• 한국ITS학회 논문지
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• 제12권5호
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• pp.87-97
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• 2013

본 연구는 충청남도를 대상으로 도시권과 농어촌권을 구분하고, 고령자 및 비고령자의 여가통행시간 영향요인의 이질성을 정량적으로 규명하고자 하였다. 분석자료는 2011년 가구통행실태조사를 활용하여 도심 및 농어촌권역의 통행자특성을 추출하고, 도심 및 농어촌권의 지역경제적특성 및 교통환경적특성을 활용하여 PLS(Partial least square) 회귀모형을 구축하였다. 분석결과, 도시권과 농어촌권 고령자의 여가통행시간에 영향을 미치는 주요변수는 버스배차간격, 버스노선수, 가구원수, 가구월평균수입으로 나타났다. 비고령자의 경우에는 고령자의 중요 영향변수 이외 지역경제(GRDP, 경제활동참가율)환경과 고용형태도 여가통행시간에 영향을 미치는 중요 변수로 나타났다. 한편, 농어촌권에 거주하는 여성고령자는 남성고령자 보다 여가통행시간에 더 민감하나 비고령자그룹은 남녀별로 큰 차이가 없는 것으로 분석되었다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.394-394
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• 2000

This Paper proposes a new nonlinear partial least square method that extends the linear PLS. Proposed nonlinear PLS uses self-organizing feature map as PLS outer relation and multilayer neural network as PLS inner regression method.

• Toxicological Research
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• 제34권2호
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• pp.127-132
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• 2018

Alcohol consumption triggers toxic effect to organs and tissues in the human body. The risks are essentially thought to be related to ethanol content in alcoholic beverages. The identification of ethanol in blood samples requires rapid, minimal sample handling, and non-destructive analysis, such as Raman Spectroscopy. This study aims to apply Raman Spectroscopy for identification of ethanol in blood samples. Silver nanoparticles were synthesized to obtain Surface Enhanced Raman Spectroscopy (SERS) spectra of blood samples. The SERS spectra were used for Partial Least Square (PLS) for determining ethanol quantitatively. To apply PLS method, $920{\sim}820cm^{-1}$ band interval was chosen and the spectral changes of the observed concentrations statistically associated with each other. The blood samples were examined according to this model and the quantity of ethanol was determined as that: first a calibration method was established. A strong relationship was observed between known concentration values and the values obtained by PLS method ($R^2=1$). Second instead of then, quantities of ethanol in 40 blood samples were predicted according to the calibration method. Quantitative analysis of the ethanol in the blood was done by analyzing the data obtained by Raman spectroscopy and the PLS method.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2008년도 학술발표회 논문집
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• pp.2249-2253
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• 2008

본 연구에서는 지점빈도분석과 지역빈도분석을 이용하여 확률홍수량을 산정 하였다. 지점빈도 분석은 Annual Maximum Series(AMS) 및 Partial Duration Series(PDS)를 이용하여 자료를 추출하고 각 자료에 적합한 확률분포를 이용하여 확률홍수량을 산정하였다. 그러나 AMS를 이용한 확률홍수량의 산정은 표본의 개수가 부족하면 이에 따른 변동성(variability)이 커지게 되는 단점이 존재하며, PDS를 사용하면 임계값(threshold)에 따른 주관적 영향이 결과에 반영되는 단점이 존재하는 것으로 알려져 있다. 따라서 본 연구에서는 PDS를 사용하는 경우의 단점을 해결하기 위해 연 1.7회의 발생횟수를 갖는 자료를 추출하고 몬테카를로 모의시험을 통하여 주관적 영향을 제거하였다. 또한 두 가지 방법에 의해 산정된 확률홍수량의 비교검토를 위해 지역빈도분석을 수행하였다. 유역의 면적과 일평균강우량으로부터 확률홍수량을 산정할 수 있는 것으로 알려진 Bayesian-Generalized Least Square(B-GLS) 방법을 이용하여 확률홍수량을 산정하였다. 최종적으로 안양천 유역의 13개 소유역에 대한 세 가지 방법에 의해 산정된 확률홍수량을 비교 검토한 결과, 특정한 방법이 항상 우수하다는 결론은 얻을 수 없었으나 각 유역별로 AMS가 가장 크고 B-GLS가 가장 작은 확률홍수량을 갖는 경향을 나타내었다.

• Archives of Pharmacal Research
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• 제27권10호
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• pp.1009-1015
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• 2004

Quantitative Structure-Resolution Relationship (QSRR) using the Comparative Molecular Field Analysis (CoMFA) software was applied to predict the chromatographic behaviors of chiral drugs with an amine moiety on the chiral cellobiohydrolase (CBH) columns. As a result of the Quantitative CoMFA-Resolution Relationship study, using the partial least square method, prediction of the behavior of drugs with amine moiety upon chiral separation became possible from their three dimensional molecular structures. When a mixed mobile phase of 10 mM aqueous phosphate buffer (pH 7.0) - isopropanol (95 : 5) was employed, the best Quantitative CoMFA-Resolution Relationship, derived from the study, provided a cross-validated $q^2$ = 0.933, a normal $r^2$ = 0.995, while the best Quantitative CoMFA-Separation Factor Relationship, also derived from the study, yielded a cross-validated $q^2$ = 0.939, a normal $r^2$ = 0.991. When all of these results are considered, this QSRR-CoMFA analysis appears to be a very useful tool for the preliminary prediction on the chromatographic behaviors of drugs with an amine moiety inside chiral CBH columns.

• Journal of the Korean Wood Science and Technology
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• 제45권4호
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• pp.399-408
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• 2017

Research on the rapid and accurate prediction of physical properties of wood using near-infrared (NIR) spectroscopy has attracted recent attention. In this study, partial least squares analysis was performed between NIR spectra and air-dried specific gravity of five domestic conifer species including larch (Larix kaempferi), Korean pine (Pinus koraiensis), red pine (Pinus densiflora), cedar (Cryptomeria japonica), and cypress (Chamaecyparis obtusa). Fifty different lumbers per species were purchased from the five National Forestry Cooperative Federations of Korea. The air-dried specific gravity of 100 knot- and defect-free specimens of each species was determined by NIR spectroscopy in the range of 680-2500 nm. Spectral data preprocessing including standard normal variate, detrend and forward first derivative (gap size = 8, smoothing = 8) were applied to all the NIR spectra of the specimens. Partial least squares analysis including cross-validation (five groups) was performed with the air-dried specific gravity and NIR spectra. When the performance of the regression model was expressed as $R^2$ (coefficient of determination) and root mean square error of calibration (RMSEC), $R^2$ and RMSEC were 0.63 and 0.027 for larch, 0.68 and 0.033 for Korean pine, 0.62 and 0.033 for red pine, 0.76 and 0.022 for cedar, and 0.79 and 0.027 for cypress, respectively. For the calibration model, which contained all species in this study, the $R^2$ was 0.75 and the RMSEC was 0.37.

• 원예과학기술지
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• 제34권2호
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• pp.324-330
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• 2016

본 연구는 FT-IR 스펙트럼 데이터를 기반한 다변량통계분석을 이용한 대사체 수준에서 아티초크(Cynara cardunculus var. scolymus L.) 품종 구분하였다. FT-IR 스펙트럼 데이터로부터 PCA(principal component analysis), PLS-DA(partial least square discriminant analysis) 그리고 HCA(hierarchical clustering analysis) 분석을 실시하였다. 아티초크 품종들은 1700-1500, 1500-1300, $1100-950cm^{-1}$ 부위에서 대사체의 양적, 질적 패턴 변화가 FT-IR 스펙트럼상에서 나타났다. FT-IR 스펙트럼의 $1700-1500cm^{-1}$ 부위는 주로 Amide I 과 II을 포함하는 아미노산 및 단백질계열의 화합물들의 질적, 양적 정보를 나타내고, $1700-1300cm^{-1}$ 부위는 phosphodiester group을 포함한 핵산 및 인지질의 정보가 반영이 되고, $1100-950cm^{-1}$ 부위는 단당류나 복합 다당류를 포함하는 carbohydrates 계열의 화합물들이 질적, 양적 정보가 반영되는 부위이다. PCA 상에 나타난 10품종의 아티초크들은 품종간에 중첩이 많이 이뤄지는 모습을 나타냈다. 아티초크 10개의 품종 중에서 'Cardoon'과 'Green Globe'가 계통분류학적으로 유연관계가 낮고, 서로간에 대사체 수준의 차이가 뚜렷하게 나타나는 것으로 보아 대사체 수준에서 마커 탐색에 가장 중요한 품종으로 작용할 것으로 판단된다. PLS-DA 분석의 경우 PCA 분석 보다 아티초크의 종간 식별이 뚜렷하게 나타났다. 따라서 본 연구에서 확립된 대사체 수준에서 아티초크의 품종 식별 기술은 품종, 계통의 신속한 선발 수단으로 활용이 가능할 것으로 기대되며 육종을 통한 품종개발 가속화에 기여 할 수 있을 것으로 예상된다.

• Communications for Statistical Applications and Methods
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• 제13권3호
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• pp.567-576
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• 2006

In this paper, we applied the multiblock dimension reduction methods to the classification of tumor based on microarray gene expressions data. This procedure involves clustering selected genes, multiblock dimension reduction and classification using linear discrimination analysis and quadratic discrimination analysis.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 1999년도 춘계학술대회 논문집
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• pp.169-172
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• 1999

Recently, the wavelet transform has been a new and powerful tool for signal processing. It is more suitable specially for the feature extraction and detection of non-stationary signals than traditional methods such as, the Fourier Transform(FT), the Fast Fourier Transform(FFT) and the Least Square Method etc. because of the characteristic of the multi-scale analysis and time-frequency domain localization. The wavelet transform has been developed for the analysis of PD pulse signal to raise in the progress of insulation degradation. In this paper, the wavelet transform was applied to one foundational method for feature extraction. For the obtain experimental data, a computer-aided partial discharge measurement system with a single acoustic sensor was used. If we are applying to the neural network method the accumulated data through the extracted feature, it is expected that we can detect the PD pulse signal in the insulation materials on the on-line.

• Journal of Biosystems Engineering
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• 제40권4호
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• pp.335-344
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• 2015

Purpose: Soybean growth is adversely affected by environmental stresses such as drought, extreme temperatures, and nutrient deficiency. The objective of this study was to develop a method for rapid measurement of drought stress in soybean plants using a hyperspectral fluorescence imaging technique. Methods: Hyperspectral fluorescence images were obtained using UV-A light with 365 nm excitation. Two soybean cultivars under drought stress were analyzed. A partial least square regression (PLSR) model was used to predict drought stress in soybeans. Results: Partial least square (PLS) images were obtained for the two soybean cultivars using the results of the developed model during the period of drought stress treatment. Analysis of the PLS images showed that the accuracy of drought stress discrimination in the two cultivars was 0.973 for an 8-day treatment group and 0.969 for a 6-day treatment group. Conclusions: These results validate the use of hyperspectral fluorescence images for assessing drought stress in soybeans.