• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.206-216
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• 2017

This paper proposes a method to simultaneously estimate two degrees of freedom in wrist forces (extension - flexion, adduction - abduction) and one degree of freedom in grasping forces using Electromyography (EMG) signals of the forearms. To correlate the EMG signals with the forces, we applied a multi - layer perceptron(MLP), which is a machine learning method, and used the characteristics of the muscles constituting the forearm to generate learning data. Through the experiments, the similarity between the MLP target value and the estimated value was investigated by applying the coefficient of determination ($R^2$) and root mean square error (RMSE) to evaluate the performance of the proposed method. As a result, the $R^2$ values with respect to the wrist flexion-extension, adduction - abduction and grasping forces were 0.79, 0.73 and 0.78 and RMSE were 0.12, 0.17, 0.13 respectively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.95-101
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• 2017

In natural images, there is generally locality, and the values of adjacent pixels are similar. It is possible to estimate the curved surface characteristics of the original image using adjacent pixels having similar pixel values. In this paper, after precisely estimating the characteristics of the curved surface existing in the image, interpolation values are obtained so as to faithfully reflect the estimated characteristics of the curved surface, We propose an effective image enlarging method that generates an enlarged image using the obtained interpolation values. The image enlarged by the proposed method maintains the curved surface characteristics of the original image, and thus the image quality of the enlarged image is improved. Experimental results show that the image quality of the proposed method is superior to that of the conventional techniques.

• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1231-1244
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• 2008

The objective of this study is to present a methodology for estimating runoff curve number(CN) using SWAT model which is capable of reflecting watershed heterogeneity such as climate condition, land use, soil type. The proposed CN estimation method is based on the asymptotic CN method and particularly, it uses surface flow data simulated by SWAT. This method has advantages to estimate spatial CN values according to subbasin division and to reflect watershed characteristics because the calibration process has been made by matching the measured and simulated streamflows. Furthermore, the method is not sensitive to rainfall-runoff data since CN estimation is on a daily basis. The SWAT based CN estimation method is applied to Chungju dam watershed. The regression equation of the estimated CN that exponentially decays with the increase of rainfall is presented.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.50 no.4
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• pp.551-555
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• 2014

ADCPs have been widely used to estimate the dynamic characteristics and biomass of sound scattering layers (SSLs), and swimming speed of fish schools for analyzing SSLs spatial distribution and/or various behavior patterns. This result showed that the verification of the mean volume backscattering strength (MVBS or averaged SV, dB) acquired by the ADCP would be necessary for a quantitative analysis on the spatial distribution and the biomass estimation of the SSLs or fish school when ADCP is used for estimating their biomass. In addition, the calibrated sphere method was used to verify values of each MVBS obtained from 4 beams of ADCP (153.6 kHz) on the base of 3 frequencies (38, 120, 200 kHz) of Scientific echo sounder's split beam system. Then, the measured SV values were compared and analyzed in its Target Strength (TS, dB) values estimated by a theoretical acoustic scattering model.

• Journal of Industrial Technology
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• v.22 no.A
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• pp.127-135
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• 2002

In this study, the preliminary risk assessment for the underground storage tanks(UST) in Chunchon city was implemented using the geographical information system(GIS). The estimation variables, such as the installation year, storage capacity, the distances from streams, and from groundwater pumping wells, were selected to estimate the relative risk levels. The weighting factors were given to all the estimation variables. Cumulative scores were induced by the combination of all the scores of the corresponding variables using the buffering technique and the overlay analysis in ArcView. Using the these process, the relative risk level of each UST was estimated. Some sites in this study are simplified and reduced because the number of useable data are limited or too enormous. Thus the selection of the comprehensive estimation variables and the proper weighting values are required for the future study. The methodology in this study could be served not only for the preliminary risk assessment of UST but also for the selection of the proper location of new and old UST. And, it can be used for the effective management system of UST.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.669-684
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• 2012

Discrete wavelet transforms are extensively preferred in biomedical signal processing for denoising, feature extraction, and compression. This paper presents a new denoising method based on the modeling of discrete wavelet coefficients of ECG in selected sub-bands with Kernel density estimation. The modeling provides a statistical distribution of information and noise. A Gaussian kernel with bounded support is used for modeling sub-band coefficients and thresholds and is estimated by placing a sliding window on a normalized cumulative density function. We evaluated this approach on offline noisy ECG records from the Cardiovascular Research Centre of the University of Glasgow and on records from the MIT-BIH Arrythmia database. Results show that our proposed technique has a more reliable physical basis and provides improvement in the Signal-to-Noise Ratio (SNR) and Percentage RMS Difference (PRD). The morphological information of ECG signals is found to be unaffected after employing denoising. This is quantified by calculating the mean square error between the feature vectors of original and denoised signal. MSE values are less than 0.05 for most of the cases.

• Journal of Sensor Science and Technology
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• v.32 no.4
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• pp.232-237
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• 2023

This paper presents a system for estimating the position of a magnet using a magnetic sensor. An algorithm is presented to analyze the waveform and output voltage values of the magnetic field generated at each position when the magnet moves and to estimate the position of the magnet based on the analyzed data. Here, the magnet is sufficiently small to be inserted into a blood vessel and has a micro-magnetic field of hundreds of nanoteslas owing to the small size and shape of the guide wire. In this study, a highly sensitive magneto-impedance (MI) sensor was used to detect these micro-magnetic fields. Nine MI sensors were arranged in a 3×3 configuration to detect a magnetic field that changes according to the position of the magnet through the MI sensor, and the voltage value output was polynomially regressed to specify a position value for each voltage value. The accuracy was confirmed by comparing the actual position value with the estimated position value by expanding it from a 1D straight line to a 3D space. Additionally, we could estimate the position of the magnet within a 3% error.

• Current Optics and Photonics
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• v.4 no.4
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• pp.317-325
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• 2020

Accurate estimation of spatial frequencies and phases for illumination patterns are essential to reconstructing super-resolution images in structured illumination microscopy (SIM). In this manuscript, we propose the improved component cross-correlation (ICC) algorithm, which is based on optimization of the cross-correlation values of the overlapping information between various spectral components. Compared to other algorithms for spatial-frequency and phase determination, the results calculated by the ICC algorithm are more accurate when the modulation depths of the illumination patterns are low. Moreover, the ICC algorithm is able to calculate the spatial frequencies and phases simultaneously. Simulation results indicate that even if the modulation depth is lower than 0.1, the ICC algorithm still estimates the parameters precisely; the images reconstructed by the ICC algorithm are much clearer than those reconstructed by other algorithms. In experiments, our home-built SIM system was used to image bovine pulmonary artery endothelial (BPAE) cells. Drawing support from the ICC algorithm, super-resolution images were reconstructed without artifacts.

• Current Research on Agriculture and Life Sciences
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• v.32 no.2
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• pp.79-84
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• 2014

The precision aerial application of agricultural unmanned helicopters has become a new paradigm for small farms with orchards, paddy, and upland fields. The needs of agricultural applications require easy and affordable control systems. Recent developments of MEMS technology based on inertial sensors and high speed DSP have enabled the fabrication of low-cost attitude system. Therefore, this study evaluates inertial MEMS sensors for estimating the attitude of an agricultural unmanned helicopter. The accuracies and errors of gyro and acceleration sensors were verified using a pendulum system. The true motion values were calculated using a theoretical estimation and absolute encoder measurement of the pendulum, and then the sensor output was compared with reference values. When comparing the sensor measurements and true values, the errors were determined to be 4.32~5.72%, 3.53~6.74%, and 3.91~4.16% for the gyro rate and x-, z- accelerations, respectively. Thus, the measurement results confirmed that the inertial sensors are effective for establishing an attitude and heading reference system (AHRES). The sensors would be constructed in gimbals for the estimating and proving attitude measurements in the following paper.

• Journal of computational fluids engineering
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• v.18 no.2
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• pp.93-98
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• 2013

In this paper, we reported the verification of numerical simulation approach for sedimentation of the multi-size particles in a container. The comparison between experimentally measured values and numerically evaluated values on settle down process of fully mixed mixture is carried out. In an attempt to represent the natural particle size distribution, various diameters of single particles are simulated and the results are compared with the outcome of the multi-size computation. When the empirical formula for mean particle size estimation is adopted to define the sediment diameter, computation and comparison are conducted.