• 농업과학연구
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• 제41권3호
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• pp.169-175
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• 2014

Objective of this study was to investigate effects of pre-processing method and number of sampling leaves on stability of the reflectance measurement for Chinese cabbage and kale leaves. Chinese cabbage and kale were transplanted and cultivated in a plant factory. Leaf samples of the kale and cabbage were collected at 4 weeks after transplanting of the seedlings. Spectra data were collected with an UV/VIS/NIR spectrometer in the wavelength region from 190 to 1130 nm. All leaves (mature and young leaves) were measured on 9 and 12 points in the blade part in the upper area for kale and cabbage leaves, respectively. To reduce the spectral noise, the raw spectral data were preprocessed by different methods: i) moving average, ii) Savitzky-Golay filter, iii) local regression using weighted linear least squares and a $1^{st}$ degree polynomial model (lowess), iv) local regression using weighted linear least squares and a $2^{nd}$ degree polynomial model (loess), v) a robust version of 'lowess', vi) a robust version of 'loess', with 7, 11, 15 smoothing points. Effects of number of sampling leaves were investigated by reflectance difference (RD) and cross-correlation (CC) methods. Results indicated that the contribution of the spectral data collected at 4 sampling leaves were good for both of the crops for reflectance measurement that does not change stability of measurement much. Furthermore, moving average method with 11 smoothing points was believed to provide reliable pre-processed data for further analysis.

• 물과 미래
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• 제26권2호
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• pp.79-87
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• 1993

크리깅을 이용하여 평균면적우량을 추정함에 있어 새로운 방법을 개발하였다. 이 방법은 크리깅 방정식에 나타나는 2중 및 4중 수치적분에 필요한 점들을 대상지역의 경계만 주면 임의로 추출하여 사용한다는 것이 기존의 방법과는 상이하다. 이로 인해 대상지역을 소구역으로 나누고, 각각의 중심점을 계산해야 했던 기존 방식의 난점을 극복하였으며, 따라서 본 연구에서 개발된 방법은 복잡한 경계를 갖는 지역의 경우 더욱 유용하다. 경계가 주어지면 그 안에서 점들을 임의로 추출하는 과정을 복소함수론에 기초한 알고리듬을 통하여 설명하였다. Monte Carlo 시뮬레이션의 결과, 개발된 방법에 의한 평균면적유량의 추정에 따른 오차는 추출점 수의 제곱근에 반비례하였다.

• 대한의용생체공학회:의공학회지
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• 제12권3호
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• pp.191-202
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• 1991

This paper describes ECG data compression algorithm using neural network. As a learning method, we use back error propagation algorithm. ECG data compression is performed using learning ability of neural network. CSE database, which is sampled 12bit digitized at 500samp1e/sec, is selected as a input signal. In order to reduce unit number of input layer, we modify sampling ratio 250samples/sec in QRS complex, 125samples/sec in P & T wave respectively. hs a input pattern of neural network, from 35 points backward to 45 points forward sample Points of R peak are used.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.86-89
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• 2003

To model a numerical problem space under the limitation of available data, we need to extract sparse but key points from the space and to efficiently approximate the space with them. This study proposes a sampling method based on the search process of genetic algorithm and a space modeling method based on least-squares approximation using the summation of Gaussian functions. We conducted simulations to evaluate them for several kinds of problem spaces: DeJong's, Schaffer's, and our original one. We then compared the performance between our sampling method and sampling at regular intervals and that between our modeling method and modeling using a polynomial. The results showed that the error between a problem space and its model was the smallest for the combination of our sampling and modeling methods for many problem spaces when the number of samples was considerably small.

• 한국지하수토양환경학회지:지하수토양환경
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• 제24권5호
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• pp.11-16
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• 2019

In this study, a reliable number of soil samples for TPH fractionation was investigated in order to perform risk assessment. TPH was fractionated into volatile petroleum hydrocarbons (VPH) with three subgroups and extractable petroleum hydrocarbons (EPH) with four subgroups. At the study site, concentrations of each fraction were determined at 18 sampling points, and the 95% upper confidence limit (UCL) value was used as an exposure concentration of each fraction. And then, 5 sampling points were randomly selected out of the 18 points, and an exposure concentration was calculated. This process was repeated 30 times, and the results were compared statistically. Exposure concentrations of EPH obtained from 18 points were 99.9, 339.1, 27.3, and 85.9 mg/kg for aliphatic $C_9-C_{18}$, $C_{19}-C_{36}$, $C_{37}-C_{40}$, and aromatic $C_{11}-C_{22}$, respectively. The corresponding exposure concentrations obtained from 5 points were 139.8, 462.8, 35.1 and 119.4 mg/kg, which were significantly higher than those from 18 points results (p <0.05). Our results suggest that limited number of samples for TPH fractionation may bias estimation of exposure concentration of TPH fractions. Also, it is recommended that more than 30 samples need to be analyzed for TPH fractionation in performing risk assessment.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.1145-1148
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• 2002

This paper presents a new method which is calculated to use only three vanishing points in order to compute the dimensions of object and its pose from a single image of perspective projection taken by a camera and the problem of recovering 3D models from three vanishing points of box scene. Our approach is to compute only three vanishing points without this information such as the focal length, rotation matrix, and translation from images in the case of perspective projection. We assume that the object can be modeled as a linear function of a dimension vector ν. The input of reconstruction is a set of correspondences between features in the model and features in the image. To minimize each the dimensions of the parameterized models, this reconstruction of optimization can be solved by the standard nonlinear optimization techniques with a multi-start method which generates multiple starting points for the optimizer by sampling the parameter space uniformly.

• International Journal of Fluid Machinery and Systems
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• 제10권3호
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• pp.240-253
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• 2017

Latin hypercube sampling is widely used design-of-experiment technique to select design points for simulation which are then used to construct a surrogate model. The exploration/exploitation properties of surrogate models depend on the size and distribution of design points in the chosen design space. The present study aimed at evaluating the performance characteristics of various surrogate models depending on the Latin hypercube sampling (LHS) procedure (sample size and spatial distribution) for a diverse set of optimization problems. The analysis was carried out for two types of problems: (1) thermal-fluid design problems (optimizations of convergent-divergent micromixer coupled with pulsatile flow and boot-shaped ribs), and (2) analytical test functions (six-hump camel back, Branin-Hoo, Hartman 3, and Hartman 6 functions). The three surrogate models, namely, response surface approximation, Kriging, and radial basis neural networks were tested. The important findings are illustrated using Box-plots. The surrogate models were analyzed in terms of global exploration (accuracy over the domain space) and local exploitation (ease of finding the global optimum point). Radial basis neural networks showed the best overall performance in global exploration characteristics as well as tendency to find the approximate optimal solution for the majority of tested problems. To build a surrogate model, it is recommended to use an initial sample size equal to 15 times the number of design variables. The study will provide useful guidelines on the effect of initial sample size and distribution on surrogate construction and subsequent optimization using LHS sampling plan.

• 한국지반환경공학회 논문집
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• 제5권2호
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• pp.5-13
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• 2004

아파트 건설용 부지내에서 중금속 및 유류로 오염된 토사가 발견되었다. 7개 위치에서 대표적인 시료를 채취하였으며 이 오염된 토사의 지반공학적 안정성을 확인하기 위하여 중금속 및 유류에 대한 환경공학적 검토가 이루어졌다. 2개 위치의 토사는 유류로 심하게 오염되어 있어 현장의 특정지역으로 반출하여 폐기해야 하는 것으로 판단하였다. 토양오염우려수준인 1개 위치의 토사에 대하여 성토재로서의 활용가능성을 확인하기 위하여 성토 안정성에 대한 해석을 수행하였으며 성토재로 사용할 수 있는 것으로 판단하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.631-634
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• 2006

Three main important sources for establishing GIS are the orthomap in scale 1:5 000 with Ground Sampling Distance of 0,5m; DEM/DTM data with height error of ${\pm}$1,0m and topographic map in scale 1: 10 000. The new era with Very High Resolution Satellite (VHRS) images as IKONOS, QuickBird, EROS, OrbView and other ones having Ground Sampling Distance (GSD) even lower than 1m has been in potential for producing orthomap in large scale 1:5 000, to update existing maps, to compile general-purpose or thematic maps and for GIS. The accuracy of orthomap generated from VHRS image affects strongly on GIS reliability. Nevertheless, orthomap accuracy taken from VHRS image is at first dependent on chosen sensor geometrical models. This paper presents, at fist, theoretical basic of the Rational Polynomial Coefficient (RPC) model installed in the commercial ImageStation Systems, realized for orthorectifying VHRS images. The RPC model of VHRS image is a replacement camera mode that represents the indirect relation between terrain and its image acquired on the flight orbit. At the end of this paper the practical accuracies of IKONOS and QuickBird image orthorectified by RPC model on Canadian PCI Geomatica System have been presented. They are important indication for practical application of producing digital orthomaps.

• Communications for Statistical Applications and Methods
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• 제19권2호
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• pp.237-246
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• 2012

다중 변환점(multiple change-point) 추론에 있어 소량자료에 관한 연구는 많지 않다. 본 논문에서는 소량 자료의 다중 변환점 추정을 위해 베이지안 비중심(noncentral) t 분포 변환점 모형을 제안하고, 제안된 모형 추론을 위해 메트로폴리스-해스팅스를 포함한 깁스 샘플링(Metropolis-Hastings-Within-Gibbs sampling) 알고리즘을 이용하였다. 모의실험 및 태풍 발생 수의 실증 분석결과는 제안된 모형과 알고리즘의 우수성을 보여 준다.