• Title/Summary/Keyword: Inverse Estimation

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Biomechanical Characterization with Inverse FE Model Parameter Estimation: Macro and Micro Applications (유한요소 모델 변수의 역 추정법을 이용한 생체의 물성 규명)

  • Ahn, Bum-Mo;Kim, Yeong-Jin;Shin, Jennifer H.;Kim, Jung
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.33 no.11
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    • pp.1202-1208
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    • 2009
  • An inverse finite element (FE) model parameter estimation algorithm can be used to characterize mechanical properties of biological tissues. Using this algorithm, we can consider the influence of material nonlinearity, contact mechanics, complex boundary conditions, and geometrical constraints in the modeling. In this study, biomechanical experiments on macro and micro samples are conducted and characterized with the developed algorithm. Macro scale experiments were performed to measure the force response of porcine livers against mechanical loadings using one-dimensional indentation device. The force response of the human liver cancer cells was also measured by the atomic force microscope (AFM). The mechanical behavior of porcine livers (macro) and human liver cancer cells (micro) were characterized with the algorithm via hyperelastic and linear viscoelastic models. The developed models are suitable for computing accurate reaction force on tools and deformation of biomechanical tissues.

Inverse Brightness Temperature Estimation for Microwave Scanning Radiometer

  • Park, Hyuk;Katkovnik, Vladimir;Kang, Gum-Sil;Kim, Sung-Hyun;Choi, Jun-Ho;Choi, Se-Hwan;Jiang, Jing-Shan;Kim, Yong-Hoon
    • Korean Journal of Remote Sensing
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    • v.19 no.1
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    • pp.53-59
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    • 2003
  • The passive microwave remote sensing has progressed considerably in recent years Important earth surface parameters are detected and monitored by airborne and space born radiometers. However the spatial resolution of real aperture measurements is constrained by the antenna aperture size available on orbiting platforms and on the ground. The inverse problem technique is researched in order to improve the spatial resolution of microwave scanning radiometer. We solve a two-dimensional (surface) temperature-imaging problem with a major intention to develop high-resolution methods. In this paper, the scenario for estimation of both radiometer point spread function (PSF) and target configuration is explained. The PSF of the radiometer is assumed to be unknown and estimated from the observations. The configuration and brightness temperature of targets are also estimated. To do this, we deal with the parametric modeling of observation scenario. The performance of developed algorithms is illustrated on two-dimensional experimental data obtained by the water vapor radiometer.

THE LENGTH-BIASED POWERED INVERSE RAYLEIGH DISTRIBUTION WITH APPLICATIONS

  • MUSTAFA, ABDELFATTAH;KHAN, M.I.
    • Journal of applied mathematics & informatics
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    • v.40 no.1_2
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    • pp.1-13
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    • 2022
  • This article introduces a new distribution called length-biased powered inverse Rayleigh distribution. Some of its statistical properties are derived. Maximum likelihood procedure is applied to report the point and interval estimations of all model parameters. The proposed distribution is also applied to two real data sets for illustrative purposes.

MCMC Approach for Parameter Estimation in the Structural Analysis and Prognosis

  • An, Da-Wn;Gang, Jin-Hyuk;Choi, Joo-Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.23 no.6
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    • pp.641-649
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    • 2010
  • Estimation of uncertain parameters is required in many engineering problems which involve probabilistic structural analysis as well as prognosis of existing structures. In this case, Bayesian framework is often employed, which is to represent the uncertainty of parameters in terms of probability distributions conditional on the provided data. The resulting form of distribution, however, is not amenable to the practical application due to its complex nature making the standard probability functions useless. In this study, Markov chain Monte Carlo (MCMC) method is proposed to overcome this difficulty, which is a modern computational technique for the efficient and straightforward estimation of parameters. Three case studies that implement the estimation are presented to illustrate the concept. The first one is an inverse estimation, in which the unknown input parameters are inversely estimated based on a finite number of measured response data. The next one is a metamodel uncertainty problem that arises when the original response function is approximated by a metamodel using a finite set of response values. The last one is a prognostics problem, in which the unknown parameters of the degradation model are estimated based on the monitored data.

Inverse active wind load inputs estimation of the multilayer shearing stress structure

  • Chen, Tsung-Chien;Lee, Ming-Hui
    • Wind and Structures
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    • v.11 no.1
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    • pp.19-33
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    • 2008
  • This research investigates the adaptive input estimation method applied to the multilayer shearing stress structure. This method is to estimate the values of wind load inputs by analyzing the active reaction of the system. The Kalman filter without the input term and the adaptive weighted recursive least square estimator are two main portions of this method. The innovation vector can be produced by the Kalman filter, and be applied to the adaptive weighted recursive least square estimator to estimate the wind load input over time. This combined method can effectively estimate the wind loads to the structure system to enhance the reliability of the system active performance analysis. The forms of the simulated inputs (loads) in this paper include the periodic sinusoidal wave, the decaying exponent, the random combination of the sinusoidal wave and the decaying exponent, etc. The active reaction computed plus the simulation error is regard as the simulated measurement and is applied to the input estimation algorithm to implement the numerical simulation of the inverse input estimation process. The availability and the precision of the input estimation method proposed in this research can be verified by comparing the actual value and the one obtained by numerical simulation.

A Study on Inverse Radiation Analysis using RPSO Algorithm (RPSO 알고리즘을 이용한 역복사 해석에 관한 연구)

  • Lee, Kyun-Ho;Kim, Ki-Wan;Kim, Man-Young;Baek, Seung-Wook
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.31 no.7 s.262
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    • pp.635-643
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    • 2007
  • An inverse radiation analysis is presented for the estimation of the radiation properties for an absorbing, emitting, and scattering media with diffusely emitting and reflecting opaque boundaries. In this study, a repulsive particle swarm optimization(RPSO) algorithm which is a relatively recent heuristic search method is proposed as an effective method for improving the search efficiency for unknown parameters. To verify the performance of the proposed RPSO algorithm, it is compared with a basic particle swarm optimization(PSO) algorithm and a hybrid genetic algorithm(HGA) for the inverse radiation problem with estimating the various radiation properties in a two-dimensional irregular medium when the measured temperatures are given at only four data positions. A finite-volume method is applied to solve the radiative transfer equation of a direct problem to obtain measured temperatures.

Wind load estimation of super-tall buildings based on response data

  • Zhi, Lun-hai;Chen, Bo;Fang, Ming-xin
    • Structural Engineering and Mechanics
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    • v.56 no.4
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    • pp.625-648
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    • 2015
  • Modern super-tall buildings are more sensitive to strong winds. The evaluation of wind loads for the design of these buildings is of primary importance. A direct monitoring of wind forces acting on super-tall structures is quite difficult to be realized. Indirect measurements interpreted by inverse techniques are therefore favourable since dynamic response measurements are easier to be carried out. To this end, a Kalman filtering based inverse approach is developed in this study so as to estimate the wind loads on super-tall buildings based on limited structural responses. The optimum solution of Kalman filter gain by solving the Riccati equation is used to update the identification accuracy of external loads. The feasibility of the developed estimation method is investigated through the wind tunnel test of a typical super-tall building by using a Synchronous Multi-Pressure Scanning System. The effects of crucial factors such as the type of wind-induced response, the covariance matrix of noise, errors of structural modal parameters and levels of noise involved in the measurements on the wind load estimations are examined through detailed parametric study. The effects of the number of vibration modes on the identification quality are studied and discussed in detail. The made observations indicate that the proposed inverse approach is an effective tool for predicting the wind loads on super-tall buildings.

A Distortion Estimation Method Using Integer Operations in H.264/AVC Encoder (H.264/AVC 부호화기에서 정수 연산을 사용한 왜곡치 예측 방식)

  • Moon, Jeong-Mee;Kim, Jae-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.1C
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    • pp.63-71
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    • 2009
  • In this paper, a new low-complexity distortion estimation method for H.264 rate-distortion optimized mode decision is proposed. The coding processes, such as DCT, quantization, inverse quantization, inverse DCT, and reconstruction are needed to compute the distortion in an H.264 encoder. To reduce these processes, we estimate distortion using integer operations with coefficients obtained in the quantization process. Inverse quantization, inverse DCT, and reconstruction processes are not needed by the proposed method. For quantization parameters 24 to 36, experimental results show that the time saving of rate-distortion optimized mode decision is on average 29 % and as high as 42 % with negligible degradation in coding performance.

Kernel Inference on the Inverse Weibull Distribution

  • Maswadah, M.
    • Communications for Statistical Applications and Methods
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    • v.13 no.3
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    • pp.503-512
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    • 2006
  • In this paper, the Inverse Weibull distribution parameters have been estimated using a new estimation technique based on the non-parametric kernel density function that introduced as an alternative and reliable technique for estimation in life testing models. This technique will require bootstrapping from a set of sample observations for constructing the density functions of pivotal quantities and thus the confidence intervals for the distribution parameters. The performances of this technique have been studied comparing to the conditional inference on the basis of the mean lengths and the covering percentage of the confidence intervals, via Monte Carlo simulations. The simulation results indicated the robustness of the proposed method that yield reasonably accurate inferences even with fewer bootstrap replications and it is easy to be used than the conditional approach. Finally, a numerical example is given to illustrate the densities and the inferential methods developed in this paper.

Optical Flow Based Vehicle Counting and Speed Estimation in CCTV Videos (Optical Flow 기반 CCTV 영상에서의 차량 통행량 및 통행 속도 추정에 관한 연구)

  • Kim, Jihae;Shin, Dokyung;Kim, Jaekyung;Kwon, Cheolhee;Byun, Hyeran
    • Journal of Broadcast Engineering
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    • v.22 no.4
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    • pp.448-461
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    • 2017
  • This paper proposes a vehicle counting and speed estimation method for traffic situation analysis in road CCTV videos. The proposed method removes a distortion in the images using Inverse perspective Mapping, and obtains specific region for vehicle counting and speed estimation using lane detection algorithm. Then, we can obtain vehicle counting and speed estimation results from using optical flow at specific region. The proposed method achieves stable accuracy of 88.94% from several CCTV images by regional groups and it totally applied at 106,993 frames, about 3 hours video.