaneous measured reference input, measurement noise variance, and filter length, are shown to provide varying degrees of tradeoff between stability and noise reduction performance. Each algorithm is evaluated experimentally for reduction of low frequency noise in communication headsets, and stability and noise reduction performance are compared with that of traditional NLMS and fixed-leakage NLMS algorithms. Acoustic measurements are made in a specially designed acoustic test cell which is based on the original work of Ryan et al. ["Enclosure for low frequency assessment of active noise reducing circumaural headsets and hearing protection," Can. Acoust. 21, 19-20 (1993)] and which provides a highly controlled and uniform acoustic environment. The stability and performance of the active noise reduction system, including a prototype communication headset, are investigated for a variety of noise sources ranging from stationary tonal noise to highly nonstationary measured F-16 aircraft noise over a 20 dB dynamic range. Results demonstrate significant improvements in stability of Lyapunov-tuned LMS algorithms over traditional leaky or nonleaky normalized algorithms, while providing noise reduction performance equivalent to that of the NLMS algorithm for idealized noise fields.

Mechanistic insights into the urea-induced denaturation of kinase domain of human integrin linked kinase.

PubMed

Syed, Sunayana Begum; Khan, Faez Iqbal; Khan, Sabab Hasan; Srivastava, Saurabha; Hasan, Gulam Mustafa; Lobb, Kevin A; Islam, Asimul; Ahmad, Faizan; Hassan, Md Imtaiyaz

2018-05-01

Integrin-linked kinase (ILK), a ubiquitously expressed intracellular Ser/Thr protein kinase, plays a major role in the oncogenesis and tumour progression. The conformational stability and unfolding of kinase domain of ILK (ILK 193-446 ) was examined in the presence of increasing concentrations of urea. The stability parameters of the urea-induced denaturation were measured by monitoring changes in [θ] 222 (mean residue ellipticity at 222nm), difference absorption coefficient at 292nm (Δε 292 ) and intrinsic fluorescence emission intensity at pH7.5 and 25±0.1°C. The urea-induced denaturation was found to be reversible. The protein unfolding transition occurred in the urea concentration range 3.0-7.0M. A coincidence of normalized denaturation curves of optical properties ([θ] 222 , Δε 292 and λ max , the wavelength of maximum emission intensity) suggested that urea-induced denaturation of kinase domain of ILK is a two-state process. We further performed molecular dynamics simulation for 100ns to see the effect of urea on structural stability of kinase domain of ILK at atomic level. Structural changes with increasing concentrations of urea were analysed, and we observed a significant increase in the root mean square deviation, root mean square fluctuations, solvent accessible surface area and radius of gyration. A correlation was observed between in vitro and in silico studies. Copyright © 2018 Elsevier B.V. All rights reserved.

Coronal Heating and the Increase of Coronal Luminosity with Magnetic Flux

NASA Technical Reports Server (NTRS)

Moore, R. L.; Falconer, D. A.; Porter, J. G.; Hathaway, D. H.; Six, N. Frank (Technical Monitor)

2002-01-01

We present the observed scaling of coronal luminosity with magnetic flux in a set of quiet regions. Comparison of this with the observed scaling found for active regions suggests an underlying difference between coronal heating in active regions and quiet regions. From SOHO/EIT coronal images and SOHO/MDI magnetograms of four similar large quiet regions, we measure L(sub corona) and Phi(sub total) in random subregions ranging in area from about four supergranules [(70,000 km)(exp 2)] to about 100 supergranules [(0.5 R(sub sun))(exp 2)], where L(sub corona) is the luminosity of the corona in a subregion and Phi(sub total) is the flux content of the magnetic network in the subregion. This sampling of our quiet regions yields a correlation plot of Log L(sub corona) vs Log Phi(sub total) appropriate for comparison with the corresponding plot for active regions. For our quiet regions, the mean values of L(sub corona) and Phi(sub total) both increase linearly with area (simply because each set of subregions of the same area has very nearly the same mean coronal luminosity per unit area and mean magnetic flux per unit area), and in each constant-area set the values of L(sub corona) and Phi(sub total) 'scatter' about their means for that area. This results in the linear least-squares fit to the Log ((L (sub corona)), vs Log ((Phi (sub total)) plot having a slope somewhat less than one. If active regions mimicked our quiet regions in that all large sets of same-area active regions had the same mean coronal luminosity per unit area and same mean magnetic flux per unit area, then the least-squares fit to their Log((L (sub corona)) vs Log((Phi (sub total)) plot would also have a slope of less than one. Instead, the slope for active regions is 1.2. Given the observed factor of three scatter about the least-squares linear fit, this slope is consistent with Phi(sub total) on average increasing linearly with area (A) as in quiet regions, but L(sub corona) on average increasing as the volume (A(exp 1.5)) of the active region instead of as the area. This possibility is reasonable if the heating in active regions is a burning down of previously-stored coronal magnetic energy rather than a steady dissipation of energy flux from below as expected in quiet regions.

Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System.

PubMed

Tang, Jinjun; Zou, Yajie; Ash, John; Zhang, Shen; Liu, Fang; Wang, Yinhai

2016-01-01

Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system are traffic flow data (volume, occupancy, and speed) collected from loop detectors located at points both upstream and downstream of a given link, and the output variable is the link travel time. A first order Takagi-Sugeno fuzzy rule set is used to complete the inference. For training the evolving fuzzy neural network (EFNN), two learning processes are proposed: (1) a K-means method is employed to partition input samples into different clusters, and a Gaussian fuzzy membership function is designed for each cluster to measure the membership degree of samples to the cluster centers. As the number of input samples increases, the cluster centers are modified and membership functions are also updated; (2) a weighted recursive least squares estimator is used to optimize the parameters of the linear functions in the Takagi-Sugeno type fuzzy rules. Testing datasets consisting of actual and simulated data are used to test the proposed method. Three common criteria including mean absolute error (MAE), root mean square error (RMSE), and mean absolute relative error (MARE) are utilized to evaluate the estimation performance. Estimation results demonstrate the accuracy and effectiveness of the EFNN method through comparison with existing methods including: multiple linear regression (MLR), instantaneous model (IM), linear model (LM), neural network (NN), and cumulative plots (CP).

Travel Time Estimation Using Freeway Point Detector Data Based on Evolving Fuzzy Neural Inference System

PubMed Central

Tang, Jinjun; Zou, Yajie; Ash, John; Zhang, Shen; Liu, Fang; Wang, Yinhai

2016-01-01

Travel time is an important measurement used to evaluate the extent of congestion within road networks. This paper presents a new method to estimate the travel time based on an evolving fuzzy neural inference system. The input variables in the system are traffic flow data (volume, occupancy, and speed) collected from loop detectors located at points both upstream and downstream of a given link, and the output variable is the link travel time. A first order Takagi-Sugeno fuzzy rule set is used to complete the inference. For training the evolving fuzzy neural network (EFNN), two learning processes are proposed: (1) a K-means method is employed to partition input samples into different clusters, and a Gaussian fuzzy membership function is designed for each cluster to measure the membership degree of samples to the cluster centers. As the number of input samples increases, the cluster centers are modified and membership functions are also updated; (2) a weighted recursive least squares estimator is used to optimize the parameters of the linear functions in the Takagi-Sugeno type fuzzy rules. Testing datasets consisting of actual and simulated data are used to test the proposed method. Three common criteria including mean absolute error (MAE), root mean square error (RMSE), and mean absolute relative error (MARE) are utilized to evaluate the estimation performance. Estimation results demonstrate the accuracy and effectiveness of the EFNN method through comparison with existing methods including: multiple linear regression (MLR), instantaneous model (IM), linear model (LM), neural network (NN), and cumulative plots (CP). PMID:26829639

Adaptation to extreme environments: macromolecular dynamics in bacteria compared in vivo by neutron scattering

PubMed Central

Tehei, Moeava; Franzetti, Bruno; Madern, Dominique; Ginzburg, Margaret; Ginzburg, Ben Z; Giudici-Orticoni, Marie-Thérèse; Bruschi, Mireille; Zaccai, Giuseppe

2004-01-01

Mean macromolecular dynamics was quantified in vivo by neutron scattering in psychrophile, mesophile, thermophile and hyperthermophile bacteria. Root mean square atomic fluctuation amplitudes determining macromolecular flexibility were found to be similar for each organism at its physiological temperature (∼1 Å in the 0.1 ns timescale). Effective force constants determining the mean macromolecular resilience were found to increase with physiological temperature from 0.2 N/m for the psychrophiles, which grow at 4°C, to 0.6 N/m for the hyperthermophiles (85°C), indicating that the increase in stabilization free energy is dominated by enthalpic rather than entropic terms. Larger resilience allows macromolecular stability at high temperatures, while maintaining flexibility within acceptable limits for biological activity. PMID:14710189

Long-Term Stability of Radio Sources in VLBI Analysis

NASA Technical Reports Server (NTRS)

Engelhardt, Gerald; Thorandt, Volkmar

2010-01-01

Positional stability of radio sources is an important requirement for modeling of only one source position for the complete length of VLBI data of presently more than 20 years. The stability of radio sources can be verified by analyzing time series of radio source coordinates. One approach is a statistical test for normal distribution of residuals to the weighted mean for each radio source component of the time series. Systematic phenomena in the time series can thus be detected. Nevertheless, an inspection of rate estimation and weighted root-mean-square (WRMS) variations about the mean is also necessary. On the basis of the time series computed by the BKG group in the frame of the ICRF2 working group, 226 stable radio sources with an axis stability of 10 as could be identified. They include 100 ICRF2 axes-defining sources which are determined independently of the method applied in the ICRF2 working group. 29 stable radio sources with a source structure index of less than 3.0 can also be used to increase the number of 295 ICRF2 defining sources.

Influence of Turbulent Flows in the Nozzle on Melt Flow Within a Slab Mold and Stability of the Metal-Flux Interface

NASA Astrophysics Data System (ADS)

Calderon-Ramos, Ismael; Morales, R. D.

2016-06-01

The design of the ports of a casting nozzle has profound effects on the fluid flow patterns in slab molds. The influence of these outlets have also considerable effects on the turbulent flow and turbulence variables inside the nozzle itself. To understand the effects of nozzle design, three approaches were employed: a theoretical analysis based on the turbulent viscosity hypothesis, dimensional analysis (both analyses aided by computer fluid dynamics), and experiments using particle image velocimetry. The first approach yields a linear relation between calculated magnitudes of scalar fields of ɛ (dissipation rate of kinetic energy) and k 2 (square of the turbulent kinetic energy), which is derived from the wall and the logarithmic-wall laws in the boundary layers. The smaller the slope of this linear relation is, the better the performance of a given nozzle is for maintaining the stability of the melt-flux interface. The second approach yields also a linear relation between flow rate of liquid metal and the cubic root of the dissipation rate of kinetic energy. In this case, the larger the slope of the linear relation is, the better the performance of a given nozzle is for maintaining the stability of the melt-flux interface. Finally, PIV measurements in a mold water model, together with equations for estimation of critical melt velocities for slag entrainment, were used to quantify the effects of nozzle design on the dynamics of the metal-slag interface. The three approaches agree in the characterization of turbulent flows in continuous casting molds using different nozzles.

Shock wave oscillation driven by turbulent boundary layer fluctuations

NASA Technical Reports Server (NTRS)

Plotkin, K. J.

1972-01-01

Pressure fluctuations due to the interaction of a shock wave with a turbulent boundary layer were investigated. A simple model is proposed in which the shock wave is convected from its mean position by velocity fluctuations in the turbulent boundary layer. Displacement of the shock is assumed limited by a linear restoring mechanism. Predictions of peak root mean square pressure fluctuation and spectral density are in excellent agreement with available experimental data.

Metrics of Balance Control for Use in Screening Tests of Vestibular Function

NASA Technical Reports Server (NTRS)

Fiedler, Matthew; Cohen, Helen; Mulavara, Ajitkumar; Peters, Brian; Miller, Chris; Bloomberg, Jacob

2011-01-01

Decrements in balance control have been documented in astronauts after space flight. Reliable measures of balance control are needed for use in postflight field tests at remote landing sites. Diffusion analysis (DA) is a statistical mechanical tool that shows the average difference of the dependent variable on varying time scales. These techniques have been shown to measure differences in open-loop and closed-loop postural control in astronauts and elderly subjects. The goal of this study was to investigate the reliability of these measures of balance control. Eleven subjects were tested using the Clinical Test of Sensory Interaction on Balance: the subject stood with feet together and arms crossed on a stable or compliant surface, with eyes open or closed and with or without head movements in the pitch or yaw plane. Subjects were instrumented with inertial motion sensors attached to their trunk segment. The DA curves for linear acceleration measures were characterized by linear fits measuring open- (Ds) and closed-loop (Dl) control, and their intersection point (X-int, Y-int). Ds and Y-int showed significant differences between the test conditions. Additionally, Ds was correlated with the root mean square (RMS) of the signal, indicating that RMS was dominated by open-loop events (< 0.5 seconds). The Y-int was found to be correlated with the average linear velocity of trunk movements. Thus DA measures could be applied to derive reliable metrics of balance stability during field tests.

Stability and uncertainty of finite-fault slip inversions: Application to the 2004 Parkfield, California, earthquake

USGS Publications Warehouse

Hartzell, S.; Liu, P.; Mendoza, C.; Ji, C.; Larson, K.M.

2007-01-01

The 2004 Parkfield, California, earthquake is used to investigate stability and uncertainty aspects of the finite-fault slip inversion problem with different a priori model assumptions. We utilize records from 54 strong ground motion stations and 13 continuous, 1-Hz sampled, geodetic instruments. Two inversion procedures are compared: a linear least-squares subfault-based methodology and a nonlinear global search algorithm. These two methods encompass a wide range of the different approaches that have been used to solve the finite-fault slip inversion problem. For the Parkfield earthquake and the inversion of velocity or displacement waveforms, near-surface related site response (top 100 m, frequencies above 1 Hz) is shown to not significantly affect the solution. Results are also insensitive to selection of slip rate functions with similar duration and to subfault size if proper stabilizing constraints are used. The linear and nonlinear formulations yield consistent results when the same limitations in model parameters are in place and the same inversion norm is used. However, the solution is sensitive to the choice of inversion norm, the bounds on model parameters, such as rake and rupture velocity, and the size of the model fault plane. The geodetic data set for Parkfield gives a slip distribution different from that of the strong-motion data, which may be due to the spatial limitation of the geodetic stations and the bandlimited nature of the strong-motion data. Cross validation and the bootstrap method are used to set limits on the upper bound for rupture velocity and to derive mean slip models and standard deviations in model parameters. This analysis shows that slip on the northwestern half of the Parkfield rupture plane from the inversion of strong-motion data is model dependent and has a greater uncertainty than slip near the hypocenter.

Feasibility study on the least square method for fitting non-Gaussian noise data

NASA Astrophysics Data System (ADS)

Xu, Wei; Chen, Wen; Liang, Yingjie

2018-02-01

This study is to investigate the feasibility of least square method in fitting non-Gaussian noise data. We add different levels of the two typical non-Gaussian noises, Lévy and stretched Gaussian noises, to exact value of the selected functions including linear equations, polynomial and exponential equations, and the maximum absolute and the mean square errors are calculated for the different cases. Lévy and stretched Gaussian distributions have many applications in fractional and fractal calculus. It is observed that the non-Gaussian noises are less accurately fitted than the Gaussian noise, but the stretched Gaussian cases appear to perform better than the Lévy noise cases. It is stressed that the least-squares method is inapplicable to the non-Gaussian noise cases when the noise level is larger than 5%.

The Improved Estimation of Ratio of Two Population Proportions

ERIC Educational Resources Information Center

Solanki, Ramkrishna S.; Singh, Housila P.

2016-01-01

In this article, first we obtained the correct mean square error expression of Gupta and Shabbir's linear weighted estimator of the ratio of two population proportions. Later we suggested the general class of ratio estimators of two population proportions. The usual ratio estimator, Wynn-type estimator, Singh, Singh, and Kaur difference-type…

Scalable analysis of nonlinear systems using convex optimization

NASA Astrophysics Data System (ADS)

Papachristodoulou, Antonis

In this thesis, we investigate how convex optimization can be used to analyze different classes of nonlinear systems at various scales algorithmically. The methodology is based on the construction of appropriate Lyapunov-type certificates using sum of squares techniques. After a brief introduction on the mathematical tools that we will be using, we turn our attention to robust stability and performance analysis of systems described by Ordinary Differential Equations. A general framework for constrained systems analysis is developed, under which stability of systems with polynomial, non-polynomial vector fields and switching systems, as well estimating the region of attraction and the L2 gain can be treated in a unified manner. We apply our results to examples from biology and aerospace. We then consider systems described by Functional Differential Equations (FDEs), i.e., time-delay systems. Their main characteristic is that they are infinite dimensional, which complicates their analysis. We first show how the complete Lyapunov-Krasovskii functional can be constructed algorithmically for linear time-delay systems. Then, we concentrate on delay-independent and delay-dependent stability analysis of nonlinear FDEs using sum of squares techniques. An example from ecology is given. The scalable stability analysis of congestion control algorithms for the Internet is investigated next. The models we use result in an arbitrary interconnection of FDE subsystems, for which we require that stability holds for arbitrary delays, network topologies and link capacities. Through a constructive proof, we develop a Lyapunov functional for FAST---a recently developed network congestion control scheme---so that the Lyapunov stability properties scale with the system size. We also show how other network congestion control schemes can be analyzed in the same way. Finally, we concentrate on systems described by Partial Differential Equations. We show that axially constant perturbations of the Navier-Stokes equations for Hagen-Poiseuille flow are globally stable, even though the background noise is amplified as R3 where R is the Reynolds number, giving a 'robust yet fragile' interpretation. We also propose a sum of squares methodology for the analysis of systems described by parabolic PDEs. We conclude this work with an account for future research.

Stabilizing skateboard speed-wobble with reflex delay.

PubMed

Varszegi, Balazs; Takacs, Denes; Stepan, Gabor; Hogan, S John

2016-08-01

A simple mechanical model of the skateboard-skater system is analysed, in which the effect of human control is considered by means of a linear proportional-derivative (PD) controller with delay. The equations of motion of this non-holonomic system are neutral delay-differential equations. A linear stability analysis of the rectilinear motion is carried out analytically. It is shown how to vary the control gains with respect to the speed of the skateboard to stabilize the uniform motion. The critical reflex delay of the skater is determined as the function of the speed. Based on this analysis, we present an explanation for the linear instability of the skateboard-skater system at high speed. Moreover, the advantages of standing ahead of the centre of the board are demonstrated from the viewpoint of reflex delay and control gain sensitivity. © 2016 The Author(s).

Analysis of Decomposition for Structure I Methane Hydrate by Molecular Dynamics Simulation

NASA Astrophysics Data System (ADS)

Wei, Na; Sun, Wan-Tong; Meng, Ying-Feng; Liu, An-Qi; Zhou, Shou-Wei; Guo, Ping; Fu, Qiang; Lv, Xin

2018-05-01

Under multi-nodes of temperatures and pressures, microscopic decomposition mechanisms of structure I methane hydrate in contact with bulk water molecules have been studied through LAMMPS software by molecular dynamics simulation. Simulation system consists of 482 methane molecules in hydrate and 3027 randomly distributed bulk water molecules. Through analyses of simulation results, decomposition number of hydrate cages, density of methane molecules, radial distribution function for oxygen atoms, mean square displacement and coefficient of diffusion of methane molecules have been studied. A significant result shows that structure I methane hydrate decomposes from hydrate-bulk water interface to hydrate interior. As temperature rises and pressure drops, the stabilization of hydrate will weaken, decomposition extent will go deep, and mean square displacement and coefficient of diffusion of methane molecules will increase. The studies can provide important meanings for the microscopic decomposition mechanisms analyses of methane hydrate.

Learning curve of single port laparoscopic cholecystectomy determined using the non-linear ordinary least squares method based on a non-linear regression model: An analysis of 150 consecutive patients.

PubMed

Han, Hyung Joon; Choi, Sae Byeol; Park, Man Sik; Lee, Jin Suk; Kim, Wan Bae; Song, Tae Jin; Choi, Sang Yong

2011-07-01

Single port laparoscopic surgery has come to the forefront of minimally invasive surgery. For those familiar with conventional techniques, however, this type of operation demands a different type of eye/hand coordination and involves unfamiliar working instruments. Herein, the authors describe the learning curve and the clinical outcomes of single port laparoscopic cholecystectomy for 150 consecutive patients with benign gallbladder disease. All patients underwent single port laparoscopic cholecystectomy using a homemade glove port by one of five operators with different levels of experiences of laparoscopic surgery. The learning curve for each operator was fitted using the non-linear ordinary least squares method based on a non-linear regression model. Mean operating time was 77.6 ± 28.5 min. Fourteen patients (6.0%) were converted to conventional laparoscopic cholecystectomy. Complications occurred in 15 patients (10.0%), as follows: bile duct injury (n = 2), surgical site infection (n = 8), seroma (n = 2), and wound pain (n = 3). One operator achieved a learning curve plateau at 61.4 min per procedure after 8.5 cases and his time improved by 95.3 min as compared with initial operation time. Younger surgeons showed significant decreases in mean operation time and achieved stable mean operation times. In particular, younger surgeons showed significant decreases in operation times after 20 cases. Experienced laparoscopic surgeons can safely perform single port laparoscopic cholecystectomy using conventional or angled laparoscopic instruments. The present study shows that an operator can overcome the single port laparoscopic cholecystectomy learning curve in about eight cases.

Pharmaceutical solid-state kinetic stability investigation by using moisture-modified Arrhenius equation and JMP statistical software.

PubMed

Fu, Mingkun; Perlman, Michael; Lu, Qing; Varga, Csanad

2015-03-25

An accelerated stress approach utilizing the moisture-modified Arrhenius equation and JMP statistical software was utilized to quantitatively assess the solid state stability of an investigational oncology drug MLNA under the influence of temperature (1/T) and humidity (%RH). Physical stability of MLNA under stress conditions was evaluated by using XRPD, DSC, TGA, and DVS, while chemical stability was evaluated by using HPLC. The major chemical degradation product was identified as a hydrolysis product of MLNA drug substance, and was subsequently subjected to an investigation of kinetics based on the isoconversion concept. A mathematical model (ln k=-11,991×(1/T)+0.0298×(%RH)+29.8823) based on the initial linear kinetics observed for the formation of this degradant at all seven stress conditions was built by using the moisture-modified Arrhenius equation and JMP statistical software. Comparison of the predicted versus experimental lnk values gave a mean deviation value of 5.8%, an R(2) value of 0.94, a p-value of 0.0038, and a coefficient of variation of the root mean square error CV(RMSE) of 7.9%. These statistics all indicated a good fit to the model for the stress data of MLNA. Both temperature and humidity were shown to have a statistically significant impact on stability by using effect leverage plots (p-value<0.05 for both 1/T and %RH). Inclusion of a term representing the interaction of relative humidity and temperature (%RH×1/T) was shown not to be justified by using Analysis of Covariance (ANCOVA), which supported the use of the moisture-corrected Arrhenius equation modeling theory. The model was found to be of value to aid setting of specifications and retest period, and storage condition selection. A model was also generated using only four conditions, as an example from a resource saving perspective, which was found to provide a good fit to the entire set of data. Copyright © 2015 Elsevier B.V. All rights reserved.

Within-Session Stability of Short-Term Heart Rate Variability Measurement

PubMed Central

2016-01-01

Abstract The primary aim of this study was to assess the retest stability of the short-term heart rate variability (HRV) measurement performed within one session and without the use of any intervention. Additionally, a precise investigation of the possible impact of intrinsic biological variation on HRV reliability was also performed. First, a single test-retest HRV measurement was conducted with 20-30 min apart from one another. Second, the HRV measurement was repeated in ten non-interrupted consecutive intervals. The lowest typical error (CV = 21.1%) was found for the square root of the mean squared differences of successive RR intervals (rMSSD) and the highest for the low frequency power (PLF) (CV = 93.9%). The standardized changes in the mean were trivial to small. The correlation analysis revealed the highest level for ln rMSSD (ICC = 0.87), while ln PLF represented the worst case (ICC = 0.59). The reliability indices for ln rMSSD in 10 consecutive intervals improved (CV = 9.9%; trivial standardized changes in the mean; ICC = 0.96). In conclusion, major differences were found in the reliability level between the HRV indices. The rMSSD demonstrated the highest reliability level. No substantial influence of intrinsic biological variation on the HRV reliability was observed. PMID:28149345

Alternative approaches to predicting methane emissions from dairy cows.

PubMed

Mills, J A N; Kebreab, E; Yates, C M; Crompton, L A; Cammell, S B; Dhanoa, M S; Agnew, R E; France, J

2003-12-01

Previous attempts to apply statistical models, which correlate nutrient intake with methane production, have been of limited value where predictions are obtained for nutrient intakes and diet types outside those used in model construction. Dynamic mechanistic models have proved more suitable for extrapolation, but they remain computationally expensive and are not applied easily in practical situations. The first objective of this research focused on employing conventional techniques to generate statistical models of methane production appropriate to United Kingdom dairy systems. The second objective was to evaluate these models and a model published previously using both United Kingdom and North American data sets. Thirdly, nonlinear models were considered as alternatives to the conventional linear regressions. The United Kingdom calorimetry data used to construct the linear models also were used to develop the three nonlinear alternatives that were all of modified Mitscherlich (monomolecular) form. Of the linear models tested, an equation from the literature proved most reliable across the full range of evaluation data (root mean square prediction error = 21.3%). However, the Mitscherlich models demonstrated the greatest degree of adaptability across diet types and intake level. The most successful model for simulating the independent data was a modified Mitscherlich equation with the steepness parameter set to represent dietary starch-to-ADF ratio (root mean square prediction error = 20.6%). However, when such data were unavailable, simpler Mitscherlich forms relating dry matter or metabolizable energy intake to methane production remained better alternatives relative to their linear counterparts.

Comparison of two-concentration with multi-concentration linear regressions: Retrospective data analysis of multiple regulated LC-MS bioanalytical projects.

PubMed

Musuku, Adrien; Tan, Aimin; Awaiye, Kayode; Trabelsi, Fethi

2013-09-01

Linear calibration is usually performed using eight to ten calibration concentration levels in regulated LC-MS bioanalysis because a minimum of six are specified in regulatory guidelines. However, we have previously reported that two-concentration linear calibration is as reliable as or even better than using multiple concentrations. The purpose of this research is to compare two-concentration with multiple-concentration linear calibration through retrospective data analysis of multiple bioanalytical projects that were conducted in an independent regulated bioanalytical laboratory. A total of 12 bioanalytical projects were randomly selected: two validations and two studies for each of the three most commonly used types of sample extraction methods (protein precipitation, liquid-liquid extraction, solid-phase extraction). When the existing data were retrospectively linearly regressed using only the lowest and the highest concentration levels, no extra batch failure/QC rejection was observed and the differences in accuracy and precision between the original multi-concentration regression and the new two-concentration linear regression are negligible. Specifically, the differences in overall mean apparent bias (square root of mean individual bias squares) are within the ranges of -0.3% to 0.7% and 0.1-0.7% for the validations and studies, respectively. The differences in mean QC concentrations are within the ranges of -0.6% to 1.8% and -0.8% to 2.5% for the validations and studies, respectively. The differences in %CV are within the ranges of -0.7% to 0.9% and -0.3% to 0.6% for the validations and studies, respectively. The average differences in study sample concentrations are within the range of -0.8% to 2.3%. With two-concentration linear regression, an average of 13% of time and cost could have been saved for each batch together with 53% of saving in the lead-in for each project (the preparation of working standard solutions, spiking, and aliquoting). Furthermore, examples are given as how to evaluate the linearity over the entire concentration range when only two concentration levels are used for linear regression. To conclude, two-concentration linear regression is accurate and robust enough for routine use in regulated LC-MS bioanalysis and it significantly saves time and cost as well. Copyright © 2013 Elsevier B.V. All rights reserved.

Daily emotional stress reactivity in emerging adulthood: temporal stability and its predictors.

PubMed

Howland, Maryhope; Armeli, Stephen; Feinn, Richard; Tennen, Howard

2017-03-01

Emotional reactivity to stress is associated with both mental and physical health and has been assumed to be a stable feature of the person. However, recent evidence suggests that the within-person association between stress and negative affect (i.e., affective stress-reactivity) may increase over time and in times of high stress, at least in older adult populations. The objective of the current study was to examine the across-time stability of stress-reactivity in a younger sample - emerging adulthood - and examine neuroticism, overall stress, social support and life events as potential moderators of stability. Undergraduate students (N = 540, mean age = 18.76 years) participated in a measurement burst design, completing a 30-day daily diary annually for four years. Moderators were assessed once at every burst, while negative affect and stress were assessed daily via a secure website. Findings suggest a relatively high degree of rank-order and mean-level stability in stress-reactivity across the four years, and within-person changes in neuroticism and overall stress predicted concurrent shifts in stress-reactivity. Unlike older samples, there was no evidence of an overall linear change in stability over time, though there was significant variability in linear change trajectories.

Synchronous front-face fluorescence spectroscopy for authentication of the adulteration of edible vegetable oil with refined used frying oil.

PubMed

Tan, Jin; Li, Rong; Jiang, Zi-Tao; Tang, Shu-Hua; Wang, Ying; Shi, Meng; Xiao, Yi-Qian; Jia, Bin; Lu, Tian-Xiang; Wang, Hao

2017-02-15

Synchronous front-face fluorescence spectroscopy has been developed for the discrimination of used frying oil (UFO) from edible vegetable oil (EVO), the estimation of the using time of UFO, and the determination of the adulteration of EVO with UFO. Both the heating time of laboratory prepared UFO and the adulteration of EVO with UFO could be determined by partial least squares regression (PLSR). To simulate the EVO adulteration with UFO, for each kind of oil, fifty adulterated samples at the adulterant amounts range of 1-50% were prepared. PLSR was then adopted to build the model and both full (leave-one-out) cross-validation and external validation were performed to evaluate the predictive ability. Under the optimum condition, the plots of observed versus predicted values exhibited high linearity (R(2)>0.96). The root mean square error of cross-validation (RMSECV) and root mean square error of prediction (RMSEP) were both lower than 3%. Copyright © 2016 Elsevier Ltd. All rights reserved.

Feasibility of using near infrared spectroscopy to detect and quantify an adulterant in high quality sandalwood oil.

PubMed

Kuriakose, Saji; Joe, I Hubert

2013-11-01

Determination of the authenticity of essential oils has become more significant, in recent years, following some illegal adulteration and contamination scandals. The present investigative study focuses on the application of near infrared spectroscopy to detect sample authenticity and quantify economic adulteration of sandalwood oils. Several data pre-treatments are investigated for calibration and prediction using partial least square regression (PLSR). The quantitative data analysis is done using a new spectral approach - full spectrum or sequential spectrum. The optimum number of PLS components is obtained according to the lowest root mean square error of calibration (RMSEC=0.00009% v/v). The lowest root mean square error of prediction (RMSEP=0.00016% v/v) in the test set and the highest coefficient of determination (R(2)=0.99989) are used as the evaluation tools for the best model. A nonlinear method, locally weighted regression (LWR), is added to extract nonlinear information and to compare with the linear PLSR model. Copyright © 2013 Elsevier B.V. All rights reserved.

Feasibility of using near infrared spectroscopy to detect and quantify an adulterant in high quality sandalwood oil

NASA Astrophysics Data System (ADS)

Kuriakose, Saji; Joe, I. Hubert

2013-11-01

Determination of the authenticity of essential oils has become more significant, in recent years, following some illegal adulteration and contamination scandals. The present investigative study focuses on the application of near infrared spectroscopy to detect sample authenticity and quantify economic adulteration of sandalwood oils. Several data pre-treatments are investigated for calibration and prediction using partial least square regression (PLSR). The quantitative data analysis is done using a new spectral approach - full spectrum or sequential spectrum. The optimum number of PLS components is obtained according to the lowest root mean square error of calibration (RMSEC = 0.00009% v/v). The lowest root mean square error of prediction (RMSEP = 0.00016% v/v) in the test set and the highest coefficient of determination (R2 = 0.99989) are used as the evaluation tools for the best model. A nonlinear method, locally weighted regression (LWR), is added to extract nonlinear information and to compare with the linear PLSR model.

Existence, uniqueness, and stability of stochastic neutral functional differential equations of Sobolev-type

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xuetao; Zhu, Quanxin, E-mail: zqx22@126.com

2015-12-15

In this paper, we are mainly concerned with a class of stochastic neutral functional differential equations of Sobolev-type with Poisson jumps. Under two different sets of conditions, we establish the existence of the mild solution by applying the Leray-Schauder alternative theory and the Sadakovskii’s fixed point theorem, respectively. Furthermore, we use the Bihari’s inequality to prove the Osgood type uniqueness. Also, the mean square exponential stability is investigated by applying the Gronwall inequality. Finally, two examples are given to illustrate the theory results.

On the phase lag of turbulent dissipation in rotating tidal flows

NASA Astrophysics Data System (ADS)

Zhang, Qianjiang; Wu, Jiaxue

2018-03-01

Field observations of rotating tidal flows in a shallow tidally swept sea reveal that a notable phase lag of both shear production and turbulent dissipation increases with height above the seafloor. These vertical delays of turbulent quantities are approximately equivalent in magnitude to that of squared mean shear. The shear production approximately equals turbulent dissipation over the phase-lag column, and thus a main mechanism of phase lag of dissipation is mean shear, rather than vertical diffusion of turbulent kinetic energy. By relating the phase lag of dissipation to that of the mean shear, a simple formulation with constant eddy viscosity is developed to describe the phase lag in rotating tidal flows. An analytical solution indicates that the phase lag increases linearly with height subjected to a combined effect of tidal frequency, Coriolis parameter and eddy viscosity. The vertical diffusion of momentum associated with eddy viscosity produces the phase lag of squared mean shear, and resultant delay of turbulent quantities. Its magnitude is inhibited by Earth's rotation. Furthermore, a theoretical formulation of the phase lag with a parabolic eddy viscosity profile can be constructed. A first-order approximation of this formulation is still a linear function of height, and its magnitude is approximately 0.8 times that with constant viscosity. Finally, the theoretical solutions of phase lag with realistic viscosity can be satisfactorily justified by realistic phase lags of dissipation.

Robust Control for Microgravity Vibration Isolation using Fixed Order, Mixed H2/Mu Design

NASA Technical Reports Server (NTRS)

Whorton, Mark

2003-01-01

Many space-science experiments need an active isolation system to provide a sufficiently quiescent microgravity environment. Modern control methods provide the potential for both high-performance and robust stability in the presence of parametric uncertainties that are characteristic of microgravity vibration isolation systems. While H2 and H(infinity) methods are well established, neither provides the levels of attenuation performance and robust stability in a compensator with low order. Mixed H2/H(infinity), controllers provide a means for maximizing robust stability for a given level of mean-square nominal performance while directly optimizing for controller order constraints. This paper demonstrates the benefit of mixed norm design from the perspective of robustness to parametric uncertainties and controller order for microgravity vibration isolation. A nominal performance metric analogous to the mu measure, for robust stability assessment is also introduced in order to define an acceptable trade space from which different control methodologies can be compared.

Average characteristics of partially coherent electromagnetic beams.

PubMed

Seshadri, S R

2000-04-01

Average characteristics of partially coherent electromagnetic beams are treated with the paraxial approximation. Azimuthally or radially polarized, azimuthally symmetric beams and linearly polarized dipolar beams are used as examples. The change in the mean squared width of the beam from its value at the location of the beam waist is found to be proportional to the square of the distance in the propagation direction. The proportionality constant is obtained in terms of the cross-spectral density as well as its spatial spectrum. The use of the cross-spectral density has advantages over the use of its spatial spectrum.

Exploring Protein Stability by Comparative Molecular Dynamics Simulations of Homologous Hyperthermophilic, Mesophilic, and Psychrophilic Proteins.

PubMed

Khan, Sara; Farooq, Umar; Kurnikova, Maria

2016-11-28

In the present studies, we analyzed the influence of temperature on the stability and dynamics of the α subunit of tryptophan synthase (TRPS) from hyperthermophilic, mesophilic, and psychrophilic homologues at different temperatures by molecular dynamics simulations. Employing different indicators such as root-mean-square deviations, root-mean-square fluctuations, principal component analysis, and free energy landscapes, this study manifests the diverse behavior of these homologues with changes in temperature. Especially, an enhancement in the collective motions, classified as representative motions, is observed at high temperature. Similarly, the criterion for the selection of electrostatic interactions in terms of their life span (duty cycle) has indeed helped in identifying the short- and long-lived electrostatic interactions and how they affect the protein's overall stability at different temperatures. Rigidity and flexibility patterns of the homologous proteins are examined using FIRST software along with the calculation of duty cycles with various threshold limits at different temperatures. Rigid cluster decomposition in TRPS of psychrophilic, mesophilic, and hyperthermophilic origin identifies the flexible and rigid regions in the protein. Early loss of rigidity is observed in mesophilic TRPS via loss of contact between the major fragments of the protein compared with the other homologues. In spite of the high similarity of their three-dimensional structures, the overall responses of the three proteins to varying temperatures are significantly different.

Non-normality and classification of amplification mechanisms in stability and resolvent analysis

NASA Astrophysics Data System (ADS)

Symon, Sean; Rosenberg, Kevin; Dawson, Scott T. M.; McKeon, Beverley J.

2018-05-01

Eigenspectra and pseudospectra of the mean-linearized Navier-Stokes operator are used to characterize amplification mechanisms in laminar and turbulent flows in which linear mechanisms are important. Success of mean flow (linear) stability analysis for a particular frequency is shown to depend on whether two scalar measures of non-normality agree: (1) the product between the resolvent norm and the distance from the imaginary axis to the closest eigenvalue and (2) the inverse of the inner product between the most amplified resolvent forcing and response modes. If they agree, the resolvent operator can be rewritten in its dyadic representation to reveal that the adjoint and forward stability modes are proportional to the forcing and response resolvent modes at that frequency. Hence the real parts of the eigenvalues are important since they are responsible for resonant amplification and the resolvent operator is low rank when the eigenvalues are sufficiently separated in the spectrum. If the amplification is pseudoresonant, then resolvent analysis is more suitable to understand the origin of observed flow structures. Two test cases are studied: low Reynolds number cylinder flow and turbulent channel flow. The first deals mainly with resonant mechanisms, hence the success of both classical and mean stability analysis with respect to predicting the critical Reynolds number and global frequency of the saturated flow. Both scalar measures of non-normality agree for the base and mean flows, and the region where the forcing and response modes overlap scales with the length of the recirculation bubble. In the case of turbulent channel flow, structures result from both resonant and pseudoresonant mechanisms, suggesting that both are necessary elements to sustain turbulence. Mean shear is exploited most efficiently by stationary disturbances while bounds on the pseudospectra illustrate how pseudoresonance is responsible for the most amplified disturbances at spatial wavenumbers and temporal frequencies corresponding to well-known turbulent structures. Some implications for flow control are discussed.

Development of a coal quality analyzer for application to power plants based on laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Zhang, Lei; Gong, Yao; Li, Yufang; Wang, Xin; Fan, Juanjuan; Dong, Lei; Ma, Weiguang; Yin, Wangbao; Jia, Suotang

2015-11-01

It is vitally important for a power plant to determine the coal property rapidly to optimize the combustion process. In this work, a fully software-controlled laser-induced breakdown spectroscopy (LIBS) based coal quality analyzer comprising a LIBS apparatus, a sampling equipment, and a control module, has been designed for possible application to power plants for offering rapid and precise coal quality analysis results. A closed-loop feedback pulsed laser energy stabilization technology is proposed to stabilize the Nd: YAG laser output energy to a preset interval by using the detected laser energy signal so as to enhance the measurement stability and applied in a month-long monitoring experiment. The results show that the laser energy stability has been greatly reduced from ± 5.2% to ± 1.3%. In order to indicate the complex relationship between the concentrations of the analyte of interest and the corresponding plasma spectra, the support vector regression (SVR) is employed as a non-linear regression method. It is shown that this SVR method combined with principal component analysis (PCA) enables a significant improvement in cross-validation accuracy by using the calibration set of coal samples. The root mean square error for prediction of ash content, volatile matter content, and calorific value decreases from 2.74% to 1.82%, 1.69% to 1.22%, and 1.23 MJ/kg to 0.85 MJ/kg, respectively. Meanwhile, the corresponding average relative error of the predicted samples is reduced from 8.3% to 5.48%, 5.83% to 4.42%, and 5.4% to 3.68%, respectively. The enhanced levels of accuracy obtained with the SVR combined with PCA based calibration models open up avenues for prospective prediction in coal properties.

Tuneable enhancement of the salt and thermal stability of polymeric micelles by cyclized amphiphiles

PubMed Central

Honda, Satoshi; Yamamoto, Takuya; Tezuka, Yasuyuki

2013-01-01

Cyclic molecules provide better stability for their aggregates. Typically in nature, the unique cyclic cell membrane lipids allow thermophilic archaea to inhabit extreme conditions. By mimicking the biological design, the robustness of self-assembled synthetic nanostructures is expected to be improved. Here we report topology effects by cyclized polymeric amphiphiles against their linear counterparts, demonstrating a drastic enhancement in the thermal, as well as salt stability of self-assembled micelles. Furthermore, through coassembly of the linear and cyclic amphiphiles, the stability was successfully tuned for a wide range of temperatures and salt concentrations. The enhanced thermal/salt stability was exploited in a halogen exchange reaction to stimulate the catalytic activity. The mechanism for the enhancement was also investigated. These topology effects by the cyclic amphiphiles offer unprecedented opportunities in polymer materials design unattainable by traditional means. PMID:23481382

Inviscid linear stability analysis of two vertical columns of different densities in a gravitational acceleration field

DOE PAGES

Prathama, Aditya Heru; Pantano, Carlos

2017-08-09

Here, we study the inviscid linear stability of a vertical interface separating two fluids of different densities and subject to a gravitational acceleration field parallel to the interface. In this arrangement, the two free streams are constantly accelerated, which means that the linear stability analysis is not amenable to Fourier or Laplace solution in time. Instead, we derive the equations analytically by the initial-value problem method and express the solution in terms of the well-known parabolic cylinder function. The results, which can be classified as an accelerating Kelvin–Helmholtz configuration, show that even in the presence of surface tension, the interfacemore » is unconditionally unstable at all wavemodes. This is a consequence of the ever increasing momentum of the free streams, as gravity accelerates them indefinitely. The instability can be shown to grow as the exponential of a quadratic function of time.« less

Estimates of tropical analysis differences in daily values produced by two operational centers

NASA Technical Reports Server (NTRS)

Kasahara, Akira; Mizzi, Arthur P.

1992-01-01

To assess the uncertainty of daily synoptic analyses for the atmospheric state, the intercomparison of three First GARP Global Experiment level IIIb datasets is performed. Daily values of divergence, vorticity, temperature, static stability, vertical motion, mixing ratio, and diagnosed diabatic heating rate are compared for the period of 26 January-11 February 1979. The spatial variance and mean, temporal mean and variance, 2D wavenumber power spectrum, anomaly correlation, and normalized square difference are employed for comparison.

Simplified large African carnivore density estimators from track indices.

PubMed

Winterbach, Christiaan W; Ferreira, Sam M; Funston, Paul J; Somers, Michael J

2016-01-01

The range, population size and trend of large carnivores are important parameters to assess their status globally and to plan conservation strategies. One can use linear models to assess population size and trends of large carnivores from track-based surveys on suitable substrates. The conventional approach of a linear model with intercept may not intercept at zero, but may fit the data better than linear model through the origin. We assess whether a linear regression through the origin is more appropriate than a linear regression with intercept to model large African carnivore densities and track indices. We did simple linear regression with intercept analysis and simple linear regression through the origin and used the confidence interval for ß in the linear model y  =  αx  + ß, Standard Error of Estimate, Mean Squares Residual and Akaike Information Criteria to evaluate the models. The Lion on Clay and Low Density on Sand models with intercept were not significant ( P  > 0.05). The other four models with intercept and the six models thorough origin were all significant ( P  < 0.05). The models using linear regression with intercept all included zero in the confidence interval for ß and the null hypothesis that ß = 0 could not be rejected. All models showed that the linear model through the origin provided a better fit than the linear model with intercept, as indicated by the Standard Error of Estimate and Mean Square Residuals. Akaike Information Criteria showed that linear models through the origin were better and that none of the linear models with intercept had substantial support. Our results showed that linear regression through the origin is justified over the more typical linear regression with intercept for all models we tested. A general model can be used to estimate large carnivore densities from track densities across species and study areas. The formula observed track density = 3.26 × carnivore density can be used to estimate densities of large African carnivores using track counts on sandy substrates in areas where carnivore densities are 0.27 carnivores/100 km 2 or higher. To improve the current models, we need independent data to validate the models and data to test for non-linear relationship between track indices and true density at low densities.

Stability and modal analysis of shock/boundary layer interactions

NASA Astrophysics Data System (ADS)

Nichols, Joseph W.; Larsson, Johan; Bernardini, Matteo; Pirozzoli, Sergio

2017-02-01

The dynamics of oblique shock wave/turbulent boundary layer interactions is analyzed by mining a large-eddy simulation (LES) database for various strengths of the incoming shock. The flow dynamics is first analyzed by means of dynamic mode decomposition (DMD), which highlights the simultaneous occurrence of two types of flow modes, namely a low-frequency type associated with breathing motion of the separation bubble, accompanied by flapping motion of the reflected shock, and a high-frequency type associated with the propagation of instability waves past the interaction zone. Global linear stability analysis performed on the mean LES flow fields yields a single unstable zero-frequency mode, plus a variety of marginally stable low-frequency modes whose stability margin decreases with the strength of the interaction. The least stable linear modes are grouped into two classes, one of which bears striking resemblance to the breathing mode recovered from DMD and another class associated with revolving motion within the separation bubble. The results of the modal and linear stability analysis support the notion that low-frequency dynamics is intrinsic to the interaction zone, but some continuous forcing from the upstream boundary layer may be required to keep the system near a limit cycle. This can be modeled as a weakly damped oscillator with forcing, as in the early empirical model by Plotkin (AIAA J 13:1036-1040, 1975).

Using the Ridge Regression Procedures to Estimate the Multiple Linear Regression Coefficients

NASA Astrophysics Data System (ADS)

Gorgees, HazimMansoor; Mahdi, FatimahAssim

2018-05-01

This article concerns with comparing the performance of different types of ordinary ridge regression estimators that have been already proposed to estimate the regression parameters when the near exact linear relationships among the explanatory variables is presented. For this situations we employ the data obtained from tagi gas filling company during the period (2008-2010). The main result we reached is that the method based on the condition number performs better than other methods since it has smaller mean square error (MSE) than the other stated methods.

A unified development of several techniques for the representation of random vectors and data sets

NASA Technical Reports Server (NTRS)

Bundick, W. T.

1973-01-01

Linear vector space theory is used to develop a general representation of a set of data vectors or random vectors by linear combinations of orthonormal vectors such that the mean squared error of the representation is minimized. The orthonormal vectors are shown to be the eigenvectors of an operator. The general representation is applied to several specific problems involving the use of the Karhunen-Loeve expansion, principal component analysis, and empirical orthogonal functions; and the common properties of these representations are developed.

Shear Melting of a Colloidal Glass

NASA Astrophysics Data System (ADS)

Eisenmann, Christoph; Kim, Chanjoong; Mattsson, Johan; Weitz, David A.

2010-01-01

We use confocal microscopy to explore shear melting of colloidal glasses, which occurs at strains of ˜0.08, coinciding with a strongly non-Gaussian step size distribution. For larger strains, the particle mean square displacement increases linearly with strain and the step size distribution becomes Gaussian. The effective diffusion coefficient varies approximately linearly with shear rate, consistent with a modified Stokes-Einstein relationship in which thermal energy is replaced by shear energy and the length scale is set by the size of cooperatively moving regions consisting of ˜3 particles.

Linear stochastic Schrödinger equations in terms of quantum Bernoulli noises

NASA Astrophysics Data System (ADS)

Chen, Jinshu; Wang, Caishi

2017-05-01

Quantum Bernoulli noises (QBN) are the family of annihilation and creation operators acting on Bernoulli functionals, which satisfy a canonical anti-commutation relation. In this paper, we study linear stochastic Schrödinger equations (LSSEs) associated with QBN in the space of square integrable complex-valued Bernoulli functionals. We first rigorously prove a formula concerning the number operator N on Bernoulli functionals. And then, by using this formula as well as Mora and Rebolledo's results on a general LSSE [C. M. Mora and R. Rebolledo, Infinite. Dimens. Anal. Quantum Probab. Relat. Top. 10, 237-259 (2007)], we obtain an easily checking condition for a LSSE associated with QBN to have a unique Nr-strong solution of mean square norm conservation for given r ≥0 . Finally, as an application of this condition, we examine a special class of LSSEs associated with QBN and some further results are proven.

A New Stochastic Equivalent Linearization Implementation for Prediction of Geometrically Nonlinear Vibrations

NASA Technical Reports Server (NTRS)

Muravyov, Alexander A.; Turner, Travis L.; Robinson, Jay H.; Rizzi, Stephen A.

1999-01-01

In this paper, the problem of random vibration of geometrically nonlinear MDOF structures is considered. The solutions obtained by application of two different versions of a stochastic linearization method are compared with exact (F-P-K) solutions. The formulation of a relatively new version of the stochastic linearization method (energy-based version) is generalized to the MDOF system case. Also, a new method for determination of nonlinear sti ness coefficients for MDOF structures is demonstrated. This method in combination with the equivalent linearization technique is implemented in a new computer program. Results in terms of root-mean-square (RMS) displacements obtained by using the new program and an existing in-house code are compared for two examples of beam-like structures.

Least squares reconstruction of non-linear RF phase encoded MR data.

PubMed

Salajeghe, Somaie; Babyn, Paul; Sharp, Jonathan C; Sarty, Gordon E

2016-09-01

The numerical feasibility of reconstructing MRI signals generated by RF coils that produce B1 fields with a non-linearly varying spatial phase is explored. A global linear spatial phase variation of B1 is difficult to produce from current confined to RF coils. Here we use regularized least squares inversion, in place of the usual Fourier transform, to reconstruct signals generated in B1 fields with non-linear phase variation. RF encoded signals were simulated for three RF coil configurations: ideal linear, parallel conductors and, circular coil pairs. The simulated signals were reconstructed by Fourier transform and by regularized least squares. The Fourier reconstruction of simulated RF encoded signals from the parallel conductor coil set showed minor distortions over the reconstruction of signals from the ideal linear coil set but the Fourier reconstruction of signals from the circular coil set produced severe geometric distortion. Least squares inversion in all cases produced reconstruction errors comparable to the Fourier reconstruction of the simulated signal from the ideal linear coil set. MRI signals encoded in B1 fields with non-linearly varying spatial phase may be accurately reconstructed using regularized least squares thus pointing the way to the use of simple RF coil designs for RF encoded MRI. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Month-to-month and year-to-year reproducibility of high frequency QRS ECG signals

NASA Technical Reports Server (NTRS)

Batdorf, Niles J.; Feiveson, Alan H.; Schlegel, Todd T.

2004-01-01

High frequency electrocardiography analyzing the entire QRS complex in the frequency range of 150 to 250 Hz may prove useful in the detection of coronary artery disease, yet the long-term stability of these waveforms has not been fully characterized. Therefore, we prospectively investigated the reproducibility of the root mean squared voltage, kurtosis, and the presence versus absence of reduced amplitude zones in signal averaged 12-lead high frequency QRS recordings acquired in the supine position one month apart in 16 subjects and one year apart in 27 subjects. Reproducibility of root mean squared voltage and kurtosis was excellent over these time intervals in the limb leads, and acceptable in the precordial leads using both the V-lead and CR-lead derivations. The relative error of root mean squared voltage was 12% month-to-month and 16% year-to-year in the serial recordings when averaged over all 12 leads. Reduced amplitude zones were also reproducible up to a rate of 87% and 81%, respectively, for the month-to-month and year-to-year recordings. We conclude that 12-lead high frequency QRS electrocardiograms are sufficiently reproducible for clinical use.

Moments and Root-Mean-Square Error of the Bayesian MMSE Estimator of Classification Error in the Gaussian Model.

PubMed

Zollanvari, Amin; Dougherty, Edward R

2014-06-01

The most important aspect of any classifier is its error rate, because this quantifies its predictive capacity. Thus, the accuracy of error estimation is critical. Error estimation is problematic in small-sample classifier design because the error must be estimated using the same data from which the classifier has been designed. Use of prior knowledge, in the form of a prior distribution on an uncertainty class of feature-label distributions to which the true, but unknown, feature-distribution belongs, can facilitate accurate error estimation (in the mean-square sense) in circumstances where accurate completely model-free error estimation is impossible. This paper provides analytic asymptotically exact finite-sample approximations for various performance metrics of the resulting Bayesian Minimum Mean-Square-Error (MMSE) error estimator in the case of linear discriminant analysis (LDA) in the multivariate Gaussian model. These performance metrics include the first, second, and cross moments of the Bayesian MMSE error estimator with the true error of LDA, and therefore, the Root-Mean-Square (RMS) error of the estimator. We lay down the theoretical groundwork for Kolmogorov double-asymptotics in a Bayesian setting, which enables us to derive asymptotic expressions of the desired performance metrics. From these we produce analytic finite-sample approximations and demonstrate their accuracy via numerical examples. Various examples illustrate the behavior of these approximations and their use in determining the necessary sample size to achieve a desired RMS. The Supplementary Material contains derivations for some equations and added figures.

Temporal Stability of the NDVI-LAI Relationship in a Napa Valley Vineyard

NASA Technical Reports Server (NTRS)

Johnson, L. F.

2003-01-01

Remotely sensed normalized difference vegetation index (NDVI) values, derived from high-resolution satellite images, were compared with ground measurements of vineyard leaf area index (LAI) periodically during the 2001 growing season. The two variables were strongly related at six ground calibration sites on each of four occasions (r squared = 0.91 to 0.98). Linear regression equations relating the two variables did not significantly differ by observation date, and a single equation accounted for 92 percent of the variance in the combined dataset. Temporal stability of the relationship opens the possibility of transforming NDVI maps to LAI in the absence of repeated ground calibration fieldwork. In order to take advantage of this circumstance, however, steps should be taken to assure temporal consistency in spectral data values comprising the NDVI.

Three-dimensional finite amplitude electroconvection in dielectric liquids

NASA Astrophysics Data System (ADS)

Luo, Kang; Wu, Jian; Yi, Hong-Liang; Tan, He-Ping

2018-02-01

Charge injection induced electroconvection in a dielectric liquid lying between two parallel plates is numerically simulated in three dimensions (3D) using a unified lattice Boltzmann method (LBM). Cellular flow patterns and their subcritical bifurcation phenomena of 3D electroconvection are numerically investigated for the first time. A unit conversion is also derived to connect the LBM system to the real physical system. The 3D LBM codes are validated by three carefully chosen cases and all results are found to be highly consistent with the analytical solutions or other numerical studies. For strong injection, the steady state roll, polygon, and square flow patterns are observed under different initial disturbances. Numerical results show that the hexagonal cell with the central region being empty of charge and centrally downward flow is preferred in symmetric systems under random initial disturbance. For weak injection, the numerical results show that the flow directly passes from the motionless state to turbulence once the system loses its linear stability. In addition, the numerically predicted linear and finite amplitude stability criteria of different flow patterns are discussed.

ELAS: A general-purpose computer program for the equilibrium problems of linear structures. Volume 2: Documentation of the program. [subroutines and flow charts

NASA Technical Reports Server (NTRS)

Utku, S.

1969-01-01

A general purpose digital computer program for the in-core solution of linear equilibrium problems of structural mechanics is documented. The program requires minimum input for the description of the problem. The solution is obtained by means of the displacement method and the finite element technique. Almost any geometry and structure may be handled because of the availability of linear, triangular, quadrilateral, tetrahedral, hexahedral, conical, triangular torus, and quadrilateral torus elements. The assumption of piecewise linear deflection distribution insures monotonic convergence of the deflections from the stiffer side with decreasing mesh size. The stresses are provided by the best-fit strain tensors in the least squares at the mesh points where the deflections are given. The selection of local coordinate systems whenever necessary is automatic. The core memory is used by means of dynamic memory allocation, an optional mesh-point relabelling scheme and imposition of the boundary conditions during the assembly time.

Wavelet regression model in forecasting crude oil price

NASA Astrophysics Data System (ADS)

Hamid, Mohd Helmie; Shabri, Ani

2017-05-01

This study presents the performance of wavelet multiple linear regression (WMLR) technique in daily crude oil forecasting. WMLR model was developed by integrating the discrete wavelet transform (DWT) and multiple linear regression (MLR) model. The original time series was decomposed to sub-time series with different scales by wavelet theory. Correlation analysis was conducted to assist in the selection of optimal decomposed components as inputs for the WMLR model. The daily WTI crude oil price series has been used in this study to test the prediction capability of the proposed model. The forecasting performance of WMLR model were also compared with regular multiple linear regression (MLR), Autoregressive Moving Average (ARIMA) and Generalized Autoregressive Conditional Heteroscedasticity (GARCH) using root mean square errors (RMSE) and mean absolute errors (MAE). Based on the experimental results, it appears that the WMLR model performs better than the other forecasting technique tested in this study.

Determination of Bosentan in Pharmaceutical Preparations by Linear Sweep, Square Wave and Differential Pulse Voltammetry Methods

PubMed Central

Atila, Alptug; Yilmaz, Bilal

2015-01-01

In this study, simple, fast and reliable cyclic voltammetry (CV), linear sweep voltammetry (LSV), square wave voltammetry (SWV) and differential pulse voltammetry (DPV) methods were developed and validated for determination of bosentan in pharmaceutical preparations. The proposed methods were based on electrochemical oxidation of bosentan at platinum electrode in acetonitrile solution containing 0.1 M TBACIO4. The well-defined oxidation peak was observed at 1.21 V. The calibration curves were linear for bosentan at the concentration range of 5-40 µg/mL for LSV and 5-35 µg/mL for SWV and DPV methods, respectively. Intra- and inter-day precision values for bosentan were less than 4.92, and accuracy (relative error) was better than 6.29%. The mean recovery of bosentan was 100.7% for pharmaceutical preparations. No interference was found from two tablet excipients at the selected assay conditions. Developed methods in this study are accurate, precise and can be easily applied to Tracleer and Diamond tablets as pharmaceutical preparation. PMID:25901151

Determination of bosentan in pharmaceutical preparations by linear sweep, square wave and differential pulse voltammetry methods.

PubMed

Atila, Alptug; Yilmaz, Bilal

2015-01-01

In this study, simple, fast and reliable cyclic voltammetry (CV), linear sweep voltammetry (LSV), square wave voltammetry (SWV) and differential pulse voltammetry (DPV) methods were developed and validated for determination of bosentan in pharmaceutical preparations. The proposed methods were based on electrochemical oxidation of bosentan at platinum electrode in acetonitrile solution containing 0.1 M TBACIO4. The well-defined oxidation peak was observed at 1.21 V. The calibration curves were linear for bosentan at the concentration range of 5-40 µg/mL for LSV and 5-35 µg/mL for SWV and DPV methods, respectively. Intra- and inter-day precision values for bosentan were less than 4.92, and accuracy (relative error) was better than 6.29%. The mean recovery of bosentan was 100.7% for pharmaceutical preparations. No interference was found from two tablet excipients at the selected assay conditions. Developed methods in this study are accurate, precise and can be easily applied to Tracleer and Diamond tablets as pharmaceutical preparation.

A Parameterized Inversion Model for Soil Moisture and Biomass from Polarimetric Backscattering Coefficients

NASA Technical Reports Server (NTRS)

Truong-Loi, My-Linh; Saatchi, Sassan; Jaruwatanadilok, Sermsak

2012-01-01

A semi-empirical algorithm for the retrieval of soil moisture, root mean square (RMS) height and biomass from polarimetric SAR data is explained and analyzed in this paper. The algorithm is a simplification of the distorted Born model. It takes into account the physical scattering phenomenon and has three major components: volume, double-bounce and surface. This simplified model uses the three backscattering coefficients ( sigma HH, sigma HV and sigma vv) at low-frequency (P-band). The inversion process uses the Levenberg-Marquardt non-linear least-squares method to estimate the structural parameters. The estimation process is entirely explained in this paper, from initialization of the unknowns to retrievals. A sensitivity analysis is also done where the initial values in the inversion process are varying randomly. The results show that the inversion process is not really sensitive to initial values and a major part of the retrievals has a root-mean-square error lower than 5% for soil moisture, 24 Mg/ha for biomass and 0.49 cm for roughness, considering a soil moisture of 40%, roughness equal to 3cm and biomass varying from 0 to 500 Mg/ha with a mean of 161 Mg/ha

Influence of age on the correlations of hematological and biochemical variables with the stability of erythrocyte membrane in relation to sodium dodecyl sulfate.

PubMed

de Freitas, Mariana V; Marquez-Bernardes, Liandra F; de Arvelos, Letícia R; Paraíso, Lara F; Gonçalves E Oliveira, Ana Flávia M; Mascarenhas Netto, Rita de C; Neto, Morun Bernardino; Garrote-Filho, Mario S; de Souza, Paulo César A; Penha-Silva, Nilson

2014-10-01

To evaluate the influence of age on the relationships between biochemical and hematological variables and stability of erythrocyte membrane in relation to the sodium dodecyl sulfate (SDS) in population of 105 female volunteers between 20 and 90 years. The stability of RBC membrane was determined by non-linear regression of the dependency of the absorbance of hemoglobin released as a function of SDS concentration, represented by the half-transition point of the curve (D50) and the variation in the concentration of the detergent to promote lysis (dD). There was an age-dependent increase in the membrane stability in relation to SDS. Analyses by multiple linear regression showed that this stability increase is significantly related to the hematological variable red cell distribution width (RDW) and the biochemical variables blood albumin and cholesterol. The positive association between erythrocyte stability and RDW may reflect one possible mechanism involved in the clinical meaning of this hematological index.

Application of near-infrared spectroscopy for the rapid quality assessment of Radix Paeoniae Rubra

NASA Astrophysics Data System (ADS)

Zhan, Hao; Fang, Jing; Tang, Liying; Yang, Hongjun; Li, Hua; Wang, Zhuju; Yang, Bin; Wu, Hongwei; Fu, Meihong

2017-08-01

Near-infrared (NIR) spectroscopy with multivariate analysis was used to quantify gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra, and the feasibility to classify the samples originating from different areas was investigated. A new high-performance liquid chromatography method was developed and validated to analyze gallic acid, catechin, albiflorin, and paeoniflorin in Radix Paeoniae Rubra as the reference. Partial least squares (PLS), principal component regression (PCR), and stepwise multivariate linear regression (SMLR) were performed to calibrate the regression model. Different data pretreatments such as derivatives (1st and 2nd), multiplicative scatter correction, standard normal variate, Savitzky-Golay filter, and Norris derivative filter were applied to remove the systematic errors. The performance of the model was evaluated according to the root mean square of calibration (RMSEC), root mean square error of prediction (RMSEP), root mean square error of cross-validation (RMSECV), and correlation coefficient (r). The results show that compared to PCR and SMLR, PLS had a lower RMSEC, RMSECV, and RMSEP and higher r for all the four analytes. PLS coupled with proper pretreatments showed good performance in both the fitting and predicting results. Furthermore, the original areas of Radix Paeoniae Rubra samples were partly distinguished by principal component analysis. This study shows that NIR with PLS is a reliable, inexpensive, and rapid tool for the quality assessment of Radix Paeoniae Rubra.

Recursive least squares estimation and its application to shallow trench isolation

NASA Astrophysics Data System (ADS)

Wang, Jin; Qin, S. Joe; Bode, Christopher A.; Purdy, Matthew A.

2003-06-01

In recent years, run-to-run (R2R) control technology has received tremendous interest in semiconductor manufacturing. One class of widely used run-to-run controllers is based on the exponentially weighted moving average (EWMA) statistics to estimate process deviations. Using an EWMA filter to smooth the control action on a linear process has been shown to provide good results in a number of applications. However, for a process with severe drifts, the EWMA controller is insufficient even when large weights are used. This problem becomes more severe when there is measurement delay, which is almost inevitable in semiconductor industry. In order to control drifting processes, a predictor-corrector controller (PCC) and a double EWMA controller have been developed. Chen and Guo (2001) show that both PCC and double-EWMA controller are in effect Integral-double-Integral (I-II) controllers, which are able to control drifting processes. However, since offset is often within the noise of the process, the second integrator can actually cause jittering. Besides, tuning the second filter is not as intuitive as a single EWMA filter. In this work, we look at an alternative way Recursive Least Squares (RLS), to estimate and control the drifting process. EWMA and double-EWMA are shown to be the least squares estimate for locally constant mean model and locally constant linear trend model. Then the recursive least squares with exponential factor is applied to shallow trench isolation etch process to predict the future etch rate. The etch process, which is a critical process in the flash memory manufacturing, is known to suffer from significant etch rate drift due to chamber seasoning. In order to handle the metrology delay, we propose a new time update scheme. RLS with the new time update method gives very good result. The estimate error variance is smaller than that from EWMA, and mean square error decrease more than 10% compared to that from EWMA.

Calculation of Linear Stability of a Stratified Gas-Liquid Flow in an Inclined Plane Channel

NASA Astrophysics Data System (ADS)

Trifonov, Yu. Ya.

2018-01-01

Linear stability of liquid and gas counterflows in an inclined channel is considered. The full Navier-Stokes equations for both phases are linearized, and the dynamics of periodic disturbances is determined by means of solving a spectral problem in wide ranges of Reynolds numbers for the liquid and vapor velocity. Two unstable modes are found in the examined ranges: surface mode (corresponding to the Kapitsa waves at small velocities of the gas) and shear mode in the gas phase. The wave length and the phase velocity of neutral disturbances of both modes are calculated as functions of the Reynolds number for the liquid. It is shown that these dependences for the surface mode are significantly affected by the gas velocity.

Diode end pumped laser and harmonic generator using same

NASA Technical Reports Server (NTRS)

Byer, Robert L. (Inventor); Dixon, George J. (Inventor); Kane, Thomas J. (Inventor)

1988-01-01

A second harmonic, optical generator is disclosed in which a laser diode produces an output pumping beam which is focused by means of a graded, refractive index rod lens into a rod of lasant material, such as Nd:YAG, disposed within an optical resonator to pump the lasant material and to excite the optical resonator at a fundamental wavelength. A non-linear electro-optic material such as MgO:LiNbO.sub.3 is coupled to the excited, fundamental mode of the optical resonator to produce a non-linear interaction with the fundamental wavelength producing a harmonic. In one embodiment, the gain medium and the non-linear material are disposed within an optical resonator defined by a pair of reflectors, one of which is formed on a face of the gain medium and the second of which is formed on a face of the non-linear medium. In another embodiment, the non-linear, electro-optic material is doped with the lasant ion such that the gain medium and the non-linear doubling material are co-extensive in volume. In another embodiment, a non-linear, doubling material is disposed in an optical resonator external of the laser gai medium for improved stability of the second harmonic generation process. In another embodiment, the laser gain medium andthe non-linear material are bonded together by means of an optically transparent cement to form a mechanically stable, monolithic structure. In another embodiment, the non-linear material has reflective faces formed thereon to define a ring resonator to decouple reflections from the non-linear medium back to the gain medium for improved stability.

Prediction of erodibility in Oxisols using iron oxides, soil color and diffuse reflectance spectroscopy

NASA Astrophysics Data System (ADS)

Arantes Camargo, Livia; Marques, José, Jr.

2015-04-01

The prediction of erodibility using indirect methods such as diffuse reflectance spectroscopy could facilitate the characterization of the spatial variability in large areas and optimize implementation of conservation practices. The aim of this study was to evaluate the prediction of interrill erodibility (Ki) and rill erodibility (Kr) by means of iron oxides content and soil color using multiple linear regression and diffuse reflectance spectroscopy (DRS) using regression analysis by least squares partial (PLSR). The soils were collected from three geomorphic surfaces and analyzed for chemical, physical and mineralogical properties, plus scanned in the spectral range from the visible and infrared. Maps of spatial distribution of Ki and Kr were built with the values calculated by the calibrated models that obtained the best accuracy using geostatistics. Interrill-rill erodibility presented negative correlation with iron extracted by dithionite-citrate-bicarbonate, hematite, and chroma, confirming the influence of iron oxides in soil structural stability. Hematite and hue were the attributes that most contributed in calibration models by multiple linear regression for the prediction of Ki (R2 = 0.55) and Kr (R2 = 0.53). The diffuse reflectance spectroscopy via PLSR allowed to predict Interrill-rill erodibility with high accuracy (R2adj = 0.76, 0.81 respectively and RPD> 2.0) in the range of the visible spectrum (380-800 nm) and the characterization of the spatial variability of these attributes by geostatistics.

Precipitation-Induced Changes in Microstrain and Its Relation with Hardness and Tempering Parameter in 17-4 PH Stainless Steel

NASA Astrophysics Data System (ADS)

Mahadevan, S.; Manojkumar, R.; Jayakumar, T.; Das, C. R.; Rao, B. P. C.

2016-06-01

17-4 PH (precipitation hardening) stainless steel is a soft martensitic stainless steel strengthened by aging at appropriate temperature for sufficient duration. Precipitation of copper particles in the martensitic matrix during aging causes coherency strains which improves the mechanical properties, namely hardness and strength of the matrix. The contributions to X-ray diffraction (XRD) profile broadening due to coherency strains caused by precipitation and crystallite size changes due to aging are separated and quantified using the modified Williamson-Hall approach. The estimated normalized mean square strain and crystallite size are used to explain the observed changes in hardness. Microstructural changes observed in secondary electron images are in qualitative agreement with crystallite size changes estimated from XRD profile analysis. The precipitation kinetics in the age-hardening regime and overaged regime are studied from hardness changes and they follow the Avrami kinetics and Wilson's model, respectively. In overaged condition, the hardness changes are linearly correlated to the tempering parameter (also known as Larson-Miller parameter). Similar linear variation is observed between the normalized mean square strain (determined from XRD line profile analysis) and the tempering parameter, in the incoherent regime which is beyond peak microstrain conditions.

Thermodynamic stability of nanosized multicomponent bubbles/droplets: the square gradient theory and the capillary approach.

PubMed

Wilhelmsen, Øivind; Bedeaux, Dick; Kjelstrup, Signe; Reguera, David

2014-01-14

Formation of nanosized droplets/bubbles from a metastable bulk phase is connected to many unresolved scientific questions. We analyze the properties and stability of multicomponent droplets and bubbles in the canonical ensemble, and compare with single-component systems. The bubbles/droplets are described on the mesoscopic level by square gradient theory. Furthermore, we compare the results to a capillary model which gives a macroscopic description. Remarkably, the solutions of the square gradient model, representing bubbles and droplets, are accurately reproduced by the capillary model except in the vicinity of the spinodals. The solutions of the square gradient model form closed loops, which shows the inherent symmetry and connected nature of bubbles and droplets. A thermodynamic stability analysis is carried out, where the second variation of the square gradient description is compared to the eigenvalues of the Hessian matrix in the capillary description. The analysis shows that it is impossible to stabilize arbitrarily small bubbles or droplets in closed systems and gives insight into metastable regions close to the minimum bubble/droplet radii. Despite the large difference in complexity, the square gradient and the capillary model predict the same finite threshold sizes and very similar stability limits for bubbles and droplets, both for single-component and two-component systems.

Thermodynamic stability of nanosized multicomponent bubbles/droplets: The square gradient theory and the capillary approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilhelmsen, Øivind, E-mail: oivind.wilhelmsen@ntnu.no; Bedeaux, Dick; Kjelstrup, Signe

Formation of nanosized droplets/bubbles from a metastable bulk phase is connected to many unresolved scientific questions. We analyze the properties and stability of multicomponent droplets and bubbles in the canonical ensemble, and compare with single-component systems. The bubbles/droplets are described on the mesoscopic level by square gradient theory. Furthermore, we compare the results to a capillary model which gives a macroscopic description. Remarkably, the solutions of the square gradient model, representing bubbles and droplets, are accurately reproduced by the capillary model except in the vicinity of the spinodals. The solutions of the square gradient model form closed loops, which showsmore » the inherent symmetry and connected nature of bubbles and droplets. A thermodynamic stability analysis is carried out, where the second variation of the square gradient description is compared to the eigenvalues of the Hessian matrix in the capillary description. The analysis shows that it is impossible to stabilize arbitrarily small bubbles or droplets in closed systems and gives insight into metastable regions close to the minimum bubble/droplet radii. Despite the large difference in complexity, the square gradient and the capillary model predict the same finite threshold sizes and very similar stability limits for bubbles and droplets, both for single-component and two-component systems.« less

Daily Emotional Stress Reactivity in Emerging Adulthood: Temporal Stability and its Predictors

PubMed Central

Howland, Maryhope; Armeli, Stephen; Feinn, Richard; Tennen, Howard

2017-01-01

Background & Objectives Emotional reactivity to stress is associated with both mental and physical health and has been assumed to be a stable feature of the person. However recent evidence suggests that the within-person association between stress and negative affect (e.g. affective stress-reactivity) may increase over time and in times of high stress, at least in older adult populations. The objective of the current study was to examine the across-time stability of stress-reactivity in a younger sample—emerging adulthood—and examine neuroticism, overall stress, social support and life events as potential moderators of stability. Design & Methods Undergraduate students (N = 540, mean age = 18.76 years) participated in a measurement burst design, completing a 30-day daily diary annually for four years. Moderators were assessed once at every burst, while negative affect and stress were assessed daily via a secure website. Results & Conclusions Findings suggest a relatively high degree of rank-order and mean-level stability in stress-reactivity across the four years, and within-person changes in neuroticism and overall stress predicted concurrent shifts in stress-reactivity. Unlike older samples, there was no evidence of an overall linear change in stability over time, though there was significant variability in linear change trajectories. PMID:27635675

Adaptive Inverse Control for Rotorcraft Vibration Reduction

NASA Technical Reports Server (NTRS)

Jacklin, Stephen A.

1985-01-01

This thesis extends the Least Mean Square (LMS) algorithm to solve the mult!ple-input, multiple-output problem of alleviating N/Rev (revolutions per minute by number of blades) helicopter fuselage vibration by means of adaptive inverse control. A frequency domain locally linear model is used to represent the transfer matrix relating the higher harmonic pitch control inputs to the harmonic vibration outputs to be controlled. By using the inverse matrix as the controller gain matrix, an adaptive inverse regulator is formed to alleviate the N/Rev vibration. The stability and rate of convergence properties of the extended LMS algorithm are discussed. It is shown that the stability ranges for the elements of the stability gain matrix are directly related to the eigenvalues of the vibration signal information matrix for the learning phase, but not for the control phase. The overall conclusion is that the LMS adaptive inverse control method can form a robust vibration control system, but will require some tuning of the input sensor gains, the stability gain matrix, and the amount of control relaxation to be used. The learning curve of the controller during the learning phase is shown to be quantitatively close to that predicted by averaging the learning curves of the normal modes. For higher order transfer matrices, a rough estimate of the inverse is needed to start the algorithm efficiently. The simulation results indicate that the factor which most influences LMS adaptive inverse control is the product of the control relaxation and the the stability gain matrix. A small stability gain matrix makes the controller less sensitive to relaxation selection, and permits faster and more stable vibration reduction, than by choosing the stability gain matrix large and the control relaxation term small. It is shown that the best selections of the stability gain matrix elements and the amount of control relaxation is basically a compromise between slow, stable convergence and fast convergence with increased possibility of unstable identification. In the simulation studies, the LMS adaptive inverse control algorithm is shown to be capable of adapting the inverse (controller) matrix to track changes in the flight conditions. The algorithm converges quickly for moderate disturbances, while taking longer for larger disturbances. Perfect knowledge of the inverse matrix is not required for good control of the N/Rev vibration. However it is shown that measurement noise will prevent the LMS adaptive inverse control technique from controlling the vibration, unless the signal averaging method presented is incorporated into the algorithm.

Oceanographic and meteorological research based on the data products of SEASAT

NASA Technical Reports Server (NTRS)

Pierson, W. J., Jr.

1985-01-01

Reservations were expressed concerning the sum of squares wind recovery algorithm and the power law model function. The SAS sum of squares (SOS) method for recovering winds from backscatter data leads to inconsistent results when V pol and H pol winds are compared. A model function that does not use a power law and that accounts for sea surface temperature is needed and is under study both theoretically and by means of the SASS mode 4 data. Aspects of the determination of winds by means of scatterometry and of the utilization of vector wind data for meteorological forecasts are elaborated. The operational aspect of an intermittent assimilation scheme currently utilized for the specification of the initial value field is considered with focus on quantifying the absolute 12-hour linear displacement error of the movement of low centers.

Theoretical Study of Free Energy in Docking Stability of Azurin(II)-Cytochrome c551(II) Complex System

NASA Astrophysics Data System (ADS)

Yamamoto, Tetsunori; Nishikawa, Keigo; Sugiyama, Ayumu; Purqon, Acep; Mizukami, Taku; Shimahara, Hideto; Nagao, Hidemi; Nishikawa, Kiyoshi

2008-02-01

The docking structure of the Azurin-Cytochrome C551 is presented. We investigate a complex system of Azurin(II)-Cytochrome C551(II) by using molecular dynamics simulation. We estimate some physical properties, such as root-mean-square deviation (RMSD), binding energy between Azurin and Cytochrome C551, distance between Azurin(II) and Cytochrome C551(II) through center of mass and each active site. We also discuss docking stability in relation to the configuration by free energy between Azurin(II)-Cytochrome C551(II) and Azurin(I)-Cytochrome C551(III).

On the Quasimonotonicity of a Square Linear Operator with Respect to a Nonnegative Cone

DTIC Science & Technology

1998-06-01

follows from the result from Perron (1907) and Frobenius (1912) on the theory of nonnegative matrices, which states that a nonnegative matrix has a...Dissertation 4. TITLE AND SUBTITLE ON THE QUASIMONOTONICITY OF A SQUARE LINEAR OPERATOR WITH RESPECT TO A NONNEGATIVE CONE 6. AUTHOR(S) Beaver, Philip...ABSTRACT (maximum 200 words) The question of when a square, linear operator is quasimonotone nondecreasing with respect to a nonnegative cone was posed for

Experimental and analytical determination of stability parameters for a balloon tethered in a wind

NASA Technical Reports Server (NTRS)

Redd, L. T.; Bennett, R. M.; Bland, S. R.

1973-01-01

Experimental and analytical techniques for determining stability parameters for a balloon tethered in a steady wind are described. These techniques are applied to a particular 7.64-meter-long balloon, and the results are presented. The stability parameters of interest appear as coefficients in linearized stability equations and are derived from the various forces and moments acting on the balloon. In several cases the results from the experimental and analytical techniques are compared and suggestions are given as to which techniques are the most practical means of determining values for the stability parameters.

Application of acoustic velocity meters for gaging discharge of three low-velocity tidal streams in the St. Johns River basin, northeast Florida

USGS Publications Warehouse

Sloat, J.V.; Gain, W.S.

1995-01-01

Index-velocity data collected with acoustic velocity meters, stage data, and cross-sectional area data were used to calculate discharge at three low-velocity, tidal streamflow stations in north-east Florida. Discharge at three streamflow stations was computed as the product of the channel cross-sectional area and the mean velocity as determined from an index velocity measured in the stream using an acoustic velocity meter. The tidal streamlflow stations used in the study were: Six Mile Creek near Picolata, Fla.; Dunns Creek near Satsuma, Fla.; and the St. Johns River at Buffalo Bluff. Cross-sectional areas at the measurement sections ranged from about 3,000 square feet at Six Mile Creek to about 18,500 square feet at St. Johns River at Buffalo Bluff. Physical characteristics for all three streams were similar except for drainage area. The topography primarily is low-relief, swampy terrain; stream velocities ranged from about -2 to 2 feet per second; and the average change in stage was about 1 foot. Instantaneous discharge was measured using a portable acoustic current meter at each of the three streams to develop a relation between the mean velocity in the stream and the index velocity measured by the acoustic velocity meter. Using least-squares linear regression, a simple linear relation between mean velocity and index velocity was determined. Index velocity was the only significant linear predictor of mean velocity for Six Mile Creek and St. Johns River at Buffalo Bluff. For Dunns Creek, both index velocity and stage were used to develop a multiple-linear predictor of mean velocity. Stage-area curves for each stream were developed from bathymetric data. Instantaneous discharge was computed by multiplying results of relations developed for cross-sectional area and mean velocity. Principal sources of error in the estimated discharge are identified as: (1) instrument errors associated with measurement of stage and index velocity, (2) errors in the representation of mean daily stage and index velocity due to natural variability over time and space, and (3) errors in cross-sectional area and mean-velocity ratings based on stage and index velocity. Standard errors for instantaneous discharge for the median cross-sectional area for Six Mile Creek, Dunns Creek, and St. Johns River at Buffalo Bluff were 94,360, and 1,980 cubic feet per second, respectively. Standard errors for mean daily discharge for the median cross-sectional area for Six Mile Creek, Dunns Creek, and St. Johns River at Buffalo Bluff were 25, 65, and 455 cubic feet per second, respectively. Mean daily discharge at the three sites ranged from about -500 to 1,500 cubic feet per second at Six Mile Creek and Dunns Creek and from about -500 to 15,000 cubic feet per second on the St. Johns River at Buffalo Bluff. For periods of high discharge, the AVM index-velocity method tended to produce estimates accurate with 2 to 6 percent. For periods of moderate discharge, errors in discharge may increase to more than 50 percent. At low flows, errors as a percentage of discharge increase toward infinity.

Forecasting transitions in systems with high-dimensional stochastic complex dynamics: a linear stability analysis of the tangled nature model.

PubMed

Cairoli, Andrea; Piovani, Duccio; Jensen, Henrik Jeldtoft

2014-12-31

We propose a new procedure to monitor and forecast the onset of transitions in high-dimensional complex systems. We describe our procedure by an application to the tangled nature model of evolutionary ecology. The quasistable configurations of the full stochastic dynamics are taken as input for a stability analysis by means of the deterministic mean-field equations. Numerical analysis of the high-dimensional stability matrix allows us to identify unstable directions associated with eigenvalues with a positive real part. The overlap of the instantaneous configuration vector of the full stochastic system with the eigenvectors of the unstable directions of the deterministic mean-field approximation is found to be a good early warning of the transitions occurring intermittently.

Stochastic growth logistic model with aftereffect for batch fermentation process

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rosli, Norhayati; Ayoubi, Tawfiqullah; Bahar, Arifah

2014-06-19

In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.

Channel estimation based on quantized MMP for FDD massive MIMO downlink

NASA Astrophysics Data System (ADS)

Guo, Yao-ting; Wang, Bing-he; Qu, Yi; Cai, Hua-jie

2016-10-01

In this paper, we consider channel estimation for Massive MIMO systems operating in frequency division duplexing mode. By exploiting the sparsity of propagation paths in Massive MIMO channel, we develop a compressed sensing(CS) based channel estimator which can reduce the pilot overhead. As compared with the conventional least squares (LS) and linear minimum mean square error(LMMSE) estimation, the proposed algorithm is based on the quantized multipath matching pursuit - MMP - reduced the pilot overhead and performs better than other CS algorithms. The simulation results demonstrate the advantage of the proposed algorithm over various existing methods including the LS, LMMSE, CoSaMP and conventional MMP estimators.

Stochastic growth logistic model with aftereffect for batch fermentation process

NASA Astrophysics Data System (ADS)

Rosli, Norhayati; Ayoubi, Tawfiqullah; Bahar, Arifah; Rahman, Haliza Abdul; Salleh, Madihah Md

2014-06-01

In this paper, the stochastic growth logistic model with aftereffect for the cell growth of C. acetobutylicum P262 and Luedeking-Piret equations for solvent production in batch fermentation system is introduced. The parameters values of the mathematical models are estimated via Levenberg-Marquardt optimization method of non-linear least squares. We apply Milstein scheme for solving the stochastic models numerically. The effciency of mathematical models is measured by comparing the simulated result and the experimental data of the microbial growth and solvent production in batch system. Low values of Root Mean-Square Error (RMSE) of stochastic models with aftereffect indicate good fits.

Improvement of near infrared spectroscopic (NIRS) analysis of caffeine in roasted Arabica coffee by variable selection method of stability competitive adaptive reweighted sampling (SCARS).

PubMed

Zhang, Xuan; Li, Wei; Yin, Bin; Chen, Weizhong; Kelly, Declan P; Wang, Xiaoxin; Zheng, Kaiyi; Du, Yiping

2013-10-01

Coffee is the most heavily consumed beverage in the world after water, for which quality is a key consideration in commercial trade. Therefore, caffeine content which has a significant effect on the final quality of the coffee products requires to be determined fast and reliably by new analytical techniques. The main purpose of this work was to establish a powerful and practical analytical method based on near infrared spectroscopy (NIRS) and chemometrics for quantitative determination of caffeine content in roasted Arabica coffees. Ground coffee samples within a wide range of roasted levels were analyzed by NIR, meanwhile, in which the caffeine contents were quantitative determined by the most commonly used HPLC-UV method as the reference values. Then calibration models based on chemometric analyses of the NIR spectral data and reference concentrations of coffee samples were developed. Partial least squares (PLS) regression was used to construct the models. Furthermore, diverse spectra pretreatment and variable selection techniques were applied in order to obtain robust and reliable reduced-spectrum regression models. Comparing the respective quality of the different models constructed, the application of second derivative pretreatment and stability competitive adaptive reweighted sampling (SCARS) variable selection provided a notably improved regression model, with root mean square error of cross validation (RMSECV) of 0.375 mg/g and correlation coefficient (R) of 0.918 at PLS factor of 7. An independent test set was used to assess the model, with the root mean square error of prediction (RMSEP) of 0.378 mg/g, mean relative error of 1.976% and mean relative standard deviation (RSD) of 1.707%. Thus, the results provided by the high-quality calibration model revealed the feasibility of NIR spectroscopy for at-line application to predict the caffeine content of unknown roasted coffee samples, thanks to the short analysis time of a few seconds and non-destructive advantages of NIRS. Copyright © 2013 Elsevier B.V. All rights reserved.

Improvement of near infrared spectroscopic (NIRS) analysis of caffeine in roasted Arabica coffee by variable selection method of stability competitive adaptive reweighted sampling (SCARS)

NASA Astrophysics Data System (ADS)

Zhang, Xuan; Li, Wei; Yin, Bin; Chen, Weizhong; Kelly, Declan P.; Wang, Xiaoxin; Zheng, Kaiyi; Du, Yiping

2013-10-01

Coffee is the most heavily consumed beverage in the world after water, for which quality is a key consideration in commercial trade. Therefore, caffeine content which has a significant effect on the final quality of the coffee products requires to be determined fast and reliably by new analytical techniques. The main purpose of this work was to establish a powerful and practical analytical method based on near infrared spectroscopy (NIRS) and chemometrics for quantitative determination of caffeine content in roasted Arabica coffees. Ground coffee samples within a wide range of roasted levels were analyzed by NIR, meanwhile, in which the caffeine contents were quantitative determined by the most commonly used HPLC-UV method as the reference values. Then calibration models based on chemometric analyses of the NIR spectral data and reference concentrations of coffee samples were developed. Partial least squares (PLS) regression was used to construct the models. Furthermore, diverse spectra pretreatment and variable selection techniques were applied in order to obtain robust and reliable reduced-spectrum regression models. Comparing the respective quality of the different models constructed, the application of second derivative pretreatment and stability competitive adaptive reweighted sampling (SCARS) variable selection provided a notably improved regression model, with root mean square error of cross validation (RMSECV) of 0.375 mg/g and correlation coefficient (R) of 0.918 at PLS factor of 7. An independent test set was used to assess the model, with the root mean square error of prediction (RMSEP) of 0.378 mg/g, mean relative error of 1.976% and mean relative standard deviation (RSD) of 1.707%. Thus, the results provided by the high-quality calibration model revealed the feasibility of NIR spectroscopy for at-line application to predict the caffeine content of unknown roasted coffee samples, thanks to the short analysis time of a few seconds and non-destructive advantages of NIRS.

Implementing Linear Algebra Related Algorithms on the TI-92+ Calculator.

ERIC Educational Resources Information Center

Alexopoulos, John; Abraham, Paul

2001-01-01

Demonstrates a less utilized feature of the TI-92+: its natural and powerful programming language. Shows how to implement several linear algebra related algorithms including the Gram-Schmidt process, Least Squares Approximations, Wronskians, Cholesky Decompositions, and Generalized Linear Least Square Approximations with QR Decompositions.…

On a program manifold's stability of one contour automatic control systems

NASA Astrophysics Data System (ADS)

Zumatov, S. S.

2017-12-01

Methodology of analysis of stability is expounded to the one contour systems automatic control feedback in the presence of non-linearities. The methodology is based on the use of the simplest mathematical models of the nonlinear controllable systems. Stability of program manifolds of one contour automatic control systems is investigated. The sufficient conditions of program manifold's absolute stability of one contour automatic control systems are obtained. The Hurwitz's angle of absolute stability was determined. The sufficient conditions of program manifold's absolute stability of control systems by the course of plane in the mode of autopilot are obtained by means Lyapunov's second method.

Transfer-function-parameter estimation from frequency response data: A FORTRAN program

NASA Technical Reports Server (NTRS)

Seidel, R. C.

1975-01-01

A FORTRAN computer program designed to fit a linear transfer function model to given frequency response magnitude and phase data is presented. A conjugate gradient search is used that minimizes the integral of the absolute value of the error squared between the model and the data. The search is constrained to insure model stability. A scaling of the model parameters by their own magnitude aids search convergence. Efficient computer algorithms result in a small and fast program suitable for a minicomputer. A sample problem with different model structures and parameter estimates is reported.

Determination of Nonlinear Stiffness Coefficients for Finite Element Models with Application to the Random Vibration Problem

NASA Technical Reports Server (NTRS)

Muravyov, Alexander A.

1999-01-01

In this paper, a method for obtaining nonlinear stiffness coefficients in modal coordinates for geometrically nonlinear finite-element models is developed. The method requires application of a finite-element program with a geometrically non- linear static capability. The MSC/NASTRAN code is employed for this purpose. The equations of motion of a MDOF system are formulated in modal coordinates. A set of linear eigenvectors is used to approximate the solution of the nonlinear problem. The random vibration problem of the MDOF nonlinear system is then considered. The solutions obtained by application of two different versions of a stochastic linearization technique are compared with linear and exact (analytical) solutions in terms of root-mean-square (RMS) displacements and strains for a beam structure.

Optical systolic solutions of linear algebraic equations

NASA Technical Reports Server (NTRS)

Neuman, C. P.; Casasent, D.

1984-01-01

The philosophy and data encoding possible in systolic array optical processor (SAOP) were reviewed. The multitude of linear algebraic operations achievable on this architecture is examined. These operations include such linear algebraic algorithms as: matrix-decomposition, direct and indirect solutions, implicit and explicit methods for partial differential equations, eigenvalue and eigenvector calculations, and singular value decomposition. This architecture can be utilized to realize general techniques for solving matrix linear and nonlinear algebraic equations, least mean square error solutions, FIR filters, and nested-loop algorithms for control engineering applications. The data flow and pipelining of operations, design of parallel algorithms and flexible architectures, application of these architectures to computationally intensive physical problems, error source modeling of optical processors, and matching of the computational needs of practical engineering problems to the capabilities of optical processors are emphasized.

Development Towards a Space Qualified Laser Stabilization System in Support of Space-Based Optical Interferometers

NASA Technical Reports Server (NTRS)

Seidel, David J.; Dubovitsky, Serge

2000-01-01

We report on the development, functional performance and space-qualification status of a laser stabilization system supporting a space-based metrology source used to measure changes in optical path lengths in space-based stellar interferometers. The Space Interferometry Mission (SIM) and Deep Space 3 (DS-3) are two missions currently funded by the National Aeronautics and Space Administration (NASA) that are space-based optical interferometers. In order to properly recombine the starlight received at each telescope of the interferometer it is necessary to perform high resolution laser metrology to stabilize the interferometer. A potentially significant error source in performing high resolution metrology length measurements is the potential for fluctuations in the laser gauge itself. If the laser frequency or wavelength is changing over time it will be misinterpreted as a length change in one of the legs of the interferometer. An analysis of the frequency stability requirement for SIM resulted in a fractional frequency stability requirement of square root (S(sub y)(f)) = <2 x 10(exp -12)/square root(Hz) at Fourier frequencies between 10 Hz and 1000 Hz. The DS-3 mission stability requirement is further increased to square root (S(sub y)(f)) = <5 x 10(exp -14)/Square root(Hz) at Fourier frequencies between 0.2 Hz and 10 kHz with a goal of extending the low frequency range to 0.05 Hz. The free running performance of the Lightwave Electronics NPRO lasers, which are the baseline laser for both SIM and DS-3 vary in stability and we have measured them to perform as follows (9 x l0(exp -11)/ f(Hz))(Hz)/square root(Hz)) = <( square root (S(sub y)(f)) = <(1.3 x l0(exp -8)/ f(Hz))/Square root(Hz). In order to improve the frequency stability of the laser we stabilize the laser to a high finesse optical cavity by locking the optical frequency of the laser to one of the transmission modes of the cavity. At JPL we have built a prototype space-qualifiable system meeting the stability requirements of SIM, which has been delivered to one of the SIM testbeds. We have also started on the development of a system to meet the stability needs of DS-3.

Use of satellite data and modeling to assess the influence of stratospheric processes on the troposphere

NASA Astrophysics Data System (ADS)

Nathan, Terrence

1991-09-01

Over the past forty years, numerous linear stability studies have been performed in order to explain the origin and structure of observed waves in the atmosphere. Of these studies, only a small fraction have considered the stability of time-dependent, zonally varying flow or the influence of radiative-photochemical feedbacks on the stability of zonally uniform flow. The stability of such flows is described, and these flows may yield important information concerning the origin, structure, and transient time scales of free waves in the atmosphere. During the period 1990 to 1991, a beta-plane model that couples radiative transfer, ozone advection, and ozone photochemistry with the quasigeostrophic dynamical circulation was developed in order to study the diabatic effects of Newtonian cooling and ozone-dynamics interaction on the linear stability of free planetary waves in the atmosphere. The stability of a basic state consisting of a westward-moving wave and a zonal mean jet was examined using a linearized, nondivergent barotropic model on sphere. The sensitivity of the stability of the flow to the strength and structure of the zonal jet was emphasized. The current research is focused on the following problems: (1) examination of the finite amplitude interactions among radiation, ozone, and dynamics; and (2) examination of the role of seasonal forcing in short-term climate variability. The plans for next year are presented.

Mixed linear-non-linear inversion of crustal deformation data: Bayesian inference of model, weighting and regularization parameters

NASA Astrophysics Data System (ADS)

Fukuda, Jun'ichi; Johnson, Kaj M.

2010-06-01

We present a unified theoretical framework and solution method for probabilistic, Bayesian inversions of crustal deformation data. The inversions involve multiple data sets with unknown relative weights, model parameters that are related linearly or non-linearly through theoretic models to observations, prior information on model parameters and regularization priors to stabilize underdetermined problems. To efficiently handle non-linear inversions in which some of the model parameters are linearly related to the observations, this method combines both analytical least-squares solutions and a Monte Carlo sampling technique. In this method, model parameters that are linearly and non-linearly related to observations, relative weights of multiple data sets and relative weights of prior information and regularization priors are determined in a unified Bayesian framework. In this paper, we define the mixed linear-non-linear inverse problem, outline the theoretical basis for the method, provide a step-by-step algorithm for the inversion, validate the inversion method using synthetic data and apply the method to two real data sets. We apply the method to inversions of multiple geodetic data sets with unknown relative data weights for interseismic fault slip and locking depth. We also apply the method to the problem of estimating the spatial distribution of coseismic slip on faults with unknown fault geometry, relative data weights and smoothing regularization weight.

Nonlinear analysis of an improved continuum model considering headway change with memory

NASA Astrophysics Data System (ADS)

Cheng, Rongjun; Wang, Jufeng; Ge, Hongxia; Li, Zhipeng

2018-01-01

Considering the effect of headway changes with memory, an improved continuum model of traffic flow is proposed in this paper. By means of linear stability theory, the new model’s linear stability with the effect of headway changes with memory is obtained. Through nonlinear analysis, the KdV-Burgers equation is derived to describe the propagating behavior of traffic density wave near the neutral stability line. Numerical simulation is carried out to study the improved traffic flow model, which explores how the headway changes with memory affected each car’s velocity, density and energy consumption. Numerical results show that when considering the effects of headway changes with memory, the traffic jams can be suppressed efficiently. Furthermore, research results demonstrate that the effect of headway changes with memory can avoid the disadvantage of historical information, which will improve the stability of traffic flow and minimize car energy consumption.

Linear and nonlinear methods in modeling the aqueous solubility of organic compounds.

PubMed

Catana, Cornel; Gao, Hua; Orrenius, Christian; Stouten, Pieter F W

2005-01-01

Solubility data for 930 diverse compounds have been analyzed using linear Partial Least Square (PLS) and nonlinear PLS methods, Continuum Regression (CR), and Neural Networks (NN). 1D and 2D descriptors from MOE package in combination with E-state or ISIS keys have been used. The best model was obtained using linear PLS for a combination between 22 MOE descriptors and 65 ISIS keys. It has a correlation coefficient (r2) of 0.935 and a root-mean-square error (RMSE) of 0.468 log molar solubility (log S(w)). The model validated on a test set of 177 compounds not included in the training set has r2 0.911 and RMSE 0.475 log S(w). The descriptors were ranked according to their importance, and at the top of the list have been found the 22 MOE descriptors. The CR model produced results as good as PLS, and because of the way in which cross-validation has been done it is expected to be a valuable tool in prediction besides PLS model. The statistics obtained using nonlinear methods did not surpass those got with linear ones. The good statistic obtained for linear PLS and CR recommends these models to be used in prediction when it is difficult or impossible to make experimental measurements, for virtual screening, combinatorial library design, and efficient leads optimization.

Repeatability of paired counts.

PubMed

Alexander, Neal; Bethony, Jeff; Corrêa-Oliveira, Rodrigo; Rodrigues, Laura C; Hotez, Peter; Brooker, Simon

2007-08-30

The Bland and Altman technique is widely used to assess the variation between replicates of a method of clinical measurement. It yields the repeatability, i.e. the value within which 95 per cent of repeat measurements lie. The valid use of the technique requires that the variance is constant over the data range. This is not usually the case for counts of items such as CD4 cells or parasites, nor is the log transformation applicable to zero counts. We investigate the properties of generalized differences based on Box-Cox transformations. For an example, in a data set of hookworm eggs counted by the Kato-Katz method, the square root transformation is found to stabilize the variance. We show how to back-transform the repeatability on the square root scale to the repeatability of the counts themselves, as an increasing function of the square mean root egg count, i.e. the square of the average of square roots. As well as being more easily interpretable, the back-transformed results highlight the dependence of the repeatability on the sample volume used.

Vehicle States Observer Using Adaptive Tire-Road Friction Estimator

NASA Astrophysics Data System (ADS)

Kwak, Byunghak; Park, Youngjin

Vehicle stability control system is a new idea which can enhance the vehicle stability and handling in the emergency situation. This system requires the information of the yaw rate, sideslip angle and road friction in order to control the traction and braking forces at the individual wheels. This paper proposes an observer for the vehicle stability control system. This observer consisted of the state observer for vehicle motion estimation and the road condition estimator for the identification of the coefficient of the road friction. The state observer uses 2 degrees-of-freedom bicycle model and estimates the system variables based on the Kalman filter. The road condition estimator uses the same vehicle model and identifies the coefficient of the tire-road friction based on the recursive least square method. Both estimators make use of each other information. We show the effectiveness and feasibility of the proposed scheme under various road conditions through computer simulations of a fifteen degree-of-freedom non-linear vehicle model.

Modelling hourly dissolved oxygen concentration (DO) using dynamic evolving neural-fuzzy inference system (DENFIS)-based approach: case study of Klamath River at Miller Island Boat Ramp, OR, USA.

PubMed

Heddam, Salim

2014-01-01

In this study, we present application of an artificial intelligence (AI) technique model called dynamic evolving neural-fuzzy inference system (DENFIS) based on an evolving clustering method (ECM), for modelling dissolved oxygen concentration in a river. To demonstrate the forecasting capability of DENFIS, a one year period from 1 January 2009 to 30 December 2009, of hourly experimental water quality data collected by the United States Geological Survey (USGS Station No: 420853121505500) station at Klamath River at Miller Island Boat Ramp, OR, USA, were used for model development. Two DENFIS-based models are presented and compared. The two DENFIS systems are: (1) offline-based system named DENFIS-OF, and (2) online-based system, named DENFIS-ON. The input variables used for the two models are water pH, temperature, specific conductance, and sensor depth. The performances of the models are evaluated using root mean square errors (RMSE), mean absolute error (MAE), Willmott index of agreement (d) and correlation coefficient (CC) statistics. The lowest root mean square error and highest correlation coefficient values were obtained with the DENFIS-ON method. The results obtained with DENFIS models are compared with linear (multiple linear regression, MLR) and nonlinear (multi-layer perceptron neural networks, MLPNN) methods. This study demonstrates that DENFIS-ON investigated herein outperforms all the proposed techniques for DO modelling.

Theoretical transient analysis of a hearing aid feedback canceller with a saturation type nonlinearity in the direct path.

PubMed

Costa, Márcio Holsbach

2017-12-01

Feedback cancellation in a hearing aid is essential for achieving high maximum stable gain to compensate for the losses in severe to profound hearing impaired people. The performance of adaptive feedback cancellers has been studied by assuming that the feedback path can be modeled as a linear system. However, limited dynamic range, low-cost loudspeakers, and nonlinear power amplifiers may distort the hearing aid output signal. In this way, linear-based predictions of the canceller performance may lead to significant deviations from its actual behavior. This work presents a theoretical performance analysis of a Least Mean Square based shadow filter that is applied to set up the coefficients of a feedback canceller, which is subject to a static saturation type nonlinearity at the output of the direct path. Deterministic recursive equations are derived to predict the mean square feedback error and the mean coefficient vector evolution between updates of the feedback canceller. These models are defined as functions of the canceller parameters and input signal statistics. Comparisons with Monte Carlo simulations show the provided models are highly accurate under the considered assumptions. The developed models allow inferences about the potential impact of an overdriven loudspeaker over the transient performance of the direct method feedback canceller, serving as insightful tools for understanding the involved mechanisms. Copyright © 2017 Elsevier Ltd. All rights reserved.

Vertically stabilized elongated cross-section tokamak

DOEpatents

Sheffield, George V.

1977-01-01

This invention provides a vertically stabilized, non-circular (minor) cross-section, toroidal plasma column characterized by an external separatrix. To this end, a specific poloidal coil means is added outside a toroidal plasma column containing an endless plasma current in a tokamak to produce a rectangular cross-section plasma column along the equilibrium axis of the plasma column. By elongating the spacing between the poloidal coil means the plasma cross-section is vertically elongated, while maintaining vertical stability, efficiently to increase the poloidal flux in linear proportion to the plasma cross-section height to achieve a much greater plasma volume than could be achieved with the heretofore known round cross-section plasma columns. Also, vertical stability is enhanced over an elliptical cross-section plasma column, and poloidal magnetic divertors are achieved.

Robust Control for The G-Limit Microgravity Vibration Isolation System

NASA Technical Reports Server (NTRS)

Whorton, Mark S.

2004-01-01

Many microgravity science experiments need an active isolation system to provide a sufficiently quiescent acceleration environment. The g-LIMIT vibration isolation system will provide isolation for Microgravity Science Glovebox experiments in the International Space Station. While standard control system technologies have been demonstrated for these applications, modern control methods have the potential for meeting performance requirements while providing robust stability in the presence of parametric uncertainties that are characteristic of microgravity vibration isolation systems. While H2 and H infinity methods are well established, neither provides the levels of attenuation performance and robust stability in a compensator with low order. Mixed H2/mu controllers provide a means for maximizing robust stability for a given level of mean-square nominal performance while directly optimizing for controller order constraints. This paper demonstrates the benefit of mixed norm design from the perspective of robustness to parametric uncertainties and controller order for microgravity vibration isolation. A nominal performance metric analogous to the mu measure for robust stability assessment is also introduced in order to define an acceptable trade space from which different control methodologies can be compared.

Modeling error analysis of stationary linear discrete-time filters

NASA Technical Reports Server (NTRS)

Patel, R.; Toda, M.

1977-01-01

The performance of Kalman-type, linear, discrete-time filters in the presence of modeling errors is considered. The discussion is limited to stationary performance, and bounds are obtained for the performance index, the mean-squared error of estimates for suboptimal and optimal (Kalman) filters. The computation of these bounds requires information on only the model matrices and the range of errors for these matrices. Consequently, a design can easily compare the performance of a suboptimal filter with that of the optimal filter, when only the range of errors in the elements of the model matrices is available.

Statistical properties of the anomalous scaling exponent estimator based on time-averaged mean-square displacement

NASA Astrophysics Data System (ADS)

Sikora, Grzegorz; Teuerle, Marek; Wyłomańska, Agnieszka; Grebenkov, Denis

2017-08-01

The most common way of estimating the anomalous scaling exponent from single-particle trajectories consists of a linear fit of the dependence of the time-averaged mean-square displacement on the lag time at the log-log scale. We investigate the statistical properties of this estimator in the case of fractional Brownian motion (FBM). We determine the mean value, the variance, and the distribution of the estimator. Our theoretical results are confirmed by Monte Carlo simulations. In the limit of long trajectories, the estimator is shown to be asymptotically unbiased, consistent, and with vanishing variance. These properties ensure an accurate estimation of the scaling exponent even from a single (long enough) trajectory. As a consequence, we prove that the usual way to estimate the diffusion exponent of FBM is correct from the statistical point of view. Moreover, the knowledge of the estimator distribution is the first step toward new statistical tests of FBM and toward a more reliable interpretation of the experimental histograms of scaling exponents in microbiology.

Impact of defects on percolation in random sequential adsorption of linear k-mers on square lattices.

PubMed

Tarasevich, Yuri Yu; Laptev, Valeri V; Vygornitskii, Nikolai V; Lebovka, Nikolai I

2015-01-01

The effect of defects on the percolation of linear k-mers (particles occupying k adjacent sites) on a square lattice is studied by means of Monte Carlo simulation. The k-mers are deposited using a random sequential adsorption mechanism. Two models L(d) and K(d) are analyzed. In the L(d) model it is assumed that the initial square lattice is nonideal and some fraction of sites d is occupied by nonconducting point defects (impurities). In the K(d) model the initial square lattice is perfect. However, it is assumed that some fraction of the sites in the k-mers d consists of defects, i.e., is nonconducting. The length of the k-mers k varies from 2 to 256. Periodic boundary conditions are applied to the square lattice. The dependences of the percolation threshold concentration of the conducting sites p(c) vs the concentration of defects d are analyzed for different values of k. Above some critical concentration of defects d(m), percolation is blocked in both models, even at the jamming concentration of k-mers. For long k-mers, the values of d(m) are well fitted by the functions d(m)∝k(m)(-α)-k(-α) (α=1.28±0.01 and k(m)=5900±500) and d(m)∝log(10)(k(m)/k) (k(m)=4700±1000) for the L(d) and K(d) models, respectively. Thus, our estimation indicates that the percolation of k-mers on a square lattice is impossible even for a lattice without any defects if k⪆6×10(3).

Coexistence and local μ-stability of multiple equilibrium points for memristive neural networks with nonmonotonic piecewise linear activation functions and unbounded time-varying delays.

PubMed

Nie, Xiaobing; Zheng, Wei Xing; Cao, Jinde

2016-12-01

In this paper, the coexistence and dynamical behaviors of multiple equilibrium points are discussed for a class of memristive neural networks (MNNs) with unbounded time-varying delays and nonmonotonic piecewise linear activation functions. By means of the fixed point theorem, nonsmooth analysis theory and rigorous mathematical analysis, it is proven that under some conditions, such n-neuron MNNs can have 5 n equilibrium points located in ℜ n , and 3 n of them are locally μ-stable. As a direct application, some criteria are also obtained on the multiple exponential stability, multiple power stability, multiple log-stability and multiple log-log-stability. All these results reveal that the addressed neural networks with activation functions introduced in this paper can generate greater storage capacity than the ones with Mexican-hat-type activation function. Numerical simulations are presented to substantiate the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Daily air temperature interpolated at high spatial resolution over a large mountainous region

USGS Publications Warehouse

Dodson, R.; Marks, D.

1997-01-01

Two methods are investigated for interpolating daily minimum and maximum air temperatures (Tmin and Tmax) at a 1 km spatial resolution over a large mountainous region (830 000 km2) in the U.S. Pacific Northwest. The methods were selected because of their ability to (1) account for the effect of elevation on temperature and (2) efficiently handle large volumes of data. The first method, the neutral stability algorithm (NSA), used the hydrostatic and potential temperature equations to convert measured temperatures and elevations to sea-level potential temperatures. The potential temperatures were spatially interpolated using an inverse-squared-distance algorithm and then mapped to the elevation surface of a digital elevation model (DEM). The second method, linear lapse rate adjustment (LLRA), involved the same basic procedure as the NSA, but used a constant linear lapse rate instead of the potential temperature equation. Cross-validation analyses were performed using the NSA and LLRA methods to interpolate Tmin and Tmax each day for the 1990 water year, and the methods were evaluated based on mean annual interpolation error (IE). The NSA method showed considerable bias for sites associated with vertical extrapolation. A correction based on climate station/grid cell elevation differences was developed and found to successfully remove the bias. The LLRA method was tested using 3 lapse rates, none of which produced a serious extrapolation bias. The bias-adjusted NSA and the 3 LLRA methods produced almost identical levels of accuracy (mean absolute errors between 1.2 and 1.3??C), and produced very similar temperature surfaces based on image difference statistics. In terms of accuracy, speed, and ease of implementation, LLRA was chosen as the best of the methods tested.

Laser beam uniformity and stability using homogenizer-based fiber optic launch method: square core fiber delivery

NASA Astrophysics Data System (ADS)

Lizotte, Todd E.

2011-03-01

Over the years, technological achievements within the laser medical diagnostic, treatment, and therapy markets have led to ever increasing requirements for greater control of critical laser beam parameters. Increased laser power/energy stabilization, temporal and spatial beam shaping and flexible laser beam delivery systems with ergonomic focusing or imaging lens systems are sought by leading medical laser system producers. With medical procedures that utilize laser energy, there is a constant emphasis on reducing adverse effects that come about by the laser itself or its optical system, but even when these variables are well controlled the medical professional will still need to deal with the multivariate nature of the human body. Focusing on the variables that can be controlled, such as accurate placement of the laser beam where it will expose a surface being treated as well as laser beam shape and uniformity is critical to minimizing adverse conditions. This paper covers the use of fiber optic beam delivery as a means of defining the beam shape (intensity/power distribution uniformity) at the target plane as well as the use of fiber delivery as a means to allow more flexible articulation of the laser beam over the surface being treated. The paper will present a new concept of using a square core fiber beam delivery design utilizing a unique micro lens array (MLA) launch method that improves the overall stability of the system, by minimizing the impact of the laser instability. The resulting performance of the prototype is presented to demonstrate its stability in comparison to simple lens launch techniques, with an emphasis on homogenization and articulated fiber delivery.

Using High Spatial Resolution Digital Imagery

DTIC Science & Technology

2005-02-01

digital base maps were high resolution U.S. Geological Survey (USGS) Digital Orthophoto Quarter Quadrangles (DOQQ). The Root Mean Square Errors (RMSE...next step was to assign real world coordinates to the linear im- age. The mosaics were geometrically registered to the panchromatic orthophotos ...useable thematic map from high-resolution imagery. A more practical approach may be to divide the Refuge into a set of smaller areas, or tiles

pth moment exponential stability of stochastic memristor-based bidirectional associative memory (BAM) neural networks with time delays.

PubMed

Wang, Fen; Chen, Yuanlong; Liu, Meichun

2018-02-01

Stochastic memristor-based bidirectional associative memory (BAM) neural networks with time delays play an increasingly important role in the design and implementation of neural network systems. Under the framework of Filippov solutions, the issues of the pth moment exponential stability of stochastic memristor-based BAM neural networks are investigated. By using the stochastic stability theory, Itô's differential formula and Young inequality, the criteria are derived. Meanwhile, with Lyapunov approach and Cauchy-Schwarz inequality, we derive some sufficient conditions for the mean square exponential stability of the above systems. The obtained results improve and extend previous works on memristor-based or usual neural networks dynamical systems. Four numerical examples are provided to illustrate the effectiveness of the proposed results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Least median of squares and iteratively re-weighted least squares as robust linear regression methods for fluorimetric determination of α-lipoic acid in capsules in ideal and non-ideal cases of linearity.

PubMed

Korany, Mohamed A; Gazy, Azza A; Khamis, Essam F; Ragab, Marwa A A; Kamal, Miranda F

2018-06-01

This study outlines two robust regression approaches, namely least median of squares (LMS) and iteratively re-weighted least squares (IRLS) to investigate their application in instrument analysis of nutraceuticals (that is, fluorescence quenching of merbromin reagent upon lipoic acid addition). These robust regression methods were used to calculate calibration data from the fluorescence quenching reaction (∆F and F-ratio) under ideal or non-ideal linearity conditions. For each condition, data were treated using three regression fittings: Ordinary Least Squares (OLS), LMS and IRLS. Assessment of linearity, limits of detection (LOD) and quantitation (LOQ), accuracy and precision were carefully studied for each condition. LMS and IRLS regression line fittings showed significant improvement in correlation coefficients and all regression parameters for both methods and both conditions. In the ideal linearity condition, the intercept and slope changed insignificantly, but a dramatic change was observed for the non-ideal condition and linearity intercept. Under both linearity conditions, LOD and LOQ values after the robust regression line fitting of data were lower than those obtained before data treatment. The results obtained after statistical treatment indicated that the linearity ranges for drug determination could be expanded to lower limits of quantitation by enhancing the regression equation parameters after data treatment. Analysis results for lipoic acid in capsules, using both fluorimetric methods, treated by parametric OLS and after treatment by robust LMS and IRLS were compared for both linearity conditions. Copyright © 2018 John Wiley & Sons, Ltd.

Evidence of directional and stabilizing selection in contemporary humans.

PubMed

Sanjak, Jaleal S; Sidorenko, Julia; Robinson, Matthew R; Thornton, Kevin R; Visscher, Peter M

2018-01-02

Modern molecular genetic datasets, primarily collected to study the biology of human health and disease, can be used to directly measure the action of natural selection and reveal important features of contemporary human evolution. Here we leverage the UK Biobank data to test for the presence of linear and nonlinear natural selection in a contemporary population of the United Kingdom. We obtain phenotypic and genetic evidence consistent with the action of linear/directional selection. Phenotypic evidence suggests that stabilizing selection, which acts to reduce variance in the population without necessarily modifying the population mean, is widespread and relatively weak in comparison with estimates from other species.

Linear-stability theory of thermocapillary convection in a model of float-zone crystal growth

NASA Technical Reports Server (NTRS)

Neitzel, G. P.; Chang, K.-T.; Jankowski, D. F.; Mittelmann, H. D.

1992-01-01

Linear-stability theory has been applied to a basic state of thermocapillary convection in a model half-zone to determine values of the Marangoni number above which instability is guaranteed. The basic state must be determined numerically since the half-zone is of finite, O(1) aspect ratio with two-dimensional flow and temperature fields. This, in turn, means that the governing equations for disturbance quantities will remain partial differential equations. The disturbance equations are treated by a staggered-grid discretization scheme. Results are presented for a variety of parameters of interest in the problem, including both terrestrial and microgravity cases.

Effect of current on spectrum of breaking waves in water of finite depth

NASA Technical Reports Server (NTRS)

Tung, C. C.; Huang, N. E.

1987-01-01

This paper presents an approximate method to compute the mean value, the mean square value and the spectrum of waves in water of finite depth taking into account the effect of wave breaking with or without the presence of current. It is assumed that there exists a linear and Gaussian ideal wave train whose spectrum is first obtained using the wave energy flux balance equation without considering wave breaking. The Miche wave breaking criterion for waves in finite water depth is used to limit the wave elevation and establish an expression for the breaking wave elevation in terms of the elevation and its second time derivative of the ideal waves. Simple expressions for the mean value, the mean square value and the spectrum are obtained. These results are applied to the case in which a deep water unidirectional wave train, propagating normally towards a straight shoreline over gently varying sea bottom of parallel and straight contours, encounters an adverse steady current whose velocity is assumed to be uniformly distributed with depth. Numerical results are obtained and presented in graphical form.

Imaging carbon nanotube interactions, diffusion, and stability in nanopores.

PubMed

Eichmann, Shannon L; Smith, Billy; Meric, Gulsum; Fairbrother, D Howard; Bevan, Michael A

2011-07-26

We report optical microscopy measurements of three-dimensional trajectories of individual multiwalled carbon nanotubes (MWCNTs) in nanoscale silica slit pores. Trajectories are analyzed to nonintrusively measure MWCNT interactions, diffusion, and stability as a function of pH and ionic strength. Evanescent wave scattering is used to track MWCNT positions normal to pore walls with nanometer-scale resolution, and video microscopy is used to track lateral positions with spatial resolution comparable to the diffraction limit. Analysis of MWCNT excursions normal to pore walls yields particle-wall potentials that agree with theoretical electrostatic and van der Waals potentials assuming a rotationally averaged potential of mean force. MWCNT lateral mean square displacements are used to quantify translational diffusivities, which are comparable to predictions based on the best available theories. Finally, measured MWCNT pH and ionic strength dependent stabilities are in excellent agreement with predictions. Our findings demonstrate novel measurement and modeling tools to understand the behavior of confined MWCNTs relevant to a broad range of applications.

What is the copper thin film thickness effect on thermal properties of NiTi/Cu bi-layer?

NASA Astrophysics Data System (ADS)

Fazeli, Sara; Vahedpour, Morteza; Khatiboleslam Sadrnezhaad, Sayed

2017-02-01

Molecular dynamics (MD) simulation was used to study of thermal properties of NiTi/Cu. Embedded atom method (EAM) potentials for describing of inter-atomic interaction and Nose-Hoover thermostat and barostat are employed. The melting of the bi-layers was considered by studying the temperature dependence of the cohesive energy and mean square displacement. To highlight the differences between bi-layers with various copper layer thickness, the effect of copper film thickness on thermal properties containing the cohesive energy, melting point, isobaric heat capacity and latent heat of fusion was estimated. The results show that thermal properties of bi-layer systems are higher than that of their corresponding of pure NiTi. But, these properties of bi-layer systems approximately are independent of copper film thicknesses. The mean square displacement (MSD) results show that, the diffusion coefficients enhance upon increasing of copper film thickness in a linear performance.

A Canonical Ensemble Correlation Prediction Model for Seasonal Precipitation Anomaly

NASA Technical Reports Server (NTRS)

Shen, Samuel S. P.; Lau, William K. M.; Kim, Kyu-Myong; Li, Guilong

2001-01-01

This report describes an optimal ensemble forecasting model for seasonal precipitation and its error estimation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. This new CCA model includes the following features: (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States precipitation field. The predictor is the sea surface temperature.

A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring.

PubMed

Martinek, Radek; Nedoma, Jan; Fajkus, Marcel; Kahankova, Radana; Konecny, Jaromir; Janku, Petr; Kepak, Stanislav; Bilik, Petr; Nazeran, Homer

2017-04-18

This paper focuses on the design, realization, and verification of a novel phonocardiographic- based fiber-optic sensor and adaptive signal processing system for noninvasive continuous fetal heart rate (fHR) monitoring. Our proposed system utilizes two Mach-Zehnder interferometeric sensors. Based on the analysis of real measurement data, we developed a simplified dynamic model for the generation and distribution of heart sounds throughout the human body. Building on this signal model, we then designed, implemented, and verified our adaptive signal processing system by implementing two stochastic gradient-based algorithms: the Least Mean Square Algorithm (LMS), and the Normalized Least Mean Square (NLMS) Algorithm. With this system we were able to extract the fHR information from high quality fetal phonocardiograms (fPCGs), filtered from abdominal maternal phonocardiograms (mPCGs) by performing fPCG signal peak detection. Common signal processing methods such as linear filtering, signal subtraction, and others could not be used for this purpose as fPCG and mPCG signals share overlapping frequency spectra. The performance of the adaptive system was evaluated by using both qualitative (gynecological studies) and quantitative measures such as: Signal-to-Noise Ratio-SNR, Root Mean Square Error-RMSE, Sensitivity-S+, and Positive Predictive Value-PPV.

A Phonocardiographic-Based Fiber-Optic Sensor and Adaptive Filtering System for Noninvasive Continuous Fetal Heart Rate Monitoring

PubMed Central

Martinek, Radek; Nedoma, Jan; Fajkus, Marcel; Kahankova, Radana; Konecny, Jaromir; Janku, Petr; Kepak, Stanislav; Bilik, Petr; Nazeran, Homer

2017-01-01

This paper focuses on the design, realization, and verification of a novel phonocardiographic- based fiber-optic sensor and adaptive signal processing system for noninvasive continuous fetal heart rate (fHR) monitoring. Our proposed system utilizes two Mach-Zehnder interferometeric sensors. Based on the analysis of real measurement data, we developed a simplified dynamic model for the generation and distribution of heart sounds throughout the human body. Building on this signal model, we then designed, implemented, and verified our adaptive signal processing system by implementing two stochastic gradient-based algorithms: the Least Mean Square Algorithm (LMS), and the Normalized Least Mean Square (NLMS) Algorithm. With this system we were able to extract the fHR information from high quality fetal phonocardiograms (fPCGs), filtered from abdominal maternal phonocardiograms (mPCGs) by performing fPCG signal peak detection. Common signal processing methods such as linear filtering, signal subtraction, and others could not be used for this purpose as fPCG and mPCG signals share overlapping frequency spectra. The performance of the adaptive system was evaluated by using both qualitative (gynecological studies) and quantitative measures such as: Signal-to-Noise Ratio—SNR, Root Mean Square Error—RMSE, Sensitivity—S+, and Positive Predictive Value—PPV. PMID:28420215

LLSURE: local linear SURE-based edge-preserving image filtering.

PubMed

Qiu, Tianshuang; Wang, Aiqi; Yu, Nannan; Song, Aimin

2013-01-01

In this paper, we propose a novel approach for performing high-quality edge-preserving image filtering. Based on a local linear model and using the principle of Stein's unbiased risk estimate as an estimator for the mean squared error from the noisy image only, we derive a simple explicit image filter which can filter out noise while preserving edges and fine-scale details. Moreover, this filter has a fast and exact linear-time algorithm whose computational complexity is independent of the filtering kernel size; thus, it can be applied to real time image processing tasks. The experimental results demonstrate the effectiveness of the new filter for various computer vision applications, including noise reduction, detail smoothing and enhancement, high dynamic range compression, and flash/no-flash denoising.

Application of quadratic optimization to supersonic inlet control

NASA Technical Reports Server (NTRS)

Lehtinen, B.; Zeller, J. R.

1971-01-01

The application of linear stochastic optimal control theory to the design of the control system for the air intake (inlet) of a supersonic air-breathing propulsion system is discussed. The controls must maintain a stable inlet shock position in the presence of random airflow disturbances and prevent inlet unstart. Two different linear time invariant control systems are developed. One is designed to minimize a nonquadratic index, the expected frequency of inlet unstart, and the other is designed to minimize the mean square value of inlet shock motion. The quadratic equivalence principle is used to obtain the best linear controller that minimizes the nonquadratic performance index. The two systems are compared on the basis of unstart prevention, control effort requirements, and sensitivity to parameter variations.

Static postural stability in women with stress urinary incontinence: Effects of vision and bladder filling.

PubMed

Chmielewska, Daria; Stania, Magdalena; Słomka, Kajetan; Błaszczak, Edward; Taradaj, Jakub; Dolibog, Patrycja; Juras, Grzegorz

2017-11-01

This case-control study was designed to compare static postural stability between women with stress urinary incontinence and continent women and it was hypothesized that women with incontinence aged around 50 years also have balance disorders. Eighteen women with incontinence and twelve women without incontinence aged 50-55 years participated in two 60-s trials of each of four different testing conditions: eyes open/full bladder, eyes open/empty bladder, eyes closed/full bladder, eyes closed/empty bladder. The center of foot pressure (COP): sway range, root mean square, velocity (in the antero-posterior and medio-lateral directions), and COP area were recorded. The stabilograms were decomposed into rambling and trembling components. The groups of women with and without incontinence differed during the full bladder condition in antero-posterior COP sway range, COP area, and rambling trajectory (range in the antero-posterior and medio-lateral directions, root mean square in the antero-posterior and medio-lateral directions and velocity in the antero-posterior direction). The women with incontinence had more difficulty controlling their postural balance than continent women while standing with a full bladder. Therefore, developing therapeutic management focused on strengthening the women's core muscles and improving their postural balance seems advisable. © 2017 Wiley Periodicals, Inc.

Exploration of structural stability in deleterious nsSNPs of the XPA gene: A molecular dynamics approach.

PubMed

Nagasundaram, N; Priya Doss, C George

2011-01-01

Distinguishing the deleterious from the massive number of non-functional nsSNPs that occur within a single genome is a considerable challenge in mutation research. In this approach, we have used the existing in silico methods to explore the mutation-structure-function relationship in the XPAgene. We used the Sorting Intolerant From Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen), I-Mutant 2.0, and the Protein Analysis THrough Evolutionary Relationships methods to predict the effects of deleterious nsSNPs on protein function and evaluated the impact of mutation on protein stability by Molecular Dynamics simulations. By comparing the scores of all the four in silico methods, nsSNP with an ID rs104894131 at position C108F was predicted to be highly deleterious. We extended our Molecular dynamics approach to gain insight into the impact of this non-synonymous polymorphism on structural changes that may affect the activity of the XPAgene. Based on the in silico methods score, potential energy, root-mean-square deviation, and root-mean-square fluctuation, we predict that deleterious nsSNP at position C108F would play a significant role in causing disease by the XPA gene. Our approach would present the application of in silicotools in understanding the functional variation from the perspective of structure, evolution, and phenotype.

Application of least mean square algorithm to suppression of maglev track-induced self-excited vibration

NASA Astrophysics Data System (ADS)

Zhou, D. F.; Li, J.; Hansen, C. H.

2011-11-01

Track-induced self-excited vibration is commonly encountered in EMS (electromagnetic suspension) maglev systems, and a solution to this problem is important in enabling the commercial widespread implementation of maglev systems. Here, the coupled model of the steel track and the magnetic levitation system is developed, and its stability is investigated using the Nyquist criterion. The harmonic balance method is employed to investigate the stability and amplitude of the self-excited vibration, which provides an explanation of the phenomenon that track-induced self-excited vibration generally occurs at a specified amplitude and frequency. To eliminate the self-excited vibration, an improved LMS (Least Mean Square) cancellation algorithm with phase correction (C-LMS) is employed. The harmonic balance analysis shows that the C-LMS cancellation algorithm can completely suppress the self-excited vibration. To achieve adaptive cancellation, a frequency estimator similar to the tuner of a TV receiver is employed to provide the C-LMS algorithm with a roughly estimated reference frequency. Numerical simulation and experiments undertaken on the CMS-04 vehicle show that the proposed adaptive C-LMS algorithm can effectively eliminate the self-excited vibration over a wide frequency range, and that the robustness of the algorithm suggests excellent potential for application to EMS maglev systems.

Noninvasive and fast measurement of blood glucose in vivo by near infrared (NIR) spectroscopy

NASA Astrophysics Data System (ADS)

Jintao, Xue; Liming, Ye; Yufei, Liu; Chunyan, Li; Han, Chen

2017-05-01

This research was to develop a method for noninvasive and fast blood glucose assay in vivo. Near-infrared (NIR) spectroscopy, a more promising technique compared to other methods, was investigated in rats with diabetes and normal rats. Calibration models are generated by two different multivariate strategies: partial least squares (PLS) as linear regression method and artificial neural networks (ANN) as non-linear regression method. The PLS model was optimized individually by considering spectral range, spectral pretreatment methods and number of model factors, while the ANN model was studied individually by selecting spectral pretreatment methods, parameters of network topology, number of hidden neurons, and times of epoch. The results of the validation showed the two models were robust, accurate and repeatable. Compared to the ANN model, the performance of the PLS model was much better, with lower root mean square error of validation (RMSEP) of 0.419 and higher correlation coefficients (R) of 96.22%.

A quasi-Monte-Carlo comparison of parametric and semiparametric regression methods for heavy-tailed and non-normal data: an application to healthcare costs.

PubMed

Jones, Andrew M; Lomas, James; Moore, Peter T; Rice, Nigel

2016-10-01

We conduct a quasi-Monte-Carlo comparison of the recent developments in parametric and semiparametric regression methods for healthcare costs, both against each other and against standard practice. The population of English National Health Service hospital in-patient episodes for the financial year 2007-2008 (summed for each patient) is randomly divided into two equally sized subpopulations to form an estimation set and a validation set. Evaluating out-of-sample using the validation set, a conditional density approximation estimator shows considerable promise in forecasting conditional means, performing best for accuracy of forecasting and among the best four for bias and goodness of fit. The best performing model for bias is linear regression with square-root-transformed dependent variables, whereas a generalized linear model with square-root link function and Poisson distribution performs best in terms of goodness of fit. Commonly used models utilizing a log-link are shown to perform badly relative to other models considered in our comparison.

Development of Super-Ensemble techniques for ocean analyses: the Mediterranean Sea case

NASA Astrophysics Data System (ADS)

Pistoia, Jenny; Pinardi, Nadia; Oddo, Paolo; Collins, Matthew; Korres, Gerasimos; Drillet, Yann

2017-04-01

Short-term ocean analyses for Sea Surface Temperature SST in the Mediterranean Sea can be improved by a statistical post-processing technique, called super-ensemble. This technique consists in a multi-linear regression algorithm applied to a Multi-Physics Multi-Model Super-Ensemble (MMSE) dataset, a collection of different operational forecasting analyses together with ad-hoc simulations produced by modifying selected numerical model parameterizations. A new linear regression algorithm based on Empirical Orthogonal Function filtering techniques is capable to prevent overfitting problems, even if best performances are achieved when we add correlation to the super-ensemble structure using a simple spatial filter applied after the linear regression. Our outcomes show that super-ensemble performances depend on the selection of an unbiased operator and the length of the learning period, but the quality of the generating MMSE dataset has the largest impact on the MMSE analysis Root Mean Square Error (RMSE) evaluated with respect to observed satellite SST. Lower RMSE analysis estimates result from the following choices: 15 days training period, an overconfident MMSE dataset (a subset with the higher quality ensemble members), and the least square algorithm being filtered a posteriori.

Linear Dimensional Stability of Irreversible Hydrocolloid Materials Over Time.

PubMed

Garrofé, Analía B; Ferrari, Beatriz A; Picca, Mariana; Kaplan, Andrea E

2015-12-01

The aim of this study was to evaluate the linear dimensional stability of different irreversible hydrocolloid materials over time. A metal mold was designed with custom trays made of thermoplastic sheets (Sabilex, sheets 0.125 mm thick). Perforations were made in order to improve retention of the material. Five impressions were taken with each of the following: Kromopan 100 (LASCOD) [AlKr], which has dimensional stability of 100 hours, and Phase Plus (ZHERMACK) [AlPh], which has dimensional stability of 48 hours. Standardized digital photographs were taken at different time intervals (0, 15, 30, 45, 60, 120 minutes; 12, 24 and 96 hours), using an "ad-hoc" device. The images were analyzed with software (UTHSCSA Image Tool) by measuring the distance between intersection of the lines previously made at the top of the mold. The results were analyzed by ANOVA for repeated measures. Initial and final values were (mean and standard deviation): AlKr: 16.44 (0.22) and 16.34 (0.11), AlPh: 16.40 (0.06) and 16.18 (0.06). Statistical evaluation showed significant effect of material and time factors. Under the conditions in this study, time significantly affects the linear dimensional stability of irreversible hydrocolloid materials. Sociedad Argentina de Investigación Odontológica.

Limb Dominance Results from Asymmetries in Predictive and Impedance Control Mechanisms

PubMed Central

Yadav, Vivek; Sainburg, Robert L.

2014-01-01

Handedness is a pronounced feature of human motor behavior, yet the underlying neural mechanisms remain unclear. We hypothesize that motor lateralization results from asymmetries in predictive control of task dynamics and in control of limb impedance. To test this hypothesis, we present an experiment with two different force field environments, a field with a predictable magnitude that varies with the square of velocity, and a field with a less predictable magnitude that varies linearly with velocity. These fields were designed to be compatible with controllers that are specialized in predicting limb and task dynamics, and modulating position and velocity dependent impedance, respectively. Because the velocity square field does not change the form of the equations of motion for the reaching arm, we reasoned that a forward dynamic-type controller should perform well in this field, while control of linear damping and stiffness terms should be less effective. In contrast, the unpredictable linear field should be most compatible with impedance control, but incompatible with predictive dynamics control. We measured steady state final position accuracy and 3 trajectory features during exposure to these fields: Mean squared jerk, Straightness, and Movement time. Our results confirmed that each arm made straighter, smoother, and quicker movements in its compatible field. Both arms showed similar final position accuracies, which were achieved using more extensive corrective sub-movements when either arm performed in its incompatible field. Finally, each arm showed limited adaptation to its incompatible field. Analysis of the dependence of trajectory errors on field magnitude suggested that dominant arm adaptation occurred by prediction of the mean field, thus exploiting predictive mechanisms for adaptation to the unpredictable field. Overall, our results support the hypothesis that motor lateralization reflects asymmetries in specific motor control mechanisms associated with predictive control of limb and task dynamics, and modulation of limb impedance. PMID:24695543

Feedback control of combustion instabilities from within limit cycle oscillations using H∞ loop-shaping and the ν-gap metric

PubMed Central

Morgans, Aimee S.

2016-01-01

Combustion instabilities arise owing to a two-way coupling between acoustic waves and unsteady heat release. Oscillation amplitudes successively grow, until nonlinear effects cause saturation into limit cycle oscillations. Feedback control, in which an actuator modifies some combustor input in response to a sensor measurement, can suppress combustion instabilities. Linear feedback controllers are typically designed, using linear combustor models. However, when activated from within limit cycle, the linear model is invalid, and such controllers are not guaranteed to stabilize. This work develops a feedback control strategy guaranteed to stabilize from within limit cycle oscillations. A low-order model of a simple combustor, exhibiting the essential features of more complex systems, is presented. Linear plane acoustic wave modelling is combined with a weakly nonlinear describing function for the flame. The latter is determined numerically using a level set approach. Its implication is that the open-loop transfer function (OLTF) needed for controller design varies with oscillation level. The difference between the mean and the rest of the OLTFs is characterized using the ν-gap metric, providing the minimum required ‘robustness margin’ for an H∞ loop-shaping controller. Such controllers are designed and achieve stability both for linear fluctuations and from within limit cycle oscillations. PMID:27493558

The evaluation of anthropogenic impact on the ecological stability of landscape.

PubMed

Michaeli, Eva; Ivanová, Monika; Koco, Štefan

2015-01-01

The model area is the northern surrounding of the water reservoir Zemplinska Irava in the east of Slovakia. Selection of the examined territory and the time horizons was not random. The aim was to capture the intensity level of anthropogenic impact on the values of the coefficient of ecological stability after the construction of water reservoir, Zempifnska Irava. The contribution evaluates ecological stability of landscape in the years 1956 and 2009 by GIS technology, using two methods. The first method determines the rate of ecological stability of landscape on the basis of the significance of land cover classes in the regular network of squares (the real size of the square is 0.5 square km). The second method determines the ecological stability of landscape secondary on the basis of the man influence on the landscape. A comparison of two methods has been made, as well as interpretation of the output data (e.g., monitoring the impact of marginal land cover classes with the minimal surfaces in the grid of square at the fluctuation of the index of ecological stability, respectively, it considers the possibilities to streamline the research results using homogeneous spatial units) and it also allows to track the changes in the ecological stability of the landscape in chronological development.

The Lanchester square-law model extended to a (2,2) conflict

NASA Astrophysics Data System (ADS)

Colegrave, R. K.; Hyde, J. M.

1993-01-01

A natural extension of the Lanchester (1,1) square-law model is the (M,N) linear model in which M forces oppose N forces with constant attrition rates. The (2,2) model is treated from both direct and inverse viewpoints. The inverse problem means that the model is to be fitted to a minimum number of observed force levels, i.e. the attrition rates are to be found from the initial force levels together with the levels observed at two subsequent times. An approach based on Hamiltonian dynamics has enabled the authors to derive a procedure for solving the inverse problem, which is readily computerized. Conflicts in which participants unexpectedly rally or weaken must be excluded.

Computationally efficient real-time interpolation algorithm for non-uniform sampled biosignals

PubMed Central

Eftekhar, Amir; Kindt, Wilko; Constandinou, Timothy G.

2016-01-01

This Letter presents a novel, computationally efficient interpolation method that has been optimised for use in electrocardiogram baseline drift removal. In the authors’ previous Letter three isoelectric baseline points per heartbeat are detected, and here utilised as interpolation points. As an extension from linear interpolation, their algorithm segments the interpolation interval and utilises different piecewise linear equations. Thus, the algorithm produces a linear curvature that is computationally efficient while interpolating non-uniform samples. The proposed algorithm is tested using sinusoids with different fundamental frequencies from 0.05 to 0.7 Hz and also validated with real baseline wander data acquired from the Massachusetts Institute of Technology University and Boston's Beth Israel Hospital (MIT-BIH) Noise Stress Database. The synthetic data results show an root mean square (RMS) error of 0.9 μV (mean), 0.63 μV (median) and 0.6 μV (standard deviation) per heartbeat on a 1 mVp–p 0.1 Hz sinusoid. On real data, they obtain an RMS error of 10.9 μV (mean), 8.5 μV (median) and 9.0 μV (standard deviation) per heartbeat. Cubic spline interpolation and linear interpolation on the other hand shows 10.7 μV, 11.6 μV (mean), 7.8 μV, 8.9 μV (median) and 9.8 μV, 9.3 μV (standard deviation) per heartbeat. PMID:27382478

Computationally efficient real-time interpolation algorithm for non-uniform sampled biosignals.

PubMed

Guven, Onur; Eftekhar, Amir; Kindt, Wilko; Constandinou, Timothy G

2016-06-01

This Letter presents a novel, computationally efficient interpolation method that has been optimised for use in electrocardiogram baseline drift removal. In the authors' previous Letter three isoelectric baseline points per heartbeat are detected, and here utilised as interpolation points. As an extension from linear interpolation, their algorithm segments the interpolation interval and utilises different piecewise linear equations. Thus, the algorithm produces a linear curvature that is computationally efficient while interpolating non-uniform samples. The proposed algorithm is tested using sinusoids with different fundamental frequencies from 0.05 to 0.7 Hz and also validated with real baseline wander data acquired from the Massachusetts Institute of Technology University and Boston's Beth Israel Hospital (MIT-BIH) Noise Stress Database. The synthetic data results show an root mean square (RMS) error of 0.9 μV (mean), 0.63 μV (median) and 0.6 μV (standard deviation) per heartbeat on a 1 mVp-p 0.1 Hz sinusoid. On real data, they obtain an RMS error of 10.9 μV (mean), 8.5 μV (median) and 9.0 μV (standard deviation) per heartbeat. Cubic spline interpolation and linear interpolation on the other hand shows 10.7 μV, 11.6 μV (mean), 7.8 μV, 8.9 μV (median) and 9.8 μV, 9.3 μV (standard deviation) per heartbeat.

Estimating Traffic Accidents in Turkey Using Differential Evolution Algorithm

NASA Astrophysics Data System (ADS)

Akgüngör, Ali Payıdar; Korkmaz, Ersin

2017-06-01

Estimating traffic accidents play a vital role to apply road safety procedures. This study proposes Differential Evolution Algorithm (DEA) models to estimate the number of accidents in Turkey. In the model development, population (P) and the number of vehicles (N) are selected as model parameters. Three model forms, linear, exponential and semi-quadratic models, are developed using DEA with the data covering from 2000 to 2014. Developed models are statistically compared to select the best fit model. The results of the DE models show that the linear model form is suitable to estimate the number of accidents. The statistics of this form is better than other forms in terms of performance criteria which are the Mean Absolute Percentage Errors (MAPE) and the Root Mean Square Errors (RMSE). To investigate the performance of linear DE model for future estimations, a ten-year period from 2015 to 2024 is considered. The results obtained from future estimations reveal the suitability of DE method for road safety applications.

Experimental and numerical analysis of pre-compressed masonry walls in two-way-bending with second order effects

NASA Astrophysics Data System (ADS)

Milani, Gabriele; Olivito, Renato S.; Tralli, Antonio

2014-10-01

The buckling behavior of slender unreinforced masonry (URM) walls subjected to axial compression and out-of-plane lateral loads is investigated through a combined experimental and numerical homogenizedapproach. After a preliminary analysis performed on a unit cell meshed by means of elastic FEs and non-linear interfaces, macroscopic moment-curvature diagrams so obtained are implemented at a structural level, discretizing masonry by means of rigid triangular elements and non-linear interfaces. The non-linear incremental response of the structure is accounted for a specific quadratic programming routine. In parallel, a wide experimental campaign is conducted on walls in two way bending, with the double aim of both validating the numerical model and investigating the behavior of walls that may not be reduced to simple cantilevers or simply supported beams. Panels investigated are dry-joint in scale square walls simply supported at the base and on a vertical edge, exhibiting the classical Rondelet's mechanism. The results obtained are compared with those provided by the numerical model.

The influence of the uplink noise on the performance of satellite data transmission systems

NASA Astrophysics Data System (ADS)

Dewal, Vrinda P.

The problem of transmission of binary phase shift keying (BPSK) modulated digital data through a bandlimited nonlinear satellite channel in the presence of uplink, downlink Gaussian noise and intersymbol interface is examined. The satellite transponder is represented by a zero memory bandpass nonlinearity, with AM/AM conversion. The proposed optimum linear receiver structure consists of tapped-delay lines followed by a decision device. The linear receiver is designed to minimize the mean square error that is a function of the intersymbol interface, the uplink and the downlink noise. The minimum mean square error equalizer (MMSE) is derived using the Wiener-Kolmogorov theory. In this receiver, the decision about the transmitted signal is made by taking into account the received sequence of present sample, and the interfering past and future samples, which represent the intersymbol interference (ISI). Illustrative examples of the receiver structures are considered for the nonlinear channels with a symmetrical and asymmetrical frequency responses of the transmitter filter. The transponder nonlinearity is simulated by a polynomial using only the first and the third orders terms. A computer simulation determines the tap gain coefficients of the MMSE equalizer that adapt to the various uplink and downlink noise levels. The performance of the MMSE equalizer is evaluated in terms of an estimate of the average probability of error.

Acoustic-articulatory mapping in vowels by locally weighted regression

PubMed Central

McGowan, Richard S.; Berger, Michael A.

2009-01-01

A method for mapping between simultaneously measured articulatory and acoustic data is proposed. The method uses principal components analysis on the articulatory and acoustic variables, and mapping between the domains by locally weighted linear regression, or loess [Cleveland, W. S. (1979). J. Am. Stat. Assoc. 74, 829–836]. The latter method permits local variation in the slopes of the linear regression, assuming that the function being approximated is smooth. The methodology is applied to vowels of four speakers in the Wisconsin X-ray Microbeam Speech Production Database, with formant analysis. Results are examined in terms of (1) examples of forward (articulation-to-acoustics) mappings and inverse mappings, (2) distributions of local slopes and constants, (3) examples of correlations among slopes and constants, (4) root-mean-square error, and (5) sensitivity of formant frequencies to articulatory change. It is shown that the results are qualitatively correct and that loess performs better than global regression. The forward mappings show different root-mean-square error properties than the inverse mappings indicating that this method is better suited for the forward mappings than the inverse mappings, at least for the data chosen for the current study. Some preliminary results on sensitivity of the first two formant frequencies to the two most important articulatory principal components are presented. PMID:19813812

A square-plate ultrasonic linear motor operating in two orthogonal first bending modes.

PubMed

Chen, Zhijiang; Li, Xiaotian; Chen, Jianguo; Dong, Shuxiang

2013-01-01

A novel square-plate piezoelectric ultrasonic linear motor operated in two orthogonal first bending vibration modes (B₁) is proposed. The piezoelectric vibrator of the linear motor is simply made of a single PZT ceramic plate (sizes: 15 x 15 x 2 mm) and poled in its thickness direction. The top surface electrode of the square ceramic plate was divided into four active areas along its two diagonal lines for exciting two orthogonal B₁ modes. The achieved driving force and speed from the linear motor are 1.8 N and 230 mm/s, respectively, under one pair orthogonal voltage drive of 150 V(p-p) at the resonance frequency of 92 kHz. The proposed linear motor has advantages over conventional ultrasonic linear motors, such as relatively larger driving force, very simple working mode and structure, and low fabrication cost.

Nonlinear filtering properties of detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Kiyono, Ken; Tsujimoto, Yutaka

2016-11-01

Detrended fluctuation analysis (DFA) has been widely used for quantifying long-range correlation and fractal scaling behavior. In DFA, to avoid spurious detection of scaling behavior caused by a nonstationary trend embedded in the analyzed time series, a detrending procedure using piecewise least-squares fitting has been applied. However, it has been pointed out that the nonlinear filtering properties involved with detrending may induce instabilities in the scaling exponent estimation. To understand this issue, we investigate the adverse effects of the DFA detrending procedure on the statistical estimation. We show that the detrending procedure using piecewise least-squares fitting results in the nonuniformly weighted estimation of the root-mean-square deviation and that this property could induce an increase in the estimation error. In addition, for comparison purposes, we investigate the performance of a centered detrending moving average analysis with a linear detrending filter and sliding window DFA and show that these methods have better performance than the standard DFA.

Chaos control in delayed phase space constructed by the Takens embedding theory

NASA Astrophysics Data System (ADS)

Hajiloo, R.; Salarieh, H.; Alasty, A.

2018-01-01

In this paper, the problem of chaos control in discrete-time chaotic systems with unknown governing equations and limited measurable states is investigated. Using the time-series of only one measurable state, an algorithm is proposed to stabilize unstable fixed points. The approach consists of three steps: first, using Takens embedding theory, a delayed phase space preserving the topological characteristics of the unknown system is reconstructed. Second, a dynamic model is identified by recursive least squares method to estimate the time-series data in the delayed phase space. Finally, based on the reconstructed model, an appropriate linear delayed feedback controller is obtained for stabilizing unstable fixed points of the system. Controller gains are computed using a systematic approach. The effectiveness of the proposed algorithm is examined by applying it to the generalized hyperchaotic Henon system, prey-predator population map, and the discrete-time Lorenz system.

Experimental and analytical study of secondary path variations in active engine mounts

NASA Astrophysics Data System (ADS)

Hausberg, Fabian; Scheiblegger, Christian; Pfeffer, Peter; Plöchl, Manfred; Hecker, Simon; Rupp, Markus

2015-03-01

Active engine mounts (AEMs) provide an effective solution to further improve the acoustic and vibrational comfort of passenger cars. Typically, adaptive feedforward control algorithms, e.g., the filtered-x-least-mean-squares (FxLMS) algorithm, are applied to cancel disturbing engine vibrations. These algorithms require an accurate estimate of the AEM active dynamic characteristics, also known as the secondary path, in order to guarantee control performance and stability. This paper focuses on the experimental and theoretical study of secondary path variations in AEMs. The impact of three major influences, namely nonlinearity, change of preload and component temperature, on the AEM active dynamic characteristics is experimentally analyzed. The obtained test results are theoretically investigated with a linear AEM model which incorporates an appropriate description for elastomeric components. A special experimental set-up extends the model validation of the active dynamic characteristics to higher frequencies up to 400 Hz. The theoretical and experimental results show that significant secondary path variations are merely observed in the frequency range of the AEM actuator's resonance frequency. These variations mainly result from the change of the component temperature. As the stability of the algorithm is primarily affected by the actuator's resonance frequency, the findings of this paper facilitate the design of AEMs with simpler adaptive feedforward algorithms. From a practical point of view it may further be concluded that algorithmic countermeasures against instability are only necessary in the frequency range of the AEM actuator's resonance frequency.

A Study of Impact Point Detecting Method Based on Seismic Signal

NASA Astrophysics Data System (ADS)

Huo, Pengju; Zhang, Yu; Xu, Lina; Huang, Yong

The projectile landing position has to be determined for its recovery and range in the targeting test. In this paper, a global search method based on the velocity variance is proposed. In order to verify the applicability of this method, simulation analysis within the scope of four million square meters has been conducted in the same array structure of the commonly used linear positioning method, and MATLAB was used to compare and analyze the two methods. The compared simulation results show that the global search method based on the speed of variance has high positioning accuracy and stability, which can meet the needs of impact point location.

46 CFR 178.330 - Simplified stability proof test.

Code of Federal Regulations, 2010 CFR

2010-10-01

...-meters (foot-pounds); P = wind pressure of: (1) 36.6 kilograms/square meter (7.5 pounds/square foot) for operation on protected waters; (2) 48.8 kilogram/square meter (10.0 pounds/square foot) for operation on partially protected waters; or (3) 73.3 kilograms/square meter (15.0 pounds/square foot) for operation on...

How to characterize the nonlinear amplifier?

NASA Technical Reports Server (NTRS)

Kallistratova, Dmitri Kouznetsov; Cotera, Carlos Flores

1994-01-01

The conception of the amplification of the coherent field is formulated. The definition of the coefficient of the amplification as the relation between the mean value of the field at the output to the value at the input and the definition of the noise as the difference between the number of photons in the output mode and square of the modulus of the mean value of the output amplitude are considered. Using a simple example it is shown that by these definitions the noise of the nonlinear amplifier may be less than the noise of the ideal linear amplifier of the same amplification coefficient. Proposals to search another definition of basic parameters of the nonlinear amplifiers are discussed. This definition should enable us to formulate the universal fundamental lower limit of the noise which should be valid for linear quantum amplifiers as for nonlinear ones.

H∞ filtering for discrete-time systems subject to stochastic missing measurements: a decomposition approach

NASA Astrophysics Data System (ADS)

Gu, Zhou; Fei, Shumin; Yue, Dong; Tian, Engang

2014-07-01

This paper deals with the problem of H∞ filtering for discrete-time systems with stochastic missing measurements. A new missing measurement model is developed by decomposing the interval of the missing rate into several segments. The probability of the missing rate in each subsegment is governed by its corresponding random variables. We aim to design a linear full-order filter such that the estimation error converges to zero exponentially in the mean square with a less conservatism while the disturbance rejection attenuation is constrained to a given level by means of an H∞ performance index. Based on Lyapunov theory, the reliable filter parameters are characterised in terms of the feasibility of a set of linear matrix inequalities. Finally, a numerical example is provided to demonstrate the effectiveness and applicability of the proposed design approach.

Identification of Synchronous Machine Stability - Parameters: AN On-Line Time-Domain Approach.

NASA Astrophysics Data System (ADS)

Le, Loc Xuan

1987-09-01

A time-domain modeling approach is described which enables the stability-study parameters of the synchronous machine to be determined directly from input-output data measured at the terminals of the machine operating under normal conditions. The transient responses due to system perturbations are used to identify the parameters of the equivalent circuit models. The described models are verified by comparing their responses with the machine responses generated from the transient stability models of a small three-generator multi-bus power system and of a single -machine infinite-bus power network. The least-squares method is used for the solution of the model parameters. As a precaution against ill-conditioned problems, the singular value decomposition (SVD) is employed for its inherent numerical stability. In order to identify the equivalent-circuit parameters uniquely, the solution of a linear optimization problem with non-linear constraints is required. Here, the SVD appears to offer a simple solution to this otherwise difficult problem. Furthermore, the SVD yields solutions with small bias and, therefore, physically meaningful parameters even in the presence of noise in the data. The question concerning the need for a more advanced model of the synchronous machine which describes subtransient and even sub-subtransient behavior is dealt with sensibly by the concept of condition number. The concept provides a quantitative measure for determining whether such an advanced model is indeed necessary. Finally, the recursive SVD algorithm is described for real-time parameter identification and tracking of slowly time-variant parameters. The algorithm is applied to identify the dynamic equivalent power system model.

Incorporation of prior information on parameters into nonlinear regression groundwater flow models: 2. Applications

USGS Publications Warehouse

Cooley, Richard L.

1983-01-01

This paper investigates factors influencing the degree of improvement in estimates of parameters of a nonlinear regression groundwater flow model by incorporating prior information of unknown reliability. Consideration of expected behavior of the regression solutions and results of a hypothetical modeling problem lead to several general conclusions. First, if the parameters are properly scaled, linearized expressions for the mean square error (MSE) in parameter estimates of a nonlinear model will often behave very nearly as if the model were linear. Second, by using prior information, the MSE in properly scaled parameters can be reduced greatly over the MSE of ordinary least squares estimates of parameters. Third, plots of estimated MSE and the estimated standard deviation of MSE versus an auxiliary parameter (the ridge parameter) specifying the degree of influence of the prior information on regression results can help determine the potential for improvement of parameter estimates. Fourth, proposed criteria can be used to make appropriate choices for the ridge parameter and another parameter expressing degree of overall bias in the prior information. Results of a case study of Truckee Meadows, Reno-Sparks area, Washoe County, Nevada, conform closely to the results of the hypothetical problem. In the Truckee Meadows case, incorporation of prior information did not greatly change the parameter estimates from those obtained by ordinary least squares. However, the analysis showed that both sets of estimates are more reliable than suggested by the standard errors from ordinary least squares.

Experimental and analytical investigations of longitudinal combustion instability in a continuously variable resonance combustor (CVRC)

NASA Astrophysics Data System (ADS)

Yu, Yen Ching

An analytical model based on linearized Euler equations (LEE) is developed and used in conjunction with a validating experiment to study combustion instability. The LEE model features mean flow effects, entropy waves, adaptability for more physically-realistic boundary conditions, and is generalized for multiple-domain conditions. The model calculates spatial modes, resonant frequencies and linear growth rates of the overall system. The predicted resonant frequencies and spatially-resolved mode shapes agree with the experimental data from a longitudinally-unstable model rocket combustor to within 7%. Different gaseous fuels (methane, ethylene, and hydrogen) were tested under fixed geometry. Tests with hydrogen were stable, whereas ethylene, methane, and JP-8 were increasingly unstable. A novel method for obtaining large amounts of stability data under variable resonance conditions in a single test was demonstrated. The continuously variable resonance combustor (CVRC) incorporates a traversing choked axial oxidizer inlet to vary the overall combustion system resonance. The CVRC experiment successfully demonstrates different level of instability, transitions between stability levels, and identifies the most stable and unstable geometric combination. Pressure oscillation amplitudes ranged from less than 10% of mean pressure to greater than 60%. At low amplitudes, measured resonant frequency changed with inlet location but at high amplitude the measured resonance frequency matched the frequency of the combustion chamber. As the system transitions from linear to non-linear instability, the higher harmonics of the fundamental resonant mode appear nearly simultaneously. Transient, high-amplitude, broadband noise, at lower frequencies (on the order of 200 Hz) are also observed. Conversely, as the system transitions back to a more linear stability regime, the higher harmonics disappear sequentially, led by the highest order. Good agreements between analytical and experimental results are attained by treating the experiment as quasi-stationary. The stability characteristics from the high frequency measurements are further analyzed using filtered pressure traces, spectrograms, power spectral density plots, and oscillation decrements. Future works recommended include: direct measurements, such as chemiluminescence or high-speed imaging to examine the unsteady combustion processes; three-way comparisons between the acoustic-based, linear Euler-based, and non-linear Euler/RANS model; use the high fidelity computation to investigate the forcing terms modeled in the acoustic-based model.

Vibration waveform effects on dynamic stabilization of ablative Rayleigh-Taylor instability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Piriz, A. R.; Lucchio, L. Di; Rodriguez Prieto, G.

2011-08-15

An analysis of dynamic stabilization of Rayleigh-Taylor instability in an ablation front is performed by considering a general square wave for modulating the vertical acceleration of the front. Such a kind of modulation allows for clarifying the role of thermal conduction in the mechanism of dynamic stabilization. In addition, the study of the effect of different modulations by varying the duration and amplitude of the square wave in each half-period provides insight on the optimum performance of dynamic stabilization.

Self-diffusion in a stochastically heated two-dimensional dusty plasma

NASA Astrophysics Data System (ADS)

Sheridan, T. E.

2016-09-01

Diffusion in a two-dimensional dusty plasma liquid (i.e., a Yukawa liquid) is studied experimentally. The dusty plasma liquid is heated stochastically by a surrounding three-dimensional toroidal dusty plasma gas which acts as a thermal reservoir. The measured dust velocity distribution functions are isotropic Maxwellians, giving a well-defined kinetic temperature. The mean-square displacement for dust particles is found to increase linearly with time, indicating normal diffusion. The measured diffusion coefficients increase approximately linearly with temperature. The effective collision rate is dominated by collective dust-dust interactions rather than neutral gas drag, and is comparable to the dusty-plasma frequency.

In Silico Template Selection of Short Antimicrobial Peptide Viscotoxin for Improving Its Antimicrobial Efficiency in Development of Potential Therapeutic Drugs.

PubMed

Senthilkumar, B; Rajasekaran, R

2017-03-01

Rapid increase in antibiotic resistance has posed a worldwide threat, due to increased mortality, morbidity, and expenditure caused by antibiotic-resistant microbes. Recent development of the antimicrobial peptides like viscotoxin (Vt) has been successfully comprehended as a substitute for classical antibiotics. A structurally stable peptide, Vt can enhance antimicrobial property and can be used for various developmental purposes. Thus, structural stability among the antimicrobial peptides, Vt A1 (3C8P), A2 (1JMN), A3 (1ED0), B (1JMP), and C (1ORL) of Viscus album was computationally analyzed. In specific, the static confirmation of VtA3 showed high number of intramolecular interactions, along with an increase in hydrophobicity than others comparatively. Further, conformational sampling was used to analyze various geometrical parameters such as root mean square deviation, root mean square fluctuation, radius of gyration, and ovality which also revealed the structural stability of VtA3. Moreover, the statistically validated contours of surface area, lipophilicity, and distance constraints of disulfide bonds also supported the priority of VtA3 with respect to stability. Finally, the functional activity of peptides was accessed by computing their free energy of membrane association and membrane interactions, which defined VtA3 as functionally stable. Currently, peptide-based antibiotics and nanoparticles have attracted the pharmaceutical industries for their potential therapeutic applications. Thereby, it is proposed that viscotoxin A3 (1ED0) could be used as a preeminent template for scaffolding potentially efficient antimicrobial peptide-based drugs and nanomaterials in future.

The dependence of sea surface slope on atmospheric stability and swell conditions

NASA Technical Reports Server (NTRS)

Hwang, Paul A.; Shemdin, Omar H.

1988-01-01

A tower-mounted optical device is used to measure the two-orthogonal components of the sea surface slope. The results indicate that an unstable stratification at the air-sea interface tends to enhance the surface roughness. The presence of a long ocean swell system steers the primary direction of shortwave propagation away from wind direction, and may increase or reduce the mean square slope of the sea surface.

A new linear least squares method for T1 estimation from SPGR signals with multiple TRs

NASA Astrophysics Data System (ADS)

Chang, Lin-Ching; Koay, Cheng Guan; Basser, Peter J.; Pierpaoli, Carlo

2009-02-01

The longitudinal relaxation time, T1, can be estimated from two or more spoiled gradient recalled echo x (SPGR) images with two or more flip angles and one or more repetition times (TRs). The function relating signal intensity and the parameters are nonlinear; T1 maps can be computed from SPGR signals using nonlinear least squares regression. A widely-used linear method transforms the nonlinear model by assuming a fixed TR in SPGR images. This constraint is not desirable since multiple TRs are a clinically practical way to reduce the total acquisition time, to satisfy the required resolution, and/or to combine SPGR data acquired at different times. A new linear least squares method is proposed using the first order Taylor expansion. Monte Carlo simulations of SPGR experiments are used to evaluate the accuracy and precision of the estimated T1 from the proposed linear and the nonlinear methods. We show that the new linear least squares method provides T1 estimates comparable in both precision and accuracy to those from the nonlinear method, allowing multiple TRs and reducing computation time significantly.

Asymptotic theory of neutral stability of the Couette flow of a vibrationally excited gas

NASA Astrophysics Data System (ADS)

Grigor'ev, Yu. N.; Ershov, I. V.

2017-01-01

An asymptotic theory of the neutral stability curve for a supersonic plane Couette flow of a vibrationally excited gas is developed. The initial mathematical model consists of equations of two-temperature viscous gas dynamics, which are used to derive a spectral problem for a linear system of eighth-order ordinary differential equations within the framework of the classical linear stability theory. Unified transformations of the system for all shear flows are performed in accordance with the classical Lin scheme. The problem is reduced to an algebraic secular equation with separation into the "inviscid" and "viscous" parts, which is solved numerically. It is shown that the thus-calculated neutral stability curves agree well with the previously obtained results of the direct numerical solution of the original spectral problem. In particular, the critical Reynolds number increases with excitation enhancement, and the neutral stability curve is shifted toward the domain of higher wave numbers. This is also confirmed by means of solving an asymptotic equation for the critical Reynolds number at the Mach number M ≤ 4.

Applying ISO 11929:2010 Standard to detection limit calculation in least-squares based multi-nuclide gamma-ray spectrum evaluation

NASA Astrophysics Data System (ADS)

Kanisch, G.

2017-05-01

The concepts of ISO 11929 (2010) are applied to evaluation of radionuclide activities from more complex multi-nuclide gamma-ray spectra. From net peak areas estimated by peak fitting, activities and their standard uncertainties are calculated by weighted linear least-squares method with an additional step, where uncertainties of the design matrix elements are taken into account. A numerical treatment of the standard's uncertainty function, based on ISO 11929 Annex C.5, leads to a procedure for deriving decision threshold and detection limit values. The methods shown allow resolving interferences between radionuclide activities also in case of calculating detection limits where they can improve the latter by including more than one gamma line per radionuclide. The co"mmon single nuclide weighted mean is extended to an interference-corrected (generalized) weighted mean, which, combined with the least-squares method, allows faster detection limit calculations. In addition, a new grouped uncertainty budget was inferred, which for each radionuclide gives uncertainty budgets from seven main variables, such as net count rates, peak efficiencies, gamma emission intensities and others; grouping refers to summation over lists of peaks per radionuclide.

Multimachine data–based prediction of high-frequency sensor signal noise for resistive wall mode control in ITER

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yueqiang; Sabbagh, S. A.; Chapman, I. T.

The high-frequency noise measured by magnetic sensors, at levels above the typical frequency of resistive wall modes, is analyzed across a range of present tokamak devices including DIII-D, JET, MAST, ASDEX Upgrade, JT-60U, and NSTX. A high-pass filter enables identification of the noise component with Gaussian-like statistics that shares certain common characteristics in all devices considered. A conservative prediction is made for ITER plasma operation of the high-frequency noise component of the sensor signals, to be used for resistive wall mode feedback stabilization, based on the multimachine database. The predicted root-mean-square n = 1 (n is the toroidal mode number)more » noise level is 10 4 to 10 5 G/s for the voltage signal, and 0.1 to 1 G for the perturbed magnetic field signal. The lower cutoff frequency of the Gaussian pickup noise scales linearly with the sampling frequency, with a scaling coefficient of about 0.1. As a result, these basic noise characteristics should be useful for the modeling-based design of the feedback control system for the resistive wall mode in ITER.« less

Multimachine data–based prediction of high-frequency sensor signal noise for resistive wall mode control in ITER

DOE PAGES

Liu, Yueqiang; Sabbagh, S. A.; Chapman, I. T.; ...

2017-03-27

The high-frequency noise measured by magnetic sensors, at levels above the typical frequency of resistive wall modes, is analyzed across a range of present tokamak devices including DIII-D, JET, MAST, ASDEX Upgrade, JT-60U, and NSTX. A high-pass filter enables identification of the noise component with Gaussian-like statistics that shares certain common characteristics in all devices considered. A conservative prediction is made for ITER plasma operation of the high-frequency noise component of the sensor signals, to be used for resistive wall mode feedback stabilization, based on the multimachine database. The predicted root-mean-square n = 1 (n is the toroidal mode number)more » noise level is 10 4 to 10 5 G/s for the voltage signal, and 0.1 to 1 G for the perturbed magnetic field signal. The lower cutoff frequency of the Gaussian pickup noise scales linearly with the sampling frequency, with a scaling coefficient of about 0.1. As a result, these basic noise characteristics should be useful for the modeling-based design of the feedback control system for the resistive wall mode in ITER.« less

Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kleijnen, J.P.C.; Helton, J.C.

1999-04-01

The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are consideredmore » for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.« less

Multivariate approaches for stability control of the olive oil reference materials for sensory analysis - part I: framework and fundamentals.

PubMed

Valverde-Som, Lucia; Ruiz-Samblás, Cristina; Rodríguez-García, Francisco P; Cuadros-Rodríguez, Luis

2018-02-09

Virgin olive oil is the only food product for which sensory analysis is regulated to classify it in different quality categories. To harmonize the results of the sensorial method, the use of standards or reference materials is crucial. The stability of sensory reference materials is required to enable their suitable control, aiming to confirm that their specific target values are maintained on an ongoing basis. Currently, such stability is monitored by means of sensory analysis and the sensory panels are in the paradoxical situation of controlling the standards that are devoted to controlling the panels. In the present study, several approaches based on similarity analysis are exploited. For each approach, the specific methodology to build a proper multivariate control chart to monitor the stability of the sensory properties is explained and discussed. The normalized Euclidean and Mahalanobis distances, the so-called nearness and hardiness indices respectively, have been defined as new similarity indices to range the values from 0 to 1. Also, the squared mean from Hotelling's T 2 -statistic and Q 2 -statistic has been proposed as another similarity index. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Squared eigenfunctions for the Sasa-Satsuma equation

NASA Astrophysics Data System (ADS)

Yang, Jianke; Kaup, D. J.

2009-02-01

Squared eigenfunctions are quadratic combinations of Jost functions and adjoint Jost functions which satisfy the linearized equation of an integrable equation. They are needed for various studies related to integrable equations, such as the development of its soliton perturbation theory. In this article, squared eigenfunctions are derived for the Sasa-Satsuma equation whose spectral operator is a 3×3 system, while its linearized operator is a 2×2 system. It is shown that these squared eigenfunctions are sums of two terms, where each term is a product of a Jost function and an adjoint Jost function. The procedure of this derivation consists of two steps: First is to calculate the variations of the potentials via variations of the scattering data by the Riemann-Hilbert method. The second one is to calculate the variations of the scattering data via the variations of the potentials through elementary calculations. While this procedure has been used before on other integrable equations, it is shown here, for the first time, that for a general integrable equation, the functions appearing in these variation relations are precisely the squared eigenfunctions and adjoint squared eigenfunctions satisfying, respectively, the linearized equation and the adjoint linearized equation of the integrable system. This proof clarifies this procedure and provides a unified explanation for previous results of squared eigenfunctions on individual integrable equations. This procedure uses primarily the spectral operator of the Lax pair. Thus two equations in the same integrable hierarchy will share the same squared eigenfunctions (except for a time-dependent factor). In the Appendix, the squared eigenfunctions are presented for the Manakov equations whose spectral operator is closely related to that of the Sasa-Satsuma equation.

Sensitivity of boundary-layer stability to base-state distortions at high Mach numbers

NASA Astrophysics Data System (ADS)

Park, Junho; Zaki, Tamer

2017-11-01

The stability diagram of high-speed boundary layers has been established by evaluating the linear instability modes of the similarity profile, over wide ranges of Reynolds and Mach numbers. In real flows, however, the base state can deviate from the similarity profile. Both the base velocity and temperature can be distorted, for example due to roughness and thermal wall treatments. We review the stability problem of high-speed boundary layer, and derive a new formulation of the sensitivity to base-state distortion using forward and adjoint parabolized stability equations. The new formulation provides qualitative and quantitative interpretations on change in growth rate due to modifications of mean-flow and mean-temperature in heated high-speed boundary layers, and establishes the foundation for future control strategies. This work has been funded by the Air Force Office of Scientific Research (AFOSR) Grant: FA9550-16-1-0103.

A comparison of methods for DPLL loop filter design

NASA Technical Reports Server (NTRS)

Aguirre, S.; Hurd, W. J.; Kumar, R.; Statman, J.

1986-01-01

Four design methodologies for loop filters for a class of digital phase-locked loops (DPLLs) are presented. The first design maps an optimum analog filter into the digital domain; the second approach designs a filter that minimizes in discrete time weighted combination of the variance of the phase error due to noise and the sum square of the deterministic phase error component; the third method uses Kalman filter estimation theory to design a filter composed of a least squares fading memory estimator and a predictor. The last design relies on classical theory, including rules for the design of compensators. Linear analysis is used throughout the article to compare different designs, and includes stability, steady state performance and transient behavior of the loops. Design methodology is not critical when the loop update rate can be made high relative to loop bandwidth, as the performance approaches that of continuous time. For low update rates, however, the miminization method is significantly superior to the other methods.

Higher-order Skyrme hair of black holes

NASA Astrophysics Data System (ADS)

Gudnason, Sven Bjarke; Nitta, Muneto

2018-05-01

Higher-order derivative terms are considered as replacement for the Skyrme term in an Einstein-Skyrme-like model in order to pinpoint which properties are necessary for a black hole to possess stable static scalar hair. We find two new models able to support stable black hole hair in the limit of the Skyrme term being turned off. They contain 8 and 12 derivatives, respectively, and are roughly the Skyrme-term squared and the so-called BPS-Skyrme-term squared. In the twelfth-order model we find that the lower branches, which are normally unstable, become stable in the limit where the Skyrme term is turned off. We check this claim with a linear stability analysis. Finally, we find for a certain range of the gravitational coupling and horizon radius, that the twelfth-order model contains 4 solutions as opposed to 2. More surprisingly, the lowest part of the would-be unstable branch turns out to be the stable one of the 4 solutions.

Basin stability measure of different steady states in coupled oscillators

NASA Astrophysics Data System (ADS)

Rakshit, Sarbendu; Bera, Bidesh K.; Majhi, Soumen; Hens, Chittaranjan; Ghosh, Dibakar

2017-04-01

In this report, we investigate the stabilization of saddle fixed points in coupled oscillators where individual oscillators exhibit the saddle fixed points. The coupled oscillators may have two structurally different types of suppressed states, namely amplitude death and oscillation death. The stabilization of saddle equilibrium point refers to the amplitude death state where oscillations are ceased and all the oscillators converge to the single stable steady state via inverse pitchfork bifurcation. Due to multistability features of oscillation death states, linear stability theory fails to analyze the stability of such states analytically, so we quantify all the states by basin stability measurement which is an universal nonlocal nonlinear concept and it interplays with the volume of basins of attractions. We also observe multi-clustered oscillation death states in a random network and measure them using basin stability framework. To explore such phenomena we choose a network of coupled Duffing-Holmes and Lorenz oscillators which are interacting through mean-field coupling. We investigate how basin stability for different steady states depends on mean-field density and coupling strength. We also analytically derive stability conditions for different steady states and confirm by rigorous bifurcation analysis.

Conserved linear dynamics of single-molecule Brownian motion.

PubMed

Serag, Maged F; Habuchi, Satoshi

2017-06-06

Macromolecular diffusion in homogeneous fluid at length scales greater than the size of the molecule is regarded as a random process. The mean-squared displacement (MSD) of molecules in this regime increases linearly with time. Here we show that non-random motion of DNA molecules in this regime that is undetectable by the MSD analysis can be quantified by characterizing the molecular motion relative to a latticed frame of reference. Our lattice occupancy analysis reveals unexpected sub-modes of motion of DNA that deviate from expected random motion in the linear, diffusive regime. We demonstrate that a subtle interplay between these sub-modes causes the overall diffusive motion of DNA to appear to conform to the linear regime. Our results show that apparently random motion of macromolecules could be governed by non-random dynamics that are detectable only by their relative motion. Our analytical approach should advance broad understanding of diffusion processes of fundamental relevance.

Conserved linear dynamics of single-molecule Brownian motion

PubMed Central

Serag, Maged F.; Habuchi, Satoshi

2017-01-01

Macromolecular diffusion in homogeneous fluid at length scales greater than the size of the molecule is regarded as a random process. The mean-squared displacement (MSD) of molecules in this regime increases linearly with time. Here we show that non-random motion of DNA molecules in this regime that is undetectable by the MSD analysis can be quantified by characterizing the molecular motion relative to a latticed frame of reference. Our lattice occupancy analysis reveals unexpected sub-modes of motion of DNA that deviate from expected random motion in the linear, diffusive regime. We demonstrate that a subtle interplay between these sub-modes causes the overall diffusive motion of DNA to appear to conform to the linear regime. Our results show that apparently random motion of macromolecules could be governed by non-random dynamics that are detectable only by their relative motion. Our analytical approach should advance broad understanding of diffusion processes of fundamental relevance. PMID:28585925

Conserved linear dynamics of single-molecule Brownian motion

NASA Astrophysics Data System (ADS)

Serag, Maged F.; Habuchi, Satoshi

2017-06-01

Macromolecular diffusion in homogeneous fluid at length scales greater than the size of the molecule is regarded as a random process. The mean-squared displacement (MSD) of molecules in this regime increases linearly with time. Here we show that non-random motion of DNA molecules in this regime that is undetectable by the MSD analysis can be quantified by characterizing the molecular motion relative to a latticed frame of reference. Our lattice occupancy analysis reveals unexpected sub-modes of motion of DNA that deviate from expected random motion in the linear, diffusive regime. We demonstrate that a subtle interplay between these sub-modes causes the overall diffusive motion of DNA to appear to conform to the linear regime. Our results show that apparently random motion of macromolecules could be governed by non-random dynamics that are detectable only by their relative motion. Our analytical approach should advance broad understanding of diffusion processes of fundamental relevance.

EEG/ERP adaptive noise canceller design with controlled search space (CSS) approach in cuckoo and other optimization algorithms.

PubMed

Ahirwal, M K; Kumar, Anil; Singh, G K

2013-01-01

This paper explores the migration of adaptive filtering with swarm intelligence/evolutionary techniques employed in the field of electroencephalogram/event-related potential noise cancellation or extraction. A new approach is proposed in the form of controlled search space to stabilize the randomness of swarm intelligence techniques especially for the EEG signal. Swarm-based algorithms such as Particles Swarm Optimization, Artificial Bee Colony, and Cuckoo Optimization Algorithm with their variants are implemented to design optimized adaptive noise canceler. The proposed controlled search space technique is tested on each of the swarm intelligence techniques and is found to be more accurate and powerful. Adaptive noise canceler with traditional algorithms such as least-mean-square, normalized least-mean-square, and recursive least-mean-square algorithms are also implemented to compare the results. ERP signals such as simulated visual evoked potential, real visual evoked potential, and real sensorimotor evoked potential are used, due to their physiological importance in various EEG studies. Average computational time and shape measures of evolutionary techniques are observed 8.21E-01 sec and 1.73E-01, respectively. Though, traditional algorithms take negligible time consumption, but are unable to offer good shape preservation of ERP, noticed as average computational time and shape measure difference, 1.41E-02 sec and 2.60E+00, respectively.

Merging physical parameters and laboratory subjective ratings for the soundscape assessment of urban squares.

PubMed

Brambilla, Giovanni; Maffei, Luigi; Di Gabriele, Maria; Gallo, Veronica

2013-07-01

An experimental study was carried out in 20 squares in the center of Rome, covering a wide range of different uses, sonic environments, geometry, and architectural styles. Soundwalks along the perimeter of each square were performed during daylight and weekdays taking binaural and video recordings, as well as spot measurements of illuminance. The cluster analysis performed on the physical parameters, not only acoustic, provided two clusters that are in satisfactory agreement with the "a priori" classification. Applying the principal component analysis (PCA) to five physical parameters, two main components were obtained which might be associated to two environmental features, namely, "chaotic/calm" and "open/enclosed." On the basis of these two features, six squares were selected for the laboratory audio-video tests where 32 subjects took part filling in a questionnaire. The PCA performed on the subjective ratings on the sonic environment showed two main components which might be associated to two emotional meanings, namely, "calmness" and "vibrancy." The linear regression modeling between five objective parameters and the mean value of subjective ratings on chaotic/calm and enclosed/open attributes showed a good correlation. Notwithstanding these interesting results being limited to the specific data set, it is worth pointing out that the complexity of the soundscape quality assessment can be more comprehensively examined merging the field measurements of physical parameters with the subjective ratings provided by field and/or laboratory tests.

Classification and Evaluation of Coherent Synchronous Sampled-Data Telemetry Systems

NASA Technical Reports Server (NTRS)

Viterbi, Andrew

1961-01-01

This paper analyzes the various types of continuous wave and pulse modulation for the transmission of sampled data over channels perturbed by white gaussian noise. Optimal coherent synchronous detection schemes for all the different modulation methods are shown to belong to one of two general classes: linear synchronous detection and correlation detection. The figures of merit, mean-square signal-to-error ratio and bandwidth occupancy, are determined for each system and compared.

Using permutations to detect dependence between time series

NASA Astrophysics Data System (ADS)

Cánovas, Jose S.; Guillamón, Antonio; Ruíz, María del Carmen

2011-07-01

In this paper, we propose an independence test between two time series which is based on permutations. The proposed test can be carried out by means of different common statistics such as Pearson’s chi-square or the likelihood ratio. We also point out why an exact test is necessary. Simulated and real data (return exchange rates between several currencies) reveal the capacity of this test to detect linear and nonlinear dependences.

Test of the diffusing-diffusivity mechanism using near-wall colloidal dynamics

NASA Astrophysics Data System (ADS)

Matse, Mpumelelo; Chubynsky, Mykyta V.; Bechhoefer, John

2017-10-01

The mechanism of diffusing diffusivity predicts that, in environments where the diffusivity changes gradually, the displacement distribution becomes non-Gaussian, even though the mean-square displacement grows linearly with time. Here, we report single-particle tracking measurements of the diffusion of colloidal spheres near a planar substrate. Because the local effective diffusivity is known, we have been able to carry out a direct test of this mechanism for diffusion in inhomogeneous media.

Optimal generalized multistep integration formulae for real-time digital simulation

NASA Technical Reports Server (NTRS)

Moerder, D. D.; Halyo, N.

1985-01-01

The problem of discretizing a dynamical system for real-time digital simulation is considered. Treating the system and its simulation as stochastic processes leads to a statistical characterization of simulator fidelity. A plant discretization procedure based on an efficient matrix generalization of explicit linear multistep discrete integration formulae is introduced, which minimizes a weighted sum of the mean squared steady-state and transient error between the system and simulator outputs.

Integrating Map Algebra and Statistical Modeling for Spatio- Temporal Analysis of Monthly Mean Daily Incident Photosynthetically Active Radiation (PAR) over a Complex Terrain.

PubMed

Evrendilek, Fatih

2007-12-12

This study aims at quantifying spatio-temporal dynamics of monthly mean dailyincident photosynthetically active radiation (PAR) over a vast and complex terrain such asTurkey. The spatial interpolation method of universal kriging, and the combination ofmultiple linear regression (MLR) models and map algebra techniques were implemented togenerate surface maps of PAR with a grid resolution of 500 x 500 m as a function of fivegeographical and 14 climatic variables. Performance of the geostatistical and MLR modelswas compared using mean prediction error (MPE), root-mean-square prediction error(RMSPE), average standard prediction error (ASE), mean standardized prediction error(MSPE), root-mean-square standardized prediction error (RMSSPE), and adjustedcoefficient of determination (R² adj. ). The best-fit MLR- and universal kriging-generatedmodels of monthly mean daily PAR were validated against an independent 37-year observeddataset of 35 climate stations derived from 160 stations across Turkey by the Jackknifingmethod. The spatial variability patterns of monthly mean daily incident PAR were moreaccurately reflected in the surface maps created by the MLR-based models than in thosecreated by the universal kriging method, in particular, for spring (May) and autumn(November). The MLR-based spatial interpolation algorithms of PAR described in thisstudy indicated the significance of the multifactor approach to understanding and mappingspatio-temporal dynamics of PAR for a complex terrain over meso-scales.

A simplified computer program for the prediction of the linear stability behavior of liquid propellant combustors

NASA Technical Reports Server (NTRS)

Mitchell, C. E.; Eckert, K.

1979-01-01

A program for predicting the linear stability of liquid propellant rocket engines is presented. The underlying model assumptions and analytical steps necessary for understanding the program and its input and output are also given. The rocket engine is modeled as a right circular cylinder with an injector with a concentrated combustion zone, a nozzle, finite mean flow, and an acoustic admittance, or the sensitive time lag theory. The resulting partial differential equations are combined into two governing integral equations by the use of the Green's function method. These equations are solved using a successive approximation technique for the small amplitude (linear) case. The computational method used as well as the various user options available are discussed. Finally, a flow diagram, sample input and output for a typical application and a complete program listing for program MODULE are presented.

Stability of nonuniform rotor blades in hover using a mixed formulation

NASA Technical Reports Server (NTRS)

Stephens, W. B.; Hodges, D. H.; Avila, J. H.; Kung, R. M.

1980-01-01

A mixed formulation for calculating static equilibrium and stability eigenvalues of nonuniform rotor blades in hover is presented. The static equilibrium equations are nonlinear and are solved by an accurate and efficient collocation method. The linearized perturbation equations are solved by a one step, second order integration scheme. The numerical results correlate very well with published results from a nearly identical stability analysis based on a displacement formulation. Slight differences in the results are traced to terms in the equations that relate moments to derivatives of rotations. With the present ordering scheme, in which terms of the order of squares of rotations are neglected with respect to unity, it is not possible to achieve completely equivalent models based on mixed and displacement formulations. The one step methods reveal that a second order Taylor expansion is necessary to achieve good convergence for nonuniform rotating blades. Numerical results for a hypothetical nonuniform blade, including the nonlinear static equilibrium solution, were obtained with no more effort or computer time than that required for a uniform blade.

The roll-up and merging of coherent structures in shallow mixing layers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lam, M. Y., E-mail: celmy@connect.ust.hk; Ghidaoui, M. S.; Kolyshkin, A. A.

2016-09-15

The current study seeks a fundamental explanation to the development of two-dimensional coherent structures (2DCSs) in shallow mixing layers. A nonlinear numerical model based on the depth-averaged shallow water equations is used to investigate the temporal evolution of shallow mixing layers, where the mapping from temporal to spatial results is made using the velocity at the center of the mixing layers. The flow is periodic in the streamwise direction. Transmissive boundary conditions are used in the cross-stream boundaries to prevent reflections. Numerical results are compared to linear stability analysis, mean-field theory, and secondary stability analysis. Results suggest that the onsetmore » and development of 2DCS in shallow mixing layers are the result of a sequence of instabilities governed by linear theory, mean-field theory, and secondary stability theory. The linear instability of the shearing velocity gradient gives the onset of 2DCS. When the perturbations reach a certain amplitude, the flow field of the perturbations changes from a wavy shape to a vortical (2DCS) structure because of nonlinearity. The development of the vertical 2DCS does not appear to follow weakly nonlinear theory; instead, it follows mean-field theory. After the formation of 2DCS, separate 2DCSs merge to form larger 2DCS. In this way, 2DCSs grow and shallow mixing layers develop and grow in scale. The merging of 2DCS in shallow mixing layers is shown to be caused by the secondary instability of the 2DCS. Eventually 2DCSs are dissipated by bed friction. The sequence of instabilities can cause the upscaling of the turbulent kinetic energy in shallow mixing layers.« less

Infrared modification of gravity from conformal symmetry

NASA Astrophysics Data System (ADS)

Gegenberg, Jack; Rahmati, Shohreh; Seahra, Sanjeev S.

2016-03-01

We reconsider a gauge theory of gravity in which the gauge group is the conformal group SO(4,2), and the action is of the Yang-Mills form, quadratic in the curvature. The resulting gravitational theory exhibits local conformal symmetry and reduces to Weyl-squared gravity under certain conditions. When the theory is linearized about flat spacetime, we find that matter which couples to the generators of special conformal transformations reproduces Newton's inverse square law. Conversely, matter which couples to generators of translations induces a constant and possibly repulsive force far from the source, which may be relevant for explaining the late-time acceleration of the Universe. The coupling constant of the theory is dimensionless, which means that it is potentially renormalizable.

Estimation of the simple correlation coefficient.

PubMed

Shieh, Gwowen

2010-11-01

This article investigates some unfamiliar properties of the Pearson product-moment correlation coefficient for the estimation of simple correlation coefficient. Although Pearson's r is biased, except for limited situations, and the minimum variance unbiased estimator has been proposed in the literature, researchers routinely employ the sample correlation coefficient in their practical applications, because of its simplicity and popularity. In order to support such practice, this study examines the mean squared errors of r and several prominent formulas. The results reveal specific situations in which the sample correlation coefficient performs better than the unbiased and nearly unbiased estimators, facilitating recommendation of r as an effect size index for the strength of linear association between two variables. In addition, related issues of estimating the squared simple correlation coefficient are also considered.

Lack of Association of Estrogen Receptor Alpha Gene Polymorphisms with Cardiorespiratory and Metabolic Variables in Young Women

PubMed Central

Rebelo, Ana Cristina; Verlengia, Rozangela; Kunz, Vandeni; Tamburus, Nayara; Cerda, Alvaro; Hirata, Rosario; Hirata, Mario; Silva, Ester

2012-01-01

This study examined the association of estrogen receptor alpha gene (ESR1) polymorphisms with cardiorespiratory and metabolic parameters in young women. In total, 354 healthy women were selected for cardiopulmonary exercise testing and short-term heart rate (HR) variability (HRV) evaluation. The HRV analysis was determined by the temporal indices rMSSD (square root of the mean squared differences of successive R–R intervals (RRi) divided by the number of RRi minus one), SDNN (root mean square of differences from mean RRi, divided by the number of RRi) and power spectrum components by low frequency (LF), high frequency (HF) and LF/HF ratio. Blood samples were obtained for serum lipids, estradiol and DNA extraction. ESR1 rs2234693 and rs9340799 polymorphisms were analyzed by PCR and fragment restriction analysis. HR and oxygen uptake (VO2) values did not differ between the ESR1 polymorphisms with respect to autonomic modulation. We not find a relationship between ESR1 T–A, T–G, C–A and C–G haplotypes and cardiorespiratory and metabolic variables. Multiple linear regression analysis demonstrated that VO2, total cholesterol and triglycerides influence HRV (p < 0.05). The results suggest that ESR1 variants have no effect on cardiorespiratory and metabolic variables, while HRV indices are influenced by aerobic capacity and lipids in healthy women. PMID:23202974

Updating QR factorization procedure for solution of linear least squares problem with equality constraints.

PubMed

Zeb, Salman; Yousaf, Muhammad

2017-01-01

In this article, we present a QR updating procedure as a solution approach for linear least squares problem with equality constraints. We reduce the constrained problem to unconstrained linear least squares and partition it into a small subproblem. The QR factorization of the subproblem is calculated and then we apply updating techniques to its upper triangular factor R to obtain its solution. We carry out the error analysis of the proposed algorithm to show that it is backward stable. We also illustrate the implementation and accuracy of the proposed algorithm by providing some numerical experiments with particular emphasis on dense problems.

Pressure fluctuations and time scales in turbulent channel flow

NASA Astrophysics Data System (ADS)

Septham, Kamthon; Morrison, Jonathan; Diwan, Sourabh

2015-11-01

Pressure fluctuations in turbulent channel flow subjected to globally stabilising linear feedback control are investigated at Reτ = 400 . The passivity-based control is adopted and explained by the conservative characteristics of the nonlinear terms contributing to the Reynolds-Orr equation (Sharma et al. Phys. Fluids 2011). The linear control operates via vU' ; the maximum forcing is located at y+ ~ 20 , corresponding to the location of the maximum in the mean-square pressure gradient. The responses of the rapid (linear) and slow (nonlinear) pressure fluctuations to the linear control are investigated using the Green's function representations. It demonstrates that the linear control operates via the linear source terms of the Poisson equation for pressure fluctuations. Landahl's timescales of the minimal flow unit (MFU) in turbulent channel flow are examined at y+ = 20 . It shows that the timescales of MFU agree well with the theoretical values proposed by Landahl (1993). Therefore, the effectiveness of the linear control to attenuate wall turbulence is explained by Landahl's theory for timescales, in that the control proceeds via the shear interaction timescale which is significantly shorter than both the nonlinear and viscous timescales.

Non-linear coherent mode interactions and the control of shear layers

NASA Technical Reports Server (NTRS)

Nikitopoulos, D. E.; Liu, J. T. C.

1990-01-01

A nonlinear integral formulation, based on local linear stability considerations, is used to study the collective interactions between discrete wave-modes associated with large-scale structures and the mean flow in a developing shear layer. Aspects of shear layer control are examined in light of the sensitivity of these interactions to the initial frequency parameter, modal energy contents and modal phases. Manipulation of the large-scale structure is argued to be an effective means of controlling the flow, including the small-scale turbulence dominated region far downstream. Cases of fundamental, 1st and 2nd subharmonic forcing are discussed in conjunction with relevant experiments.

Molecular Dynamics Approach in Designing Thermostable Aspergillus niger Xylanase

NASA Astrophysics Data System (ADS)

Malau, N. D.; Sianturi, M.

2017-03-01

Molecular dynamics methods we have applied as a tool in designing thermostable Aspergillus niger Xylanase, by examining Root Mean Square Deviation (RMSD) and The Stability of the Secondary Structure of enzymes structure at its optimum temperature and compare with its high temperature behavior. As RMSD represents structural fluctuation at a particular temperature, a better understanding of this factor will suggest approaches to bioengineer these enzymes to enhance their thermostability. In this work molecular dynamic simulations of Aspergillus niger xylanase (ANX) have been carried at 400K (optimum catalytic temperature) for 2.5 ns and 500K (ANX reported inactive temperature) for 2.5 ns. Analysis have shown that the Root Mean Square Deviation (RMSD) significant increase at higher temperatures compared at optimum temperature and some of the secondary structures of ANX that have been damaged at high temperature. Structural analysis revealed that the fluctuations of the α-helix and β-sheet regions are larger at higher temperatures compared to the fluctuations at optimum temperature.

Characterization of the Interaction between Gallic Acid and Lysozyme by Molecular Dynamics Simulation and Optical Spectroscopy

PubMed Central

Zhan, Minzhong; Guo, Ming; Jiang, Yanke; Wang, Xiaomeng

2015-01-01

The binding interaction between gallic acid (GA) and lysozyme (LYS) was investigated and compared by molecular dynamics (MD) simulation and spectral techniques. The results from spectroscopy indicate that GA binds to LYS to generate a static complex. The binding constants and thermodynamic parameters were calculated. MD simulation revealed that the main driving forces for GA binding to LYS are hydrogen bonding and hydrophobic interactions. The root-mean-square deviation verified that GA and LYS bind to form a stable complex, while the root-mean-square fluctuation results showed that the stability of the GA-LYS complex at 298 K was higher than that at 310 K. The calculated free binding energies from the molecular mechanics/Poisson-Boltzmann surface area method showed that van der Waals forces and electrostatic interactions are the predominant intermolecular forces. The MD simulation was consistent with the spectral experiments. This study provides a reference for future study of the pharmacological mechanism of GA. PMID:26140374

Characterization of the Interaction between Gallic Acid and Lysozyme by Molecular Dynamics Simulation and Optical Spectroscopy.

PubMed

Zhan, Minzhong; Guo, Ming; Jiang, Yanke; Wang, Xiaomeng

2015-07-01

The binding interaction between gallic acid (GA) and lysozyme (LYS) was investigated and compared by molecular dynamics (MD) simulation and spectral techniques. The results from spectroscopy indicate that GA binds to LYS to generate a static complex. The binding constants and thermodynamic parameters were calculated. MD simulation revealed that the main driving forces for GA binding to LYS are hydrogen bonding and hydrophobic interactions. The root-mean-square deviation verified that GA and LYS bind to form a stable complex, while the root-mean-square fluctuation results showed that the stability of the GA-LYS complex at 298 K was higher than that at 310 K. The calculated free binding energies from the molecular mechanics/Poisson-Boltzmann surface area method showed that van der Waals forces and electrostatic interactions are the predominant intermolecular forces. The MD simulation was consistent with the spectral experiments. This study provides a reference for future study of the pharmacological mechanism of GA.

Research on the infiltration processes of lawn soils of the Babao River in the Qilian Mountain.

PubMed

Li, GuangWen; Feng, Qi; Zhang, FuPing; Cheng, AiFang

2014-01-01

Using a Guelph Permeameter, the soil water infiltration processes were analyzed in the Babao River of the Qilian Mountain in China. The results showed that the average soil initial infiltration and the steady infiltration rates in the upstream reaches of the Babao River are 1.93 and 0.99 cm/min, whereas those of the middle area are 0.48 cm/min and 0.21 cm/min, respectively. The infiltration processes can be divided into three stages: the rapidly changing stage (0-10 min), the slowly changing stage (10-30 min) and the stabilization stage (after 30 min). We used field data collected from lawn soils and evaluated the performances of the infiltration models of Philip, Kostiakov and Horton with the sum of squared error, the root mean square error, the coefficient of determination, the mean error, the model efficiency and Willmott's index of agreement. The results indicated that the Kostiakov model was most suitable for studying the infiltration process in the alpine lawn soils.

Exploration of structural stability in deleterious nsSNPs of the XPA gene: A molecular dynamics approach

PubMed Central

NagaSundaram, N; Priya Doss, C George

2011-01-01

Background: Distinguishing the deleterious from the massive number of non-functional nsSNPs that occur within a single genome is a considerable challenge in mutation research. In this approach, we have used the existing in silico methods to explore the mutation-structure-function relationship in the XPAgene. Materials and Methods: We used the Sorting Intolerant From Tolerant (SIFT), Polymorphism Phenotyping (PolyPhen), I-Mutant 2.0, and the Protein Analysis THrough Evolutionary Relationships methods to predict the effects of deleterious nsSNPs on protein function and evaluated the impact of mutation on protein stability by Molecular Dynamics simulations. Results: By comparing the scores of all the four in silico methods, nsSNP with an ID rs104894131 at position C108F was predicted to be highly deleterious. We extended our Molecular dynamics approach to gain insight into the impact of this non-synonymous polymorphism on structural changes that may affect the activity of the XPAgene. Conclusion: Based on the in silico methods score, potential energy, root-mean-square deviation, and root-mean-square fluctuation, we predict that deleterious nsSNP at position C108F would play a significant role in causing disease by the XPA gene. Our approach would present the application of in silicotools in understanding the functional variation from the perspective of structure, evolution, and phenotype. PMID:22190868

Estimating patient-specific soft-tissue properties in a TKA knee.

PubMed

Ewing, Joseph A; Kaufman, Michelle K; Hutter, Erin E; Granger, Jeffrey F; Beal, Matthew D; Piazza, Stephen J; Siston, Robert A

2016-03-01

Surgical technique is one factor that has been identified as critical to success of total knee arthroplasty. Researchers have shown that computer simulations can aid in determining how decisions in the operating room generally affect post-operative outcomes. However, to use simulations to make clinically relevant predictions about knee forces and motions for a specific total knee patient, patient-specific models are needed. This study introduces a methodology for estimating knee soft-tissue properties of an individual total knee patient. A custom surgical navigation system and stability device were used to measure the force-displacement relationship of the knee. Soft-tissue properties were estimated using a parameter optimization that matched simulated tibiofemoral kinematics with experimental tibiofemoral kinematics. Simulations using optimized ligament properties had an average root mean square error of 3.5° across all tests while simulations using generic ligament properties taken from literature had an average root mean square error of 8.4°. Specimens showed large variability among ligament properties regardless of similarities in prosthetic component alignment and measured knee laxity. These results demonstrate the importance of soft-tissue properties in determining knee stability, and suggest that to make clinically relevant predictions of post-operative knee motions and forces using computer simulations, patient-specific soft-tissue properties are needed. © 2015 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Performance Metrics, Error Modeling, and Uncertainty Quantification

NASA Technical Reports Server (NTRS)

Tian, Yudong; Nearing, Grey S.; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Tang, Ling

2016-01-01

A common set of statistical metrics has been used to summarize the performance of models or measurements-­ the most widely used ones being bias, mean square error, and linear correlation coefficient. They assume linear, additive, Gaussian errors, and they are interdependent, incomplete, and incapable of directly quantifying un­certainty. The authors demonstrate that these metrics can be directly derived from the parameters of the simple linear error model. Since a correct error model captures the full error information, it is argued that the specification of a parametric error model should be an alternative to the metrics-based approach. The error-modeling meth­odology is applicable to both linear and nonlinear errors, while the metrics are only meaningful for linear errors. In addition, the error model expresses the error structure more naturally, and directly quantifies uncertainty. This argument is further explained by highlighting the intrinsic connections between the performance metrics, the error model, and the joint distribution between the data and the reference.

The Analysis and Construction of Perfectly Matched Layers for the Linearized Euler Equations

NASA Technical Reports Server (NTRS)

Hesthaven, J. S.

1997-01-01

We present a detailed analysis of a recently proposed perfectly matched layer (PML) method for the absorption of acoustic waves. The split set of equations is shown to be only weakly well-posed, and ill-posed under small low order perturbations. This analysis provides the explanation for the stability problems associated with the split field formulation and illustrates why applying a filter has a stabilizing effect. Utilizing recent results obtained within the context of electromagnetics, we develop strongly well-posed absorbing layers for the linearized Euler equations. The schemes are shown to be perfectly absorbing independent of frequency and angle of incidence of the wave in the case of a non-convecting mean flow. In the general case of a convecting mean flow, a number of techniques is combined to obtain a absorbing layers exhibiting PML-like behavior. The efficacy of the proposed absorbing layers is illustrated though computation of benchmark problems in aero-acoustics.

Modification of the USLE K factor for soil erodibility assessment on calcareous soils in Iran

NASA Astrophysics Data System (ADS)

Ostovari, Yaser; Ghorbani-Dashtaki, Shoja; Bahrami, Hossein-Ali; Naderi, Mehdi; Dematte, Jose Alexandre M.; Kerry, Ruth

2016-11-01

The measurement of soil erodibility (K) in the field is tedious, time-consuming and expensive; therefore, its prediction through pedotransfer functions (PTFs) could be far less costly and time-consuming. The aim of this study was to develop new PTFs to estimate the K factor using multiple linear regression, Mamdani fuzzy inference systems, and artificial neural networks. For this purpose, K was measured in 40 erosion plots with natural rainfall. Various soil properties including the soil particle size distribution, calcium carbonate equivalent, organic matter, permeability, and wet-aggregate stability were measured. The results showed that the mean measured K was 0.014 t h MJ- 1 mm- 1 and 2.08 times less than the estimated mean K (0.030 t h MJ- 1 mm- 1) using the USLE model. Permeability, wet-aggregate stability, very fine sand, and calcium carbonate were selected as independent variables by forward stepwise regression in order to assess the ability of multiple linear regression, Mamdani fuzzy inference systems and artificial neural networks to predict K. The calcium carbonate equivalent, which is not accounted for in the USLE model, had a significant impact on K in multiple linear regression due to its strong influence on the stability of aggregates and soil permeability. Statistical indices in validation and calibration datasets determined that the artificial neural networks method with the highest R2, lowest RMSE, and lowest ME was the best model for estimating the K factor. A strong correlation (R2 = 0.81, n = 40, p < 0.05) between the estimated K from multiple linear regression and measured K indicates that the use of calcium carbonate equivalent as a predictor variable gives a better estimation of K in areas with calcareous soils.

Post-processing through linear regression

NASA Astrophysics Data System (ADS)

van Schaeybroeck, B.; Vannitsem, S.

2011-03-01

Various post-processing techniques are compared for both deterministic and ensemble forecasts, all based on linear regression between forecast data and observations. In order to evaluate the quality of the regression methods, three criteria are proposed, related to the effective correction of forecast error, the optimal variability of the corrected forecast and multicollinearity. The regression schemes under consideration include the ordinary least-square (OLS) method, a new time-dependent Tikhonov regularization (TDTR) method, the total least-square method, a new geometric-mean regression (GM), a recently introduced error-in-variables (EVMOS) method and, finally, a "best member" OLS method. The advantages and drawbacks of each method are clarified. These techniques are applied in the context of the 63 Lorenz system, whose model version is affected by both initial condition and model errors. For short forecast lead times, the number and choice of predictors plays an important role. Contrarily to the other techniques, GM degrades when the number of predictors increases. At intermediate lead times, linear regression is unable to provide corrections to the forecast and can sometimes degrade the performance (GM and the best member OLS with noise). At long lead times the regression schemes (EVMOS, TDTR) which yield the correct variability and the largest correlation between ensemble error and spread, should be preferred.

On a stronger-than-best property for best prediction

NASA Astrophysics Data System (ADS)

Teunissen, P. J. G.

2008-03-01

The minimum mean squared error (MMSE) criterion is a popular criterion for devising best predictors. In case of linear predictors, it has the advantage that no further distributional assumptions need to be made, other then about the first- and second-order moments. In the spatial and Earth sciences, it is the best linear unbiased predictor (BLUP) that is used most often. Despite the fact that in this case only the first- and second-order moments need to be known, one often still makes statements about the complete distribution, in particular when statistical testing is involved. For such cases, one can do better than the BLUP, as shown in Teunissen (J Geod. doi: 10.1007/s00190-007-0140-6, 2006), and thus devise predictors that have a smaller MMSE than the BLUP. Hence, these predictors are to be preferred over the BLUP, if one really values the MMSE-criterion. In the present contribution, we will show, however, that the BLUP has another optimality property than the MMSE-property, provided that the distribution is Gaussian. It will be shown that in the Gaussian case, the prediction error of the BLUP has the highest possible probability of all linear unbiased predictors of being bounded in the weighted squared norm sense. This is a stronger property than the often advertised MMSE-property of the BLUP.

Tuning the control system of a nonlinear inverted pendulum by means of the new method of Lyapunov exponents estimation

NASA Astrophysics Data System (ADS)

Balcerzak, Marek; Dąbrowski, Artur; Pikunov, Danylo

2018-01-01

This paper presents a practical application of a new, simplified method of Lyapunov exponents estimation. The method has been applied to optimization of a real, nonlinear inverted pendulum system. Authors presented how the algorithm of the Largest Lyapunov Exponent (LLE) estimation can be applied to evaluate control systems performance. The new LLE-based control performance index has been proposed. Equations of the inverted pendulum system of the fourth order have been found. The nonlinear friction of the regulation object has been identified by means of the nonlinear least squares method. Three different friction models have been tested: linear, cubic and Coulomb model. The Differential Evolution (DE) algorithm has been used to search for the best set of parameters of the general linear regulator. This work proves that proposed method is efficient and results in faster perturbation rejection, especially when disturbances are significant.

Arrhenius time-scaled least squares: a simple, robust approach to accelerated stability data analysis for bioproducts.

PubMed

Rauk, Adam P; Guo, Kevin; Hu, Yanling; Cahya, Suntara; Weiss, William F

2014-08-01

Defining a suitable product presentation with an acceptable stability profile over its intended shelf-life is one of the principal challenges in bioproduct development. Accelerated stability studies are routinely used as a tool to better understand long-term stability. Data analysis often employs an overall mass action kinetics description for the degradation and the Arrhenius relationship to capture the temperature dependence of the observed rate constant. To improve predictive accuracy and precision, the current work proposes a least-squares estimation approach with a single nonlinear covariate and uses a polynomial to describe the change in a product attribute with respect to time. The approach, which will be referred to as Arrhenius time-scaled (ATS) least squares, enables accurate, precise predictions to be achieved for degradation profiles commonly encountered during bioproduct development. A Monte Carlo study is conducted to compare the proposed approach with the common method of least-squares estimation on the logarithmic form of the Arrhenius equation and nonlinear estimation of a first-order model. The ATS least squares method accommodates a range of degradation profiles, provides a simple and intuitive approach for data presentation, and can be implemented with ease. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

In-situ X-ray diffraction studies of the phase transformations and structural states of B2, R and B19′ phases in Ti{sub 49.5}Ni{sub 50.5} alloy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ostapenko, Marina G., E-mail: artifakt@ispms.tsc.ru; National Research Tomsk Polytechnic University, Tomsk, 634050; Meisner, Ludmila L., E-mail: llm@ispms.tsc.ru

2015-10-27

The martensitic transformation, Debye–Waller factor, mean-square atomic displacements and the coefficient of thermal expansion on cooling of the Ti{sub 49.5}Ni{sub 50.5} shape memory alloy were examined using in-situ X-ray diffraction. It was revealed B2→R (T{sub R} ≡ T = 273 ± 10 K) along with B2→B19’ (M{sub s} ≡ T = 273 ± 10 K) transitions occur. It was found that Debye–Waller factor and mean-square displacement of B2 phase undergo significant increase as functions of temperature when phase transition B2→R and B2→B19’ take place. The analysis of the thermal expansion coefficient of the B2 phase indicates that the value of a increasesmore » almost linearly while cooling.« less

Variable complexity online sequential extreme learning machine, with applications to streamflow prediction

NASA Astrophysics Data System (ADS)

Lima, Aranildo R.; Hsieh, William W.; Cannon, Alex J.

2017-12-01

In situations where new data arrive continually, online learning algorithms are computationally much less costly than batch learning ones in maintaining the model up-to-date. The extreme learning machine (ELM), a single hidden layer artificial neural network with random weights in the hidden layer, is solved by linear least squares, and has an online learning version, the online sequential ELM (OSELM). As more data become available during online learning, information on the longer time scale becomes available, so ideally the model complexity should be allowed to change, but the number of hidden nodes (HN) remains fixed in OSELM. A variable complexity VC-OSELM algorithm is proposed to dynamically add or remove HN in the OSELM, allowing the model complexity to vary automatically as online learning proceeds. The performance of VC-OSELM was compared with OSELM in daily streamflow predictions at two hydrological stations in British Columbia, Canada, with VC-OSELM significantly outperforming OSELM in mean absolute error, root mean squared error and Nash-Sutcliffe efficiency at both stations.

Combining forecast weights: Why and how?

NASA Astrophysics Data System (ADS)

Yin, Yip Chee; Kok-Haur, Ng; Hock-Eam, Lim

2012-09-01

This paper proposes a procedure called forecast weight averaging which is a specific combination of forecast weights obtained from different methods of constructing forecast weights for the purpose of improving the accuracy of pseudo out of sample forecasting. It is found that under certain specified conditions, forecast weight averaging can lower the mean squared forecast error obtained from model averaging. In addition, we show that in a linear and homoskedastic environment, this superior predictive ability of forecast weight averaging holds true irrespective whether the coefficients are tested by t statistic or z statistic provided the significant level is within the 10% range. By theoretical proofs and simulation study, we have shown that model averaging like, variance model averaging, simple model averaging and standard error model averaging, each produces mean squared forecast error larger than that of forecast weight averaging. Finally, this result also holds true marginally when applied to business and economic empirical data sets, Gross Domestic Product (GDP growth rate), Consumer Price Index (CPI) and Average Lending Rate (ALR) of Malaysia.

Computation and evaluation of features of surface electromyogram to identify the force of muscle contraction and muscle fatigue.

PubMed

Arjunan, Sridhar P; Kumar, Dinesh K; Naik, Ganesh

2014-01-01

The relationship between force of muscle contraction and muscle fatigue with six different features of surface electromyogram (sEMG) was determined by conducting experiments on thirty-five volunteers. The participants performed isometric contractions at 50%, 75%, and 100% of their maximum voluntary contraction (MVC). Six features were considered in this study: normalised spectral index (NSM5), median frequency, root mean square, waveform length, normalised root mean square (NRMS), and increase in synchronization (IIS) index. Analysis of variance (ANOVA) and linear regression analysis were performed to determine the significance of the feature with respect to the three factors: muscle force, muscle fatigue, and subject. The results show that IIS index of sEMG had the highest correlation with muscle fatigue and the relationship was statistically significant (P < 0.01), while NSM5 associated best with level of muscle contraction (%MVC) (P < 0.01). Both of these features were not affected by the intersubject variations (P > 0.05).

Computation and Evaluation of Features of Surface Electromyogram to Identify the Force of Muscle Contraction and Muscle Fatigue

PubMed Central

Arjunan, Sridhar P.; Kumar, Dinesh K.; Naik, Ganesh

2014-01-01

The relationship between force of muscle contraction and muscle fatigue with six different features of surface electromyogram (sEMG) was determined by conducting experiments on thirty-five volunteers. The participants performed isometric contractions at 50%, 75%, and 100% of their maximum voluntary contraction (MVC). Six features were considered in this study: normalised spectral index (NSM5), median frequency, root mean square, waveform length, normalised root mean square (NRMS), and increase in synchronization (IIS) index. Analysis of variance (ANOVA) and linear regression analysis were performed to determine the significance of the feature with respect to the three factors: muscle force, muscle fatigue, and subject. The results show that IIS index of sEMG had the highest correlation with muscle fatigue and the relationship was statistically significant (P < 0.01), while NSM5 associated best with level of muscle contraction (%MVC) (P < 0.01). Both of these features were not affected by the intersubject variations (P > 0.05). PMID:24995275

Robust design optimization using the price of robustness, robust least squares and regularization methods

NASA Astrophysics Data System (ADS)

Bukhari, Hassan J.

2017-12-01

In this paper a framework for robust optimization of mechanical design problems and process systems that have parametric uncertainty is presented using three different approaches. Robust optimization problems are formulated so that the optimal solution is robust which means it is minimally sensitive to any perturbations in parameters. The first method uses the price of robustness approach which assumes the uncertain parameters to be symmetric and bounded. The robustness for the design can be controlled by limiting the parameters that can perturb.The second method uses the robust least squares method to determine the optimal parameters when data itself is subjected to perturbations instead of the parameters. The last method manages uncertainty by restricting the perturbation on parameters to improve sensitivity similar to Tikhonov regularization. The methods are implemented on two sets of problems; one linear and the other non-linear. This methodology will be compared with a prior method using multiple Monte Carlo simulation runs which shows that the approach being presented in this paper results in better performance.

A Biomechanical Comparison of Three 1.5-mm Plate and Screw Configurations and a Single 2.0-mm Plate for Internal Fixation of a Mandibular Condylar Fracture

PubMed Central

Aquilina, Peter; Parr, William C.H.; Chamoli, Uphar; Wroe, Stephen; Clausen, Philip

2014-01-01

The most stable pattern of internal fixation for mandibular condyle fractures is an area of ongoing discussion. This study investigates the stability of three patterns of plate fixation using readily available, commercially pure titanium implants. Finite element models of a simulated mandibular condyle fracture were constructed. The completed models were heterogeneous in bone material properties, contained approximately 1.2 million elements and incorporated simulated jaw adducting musculature. Models were run assuming linear elasticity and isotropic material properties for bone. No human subjects were involved in this investigation. The stability of the simulated condylar fracture reduced with the different implant configurations, and the von Mises stresses of a 1.5-mm X-shaped plate, a 1.5-mm rectangular plate, and a 1.5-mm square plate (all Synthes (Synthes GmbH, Zuchwil, Switzerland) were compared. The 1.5-mm X plate was the most stable of the three 1.5-mm profile plate configurations examined and had comparable mechanical performance to a single 2.0-mm straight four-hole plate. This study does not support the use of rectangular or square plate patterns in the open reduction and internal fixation of mandibular condyle fractures. It does provide some support for the use of a 1.5-mm X plate to reduce condylar fractures in selected clinical cases. PMID:25136411

An optimal control approach to the design of moving flight simulators

NASA Technical Reports Server (NTRS)

Sivan, R.; Ish-Shalom, J.; Huang, J.-K.

1982-01-01

An abstract flight simulator design problem is formulated in the form of an optimal control problem, which is solved for the linear-quadratic-Gaussian special case using a mathematical model of the vestibular organs. The optimization criterion used is the mean-square difference between the physiological outputs of the vestibular organs of the pilot in the aircraft and the pilot in the simulator. The dynamical equations are linearized, and the output signal is modeled as a random process with rational power spectral density. The method described yields the optimal structure of the simulator's motion generator, or 'washout filter'. A two-degree-of-freedom flight simulator design, including single output simulations, is presented.

Optimal Estimation of Clock Values and Trends from Finite Data

NASA Technical Reports Server (NTRS)

Greenhall, Charles

2005-01-01

We show how to solve two problems of optimal linear estimation from a finite set of phase data. Clock noise is modeled as a stochastic process with stationary dth increments. The covariance properties of such a process are contained in the generalized autocovariance function (GACV). We set up two principles for optimal estimation: with the help of the GACV, these principles lead to a set of linear equations for the regression coefficients and some auxiliary parameters. The mean square errors of the estimators are easily calculated. The method can be used to check the results of other methods and to find good suboptimal estimators based on a small subset of the available data.

Equivalent Linearization Analysis of Geometrically Nonlinear Random Vibrations Using Commercial Finite Element Codes

NASA Technical Reports Server (NTRS)

Rizzi, Stephen A.; Muravyov, Alexander A.

2002-01-01

Two new equivalent linearization implementations for geometrically nonlinear random vibrations are presented. Both implementations are based upon a novel approach for evaluating the nonlinear stiffness within commercial finite element codes and are suitable for use with any finite element code having geometrically nonlinear static analysis capabilities. The formulation includes a traditional force-error minimization approach and a relatively new version of a potential energy-error minimization approach, which has been generalized for multiple degree-of-freedom systems. Results for a simply supported plate under random acoustic excitation are presented and comparisons of the displacement root-mean-square values and power spectral densities are made with results from a nonlinear time domain numerical simulation.

A variable-step-size robust delta modulator.

NASA Technical Reports Server (NTRS)

Song, C. L.; Garodnick, J.; Schilling, D. L.

1971-01-01

Description of an analytically obtained optimum adaptive delta modulator-demodulator configuration. The device utilizes two past samples to obtain a step size which minimizes the mean square error for a Markov-Gaussian source. The optimum system is compared, using computer simulations, with a linear delta modulator and an enhanced Abate delta modulator. In addition, the performance is compared to the rate distortion bound for a Markov source. It is shown that the optimum delta modulator is neither quantization nor slope-overload limited. The highly nonlinear equations obtained for the optimum transmitter and receiver are approximated by piecewise-linear equations in order to obtain system equations which can be transformed into hardware. The derivation of the experimental system is presented.

Forecasting currency circulation data of Bank Indonesia by using hybrid ARIMAX-ANN model

NASA Astrophysics Data System (ADS)

Prayoga, I. Gede Surya Adi; Suhartono, Rahayu, Santi Puteri

2017-05-01

The purpose of this study is to forecast currency inflow and outflow data of Bank Indonesia. Currency circulation in Indonesia is highly influenced by the presence of Eid al-Fitr. One way to forecast the data with Eid al-Fitr effect is using autoregressive integrated moving average with exogenous input (ARIMAX) model. However, ARIMAX is a linear model, which cannot handle nonlinear correlation structures of the data. In the field of forecasting, inaccurate predictions can be considered caused by the existence of nonlinear components that are uncaptured by the model. In this paper, we propose a hybrid model of ARIMAX and artificial neural networks (ANN) that can handle both linear and nonlinear correlation. This method was applied for 46 series of currency inflow and 46 series of currency outflow. The results showed that based on out-of-sample root mean squared error (RMSE), the hybrid models are up to10.26 and 10.65 percent better than ARIMAX for inflow and outflow series, respectively. It means that ANN performs well in modeling nonlinear correlation of the data and can increase the accuracy of linear model.

Experimental and numerical analysis of pre-compressed masonry walls in two-way-bending with second order effects

DOE Office of Scientific and Technical Information (OSTI.GOV)

Milani, Gabriele, E-mail: milani@stru.polimi.it; Olivito, Renato S.; Tralli, Antonio

2014-10-06

The buckling behavior of slender unreinforced masonry (URM) walls subjected to axial compression and out-of-plane lateral loads is investigated through a combined experimental and numerical homogenizedapproach. After a preliminary analysis performed on a unit cell meshed by means of elastic FEs and non-linear interfaces, macroscopic moment-curvature diagrams so obtained are implemented at a structural level, discretizing masonry by means of rigid triangular elements and non-linear interfaces. The non-linear incremental response of the structure is accounted for a specific quadratic programming routine. In parallel, a wide experimental campaign is conducted on walls in two way bending, with the double aim ofmore » both validating the numerical model and investigating the behavior of walls that may not be reduced to simple cantilevers or simply supported beams. Panels investigated are dry-joint in scale square walls simply supported at the base and on a vertical edge, exhibiting the classical Rondelet’s mechanism. The results obtained are compared with those provided by the numerical model.« less

Thermal Noise Limit in Frequency Stabilization of Lasers with Rigid Cavities

NASA Technical Reports Server (NTRS)

Numata, Kenji; Kemery, Amy; Camp, Jordan

2004-01-01

We evaluated thermal noise (Brownian motion) in a rigid reference cavity used for frequency stabilization of lasers, based on the mechanical loss of cavity materials and the numerical analysis of the mirror-spacer mechanics with t.he direct application of the fluctuation dissipation theorem. This noise sets a fundamental limit for the frequency stability achieved with a rigid frequency- reference cavity of order 1 Hz/square root Hz(0.01 Hz/square root Hz) at 10 mHz (100 Hz) at room temperature. This level coincides with the world-highest level stabilization results.

The drag and lift of different non-spherical particles from low to high Re

NASA Astrophysics Data System (ADS)

Sanjeevi, Sathish K. P.; Padding, Johan

2017-11-01

The present work investigates a simplified drag and lift model that can be used for different non-spherical particles. The flow around different non-spherical particles is studied using a multi-relaxation-time lattice Boltzmann method. We compute the mean drag coefficient CD , ϕ at different incident angles ϕ for a wide range of Reynolds numbers (Re). We show that the sine-squared drag law CD , ϕ =CD , ϕ =0° +(CD , ϕ =90° -CD , ϕ =0°) sin2 ϕ holds up to large Reynolds numbers Re = 2000 . The sine-squared dependence of CD occurs at Stokes flow (very low Re) due to linearity of the flow fields. We explore the physical origin behind the sine-squared law at high Re , and reveal that surprisingly, this does not occur due to linearity of flow fields. Instead, it occurs due to an interesting pattern of pressure distribution contributing to the drag, at higher Re , for different incident angles. Similarly, we find that the equivalent theoretical equation of lift coefficient CL can provide a decent approximation, even at high Re , for elongated particles. Such a drag and lift law valid at high Re is very much useful for Euler-Lagrangian fluidization simulations of the non-spherical particles. European Research Council (ERC) consolidator Grant scheme, Contract No. 615096 (NonSphereFlow).

Comparison of linear and square superposition hardening models for the surface nanoindentation of ion-irradiated materials

NASA Astrophysics Data System (ADS)

Xiao, Xiazi; Yu, Long

2018-05-01

Linear and square superposition hardening models are compared for the surface nanoindentation of ion-irradiated materials. Hardening mechanisms of both dislocations and defects within the plasticity affected region (PAR) are considered. Four sets of experimental data for ion-irradiated materials are adopted to compare with theoretical results of the two hardening models. It is indicated that both models describe experimental data equally well when the PAR is within the irradiated layer; whereas, when the PAR is beyond the irradiated region, the square superposition hardening model performs better. Therefore, the square superposition model is recommended to characterize the hardening behavior of ion-irradiated materials.

Stochastic stability properties of jump linear systems

NASA Technical Reports Server (NTRS)

Feng, Xiangbo; Loparo, Kenneth A.; Ji, Yuandong; Chizeck, Howard J.

1992-01-01

Jump linear systems are defined as a family of linear systems with randomly jumping parameters (usually governed by a Markov jump process) and are used to model systems subject to failures or changes in structure. The authors study stochastic stability properties in jump linear systems and the relationship among various moment and sample path stability properties. It is shown that all second moment stability properties are equivalent and are sufficient for almost sure sample path stability, and a testable necessary and sufficient condition for second moment stability is derived. The Lyapunov exponent method for the study of almost sure sample stability is discussed, and a theorem which characterizes the Lyapunov exponents of jump linear systems is presented.

Crossflow Stability and Transition Experiments in Swept-Wing Flow

NASA Technical Reports Server (NTRS)

Dagenhart, J. Ray; Saric, William S.

1999-01-01

An experimental examination of crossflow instability and transition on a 45deg swept wing was conducted in the Arizona State University Unsteady Wind Tunnel. The stationary-vortex pattern and transition location are visualized by using both sublimating chemical and liquid-crystal coatings. Extensive hot-wire measurements were obtained at several measurement stations across a single vortex track. The mean and travelling wave disturbances were measured simultaneously. Stationary crossflow disturbance profiles were determined by subtracting either a reference or a span-averaged velocity profile from the mean velocity data. Mean, stationary crossflow, and traveling wave velocity data were presented as local boundary layer profiles and contour plots across a single stationary crossflow vortex track. Disturbance mode profiles and growth rates were determined. The experimental data are compared with predictions from linear stability theory.

Applicational possibilities of linear and non-linear (polynomial) regression and analysis of variance. III. Stability determination of pharmaceutical preparations: stability of diclofenac-sodium in Diclofen injections.

PubMed

Arambasić, M B; Jatić-Slavković, D

2004-05-01

This paper presents the application of the regression analysis program and the program for comparing linear regressions (modified method for one-way, analysis of variance), writtens in BASIC program language, for instance, determination of content of Diclofenac-Sodium (active ingredient in DIKLOFEN injections, ampules á 75 mg/3 ml). Stability testing of Diclofenac-Sodium was done by isothermic method of accelerated aging at 4 different temperatures (30 degrees, 40 degrees, 50 degrees and 60 degrees C) as a function of time (4 different duration of treatment: (0-155, 0-145, 0-74 and 0-44 days). The decrease in stability (decrease in the mean value of the content of Diclofenac-Sodium (in %), at different temperatures as a function of time, is possible to describe by, linear dependance. According to the value for regression equation values, the times are assessed in which the content of Diclofenac-Sodium (in %) will decrease by 10%, of the initial value. The times are follows at 30 degrees C 761.02 days, at 40 degrees C 397.26 days, at 50 degrees C 201.96 days and at 60 degrees C 58.85 days. The estimated times (in days) in which the mean value for Diclofenac-Sodium content (in %) will by 10% of the initial values, as a junction of time, are most suitably described by 3rd order parabola. Based on the parameter values which describe the 3rd order parabola, the time was estimated in which Diclofenac-Sodium content mean value (in %) will fall by 10% of the initial one at average ambient temperatures of 20 degrees C and 25 degrees C. The times are: 1409.47 days (20 degrees C) and 1042.39 days (25 degrees C). Based on the value for Fischer's coefficien (F), the comparison of trenf of Diclofenac-Sodium content (in %) shows that, under the influence of different temperatures as a function of time, among them, depending on temperature value, there is: statistically very significant difference (P < .05) at 50 degrees C and lower toward 60 degrees C, i.e. statistically probably significant difference (P > 0.01) at 40 degrees C and lower towards 50 degrees C and there is no statistically significance difference (P > 0.05) at 30 degrees C towards 40 degrees C.

Stability and square integrability of derivatives of solutions of nonlinear fourth order differential equations with delay.

PubMed

Korkmaz, Erdal

2017-01-01

In this paper, we give sufficient conditions for the boundedness, uniform asymptotic stability and square integrability of the solutions to a certain fourth order non-autonomous differential equations with delay by using Lyapunov's second method. The results obtained essentially improve, include and complement the results in the literature.

Stability of phases of a square-well fluid within superposition approximation

NASA Astrophysics Data System (ADS)

Piasecki, Jarosław; Szymczak, Piotr; Kozak, John J.

2013-04-01

The analytic and numerical methods introduced previously to study the phase behavior of hard sphere fluids starting from the Yvon-Born-Green (YBG) equation under the Kirkwood superposition approximation (KSA) are adapted to the square-well fluid. We are able to show conclusively that the YBG equation under the KSA closure when applied to the square-well fluid: (i) predicts the existence of an absolute stability limit corresponding to freezing where undamped oscillations appear in the long-distance behavior of correlations, (ii) in accordance with earlier studies reveals the existence of a liquid-vapor transition by the appearance of a "near-critical region" where monotonically decaying correlations acquire very long range, although the system never loses stability.

Nonlinear aeroacoustic characterization of Helmholtz resonators with a local-linear neuro-fuzzy network model

NASA Astrophysics Data System (ADS)

Förner, K.; Polifke, W.

2017-10-01

The nonlinear acoustic behavior of Helmholtz resonators is characterized by a data-based reduced-order model, which is obtained by a combination of high-resolution CFD simulation and system identification. It is shown that even in the nonlinear regime, a linear model is capable of describing the reflection behavior at a particular amplitude with quantitative accuracy. This observation motivates to choose a local-linear model structure for this study, which consists of a network of parallel linear submodels. A so-called fuzzy-neuron layer distributes the input signal over the linear submodels, depending on the root mean square of the particle velocity at the resonator surface. The resulting model structure is referred to as an local-linear neuro-fuzzy network. System identification techniques are used to estimate the free parameters of this model from training data. The training data are generated by CFD simulations of the resonator, with persistent acoustic excitation over a wide range of frequencies and sound pressure levels. The estimated nonlinear, reduced-order models show good agreement with CFD and experimental data over a wide range of amplitudes for several test cases.

Orthogonal Regression: A Teaching Perspective

ERIC Educational Resources Information Center

Carr, James R.

2012-01-01

A well-known approach to linear least squares regression is that which involves minimizing the sum of squared orthogonal projections of data points onto the best fit line. This form of regression is known as orthogonal regression, and the linear model that it yields is known as the major axis. A similar method, reduced major axis regression, is…

On Least Squares Fitting Nonlinear Submodels.

ERIC Educational Resources Information Center

Bechtel, Gordon G.

Three simplifying conditions are given for obtaining least squares (LS) estimates for a nonlinear submodel of a linear model. If these are satisfied, and if the subset of nonlinear parameters may be LS fit to the corresponding LS estimates of the linear model, then one attains the desired LS estimates for the entire submodel. Two illustrative…

Dynamics of the stochastic low concentration trimolecular oscillatory chemical system with jumps

NASA Astrophysics Data System (ADS)

Wei, Yongchang; Yang, Qigui

2018-06-01

This paper is devoted to discern long time dynamics through the stochastic low concentration trimolecular oscillatory chemical system with jumps. By Lyapunov technique, this system is proved to have a unique global positive solution, and the asymptotic stability in mean square of such model is further established. Moreover, the existence of random attractor and Lyapunov exponents are obtained for the stochastic homeomorphism flow generated by the corresponding global positive solution. And some numerical simulations are given to illustrate the presented results.

Development of laser interferometric high-precision geometry monitor for JASMINE

NASA Astrophysics Data System (ADS)

Niwa, Yoshito; Arai, Koji; Ueda, Akitoshi; Sakagami, Masaaki; Gouda, Naoteru; Kobayashi, Yukiyasu; Yamada, Yoshiyuki; Yano, Taihei

2008-07-01

The telescope geometry of JASMINE should be stabilized and monitored with the accuracy of about 10 to 100 picometer or 10 to 100 picoradian in root-mean-square over about 10 hours. For this purpose, a high-precision interferometric laser metrology system is employed. One of useful techniques for measuring displacements in extremely minute scales is the heterodyne interferometrical method. Experiment for verification of multi degree of freedom measurement was performed and mirror motions were successfully monitored with three degree of freedom.

Linking topology of tethered polymer rings with applications to chromosome segregation and estimation of the knotting length.

PubMed

Marko, John F

2009-05-01

The Gauss linking number (Ca) of two flexible polymer rings which are tethered to one another is investigated. For ideal random walks, mean linking-squared varies with the square root of polymer length while for self-avoiding walks, linking-squared increases logarithmically with polymer length. The free-energy cost of linking of polymer rings is therefore strongly dependent on degree of self-avoidance, i.e., on intersegment excluded volume. Scaling arguments and numerical data are used to determine the free-energy cost of fixed linking number in both the fluctuation and large-Ca regimes; for ideal random walks, for |Ca|>N;{1/4} , the free energy of catenation is found to grow proportional, variant|Ca/N;{1/4}|;{4/3} . When excluded volume interactions between segments are present, the free energy rapidly approaches a linear dependence on Gauss linking (dF/dCa approximately 3.7k_{B}T) , suggestive of a novel "catenation condensation" effect. These results are used to show that condensation of long entangled polymers along their length, so as to increase excluded volume while decreasing number of statistical segments, can drive disentanglement if a mechanism is present to permit topology change. For chromosomal DNA molecules, lengthwise condensation is therefore an effective means to bias topoisomerases to eliminate catenations between replicated chromatids. The results for mean-square catenation are also used to provide a simple approximate estimate for the "knotting length," or number of segments required to have a knot along a single circular polymer, explaining why the knotting length ranges from approximately 300 for an ideal random walk to 10;{6} for a self-avoiding walk.

Effect of Surface Waviness on Transition in Three-Dimensional Boundary-Layer Flow

NASA Technical Reports Server (NTRS)

Masad, Jamal A.

1996-01-01

The effect of a surface wave on transition in three-dimensional boundary-layer flow over an infinite swept wing was studied. The mean flow computed using interacting boundary-layer theory, and transition was predicted using linear stability theory coupled with the empirical eN method. It was found that decreasing the wave height, sweep angle, or freestream unit Reynolds number, and increasing the freestream Mach number or suction level all stabilized the flow and moved transition onset to downstream locations.

Effects of shock on hypersonic boundary layer stability

NASA Astrophysics Data System (ADS)

Pinna, F.; Rambaud, P.

2013-06-01

The design of hypersonic vehicles requires the estimate of the laminar to turbulent transition location for an accurate sizing of the thermal protection system. Linear stability theory is a fast scientific way to study the problem. Recent improvements in computational capabilities allow computing the flow around a full vehicle instead of using only simplified boundary layer equations. In this paper, the effect of the shock is studied on a mean flow provided by steady Computational Fluid Dynamics (CFD) computations and simplified boundary layer calculations.

Image-based gradient non-linearity characterization to determine higher-order spherical harmonic coefficients for improved spatial position accuracy in magnetic resonance imaging.

PubMed

Weavers, Paul T; Tao, Shengzhen; Trzasko, Joshua D; Shu, Yunhong; Tryggestad, Erik J; Gunter, Jeffrey L; McGee, Kiaran P; Litwiller, Daniel V; Hwang, Ken-Pin; Bernstein, Matt A

2017-05-01

Spatial position accuracy in magnetic resonance imaging (MRI) is an important concern for a variety of applications, including radiation therapy planning, surgical planning, and longitudinal studies of morphologic changes to study neurodegenerative diseases. Spatial accuracy is strongly influenced by gradient linearity. This work presents a method for characterizing the gradient non-linearity fields on a per-system basis, and using this information to provide improved and higher-order (9th vs. 5th) spherical harmonic coefficients for better spatial accuracy in MRI. A large fiducial phantom containing 5229 water-filled spheres in a grid pattern is scanned with the MR system, and the positions all the fiducials are measured and compared to the corresponding ground truth fiducial positions as reported from a computed tomography (CT) scan of the object. Systematic errors from off-resonance (i.e., B0) effects are minimized with the use of increased receiver bandwidth (±125kHz) and two acquisitions with reversed readout gradient polarity. The spherical harmonic coefficients are estimated using an iterative process, and can be subsequently used to correct for gradient non-linearity. Test-retest stability was assessed with five repeated measurements on a single scanner, and cross-scanner variation on four different, identically-configured 3T wide-bore systems. A decrease in the root-mean-square error (RMSE) over a 50cm diameter spherical volume from 1.80mm to 0.77mm is reported here in the case of replacing the vendor's standard 5th order spherical harmonic coefficients with custom fitted 9th order coefficients, and from 1.5mm to 1mm by extending custom fitted 5th order correction to the 9th order. Minimum RMSE varied between scanners, but was stable with repeated measurements in the same scanner. The results suggest that the proposed methods may be used on a per-system basis to more accurately calibrate MR gradient non-linearity coefficients when compared to vendor standard corrections. Copyright © 2016 Elsevier Inc. All rights reserved.

Kinematic variability, fractal dynamics and local dynamic stability of treadmill walking

PubMed Central

2011-01-01

Background Motorized treadmills are widely used in research or in clinical therapy. Small kinematics, kinetics and energetics changes induced by Treadmill Walking (TW) as compared to Overground Walking (OW) have been reported in literature. The purpose of the present study was to characterize the differences between OW and TW in terms of stride-to-stride variability. Classical (Standard Deviation, SD) and non-linear (fractal dynamics, local dynamic stability) methods were used. In addition, the correlations between the different variability indexes were analyzed. Methods Twenty healthy subjects performed 10 min TW and OW in a random sequence. A triaxial accelerometer recorded trunk accelerations. Kinematic variability was computed as the average SD (MeanSD) of acceleration patterns among standardized strides. Fractal dynamics (scaling exponent α) was assessed by Detrended Fluctuation Analysis (DFA) of stride intervals. Short-term and long-term dynamic stability were estimated by computing the maximal Lyapunov exponents of acceleration signals. Results TW did not modify kinematic gait variability as compared to OW (multivariate T2, p = 0.87). Conversely, TW significantly modified fractal dynamics (t-test, p = 0.01), and both short and long term local dynamic stability (T2 p = 0.0002). No relationship was observed between variability indexes with the exception of significant negative correlation between MeanSD and dynamic stability in TW (3 × 6 canonical correlation, r = 0.94). Conclusions Treadmill induced a less correlated pattern in the stride intervals and increased gait stability, but did not modify kinematic variability in healthy subjects. This could be due to changes in perceptual information induced by treadmill walking that would affect locomotor control of the gait and hence specifically alter non-linear dependencies among consecutive strides. Consequently, the type of walking (i.e. treadmill or overground) is important to consider in each protocol design. PMID:21345241

Towards Stability Analysis of Jump Linear Systems with State-Dependent and Stochastic Switching

NASA Technical Reports Server (NTRS)

Tejada, Arturo; Gonzalez, Oscar R.; Gray, W. Steven

2004-01-01

This paper analyzes the stability of hierarchical jump linear systems where the supervisor is driven by a Markovian stochastic process and by the values of the supervised jump linear system s states. The stability framework for this class of systems is developed over infinite and finite time horizons. The framework is then used to derive sufficient stability conditions for a specific class of hybrid jump linear systems with performance supervision. New sufficient stochastic stability conditions for discrete-time jump linear systems are also presented.

Computing daily mean streamflow at ungaged locations in Iowa by using the Flow Anywhere and Flow Duration Curve Transfer statistical methods

USGS Publications Warehouse

Linhart, S. Mike; Nania, Jon F.; Sanders, Curtis L.; Archfield, Stacey A.

2012-01-01

The U.S. Geological Survey (USGS) maintains approximately 148 real-time streamgages in Iowa for which daily mean streamflow information is available, but daily mean streamflow data commonly are needed at locations where no streamgages are present. Therefore, the USGS conducted a study as part of a larger project in cooperation with the Iowa Department of Natural Resources to develop methods to estimate daily mean streamflow at locations in ungaged watersheds in Iowa by using two regression-based statistical methods. The regression equations for the statistical methods were developed from historical daily mean streamflow and basin characteristics from streamgages within the study area, which includes the entire State of Iowa and adjacent areas within a 50-mile buffer of Iowa in neighboring states. Results of this study can be used with other techniques to determine the best method for application in Iowa and can be used to produce a Web-based geographic information system tool to compute streamflow estimates automatically. The Flow Anywhere statistical method is a variation of the drainage-area-ratio method, which transfers same-day streamflow information from a reference streamgage to another location by using the daily mean streamflow at the reference streamgage and the drainage-area ratio of the two locations. The Flow Anywhere method modifies the drainage-area-ratio method in order to regionalize the equations for Iowa and determine the best reference streamgage from which to transfer same-day streamflow information to an ungaged location. Data used for the Flow Anywhere method were retrieved for 123 continuous-record streamgages located in Iowa and within a 50-mile buffer of Iowa. The final regression equations were computed by using either left-censored regression techniques with a low limit threshold set at 0.1 cubic feet per second (ft3/s) and the daily mean streamflow for the 15th day of every other month, or by using an ordinary-least-squares multiple linear regression method and the daily mean streamflow for the 15th day of every other month. The Flow Duration Curve Transfer method was used to estimate unregulated daily mean streamflow from the physical and climatic characteristics of gaged basins. For the Flow Duration Curve Transfer method, daily mean streamflow quantiles at the ungaged site were estimated with the parameter-based regression model, which results in a continuous daily flow-duration curve (the relation between exceedance probability and streamflow for each day of observed streamflow) at the ungaged site. By the use of a reference streamgage, the Flow Duration Curve Transfer is converted to a time series. Data used in the Flow Duration Curve Transfer method were retrieved for 113 continuous-record streamgages in Iowa and within a 50-mile buffer of Iowa. The final statewide regression equations for Iowa were computed by using a weighted-least-squares multiple linear regression method and were computed for the 0.01-, 0.05-, 0.10-, 0.15-, 0.20-, 0.30-, 0.40-, 0.50-, 0.60-, 0.70-, 0.80-, 0.85-, 0.90-, and 0.95-exceedance probability statistics determined from the daily mean streamflow with a reporting limit set at 0.1 ft3/s. The final statewide regression equation for Iowa computed by using left-censored regression techniques was computed for the 0.99-exceedance probability statistic determined from the daily mean streamflow with a low limit threshold and a reporting limit set at 0.1 ft3/s. For the Flow Anywhere method, results of the validation study conducted by using six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 1,016 to 138 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 1,690 to 237 ft3/s. Values of the percent root-mean-square error ranged from 115 percent to 26.2 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 13.0 to 5.3 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.80 to 0.40. Percent-bias values ranged from 25.4 to 4.0 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.35. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.86 to 0.56. For the streamgage with the best agreement between observed and estimated streamflow, higher streamflows appear to be underestimated. For the streamgage with the worst agreement between observed and estimated streamflow, low flows appear to be overestimated whereas higher flows seem to be underestimated. Estimated cumulative streamflows for the period October 1, 2004, to September 30, 2009, are underestimated by -25.8 and -7.4 percent for the closest and poorest comparisons, respectively. For the Flow Duration Curve Transfer method, results of the validation study conducted by using the same six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 437 to 93.9 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 906 to 169 ft3/s. Values of the percent root-mean-square-error ranged from 67.0 to 25.6 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 12.5 to 4.4 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.79 to 0.40. Percent-bias values ranged from 22.7 to 0.94 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.38. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.89 to 0.48. For the streamgage with the closest agreement between observed and estimated streamflow, there is relatively good agreement between observed and estimated streamflows. For the streamgage with the poorest agreement between observed and estimated streamflow, streamflows appear to be substantially underestimated for much of the time period. Estimated cumulative streamflow for the period October 1, 2004, to September 30, 2009, are underestimated by -9.3 and -22.7 percent for the closest and poorest comparisons, respectively.

Equilibrium Phase Behavior of the Square-Well Linear Microphase-Forming Model.

PubMed

Zhuang, Yuan; Charbonneau, Patrick

2016-07-07

We have recently developed a simulation approach to calculate the equilibrium phase diagram of particle-based microphase formers. Here, this approach is used to calculate the phase behavior of the square-well linear model for different strengths and ranges of the linear long-range repulsive component. The results are compared with various theoretical predictions for microphase formation. The analysis further allows us to better understand the mechanism for microphase formation in colloidal suspensions.

Aircraft Airframe Cost Estimation Using a Random Coefficients Model

DTIC Science & Technology

1979-12-01

approach will also be used here. 2 Model Formulation Several different types of equations could be used for the basic form of the CER, such as linear ...5) Marcotte developed several CER’s for fighter aircraft airframes using the log- linear model . A plot of the residuals from the CER for recurring...of the natural logarithm. Ordinary Least Squares The ordinary least squares procedure starts with the equation for the general linear model . The

Modelling thermal comfort of visitors at urban squares in hot and arid climate using NN-ARX soft computing method

NASA Astrophysics Data System (ADS)

Kariminia, Shahab; Motamedi, Shervin; Shamshirband, Shahaboddin; Piri, Jamshid; Mohammadi, Kasra; Hashim, Roslan; Roy, Chandrabhushan; Petković, Dalibor; Bonakdari, Hossein

2016-05-01

Visitors utilize the urban space based on their thermal perception and thermal environment. The thermal adaptation engages the user's behavioural, physiological and psychological aspects. These aspects play critical roles in user's ability to assess the thermal environments. Previous studies have rarely addressed the effects of identified factors such as gender, age and locality on outdoor thermal comfort, particularly in hot, dry climate. This study investigated the thermal comfort of visitors at two city squares in Iran based on their demographics as well as the role of thermal environment. Assessing the thermal comfort required taking physical measurement and questionnaire survey. In this study, a non-linear model known as the neural network autoregressive with exogenous input (NN-ARX) was employed. Five indices of physiological equivalent temperature (PET), predicted mean vote (PMV), standard effective temperature (SET), thermal sensation votes (TSVs) and mean radiant temperature ( T mrt) were trained and tested using the NN-ARX. Then, the results were compared to the artificial neural network (ANN) and the adaptive neuro-fuzzy inference system (ANFIS). The findings showed the superiority of the NN-ARX over the ANN and the ANFIS. For the NN-ARX model, the statistical indicators of the root mean square error (RMSE) and the mean absolute error (MAE) were 0.53 and 0.36 for the PET, 1.28 and 0.71 for the PMV, 2.59 and 1.99 for the SET, 0.29 and 0.08 for the TSV and finally 0.19 and 0.04 for the T mrt.

Analytical potential-density pairs for bars

NASA Astrophysics Data System (ADS)

Vogt, D.; Letelier, P. S.

2010-11-01

An identity that relates multipolar solutions of the Einstein equations to Newtonian potentials of bars with linear densities proportional to Legendre polynomials is used to construct analytical potential-density pairs of infinitesimally thin bars with a given linear density profile. By means of a suitable transformation, softened bars that are free of singularities are also obtained. As an application we study the equilibrium points and stability for the motion of test particles in the gravitational field for three models of rotating bars.

Protein stability and dynamics influenced by ligands in extremophilic complexes - a molecular dynamics investigation.

PubMed

Khan, Sara; Farooq, Umar; Kurnikova, Maria

2017-08-22

In this study, we explore the structural and dynamic adaptations of the Tryptophan synthase α-subunit in a ligand bound state in psychrophilic, mesophilic and hyperthermophilic organisms at different temperatures by MD simulations. We quantify the global and local fluctuations in the 40 ns time scale by analyzing the root mean square deviation/fluctuations. The distinct behavior of the active site and loop 6 is observed with the elevation of temperature. Protein stability relies more on electrostatic interactions, and these interactions might be responsible for the stability of varying temperature evolved proteins. The paper also focuses on the effect of temperature on protein dynamics and stability governed by the distinct behavior of the ligand associated with its retention, binding and dissociation over the course of time. The integration of principle component analysis and a free energy landscape was useful in identifying the conformational space accessible to ligand bound homologues and how the presence of the ligand alters the conformational and dynamic properties of the protein.

Masonry Columns Confined by Steel Fiber Composite Wraps

PubMed Central

Borri, Antonio; Castori, Giulio; Corradi, Marco

2011-01-01

The application of steel fiber reinforced polymer (SRP) as a means of increasing the capacity of masonry columns is investigated in this study. The behavior of 23 solid-brick specimens that are externally wrapped by SRP sheets in low volumetric ratios is presented. The specimens are subjected to axial monotonic load until failure occurs. Two widely used types of masonry columns of differing square cross-sections were tested in compression (square and octagonal cross-sections). It is concluded that SRP-confined masonry behaves very much like fiber reinforced polymers (FRP)-confined masonry. Confinement increases both the load-carrying capacity and the deformability of masonry almost linearly with average confining stress. A comparative analysis between experimental and theoretical values computed in compliance with the Italian Council of Research (CNR) was also developed. PMID:28879991

Masonry Columns Confined by Steel Fiber Composite Wraps.

PubMed

Borri, Antonio; Castori, Giulio; Corradi, Marco

2011-01-21

The application of steel fiber reinforced polymer (SRP) as a means of increasing the capacity of masonry columns is investigated in this study. The behavior of 23 solid-brick specimens that are externally wrapped by SRP sheets in low volumetric ratios is presented. The specimens are subjected to axial monotonic load until failure occurs. Two widely used types of masonry columns of differing square cross-sections were tested in compression (square and octagonal cross-sections). It is concluded that SRP-confined masonry behaves very much like fiber reinforced polymers (FRP)-confined masonry. Confinement increases both the load-carrying capacity and the deformability of masonry almost linearly with average confining stress. A comparative analysis between experimental and theoretical values computed in compliance with the Italian Council of Research (CNR) was also developed.

Systems identification using a modified Newton-Raphson method: A FORTRAN program

NASA Technical Reports Server (NTRS)

Taylor, L. W., Jr.; Iliff, K. W.

1972-01-01

A FORTRAN program is offered which computes a maximum likelihood estimate of the parameters of any linear, constant coefficient, state space model. For the case considered, the maximum likelihood estimate can be identical to that which minimizes simultaneously the weighted mean square difference between the computed and measured response of a system and the weighted square of the difference between the estimated and a priori parameter values. A modified Newton-Raphson or quasilinearization method is used to perform the minimization which typically requires several iterations. A starting technique is used which insures convergence for any initial values of the unknown parameters. The program and its operation are described in sufficient detail to enable the user to apply the program to his particular problem with a minimum of difficulty.

A channel estimation scheme for MIMO-OFDM systems

NASA Astrophysics Data System (ADS)

He, Chunlong; Tian, Chu; Li, Xingquan; Zhang, Ce; Zhang, Shiqi; Liu, Chaowen

2017-08-01

In view of the contradiction of the time-domain least squares (LS) channel estimation performance and the practical realization complexity, a reduced complexity channel estimation method for multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) based on pilot is obtained. This approach can transform the complexity of MIMO-OFDM channel estimation problem into a simple single input single output-orthogonal frequency division multiplexing (SISO-OFDM) channel estimation problem and therefore there is no need for large matrix pseudo-inverse, which greatly reduces the complexity of algorithms. Simulation results show that the bit error rate (BER) performance of the obtained method with time orthogonal training sequences and linear minimum mean square error (LMMSE) criteria is better than that of time-domain LS estimator and nearly optimal performance.

Magnitude and Temporal Variability of Inter-stimulus EEG Modulate the Linear Relationship Between Laser-Evoked Potentials and Fast-Pain Perception

PubMed Central

Li, Linling; Huang, Gan; Lin, Qianqian; Liu, Jia; Zhang, Shengli; Zhang, Zhiguo

2018-01-01

The level of pain perception is correlated with the magnitude of pain-evoked brain responses, such as laser-evoked potentials (LEP), across trials. The positive LEP-pain relationship lays the foundation for pain prediction based on single-trial LEP, but cross-individual pain prediction does not have a good performance because the LEP-pain relationship exhibits substantial cross-individual difference. In this study, we aim to explain the cross-individual difference in the LEP-pain relationship using inter-stimulus EEG (isEEG) features. The isEEG features (root mean square as magnitude and mean square successive difference as temporal variability) were estimated from isEEG data (at full band and five frequency bands) recorded between painful stimuli. A linear model was fitted to investigate the relationship between pain ratings and LEP response for fast-pain trials on a trial-by-trial basis. Then the correlation between isEEG features and the parameters of LEP-pain model (slope and intercept) was evaluated. We found that the magnitude and temporal variability of isEEG could modulate the parameters of an individual's linear LEP-pain model for fast-pain trials. Based on this, we further developed a new individualized fast-pain prediction scheme, which only used training individuals with similar isEEG features as the test individual to train the fast-pain prediction model, and obtained improved accuracy in cross-individual fast-pain prediction. The findings could help elucidate the neural mechanism of cross-individual difference in pain experience and the proposed fast-pain prediction scheme could be potentially used as a practical and feasible pain prediction method in clinical practice. PMID:29904336

A new approach to measure visual field progression in glaucoma patients using variational bayes linear regression.

PubMed

Murata, Hiroshi; Araie, Makoto; Asaoka, Ryo

2014-11-20

We generated a variational Bayes model to predict visual field (VF) progression in glaucoma patients. This retrospective study included VF series from 911 eyes of 547 glaucoma patients as test data, and VF series from 5049 eyes of 2858 glaucoma patients as training data. Using training data, variational Bayes linear regression (VBLR) was created to predict VF progression. The performance of VBLR was compared against ordinary least-squares linear regression (OLSLR) by predicting VFs in the test dataset. The total deviation (TD) values of test patients' 11th VFs were predicted using TD values from their second to 10th VFs (VF2-10), the root mean squared error (RMSE) associated with each approach then was calculated. Similarly, mean TD (mTD) of test patients' 11th VFs was predicted using VBLR and OLSLR, and the absolute prediction errors compared. The RMSE resulting from VBLR averaged 3.9 ± 2.1 (SD) and 4.9 ± 2.6 dB for prediction based on the second to 10th VFs (VF2-10) and the second to fourth VFs (VF2-4), respectively. The RMSE resulting from OLSLR was 4.1 ± 2.0 (VF2-10) and 19.9 ± 12.0 (VF2-4) dB. The absolute prediction error (SD) for mTD using VBLR was 1.2 ± 1.3 (VF2-10) and 1.9 ± 2.0 (VF2-4) dB, while the prediction error resulting from OLSLR was 1.2 ± 1.3 (VF2-10) and 6.2 ± 6.6 (VF2-4) dB. The VBLR more accurately predicts future VF progression in glaucoma patients compared to conventional OLSLR, especially in short VF series. © ARVO.

Daily Suspended Sediment Discharge Prediction Using Multiple Linear Regression and Artificial Neural Network

NASA Astrophysics Data System (ADS)

Uca; Toriman, Ekhwan; Jaafar, Othman; Maru, Rosmini; Arfan, Amal; Saleh Ahmar, Ansari

2018-01-01

Prediction of suspended sediment discharge in a catchments area is very important because it can be used to evaluation the erosion hazard, management of its water resources, water quality, hydrology project management (dams, reservoirs, and irrigation) and to determine the extent of the damage that occurred in the catchments. Multiple Linear Regression analysis and artificial neural network can be used to predict the amount of daily suspended sediment discharge. Regression analysis using the least square method, whereas artificial neural networks using Radial Basis Function (RBF) and feedforward multilayer perceptron with three learning algorithms namely Levenberg-Marquardt (LM), Scaled Conjugate Descent (SCD) and Broyden-Fletcher-Goldfarb-Shanno Quasi-Newton (BFGS). The number neuron of hidden layer is three to sixteen, while in output layer only one neuron because only one output target. The mean absolute error (MAE), root mean square error (RMSE), coefficient of determination (R2 ) and coefficient of efficiency (CE) of the multiple linear regression (MLRg) value Model 2 (6 input variable independent) has the lowest the value of MAE and RMSE (0.0000002 and 13.6039) and highest R2 and CE (0.9971 and 0.9971). When compared between LM, SCG and RBF, the BFGS model structure 3-7-1 is the better and more accurate to prediction suspended sediment discharge in Jenderam catchment. The performance value in testing process, MAE and RMSE (13.5769 and 17.9011) is smallest, meanwhile R2 and CE (0.9999 and 0.9998) is the highest if it compared with the another BFGS Quasi-Newton model (6-3-1, 9-10-1 and 12-12-1). Based on the performance statistics value, MLRg, LM, SCG, BFGS and RBF suitable and accurately for prediction by modeling the non-linear complex behavior of suspended sediment responses to rainfall, water depth and discharge. The comparison between artificial neural network (ANN) and MLRg, the MLRg Model 2 accurately for to prediction suspended sediment discharge (kg/day) in Jenderan catchment area.

Extension of suboptimal control theory for flow around a square cylinder

NASA Astrophysics Data System (ADS)

Fujita, Yosuke; Fukagata, Koji

2017-11-01

We extend the suboptimal control theory to control of flow around a square cylinder, which has no point symmetry on the impulse response from the wall in contrast to circular cylinders and spheres previously studied. The cost functions examined are the pressure drag (J1), the friction drag (J2), the squared difference between target pressure and wall pressure (J3) and the time-averaged dissipation (J4). The control input is assumed to be continuous blowing and suction on the cylinder wall and the feedback sensors are assumued on the entire wall surface. The control law is derived so as to minimize the cost function under the constraint of linearized Navier-Stokes equation, and the impulse response field to be convolved with the instantaneous flow quanties are numerically obtained. The amplitide of control input is fixed so that the maximum blowing/suction velocity is 40% of the freestream velocity. When J2 is used as the cost function, the friction drag is reduced as expected but the mean drag is found to increase. In constast, when J1, J3, and J4 were used, the mean drag was found to decrease by 21%, 12%, and 22%, respectively; in addition, vortex shedding is suppressed, which leads to reduction of lift fluctuations.

Hyperspectral analysis of soil organic matter in coal mining regions using wavelets, correlations, and partial least squares regression.

PubMed

Lin, Lixin; Wang, Yunjia; Teng, Jiyao; Wang, Xuchen

2016-02-01

Hyperspectral estimation of soil organic matter (SOM) in coal mining regions is an important tool for enhancing fertilization in soil restoration programs. The correlation--partial least squares regression (PLSR) method effectively solves the information loss problem of correlation--multiple linear stepwise regression, but results of the correlation analysis must be optimized to improve precision. This study considers the relationship between spectral reflectance and SOM based on spectral reflectance curves of soil samples collected from coal mining regions. Based on the major absorption troughs in the 400-1006 nm spectral range, PLSR analysis was performed using 289 independent bands of the second derivative (SDR) with three levels and measured SOM values. A wavelet-correlation-PLSR (W-C-PLSR) model was then constructed. By amplifying useful information that was previously obscured by noise, the W-C-PLSR model was optimal for estimating SOM content, with smaller prediction errors in both calibration (R(2) = 0.970, root mean square error (RMSEC) = 3.10, and mean relative error (MREC) = 8.75) and validation (RMSEV = 5.85 and MREV = 14.32) analyses, as compared with other models. Results indicate that W-C-PLSR has great potential to estimate SOM in coal mining regions.

On the Conditioning of Machine-Learning-Assisted Turbulence Modeling

NASA Astrophysics Data System (ADS)

Wu, Jinlong; Sun, Rui; Wang, Qiqi; Xiao, Heng

2017-11-01

Recently, several researchers have demonstrated that machine learning techniques can be used to improve the RANS modeled Reynolds stress by training on available database of high fidelity simulations. However, obtaining improved mean velocity field remains an unsolved challenge, restricting the predictive capability of current machine-learning-assisted turbulence modeling approaches. In this work we define a condition number to evaluate the model conditioning of data-driven turbulence modeling approaches, and propose a stability-oriented machine learning framework to model Reynolds stress. Two canonical flows, the flow in a square duct and the flow over periodic hills, are investigated to demonstrate the predictive capability of the proposed framework. The satisfactory prediction performance of mean velocity field for both flows demonstrates the predictive capability of the proposed framework for machine-learning-assisted turbulence modeling. With showing the capability of improving the prediction of mean flow field, the proposed stability-oriented machine learning framework bridges the gap between the existing machine-learning-assisted turbulence modeling approaches and the demand of predictive capability of turbulence models in real applications.

A simplified diagnostic model of orographic rainfall for enhancing satellite-based rainfall estimates in data-poor regions

USGS Publications Warehouse

Funk, Christopher C.; Michaelsen, Joel C.

2004-01-01

An extension of Sinclair's diagnostic model of orographic precipitation (“VDEL”) is developed for use in data-poor regions to enhance rainfall estimates. This extension (VDELB) combines a 2D linearized internal gravity wave calculation with the dot product of the terrain gradient and surface wind to approximate terrain-induced vertical velocity profiles. Slope, wind speed, and stability determine the velocity profile, with either sinusoidal or vertically decaying (evanescent) solutions possible. These velocity profiles replace the parameterized functions in the original VDEL, creating VDELB, a diagnostic accounting for buoyancy effects. A further extension (VDELB*) uses an on/off constraint derived from reanalysis precipitation fields. A validation study over 365 days in the Pacific Northwest suggests that VDELB* can best capture seasonal and geographic variations. A new statistical data-fusion technique is presented and is used to combine VDELB*, reanalysis, and satellite rainfall estimates in southern Africa. The technique, matched filter regression (MFR), sets the variance of the predictors equal to their squared correlation with observed gauge data and predicts rainfall based on the first principal component of the combined data. In the test presented here, mean absolute errors from the MFR technique were 35% lower than the satellite estimates alone. VDELB assumes a linear solution to the wave equations and a Boussinesq atmosphere, and it may give unrealistic responses under extreme conditions. Nonetheless, the results presented here suggest that diagnostic models, driven by reanalysis data, can be used to improve satellite rainfall estimates in data-sparse regions.

A sensor fusion method for tracking vertical velocity and height based on inertial and barometric altimeter measurements.

PubMed

Sabatini, Angelo Maria; Genovese, Vincenzo

2014-07-24

A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04-0.24 m/s; height RMSE was in the range 5-68 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions.

Understanding Least Squares through Monte Carlo Calculations

ERIC Educational Resources Information Center

Tellinghuisen, Joel

2005-01-01

The method of least squares (LS) is considered as an important data analysis tool available to physical scientists. The mathematics of linear least squares(LLS) is summarized in a very compact matrix rotation that renders it practically "formulaic".

Determining a one-tailed upper limit for future sample relative reproducibility standard deviations.

PubMed

McClure, Foster D; Lee, Jung K

2006-01-01

A formula was developed to determine a one-tailed 100p% upper limit for future sample percent relative reproducibility standard deviations (RSD(R),%= 100s(R)/y), where S(R) is the sample reproducibility standard deviation, which is the square root of a linear combination of the sample repeatability variance (s(r)2) plus the sample laboratory-to-laboratory variance (s(L)2), i.e., S(R) = s(L)2, and y is the sample mean. The future RSD(R),% is expected to arise from a population of potential RSD(R),% values whose true mean is zeta(R),% = 100sigmaR, where sigmaR and mu are the population reproducibility standard deviation and mean, respectively.

Spectrophotometric determination of ternary mixtures of thiamin, riboflavin and pyridoxal in pharmaceutical and human plasma by least-squares support vector machines.

PubMed

Niazi, Ali; Zolgharnein, Javad; Afiuni-Zadeh, Somaie

2007-11-01

Ternary mixtures of thiamin, riboflavin and pyridoxal have been simultaneously determined in synthetic and real samples by applications of spectrophotometric and least-squares support vector machines. The calibration graphs were linear in the ranges of 1.0 - 20.0, 1.0 - 10.0 and 1.0 - 20.0 microg ml(-1) with detection limits of 0.6, 0.5 and 0.7 microg ml(-1) for thiamin, riboflavin and pyridoxal, respectively. The experimental calibration matrix was designed with 21 mixtures of these chemicals. The concentrations were varied between calibration graph concentrations of vitamins. The simultaneous determination of these vitamin mixtures by using spectrophotometric methods is a difficult problem, due to spectral interferences. The partial least squares (PLS) modeling and least-squares support vector machines were used for the multivariate calibration of the spectrophotometric data. An excellent model was built using LS-SVM, with low prediction errors and superior performance in relation to PLS. The root mean square errors of prediction (RMSEP) for thiamin, riboflavin and pyridoxal with PLS and LS-SVM were 0.6926, 0.3755, 0.4322 and 0.0421, 0.0318, 0.0457, respectively. The proposed method was satisfactorily applied to the rapid simultaneous determination of thiamin, riboflavin and pyridoxal in commercial pharmaceutical preparations and human plasma samples.

An analytical method to calculate equivalent fields to irregular symmetric and asymmetric photon fields.

PubMed

Tahmasebi Birgani, Mohamad J; Chegeni, Nahid; Zabihzadeh, Mansoor; Hamzian, Nima

2014-01-01

Equivalent field is frequently used for central axis depth-dose calculations of rectangular- and irregular-shaped photon beams. As most of the proposed models to calculate the equivalent square field are dosimetry based, a simple physical-based method to calculate the equivalent square field size was used as the basis of this study. The table of the sides of the equivalent square or rectangular fields was constructed and then compared with the well-known tables by BJR and Venselaar, et al. with the average relative error percentage of 2.5 ± 2.5% and 1.5 ± 1.5%, respectively. To evaluate the accuracy of this method, the percentage depth doses (PDDs) were measured for some special irregular symmetric and asymmetric treatment fields and their equivalent squares for Siemens Primus Plus linear accelerator for both energies, 6 and 18MV. The mean relative differences of PDDs measurement for these fields and their equivalent square was approximately 1% or less. As a result, this method can be employed to calculate equivalent field not only for rectangular fields but also for any irregular symmetric or asymmetric field. © 2013 American Association of Medical Dosimetrists Published by American Association of Medical Dosimetrists All rights reserved.

Weibull Modulus Estimated by the Non-linear Least Squares Method: A Solution to Deviation Occurring in Traditional Weibull Estimation

NASA Astrophysics Data System (ADS)

Li, T.; Griffiths, W. D.; Chen, J.

2017-11-01

The Maximum Likelihood method and the Linear Least Squares (LLS) method have been widely used to estimate Weibull parameters for reliability of brittle and metal materials. In the last 30 years, many researchers focused on the bias of Weibull modulus estimation, and some improvements have been achieved, especially in the case of the LLS method. However, there is a shortcoming in these methods for a specific type of data, where the lower tail deviates dramatically from the well-known linear fit in a classic LLS Weibull analysis. This deviation can be commonly found from the measured properties of materials, and previous applications of the LLS method on this kind of dataset present an unreliable linear regression. This deviation was previously thought to be due to physical flaws ( i.e., defects) contained in materials. However, this paper demonstrates that this deviation can also be caused by the linear transformation of the Weibull function, occurring in the traditional LLS method. Accordingly, it may not be appropriate to carry out a Weibull analysis according to the linearized Weibull function, and the Non-linear Least Squares method (Non-LS) is instead recommended for the Weibull modulus estimation of casting properties.

Stability of hypersonic compression cones

NASA Astrophysics Data System (ADS)

Reed, Helen; Kuehl, Joseph; Perez, Eduardo; Kocian, Travis; Oliviero, Nicholas

2012-11-01

Our activities focus on the identification and understanding of the second-mode instability for representative configurations in hypersonic flight. These include the Langley 93-10 flared cone and the Purdue compression cone, both at 0 degrees angle of attack at Mach 6. Through application of nonlinear parabolized stability equations (NPSE) and linear parabolized stability equations (PSE) to both geometries, it is concluded that mean-flow distortion tends to amplify frequencies less than the peak frequency and stabilize those greater by modifying the boundary-layer thickness. As initial disturbance amplitude is increased and/or a broad spectrum disturbance is introduced, direct numerical simulations (DNS) or NPSE appear to be the proper choices to model the evolution, and relative evolution, because these computational tools include these nonlinear effects (mean-flow distortion). Support from AFOSR/NASA National Center for Hypersonic Research in Laminar-Turbulent Transition through Grant FA9550-09-1-0341 is gratefully acknowledged. The authors also thank Pointwise, AeroSoft, and Texas Advanced Computing Center (TACC).

Finding reproducible cluster partitions for the k-means algorithm

PubMed Central

2013-01-01

K-means clustering is widely used for exploratory data analysis. While its dependence on initialisation is well-known, it is common practice to assume that the partition with lowest sum-of-squares (SSQ) total i.e. within cluster variance, is both reproducible under repeated initialisations and also the closest that k-means can provide to true structure, when applied to synthetic data. We show that this is generally the case for small numbers of clusters, but for values of k that are still of theoretical and practical interest, similar values of SSQ can correspond to markedly different cluster partitions. This paper extends stability measures previously presented in the context of finding optimal values of cluster number, into a component of a 2-d map of the local minima found by the k-means algorithm, from which not only can values of k be identified for further analysis but, more importantly, it is made clear whether the best SSQ is a suitable solution or whether obtaining a consistently good partition requires further application of the stability index. The proposed method is illustrated by application to five synthetic datasets replicating a real world breast cancer dataset with varying data density, and a large bioinformatics dataset. PMID:23369085

Finding reproducible cluster partitions for the k-means algorithm.

PubMed

Lisboa, Paulo J G; Etchells, Terence A; Jarman, Ian H; Chambers, Simon J

2013-01-01

K-means clustering is widely used for exploratory data analysis. While its dependence on initialisation is well-known, it is common practice to assume that the partition with lowest sum-of-squares (SSQ) total i.e. within cluster variance, is both reproducible under repeated initialisations and also the closest that k-means can provide to true structure, when applied to synthetic data. We show that this is generally the case for small numbers of clusters, but for values of k that are still of theoretical and practical interest, similar values of SSQ can correspond to markedly different cluster partitions. This paper extends stability measures previously presented in the context of finding optimal values of cluster number, into a component of a 2-d map of the local minima found by the k-means algorithm, from which not only can values of k be identified for further analysis but, more importantly, it is made clear whether the best SSQ is a suitable solution or whether obtaining a consistently good partition requires further application of the stability index. The proposed method is illustrated by application to five synthetic datasets replicating a real world breast cancer dataset with varying data density, and a large bioinformatics dataset.

Electronic Structure and Bonding in Transition Metal Inorganic and Organometallic Complexes: New Basis Sets, Linear Semibridging Carbonyls and Thiocarbonyls, and Oxidative Addition of Molecular Hydrogen to Square - Iridium Complexes.

NASA Astrophysics Data System (ADS)

Sargent, Andrew Landman

Approximate molecular orbital and ab initio quantum chemical techniques are used to investigate the electronic structure, bonding and reactivity of several transition metal inorganic and organometallic complexes. Modest-sized basis sets are developed for the second-row transition metal atoms and are designed for use in geometry optimizations of inorganic and organometallic complexes incorporating these atoms. The basis sets produce optimized equilibrium geometries which are slightly better than those produced with standard 3-21G basis sets, and which are significantly better than those produced with effective core potential basis sets. Linear semibridging carbonyl ligands in heterobimetallic complexes which contain a coordinatively unsaturated late transition metal center are found to accept electron density from, rather than donate electron density to, these centers. Only when the secondary metal center is a coordinatively unsaturated early transition metal center does the semibridging ligand donate electron density to this center. Large holes in the d shell around the metal center are more prominent and prevalent in early than in late transition metal centers, and the importance of filling in these holes outweighs the importance of mitigating the charge imbalance due to the dative metal-metal interaction. Semibridging thiocarbonyl ligands are more effective donors of electron density than the carbonyl ligands since the occupied donor orbitals of pi symmetry are higher in energy. The stereoselectivity of H_2 addition to d^8 square-planar transition metal complexes is controlled by the interactions between the ligands in the plane of addition and the concentrations of electronic charge around the metal center as the complex evolves from a four-coordinate to a six-coordinate species. Electron -withdrawing ligands help stabilize the five-coordinate species while strong electron donor ligands contribute only to the destabilizing repulsive interactions. The relative thermodynamic stabilities of the final complexes can be predicted based on the relative orientations of the strongest sigma-donor ligands.

On the Stability of Periodic Mercury-type Rotations

NASA Astrophysics Data System (ADS)

Churkina, Tatyana E.; Stepanov, Sergey Y.

2017-12-01

We consider the stability of planar periodic Mercury-type rotations of a rigid body around its center of mass in an elliptical orbit in a central Newtonian field of forces. Mercurytype rotations mean that the body makes 3 turns around its center of mass during 2 revolutions of the center of mass in its orbit (resonance 3:2). These rotations can be 1) symmetrical 2π- periodic, 2) symmetrical 4π-periodic and 3) asymmetrical 4π-periodic. The stability of rotations of type 1) was investigated by A.P.Markeev. In our paper we present a nonlinear stability analysis for some rotations of types 2) and 3) in 3rd- and 4th-order resonant cases, in the nonresonant case and at the boundaries of regions of linear stability.

Nonempirical calculations of the structure and stability of ALi/sub 2k/ lithium clusters of group-two elements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klimenko, N.M.; Musaev, D.G.; Gorbik, A.A.

Nonempirical Hartree-Fock calculations of the geometric and relative energetic characteristics of linear ALi/sub 2/ molecules and square ALi/sub 4/ molecules, where A = Be, Mg, Ca, and Zn, have been performed. The results for BeLi/sup +/, BeLi/sup 2/, BeLi/sub 4/, and MgLi/sub 2/ have been refined with consideration of the electron correlation in the framework of the theory of self-consistent electron pairs (SCEP). It has been shown that the stability of ALi/sub 2k/ increases with increasing size of the cluster and that the energy of the singlet-triplet transitions does not exceed 0.5-1.5 eV in all cases. The interactions between themore » atoms in the clusters have a cooperative character: the overlapping Q(Li-Li) between the Li atoms is no less significant than the overlapping Q(A-Li) between the Li atoms and the central atom A.« less

Adjustment of Adaptive Gain with Bounded Linear Stability Analysis to Improve Time-Delay Margin for Metrics-Driven Adaptive Control

NASA Technical Reports Server (NTRS)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje Srinvas

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a linear damaged twin-engine generic transport model of aircraft. The analysis shows that the system with the adjusted adaptive gain becomes more robust to unmodeled dynamics or time delay.

Analyzing Multilevel Data: Comparing Findings from Hierarchical Linear Modeling and Ordinary Least Squares Regression

ERIC Educational Resources Information Center

Rocconi, Louis M.

2013-01-01

This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student…

Lorentz symmetry violation and UHECR experiments

NASA Astrophysics Data System (ADS)

Gonzalez-Mestres, L.

2001-08-01

Lorentz symmetry violation (LSV) at Planck scale can be tested through ultra-high energy cosmic rays (UHECR). We discuss deformed Lorentz symmetry (DLS) and energy non-conservation (ENC) patterns where the effective LSV parameter varies like the square of the momentum scale (e.g. quadratically de-formed relativistic kinematics, QDRK). In such patterns, a ≈ 106 LSV at Planck scale would be enough to produce observable effects on the properties of cosmic rays at the ≈ 1020 eV scale: absence of GZK cutoff, stability of unstable particles, lower interaction rates, kinematical failure of any parton model and of standard formulae for Lorentz contraction and time dilation... Its phenomeno-logical implications are compatible with existing data. Precise signatures are discussed in several patterns. If the effective LSV or ENC parameter is taken to vary linearly with the momentum scale (e.g. linearly deformed relativistic kinematics, LDRK), contradictions seem to arise with UHECR data. Conse-quences are important for UHECR and high-energy gamma-ray exper iments, as well as for high-energy cosmic rays and gravitational waves.

Linear Least Squares for Correlated Data

NASA Technical Reports Server (NTRS)

Dean, Edwin B.

1988-01-01

Throughout the literature authors have consistently discussed the suspicion that regression results were less than satisfactory when the independent variables were correlated. Camm, Gulledge, and Womer, and Womer and Marcotte provide excellent applied examples of these concerns. Many authors have obtained partial solutions for this problem as discussed by Womer and Marcotte and Wonnacott and Wonnacott, which result in generalized least squares algorithms to solve restrictive cases. This paper presents a simple but relatively general multivariate method for obtaining linear least squares coefficients which are free of the statistical distortion created by correlated independent variables.

Impact of dietary fiber and physical form on performance of lactating dairy cows.

PubMed

Woodford, J A; Jorgensen, N A; Barrington, G P

1986-04-01

Two trials were conducted to study the effects of forage intake and physical form on lactating cow performance. In trial 1, four cows in a 4 X 4 Latin square were fed long alfalfa hay at 28, 36, 45, and 53% of total dry matter plus concentrate. Total dry matter intake was not affected by forage percent. Total chewing time and milk fat percentage increased linearly with increasing forage consumption. Maximum 4% fat-corrected milk production occurred when diets contained 27% neutral detergent fiber and 18% acid detergent fiber. In trial 2, four cows in a 4 X 4 Latin square were fed diets of chopped alfalfa hay and concentrate in proportions to supply 27.4% total ration neutral detergent fiber. Mean particle length measured with an oscillating screen particle separator of the chopped hay was .26, .46, .64, and .90 cm. Total dry matter and forage dry matter intakes and total chewing were not influenced by forage mean particle length. Mean particle length did not affect actual milk or 4% fat-corrected milk production. Depression of milk fat percentage was prevented when forage mean particle length was greater than or equal .64 cm. Apparent digestibility of dietary constituents and rate of passage of hay and concentrate was not influenced by forage intake or physical form.

Global Mittag-Leffler stability analysis of fractional-order impulsive neural networks with one-side Lipschitz condition.

PubMed

Zhang, Xinxin; Niu, Peifeng; Ma, Yunpeng; Wei, Yanqiao; Li, Guoqiang

2017-10-01

This paper is concerned with the stability analysis issue of fractional-order impulsive neural networks. Under the one-side Lipschitz condition or the linear growth condition of activation function, the existence of solution is analyzed respectively. In addition, the existence, uniqueness and global Mittag-Leffler stability of equilibrium point of the fractional-order impulsive neural networks with one-side Lipschitz condition are investigated by the means of contraction mapping principle and Lyapunov direct method. Finally, an example with numerical simulation is given to illustrate the validity and feasibility of the proposed results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Numerical Technique for Analyzing Rotating Rake Mode Measurements in a Duct With Passive Treatment and Shear Flow

NASA Technical Reports Server (NTRS)

Dahl, Milo D.; Sutliff, Daniel L.

2007-01-01

A technique is presented for the analysis of measured data obtained from a rotating microphone rake system. The system is designed to measure the interaction modes of ducted fans. A Fourier analysis of the data from the rotating system results in a set of circumferential mode levels at each radial location of a microphone inside the duct. Radial basis functions are then least-squares fit to this data to obtain the radial mode amplitudes. For ducts with soft walls and mean flow, the radial basis functions must be numerically computed. The linear companion matrix method is used to obtain both the eigenvalues of interest, without an initial guess, and the radial basis functions. The governing equations allow for the mean flow to have a boundary layer at the wall. In addition, a nonlinear least-squares method is used to adjust the wall impedance to best fit the data in an attempt to use the rotating system as an in-duct wall impedance measurement tool. Simulated and measured data are used to show the effects of wall impedance and mean flow on the computed results.

Performance tests of a single-cylinder compression-ignition engine with a displacer piston

NASA Technical Reports Server (NTRS)

Moore, C S; Foster, H H

1935-01-01

Engine performance was investigated using a rectangular displacer on the piston crown to cause a forced air flow in a vertical-disk combustion chamber of a single-cylinder, 4-stroke-cycle compression-ignition engine. The optimum air-flow area was determined first with the area concentrated at one end of the displacer and then with the area equally divided between two passages, one at each end of the displacer. Best performance was obtained with the two-passage air flow arranged to give a calculated maximum air-flow speed of 8 times the linear crank-pin speed. With the same fuel-spray formation as used without the air flow, the maximum clear exhaust brake mean effective pressure at 1,500 r.p.m. was increased from 90 to 115 pounds per square inch and the corresponding fuel consumption reduced from 0.46 to 0.43 pound per brake horsepower-hour. At 1,200 r.p.m., a maximum clear exhaust brake mean effective pressure of 120 pounds per square inch was obtained at a fuel consumption of 0.42 pound per brake horsepower-hour. At higher specific fuel consumption the brake mean effective pressure was still increasing rapidly.

[Influence of autoclave sterilization on dimensional stability and detail reproduction of 5 additional silicone impression materials].

PubMed

Xu, Tong-kai; Sun, Zhi-hui; Jiang, Yong

2012-03-01

To evaluate the dimensional stability and detail reproduction of five additional silicone impression materials after autoclave sterilization. Impressions were made on the ISO 4823 standard mold containing several marking lines, in five kinds of additional silicone. All the impressions were sterilized by high temperature and pressure (135 °C, 212.8 kPa) for 25 min. Linear measurements of pre-sterilization and post-sterilization were made with a measuring microscope. Statistical analysis utilized single-factor analysis with pair-wise comparison of mean values when appropriate. Hypothesis testing was conducted at alpha = 0.05. No significant difference was found between the pre-sterilization and post-sterilization conditions for all locations, and all the absolute valuse of linear rate of change less than 8%. All the sterilization by the autoclave did not affect the surfuce detail reproduction of the 5 impression materials. The dimensional stability and detail reproduction of the five additional silicone impression materials in the study was unaffected by autoclave sterilization.

Linear and nonlinear ARMA model parameter estimation using an artificial neural network

NASA Technical Reports Server (NTRS)

Chon, K. H.; Cohen, R. J.

1997-01-01

This paper addresses parametric system identification of linear and nonlinear dynamic systems by analysis of the input and output signals. Specifically, we investigate the relationship between estimation of the system using a feedforward neural network model and estimation of the system by use of linear and nonlinear autoregressive moving-average (ARMA) models. By utilizing a neural network model incorporating a polynomial activation function, we show the equivalence of the artificial neural network to the linear and nonlinear ARMA models. We compare the parameterization of the estimated system using the neural network and ARMA approaches by utilizing data generated by means of computer simulations. Specifically, we show that the parameters of a simulated ARMA system can be obtained from the neural network analysis of the simulated data or by conventional least squares ARMA analysis. The feasibility of applying neural networks with polynomial activation functions to the analysis of experimental data is explored by application to measurements of heart rate (HR) and instantaneous lung volume (ILV) fluctuations.

Linear Mechanisms and Pressure Fluctuations in Wall Turbulence

NASA Astrophysics Data System (ADS)

Septham, Kamthon; Morrison, Jonathan

2014-11-01

Full-domain, linear feedback control of turbulent channel flow at Reτ <= 400 via vU' at low wavenumbers is an effective method to attenuate turbulent channel flow such that it is relaminarised. The passivity-based control approach is adopted and explained by the conservative characteristics of the nonlinear terms contributing to the Reynolds-Orr equation (Sharma et al .Phys .Fluids 2011). The linear forcing acts on the wall-normal velocity field and thus the pressure field via the linear (rapid) source term of the Poisson equation for pressure fluctuations, 2U'∂v/∂x . The minimum required spanwise wavelength resolution without losing control is constant at λz+ = 125, based on the wall friction velocity at t = 0 . The result shows that the maximum forcing is located at y+ ~ 20 , corresponding to the location of the maximum in the mean-square pressure gradient. The effectiveness of linear control is qualitatively explained by Landahl's theory for timescales, in that the control proceeds via the shear interaction timescale which is much shorter than both the nonlinear and viscous timescales. The response of the rapid (linear) and slow (nonlinear) pressure fluctuations to the linear control is examined and discussed.

46 CFR 178.340 - Stability standards for pontoon vessels on protected waters.

Code of Federal Regulations, 2011 CFR

2011-10-01

... = 2.0 feet (0.61 meters); Mw = Wind heeling moment in foot-pounds (kilogram-meters) P = Wind pressure of 7.5 pounds/square foot (36.6 kilograms/square meter); A = Area, in square feet (square meters), of the projected lateral surface of the vessel above the waterline (including each projected area of the...

46 CFR 178.340 - Stability standards for pontoon vessels on protected waters.

Code of Federal Regulations, 2014 CFR

2014-10-01

... = 2.0 feet (0.61 meters); Mw = Wind heeling moment in foot-pounds (kilogram-meters) P = Wind pressure of 7.5 pounds/square foot (36.6 kilograms/square meter); A = Area, in square feet (square meters), of the projected lateral surface of the vessel above the waterline (including each projected area of the...

46 CFR 178.340 - Stability standards for pontoon vessels on protected waters.

Code of Federal Regulations, 2012 CFR

2012-10-01

... = 2.0 feet (0.61 meters); Mw = Wind heeling moment in foot-pounds (kilogram-meters) P = Wind pressure of 7.5 pounds/square foot (36.6 kilograms/square meter); A = Area, in square feet (square meters), of the projected lateral surface of the vessel above the waterline (including each projected area of the...

46 CFR 178.340 - Stability standards for pontoon vessels on protected waters.

Code of Federal Regulations, 2013 CFR

2013-10-01

... = 2.0 feet (0.61 meters); Mw = Wind heeling moment in foot-pounds (kilogram-meters) P = Wind pressure of 7.5 pounds/square foot (36.6 kilograms/square meter); A = Area, in square feet (square meters), of the projected lateral surface of the vessel above the waterline (including each projected area of the...

Optimization of the geometrical stability in square ring laser gyroscopes

NASA Astrophysics Data System (ADS)

Santagata, R.; Beghi, A.; Belfi, J.; Beverini, N.; Cuccato, D.; Di Virgilio, A.; Ortolan, A.; Porzio, A.; Solimeno, S.

2015-03-01

Ultra-sensitive ring laser gyroscopes are regarded as potential detectors of the general relativistic frame-dragging effect due to the rotation of the Earth. Our project for this goal is called GINGER (gyroscopes in general relativity), and consists of a ground-based triaxial array of ring lasers aimed at measuring the rotation rate of the Earth with an accuracy of {{10}-14} rad {{s}-1}. Such an ambitious goal is now within reach, as large-area ring lasers are very close to the required sensitivity and stability. However, demanding constraints on the geometrical stability of the optical path of the laser inside the ring cavity are required. Thus, we have begun a detailed study of the geometry of an optical cavity in order to find a control strategy for its geometry that could meet the specifications of the GINGER project. As the cavity perimeter has a stationary point for the square configuration, we identify a set of transformations on the mirror positions that allows us to adjust the laser beam steering to the shape of a square. We show that the geometrical stability of a square cavity strongly increases by implementing a suitable system to measure the mirror distances, and that the geometry stabilization can be achieved by measuring the absolute lengths of the two diagonals and the perimeter of the ring.

A comparison of methods for estimating the random effects distribution of a linear mixed model.

PubMed

Ghidey, Wendimagegn; Lesaffre, Emmanuel; Verbeke, Geert

2010-12-01

This article reviews various recently suggested approaches to estimate the random effects distribution in a linear mixed model, i.e. (1) the smoothing by roughening approach of Shen and Louis,(1) (2) the semi-non-parametric approach of Zhang and Davidian,(2) (3) the heterogeneity model of Verbeke and Lesaffre( 3) and (4) a flexible approach of Ghidey et al. (4) These four approaches are compared via an extensive simulation study. We conclude that for the considered cases, the approach of Ghidey et al. (4) often shows to have the smallest integrated mean squared error for estimating the random effects distribution. An analysis of a longitudinal dental data set illustrates the performance of the methods in a practical example.

Guaranteed estimation of solutions to Helmholtz transmission problems with uncertain data from their indirect noisy observations

NASA Astrophysics Data System (ADS)

Podlipenko, Yu. K.; Shestopalov, Yu. V.

2017-09-01

We investigate the guaranteed estimation problem of linear functionals from solutions to transmission problems for the Helmholtz equation with inexact data. The right-hand sides of equations entering the statements of transmission problems and the statistical characteristics of observation errors are supposed to be unknown and belonging to certain sets. It is shown that the optimal linear mean square estimates of the above mentioned functionals and estimation errors are expressed via solutions to the systems of transmission problems of the special type. The results and techniques can be applied in the analysis and estimation of solution to forward and inverse electromagnetic and acoustic problems with uncertain data that arise in mathematical models of the wave diffraction on transparent bodies.

Dynamic stability analysis of torsional vibrations of a shaft system connected by a Hooke's joint through a continuous system model

NASA Astrophysics Data System (ADS)

Bulut, Gökhan

2014-08-01

Stability of parametrically excited torsional vibrations of a shaft system composed of two torsionally elastic shafts interconnected through a Hooke's joint is studied. The shafts are considered to be continuous (distributed-parameter) systems and an approximate discrete model for the torsional vibrations of the shaft system is derived via a finite element scheme. The stability of the solutions of the linearized equations of motion, consisting of a set of Mathieu-Hill type equations, is examined by means of a monodromy matrix method and the results are presented in the form of a Strutt-Ince diagram visualizing the effects of the system parameters on the stability of the shaft system.

Performance of statistical models to predict mental health and substance abuse cost.

PubMed

Montez-Rath, Maria; Christiansen, Cindy L; Ettner, Susan L; Loveland, Susan; Rosen, Amy K

2006-10-26

Providers use risk-adjustment systems to help manage healthcare costs. Typically, ordinary least squares (OLS) models on either untransformed or log-transformed cost are used. We examine the predictive ability of several statistical models, demonstrate how model choice depends on the goal for the predictive model, and examine whether building models on samples of the data affects model choice. Our sample consisted of 525,620 Veterans Health Administration patients with mental health (MH) or substance abuse (SA) diagnoses who incurred costs during fiscal year 1999. We tested two models on a transformation of cost: a Log Normal model and a Square-root Normal model, and three generalized linear models on untransformed cost, defined by distributional assumption and link function: Normal with identity link (OLS); Gamma with log link; and Gamma with square-root link. Risk-adjusters included age, sex, and 12 MH/SA categories. To determine the best model among the entire dataset, predictive ability was evaluated using root mean square error (RMSE), mean absolute prediction error (MAPE), and predictive ratios of predicted to observed cost (PR) among deciles of predicted cost, by comparing point estimates and 95% bias-corrected bootstrap confidence intervals. To study the effect of analyzing a random sample of the population on model choice, we re-computed these statistics using random samples beginning with 5,000 patients and ending with the entire sample. The Square-root Normal model had the lowest estimates of the RMSE and MAPE, with bootstrap confidence intervals that were always lower than those for the other models. The Gamma with square-root link was best as measured by the PRs. The choice of best model could vary if smaller samples were used and the Gamma with square-root link model had convergence problems with small samples. Models with square-root transformation or link fit the data best. This function (whether used as transformation or as a link) seems to help deal with the high comorbidity of this population by introducing a form of interaction. The Gamma distribution helps with the long tail of the distribution. However, the Normal distribution is suitable if the correct transformation of the outcome is used.

Crossflow Stability and Transition Experiments in a Swept-Wing Flow. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Dagenhart, John Ray

1992-01-01

An experimental examination of crossflow instability and transition on a 45 degree swept wing is conducted in the Arizona State University Unsteady Wind Tunnel. The stationary-vortex pattern and transition location are visualized using both sublimating-chemical and liquid-crystal coatings. Extensive hot-wire measurements are conducted at several measurement stations across a single vortex track. The mean and travelling-wave disturbances are measured simultaneously. Stationary-crossflow disturbance profiles are determined by subtracting either a reference or a span-averaged velocity profile from the mean-velocity data. Mean, stationary-crossflow, and travelling-wave velocity data are presented as local boundary-layer profiles and as contour plots across a single stationary-crossflow vortex track. Disturbance-mode profiles and growth rates are determined. The experimental data are compared to predictions from linear stability theory.

Robustness Analysis and Optimally Robust Control Design via Sum-of-Squares

NASA Technical Reports Server (NTRS)

Dorobantu, Andrei; Crespo, Luis G.; Seiler, Peter J.

2012-01-01

A control analysis and design framework is proposed for systems subject to parametric uncertainty. The underlying strategies are based on sum-of-squares (SOS) polynomial analysis and nonlinear optimization to design an optimally robust controller. The approach determines a maximum uncertainty range for which the closed-loop system satisfies a set of stability and performance requirements. These requirements, de ned as inequality constraints on several metrics, are restricted to polynomial functions of the uncertainty. To quantify robustness, SOS analysis is used to prove that the closed-loop system complies with the requirements for a given uncertainty range. The maximum uncertainty range, calculated by assessing a sequence of increasingly larger ranges, serves as a robustness metric for the closed-loop system. To optimize the control design, nonlinear optimization is used to enlarge the maximum uncertainty range by tuning the controller gains. Hence, the resulting controller is optimally robust to parametric uncertainty. This approach balances the robustness margins corresponding to each requirement in order to maximize the aggregate system robustness. The proposed framework is applied to a simple linear short-period aircraft model with uncertain aerodynamic coefficients.

Development of CFRP mirrors for space telescopes

NASA Astrophysics Data System (ADS)

Utsunomiya, Shin; Kamiya, Tomohiro; Shimizu, Ryuzo

2013-09-01

CFRP (Caron fiber reinforced plastics) have superior properties of high specific elasticity and low thermal expansion for satellite telescope structures. However, difficulties to achieve required surface accuracy and to ensure stability in orbit have discouraged CFRP application as main mirrors. We have developed ultra-light weight and high precision CFRP mirrors of sandwich structures composed of CFRP skins and CFRP cores using a replica technique. Shape accuracy of the demonstrated mirrors of 150 mm in diameter was 0.8 μm RMS (Root Mean Square) and surface roughness was 5 nm RMS as fabricated. Further optimization of fabrication process conditions to improve surface accuracy was studied using flat sandwich panels. Then surface accuracy of the flat CFRP sandwich panels of 150 mm square was improved to flatness of 0.2 μm RMS with surface roughness of 6 nm RMS. The surface accuracy vs. size of trial models indicated high possibility of fabrication of over 1m size mirrors with surface accuracy of 1μm. Feasibility of CFRP mirrors for low temperature applications was examined for JASMINE project as an example. Stability of surface accuracy of CFRP mirrors against temperature and moisture was discussed.

Multivariate Quantification of the Solid State Phase Composition of Co-Amorphous Naproxen-Indomethacin.

PubMed

Beyer, Andreas; Grohganz, Holger; Löbmann, Korbinian; Rades, Thomas; Leopold, Claudia S

2015-10-27

To benefit from the optimized dissolution properties of active pharmaceutical ingredients in their amorphous forms, co-amorphisation as a viable tool to stabilize these amorphous phases is of both academic and industrial interest. Reports dealing with the physical stability and recrystallization behavior of co-amorphous systems are however limited to qualitative evaluations based on the corresponding X-ray powder diffractograms. Therefore, the objective of the study was to develop a quantification model based on X-ray powder diffractometry (XRPD), followed by a multivariate partial least squares regression approach that enables the simultaneous determination of up to four solid state fractions: crystalline naproxen, γ-indomethacin, α-indomethacin as well as co-amorphous naproxen-indomethacin. For this purpose, a calibration set that covers the whole range of possible combinations of the four components was prepared and analyzed by XRPD. In order to test the model performances, leave-one-out cross validation was performed and revealed root mean square errors of validation between 3.11% and 3.45% for the crystalline molar fractions and 5.57% for the co-amorphous molar fraction. In summary, even four solid state phases, involving one co-amorphous phase, can be quantified with this XRPD data-based approach.

Predicting Stability Constants for Uranyl Complexes Using Density Functional Theory

DOE PAGES

Vukovic, Sinisa; Hay, Benjamin P.; Bryantsev, Vyacheslav S.

2015-04-02

The ability to predict the equilibrium constants for the formation of 1:1 uranyl:ligand complexes (log K 1 values) provides the essential foundation for the rational design of ligands with enhanced uranyl affinity and selectivity. We also use density functional theory (B3LYP) and the IEFPCM continuum solvation model to compute aqueous stability constants for UO 2 2+ complexes with 18 donor ligands. Theoretical calculations permit reasonably good estimates of relative binding strengths, while the absolute log K 1 values are significantly overestimated. Accurate predictions of the absolute log K 1 values (root mean square deviation from experiment < 1.0 for logmore » K 1 values ranging from 0 to 16.8) can be obtained by fitting the experimental data for two groups of mono and divalent negative oxygen donor ligands. The utility of correlations is demonstrated for amidoxime and imide dioxime ligands, providing a useful means of screening for new ligands with strong chelate capability to uranyl.« less

Preprocessing Inconsistent Linear System for a Meaningful Least Squares Solution

NASA Technical Reports Server (NTRS)

Sen, Syamal K.; Shaykhian, Gholam Ali

2011-01-01

Mathematical models of many physical/statistical problems are systems of linear equations. Due to measurement and possible human errors/mistakes in modeling/data, as well as due to certain assumptions to reduce complexity, inconsistency (contradiction) is injected into the model, viz. the linear system. While any inconsistent system irrespective of the degree of inconsistency has always a least-squares solution, one needs to check whether an equation is too much inconsistent or, equivalently too much contradictory. Such an equation will affect/distort the least-squares solution to such an extent that renders it unacceptable/unfit to be used in a real-world application. We propose an algorithm which (i) prunes numerically redundant linear equations from the system as these do not add any new information to the model, (ii) detects contradictory linear equations along with their degree of contradiction (inconsistency index), (iii) removes those equations presumed to be too contradictory, and then (iv) obtain the minimum norm least-squares solution of the acceptably inconsistent reduced linear system. The algorithm presented in Matlab reduces the computational and storage complexities and also improves the accuracy of the solution. It also provides the necessary warning about the existence of too much contradiction in the model. In addition, we suggest a thorough relook into the mathematical modeling to determine the reason why unacceptable contradiction has occurred thus prompting us to make necessary corrections/modifications to the models - both mathematical and, if necessary, physical.

Preprocessing in Matlab Inconsistent Linear System for a Meaningful Least Squares Solution

NASA Technical Reports Server (NTRS)

Sen, Symal K.; Shaykhian, Gholam Ali

2011-01-01

Mathematical models of many physical/statistical problems are systems of linear equations Due to measurement and possible human errors/mistakes in modeling/data, as well as due to certain assumptions to reduce complexity, inconsistency (contradiction) is injected into the model, viz. the linear system. While any inconsistent system irrespective of the degree of inconsistency has always a least-squares solution, one needs to check whether an equation is too much inconsistent or, equivalently too much contradictory. Such an equation will affect/distort the least-squares solution to such an extent that renders it unacceptable/unfit to be used in a real-world application. We propose an algorithm which (i) prunes numerically redundant linear equations from the system as these do not add any new information to the model, (ii) detects contradictory linear equations along with their degree of contradiction (inconsistency index), (iii) removes those equations presumed to be too contradictory, and then (iv) obtain the . minimum norm least-squares solution of the acceptably inconsistent reduced linear system. The algorithm presented in Matlab reduces the computational and storage complexities and also improves the accuracy of the solution. It also provides the necessary warning about the existence of too much contradiction in the model. In addition, we suggest a thorough relook into the mathematical modeling to determine the reason why unacceptable contradiction has occurred thus prompting us to make necessary corrections/modifications to the models - both mathematical and, if necessary, physical.

Continuous monitoring of sonomyography, electromyography and torque generated by normal upper arm muscles during isometric contraction: sonomyography assessment for arm muscles.

PubMed

Shi, Jun; Zheng, Yong-Ping; Huang, Qing-Hua; Chen, Xin

2008-03-01

The aim of this study is to demonstrate the feasibility of using the continuous signals about the thickness and pennation angle changes of muscles detected in real-time from ultrasound images, named as sonomyography (SMG), to characterize muscles under isometric contraction, along with synchronized surface electromyography (EMG) and generated torque signals. The right biceps brachii muscles of seven normal young adult subjects were tested. We observed that exponential functions could well represent the relationships between the normalized EMG root-mean-square (RMS) and the torque, the RMS and the muscle deformation SMG, and the RMS and the pennation angle SMG for the data of the contraction phase, with exponent coefficients of 0.0341 +/- 0.0148 (Mean SD), 0.0619 +/- 0.0273, and 0.0266 +/- 0.0076, respectively. In addition, the preliminary results also demonstrated linear relationships between the normalized torque and the muscle deformation as well as the pennation angle with the ratios of 9 .79 +/- 3.01 and 2.02 +/- 0.53, respectively. The overall mean R2 for the regressions was approximately 0.9 and the overall mean relative root mean square error (RRMSE) smaller than 15%. The potential values of SMG together with EMG to provide a more comprehensive assessment for the muscle functions should be further investigated with more subjects and more muscle groups.

Estimation of parameters in rational reaction rates of molecular biological systems via weighted least squares

NASA Astrophysics Data System (ADS)

Wu, Fang-Xiang; Mu, Lei; Shi, Zhong-Ke

2010-01-01

The models of gene regulatory networks are often derived from statistical thermodynamics principle or Michaelis-Menten kinetics equation. As a result, the models contain rational reaction rates which are nonlinear in both parameters and states. It is challenging to estimate parameters nonlinear in a model although there have been many traditional nonlinear parameter estimation methods such as Gauss-Newton iteration method and its variants. In this article, we develop a two-step method to estimate the parameters in rational reaction rates of gene regulatory networks via weighted linear least squares. This method takes the special structure of rational reaction rates into consideration. That is, in the rational reaction rates, the numerator and the denominator are linear in parameters. By designing a special weight matrix for the linear least squares, parameters in the numerator and the denominator can be estimated by solving two linear least squares problems. The main advantage of the developed method is that it can produce the analytical solutions to the estimation of parameters in rational reaction rates which originally is nonlinear parameter estimation problem. The developed method is applied to a couple of gene regulatory networks. The simulation results show the superior performance over Gauss-Newton method.

Global long-term ozone trends derived from different observed and modelled data sets

NASA Astrophysics Data System (ADS)

Coldewey-Egbers, M.; Loyola, D.; Zimmer, W.; van Roozendael, M.; Lerot, C.; Dameris, M.; Garny, H.; Braesicke, P.; Koukouli, M.; Balis, D.

2012-04-01

The long-term behaviour of stratospheric ozone amounts during the past three decades is investigated on a global scale using different observed and modelled data sets. Three European satellite sensors GOME/ERS-2, SCIAMACHY/ENVISAT, and GOME-2/METOP are combined and a merged global monthly mean total ozone product has been prepared using an inter-satellite calibration approach. The data set covers the 16-years period from June 1995 to June 2011 and it exhibits an excellent long-term stability, which is required for such trend studies. A multiple linear least-squares regression algorithm using different explanatory variables is applied to the time series and statistically significant positive trends are detected in the northern mid latitudes and subtropics. Global trends are also estimated using a second satellite-based Merged Ozone Data set (MOD) provided by NASA. For few selected geographical regions ozone trends are additionally calculated using well-maintained measurements of individual Dobson/Brewer ground-based instruments. A reasonable agreement in the spatial patterns of the trends is found amongst the European satellite, the NASA satellite, and the ground-based observations. Furthermore, two long-term simulations obtained with the Chemistry-Climate Models E39C-A provided by German Aerospace Center and UMUKCA-UCAM provided by University of Cambridge are analysed.

Decentralization, stabilization, and estimation of large-scale linear systems

NASA Technical Reports Server (NTRS)

Siljak, D. D.; Vukcevic, M. B.

1976-01-01

In this short paper we consider three closely related aspects of large-scale systems: decentralization, stabilization, and estimation. A method is proposed to decompose a large linear system into a number of interconnected subsystems with decentralized (scalar) inputs or outputs. The procedure is preliminary to the hierarchic stabilization and estimation of linear systems and is performed on the subsystem level. A multilevel control scheme based upon the decomposition-aggregation method is developed for stabilization of input-decentralized linear systems Local linear feedback controllers are used to stabilize each decoupled subsystem, while global linear feedback controllers are utilized to minimize the coupling effect among the subsystems. Systems stabilized by the method have a tolerance to a wide class of nonlinearities in subsystem coupling and high reliability with respect to structural perturbations. The proposed output-decentralization and stabilization schemes can be used directly to construct asymptotic state estimators for large linear systems on the subsystem level. The problem of dimensionality is resolved by constructing a number of low-order estimators, thus avoiding a design of a single estimator for the overall system.

Quantification of endocrine disruptors and pesticides in water by gas chromatography-tandem mass spectrometry. Method validation using weighted linear regression schemes.

PubMed

Mansilha, C; Melo, A; Rebelo, H; Ferreira, I M P L V O; Pinho, O; Domingues, V; Pinho, C; Gameiro, P

2010-10-22

A multi-residue methodology based on a solid phase extraction followed by gas chromatography-tandem mass spectrometry was developed for trace analysis of 32 compounds in water matrices, including estrogens and several pesticides from different chemical families, some of them with endocrine disrupting properties. Matrix standard calibration solutions were prepared by adding known amounts of the analytes to a residue-free sample to compensate matrix-induced chromatographic response enhancement observed for certain pesticides. Validation was done mainly according to the International Conference on Harmonisation recommendations, as well as some European and American validation guidelines with specifications for pesticides analysis and/or GC-MS methodology. As the assumption of homoscedasticity was not met for analytical data, weighted least squares linear regression procedure was applied as a simple and effective way to counteract the greater influence of the greater concentrations on the fitted regression line, improving accuracy at the lower end of the calibration curve. The method was considered validated for 31 compounds after consistent evaluation of the key analytical parameters: specificity, linearity, limit of detection and quantification, range, precision, accuracy, extraction efficiency, stability and robustness. Copyright © 2010 Elsevier B.V. All rights reserved.

Application of Near Infrared Spectroscopy Coupled with Fluidized Bed Enrichment and Chemometrics to Detect Low Concentration of β-Naphthalenesulfonic Acid.

PubMed

Li, Wei; Zhang, Xuan; Zheng, Kaiyi; Du, Yiping; Cap, Peng; Sui, Tao; Geng, Jinpei

2015-01-01

A fluidized bed enrichment technique was developed to improve sensitivity of near infrared (NIR) spectroscopy with features of rapidness and large volume solution. D301 resin was used as an adsorption material to preconcentrate β-naphthalenesulfonic acid in solutions in a concentration range of 2.0-100.0 μg/mL, and NIR spectra were measured directly relative to the β-naphthalenesulfonic acid adsorbed on the material. An improved partial least squares (PLS) model was attained with the aid of multiplicative scatter correction pretreatment and stability competitive adaptive reweighted sampling wavenumber selection method. The root mean square error of cross validation was 1.87 μg/mL at PLS factor of 7. An independent test set was used to assess the model, with the relative error (RE) in an acceptable range of 0.46 to 10.03% and mean RE of 3.72%. This study confirmed the viability of the proposed method for the measurement of a low content of β-naphthalenesulfonic acid in water.

Evolution driven structural changes in CENP-E motor domain.

PubMed

Kumar, Ambuj; Kamaraj, Balu; Sethumadhavan, Rao; Purohit, Rituraj

2013-06-01

Genetic evolution corresponds to various biochemical changes that are vital development of new functional traits. Phylogenetic analysis has provided an important insight into the genetic closeness among species and their evolutionary relationships. Centromere-associated protein-E (CENP-E) protein is vital for maintaining cell cycle and checkpoint signal mechanisms are vital for recruitment process of other essential kinetochore proteins. In this study we have focussed on the evolution driven structural changes in CENP-E motor domain among primate lineage. Through molecular dynamics simulation and computational chemistry approaches we examined the changes in ATP binding affinity and conformational deviations in human CENP-E motor domain as compared to the other primates. Root mean square deviation (RMSD), Root mean square fluctuation (RMSF), Radius of gyration (Rg) and principle component analysis (PCA) results together suggested a gain in stability level as we move from tarsier towards human. This study provides a significant insight into how the cell cycle proteins and their corresponding biochemical activities are evolving and illustrates the potency of a theoretical approach for assessing, in a single study, the structural, functional, and dynamical aspects of protein evolution.

Monte Carlo simulation of ferroelectric domain growth

NASA Astrophysics Data System (ADS)

Li, B. L.; Liu, X. P.; Fang, F.; Zhu, J. L.; Liu, J.-M.

2006-01-01

The kinetics of two-dimensional isothermal domain growth in a quenched ferroelectric system is investigated using Monte Carlo simulation based on a realistic Ginzburg-Landau ferroelectric model with cubic-tetragonal (square-rectangle) phase transitions. The evolution of the domain pattern and domain size with annealing time is simulated, and the stability of trijunctions and tetrajunctions of domain walls is analyzed. It is found that in this much realistic model with strong dipole alignment anisotropy and long-range Coulomb interaction, the powerlaw for normal domain growth still stands applicable. Towards the late stage of domain growth, both the average domain area and reciprocal density of domain wall junctions increase linearly with time, and the one-parameter dynamic scaling of the domain growth is demonstrated.

Least Squares Procedures.

ERIC Educational Resources Information Center

Hester, Yvette

Least squares methods are sophisticated mathematical curve fitting procedures used in all classical parametric methods. The linear least squares approximation is most often associated with finding the "line of best fit" or the regression line. Since all statistical analyses are correlational and all classical parametric methods are least…

Fuzzy C-mean clustering on kinetic parameter estimation with generalized linear least square algorithm in SPECT

NASA Astrophysics Data System (ADS)

Choi, Hon-Chit; Wen, Lingfeng; Eberl, Stefan; Feng, Dagan

2006-03-01

Dynamic Single Photon Emission Computed Tomography (SPECT) has the potential to quantitatively estimate physiological parameters by fitting compartment models to the tracer kinetics. The generalized linear least square method (GLLS) is an efficient method to estimate unbiased kinetic parameters and parametric images. However, due to the low sensitivity of SPECT, noisy data can cause voxel-wise parameter estimation by GLLS to fail. Fuzzy C-Mean (FCM) clustering and modified FCM, which also utilizes information from the immediate neighboring voxels, are proposed to improve the voxel-wise parameter estimation of GLLS. Monte Carlo simulations were performed to generate dynamic SPECT data with different noise levels and processed by general and modified FCM clustering. Parametric images were estimated by Logan and Yokoi graphical analysis and GLLS. The influx rate (K I), volume of distribution (V d) were estimated for the cerebellum, thalamus and frontal cortex. Our results show that (1) FCM reduces the bias and improves the reliability of parameter estimates for noisy data, (2) GLLS provides estimates of micro parameters (K I-k 4) as well as macro parameters, such as volume of distribution (Vd) and binding potential (BP I & BP II) and (3) FCM clustering incorporating neighboring voxel information does not improve the parameter estimates, but improves noise in the parametric images. These findings indicated that it is desirable for pre-segmentation with traditional FCM clustering to generate voxel-wise parametric images with GLLS from dynamic SPECT data.

Long-term forecasting of meteorological time series using Nonlinear Canonical Correlation Analysis (NLCCA)

NASA Astrophysics Data System (ADS)

Woldesellasse, H. T.; Marpu, P. R.; Ouarda, T.

2016-12-01

Wind is one of the crucial renewable energy sources which is expected to bring solutions to the challenges of clean energy and the global issue of climate change. A number of linear and nonlinear multivariate techniques has been used to predict the stochastic character of wind speed. A wind forecast with good accuracy has a positive impact on the reduction of electricity system cost and is essential for the effective grid management. Over the past years, few studies have been done on the assessment of teleconnections and its possible effects on the long-term wind speed variability in the UAE region. In this study Nonlinear Canonical Correlation Analysis (NLCCA) method is applied to study the relationship between global climate oscillation indices and meteorological variables, with a major emphasis on wind speed and wind direction, of Abu Dhabi, UAE. The wind dataset was obtained from six ground stations. The first mode of NLCCA is capable of capturing the nonlinear mode of the climate indices at different seasons, showing the symmetry between the warm states and the cool states. The strength of the nonlinear canonical correlation between the two sets of variables varies with the lead/lag time. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE) and Mean absolute error (MAE). The results indicated that NLCCA models provide more accurate information about the nonlinear intrinsic behaviour of the dataset of variables than linear CCA model in terms of the correlation and root mean square error. Key words: Nonlinear Canonical Correlation Analysis (NLCCA), Canonical Correlation Analysis, Neural Network, Climate Indices, wind speed, wind direction

Dynamic aeroelastic stability of vertical-axis wind turbines under constant wind velocity

NASA Astrophysics Data System (ADS)

Nitzsche, Fred

1994-05-01

The flutter problem associated with the blades of a class of vertical-axis wind turbines called Darrieus is studied in detail. The spinning blade is supposed to be initially curved in a particular shape characterized by a state of pure tension at the blade cross section. From this equilibrium position a three-dimensional linear perturbation pattern is superimposed to determine the dynamic aeroelastic stability of the blade in the presence of free wind speed by means of the Floquet-Lyapunov theory for periodic systems.

Soft tissue changes and its stability as a sequlae to mandibular advancement.

PubMed

Uppada, Uday Kiran; Sinha, Ramen; Reddy, D Sreenatha; Paul, Dushyanth

2014-01-01

To predict the changes and evaluate the stability that occurs in the soft tissues following the skeletal movement subsequent to surgical advancement of the mandible through bilateral sagittal split osteotomy and to provide the patient reliable information with regard to esthetic changes that can be expected following the treatment. Twenty adult patients diagnosed with skeletal class II malocclusion and underwent bilateral sagittal split osteotomy for mandibular advancement by a mean of 8 mm using rigid fixation were included in the study. Soft tissue changes brought about by the surgical procedure and their stability over a period of time were evaluated prospectively using 12 linear (4 vertical and 8 horizontal) and 4 angular measurements on profile cephalograms which were taken preoperatively after the pre-surgical orthodontics (T1) and postoperatively with duration of 1 month (T2) and 6 months (T3) respectively. It was observed that compared to the linear measurements, the angular measurements showed significant changes. The improvement in the esthetic outcome is a direct reflection of the angular changes whereas the linear changes played a contributing role. Following mandibular advancement surgery the profiles of the patients was perceived to have improved with reduction in the facial convexity, an increase in the lower facial height, decrease in the depth of the mentolabial sulcus and improvement in the lip competency with lengthening, straightening and thinning of the lower lip. The soft tissue response and its stability depends on the stability of the surgical procedure itself, postsurgical growth and remodeling of the hard tissues and soft tissue changes as a result of maturation and aging.

Influence of anisotropy on percolation and jamming of linear k-mers on square lattice with defects

NASA Astrophysics Data System (ADS)

Tarasevich, Yu Yu; Laptev, V. V.; Burmistrov, A. S.; Shinyaeva, T. S.

2015-09-01

By means of the Monte Carlo simulation, we study the layers produced by the random sequential adsorption of the linear rigid objects (k-mers also known as rigid or stiff rods, sticks, needles) onto the square lattice with defects in the presence of an external field. The value of k varies from 2 to 32. The point defects randomly and uniformly placed on the substrate hinder adsorption of the elongated objects. The external field affects isotropic deposition of the particles, consequently the deposited layers are anisotropic. We study the influence of the defect concentration, the length of the objects, and the external field on the percolation threshold and the jamming concentration. Our main findings are (i) the critical defect concentration at which the percolation never occurs even at jammed state decreases for short k-mers (k < 16) and increases for long k-mers (k > 16) as anisotropy increases, (ii) the corresponding critical k-mer concentration decreases with anisotropy growth, (iii) the jamming concentration decreases drastically with growth of k-mer length for any anisotropy, (iv) for short k-mers, the percolation threshold is almost insensitive to the defect concentration for any anisotropy.

A non-linear data mining parameter selection algorithm for continuous variables

PubMed Central

Razavi, Marianne; Brady, Sean

2017-01-01

In this article, we propose a new data mining algorithm, by which one can both capture the non-linearity in data and also find the best subset model. To produce an enhanced subset of the original variables, a preferred selection method should have the potential of adding a supplementary level of regression analysis that would capture complex relationships in the data via mathematical transformation of the predictors and exploration of synergistic effects of combined variables. The method that we present here has the potential to produce an optimal subset of variables, rendering the overall process of model selection more efficient. This algorithm introduces interpretable parameters by transforming the original inputs and also a faithful fit to the data. The core objective of this paper is to introduce a new estimation technique for the classical least square regression framework. This new automatic variable transformation and model selection method could offer an optimal and stable model that minimizes the mean square error and variability, while combining all possible subset selection methodology with the inclusion variable transformations and interactions. Moreover, this method controls multicollinearity, leading to an optimal set of explanatory variables. PMID:29131829

Voltammetry of naltrexone in commercial formulation and human body fluids: Quantification and pharmacokinetic studies.

PubMed

Ghoneim, Mohamed M; El-Desoky, Hanaa S; Abdel-Galeil, Mohamed M

2011-06-01

Naltrexone HCl (NAL.HCl) has been reduced at the mercury electrode in Britton-Robinson universal buffer of pH values 2-11 with a mechanism involving the quasi-reversible uptake of the first transferring electron followed by a rate-determining protonation step of its C=O double bond at position C-6. Simple, sensitive, selective and reliable linear-sweep and square-wave adsorptive cathodic stripping voltammetry methods have been described for trace quantitation of NAL.HCl in bulk form, commercial formulation and human body fluids without the necessity for sample pretreatment and/or time-consuming extraction steps prior to the analysis. Limits of quantitation of 6.0×10(-9)M and 8.0×10(-10)M NAL.HCl in bulk form or commercial formulation and of 9.0×10(-9) and 1.0×10(-9)M NAL.HCl in spiked human serum samples were achieved by the described linear and square-wave stripping voltammetry methods, respectively. Furthermore, pharmacokinetic parameters of the drug in human plasma samples of healthy volunteers following the administration of an oral single dose of 50mg NAL.HCl (one Revia(®) tablet) were estimated by means of the described square-wave stripping voltammetry method without interferences from the drug's metabolites and/or endogenous human plasma constituents. The estimated pharmacokinetic parameters were favorably compared with those reported in literature. Copyright © 2011 Elsevier B.V. All rights reserved.

The comparison of robust partial least squares regression with robust principal component regression on a real

NASA Astrophysics Data System (ADS)

Polat, Esra; Gunay, Suleyman

2013-10-01

One of the problems encountered in Multiple Linear Regression (MLR) is multicollinearity, which causes the overestimation of the regression parameters and increase of the variance of these parameters. Hence, in case of multicollinearity presents, biased estimation procedures such as classical Principal Component Regression (CPCR) and Partial Least Squares Regression (PLSR) are then performed. SIMPLS algorithm is the leading PLSR algorithm because of its speed, efficiency and results are easier to interpret. However, both of the CPCR and SIMPLS yield very unreliable results when the data set contains outlying observations. Therefore, Hubert and Vanden Branden (2003) have been presented a robust PCR (RPCR) method and a robust PLSR (RPLSR) method called RSIMPLS. In RPCR, firstly, a robust Principal Component Analysis (PCA) method for high-dimensional data on the independent variables is applied, then, the dependent variables are regressed on the scores using a robust regression method. RSIMPLS has been constructed from a robust covariance matrix for high-dimensional data and robust linear regression. The purpose of this study is to show the usage of RPCR and RSIMPLS methods on an econometric data set, hence, making a comparison of two methods on an inflation model of Turkey. The considered methods have been compared in terms of predictive ability and goodness of fit by using a robust Root Mean Squared Error of Cross-validation (R-RMSECV), a robust R2 value and Robust Component Selection (RCS) statistic.

Dynamical mean-field theory and weakly non-linear analysis for the phase separation of active Brownian particles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Speck, Thomas; Menzel, Andreas M.; Bialké, Julian

2015-06-14

Recently, we have derived an effective Cahn-Hilliard equation for the phase separation dynamics of active Brownian particles by performing a weakly non-linear analysis of the effective hydrodynamic equations for density and polarization [Speck et al., Phys. Rev. Lett. 112, 218304 (2014)]. Here, we develop and explore this strategy in more detail and show explicitly how to get to such a large-scale, mean-field description starting from the microscopic dynamics. The effective free energy emerging from this approach has the form of a conventional Ginzburg-Landau function. On the coarsest scale, our results thus agree with the mapping of active phase separation ontomore » that of passive fluids with attractive interactions through a global effective free energy (motility-induced phase transition). Particular attention is paid to the square-gradient term necessary for the phase separation kinetics. We finally discuss results from numerical simulations corroborating the analytical results.« less

Statistical and clustering analysis for disturbances: A case study of voltage dips in wind farms

DOE PAGES

Garcia-Sanchez, Tania; Gomez-Lazaro, Emilio; Muljadi, Eduard; ...

2016-01-28

This study proposes and evaluates an alternative statistical methodology to analyze a large number of voltage dips. For a given voltage dip, a set of lengths is first identified to characterize the root mean square (rms) voltage evolution along the disturbance, deduced from partial linearized time intervals and trajectories. Principal component analysis and K-means clustering processes are then applied to identify rms-voltage patterns and propose a reduced number of representative rms-voltage profiles from the linearized trajectories. This reduced group of averaged rms-voltage profiles enables the representation of a large amount of disturbances, which offers a visual and graphical representation ofmore » their evolution along the events, aspects that were not previously considered in other contributions. The complete process is evaluated on real voltage dips collected in intense field-measurement campaigns carried out in a wind farm in Spain among different years. The results are included in this paper.« less

Temperature compensation via cooperative stability in protein degradation

NASA Astrophysics Data System (ADS)

Peng, Yuanyuan; Hasegawa, Yoshihiko; Noman, Nasimul; Iba, Hitoshi

2015-08-01

Temperature compensation is a notable property of circadian oscillators that indicates the insensitivity of the oscillator system's period to temperature changes; the underlying mechanism, however, is still unclear. We investigated the influence of protein dimerization and cooperative stability in protein degradation on the temperature compensation ability of two oscillators. Here, cooperative stability means that high-order oligomers are more stable than their monomeric counterparts. The period of an oscillator is affected by the parameters of the dynamic system, which in turn are influenced by temperature. We adopted the Repressilator and the Atkinson oscillator to analyze the temperature sensitivity of their periods. Phase sensitivity analysis was employed to evaluate the period variations of different models induced by perturbations to the parameters. Furthermore, we used experimental data provided by other studies to determine the reasonable range of parameter temperature sensitivity. We then applied the linear programming method to the oscillatory systems to analyze the effects of protein dimerization and cooperative stability on the temperature sensitivity of their periods, which reflects the ability of temperature compensation in circadian rhythms. Our study explains the temperature compensation mechanism for circadian clocks. Compared with the no-dimer mathematical model and linear model for protein degradation, our theoretical results show that the nonlinear protein degradation caused by cooperative stability is more beneficial for realizing temperature compensation of the circadian clock.

Optimal design of minimum mean-square error noise reduction algorithms using the simulated annealing technique.

PubMed

Bai, Mingsian R; Hsieh, Ping-Ju; Hur, Kur-Nan

2009-02-01

The performance of the minimum mean-square error noise reduction (MMSE-NR) algorithm in conjunction with time-recursive averaging (TRA) for noise estimation is found to be very sensitive to the choice of two recursion parameters. To address this problem in a more systematic manner, this paper proposes an optimization method to efficiently search the optimal parameters of the MMSE-TRA-NR algorithms. The objective function is based on a regression model, whereas the optimization process is carried out with the simulated annealing algorithm that is well suited for problems with many local optima. Another NR algorithm proposed in the paper employs linear prediction coding as a preprocessor for extracting the correlated portion of human speech. Objective and subjective tests were undertaken to compare the optimized MMSE-TRA-NR algorithm with several conventional NR algorithms. The results of subjective tests were processed by using analysis of variance to justify the statistic significance. A post hoc test, Tukey's Honestly Significant Difference, was conducted to further assess the pairwise difference between the NR algorithms.

Transport of oxygen ions in Er doped La2Mo2O9 oxide ion conductors: Correlation with microscopic length scales

NASA Astrophysics Data System (ADS)

Paul, T.; Ghosh, A.

2018-01-01

We report oxygen ion transport in La2-xErxMo2O9 (0.05 ≤ x ≤ 0.25) oxide ion conductors. We have measured conductivity and dielectric spectra at different temperatures in a wide frequency range. The mean square displacement and spatial extent of non-random sub-diffusive regions are estimated from the conductivity spectra and dielectric spectra, respectively, using linear response theory. The composition dependence of the conductivity is observed to be similar to that of the spatial extent of non-random sub-diffusive regions. The behavior of the composition dependence of the mean square displacement of oxygen ions is opposite to that of the conductivity. The attempt frequency estimated from the analysis of the electric modulus agrees well with that obtained from the Raman spectra analysis. The full Rietveld refinement of X-ray diffraction data of the samples is performed to estimate the distance between different oxygen lattice sites. The results obtained from such analysis confirm the ion hopping within the spatial extent of non-random sub-diffusive regions.

New techniques for diffusing-wave spectroscopy

NASA Technical Reports Server (NTRS)

Mason, T. G.; Gang, HU; Krall, A. H.; Weitz, David A.

1994-01-01

We present two new types of measurements that can be made with diffusing-wave spectroscopy (DWS), a form of dynamic light scattering that applies in limit of strong multiple scattering. The first application is to measure the frequency-dependent linear viscoelastic moduli of complex fluids using light scattering. This is accomplished by measuring the mean square displacement of probe particles using DWS. Their response to thermal fluctuations is determined by the fluctuation-dissipation relation, and is controlled by the response of the surrounding complex fluid. This response can be described in terms of a memory function, which is directly related to the complex elastic modulus of the system. Thus by measuring the mean square displacement, we are able to determine the frequency dependent modulus. The second application is the measurement of shape fluctuations of scattering particles. This is achieved by generalizing the theory for DWS to incorporate the effects if amplitude fluctuations in the scattering intensity of the particles. We apply this new method to study the thermally induced fluctuations in the shape of spherical emulsion droplets whose geometry is controlled by surface tension.

Application of Bounded Linear Stability Analysis Method for Metrics-Driven Adaptive Control

NASA Technical Reports Server (NTRS)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics-driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a second order system that represents a pitch attitude control of a generic transport aircraft. The analysis shows that the system with the metrics-conforming variable adaptive gain becomes more robust to unmodeled dynamics or time delay. The effect of analysis time-window for BLSA is also evaluated in order to meet the stability margin criteria.

Regulation of the Two Delta Crystallin Genes during Lens Development in the Chicken Embryo

DTIC Science & Technology

1991-08-22

Stabilization of tubulin mRNA by inhibition of protein synthesis sea 148 urchin embryos. Mol. Cell. Biol. 8, 3518-3525. Goto, K., Okada, T.S...counts from twenty lens epithelia. Error bars are ± SEM . Symbols: control lens tissue, (square), 0.5 ng/ml actinomycin D, (inverted triangle), 30 ng...Ŝ]-methionine for 5 hr in the absence or presence of actinomycin D (0.5 or 30 M-g/̂ iD • Values are the means ± SEM for ten groups of three lens

Mixed linear-nonlinear fault slip inversion: Bayesian inference of model, weighting, and smoothing parameters

NASA Astrophysics Data System (ADS)

Fukuda, J.; Johnson, K. M.

2009-12-01

Studies utilizing inversions of geodetic data for the spatial distribution of coseismic slip on faults typically present the result as a single fault plane and slip distribution. Commonly the geometry of the fault plane is assumed to be known a priori and the data are inverted for slip. However, sometimes there is not strong a priori information on the geometry of the fault that produced the earthquake and the data is not always strong enough to completely resolve the fault geometry. We develop a method to solve for the full posterior probability distribution of fault slip and fault geometry parameters in a Bayesian framework using Monte Carlo methods. The slip inversion problem is particularly challenging because it often involves multiple data sets with unknown relative weights (e.g. InSAR, GPS), model parameters that are related linearly (slip) and nonlinearly (fault geometry) through the theoretical model to surface observations, prior information on model parameters, and a regularization prior to stabilize the inversion. We present the theoretical framework and solution method for a Bayesian inversion that can handle all of these aspects of the problem. The method handles the mixed linear/nonlinear nature of the problem through combination of both analytical least-squares solutions and Monte Carlo methods. We first illustrate and validate the inversion scheme using synthetic data sets. We then apply the method to inversion of geodetic data from the 2003 M6.6 San Simeon, California earthquake. We show that the uncertainty in strike and dip of the fault plane is over 20 degrees. We characterize the uncertainty in the slip estimate with a volume around the mean fault solution in which the slip most likely occurred. Slip likely occurred somewhere in a volume that extends 5-10 km in either direction normal to the fault plane. We implement slip inversions with both traditional, kinematic smoothing constraints on slip and a simple physical condition of uniform stress drop.

Assessment of environmental and nondestructive earthquake effects on modal parameters of an office building based on long-term vibration measurements

NASA Astrophysics Data System (ADS)

Wu, Wen-Hwa; Wang, Sheng-Wei; Chen, Chien-Chou; Lai, Gwolong

2017-05-01

Identification for the modal parameters of an instrumented office building using ambient vibration measurements is conducted in this study based on a recently developed stochastic subspace identification methodology equipped with an alternative stabilization diagram and a hierarchical sifting process. The identified results are then deliberately examined to recognize the dynamic features for quite a few dominant modes of this building structure including three pairs of closely-spaced modes. Making use of the collected three-month data including three seismic events, the analyzed results show that the root-mean-square vibration response is directly related to the wind speed and indirectly related to the air temperature under a specific condition. More importantly, it is discovered that the root-mean-square response is the dominant factor to induce the variation of modal parameters. Except for the torsional modes, all the other modal frequencies are highly correlated with the root-mean-square acceleration in a negative manner and the corresponding damping ratios also clearly display a positive correlation. Another crucial observation from this assessment is that the percentages of frequency variation in three months for most of the identified modes go beyond 10%. The effects of three nondestructive earthquakes are further traced to observe the tendencies of reducing the modal frequencies and raising the damping ratios, both with a variation level possibly increasing with the seismic intensity. But different from the effects of environmental factors, the changes in modal parameters caused by nondestructive earthquakes will vanish right after the seismic events.

A Review of Hypersonic Boundary Layer Stability Experiments in a Quiet Mach 6 Wind Tunnel

NASA Technical Reports Server (NTRS)

Wilkinson, Stephen P.

1997-01-01

Three recent experimental studies of transition on cones with adverse pressure gradient produced by a flared afterbody and with the additive stability modifiers of wall cooling, angle of attack and bluntness are reviewed. All tests were conducted in a quiet Mach 6 wind tunnel. The dominant instability was found to be the second mode. For the cases examined with linear stability theory, the N factors at mode saturation were in the range of 8.5 to 11. Evidence of a combined second-mode/Gortler transition process was found. Mean, rms and spectral freestream data for the quiet facility is presented and the role of low frequency freestream noise is discussed.

Evaluation of the Bitterness of Traditional Chinese Medicines using an E-Tongue Coupled with a Robust Partial Least Squares Regression Method.

PubMed

Lin, Zhaozhou; Zhang, Qiao; Liu, Ruixin; Gao, Xiaojie; Zhang, Lu; Kang, Bingya; Shi, Junhan; Wu, Zidan; Gui, Xinjing; Li, Xuelin

2016-01-25

To accurately, safely, and efficiently evaluate the bitterness of Traditional Chinese Medicines (TCMs), a robust predictor was developed using robust partial least squares (RPLS) regression method based on data obtained from an electronic tongue (e-tongue) system. The data quality was verified by the Grubb's test. Moreover, potential outliers were detected based on both the standardized residual and score distance calculated for each sample. The performance of RPLS on the dataset before and after outlier detection was compared to other state-of-the-art methods including multivariate linear regression, least squares support vector machine, and the plain partial least squares regression. Both R² and root-mean-squares error (RMSE) of cross-validation (CV) were recorded for each model. With four latent variables, a robust RMSECV value of 0.3916 with bitterness values ranging from 0.63 to 4.78 were obtained for the RPLS model that was constructed based on the dataset including outliers. Meanwhile, the RMSECV, which was calculated using the models constructed by other methods, was larger than that of the RPLS model. After six outliers were excluded, the performance of all benchmark methods markedly improved, but the difference between the RPLS model constructed before and after outlier exclusion was negligible. In conclusion, the bitterness of TCM decoctions can be accurately evaluated with the RPLS model constructed using e-tongue data.

Bounded Linear Stability Margin Analysis of Nonlinear Hybrid Adaptive Control

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Boskovic, Jovan D.

2008-01-01

This paper presents a bounded linear stability analysis for a hybrid adaptive control that blends both direct and indirect adaptive control. Stability and convergence of nonlinear adaptive control are analyzed using an approximate linear equivalent system. A stability margin analysis shows that a large adaptive gain can lead to a reduced phase margin. This method can enable metrics-driven adaptive control whereby the adaptive gain is adjusted to meet stability margin requirements.

Visualizing the Sample Standard Deviation

ERIC Educational Resources Information Center

Sarkar, Jyotirmoy; Rashid, Mamunur

2017-01-01

The standard deviation (SD) of a random sample is defined as the square-root of the sample variance, which is the "mean" squared deviation of the sample observations from the sample mean. Here, we interpret the sample SD as the square-root of twice the mean square of all pairwise half deviations between any two sample observations. This…

Technology of Synergy Manifestation in the Research of Solution's Stability of Differential Equations System

ERIC Educational Resources Information Center

Dvoryatkina, Svetlana N.; Melnikov, Roman A. M.; Smirnov, Eugeny I.

2017-01-01

Effectiveness of mathematical education as non-linear, composite and open system, formation and development of cognitive abilities of the trainee are wholly defined in the solution of complex tasks by means of modern achievements in science to high school practice adaptation. The possibility of complex tasks solution arises at identification of…

Dynamical Analysis in the Mathematical Modelling of Human Blood Glucose

ERIC Educational Resources Information Center

Bae, Saebyok; Kang, Byungmin

2012-01-01

We want to apply the geometrical method to a dynamical system of human blood glucose. Due to the educational importance of model building, we show a relatively general modelling process using observational facts. Next, two models of some concrete forms are analysed in the phase plane by means of linear stability, phase portrait and vector…

Near infra red spectroscopy as a multivariate process analytical tool for predicting pharmaceutical co-crystal concentration.

PubMed

Wood, Clive; Alwati, Abdolati; Halsey, Sheelagh; Gough, Tim; Brown, Elaine; Kelly, Adrian; Paradkar, Anant

2016-09-10

The use of near infra red spectroscopy to predict the concentration of two pharmaceutical co-crystals; 1:1 ibuprofen-nicotinamide (IBU-NIC) and 1:1 carbamazepine-nicotinamide (CBZ-NIC) has been evaluated. A partial least squares (PLS) regression model was developed for both co-crystal pairs using sets of standard samples to create calibration and validation data sets with which to build and validate the models. Parameters such as the root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP) and correlation coefficient were used to assess the accuracy and linearity of the models. Accurate PLS regression models were created for both co-crystal pairs which can be used to predict the co-crystal concentration in a powder mixture of the co-crystal and the active pharmaceutical ingredient (API). The IBU-NIC model had smaller errors than the CBZ-NIC model, possibly due to the complex CBZ-NIC spectra which could reflect the different arrangement of hydrogen bonding associated with the co-crystal compared to the IBU-NIC co-crystal. These results suggest that NIR spectroscopy can be used as a PAT tool during a variety of pharmaceutical co-crystal manufacturing methods and the presented data will facilitate future offline and in-line NIR studies involving pharmaceutical co-crystals. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

A new method for the prediction of combustion instability

NASA Astrophysics Data System (ADS)

Flanagan, Steven Meville

This dissertation presents a new approach to the prediction of combustion instability in solid rocket motors. Previous attempts at developing computational tools to solve this problem have been largely unsuccessful, showing very poor agreement with experimental results and having little or no predictive capability. This is due primarily to deficiencies in the linear stability theory upon which these efforts have been based. Recent advances in linear instability theory by Flandro have demonstrated the importance of including unsteady rotational effects, previously considered negligible. Previous versions of the theory also neglected corrections to the unsteady flow field of the first order in the mean flow Mach number. This research explores the stability implications of extending the solution to include these corrections. Also, the corrected linear stability theory based upon a rotational unsteady flow field extended to first order in mean flow Mach number has been implemented in two computer programs developed for the Macintosh platform. A quasi one-dimensional version of the program has been developed which is based upon an approximate solution to the cavity acoustics problem. The three-dimensional program applies Greens's Function Discretization (GFD) to the solution for the acoustic mode shapes and frequency. GFD is a recently developed numerical method for finding fully three dimensional solutions for this class of problems. The analysis of complex motor geometries, previously a tedious and time consuming task, has also been greatly simplified through the development of a drawing package designed specifically to facilitate the specification of typical motor geometries. The combination of the drawing package, improved acoustic solutions, and new analysis, results in a tool which is capable of producing more accurate and meaningful predictions than have been possible in the past.

Inter-Annual Variability of Burned Area in Brazil Based on a Synergistic use of Information Derived from MODIS and Landsat-TM

NASA Astrophysics Data System (ADS)

Libonati, R.; Dacamara, C. C.; Setzer, A. W.; Morelli, F.

2014-12-01

A procedure is presented that allows using information from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor to improve the quality of monthly burned area estimates over Brazil. The method integrates MODIS derived information from two sources; the NASA MCD64A1 Direct Broadcast Monthly Burned Area Product and INPE's Monthly Burned Area MODIS product (AQM-MODIS). The latter product relies on an algorithm that was specifically designed for ecosystems in Brazil, taking advantage of the ability of MIR reflectances to discriminate burned areas. Information from both MODIS products is incorporated by means of a linear regression model where an optimal estimate of the burned area is obtained as a linear combination of burned area estimates from MCD64A1 and AQM-MODIS. The linear regression model is calibrated using as optimal estimates values of burned area derived from Landsat TM during 2005 and 2006 over Jalapão, a region of Cerrado covering an area of 187 x 187 km2. Obtained values of coefficients for MCD64A1 and AQM-MODIS were 0.51 and 0.35, respectively and the root mean square error was 7.6 km2. Robustness of the model was checked by calibrating the model separately for 2005 and 2006 and cross-validating with 2006 and 2005; coefficients for 2005 (2006) were 0.46 (0.54) for MCD64A1 and 0.35 (0.35) for AQM-MODIS and the corresponding root mean square errors for 2006 (2005) were 7.8 (7.4) km2. The linear model was then applied to Brazil as well as to the six Brazilian main biomes, namely Cerrado, Amazônia, Caatinga, Pantanal, Mata Atlântica and Pampa. As to be expected the interannual variability based on the proposed synergistic use of MCD64A1, AQM-MODIS and Landsat Tm data for the period 2005-2010 presents marked differences with the corresponding amounts derived from MCD64A1 alone. For instance during the considered period, values (in 103 km2) from the proposed approach (from MCD64A1) are 399 (142), 232 (62), 559 (259), 274 (73), 219 (31) and 415 (251). Values obtained with the proposed approach may be viewed as an improved alternative to the currently available products over Brazil.

Isotherm investigation for the sorption of fluoride onto Bio-F: comparison of linear and non-linear regression method

NASA Astrophysics Data System (ADS)

Yadav, Manish; Singh, Nitin Kumar

2017-12-01

A comparison of the linear and non-linear regression method in selecting the optimum isotherm among three most commonly used adsorption isotherms (Langmuir, Freundlich, and Redlich-Peterson) was made to the experimental data of fluoride (F) sorption onto Bio-F at a solution temperature of 30 ± 1 °C. The coefficient of correlation (r2) was used to select the best theoretical isotherm among the investigated ones. A total of four Langmuir linear equations were discussed and out of which linear form of most popular Langmuir-1 and Langmuir-2 showed the higher coefficient of determination (0.976 and 0.989) as compared to other Langmuir linear equations. Freundlich and Redlich-Peterson isotherms showed a better fit to the experimental data in linear least-square method, while in non-linear method Redlich-Peterson isotherm equations showed the best fit to the tested data set. The present study showed that the non-linear method could be a better way to obtain the isotherm parameters and represent the most suitable isotherm. Redlich-Peterson isotherm was found to be the best representative (r2 = 0.999) for this sorption system. It is also observed that the values of β are not close to unity, which means the isotherms are approaching the Freundlich but not the Langmuir isotherm.

Exploration of POD-Galerkin Techniques for Developing Reduced Order Models of the Euler Equations

DTIC Science & Technology

2015-07-01

modes [1]. Barone et al [15, 16] proposed to stabilize the reduced system by symmetrizing the higher-order PDE with a preconditioning matrix. Rowley et...advection scalar equation. The ROM is obtained by employing Galerkin’s method to reduce the high-order PDEs to a lower- order ODE system by means of POD...high-order PDEs to a lower-order ODE system by means of POD eigen-bases. For purposes of this study, a linearized version of the Euler equations is

An Incremental Weighted Least Squares Approach to Surface Lights Fields

NASA Astrophysics Data System (ADS)

Coombe, Greg; Lastra, Anselmo

An Image-Based Rendering (IBR) approach to appearance modelling enables the capture of a wide variety of real physical surfaces with complex reflectance behaviour. The challenges with this approach are handling the large amount of data, rendering the data efficiently, and previewing the model as it is being constructed. In this paper, we introduce the Incremental Weighted Least Squares approach to the representation and rendering of spatially and directionally varying illumination. Each surface patch consists of a set of Weighted Least Squares (WLS) node centers, which are low-degree polynomial representations of the anisotropic exitant radiance. During rendering, the representations are combined in a non-linear fashion to generate a full reconstruction of the exitant radiance. The rendering algorithm is fast, efficient, and implemented entirely on the GPU. The construction algorithm is incremental, which means that images are processed as they arrive instead of in the traditional batch fashion. This human-in-the-loop process enables the user to preview the model as it is being constructed and to adapt to over-sampling and under-sampling of the surface appearance.

Big Five personality stability, change, and codevelopment across adolescence and early adulthood.

PubMed

Borghuis, Jeroen; Denissen, Jaap J A; Oberski, Daniel; Sijtsma, Klaas; Meeus, Wim H J; Branje, Susan; Koot, Hans M; Bleidorn, Wiebke

2017-10-01

Using data from 2 large and overlapping cohorts of Dutch adolescents, containing up to 7 waves of longitudinal data each (N = 2,230), the present study examined Big Five personality trait stability, change, and codevelopment in friendship and sibling dyads from age 12 to 22. Four findings stand out. First, the 1-year rank-order stability of personality traits was already substantial at age 12, increased strongly from early through middle adolescence, and remained rather stable during late adolescence and early adulthood. Second, we found linear mean-level increases in girls' conscientiousness, in both genders' agreeableness, and in boys' openness. We also found temporal dips (i.e., U-shaped mean-level change) in boys' conscientiousness and in girls' emotional stability and extraversion. We did not find a mean-level change in boys' emotional stability and extraversion, and we found an increase followed by a decrease in girls' openness. Third, adolescents showed substantial individual differences in the degree and direction of personality trait changes, especially with respect to conscientiousness, extraversion, and emotional stability. Fourth, we found no evidence for personality trait convergence, for correlated change, or for time-lagged partner effects in dyadic friendship and sibling relationships. This lack of evidence for dyadic codevelopment suggests that adolescent friends and siblings tend to change independently from each other and that their shared experiences do not have uniform influences on their personality traits. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Quantitative coronary angiography using image recovery techniques for background estimation in unsubtracted images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wong, Jerry T.; Kamyar, Farzad; Molloi, Sabee

2007-10-15

Densitometry measurements have been performed previously using subtracted images. However, digital subtraction angiography (DSA) in coronary angiography is highly susceptible to misregistration artifacts due to the temporal separation of background and target images. Misregistration artifacts due to respiration and patient motion occur frequently, and organ motion is unavoidable. Quantitative densitometric techniques would be more clinically feasible if they could be implemented using unsubtracted images. The goal of this study is to evaluate image recovery techniques for densitometry measurements using unsubtracted images. A humanoid phantom and eight swine (25-35 kg) were used to evaluate the accuracy and precision of the followingmore » image recovery techniques: Local averaging (LA), morphological filtering (MF), linear interpolation (LI), and curvature-driven diffusion image inpainting (CDD). Images of iodinated vessel phantoms placed over the heart of the humanoid phantom or swine were acquired. In addition, coronary angiograms were obtained after power injections of a nonionic iodinated contrast solution in an in vivo swine study. Background signals were estimated and removed with LA, MF, LI, and CDD. Iodine masses in the vessel phantoms were quantified and compared to known amounts. Moreover, the total iodine in left anterior descending arteries was measured and compared with DSA measurements. In the humanoid phantom study, the average root mean square errors associated with quantifying iodine mass using LA and MF were approximately 6% and 9%, respectively. The corresponding average root mean square errors associated with quantifying iodine mass using LI and CDD were both approximately 3%. In the in vivo swine study, the root mean square errors associated with quantifying iodine in the vessel phantoms with LA and MF were approximately 5% and 12%, respectively. The corresponding average root mean square errors using LI and CDD were both 3%. The standard deviations in the differences between measured iodine mass in left anterior descending arteries using DSA and LA, MF, LI, or CDD were calculated. The standard deviations in the DSA-LA and DSA-MF differences (both {approx}21 mg) were approximately a factor of 3 greater than that of the DSA-LI and DSA-CDD differences (both {approx}7 mg). Local averaging and morphological filtering were considered inadequate for use in quantitative densitometry. Linear interpolation and curvature-driven diffusion image inpainting were found to be effective techniques for use with densitometry in quantifying iodine mass in vitro and in vivo. They can be used with unsubtracted images to estimate background anatomical signals and obtain accurate densitometry results. The high level of accuracy and precision in quantification associated with using LI and CDD suggests the potential of these techniques in applications where background mask images are difficult to obtain, such as lumen volume and blood flow quantification using coronary arteriography.« less

Investigation on Stability in Roll of Square Section Missile at High Angle of Attack

NASA Astrophysics Data System (ADS)

Tao, Yang; Fan, Zhaolin; Wu, Jifei; Wu, Wenhua

An experimental investigation of the stability in roll of a square section missile at high incidence was conducted in FL-23 wind tunnel. Dynamic motions were obtained on a square section missile that is free to rotate about its longitudinal axis. Different dynamic rolling motions were observed depending on the incidence of the model sting. These dynamic regimes include damped oscillations, quasi-limit-cycle wing-rock motion, and constant rolling. A coupling numerical method was established by solving the fluid dynamics equations and the rigid-body dynamics equations synchronously in order to predict the onset and the development of uncommented motions and then explore the unsteady movement characteristics of the aircraft. The study indicates that the aircraft loss stability at high incidence is caused by the asymmetric vertex on the level fin tip liftoff and attach alternately. The computation results are in line with the experiment results.

Near infrared spectral linearisation in quantifying soluble solids content of intact carambola.

PubMed

Omar, Ahmad Fairuz; MatJafri, Mohd Zubir

2013-04-12

This study presents a novel application of near infrared (NIR) spectral linearisation for measuring the soluble solids content (SSC) of carambola fruits. NIR spectra were measured using reflectance and interactance methods. In this study, only the interactance measurement technique successfully generated a reliable measurement result with a coefficient of determination of (R2) = 0.724 and a root mean square error of prediction for (RMSEP) = 0.461° Brix. The results from this technique produced a highly accurate and stable prediction model compared with multiple linear regression techniques.

Near Infrared Spectral Linearisation in Quantifying Soluble Solids Content of Intact Carambola

PubMed Central

Omar, Ahmad Fairuz; MatJafri, Mohd Zubir

2013-01-01

This study presents a novel application of near infrared (NIR) spectral linearisation for measuring the soluble solids content (SSC) of carambola fruits. NIR spectra were measured using reflectance and interactance methods. In this study, only the interactance measurement technique successfully generated a reliable measurement result with a coefficient of determination of (R2) = 0.724 and a root mean square error of prediction for (RMSEP) = 0.461° Brix. The results from this technique produced a highly accurate and stable prediction model compared with multiple linear regression techniques. PMID:23584118

Analysis of Fluid Gauge Sensor for Zero or Microgravity Conditions using Finite Element Method

NASA Technical Reports Server (NTRS)

Deshpande, Manohar D.; Doiron, Terence a.

2007-01-01

In this paper the Finite Element Method (FEM) is presented for mass/volume gauging of a fluid in a tank subjected to zero or microgravity conditions. In this approach first mutual capacitances between electrodes embedded inside the tank are measured. Assuming the medium properties the mutual capacitances are also estimated using FEM approach. Using proper non-linear optimization the assumed properties are updated by minimizing the mean square error between estimated and measured capacitances values. Numerical results are presented to validate the present approach.

Memory-less response and violation of the fluctuation-dissipation theorem in colloids suspended in an active bath.

PubMed

Maggi, Claudio; Paoluzzi, Matteo; Angelani, Luca; Di Leonardo, Roberto

2017-12-14

We investigate experimentally and numerically the stochastic dynamics and the time-dependent response of colloids subject to a small external perturbation in a dense bath of motile E. coli bacteria. The external field is a magnetic field acting on a superparamagnetic microbead suspended in an active medium. The measured linear response reveals an instantaneous friction kernel despite the complexity of the bacterial bath. By comparing the mean squared displacement and the response function we detect a clear violation of the fluctuation dissipation theorem.

Precision control of carrier-envelope phase in grating based chirped pulse amplifiers.

PubMed

Li, Chengquan; Moon, Eric; Mashiko, Hiroki; Nakamura, Christopher M; Ranitovic, Predrag; Maharjan, Chakra M; Cocke, C Lewis; Chang, Zenghu; Paulus, Gerhard G

2006-11-13

It is demonstrated that the carrier-envelope (CE) phase of pulses from a high power ultrafast laser system with a grating-based stretcher and compressor can be stabilized to a root mean square (rms) value of 180 mrad over almost 2 hours, excluding a brief re-locking period. The stabilization was accomplished via feedback control of the grating separation in the stretcher. It shows that the long term CE phase stability of a grating based chirped pulse amplification system can be as good as that of lasers using a glass-block stretcher and a prism pair compressor. Moreover, by adjusting the grating separation to preset values, the relative CE phase could be locked to an arbitrary value in the range of 2pi. This method is better than using a pair of wedge plates to adjust the phase after the hollow-core fiber compressor. The CE phase stabilization after a hollow-core fiber compressor was confirmed by a CE-phase meter based on the measurement of the left-to-right asymmetry of electrons produced by above-threshold ionization.

Analysis of Learning Curve Fitting Techniques.

DTIC Science & Technology

1987-09-01

1986. 15. Neter, John and others. Applied Linear Regression Models. Homewood IL: Irwin, 19-33. 16. SAS User’s Guide: Basics, Version 5 Edition. SAS... Linear Regression Techniques (15:23-52). Random errors are assumed to be normally distributed when using -# ordinary least-squares, according to Johnston...lot estimated by the improvement curve formula. For a more detailed explanation of the ordinary least-squares technique, see Neter, et. al., Applied

A quadratic-tensor model algorithm for nonlinear least-squares problems with linear constraints

NASA Technical Reports Server (NTRS)

Hanson, R. J.; Krogh, Fred T.

1992-01-01

A new algorithm for solving nonlinear least-squares and nonlinear equation problems is proposed which is based on approximating the nonlinear functions using the quadratic-tensor model by Schnabel and Frank. The algorithm uses a trust region defined by a box containing the current values of the unknowns. The algorithm is found to be effective for problems with linear constraints and dense Jacobian matrices.

A kernel adaptive algorithm for quaternion-valued inputs.

PubMed

Paul, Thomas K; Ogunfunmi, Tokunbo

2015-10-01

The use of quaternion data can provide benefit in applications like robotics and image recognition, and particularly for performing transforms in 3-D space. Here, we describe a kernel adaptive algorithm for quaternions. A least mean square (LMS)-based method was used, resulting in the derivation of the quaternion kernel LMS (Quat-KLMS) algorithm. Deriving this algorithm required describing the idea of a quaternion reproducing kernel Hilbert space (RKHS), as well as kernel functions suitable with quaternions. A modified HR calculus for Hilbert spaces was used to find the gradient of cost functions defined on a quaternion RKHS. In addition, the use of widely linear (or augmented) filtering is proposed to improve performance. The benefit of the Quat-KLMS and widely linear forms in learning nonlinear transformations of quaternion data are illustrated with simulations.

Signal processing methodologies for an acoustic fetal heart rate monitor

NASA Technical Reports Server (NTRS)

Pretlow, Robert A., III; Stoughton, John W.

1992-01-01

Research and development is presented of real time signal processing methodologies for the detection of fetal heart tones within a noise-contaminated signal from a passive acoustic sensor. A linear predictor algorithm is utilized for detection of the heart tone event and additional processing derives heart rate. The linear predictor is adaptively 'trained' in a least mean square error sense on generic fetal heart tones recorded from patients. A real time monitor system is described which outputs to a strip chart recorder for plotting the time history of the fetal heart rate. The system is validated in the context of the fetal nonstress test. Comparisons are made with ultrasonic nonstress tests on a series of patients. Comparative data provides favorable indications of the feasibility of the acoustic monitor for clinical use.

Random mechanics: Nonlinear vibrations, turbulences, seisms, swells, fatigue

NASA Astrophysics Data System (ADS)

Kree, P.; Soize, C.

The random modeling of physical phenomena, together with probabilistic methods for the numerical calculation of random mechanical forces, are analytically explored. Attention is given to theoretical examinations such as probabilistic concepts, linear filtering techniques, and trajectory statistics. Applications of the methods to structures experiencing atmospheric turbulence, the quantification of turbulence, and the dynamic responses of the structures are considered. A probabilistic approach is taken to study the effects of earthquakes on structures and to the forces exerted by ocean waves on marine structures. Theoretical analyses by means of vector spaces and stochastic modeling are reviewed, as are Markovian formulations of Gaussian processes and the definition of stochastic differential equations. Finally, random vibrations with a variable number of links and linear oscillators undergoing the square of Gaussian processes are investigated.

Validity of an ultra-wideband local positioning system to measure locomotion in indoor sports.

PubMed

Serpiello, F R; Hopkins, W G; Barnes, S; Tavrou, J; Duthie, G M; Aughey, R J; Ball, K

2018-08-01

The validity of an Ultra-wideband (UWB) positioning system was investigated during linear and change-of-direction (COD) running drills. Six recreationally-active men performed ten repetitions of four activities (walking, jogging, maximal acceleration, and 45º COD) on an indoor court. Activities were repeated twice, in the centre of the court and on the side. Participants wore a receiver tag (Clearsky T6, Catapult Sports) and two reflective markers placed on the tag to allow for comparisons with the criterion system (Vicon). Distance, mean and peak velocity, acceleration, and deceleration were assessed. Validity was assessed via percentage least-square means difference (Clearsky-Vicon) with 90% confidence interval and magnitude-based inference; typical error was expressed as within-subject standard deviation. The mean differences for distance, mean/peak speed, and mean/peak accelerations in the linear drills were in the range of 0.2-12%, with typical errors between 1.2 and 9.3%. Mean and peak deceleration had larger differences and errors between systems. In the COD drill, moderate-to-large differences were detected for the activity performed in the centre of the court, increasing to large/very large on the side. When filtered and smoothed following a similar process, the UWB-based positioning system had acceptable validity, compared to Vicon, to assess movements representative of indoor sports.

Tri-Squared Mean Cross Comparative Analysis: An Advanced Post Hoc Qualitative and Quantitative Metric for a More In-Depth Examination of the Initial Research Outcomes of the Tri-Square Test

ERIC Educational Resources Information Center

Osler, James Edward

2013-01-01

This monograph provides an epistemological rational for the design of an advanced novel analysis metric. The metric is designed to analyze the outcomes of the Tri-Squared Test. This methodology is referred to as: "Tri-Squared Mean Cross Comparative Analysis" (given the acronym TSMCCA). Tri-Squared Mean Cross Comparative Analysis involves…

Capillary Pressure of a Liquid Between Uniform Spheres Arranged in a Square-Packed Layer

NASA Technical Reports Server (NTRS)

Alexader, J. Iwan D.; Slobozhanin, Lev A.; Collicott, Steven H.

2004-01-01

The capillary pressure in the pores defined by equidimensional close-packed spheres is analyzed numerically. In the absence of gravity the menisci shapes are constructed using Surface Evolver code. This permits calculation the free surface mean curvature and hence the capillary pressure. The dependences of capillary pressure on the liquid volume constructed here for a set of contact angles allow one to determine the evolution of basic capillary characteristics under quasi-static infiltration and drainage. The maximum pressure difference between liquid and gas required for a meniscus passing through a pore is calculated and compared with that for hexagonal packing and with approximate solution given by Mason and Morrow [l]. The lower and upper critical liquid volumes that determine the stability limits for the equilibrium capillary liquid in contact with square packed array of spheres are tabulated for a set of contact angles.

Low frequency AC waveform generator

DOEpatents

Bilharz, Oscar W.

1986-01-01

Low frequency sine, cosine, triangle and square waves are synthesized in circuitry which allows variation in the waveform amplitude and frequency while exhibiting good stability and without requiring significant stabilization time. A triangle waveform is formed by a ramped integration process controlled by a saturation amplifier circuit which produces the necessary hysteresis for the triangle waveform. The output of the saturation circuit is tapped to produce the square waveform. The sine waveform is synthesized by taking the absolute value of the triangular waveform, raising this absolute value to a predetermined power, multiplying the raised absolute value of the triangle wave with the triangle wave itself and properly scaling the resultant waveform and subtracting it from the triangular waveform itself. The cosine is synthesized by squaring the triangular waveform, raising the triangular waveform to a predetermined power and adding the squared waveform raised to the predetermined power with a DC reference and subtracting the squared waveform therefrom, with all waveforms properly scaled. The resultant waveform is then multiplied with a square wave in order to correct the polarity and produce the resultant cosine waveform.

Cross-conditional entropy and coherence analysis of pharmaco-EEG changes induced by alprazolam.

PubMed

Alonso, J F; Mañanas, M A; Romero, S; Rojas-Martínez, M; Riba, J

2012-06-01

Quantitative analysis of electroencephalographic signals (EEG) and their interpretation constitute a helpful tool in the assessment of the bioavailability of psychoactive drugs in the brain. Furthermore, psychotropic drug groups have typical signatures which relate biochemical mechanisms with specific EEG changes. To analyze the pharmacological effect of a dose of alprazolam on the connectivity of the brain during wakefulness by means of linear and nonlinear approaches. EEG signals were recorded after alprazolam administration in a placebo-controlled crossover clinical trial. Nonlinear couplings assessed by means of corrected cross-conditional entropy were compared to linear couplings measured with the classical magnitude squared coherence. Linear variables evidenced a statistically significant drug-induced decrease, whereas nonlinear variables showed significant increases. All changes were highly correlated to drug plasma concentrations. The spatial distribution of the observed connectivity changes clearly differed from a previous study: changes before and after the maximum drug effect were mainly observed over the anterior half of the scalp. Additionally, a new variable with very low computational cost was defined to evaluate nonlinear coupling. This is particularly interesting when all pairs of EEG channels are assessed as in this study. Results showed that alprazolam induced changes in terms of uncoupling between regions of the scalp, with opposite trends depending on the variables: decrease in linear ones and increase in nonlinear features. Maps provided consistent information about the way brain changed in terms of connectivity being definitely necessary to evaluate separately linear and nonlinear interactions.

16 CFR 500.12 - Measurement of commodities by length and width, how expressed.

Code of Federal Regulations, 2013 CFR

2013-01-01

... square foot (929 cm2) be expressed in terms of length and width in linear measure. The customary inch... of 1 square foot (929 cm2) or more, but less than 4 square feet (37.1 dm2), be expressed in terms of... in square inches with length and width expressed in the largest whole unit (yard or foot) with any...

16 CFR 500.12 - Measurement of commodities by length and width, how expressed.

Code of Federal Regulations, 2011 CFR

2011-01-01

... square foot (929 cm2) be expressed in terms of length and width in linear measure. The customary inch... of 1 square foot (929 cm2) or more, but less than 4 square feet (37.1 dm2), be expressed in terms of... in square inches with length and width expressed in the largest whole unit (yard or foot) with any...

16 CFR 500.12 - Measurement of commodities by length and width, how expressed.

Code of Federal Regulations, 2014 CFR

2014-01-01

... square foot (929 cm2) be expressed in terms of length and width in linear measure. The customary inch... of 1 square foot (929 cm2) or more, but less than 4 square feet (37.1 dm2), be expressed in terms of... in square inches with length and width expressed in the largest whole unit (yard or foot) with any...

16 CFR 500.12 - Measurement of commodities by length and width, how expressed.

Code of Federal Regulations, 2012 CFR

2012-01-01

... square foot (929 cm2) be expressed in terms of length and width in linear measure. The customary inch... of 1 square foot (929 cm2) or more, but less than 4 square feet (37.1 dm2), be expressed in terms of... in square inches with length and width expressed in the largest whole unit (yard or foot) with any...

A colorimetric method for the molecular weight determination of polyethylene glycol using gold nanoparticles

PubMed Central

2013-01-01

A gold nanoparticle (AuNP)-based colorimetric method was developed for the molecular weight (MW) determination of polyethylene glycol (PEG), a commonly used hydrophilic polymer. Addition of a salt solution to PEG-coated AuNP solutions helps in screening the electrostatic repulsion between nanoparticles and generating a color change of the solutions from wine red to blue in 10 min in accordance with the MW of PEG, which illustrates the different stability degrees (SDs) of the AuNPs. The SDs are calculated by the absorbance ratios of the stable to the aggregated AuNPs in the solution. The root mean square end-to-end length (〈h2〉1/2) of PEG molecules shows a linear fit to the SDs of the PEG-coated AuNPs in a range of 1.938 ± 0.156 to 10.151 ± 0.176 nm. According to the Derjaguin-Landau-Verwey-Overbeek theory, the reason for this linear relationship is that the thickness of the PEG adlayer is roughly equivalent to the 〈h2〉1/2 of the PEG molecules in solution, which determines the SDs of the AuNPs. Subsequently, the MW of the PEG can be obtained from its 〈h2〉1/2 using a mathematical relationship between 〈h2〉1/2 and MW of PEG molecule. Applying this approach, we determined the 〈h2〉1/2 and the MW of four PEG samples according to their absorbance values from the ordinary ultraviolet–visible spectrophotometric measurements. Therefore, the MW of PEG can be distinguished straightforwardly by visual inspection and determined by spectrophotometry. This novel approach is simple, rapid, and sensitive. PMID:24359120

A Sensor Fusion Method for Tracking Vertical Velocity and Height Based on Inertial and Barometric Altimeter Measurements

PubMed Central

Sabatini, Angelo Maria; Genovese, Vincenzo

2014-01-01

A sensor fusion method was developed for vertical channel stabilization by fusing inertial measurements from an Inertial Measurement Unit (IMU) and pressure altitude measurements from a barometric altimeter integrated in the same device (baro-IMU). An Extended Kalman Filter (EKF) estimated the quaternion from the sensor frame to the navigation frame; the sensed specific force was rotated into the navigation frame and compensated for gravity, yielding the vertical linear acceleration; finally, a complementary filter driven by the vertical linear acceleration and the measured pressure altitude produced estimates of height and vertical velocity. A method was also developed to condition the measured pressure altitude using a whitening filter, which helped to remove the short-term correlation due to environment-dependent pressure changes from raw pressure altitude. The sensor fusion method was implemented to work on-line using data from a wireless baro-IMU and tested for the capability of tracking low-frequency small-amplitude vertical human-like motions that can be critical for stand-alone inertial sensor measurements. Validation tests were performed in different experimental conditions, namely no motion, free-fall motion, forced circular motion and squatting. Accurate on-line tracking of height and vertical velocity was achieved, giving confidence to the use of the sensor fusion method for tracking typical vertical human motions: velocity Root Mean Square Error (RMSE) was in the range 0.04–0.24 m/s; height RMSE was in the range 5–68 cm, with statistically significant performance gains when the whitening filter was used by the sensor fusion method to track relatively high-frequency vertical motions. PMID:25061835

Meteorological adjustment of yearly mean values for air pollutant concentration comparison

NASA Technical Reports Server (NTRS)

Sidik, S. M.; Neustadter, H. E.

1976-01-01

Using multiple linear regression analysis, models which estimate mean concentrations of Total Suspended Particulate (TSP), sulfur dioxide, and nitrogen dioxide as a function of several meteorologic variables, two rough economic indicators, and a simple trend in time are studied. Meteorologic data were obtained and do not include inversion heights. The goodness of fit of the estimated models is partially reflected by the squared coefficient of multiple correlation which indicates that, at the various sampling stations, the models accounted for about 23 to 47 percent of the total variance of the observed TSP concentrations. If the resulting model equations are used in place of simple overall means of the observed concentrations, there is about a 20 percent improvement in either: (1) predicting mean concentrations for specified meteorological conditions; or (2) adjusting successive yearly averages to allow for comparisons devoid of meteorological effects. An application to source identification is presented using regression coefficients of wind velocity predictor variables.

Order-constrained linear optimization.

PubMed

Tidwell, Joe W; Dougherty, Michael R; Chrabaszcz, Jeffrey S; Thomas, Rick P

2017-11-01

Despite the fact that data and theories in the social, behavioural, and health sciences are often represented on an ordinal scale, there has been relatively little emphasis on modelling ordinal properties. The most common analytic framework used in psychological science is the general linear model, whose variants include ANOVA, MANOVA, and ordinary linear regression. While these methods are designed to provide the best fit to the metric properties of the data, they are not designed to maximally model ordinal properties. In this paper, we develop an order-constrained linear least-squares (OCLO) optimization algorithm that maximizes the linear least-squares fit to the data conditional on maximizing the ordinal fit based on Kendall's τ. The algorithm builds on the maximum rank correlation estimator (Han, 1987, Journal of Econometrics, 35, 303) and the general monotone model (Dougherty & Thomas, 2012, Psychological Review, 119, 321). Analyses of simulated data indicate that when modelling data that adhere to the assumptions of ordinary least squares, OCLO shows minimal bias, little increase in variance, and almost no loss in out-of-sample predictive accuracy. In contrast, under conditions in which data include a small number of extreme scores (fat-tailed distributions), OCLO shows less bias and variance, and substantially better out-of-sample predictive accuracy, even when the outliers are removed. We show that the advantages of OCLO over ordinary least squares in predicting new observations hold across a variety of scenarios in which researchers must decide to retain or eliminate extreme scores when fitting data. © 2017 The British Psychological Society.

Robust identification and localization of intramedullary nail holes for distal locking using CBCT: a simulation study.

PubMed

Kamarianakis, Z; Buliev, I; Pallikarakis, N

2011-05-01

Closed intramedullary nailing is a common technique for treatment of femur and tibia fractures. The most challenging step in this procedure is the precise placement of the lateral screws that stabilize the fragmented bone. The present work concerns the development and the evaluation of a method to accurately identify in the 3D space the axes of the nail hole canals. A limited number of projection images are acquired around the leg with the help of a C-arm. On two of them, the locking hole entries are interactively selected and a rough localization of the hole axes is performed. Perpendicularly to one of them, cone-beam computed tomography (CBCT) reconstructions are produced. The accurate identification and localization of the hole axes are done by an identification of the centers of the nail holes on the tomograms and a further 3D linear regression through principal component analysis (PCA). Various feature-based approaches (RANSAC, least-square fitting, Hough transform) have been compared for best matching the contours and the centers of the holes on the tomograms. The robustness of the suggested method was investigated using simulations. Programming is done in Matlab and C++. Results obtained on synthetic data confirm very good localization accuracy - mean translational error of 0.14 mm (std=0.08 mm) and mean angular error of 0.84° (std=0.35°) at no radiation excess. Successful localization can be further used to guide a surgeon or a robot for correct drilling the bone along the nail openings. Copyright © 2010 IPEM. Published by Elsevier Ltd. All rights reserved.

Metal adsorption onto bacterial surfaces: development of a predictive approach

NASA Astrophysics Data System (ADS)

Fein, Jeremy B.; Martin, Aaron M.; Wightman, Peter G.

2001-12-01

Aqueous metal cation adsorption onto bacterial surfaces can be successfully modeled by means of a surface complexation approach. However, relatively few stability constants for metal-bacterial surface complexes have been measured. In order to determine the bacterial adsorption behavior of cations that have not been studied in the laboratory, predictive techniques are required that enable estimation of the stability constants of bacterial surface complexes. In this study, we use a linear free-energy approach to compare previously measured stability constants for Bacillus subtilis metal-carboxyl surface complexes with aqueous metal-organic acid anion stability constants. The organic acids that we consider are acetic, oxalic, citric, and tiron. We add to this limited data set by conducting metal adsorption experiments onto Bacillus subtilis, determining bacterial surface stability constants for Co, Nd, Ni, Sr, and Zn. The adsorption behavior of each of the metals studied here was described well by considering metal-carboxyl bacterial surface complexation only, except for the Zn adsorption behavior, which required carboxyl and phosphoryl complexation to obtain a suitable fit to the data. The best correlation between bacterial carboxyl surface complexes and aqueous organic acid anion stability constants was obtained by means of metal-acetate aqueous complexes, with a linear correlation coefficient of 0.97. This correlation applies only to unhydrolyzed aqueous cations and only to carboxyl binding of those cations, and it does not predict the binding behavior under conditions where metal binding to other bacterial surface site types occurs. However, the relationship derived in this study permits estimation of the carboxyl site adsorption behavior of a wide range of aqueous metal cations for which there is an absence of experimental data. This technique, coupled with the observation of similar adsorption behaviors across bacterial species (Yee and Fein, 2001), enables estimation of the effects of bacterial adsorption on metal mobilities for a large number of environmental and geologic applications.

Stabilized high-accuracy correction of ocular aberrations with liquid crystal on silicon spatial light modulator in adaptive optics retinal imaging system.

PubMed

Huang, Hongxin; Inoue, Takashi; Tanaka, Hiroshi

2011-08-01

We studied the long-term optical performance of an adaptive optics scanning laser ophthalmoscope that uses a liquid crystal on silicon spatial light modulator to correct ocular aberrations. The system achieved good compensation of aberrations while acquiring images of fine retinal structures, excepting during sudden eye movements. The residual wavefront aberrations collected over several minutes in several situations were statistically analyzed. The mean values of the root-mean-square residual wavefront errors were 23-30 nm, and for around 91-94% of the effective time the errors were below the Marechal criterion for diffraction limited imaging. The ability to axially shift the imaging plane to different retinal depths was also demonstrated.

Artificial Intelligence Techniques for Predicting and Mapping Daily Pan Evaporation

NASA Astrophysics Data System (ADS)

Arunkumar, R.; Jothiprakash, V.; Sharma, Kirty

2017-09-01

In this study, Artificial Intelligence techniques such as Artificial Neural Network (ANN), Model Tree (MT) and Genetic Programming (GP) are used to develop daily pan evaporation time-series (TS) prediction and cause-effect (CE) mapping models. Ten years of observed daily meteorological data such as maximum temperature, minimum temperature, relative humidity, sunshine hours, dew point temperature and pan evaporation are used for developing the models. For each technique, several models are developed by changing the number of inputs and other model parameters. The performance of each model is evaluated using standard statistical measures such as Mean Square Error, Mean Absolute Error, Normalized Mean Square Error and correlation coefficient (R). The results showed that daily TS-GP (4) model predicted better with a correlation coefficient of 0.959 than other TS models. Among various CE models, CE-ANN (6-10-1) resulted better than MT and GP models with a correlation coefficient of 0.881. Because of the complex non-linear inter-relationship among various meteorological variables, CE mapping models could not achieve the performance of TS models. From this study, it was found that GP performs better for recognizing single pattern (time series modelling), whereas ANN is better for modelling multiple patterns (cause-effect modelling) in the data.

Treatment of cells with alkaline borate buffer extends the capability of interphase FISH mapping.

PubMed

Yokota, H; van den Engh, G; Mostert, M; Trask, B J

1995-01-20

Interphase fluorescence in situ hybridization (FISH) has been shown to be a means to map DNA sequences relative to each other in the 100 kb to 1-2 Mb genomic-separation range. At distances below 0.1 Mb, probe sites are infrequently resolved in interphase chromatin. In the 0.1- to 1-Mb range, interphase chromatin can be modeled as a freely flexible chain. The mean square interphase distance between two probes is proportional to the genomic separation between the probes on the linear DNA molecule. Above 1-2 Mb, the relationship between interphase distance and genomic separation changes abruptly and appears to level off. We have used alkaline-borate treatment to expand the capability of interphase FISH mapping. We show here that alkaline-borate treatment increases nuclear diameter, the interphase distance between probes on homologous chromosomes, and the distance between probes on the same chromosome. We also show that the mean square distance between hybridization sites in borate-treated nuclei is proportional to genomic separation up to 4 Mb. Thus, alkaline-borate treatment enhances the capability of interphase FISH mapping by increasing the absolute distance between probes and extending the range of the simple relationship between interphase distance and genomic separation.

Treatment of cells with alkaline borate buffer extends the capability of interphase FISH mapping

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yokota, H.; Van Den Engh, G.; Mostert, M.

1995-01-20

Interphase fluorescence in situ hybridization (FISH) has been shown to be a means to map DNA sequences relative to each other in the 100 kb to 1-2 Mb genomic-separation range. At distances below 0.1 Mb, probe sites are infrequently resolved in interphase chromatin. In the 0.1- to 1-Mb range, interphase chromatin can be modeled as a freely flexible chain. The mean square interphase distance between two probes is proportional to the genomic separation between the probes on the linear DNA molecule. Above 1-2 Mb, the relationship between interphase distance and genomic separation changes abruptly and appears to level off. Wemore » have used alkaline-borate treatment to expand the capability of interphase FISH mapping. We show here that alkaline-borate treatment increases nuclear diameter, the interphase distance between probes on homologous chromosomes, and the distance between probes on the same chromosome. We also show that the mean square distance between hybridization sites in borate-treated nuclei is proportional to genomic separation up to 4 Mb. Thus, alkaline-borate treatment enhances the capability of interphase FISH mapping by increasing the absolute distance between probes and extending the range of the simple relationship between interphase distance and genomic separation. 31 refs., 5 figs.« less

Structural flexibility and protein adaptation to temperature: Molecular dynamics analysis of malate dehydrogenases of marine molluscs.

PubMed

Dong, Yun-Wei; Liao, Ming-Ling; Meng, Xian-Liang; Somero, George N

2018-02-06

Orthologous proteins of species adapted to different temperatures exhibit differences in stability and function that are interpreted to reflect adaptive variation in structural "flexibility." However, quantifying flexibility and comparing flexibility across proteins has remained a challenge. To address this issue, we examined temperature effects on cytosolic malate dehydrogenase (cMDH) orthologs from differently thermally adapted congeners of five genera of marine molluscs whose field body temperatures span a range of ∼60 °C. We describe consistent patterns of convergent evolution in adaptation of function [temperature effects on K M of cofactor (NADH)] and structural stability (rate of heat denaturation of activity). To determine how these differences depend on flexibilities of overall structure and of regions known to be important in binding and catalysis, we performed molecular dynamics simulation (MDS) analyses. MDS analyses revealed a significant negative correlation between adaptation temperature and heat-induced increase of backbone atom movements [root mean square deviation (rmsd) of main-chain atoms]. Root mean square fluctuations (RMSFs) of movement by individual amino acid residues varied across the sequence in a qualitatively similar pattern among orthologs. Regions of sequence involved in ligand binding and catalysis-termed mobile regions 1 and 2 (MR1 and MR2), respectively-showed the largest values for RMSF. Heat-induced changes in RMSF values across the sequence and, importantly, in MR1 and MR2 were greatest in cold-adapted species. MDS methods are shown to provide powerful tools for examining adaptation of enzymes by providing a quantitative index of protein flexibility and identifying sequence regions where adaptive change in flexibility occurs.