• Journal of Korea Society of Industrial Information Systems
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• v.11 no.2
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• pp.69-78
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• 2006

This paper is concerned with analyzing the images of Korean automobiles using, so called, sensory engineering, which adapts the sensory and subjective assessment of human beings in evaluating the quality of product. The methodology of analysis is suggested in this paper according to the following steps. First, 14 pairs of adjectives, which describe the image of object cars in view of the semantic differential method, are derived from consulting with several expert panels. Nextly, factor analysis is performed in order to obtain the axises, by which the images space of the object automobiles are specified, and then the images of the object automobiles are measured by the coordinate of all the object automobiles in the image space. In this paper, a sensory estimation experiment is performed to a panel consisting with In undergraduate students residing in the region of Daegu. From the result of analysis of this paper, target images, which the automobile manufacturers are intended, are achieved by and large except one company.

• Korean Journal of Remote Sensing
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• v.3 no.1
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• pp.41-54
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• 1987

Accurate determination of Sea Surface Temperature (SST) is essential for ocean and climate studies. This paper estimated SST in the sea region around the Korea from the Advenced Very High Resolution Radiometer(AVHRR) channel 4 data on board NOAA-9 satellite. The processing procedure used to derive SSTs utilized: 1) Ascending node prediction of satellite orbit 2) Geometric correction 3) Radiometric calibration and radiance to temperature conversion look up table 4) Removing cloudy area. SST product results are displayed as colored video and hardcopy. In this processing, geometric correction is derived from equator crossing time, ascending time and subpoint coordinate information. Also, normalized response function of infrared 10.5-11.5$\mu\textrm{m}$ wavelength is used for temperature conversion. The SST derived from this processing is relatively similar to the measurements made by ship data, but because of water vapor attenuation SST from satellite are in general 2$^{\circ}$- $^{\circ}C$ lower than the ship data.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.580-591
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• 2019

This paper focuses on to improving object detection performance using the camera and LiDAR on autonomous vehicle platforms by fusing detected objects from individual sensors through a late fusion approach. In the case of object detection using camera sensor, YOLOv3 model was employed as a one-stage detection process. Furthermore, the distance estimation of the detected objects is based on the formulations of Perspective matrix. On the other hand, the object detection using LiDAR is based on K-means clustering method. The camera and LiDAR calibration was carried out by PnP-Ransac in order to calculate the rotation and translation matrix between two sensors. For Sensor fusion, intersection over union(IoU) on the image plane with respective to the distance and angle on world coordinate were estimated. Additionally, all the three attributes i.e; IoU, distance and angle were fused using logistic regression. The performance evaluation in the sensor fusion scenario has shown an effective 5% improvement in object detection performance compared to the usage of single sensor.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.1
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• pp.67-74
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• 2022

To analyze the motion of aircraft through computing the dynamics equations, true airspeed is essential for obtaining aerodynamic loads. Although the airspeed is measured by on-board instruments such as pitot tubes, measurement data are difficult to obtain for commercial flights because they include sensitive data about the airline operations. One of the commonly available trajectory data, Automatic Dependent Surveillance-Broadcast data, provide aircraft's speed in the form of ground speed. The ground speed is a vector sum of the local wind velocity and the true airspeed. This paper present a method to estimate true airspeed by combining the trajectory, meteorological, and topology data available to the public. To integrate each data, we first matched the coordinate system and then unified the altitude reference to the mean sea level. We calculated the wind vector for all trajectory points by interpolating from the lower resolution grid of the meteorological data. Finally, we calculate the true airspeed from the ground speed and the wind vector. These processes were applied to several sample trajectories with corresponding meteorological data and the topology data, and the estimated true airspeeds are presented.

• Journal of Drive and Control
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• v.20 no.2
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• pp.15-23
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• 2023

In this study, two-dimensional location of crops for auto weeding was detected using deep learning. To construct a dataset for soybean detection, an image-capturing system was developed using a mono camera and single-board computer and the system was mounted on a weeding robot to collect soybean images. A dataset was constructed by extracting RoI (region of interest) from the raw image and each sample was labeled with soybean and the background for classification learning. The deep learning model consisted of four convolutional layers and was trained with a weakly supervised learning method that can provide object localization only using image-level labeling. Localization of the soybean area can be visualized via CAM and the two-dimensional position of the soybean was estimated by clustering the pixels associated with the soybean area and transforming the pixel coordinates to world coordinates. The actual position, which is determined manually as pixel coordinates in the image was evaluated and performances were 6.6(X-axis), 5.1(Y-axis) and 1.2(X-axis), 2.2(Y-axis) for MSE and RMSE about world coordinates, respectively. From the results, we confirmed that the center position of the soybean area derived through deep learning was sufficient for use in automatic weeding systems.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.61.3-61.3
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• 2019

The epochs of observation for the 28 determinative stars in the Shi Shi Xing Jing and Cheonsang Yeolcha Bunyajido are estimated by using two fitting methods. The coordinate values in these tables were thought to be measured with meridian instruments, and so they have the axis-misalignment errors and random errors. We adopt a Fourier method, and also we devise a least square fitting method. We do bootstrap resamplings to estimate the variance of the epochs. As results, we find that both data sets were made during the 1^st century BCE or the latter period of the Former Han dynasty. The sample mean of the epoch for the SSXJ data is earlier by about 15-20 years than that for the Cheonsang Yeolcha Bunyajido. However, their variances are so large that we cannot decide whether the Shi Shi Xing Jing data was formed around 77 BCE and the Cheonsang Yeolcha Bunyajido was measured in 52 BCE. We need either more data points or data points measured with better precision. We will discuss on the other 120 coordinates of stars listed in the Shi Shi Xing Jing.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.2
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• pp.99-112
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• 2013

This paper presents a subspace system identification for estimating the stiffness matrix and flexural rigidities of a shear building. System matrices are estimated by LQ decomposition and singular value decomposition from an input-output Hankel matrix. The estimated system matrices are converted into a real coordinate through similarity transformation, and the stiffness matrix is estimated from the system matrices. The accuracy and the stability of an estimated stiffness matrix depend on the size of the associated Hankel matrix. The estimation error curve of the stiffness matrix is obtained with respect to the size of a Hankel matrix using a prior finite element model of a shear building. The sizes of the Hankel matrix, which are consistent with a target accuracy level, are chosen through this curve. Among these candidate sizes of the Hankel matrix, more proper one can be determined considering the computational cost of subspace identification. The stiffness matrix and flexural rigidities are estimated using the Hankel matrix with the candidate sizes. The validity of the proposed method is demonstrated through the numerical example of a five-story shear building model with and without damage.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.567-578
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• 2018

In this study, to investigate the effect of the stress reduction of group piles by dynamic loading, a dynamic p-y curve was established and the dynamic p-multiplier was calculated. Dynamic numerical analysis was performed by input sinusoidal waves to the bottom of the pile - ground system for $2{\times}2$ group pile, single pile and $5{\times}5$ group pile, single pile in dry sandy soil, and the pile spacing was changed to 2.5 and 5.0 times of the pile diameter. By establishing and comparing the dynamic p-y curves of the single pile and group piles, the dynamic group pile effect of the piles according to the pile center spacing and row position of the group pile piles is analyzed. $5{\times}5$ showed symmetry of the dynamic P-multiplier value around the pile origin coordinate. The dynamic p-multiplier value at the single pile, $5{\times}5$ pile (pile spacing: 2.5D) is 0.26 ~ 0.30 at the pile number 3, pile number 23, 0.14 pile number 13, and 0.14 ~ 0.38 at the pile number 5, pile number 18. These values differed from the static p-multiplier, especially due to the different loading conditions. The dynamic p-multiplier ($P_{dm}$) estimation through various types of input dynamic loads is expected to be used for dynamic design and analysis of group pile-ground systems of civil foundation structures.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.2
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• pp.1-8
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• 2001

In this paper, we propose an algorithm which estimates the displacements and velocities of objects in the soccer field from the soccer image sequences. Assuming the time interval of an object movement is given, we transform the object positions into those in the soccer field model and compute the distance and the velocity. When four corresponding pairs of the feature points, such as the crossing points of the lines in the soccer field, exist and three of them are not on a line, we transform the object positions in the soccer image into those in the soccer field by using the perspective displacement field model. In addition, when the soccer image has less than four feature points, we first transform the object positions into those in the image which has more than four feature points, and then transform the positions into those in the soccer field again. To find the coordinate transformation between two images, we estimate the panning and zooming for consecutive images in the sequence. In the experimental results, we quantitatively evaluated the estimation accuracy by applying our algorithm to the synthetic. soccer image sequences generated by graphic tools, and applied it to the real soccer image sequences for broadcasting to show its usefulness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.156-165
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• 2006

In this paper, a new intelligent moving target tracking and surveillance system basing on the pan/tilt-embedded stereo camera system is suggested and implemented. In the proposed system, once the face area of a target is detected from the input stereo image by using a YCbCr color model and phase-type correlation scheme and then, using this data as well as the geometric information of the tracking system, the distance and 3D information of the target are effectively extracted in real-time. Basing on these extracted data the pan/tilted-imbedded stereo camera system is adaptively controlled and as a result, the proposed system can track the target adaptively under the various circumstance of the target. From some experiments using 480 frames of the test input stereo image, it is analyzed that a standard variation between the measured and computed the estimated target's height and an error ratio between the measured and computed 3D coordinate values of the target is also kept to be very low value of 1.03 and 1.18$\%$ on average, respectively. From these good experimental results a possibility of implementing a new real-time intelligent stereo target tracking and surveillance system using the proposed scheme is finally suggested.