• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.2
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• pp.41-45
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• 2006

To get accurate positions of GPS antennas, one should apply phase center variations (PCV) corrections in the data processing. Until recently, relative calibrations, originally proposed by National Geodetic Survey of United States, were the international standard. However, in late 2006, International GNSS Service will switch to absolute calibration methods. In this study, we compared the position differences caused by different PCV models, and their effects on the calculations of Precipitable Water Vapor (PWV) in the atmosphere. Data from ${\sim}40$ permanent GPS stations in Korea were processed and we found that the vertical position differences reach up to 5 cm, depending on the model selected. Also the PWV values varied quite significantly: the maximum bias in the computed PWV values was ${\sim}4$ mm.

• 한국항공우주학회지
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• 제45권7호
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• pp.531-538
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• 2017

비행속력 및 받음각과 옆미끄럼각을 측정할 수 있는 플러시 대기자료측정장치를 소형의 무인항공기를 대상으로 설계/제작하였다. 동체 노즈콘 표면에 4개 압력 측정점과 5개 압력 측정점의 2가지 타입으로 플러시 압력공들을 만들었다. 플러시 압력공의 교정 압력 데이터는 전기체를 전산유체해석 코드로 계산하여 구축하였다. 교정압력 데이터로부터 받음각, 옆미끄럼각, 전압계수, 정압계수는 4차 다항식으로 표현하고, 최소자승법으로 교정계수 행렬을 구하였다. 비행시험 결과 4개 플러시 압력공 및 5개 플러시 압력공을 이용하여 예측된 비행속력, 받음각과 옆미끄럼각은 비교를 위해 장착한 5-압력공 프로브로 예측된 것과 잘 일치하였으며, 특히 4개의 압력공으로 5개 압력공과 거의 동일한 결과를 얻을 수 있었다.

• 한국작물학회지
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• 제56권1호
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• pp.88-93
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• 2011

This experiment was carried out to find suitable sample type for the more accurate prediction and non-destructive way in the application of near infrared reflectance spectroscopy (NIRS) technique for estimation the protein, total amino acids, and total isoflavone of soybean by comparing three different sample types, single seed, whole seeds, and milled seeds powder. The coefficient of determination in calibration ($R^2$) and coefficient of determination in cross-validation (1-VR) for three components analyzed using NIRS revealed that milled powder sample type yielded the highest, followed by single seed, and the whole seeds as the lowest. The coefficient of determination in calibration for single seed was moderately low($R^2$ 0.70-0.84), while the calibration equation developed with NIRS data scanned with whole seeds showed the lowest accuracy and reliability compared with other sample groups. The scatter plot for NIRS data versus the reference data of whole seeds showed the widest data cloud, in contrary with the milled powder type which showed flatter data cloud. By comparison of NIRS results for total isoflavone, total amino acids, and protein of soybean seeds with three sample types, the powder sample could be estimated for the most accurate prediction. However, based from the results, the use of single bean samples, without grinding the seeds and in consideration with NIRS application for more nondestructive and faster prediction, is proven to be a promising strategy for soybean component estimation using NIRS.

• 한국자동차공학회논문집
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• 제16권6호
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• pp.104-108
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• 2008

Recently, studies conducted by our research group, revealed the possibility for reducing BSFC, NOx and PM emissions to meet the Euro 4 & 5 legislations. The main objective of the present study is to get better fuel economy in commercial vehicles by considering real driving conditions. Firstly, in order to improve fuel economy on fields, specifically it is required to analyze the driving pattern and make the representative modes from real field data. Secondly, it is performed to make the engine dynometer test to optimize the fuel consumption by reflecting on the representative driving modes, based on the Korea 2008 emission legislation equal to the Euro 4. The engine components such as engine calibration, combustion chamber, turbocharger and ancilliaries were modified to optimize vehicle fuel economy over a typical customer drive cycle whilst still meeting the exhaust emission restrictions. Finally, these results were confirmed by field testing of vehicle equipped with the updated calibration engine. It was placed the two vehicles together traveling the same route and accomplishing the same amount of stops(back to back), in order to evaluate the fuel consumption in comparison to the current vehicle. Through several repeats such as the engine calibration and field test, we could get 3 % to 7.7 % vehicle fuel economy improvements compared to previous vehicle.

• 대한원격탐사학회지
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• 제37권1호
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• pp.169-176
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• 2021

The Global Space-based Inter-Calibration System (GSICS) is an international partnership sponsored by World Meteorological Organization (WMO) to continue and improve climate monitoring and to ensure consistent accuracy between observation data from meteorological satellites operating around the world. The objective for GSICS is to inter-calibration from pairs of satellites observations, which includes direct comparison of collocated Geostationary Earth Orbit (GEO)-Low Earth Orbit (LEO) observations. One of the GSICS inter-calibration methods, the Ray-matching technique, is a surrogate approach that uses matched, co-angled and co-located pixels to transfer the calibration from a well calibrated satellite sensor to another sensor. In Korea, the first GEO satellite, Communication Ocean and Meteorological Satellite (COMS), is used to participate in the GSICS program. The National Meteorological Satellite Center (NMSC), which operated COMS/MI, calculated the Radiative Transfer Model (RTM)-based GSICS coefficient coefficients. The L1P reproduced through GSICS correction coefficient showed lower RMSE and Bias than L1B without GSICS correction coefficient applied. The calculation cycles of the GSICS correction coefficients for COMS/MI visible channel are provided annual and diurnal (2, 5, 10, 14-day), but long-term evaluation according to these cycles was not performed. The purpose of this paper is to perform evaluation depending on the annual/diurnal cycles of COMS/MI GSICS correction coefficients based on the ray-matching technique using Suomi-NPP/Visible Infrared Imaging Radiometer Suite (VIIRS) data as reference data. As a result of evaluation, the diurnal cycle had a higher coincidence rate with the reference data than the annual cycle, and the 14-day diurnal cycle was the most suitable for use as the GSICS correction coefficient.

• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1141-1141
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• 2001

The aim of the study was to evaluate the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural network (ANN) on the prediction of chemical composition of forages, using a large NIR database. The study used forage samples (n=25,977) from Australia, Europe (Belgium, Germany, Italy and Sweden) and North America (Canada and U.S.A) with information relative to moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected with 10 different Foss NIR Systems instruments, which were either standardized or not standardized to one master instrument. The spectra were trimmed to a wavelength range between 1100 and 2498 nm. Two data sets, one standardized (IVAL) and the other not standardized (SVAL) were used as independent validation sets, but 10% of both sets were omitted and kept for later expansion of the calibration database. The remaining samples were combined into one database (n=21,696), which was split into 75% calibration (CALBASE) and 25% validation (VALBASE). The chemical components in the 3 validation data sets were predicted with each model derived from CALBASE using the calibration database before and after it was expanded with 10% of the samples from IVAL and SVAL data sets. Calibration performance was evaluated using standard error of prediction corrected for bias (SEP(C)), bias, slope and R2. None of the models appeared to be consistently better across all validation sets. VALBASE was predicted well by all models, with smaller SEP(C) and bias values than for IVAL and SVAL. This was not surprising as VALBASE was selected from the calibration database and it had a sample population similar to CALBASE, whereas IVAL and SVAL were completely independent validation sets. In most cases, Local and ANN models, but not modified PLS, showed considerable improvement in the prediction of IVAL and SVAL after the calibration database had been expanded with the 10% samples of IVAL and SVAL reserved for calibration expansion. The effects of sample processing, instrument standardization and differences in reference procedure were partially confounded in the validation sets, so it was not possible to determine which factors were most important. Further work on the development of large databases must address the problems of standardization of instruments, harmonization and standardization of laboratory procedures and even more importantly, the definition of the database population.

• 한국해양학회지:바다
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• 제9권4호
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• pp.204-211
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• 2004

자동 수직물성관측 뜰개는 매우 유용한 해양관측장비이지만 이에 부착된 CTD의 사후 보정이 불가능하기 때문에 뜰개자료의 정확도 검증이 사후자료관리나 자료활용에 있어 중요한 문제 중 하나이다. 동해 중심층의 염분변화가 국제 Argo프로그램에서 요구하는 정확도 0.01과 유사하기 때문에 동해를 항염분수조로 취급하여 동해에 투하된 뜰개가 관측한 염분자료의 신뢰성을 세 가지 방법을 통하여 검증하였다. 각각의 방법은 1)부근 해역에서 얻은 정확도가 높은 정선 CTD자료와 뜰개자료의 비교, 2)비슷한 시각에 비슷한 해역에서 얻은 뜰개자료의 비교, 3)체류 수심에서 얻은 염분자료의 장기간에 걸친 안정도 및 정확도 검증이다. 세 방법 모두 뜰개에서 얻은 염분자료가 아무런 보정없이도 Argo프로그램이 요구하는 정확도를 만족함을 보여주었다. 동해의 심층 수온이 일정하다는 가정하에 위의 세 가지 방법을 적용하여 얻은 수온값의 정확도 0.01$^{\circ}C$는 Argo프로그램에서 요구하는 정확도의 2배 정도이다. 하지만 동해의 중층 수온은 Argo프로그램이 요구하는 정확도 이상으로 시공간적으로 변화하기 때문에, 위의 결과는 수온 자료가 부정확하다는 것을 의미하지는 않는다. 동해 중층수온의 시공간적 변화를 고려한다면 수온자료의 정확도도 Argo프로그램이 요구하는 것과 큰 차이가 없다고 할 수 있다. 따라서 이 연구에서 검증된 뜰개가 관측한 수온 염분자료 모두 특별한 보정 없이 사용할 수 있다.

• 한국자동차공학회논문집
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• 제24권3호
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• pp.365-371
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• 2016

The electromechanical brake (EMB) is one of future brake systems due to its many advantages. For implementation of the EMB, the correct feed back about clamping force is necessary. Keeping commercialization of the EMB in mind, it is strongly demanded that an expensive load cell measuring the clamping force is replaced with an estimation algorithm. In addition, an estimation of the kissing point where the brake pads start to come into contact with a disk wheel is proposed in this paper. With these estimation algorithms, the clamping force can be expressed as a polynomial characteristic curve versus the motor angle. Also, a method for calibration of measured values by the load cell is proposed and used for an actual characteristic curve. Lastly, the performance of the proposed algorithms is evaluated in comparison with the actual curve on a developed EMB test bench.

• 환경영향평가
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• 제20권5호
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• pp.765-777
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• 2011

According to the total pollution load management system, exact prediction and analysis of water quality and discharge has been required in order to allocate the amount of pollution load to each local government. In this study, QUAL2E model was used for comparison with other water quality models and improve the inadequate to forecast future water quality. And Various calibration and verification methods were applied to deal with existing uncertainties of parameter during modeling water quality. For user convenience, A GUI(Graphical User Interface) system named "QL2-XP" model is developed by object-oriented language for the user convenience and practical usage. Suggested GUI system consist of hydraulic analysis, water quality analysis, optimized model calibration processes, and postprocessing the simulation results. Therefore this model will be effectively utilized to manage practical and efficient water quality.

• Journal of Biosystems Engineering
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• 제32권4호
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• pp.256-262
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• 2007

Image processing systems have been used to measure the plant parameters such as size, shape and structure of plants. There are yet some limited applications for evaluating plant colors due to illumination conditions. This study was focused to present adaptive methods to analyze plant leaf color regardless of illumination conditions. Color patches attached on the calibration bars were selected to represent leaf colors of lettuces and to test a possibility of health monitoring of lettuces. Repeatability of assigning leaf colors to color patches was investigated by two-tailed t-test for paired comparison. It resulted that there were no differences of assignment histogram between two images of one lettuce that were acquired at different light conditions. It supported that use of the calibration bars proposed for leaf color analysis provided color constancy, which was one of the most important issues in a video color analysis. A health discrimination equation was developed to classify lettuces into one of two classes, SOUND group and POOR group, using the machine vision. The classification accuracy of the developed health discrimination equation was 80.8%, compared to farmers' decision. This study could provide a feasible method to develop a standard color chart for evaluating leaf colors of plants and plant health monitoring system using the machine vision.