• Korean Journal of Remote Sensing
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• v.16 no.2
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• pp.109-116
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• 2000

This study was carried out to assess the use of RADARSAT data which is C-band with HH polarization for the rice growth monitoring in Korea. Nine time-series data were taken by shallow incidence angle (standard beam mode 5 or 6) during rice growing season. And then, backscattering coefficients ($\sigma$$^{\circ}$) were extracted by calibration process for comparing with rice growth parameters such as plant height, leaf area index(LAI), and fresh and dry biomass. Field experimental data concerned with rice growth were collected 8 times for the ground truth at the study area, Tangjin, Chungnam, Korea. At the beginning of rice growth, backscattering coefficients were ranged from -l6~-l3dB when rice fields were not covered with rice canopy and flooded. At the maximum vegetative stage of rice, backscattering coefficients of the rice field were the highest ranging from -4.4dB~-3.1dB. The temporal variation of backscattering coefficient($\sigma$$^{\circ}$) in rice field was significant in this study. Backscattering coefficient ($\sigma$$^{\circ}$) of rice field was a little bit lower again after heading stage than before. This results show RADARSAT data is promising for rice monitoring.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.1 s.145
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• pp.32-42
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• 2006

This study aims at establishing a technique for sailing yachts model tests with sailing condition. It is very important to estimate a ship's potential speed performance before building a real ship. Several methods are used to estimate a ship's potential speed performance such as using parent ship data, standard vessel chart and model test. Model test is the most precise among these options. In korea. model testing is widely used with general vessels but not with sailing yachts. Because sailing yachts are propelled with heeling and leeway. using the wind. another method is needed to estimate their speed. The new model test. which is different from tests for upright general vessels, is in a great demand. In this paper. we describe a test method for the sailing yacht model test. based on Masuyama's equation of motion. And we describe choosing scale ratio. production process and materials of the model. Also. various ways of measuring instruments. attaching jigs and adjusting calibration are described so that they can be utilized as useful data for model testing.

• Structural Engineering and Mechanics
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• v.69 no.1
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• pp.43-50
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• 2019

In this research, the effect of bedding layer on the tensile failure mechanism of rocks has been investigated using PFC2D. For this purpose, firstly calibration of PFC2d was performed using Brazilian tensile strength. Secondly Brazilian test was performed on the bedding layer. Thickness of layers were 5 mm, 10 mm and 20 mm. in each thickness layer, layer angles changes from $0^{\circ}$ to $90^{\circ}$ with increment of $15^{\circ}$. Totally, 21 model were simulated and tested by loading rate of 0.016 mm/s. The results show that when layer angle is less than 15, tensile cracks initiates between the layers and propagate till coalesce with model boundary. Its trace is too high. With increasing the layer angle, less layer mobilizes in failure process. Also, the failure trace is very short. It's to be noted that number of cracks decrease with increasing the layer thickness. Also, Brazilian tensile strength is minimum when bedding layer angle is between $45^{\circ}$ and $75^{\circ}$. The maximum one is related to layer angle of $90^{\circ}$.

• Journal of Sensor Science and Technology
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• v.28 no.5
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• pp.284-288
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• 2019

A calibration-free analog neuron circuit is proposed as a viable alternative to the power hungry digital neuron in implementing a deep neural network. The conventional analog neuron requires calibrations because a voltage-mode link is used between the soma and the synapse, which results in significant uncertainty in terms of current mapping. In this work, a current-mode link is used to establish a robust link between the soma and the synapse against the variations in the process and interconnection impedances. The increased hardware owing to the adoption of the current-mode link is estimated to be manageable because the number of neurons in each layer of the neural network is typically bounded. To demonstrate the utility of the proposed analog neuron, a simple neural network with $4{\times}7{\times}3$ architecture has been designed for classifying iris flowers. The chip is now under fabrication in 0.35 mm CMOS technology. Thus, the proposed true current-mode analog neuron can be a practical option in realizing power-efficient neural networks for edge computing.

• Journal of Korea Multimedia Society
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• v.22 no.9
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• pp.1011-1019
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• 2019

In this paper, we propose a system that can more precisely identify and monitor the position of the tool used in the assembling workplace such as automobile production. The proposed positioning monitoring system is a combination of UWB communication module and MEMS IMU sensor. Since UWB does not need modulation and demodulation function and has low power density, UWB is widely used in indoor positioning field. However, it may cause positioning error due to errors in RF transmission and reception process, which may cause positioning accuracy. Therefore, in this paper, we propose an algorithm that uses IMU as an auxiliary means to compensate for errors that may occur in positioning using only UWB. The tag and anchor of UWB module measure the transmission / reception time by transmitting signals to each other and then estimate the distance between tag and anchor. The MEMS IMU sensor serves to provide positioning calibration information. The tag, which is a mobile node and attached to a moving tool, measures the three-dimensional position of the tool and transfers the coordinate data to the anchor. Thus, it is possible to confirm whether or not the specific tool is properly used according to the prescribed regulations.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.41.1-41.1
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• 2018

We constrain cosmological parameters by combining three different power spectra measured from galaxy clustering, galaxy-galaxy lensing, and cosmic shear using the Deep Lens Survey (DLS). Two lens bins (centered at z~0.27 and 0.54) and two source bins (centered at z~0.64, and 1.1) containing more than one million galaxies are selected to measure the power spectra. We re-calibrate the initial photo-z estimation of the lens bins by matching with SHELS and PRIMUS and confirm its fidelity by measuring a cross-correlation between the bins. We also check the reliability of the lensing signals through the null tests, lens-source flipping and cross shear measurement. Residual systematic errors from photometric redshift and shear calibration uncertainties are marginalized over in the nested sampling during our parameter constraint process. For the flat LCDM model, we determine S_8=sigma_8(Omega_m/0.3)^0.5=0.832+-0.028, which is in great agreement with the Planck data. We also verify that the two independent constraints from the cosmic shear and the galaxy clustering+galaxy-galaxy lensing measurements are consistent with each other. To address baryonic feedback effects on small scales, we marginalize over a baryonic feedback parameter, which we are able to constrain with the DLS data alone and more tightly when combined with Planck data. The constrained value hints at the possibility that the AGN feedback in the current OWLS simulations might not be strong enough.

• Journal of Broadcast Engineering
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• v.25 no.7
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• pp.1095-1106
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• 2020

In this paper, we propose an algorithm that extracts a high-precision 3D skeleton using a model generated using a distributed RGB-D camera. When information about a 3D model is extracted through a distributed RGB-D camera, if the information of the 3D model is used, a skeleton with higher precision can be obtained. In this paper, in order to improve the precision of the 2D skeleton, we find the conditions to obtain the 2D skeleton well using the PCA. Through this, high-quality 2D skeletons are obtained, and high-precision 3D skeletons are extracted by combining the information of the 2D skeletons. Even though this process goes through, the generated skeleton may have errors, so we propose an algorithm that removes these errors by using the information of the 3D model. We were able to extract very high accuracy skeletons using the proposed method.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.927-932
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• 2022

Instrument drift is caused by the passage of time, environmental changes, normal wear and tear, debris buildup, sudden shock, vibrations, electromagnetic fields, and improper use. Since it is inappropriate to directly determine the change of the output value as drift during the limited test period, a new algorithm that reflects both zero drift and span drift by giving changes over time to the calibration method of the instrument was proposed. The temperature drift was calculated to be 0.49% for about 60 minutes at 1-minute intervals in the nine-step constant temperature environment through the warming and cooling process.

• Food Science of Animal Resources
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• v.42 no.4
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• pp.655-671
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• 2022

There are differences of spectral characteristics between different types of meat cut, which means the model established using only one type of meat cut for meat quality prediction is not suitable for other meat cut types. A novel portable visible and near-infrared (Vis/NIR) optical system was used to simultaneously predict multiple quality indicators for different commercial meat cut types (silverside, back strap, oyster, fillet, thick flank, and tenderloin) from Small-tailed Han sheep. The correlation coefficients of the calibration set (R_c) and prediction set (R_p) of the optimal prediction models were 0.82 and 0.81 for pH, 0.88 and 0.84 for L^*, 0.83 and 0.78 for a^*, 0.83 and 0.82 for b^*, 0.94 and 0.86 for cooking loss, 0.90 and 0.88 for shear force, 0.84 and 0.83 for protein, 0.93 and 0.83 for fat, 0.92 and 0.87 for moisture contents, respectively. This study demonstrates that Vis/NIR spectroscopy is a promising tool to achieve the predictions of multiple quality parameters for different commercial meat cut types.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.5
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• pp.723-740
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• 2022

This study aimed to develop an Arduino-based garment pressure device (APD) on the basis of using Single-Tact sensor by suggesting the reliable clothing pressure range and coefficient of selected sensors through the APD calibration process. Once the APD was validated, the pressure of the experimental men's lower body compression wears was measured using the APD and was compared to the pressure measured using the existing air-pack type pressure meter. The subjects were one mannequin and eight men in their 20's, and the trial compression wears were calf sleeves and pants. Clothing pressures were measured in hip, mid-thigh, calf, and ankle. In terms of the 99% confidence level, the experimental clothing pressure measured at the designated measuring points using the APD was considered identical to the one measured using an existing clothing pressure meter. Therefore, on the basis of the experiment results, this study demonstrated that the APD is as reliable as the existing clothing pressure meter within the pressure ranges of 0.54-16.79 kPa and 0.18-25.47 kPa as provided by the SingleTact sensor supplier's data on the basis of using an external ADC (Analog to Digital Converter) module.