• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.315-319
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• 2007

A technique to model plasma processes was presented. This was accomplished by combining the backpropagation neural network (BPNN) and genetic algorithm (GA). Particularly, the GA was used to optimize five training factor effects by balancing the training and test errors. The technique was evaluated with the plasma etch data, characterized by a face-centered Box Wilson experiment. The etch outputs modeled include Al etch rate, AI selectivity, DC bias, and silica profile angle. Scanning electron microscope was used to quantify the etch outputs. For comparison, the etch outputs were modeled in a conventional fashion. GABPNN models demonstrated a considerable improvement of more than 25% for all etch outputs only but he DC bias. About 40% improvements were even achieved for the profile angle and AI etch rate. The improvements demonstrate that the presented technique is effective to improving BPNN prediction performance.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.339-341
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• 2006

This paper proposes a method of container position measurement using automatic landing system that is estimated by a laser range finder. In the most of container position measurement methods, CCD cameras or laser scanners have been used to get the source data. However those sensors are not only weak for disturbances, for examples, the light, fog, and rain, but also the system cost is high. When the spreader arrives the goal position, it is still swung by inertia or by wind effect. In this paper, the spreader swung data have been used to find the container position. The laser range finder is equipped in the front side of spreader. It can measure distance and relative position between spreader and container. This laser range finder can be rotated as desired by a motor. And a tilt sensor is equipped on the spreader to measure spreader sway. We estimate the relative position information between the spreader and a container using the laser range finder and tilt sensor through the geometrical analysis.

• 한국전산유체공학회:학술대회논문집
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• 2002.05a
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• pp.88-93
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• 2002

In the present research, a parametric study of aerodynamic characteristics for multi-element airfoils is performed. The major geometric parameters of interest are the gap distance between airfoils and relative deflection angle of slat/flap. The present results are mainly obtained by using inviscid flow calculation, and the aerodynamic characteristics are focused on the surface pressure distribution and the lifts. The results of the present research may be used as not only qualitative data but also quantitative data for small angle of attack flows, where the viscous effect does not play major role in terms of surface pressure distribution and lifts. A further research in this subject including viscous calculation and more geometric parameters is to be performed in the future.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.10
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• pp.825-831
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• 2017

Radar clutter in real environment is in general heterogeneous and especially nonstationary if radar geometry is of non-sidelooking monostatic structure or bistatic structure. These clutter properties lead to the insufficient number of secondary data of IID(Independent identically distributed) property, conclusively deteriorate clutter suppression performance. In this paper, we propose a clutter suppression algorithm that estimates the clutter signal belonging to cull under test via calculation using only prior information, rather than using the secondary data. Through analyzing the angle-Doppler spectrum of the clutter signal, we show the estimation of the clutter signal using prior information only is possible and present the derivation of a clutter suppression algorithm through eigen-value analysis. Finally, we show the performance of the proposed algorithm by simulation.

• Korean Journal of Remote Sensing
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• v.22 no.2
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• pp.111-121
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• 2006

The classification using spectral angle is a new approach based on the fact that the spectra of the same type of surface objects in RS data are approximately linearly scaled variations of one another due to atmospheric and topographic effects. There are many researches on the unsupervised classification using spectral angle recently. Nevertheless, there are only a few which consider the characteristics of Hyperspectral data. On this study, we propose the ISOMUSAC(Iterative Self-Organizing Modified Unsupervised Spectral Angle Classification) which can supplement the defects of previous unsupervised spectral angle classification. ISOMUSAC uses the Angle Division for the selection of seed points and calculates the center of clusters using spectral angle. In addition, ISOMUSAC perform the iterative merging and splitting clusters. As a result, the proposed algorithm can reduce the time of processing and generate better classification result than previous unsupervised classification algorithms by visual and quantitative analysis. For the comparison with previous unsupervised spectral angle classification by quantitative analysis, we propose Validity Index using spectral angle.

• 전기의세계
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• v.19 no.2
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• pp.12-17
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• 1970

In the design of electrical equipment insulation, it is customary to place pressboard and other insulating material at right angle to the electrical discharge path, which is based on the insulation tests performed on equipment under various conditions such as types of insulation, applied voltage and other unique situations. Since electrical equipment manufacturing started only recently, there is a scarcity of available data on insulation problems, which make it difficult for the design engineers. The author untook this study to provide such analytical design data for various conditions based on the experiment conducted on the equipment being manufactured, thus reducing possible errors in the process.

• Journal of Fisheries and Marine Sciences Education
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• v.21 no.1
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• pp.59-67
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• 2009

It is necessary for navigator to understand sufficiently maneuverabilities based on experiences and the data which were gotten from several tests of the ship when he maneuver his vessel. By the way most navigators used to rely on his experiences or feelings only maneuvering ship. But when he encounters situations he did not experience before he may be in difficulties. So navigator must get both experiences and data based on experimental results. In this paper author performs several tests such as turning test, Zig-zag test and spiral test to provide informations of maneuverabilities for navigators. The obtained results are as follows: There occurs almost no difference in size of the turning circle by the changes of ship's speeds. The scale of the turning circle was decreased exponentially when the rudder angle was increased. The maneuverabilities is better turning to starboard side than to port side. Maneuverabilities are more effective when the rudder is used to small angle than to large angle. As a result of spiral test course stability was comparatively seemed to be good.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.243-250
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• 2012

This paper proposes a 3D map-building algorithm using one LRF (Laser Range Finder) while a mobile robot is navigating on the slanted surface. There are several researches on 3D map buildings using the LRF. However most of them are performing the map building only on the flat surface. While a mobile robot is moving on the slanted surface, the view angle of LRF is dynamically changing, which makes it very difficult to build the 3D map using encoder data. To cope with this dynamic change of the view angle in build 3D map, IMU and balance filters are fused to correct the unstable encoder data in this research. Through the real navigation experiments, it is verified that the fusion of multiple sensors are properly performed to correct the slope angle of the slanted surface. The effectiveness of the balance filter are also checked through the hill climbing navigations.

• Journal of Astronomy and Space Sciences
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• v.37 no.4
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• pp.219-228
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• 2020

A CubeSat platform has become a popular choice due to inexpensive commercial off-the-shelf (COTS) components and low launch cost. However, it requires more power-efficient and higher-data rate downlink capability for space applications related to remote sensing. In addition, the platform is limited by the size, weight and power (SWaP) constraints as well as the regulatory issue of licensing the radio frequency (RF) spectrum. The requirements and limitations have put optical communications on promising alternatives to RF communications for a CubeSat platform, owing to the power efficiency and high data rate as well as the license free spectrum. In this study, we analyzed the performance of optical downlink communications compatible with CubeSat platforms in terms of data rate, bit error rate (BER) and outage probability. Mathematical models of BER and outage probability were derived based on not only the log-normal model of atmospheric turbulence but also a transmitter with a finite extinction ratio. Given the fixed slot width, the optimal guard time and modulation orders were chosen to achieve the target data rate. And the two performance metrics, BER and outage data rate, were analyzed and discussed with respect to beam divergence angle, scintillation index and zenith angle.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.111-126
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• 2022

Land use and land cover (LULC) mapping is an important factor in geospatial analysis. Although highly precise ground-based LULC monitoring is possible, it is time consuming and costly. Conversely, because the synthetic aperture radar (SAR) sensor is an all-weather sensor with high resolution, it could replace field-based LULC monitoring systems with low cost and less time requirement. Thus, LULC is one of the major areas in SAR applications. We developed a LULC model using only KOMPSAT-5 single co-polarized data and digital elevation model (DEM) data. Twelve HH-polarized images and 18 VV-polarized images were collected, and two HH-polarized images and four VV-polarized images were selected for the model testing. To train the LULC model, we applied the conditional generative adversarial network (cGAN) method. We used U-Net combined with the residual unit (ResUNet) model to generate the cGAN method. When analyzing the training history at 1732 epochs, the ResUNet model showed a maximum overall accuracy (OA) of 93.89 and a Kappa coefficient of 0.91. The model exhibited high performance in the test datasets with an OA greater than 90. The model accurately distinguished water body areas and showed lower accuracy in wetlands than in the other LULC types. The effect of the DEM on the accuracy of LULC was analyzed. When assessing the accuracy with respect to the incidence angle, owing to the radar shadow caused by the side-looking system of the SAR sensor, the OA tended to decrease as the incidence angle increased. This study is the first to use only KOMPSAT-5 single co-polarized data and deep learning methods to demonstrate the possibility of high-performance LULC monitoring. This study contributes to Earth surface monitoring and the development of deep learning approaches using the KOMPSAT-5 data.