• Journal of Institute of Control, Robotics and Systems
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• v.19 no.6
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• pp.513-519
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• 2013

The current vision-based approaches for emotion recognition, such as facial expression analysis, have many technical limitations in real circumstances, and are not suitable for applications that use them solely in practical environments. In this paper, we propose an approach for emotion recognition by combining extrinsic representations and intrinsic activities among the natural responses of humans which are given specific imuli for inducing emotional states. The intrinsic activities can be used to compensate the uncertainty of extrinsic representations of emotional states. This combination is done by using PRMs (Probabilistic Relational Models) which are extent version of bayesian networks and are learned by greedy-search algorithms and expectation-maximization algorithms. Previous research of facial expression-related extrinsic emotion features and physiological signal-based intrinsic emotion features are combined into the attributes of the PRMs in the emotion recognition domain. The maximum likelihood estimation with the given dependency structure and estimated parameter set is used to classify the label of the target emotional states.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.6
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• pp.26-34
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• 1999

This study shows an alternative method for the determination of object's position, based on a computer vision method. This approach develops the vision system model to define the reciprocal relationship between the 3-D real space and 2-D image plane. The developed model involves the bilinear six-view parameters, which is estimated using the relationship between the camera space location and real coordinates of known position. Based on estimated parameters in independent cameras, the position of unknown object is accomplished using a sequential estimation scheme that permits data of unknown points in each of the 2-D image plane of cameras. This vision control methods the robust and reliable, which overcomes the difficulties of the conventional research such as precise calibration of the vision sensor, exact kinematic modeling of the robot, and correct knowledge of the relative positions and orientation of the robot and CCD camera. Finally, the developed vision control method is tested experimentally by performing determination of object position in the space using computer vision system. These results show the presented method is precise and compatible.

• Journal of Power Electronics
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• v.16 no.2
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• pp.643-653
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• 2016

The conventional methods used to evaluate battery state-of-charge (SOC) cannot accommodate the chemistry nonlinearities, measurement inaccuracies and parameter perturbations involved in estimation systems. In this paper, an impedance-based equivalent circuit model has been constructed with respect to a LiFePO₄ battery by approximating the electrochemical impedance spectrum (EIS) with RC circuits. The efficiencies of approximating the EIS with RC networks in different series-parallel forms are first discussed. Additionally, the typical hysteresis characteristic is modeled through an empirical approach. Subsequently, a methodology incorporating an H-infinity observer designated for open-circuit voltage (OCV) observation and a hysteresis model developed for OCV-SOC mapping is proposed. Thereafter, evaluation experiments under FUDS and UDDS test cycles are undertaken with varying temperatures and different current-sense bias. Experimental comparisons, in comparison with the EKF based method, indicate that the proposed SOC estimator is more effective and robust. Moreover, test results on a group of Li-ion batteries, from different manufacturers and of different chemistries, show that the proposed method has high generalization capability for all the three types of Li-ion batteries.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.6
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• pp.111-119
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• 2012

Applicability of 8 day interval flow data for the calibration of hydrologic model was evaluated using Hydrological Simulation Program-Fortran (HSPF) at Kyungan watershed. The 8 day interval flow monitored by Ministry of Environment located at upstream was calibrated and periodically validated during 2004-2008. And continuous daily flow monitored by Ministry of Construction & Transportation (MOCT) and located at the mouth was compared with daily simulated data during 2004-2007 as spatial validation. Automatic calibration tool which is Model-Independent Parameter Estimation & Uncertainty Analysis (PEST) was applied for HSPF calibration procedure. The model efficiencies for calibration and periodic validation were 0.63 and 0.88, and model performances were fair and very good, respectively, based on criteria of calibration tolerances. Continuous daily stream flow at the mouth of Kyungan watershed were good agreement with observed continuous daily stream flow with showing 0.63 NS value. The PEST program is very useful tool for HSPF hydrologic calibration using non-continuous daily stream flow as well as continuous daily stream flow. The 8 day interval flow data monitored by MOE could be used to calibrate hydrologic model if the continuous daily stream flow is unavailable.

• Structural Engineering and Mechanics
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• v.81 no.1
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• pp.103-115
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• 2022

The prediction error variances for frequencies are usually considered as unknown in the Bayesian system identification process. However, the error variances for mode shapes are taken as known to reduce the dimension of an identification problem. The present study attempts to explore the effectiveness of Bayesian approach of model parameters updating using Markov Chain Monte Carlo (MCMC) technique considering the prediction error variances for both the frequencies and mode shapes. To remove the ergodicity of Markov Chain, the posterior distribution is obtained by Gaussian Random walk over the proposal distribution. The prior distributions of prediction error variances of modal evidences are implemented through inverse gamma distribution to assess the effectiveness of estimation of posterior values of model parameters. The issue of incomplete data that makes the problem ill-conditioned and the associated singularity problem is prudently dealt in by adopting a regularization technique. The proposed approach is demonstrated numerically by considering an eight-storey frame model with both complete and incomplete modal data sets. Further, to study the effectiveness of the proposed approach, a comparative study with regard to accuracy and computational efficacy of the proposed approach is made with the Sequential Monte Carlo approach of model parameter updating.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.2
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• pp.261-269
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• 2018

This paper presents a convenient method to estimate the internal parameters of plenoptic camera using CCD(charge-coupled device) camera model. The images used for plenoptic camera calibration generally use the checkerboard pattern used in CCD camera calibration. Based on the CCD camera model, the determinant of the plenoptic camera model can be derived through the relationship with the plenoptic camera model. We formulate four equations that express the focal length, the principal point, the baseline, and distance between the virtual camera and the object. By performing a nonlinear optimization technique, we solve the equations to estimate the parameters. We compare the estimation results with the actual parameters and evaluate the reprojection error. Experimental results show that the MSE(mean square error) is 0.309 and estimation values are very close to actual values.

• Journal of Korean Society on Water Environment
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• v.34 no.3
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• pp.328-338
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• 2018

The objective of this study was to evaluate the applicability of a HSPF (Hydrological Simulation Program-Fortran) model for runoff estimation in the Namgang dam watershed. Spatial data, such as watershed, stream, land use, and a digital elevation map, were used as input for the HSPF model, which was calibrated and validated using observed runoff data from 2004 to 2015 for three stations (Sancheong, Shinan, Changchon) in the study watershed. Parameters for runoff calibration were selected based on the user's manual and references, and parameter calibration was done by trial and error. The $R^2$ (determination coefficient), RMSE (root-mean-square error), NSE (Nash-Sutcliffe efficiency coefficient), and RMAE (relative mean absolute error) were used to evaluate the model's performance. Calibration and validation results showed that annual mean runoff was within a ${\pm}5%$ error in Sancheong and Shinan, whereas there was a14% error in Changchon. The model performance criteria for calibration and validation showed that $R^2$ ranged from 0.80 to 0.92, RMSE was 2.33 to 2.39 mm/day, NSE was 0.71 to 0.85, and RMAE was 0.37 to 0.57 mm/day for daily runoff. Visual inspection showed that the simulated daily flow, monthly flow, and flow exceedance graph agreed well with observations for the Sancheong and Shinan stations, whereas the simulated flow was higher than observed at the Changchon station.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.641-648
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• 2022

In this study, the performance of the NHPP software reliability model with exponential distribution (Exponential Basic, Inverse Exponential, Lindley, Rayleigh) characteristics was comparatively analyzed, and based on this, the optimal reliability model was also presented. To analyze the software failure phenomenon, the failure time data collected during system operation was used, and the parameter estimation was solved by applying the maximum likelihood estimation method (MLE). Through various comparative analysis (mean square error analysis, true value predictive power analysis of average value function, strength function evaluation, and reliability evaluation applied with mission time), it was found that the Lindley model was an efficient model with the best performance. Through this study, the reliability performance of the distribution with the characteristic of the exponential form, which has no existing research case, was newly identified, and through this, basic design data that software developers could use in the initial stage can be presented.

• Earthquakes and Structures
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• v.12 no.3
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• pp.321-332
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• 2017

The reverse fault is a dangerous geological hazard faced by buried steel pipelines. Permanent ground deformation along the fault trace will induce large compressive strain leading to buckling failure of the pipe. A hybrid pipe-shell element based numerical model programed by INP code supported by ABAQUS solver was proposed in this study to explore the strain performance of buried X80 steel pipeline under reverse fault displacement. Accuracy of the numerical model was validated by previous full scale experimental results. Based on this model, parametric analysis was conducted to study the effects of four main kinds of parameters, e.g., pipe parameters, fault parameters, load parameter and soil property parameters, on the strain demand. Based on 2340 peak strain results of various combinations of design parameters, a semi-empirical model for strain demand prediction of X80 pipeline at reverse fault crossings was proposed. In general, reverse faults encountered by pipelines are involved in 3D oblique reverse faults, which can be considered as a combination of reverse fault and strike-slip fault. So a compressive strain demand estimation procedure for X80 pipeline crossing oblique-reverse faults was proposed by combining the presented semi-empirical model and the previous one for compression strike-slip fault (Liu 2016). Accuracy and efficiency of this proposed method was validated by fifteen design cases faced by the Second West to East Gas pipeline. The proposed method can be directly applied to the strain based design of X80 steel pipeline crossing oblique-reverse faults, with much higher efficiency than common numerical models.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1224-1234
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• 2019

Hybrid rotor position estimation methods that integrate a fundamental model and high frequency (HF) signal injection are widely used for the wide speed-range sensorless control of interior permanent-magnet synchronous machines (IPMSMs). However, the direct transition of two different schemes may lead to system fluctuations or system instability since two estimated rotor positions based on two different schemes are always unequal due to the effects of parameter variations, system delays and inverter nonlinearities. In order to avoid these problems, a seamless transition strategy to define and construct a virtual q-axis inductance is proposed in this paper. With the proposed seamless transition strategy, an estimated rotor position based on a fundamental model is forced to track that based on HF signal injection before the transition by adjusting the constructed virtual q-axis inductance. Meanwhile, considering that the virtual q-axis inductance changes with rotor position estimation errors, a new observer with a two-phase phase-locked loop (TP-PLL) is developed to accurately obtain the virtual q-axis inductance online. Furthermore, IPMSM sensorless control with maximum torque per ampere (MTPA) operations can be tracked automatically by selecting the proper virtual q-axis inductance. Finally, experimental results obtained from an IPMSM demonstrate the feasibility of the proposed seamless transition strategy.