• Bulletin of the Korean Space Science Society
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• 2010.04a
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• pp.28.4-29
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• 2010

이 연구는 심우주 추적망(Deep Space Network) 측정 시스템의 구현을 위한 한국형 심우주 항법 예비 소프트웨어(Korean Deep Space Orbit Determination Program version 1; K-DSODP ver.1)의 개발을 목표로 한다. 연구의 주 내용은 심우주 항법을 위한 기초 기술 연구로 지구로부터 달까지 진행하는 탐사선의 궤적 추정에 대한 것이며, 연구의 시작에 앞서 사용될 관측 데이터를 얻기 위해 한국형 심우주 항법 관측데이터 생성 소프트웨어(Korean Deep Space Observation Data Generation Program version 1; K-DSODGP ver.1)를 개발하여 사용하였다. 임의의 잡음이 추가된 가상의 관측 데이터를 생성한 후, 이 관측 데이터를 실제 궤도로 상정하여 기하학적인 관측 모델을 수립하였고, 일정한 시간 간격동안 모은 임의의 관측 데이터를 가지고 궤도 결정을 수행하여 추정된 궤도를 전파하였다. 궤도 결정 알고리즘을 구성하기 위해 기본적인 좌표계, 탐사선에 미치는 지구의 중력에 대한 동역학 모델, 천체력과 탐사선의 동역학 모델로 구성된 관측 모델들을 유도하였으며, 탐사선의 위치와 속도를 추정하는 과정에서 가중치 최소 자승법을 적용하여 추정 궤도와 실제 궤도의 최소화를 유도하였다. 이러한 일련의 과정을 통해 요구한 시각의 탐사선의 위치와 속도를 결정하는 궤도결정 시스템을 구현하였고, 궤도 결정 시스템의 성능을 평가하기 위해 전파된 궤도와 실제 궤도의 차이를 분석하였다. 결과적으로 300초마다 관측데이터를 받을 경우, 2일 이상의 궤도결정 시간간격을 상정했을 때 평균 오차는 각각 약 0.26km RMS(range), 6.84km/s RMS(range-rate) 이내의 결과를 얻었고, 600초마다 관측데이터를 받을 경우, 평균 오차는 각각 약 0.30km RMS (range), 6.35km/s RMS(range-rate) 이내의 안정적인 결과를 얻었다. 이 연구의 결과를 통하여 추후 심화된 심우주 항법 소프트웨어 개발을 위한 기반이 마련될 것이다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.822-828
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• 2002

Optical flow estimation based on multi constraint approaches is frequently used for recognition of moving objects. However, the use have been confined because of OF estimation time as well as error problem. This paper shows a new method form effectively extracting movement information using the multi-constraint base approaches with sobel edge detection. The moving objects anr extraced in the input image sequence using edge detection and segmentation. Edge detection and difference of the two input image sequence gives us the moving objects in the images. The process of thresholding removes the moving objects detected due to noise. After thresholding the real moving objects, we applied the Combinatorial Hough Transform (CHT) and voting accumulation to find the optimal constraint lines for optical flow estimation. The moving objects found in the two consecutive images by using edge detection and segmentation greatly reduces the time for comutation of CHT. The voting based CHT avoids the errors associated with least squares methods. Calculation of a large number of points along the constraint line is also avoided by using the transformed slope-intercept parameter domain. The simulation results show that the proposed method is very effective for extracting optical flow vectors and hence recognizing moving objects in the images.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.125-134
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• 2021

With the rapid development of the film industry, the number of films is significantly increasing and movie recommendation system can help user to predict the preferences of users based on their past behavior or feedback. This paper proposes a movie recommendation system based on the latent factor model with the adjustment of mean and bias in rating. Singular value decomposition is used to decompose the rating matrix and stochastic gradient descent is used to optimize the parameters for least-square loss function. And root mean square error is used to evaluate the performance of the proposed system. We implement the proposed system with Surprise package. The simulation results shows that root mean square error is 0.671 and the proposed system has good performance compared to other papers.

• Food Science of Animal Resources
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• v.31 no.1
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• pp.115-121
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• 2011

The objective of this study was to develop models to predict freshness factors (total viable counts (TVC), pH, volatile basic nitrogen (VBN), trimethylamine (TMA), and thiobarbituric acid (TBA) values) and the storage period in beef using a visible and near-infrared (NIR) spectroscopic technique. A total of 216 beef spectra were collected during the storage period from 0 to 14 d at a $10^{\circ}C$ storage. A spectrophotometer was used to measure reflectance spectra from beef samples, and beef freshness spectra were divided into a calibration set and a validation set. Multi-linear regression (MLR) models using the stepwise method were developed to predict the factors. The MLR results showed that beef freshness had a good correlation between the predicted and measured factors using the selected wavelength. The correlation of determination ($r^2$), standard error of prediction (SEP), and ratio of standard deviation to SEP (RPD) of the prediction set for TVC was 0.74, 0.64, and 2.75 Log CFU/$cm^2$, respectively. The $r^2$, SEP, and RPD values for pH were 0.43, 0.10, and 1.10; those for VBN were 0.73, 1.45, and 2.00 mg%; those for TMA were 0.70, 0.19, and 2.58 mg%; those for TBA values were 0.73, 0.13, and 2.77 mg MA/kg; and those for storage period were 0.77, 1.94, and 2.53 d, respectively. The results indicate that visible and NIR spectroscopy can predict beef freshness during storage.

• The Transactions of the Korean Institute of Power Electronics
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• v.14 no.5
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• pp.372-378
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• 2009

With the increase in capacity of photovoltaic generation systems, studies are being actively conducted to improve system efficiency. In order to develop the high performance photovoltaic power system it is required to understand the physical characteristics of the solar cell. However, solar cell models have a non-linear form with many parameters entangled and conventional methods suggested to extract the parameters of the solar cell model require some kind of assumptions, which accompanies the calculation errors, thereby lowering the accuracy of the model. Therefore, in this paper a novel method is proposed to calculate the ideality factor and reverse saturation current of the solar cell from the I-V curve measured and announced by solar cell manufacturers, derive the ideal I-V curve, and then extract the series and shunt resistances value from the difference between the ideal and measured I-V curve. Also, validity of the proposed method is demonstrated by calculating the correlation between I-V curve based on modeling parameters and I-V curve actually measured through least squares method.

• Journal of The Korean Society of Grassland and Forage Science
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• v.35 no.2
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• pp.125-130
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• 2015

The objective of this study was to investigate the feasibility of using near infrared spectroscopy (NIRS) to discriminate between grass spices. A combination of NIRS and chemometrics was used to discriminate between Italian ryegrass, perennial ryegrass, and tall fescue seeds. A total of 240 samples were used to develop the best discriminant equation, whereby three spectra range (visible, NIR, and full range) were applied within a 680 nm to 2500 nm wavelength. The calibration equation for the discriminant analysis was developed using partial least square (PLS) regression and discrimination equation (DE) analysis. A PLS discriminant analysis model for the three spectra range that was developed with the mathematic pretreatment "1,8,8,1" successfully discriminated between Italian ryegrass, perennial ryegrass, and tall fescue. An external validation indicated that all of the samples were discriminated correctly. The discriminant accuracy was shown as 68%, 78%, and 73% for Italian ryegrass, perennial ryegrass, and tall fescue, respectively, with the NIR full-range spectra. The results demonstrate the usefulness of the NIRS-chemometrics combination as a rapid method for the discrimination of grass species by seed.

• Journal of The Korean Society of Grassland and Forage Science
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• v.40 no.4
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• pp.259-264
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• 2020

The aim of this study was to investigate the feasibility of discrimination 12 different cultivar of sorghum × sudangrass hybrid (Sorghum genus) seed through near infrared spectroscopy (NIRS). The amount of samples for develop to the best discriminant equation was 360. Whole samples were applied different three spectra range (visible, NIR and full range) within 680-2500 nm wavelength and the spectrastar 2500 Near near infrared was used to measure spectra. The calibration equation for discriminant analysis was developed partial least square (PLS) regression and discrimination equation (DE) analysis. The PLS discriminant analysis model for three spectra range developed with mathematic pretreatment 1,8,8,1 successfully discriminated 12 different sorghum genus. External validation indicated that all samples were discriminated correctly. The whole discriminant accuracy shown 82 ~ 100 % in NIR full range spectra. The results demonstrated the usefulness of NIRS combined with chemometrics as a rapid method for discrimination of sorghum × sudangrass hybrid cultivar through seed.

• Journal of Korea Water Resources Association
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• v.39 no.7 s.168
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• pp.593-603
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• 2006

The basin response to storm is regarded as nonlinearity inherently. In addition, the consistent nonlinearity of hydrologic system response to rainfall has been very tough and cumbersome to be treated analytically. The thing is that such nonlinear models have been avoided because of computational difficulties in identifying the model parameters from recorded data. The parameters of nonlinear system considered as dynamic effects in the conceptual model are optimized as the sum of errors between the observed and computed runoff is minimized. For obtaining the optimal parameters of functions, the historical data for the Bocheong watershed in the Geum river basin were tested by applying the numerical methods, such as quasi-linearization technique, Runge-Kutta procedure, and pattern-search method. The estimated runoff carried through from the storage function with dynamic effects was compared with the one of 1st-order differential equation model expressing just nonlinearity, and also done with Nash model. It was found that the 2nd-order model yields a better prediction of the hydrograph from each storm than the 1st-order model. However, the 2nd-order model was shown to be equivalent to Nash model when it comes to results. As a result, the parameters of nonlinear 2nd-order differential equation model performed from the present study provided not only a considerable physical meaning but also a applicability to Korean watersheds.

• Geophysics and Geophysical Exploration
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• v.15 no.2
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• pp.85-91
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• 2012

Multiple Lapse Time Window (MLTW) analysis for obtaining intrinsic attenuation value require numerous data without directional bias to compensate focal mechanism. The first window of MLTW, therefore, shows large deviation in fitting smoothed theoretical curve. The information on the focal mechanism may reduce burdens of number and distribution. This study combined algorithm of computing focal mechanism to DSMC method by Yoshimoto (2000). However, the MLTW method based on the numerous data was not applicable to this study, because of the limited data to the almost same fault plane solution. This study showed that the available data was too insufficient to construct smoothed theoretical curve, although the deviation of the first window was improved. Instead of conventional solution by more data, the study seems to be needed for new constraints to obtain smoothed curve.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.3
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• pp.249-257
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• 2011

In this paper, an systematic approach is presented, in which the mixed variational theorem is employed to incorporate independent transverse shear stresses into a classical higher-order shear deformation theory(HSDT). The HSDT displacement field is taken to amplify the benefits of using a classical shear deformation theory such as simple and straightforward calculation and numerical efficiency. Those independent transverse shear stresses are taken from the fifth-order polynomial-based zig-zag theory where the fourth-order transverse shear strains can be obtained. The classical displacement field and independent transverse shear stresses are systematically blended via the mixed variational theorem. Resulting strain energy expressions are named as an enhanced higher-order shear deformation theory via mixed variational theorem(EHSDTM). The EHSDTM possess the same computational advantage as the classical HSDT while allowing for improved through-the-thickness stress and displacement variations via the post-processing procedure. Displacement and stress distributions obtained herein are compared to those of the classical HSDT, three-dimensional elasticity, and available data in literature.