Model-based Parameter Estimation Research Articles

The shape of the myelosuppression time profile is related to the probability of developing neutropenic fever in patients with docetaxel-induced grade IV neutropenia

Chemotherapy-induced neutropenia is associated with the risk of developing febrile neutropenia (FN). The aim was to describe the time course of myelosuppression in breast cancer patients treated with docetaxel and to investigate how the shape of the predicted myelosuppression time course and earlier proposed risk factors influence the probability of developing FN. Neutrophil counts from 140 breast cancer patients with observed grade IV neutropenia during the first course of docetaxel treatment were included. Twenty-six of the patients (19%) experienced FN. The myelosuppression time course was described using a semi-mechanistic myelosuppression model in NONMEM. The individual myelosuppression model parameters [baseline neutrophil count, mean transit time (MTT) and drug effect parameter (EC(50))], myelosuppression descriptors (nadir, duration of grade IV neutropenia) and earlier suggested risk factors (age, performance status, haemoglobin and liver function) were explored to be related to FN by logistic regression. The neutrophil time course following docetaxel treatment was well described by the model. EC(50) and MTT were both significantly related to the probability of developing FN where low parameter values result in a rapid decline, low nadir and an increased risk of FN. None of the evaluated risk factors or myelosuppression descriptors were significant. The probability to develop FN in patients who experience grade IV neutropenia was dependent on the myelosuppression time profile. Patients with a rapid neutrophil decline and high drug sensitivity had a higher probability to develop FN. Model-based parameter estimates were superior predictors over descriptive values such as the nadir or duration of neutropenia.

Fast broadband analysis of microstrip by interpolating both impedance and preconditioning matrices with MBPE

An interpolation scheme using model-based parameter estimation (MBPE) for fast analysis of the microstrip structures over a wideband is proposed.The microstrip structures are analyzed by the mixed potential integral equation with the generated dense impedance matrix partitioned and compressed hierarchically by the UV method. The linear systems are solved by the generalized minimal residual method with its convergence accelerated by the sparse approximate inversion (SAI) preconditioning technique. Over a wide frequency band, both the near field impedance matrix and the SAI preconditioning matrix are interpolated by MBPE. Numerical results show that the proposed method can reduce the computation time significantly. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26155

Modeling delayed drug effect using discrete-time nonlinear autoregressive models: a connection with indirect response models

Indirect response (IDR) models have been widely applied to pharmacodynamic (PD) modeling, particularly when delayed response (hysteresis) is present. This paper proposes a class of nonlinear discrete-time autoregressive (AR) models with drug concentrations acting as a time-varying covariate on the asymptote parameter or the autocorrelation parameter of the AR models as an alternative modeling approach for delayed response data. The mathematical derivations revealed the inherent connection between IDR models and nonlinear AR models, and showed that the nonlinear AR models approximate the IDR models when the time interval between response data is small. Simulations demonstrate that the IDR models and the corresponding AR models produce similar temporal response profiles, and as the time interval decreased (i.e., more intensive sampling designs), the AR model based parameter estimates were more comparable to those estimated from the IDR models. In conjunction with mixed-effects modeling, the nonlinear AR models have been shown to well describe a set of simulated longitudinal PK/PD data for a clinical study. Further extensions of the proposed nonlinear AR models are warranted to model irregular and sparse PK/PD data.

Analysis of the radar range extension in open-ended waveguide type geometries

High frequency EM backscatter modeling of large waveguide type geometries is a difficult task. In analysis of radar range profile, wider bandwidths make modeling even more challenging. Here, a new dispersive scattering center model is used based on Model Based Parameter Estimation (MBPE) approach. The model is capable of representing the radar range extension according the nonlinear variations of the scattering phase. A population-based Maximum Likelihood (ML) algorithm is used to calculate the parameters. The PRONY method is used for initialization. Wideband sparse measured frequency domain samples are the inputs of the model. The results are compared with IFFT outcomes.

WIDEBAND DISPERSION ANALYSIS OF WAVEGUIDE GEOMETRIES USING FINITE SAMPLED DATA

Wideband analysis of frequency dispersive geometries is a challenge in inverse scattering problems. Waveguide duct is an important case in aerial targets with dominant returns. Its dispersive behavior afiects the range proflle analysis due to occurrence of unwanted range extension. A new high frequency analysis using model based parameter estimation (MBPE) approach is presented. A group delay criteria derived from the nonlinear scattering phase response represents the duct length. Wideband sparse measured frequency domain samples of various waveguides are used as inputs to the model. Comparison is made with joint time-frequency analysis (JTFA) and inverse fast Fourier transform (IFFT) results.

Identification of Friction in the 50/80 cm ARIES Schmidt Telescope Using the LuGre Model

AbstractIn this paper, we discuss the LuGre model based parameter estimation of the friction present in the 50/80 cm Schmidt telescope at the Aryabhatta Research Institute of Observational sciencES (ARIES). Identification and compensation of friction in telescopes is essential to achieve sub-arcsec pointing and tracking accuracies at very low velocities. The six parameter LuGre model which is an extension of the Dahl model captures most of the observed dynamic behavior of friction. High accuracy encoders mounted on the telescope axes are capable of measuring micro and macro displacements useful for estimating the six parameters. A suitable PI controller was developed for performing experiments on the Schmidt telescope to estimate the friction. It was observed that the system exhibits the behaviour described by the LuGre friction model.

Evaluation of pipeline defect's characteristic axial length via model-based parameter estimation in ultrasonic guided wave-based inspection

The reflection signal from a defect in the process of guided wave-based pipeline inspection usually includes sufficient information to detect and define the defect. In previous research, it has been found that the reflection of guided waves from even a complex defect primarily results from the interference between reflection components generated at the front and the back edges of the defect. The respective contribution of different parameters of a defect to the overall reflection can be affected by the features of the two primary reflection components. The identification of these components embedded in the reflection signal is therefore useful in characterizing the concerned defect. In this research, we propose a method of model-based parameter estimation with the aid of the Hilbert–Huang transform technique for the purpose of decomposition of a reflection signal to enable characterization of the pipeline defect. Once two primary edge reflection components are decomposed and identified, the distance between the reflection positions, which closely relates to the axial length of the defect, could be easily and accurately determined. Considering the irregular profiles of complex pipeline defects at their two edges, which is often the case in real situations, the average of varied axial lengths of such a defect along the circumference of the pipeline is used in this paper as the characteristic value of actual axial length for comparison purpose. The experimental results of artificial defects and real corrosion in sample pipes were considered in this paper to demonstrate the effectiveness of the proposed method.

A three-compartment model of the C-peptide–insulin dynamic during the DIST test

Dynamic insulin sensitivity ( SI) tests often utilise model-based parameter estimation. This research analyses the impact of expanding the typically used two-compartment model of insulin and C-peptide kinetics to incorporate a hepatic third compartment. The proposed model requires only four C-peptide assays to simulate endogenous insulin production ( uen), greatly reducing the cost and clinical burden. Sixteen subjects participated in 46 dynamic insulin sensitivity tests (DIST). Population kinetic parameters are identified for the new compartment. Results are assessed by model error versus measured data and repeatability of the identified SI. The median C-peptide error was 0% (IQR: −7.3, 6.7)%. Median insulin error was 7% (IQR: −28.7, 6.3)%. Strong correlation ( r = 0.92) existed between the SI values of the new model and those from the original two-compartment model. Repeatability in SI was similar between models (new model inter/intra-dose variability 3.6/12.3% original model −8.5/11.3%). When frequent C-peptide samples may be available, the added hepatic compartment does not offer significant diagnostic, repeatability improvement over the two-compartment model. However, a novel and successful three-compartment modelling strategy was developed which provided accurate estimation of endogenous insulin production and the subsequent SI identification from sparse C-peptide data.

Improved Model-Based Parameter Estimation Approach for Accelerated Periodic Method of Moments Solutions With Application to the Analysis of Convoluted Frequency Selected Surfaces and Metamaterials

An improved ¿smart¿ interpolation approach known as model-based parameter estimation (MBPE) is applied to the wide-band interpolation of periodic method of moments (PMM) impedance matrices for normal and oblique incidence cases. Prior to interpolation, easy to calculate but hard to interpolate, phase terms are removed from the impedance matrices. An efficient spectral-domain PMM formulation is introduced for the accelerated analysis of frequency selective surface (FSS) problems with a large number of unknowns, employing a one dimensional O(N log N) FFT-based method to speed up the computation of matrix-vector products within the bi-conjugate gradient (BCG) iterative solver, which is made possible by the asymmetric multilevel block-Toeplitz structure of the impedance-matrix. The MBPE interpolation algorithm provides a faster matrix fill time than the brute force method and is comparable or even faster than the 2-D FFT-based method for a large number of unknowns. It also has the advantage that it can be applied to non-uniform gridding cases. The accuracy and efficiency of the proposed techniques for large FSS problems are demonstrated by several design examples for both the normal and oblique incidence cases. We also apply this efficient analysis tool to the design of multiband single-layer FSS filters and artificial magnetic conductors (AMC) comprised of a 2-D periodic arrangement of convoluted metallic strips in the shape of a Hilbert curve. The multiband properties of the Hilbert curve FSS filters are studied for different iteration orders (i.e., different degrees of space-filling).

An Improved Super-Resolution Source Reconstruction Method

The source reconstruction method (SRM) is a technique developed for antenna diagnostics and for carrying out near-field (NF) to far-field (FF) transformation. The SRM is based on the application of the electromagnetic equivalence principle, in which one establishes an equivalent current distribution that radiates the same fields as the actual currents induced in the antenna under test (AUT). The knowledge of the equivalent currents allows the determination of the antenna radiating elements, as well as the prediction of the AUT-radiated fields outside the equivalent currents domain. The unique feature of the novel methodology presented in this paper is that it can resolve equivalent currents that are smaller than half a wavelength in size, thus providing super-resolution. Furthermore, the measurement field samples can be taken at field spacings greater than half a wavelength, thus going beyond the classical sampling criteria. These two distinctive features are possible due to the choice of a model-based parameter estimation methodology where the unknowns are approximated by a continuous basis and, secondly, through the use of the analytic Green's function. The latter condition also guarantees the invertibility of the electric field operator and provides a stable solution for the currents even when evanescent waves are present in the measurements. In addition, the use of the singular value decomposition in the solution of the matrix equations provides the user with a quantitative tool to assess the quality and the quantity of the measured data. Alternatively, the use of the iterative conjugate gradient (CG) method in solving the ill-conditioned matrix equations can also be implemented. Two examples of an antenna diagnostics method are presented to illustrate the applicability and accuracy of the proposed methodology.

Using MBPE technique to accelerate solving the thin-wire EFIE used in numerical simulation of lightning

The antenna theory (AT) model is widely used to numerically simulate the propagation of current wave along lightning return-stroke channels and compute the radiated electromagnetic fields. In this model, the return stroke channel is considered as a vertical monopole antenna above perfectly conducting ground for which the numerical solution of the governing electric field integral equation (EFIE) in the frequency domain by the conventional method of moment (MoM) is prohibitively slow. In this paper, a model-based parameter estimation (MBPE) technique is proposed to reduce the number of frequency-domain calculation points required for the evaluation of space-time current distribution along a lightning return stroke channel. In applying this technique to a rational function model for the channel current distribution, a uniform-like sampling strategy is investigated. In order to accelerate the building of the moment impedance matrix, the reciprocal closed-form mutual impedance of sinusoidal electric dipoles and the symmetry of the model are used. The proposed technique is validated against the conventional inverse fast Fourier transform algorithm which uses a MoM solution for all frequencies within the channel base current spectrum. It is shown that considerable computation efficiency is achieved in terms of CPU time without losing accuracy.

Fast and accurate radar cross-section computation over a broad frequency band using the best uniform rational approximation

The method of moments (MOM) in conjugation with the best uniform rational approximation is applied to predict the broad-band radar cross-section of arbitrarily shaped three-dimensional (3D) bodies. The surface integral equations are solved using MOM to obtain the equivalent surface currents at the frequency points corresponding to the Chebyshev nodes, and then the surface current within the given frequency band is represented by the Chebyshev series. To improve the accuracy, the Chebyshev series is matched via the Maehly approximation to a rational function, which can be as good as the best uniform rational approximation. Using the rational function, the surface current is obtained at any frequency point within the frequency band. Numerical results for 3D arbitrarily shaped perfectly electric conducting objects and homogenous dielectric bodies are considered. Compared with the asymptotic waveform evaluation technique and the model-based parameter estimation, the proposed technique is accurate in much broader frequency band with lower memory required.

THE RELATION BETWEEN LUMPED-ELEMENT CIRCUIT MODELS FOR CYLINDRICAL DIELECTRIC RESONATOR AND ANTENNA PARAMETERS USING MBPE

Finite-Difference Time Domain (FDTD) is used to calculate the input impedance of the cylindrical dielectric resonator (DRA) antenna with different dimensions. A lumpedelement circuit model for the input impedance calculation is proposed. The genetic algorithm is used to calculate the elements of the equivalent circuit. The Model-Based Parameter Estimation (MBPE) technique is used to find the variation of each element in the equivalent circuit with varying the physical dimensions of the antenna. The use of this method reduces the time required for calculating the input impedance of the cylindrical DRA in each variation of the antenna dimension.

Application of rational function approximation technique to hybrid FE/BI/MLFMA for 3D scattering

In this article, the rational function approximation technique (RFAT) is applied to the hybrid finite-element/boundary-integral/multilevel fast multipole algorithm (FE/BI/MLFMA) to acquire wide-band and wide-angle backscatter radar-cross-section (RCS) by complex targets. The two approaches of using the rational function approximation technique, asymptotic waveform evaluation (AWE) and model-based parameter estimation (MBPE), both have been investigated and compared by theoretical analysis and numerical experiments. The numerical results acquired by the developed computing algorithm of integrating the hybrid FE/BI/MLFMA with the RFAT are presented in the article, demonstrating that the rational function approximation technique can greatly speed up the hybrid FE/BI/MLFMA to acquire wide-band and wide-angle backscatter RCS by complex targets. © 2007 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2007.

Motion estimation of elastic articulated objects from points and contours with volume invariable constraint

This paper presents a model of elastic articulated objects based on revolving conic surface and a method of model-based motion estimation. The model includes 3D object skeleton and deformable surfaces that can represent the deformation of human body surfaces. In each limb, surface deformation is represented by adjusting one or two deformation parameters. Then, the 3D deformation parameters are determined by corresponding 2D image points and contours with volume invariable constraint from a sequence of stereo images. The 3D motion parameters are estimated based on the 3D model. The algorithm presented in this paper includes model-based parameter estimation of motion and parameter determination of deformable surfaces.

Indirect Measurement of a Bar Magnet Position Using a Hall Sensor Array

The measured magnetic induction field of a bar magnet can be used to compute or measure indirectly the position of the magnet. A model-based parameter estimation approach requires a precise induction field model and knowledge of the model error. In this paper, different analytic models describing the axial component of the induction field in front of a small cylindrical bar magnet are compared with Hall sensor array measurements and finite-element simulations. The used solenoid model matched the finite-element method simulations but requires a high numerical effort. The approximate dipole model is suitable when a proposed correction function for the estimated distance is applied and current and position are estimated simultaneously

Metallic and dielectric photonic crystal filter design using multiple multipole program and model-based parameter estimation methods

Ultra compact photonic crystal filters with and without metallic parts operating at telecommunication wavelengths are designed using the multiple multipole program combined with the model-based parameter estimation technique. Material loss is taken into account and measured material properties are employed for practical design considerations. Stochastic and deterministic optimization techniques are applied to obtain optimum filter characteristics.

Phenomenological model to fit complex permittivity data of water from radio to optical frequencies

A general factorized form of the dielectric function together with a fractional model-based parameter estimation method is used to provide an accurate analytical formula for the complex refractive index in water for the frequency range 10(8)-10(16)Hz . The analytical formula is derived using a combination of a microscopic frequency-dependent rational function for adjusting zeros and poles of the dielectric dispersion together with the macroscopic statistical Fermi-Dirac distribution to provide a description of both the real and imaginary parts of the complex permittivity for water. The Fermi-Dirac distribution allows us to model the dramatic reduction in the imaginary part of the permittivity in the visible window of the water spectrum.

A Modified Model-Based Interpolation Method to Accelerate the Characterization of UWB Antenna System

The persisting problem associated with ultrawideband (UWB) antenna design is the lack of an efficient method to characterize the antenna system. In this paper, the characteristics of the antenna system are described by a transfer function. In order to alleviate the computation intensity, a modified model based parameter estimation method is applied to the rational modeling of the transfer function by employing the intrinsic features of the UWB antenna system. With this modified rational modeling method, only a small quantity of samples is needed to give a complete representation of the performance of the UWB antenna system. Therefore, the characterization of the UWB system is largely accelerated while maintaining results with high accuracy

Hierarchical multiscale model-based design of experiments, catalysts, and reactors for fuel processing

In this paper a hierarchical multiscale simulation framework is outlined and experimental data injection into this framework is discussed. Specifically, we discuss multiscale model-based design of experiments to optimize the chemical information content of a detailed reaction mechanism in order to improve the fidelity and accuracy of reaction models. Extension of this framework to product (catalyst) design is briefly touched upon. Furthermore, we illustrate the use of such detailed and reduced kinetic models in reactor optimization as an example toward more conventional process design. It is proposed that hierarchical multiscale modeling offers a systematic framework for identification of the important scale(s) and model(s) where one should focus research efforts on. The ammonia decomposition on ruthenium to produce hydrogen and the water–gas shift reactions on platinum for converting syngas to hydrogen serve as illustrative fuel processing examples of various topics. The former is used to illustrate hierarchical multiscale model development and model-based parameter estimation as well as product engineering. The latter is employed to demonstrate model reduction and process optimization. Finally, opportunities for process design and control in portable microchemical devices (lab-on-a chip) for power generation are discussed.