• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.2
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• pp.105-112
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• 2018

To determine the position of receiver, the GPS (Global Positioning System) uses position information of satellites and pseudo ranges based on signals. These are reflected by surrounding structures and multipath errors occur. This paper proposes a method for multipath error reduction using digital images to enhance the accuracy. The goal of the study is to calculate the shielding environment of receiver using image processing and apply it to GPS positioning. The proposed method, firstly, performs a preprocessing to reduce the effect of noise on images. Next, it uses hough transform to detect the outline of building roofs and determines mask angles and permissible azimuth range. Then, it classifies the satellites according to the condition using the image processing results. Finally, base on point positioning, it computes the receiver position by applying a weight model that assigns different weights to the classified satellites. We confirmed that the RMSE (Root Mean Square Error) was reduced by 2.29m in the horizontal direction and by 15.62m in the vertical direction. This paper showed the potential for the hybrid of GPS positioning and image processing technology.

• Journal of Internet Computing and Services
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• v.14 no.5
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• pp.49-57
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• 2013

A novel approach for the feature selection is proposed, which is the important preprocessing task of on-line document classification. In previous researches, the features based on information from their single population for feature selection task have been selected. In this paper, a mixed feature set is constructed by selecting features from multi-population as well as single population based on various information. The mixed feature set consists of two feature sets: the original feature set that is made up of words on documents and the transformed feature set that is made up of features generated by LSA. The hybrid feature selection method using both filter and wrapper method is used to obtain optimal features set from the mixed feature set. We performed classification experiments using the obtained optimal feature sets. As a result of the experiments, our expectation that our approach makes better performance of classification is verified, which is over 90% accuracy. In particular, it is confirmed that our approach has over 90% recall and precision that have a low deviation between categories.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.29-37
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• 2015

In this paper, we propose a robust pre-processing module for camera-based Optical Music Score Recognition (OMR) on mobile device. The captured images likely suffer for recognition from many distortions such as illumination, blur, low resolution, etc. Especially, the complex background music sheets recognition are difficult. Through any symbol recognition system, the staff line height and staff line space are used many times and have a big impact on recognition module. A robust and accurate staff line height and staff line space are essential. Some staff line height and staff line space are proposed for binary image. But in case of complex background music sheet image, the binarization results from common binarization algorithm are not satisfactory. It can cause incorrect staff line height and staff line space estimation. We propose a robust staff line height and staff line space estimation by using run-length encoding technique on edge image. Proposed method is composed of two steps, first step, we conducted the staff line height and staff line space estimation based on edge image using by Sobel operator on image blocks. Each column of edge image is encoded by run-length encoding algorithm Second step, we detect the staff line using by Stable Path algorithm and removal the staff line using by adaptive Line Track Height algorithm which is to track the staff lines positions. The result has shown that robust and accurate estimation is possible even in complex background cases.

• Atmosphere
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• v.28 no.2
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• pp.113-121
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• 2018

In order to monitor greenhouse gases including $CO_2$, various types of surface-, aircraft-, and satellite-based measurement projects have been conducted. These data help understand the variations of greenhouse gases and are used in atmospheric inverse modeling systems to simulate surface fluxes for greenhouse gases. CarbonTracker is a system for estimating surface $CO_2$ flux, using an atmospheric inverse modeling method, based on only surface observation data. Because of the insufficient surface observation data available for accurate estimation of the surface $CO_2$ flux, additional observations would be required. In this study, a system that assimilates aircraft $CO_2$ measurement data in CarbonTracker (CT2013B) is developed, and the estimated results from this data assimilation system are evaluated. The aircraft $CO_2$ measurement data used are obtained from the Comprehensive Observation Network for Trace gases by the Airliner (CONTRAIL) project. The developed system includes the preprocessor of the raw observation data, the observation operator, and the ensemble Kalman filter (EnKF) data assimilation process. After preprocessing the raw data, the modeled value corresponding spatially and temporally to each observation is calculated using the observation operator. These modeled values and observations are then averaged in space and time, and used in the EnKF data assimilation process. The modeled values are much closer to the observations and show smaller biases and root-mean-square errors, after the assimilation of the aircraft $CO_2$ measurement data. This system could also be used to assimilate other aircraft $CO_2$ measurement data in CarbonTracker.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.183-191
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• 2014

This paper describes the development of the observational data transmission algorithm for high-speed network in radio astronomy. For the preprocessing of VLBI data observed by radio telescope, data transmission algorithm uses the VDIF specification, VDIFCP, and UDP protocol by transferring VLBI data stored in a massive storage server with one-to-one correspondence between the server and the RVDB of Daejeon correlator. A transmission method is proposed, which reads the recorded data in Mark5B VSI format and trnasmits 2048 Mbps VLBI data by software through UDP packet transmission, while RVDB system is waiting for the transmitting data from the server. In order to check the effectiveness of the proposed method, the data transmission between the massive storage server and RVDB is conducted and the transmitted data is correlated by Daejeon correlator for the accurate comparison concerning the data before and after. The transmitted data is shown to be completely the same as the original data without any data transmission loss. Henceforth, the developed data transmission algorithm in this research is expected to be applied effectively as e-VLBI for KaVA network.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.4
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• pp.87-98
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• 2011

Detecting a moving object from videos and tracking it are basic and necessary preprocessing steps in many video systems like object recognition, context aware, and intelligent visual surveillance. In this paper, we propose a method that is able to detect a moving object quickly and accurately in a condition that background and light change in a real time. Furthermore, our system detects strongly an object in a condition that the target object is covered with other objects. For effective detection, effective Eigen-space and FCM are combined and employed, and a CONDENSATION algorithm is used to trace a detected object strongly. First, training data collected from a background image are linear-transformed using Principal Component Analysis (PCA). Second, an Eigen-background is organized from selected principal components having excellent discrimination ability on an object and a background. Next, an object is detected with FCM that uses a convolution result of the Eigen-vector of previous steps and the input image. Finally, an object is tracked by using coordinates of an detected object as an input value of condensation algorithm. Images including various moving objects in a same time are collected and used as training data to realize our system that is able to be adapted to change of light and background in a fixed camera. The result of test shows that the proposed method detects an object strongly in a condition having a change of light and a background, and partial movement of an object.

• Geophysics and Geophysical Exploration
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• v.16 no.1
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• pp.6-17
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• 2013

Multicomponent seismic data including both P- and PS-waves have advantages in discriminating the type of pore fluid, characterizing the lithologic attributes and producing the high resolution image. However, multicomponent seismic data recorded at the vertical and horizontal component receivers contain both P- and PS-waves which have different features, simultaneously. Therefore, the wavefield separation of P- and PS-waves as a preprocessing is inevitable in order to use the multicomponent seismic data successfully. In this study, we analyzed the previous study of the wavefield separation method suggested by Jeong and Byun in 2011, where the approximated reflection angle calculated only from one refernce depth is used in rotation transform, and showed its limitation for seismic data containing various reflected events from the multi-layered structure. In order to overcome its limitation, we suggested a new effective wavefield separation method of P- and PS-waves. In new method, we calculate the reflection angles with various reference depths and apply rotation transforms to the data with those reflection angles. Then we stack all results to obtain the final separated data. To verify our new method, we applied it to the synthetic data sets from a multi-layered model, a fault model, and the Marmousi-2 model. The results showed that the proposed method separated successfully P- and PS-reflection events from the multicomponent data from mild dipping layered model as long as the dip is not too steep.

• 한국지구물리탐사학회:학술대회논문집
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• 2008.10a
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• pp.107-112
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• 2008

In the case of the deep reservoirs like the gas reservoirs in the East-sea, it is often difficult to observe AVO responses in CMP gathers. Because the reservoir becomes more consolidated as its depth deepens, P-wave velocity does not decrease significantly when the pore fluid is replaced by the gas. In this study, we analyzed the effects of Poisson's ratio difference on AVO response with a variety of Poisson's ratios for the upper and lower layers. The results show that, as the difference in Poisson's ratio between the upper and lower layers decreases, the change in the reflection amplitude with incidence angle decreases. To consider the limitation of AVO responses shown in the gas reservoir in East-sea, the velocity model was made by simulation Gorae V structure with seismic data and well logs. The results of comparing AVO responses observed from the synthetic data with theoretical AVO responses calculated by using material properties show that the amount of the change in reflection amplitude with increasing incident angle is very small when the difference in Poisson's ratio between the upper and lower layers is small. In addition, the characteristics of AVO responses were concealed by noise or amplitude distortion arisen during preprocessing. To overcome such limitations of AVO analysis of the data from deep reservoirs, we need to acquire precisely reflection amplitudes in data acquisition stage and use processing tools which preserve reflection amplitude in data processing stage.

• Korean Journal of Medicinal Crop Science
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• v.16 no.6
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• pp.446-454
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• 2008

An advanced extraction method by ultrasonic extraction with applied solid phase extraction (SPE) has been developed for the determination of simultaneous eight major ginsenosides, namely ginsenosides Rg1, Re, Rf, Rb1, Rg2, Rc, Rb2, and Rd in the root of Panax ginseng. Four extraction methods including n-BuOH reflux extraction (Method A), 70% EtOH reflux extraction (Method B), 50% MeOH reflux extraction with SPE (Method C), and 50% MeOH ultrasonication with SPE clean-up process (Method D) were investigated for the determination of eight major ginsenosides. Total contents of ginsenosides were highest by extraction of Method C as $2.408{\pm}0.011%$. However, Method D was evaluated as relatively simpler and more efficient method due to short extraction time, small solvent consumption and less expensive, compared to conservative reflux method. Ginsenosides were also satisfactorily separated with good resolution and the accuracy range was between 1.05 and 4.06% as relative standard deviation (RSD) by Method D. SPE condition and HPLC condition were further optimized for determination of eight major ginsenosides by the ultrasonic extraction method. Conclusively, ultrasonic extraction of 2 g sample of ginseng using ultrasonic bath and 1 loading for SPE was evaluated as proper condition for extraction of ginseng.

• Clean Technology
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• v.17 no.3
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• pp.215-224
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• 2011

It is an important issue to develop quality assessing system for biofuel for the purpose of accelerating the mass production of biofuel. It is particularly challenging to conduct testing method in the mass production of bioethanol while meeting quality specifications such as ASTM (American Society for Testing & Materials) D4806-10. In order to address this challenge, this paper proposes on-line spectroscopic quality assesment system based on Near Infrared spectrum and Partial Least Squares method in Chemometrics. As a result of testing a number of preprocessing methods and Partial Least Squares, it was found out that Savitzky-Golay method showed the best performance in terms of spectrum correction, noise reduction, and model maintenance. The proposed system allows us to assess multiple quality components continuously using spectroscopic facilities with the cheap cost. Since the value of R2 is more than 0.99, it is possible to replace the laboratory analysis.