• Proceedings of the Korean Society of Postharvest Science and Technology of Agricultural Products Conference
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• 2003.04a
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• pp.120-121
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• 2003

과수원에서 재배되는 배는 과수원 내의 위치, 시비, 토양 등의 요인에 따라 다양한 품질을 나타내며, 당도와 숙도의 편차가 크기 때문에 과수농가에서는 경험에 의존하여 적정 숙기로 판단되는 배를 수확하고 있다. 그러나 과학적이지 못한 사실에 기초한 수확 관행은 시장유통되는 배에 대하여 소비자들의 신뢰성 저하를 초래하게 되고 소비 감소와 더불어 농가 소득 감소로 이어지게 된다. 최근, 전국의 청과물 산지유통센터에는 근적외선을 이용하여 과일 내부의 당도, 산도, 결함 등을 실시간으로 판정할 수 있는 비파괴 선별기가 보급되고 있으나 이는 수확이후의 선별.규격화 유통을 위한 것이다. 본 연구에서는 이와는 달리, 수확 이전, 즉 재배 단계에서 배의 당도와 숙도를 판정하여 수확적기를 판단할 수 있도록 나무에 매달린 배에 대하여 가시광선과 근적외선 반사스펙트럼을 측정할 수 있고 이를 이용하여 당도와 숙도가 판정가능한 휴대형 센서를 개발하였으며, 개발된 시작기를 이용하여 당도판정의 가능성을 시험하였다. 휴대형 당도판정센서는 광원과 광섬유프로브, 광검출부, 당도판정부, 전원공급부로 구성된다. 광원은 할로겐램프(6V)를 이용하였고, 광섬유프로브는 동심원 형태로서 외부의 광섬유를 통하여 광원에서 시료로 빛이 조사되게 하고, 내부의 광섬유를 통하여 광검출기로 확산반사되는 광이 전달될 수 있도록 하였다. 전원공급부는 휴대와 충전이 가능한 배터리(12V, 2AH)와 이 배터리에서 정전류가 광원으로 보내어 질 수 있도록 제작된 회로로 구성하였다. 당도 판정을 위하여 518nm에서 1046nm의 파장대역에서의 반사스펙트럼을 이용하였고, 레퍼런스로써 백색 테플론 구를 제작하여 사용하였다. 수원 농산물 도매시장에서 판매중인 2002년산 신고 배를 구매하고, 시작기를 이용하여 총 113개의 배에 대한 반사스펙트럼을 측정하였다. 다음으로 굴절당도계로 당도값을 측정하고 반사스펙트림을 이용하여 당도값을 예측하기 위한 부분최소제곱회귀(PLSR)모델을 개발하였다. 여기서 모델의 정밀도는 교차검정법을 이용하여 검증하였다. 시료 표면과 광섬유프로브와의 접촉상태 불균일, 광원의 시간에 따른 경시 변화, 과일 형상의 차이 등에 의하여 측정된 반사스펙트럼은 상당한 변이를 나타내었으므로 이를 보정하기 위하여 반사 스펙트럼은 다분산보정처리하여 이용하였다. 당도 예측용 PLSR모델 개발의 결과, 모델의 결정계수($R^2$)는 0.67, SEC는 $\pm$0.4brix.로 나타났으며, 교차검정에 의한 미지 시료의 예측에서 총 113개의 미지 시료에 대한 결정계수는 0.57, SEP는 $\pm$ 0.46brix.로 나타났으며, 이는 현장에서 충분히 활용가능할 것으로 판단되었다. 금후, 전체 시스템의 부피와 중량을 줄이고 각 부분품들의 전력소모의 최소화할 수 있도록 개선할 계획이다.

• Journal of Venture Innovation
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• v.7 no.1
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• pp.17-39
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• 2024

The purpose of this study was to analyze the effect of the government's R&D support and the use of stock options by venture companies on the innovation of venture companies, that is, innovation capabilities and innovation performance. An empirical analysis was conducted using the partial least squares structural equation modeling (PLS-SEM) method using the data from the detailed survey of venture companies conducted on domestic venture confirmation companies. As a result of the analysis, it was found that the benefit of government R&D support had a positive (+) effect on strengthening the innovation capabilities of venture companies, and R&D support also had a positive (+) effect on the innovation performance of venture companies. Next, it was found that the use of stock options by venture companies had a positive (+) effect on the reinforcement of the innovation capabilities of companies and a positive (+) effect on the innovation performance of venture companies. In addition, it was found that the innovation capabilities of venture companies significantly mediate between the government's R&D support and the use of stock options by venture companies and the innovation performance of companies. These analysis results show that the government's R&D support and the use of stock option systems can play a meaningful role in the innovation of venture companies, and also show that the innovation capabilities of venture companies have an important meaning in the process of innovation. Therefore, it is necessary to continue the stance of R&D support for ventures and at the same time to introduce multi-faceted policy measures to support corporate capacity building, and legal and institutional maintenance and policy support to revitalize the stock option system need to be continuously provided.

• Analytical Science and Technology
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• v.16 no.4
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• pp.277-282
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• 2003

The amount of water for the cultivation of citrus is different based on the growing period. The effect of water stress induces to enhance of sugar accumulation in citrus. The water content in the leaves of citrus can be a index for watering during cultivation. The purpose of this study is to determine the water content of citrus leaves non-destructively by using near infrared spectroscopy (NIRS). Citrus leaves were prepared from 'Okitsu' Satusuma mandarin leaves (Citrus unshiu Marc.) ranging from 20.80 to 69.98% of water content by loss on drying method, and NIR reflectance spectra of citrus leaves were acquired by using a fiber optic probe. It was found that the variation of absorbance band 1450 nm from OH vibration of water depending on the water content change. Partial least squares regression (PLSR) was applied to develop a calibration model over the spectral range 1100-1700 nm. The calibration model predicted the water content for the validation set with a standard errors of prediction (SEP) of 0.97%. In order to validate the developed calibration model, routine analyses were performed using independently prepared citrus leaves. The NIR routine analyses showed good results with those of loss on drying method with a SEP of 0.81%. The rapid and non-destructive determination of the water content in citrus leaves was successfully performed by portable NIR system.

• Journal of the Korean Geographical Society
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• v.51 no.4
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• pp.509-523
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• 2016

The soil prediction can provide quantitative soil information for sustainable mountainous ecosystem management. Visible near infrared spectroscopy, one of soil prediction methods, has been applied to predict several soil properties with effective costs, rapid and nondesctructive analysis, and satisfactory accuracy. Spectral preprocessing is a essential procedure to correct noisy spectra for visible near infrared spectroscopy. However, there are no attempts to evaluate various spectral preprocessing methods. We tested 5 different pretreatments, namely continuum removal, Savitzky-Golay filter, discrete wavelet transform, 1st derivative, and 2nd derivative to predict soil carbon(C) and nitrogen(N). Partial least squares regression was used for the prediction method. The total of 153 soil samples was split into 122 samples for calibration and 31 samples for validation. In the all range, absorption was increased with increasing C contents. Specifically, the visible region (650nm and 700nm) showed high values of the correlation coefficient with soil C and N contents. For spectral preprocessing methods, continuum removal had the highest prediction accuracy(Root Mean Square Error) for C(9.53mg/g) and N(0.79mg/g). Therefore, continuum removal was selected as the best preprocessing method. Additionally, there were no distinct differences between Savitzky-Golay filter and discrete wavelet transform for visual assessment and the methods showed similar validation results. According to the results, we also recommended Savitzky-Golay filter that is a simple pre-treatment with continuum removal.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.147-147
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• 2017

우리나라에서는 수입 개방화 추세에 따라 공정한 유통질서 확립하고 국내 생산자와 소비자를 보호하기 위하여 원산지 표시제가 시행되고 있다. 그러나 수입 농산물과 국산 농산물의 큰 가격차이로 인하여 원산지를 허위 표시하는 경우가 증가하고 있다. 특히 쌀 관세화 전환 의무에 따른 수입산 쌀 증가하고 있으며 단립종과 중립종 수입산 쌀은 국내산 쌀과 외관이 유사하여 육안식별이 어려워 국내산 쌀로 둔갑할 우려가 있다. 이에 신속하고 비파괴적으로 쌀의 원산지를 판별할 수 있는 기술 개발이 요구되고 있다. 따라서 본 연구에서는 국내산 쌀과 중국산 쌀의 원산지를 신속하게 판별가능한 영상 처리기술을 개발하였다. 쌀은 국내에서 생산된 중립종 50점과 중국에서 생산된 단립종 및 중립종 51점이 수집되어 사용되었다. 쌀의 분광 영상은 초분광 가시광 및 근적외선 영상 시스템을 이용하여 측정하였다. 이 시스템은 할로겐-텅스텐 라인광, 시료 이송부, 초분광 영상 획득부로 구성되어 있다. 텅스텐-할로겐 라인광은 $15^{\circ}$ 각도로 대칭으로 시료에 조사되고 400 ~ 1000 nm 파장 영역의 반사광 영상 스펙트럼이 측정되었다. 초분광 영상 데이터는 광에 노출되지 않은 암실에서의 파장별 영상과 반사율이 99% 이상인 기준판의 파장별 영상을 이용하여 교정되었다. 부분최소제곱회귀법을 이용하여 쌀 원산지 판별모델 식을 개발하였고, 이 판별 모델식을 교정된 초분광 영상에 적용하여 영상처리 판별 모델을 개발하였다. 그 결과, 원산지 판별정확도가 97.4% 이상으로 나타났으며, 국내산과 중국산 쌀의 원산지 판별이 가능하였다.

• Horticultural Science & Technology
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• v.34 no.2
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• pp.324-330
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• 2016

To determine whether FT-IR spectral analysis based on multivariate analysis for whole cell extracts can be used to discriminate between artichoke (Cynara cardunculus var. scolymus L.) plants at the metabolic level, leaves of ten artichoke plants were subjected to Fourier transform infrared(FT-IR) spectroscopy. FT-IR spectral data from leaves were analyzed by principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA). FT-IR spectra confirmed typical spectral differences between the frequency regions of 1,700-1,500, 1,500-1,300 and $1,100-950cm^{-1}$, respectively. These spectral regions reflect the quantitative and qualitative variations of amide I, II from amino acids and proteins ($1,700-1,500cm^{-1}$), phosphodiester groups from nucleic acid and phospholipid ($1,500-1,300cm^{-1}$) and carbohydrate compounds ($1,100-950cm^{-1}$). PCA revealed separate clusters that corresponded to their species relationship. Thus, PCA could be used to distinguish between artichoke species with different metabolite contents. PLS-DA showed similar species classification of artichoke. Furthermore these metabolic discrimination systems could be used for the rapid selection and classification of useful artichoke cultivars.

• Journal of the Korean Society of Food Science and Nutrition
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• v.43 no.10
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• pp.1543-1548
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• 2014

To study traditional Doenjang characteristics, Doenjang was purchased from five different provinces: Chungcheong (CC), Gangwon (GW), Gyeonggi (GG), Gyeongsang (GS), and Jeolla (JL). To determine physicochemical characteristics, contents of reducing sugar, amino type nitrogen, salt, pH, and acidity were analyzed. The sensory characteristics were analyzed by sensory descriptive analysis. Reducing sugar content was highest for Doenjang from GW province. Amino type nitrogen content was highest for Doenjang from JL province. The salt content was highest in Doenjang from CC and GS provinces. After principal component analysis (PCA) based on sensory descriptive analysis, salty taste and aftertaste were highly correlated with overall acceptance. In the correlation analysis among chemical compounds and overall acceptance, Doenjang contained low reducing sugar content, and high pH value was positively correlated with overall acceptance. In conclusion, Doenjang with high pH value and salty taste and aftertaste have high overall acceptance.

• Journal of the Korean Chemical Society
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• v.53 no.6
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• pp.717-726
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• 2009

Multivariate models were developed for the simultaneous spectrophotometric determination of copper (II), nickel (II) and zinc (II) in water with 1-(2-thiazolylazo)-2-naphthol as chromogenic reagent in the presence of Triton X-100. To overcome the drawback of spectral interferences, principal component regression (PCR) and partial least square (PLS) multivariate calibration approaches were applied. Performances were validated with several test sets, and their results were then compared. In general, no significant difference in analytical performance between PLS and PCR models. The root mean square error of prediction (RMSEP) using three components for $Cu^{2+}$, $Ni^{2+}$ and $Zn^{2+}$ were 0.018, 0.010, 0.011 ppm, respectively. Figures of merit such as sensitivity, analytical sensitivity, limit of detection (LOD) were also estimated. High reliability was achieved when the proposed procedure was applied to simultaneous determination of $Cu^{2+}$, $Ni^{2+}$ and $Zn^{2+}$ in synthetic mixture and tap water.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2001.06a
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• pp.162-177
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• 2001

The hydrolysis rates of seven kinds of polyol ester base oils 〔POEs〕 of different branch shape were investigated by using a simple apparatus under mild acidic condition. Seven polyol ester base oils were made of poly hydric alcohols of two-four valence, normal or branched fatty acids of different carbon number. p-Toluene sulfonic acid was used as acid catalyst to accelerate the rate of hydrolysis. Partial esters and fatty acid produced by sequential hydrolysis of POEs were identified and their concentrations were determined by calibrated-internal standard method using Gas Chromatography. The rate constants of each step in sequential hydrolysis were determined by the least square method from rate equation and the concentration of each component, were compared with one another. It was shown that the rate of hydrolysis of POEs was strongly affected by whether molecular structure of fatty acid was straight chain or branch chain and which position was branched. The hydrolysis stability for all the POEs can be reasonably explained by using a steric hindrance effect anticipated fi:om their molecular structures affecting as water molecule makes an attack on the carbonyl carbon of POEs.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.1-9
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• 2021

In this paper, we propose a training algorithm of support vector machine (SVM) with a sensitive variable. Although machine learning models enable automatic decision making in the real world applications, regulations prohibit sensitive information from being used to protect privacy. In particular, the privacy protection of the legally protected attributes such as race, gender, and disability is compulsory. We present an efficient least square SVM (LSSVM) training algorithm using a fully homomorphic encryption (FHE) to protect a partial sensitive attribute. Our framework posits that data owner has both non-sensitive attributes and a sensitive attribute while machine learning service provider (MLSP) can get non-sensitive attributes and an encrypted sensitive attribute. As a result, data owner can obtain the encrypted model parameters without exposing their sensitive information to MLSP. In the inference phase, both non-sensitive attributes and a sensitive attribute are encrypted, and all computations should be conducted on encrypted domain. Through the experiments on real data, we identify that our proposed method enables to implement privacy-preserving sensitive LSSVM with FHE that has comparable performance with the original LSSVM algorithm. In addition, we demonstrate that the efficient sensitive LSSVM with FHE significantly improves the computational cost with a small degradation of performance.