• 농업과학연구
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• 제47권3호
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• pp.645-655
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• 2020

Bacteria are a very common cause of food poisoning. Moreover, bacteria form biofilms to protect themselves from harsh environments. Conventional detection methods for foodborne bacterial pathogens including the plate count method, enzyme-linked immunosorbent assays (ELISA), and polymerase chain reaction (PCR) assays require a lot of time and effort. Hyperspectral imaging has been used for food safety because of its non-destructive and real-time detection capability. This study assessed the feasibility of using hyperspectral imaging and machine learning techniques to detect biofilms formed by Escherichia coli. E. coli was cultured on a high-density polyethylene (HDPE) coupon, which is a main material of food processing facilities. Hyperspectral fluorescence images were acquired from 420 to 730 nm and analyzed by a single wavelength method and machine learning techniques to determine whether an E. coli culture was present. The prediction accuracy of a biofilm by the single wavelength method was 84.69%. The prediction accuracy by the machine learning techniques were 87.49, 91.16, 86.61, and 86.80% for decision tree (DT), k-nearest neighbor (k-NN), linear discriminant analysis (LDA), and partial least squares-discriminant analysis (PLS-DA), respectively. This result shows the possibility of using machine learning techniques, especially the k-NN model, to effectively detect bacterial pathogens and confirm food poisoning through hyperspectral images.

• 분석과학
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• 제11권1호
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• pp.47-53
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• 1998

본 연구는 당뇨병 진단방법의 개선을 위하여 채혈을 직접적으로 하지 않고 혈당을 측정할 수 있도록 하기 위하여 근적외선 분광법을 적용하였다. 본 연구를 위하여 근적외선 분광법을 이용하여 1 mg/dL에서 200 mg/dL 사이의 표준 시료 80개 글루코오스 흡수 스팩트럼을 측정하고 이를 정량하여 표준 농도와의 상관관계를 비교하였을 때 1.8 mg/dL 오차범위에서 매우 우수하였다. 그리고 실제 혈액중에 존재할 수 있는 전해질 및 피부에 의한 산란의 영향을 연구하였을 때 모두 2.8 mg/dL 및 3.8 mg/dL의 표준오차를 나타내었다. 특히 실제 피부에 적용하기 위하여 검량곡선에 비직선성을 유발하는 빛의 산란 현상에 관한 모델링을 통하여 정확도를 향상시키는 통계적인 방법을 제시하였다.

• 한국정보통신학회논문지
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• 제17권5호
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• pp.1219-1226
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• 2013

본 연구에서는 혁신확산이론을 기반으로 스마트폰 지속적 사용의도에 미치는 영향을 분석하고자 하였다. 또한 인구통계학적 특성을 이용하여 아이폰 사용자와 안드로이드 플랫폼 사용자 그룹의 충성도 차이가 있는지를 비교하였다. 예측변수로는 혁신확산이론에서 제시된 혁신성과 편리성, 경제적 비용, 사회적 영향, 커뮤니케이션 채널, 적합성 그리고 복잡성을 선택하였다. 연구대상은 부산 경남지역에 거주하는 스마트폰 사용자 278명이며 설문지를 통해 자료를 수집하였다. 인구통계학적인 분석은 IBM SPSS Statistics 19로 하였고 Smart PLS를 사용하여 확인적 요인분석과 변수들 간의 인과관계에 대한 경로분석을 실시하였다. 분석결과 복잡성을 제외한 스마트폰 지속사용의도와 충성도에 이르는 모든 경로가 유의미한 영향을 미치는 것으로 나타났다. 결과를 바탕으로 연구의 한계와 시사점을 제시하고자 한다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 추계학술대회
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• pp.142-145
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• 2017

우리나라 스마트폰 이용자는 경제활동 인구의 99% 이상 대부분이 사용하고 있으며 초기 형성단계를 지나 포화상태에 도달한 것으로 전문가들은 내다보고 있다. 본 연구는 지배적 디자인 속성이 스마트폰 사용자의 지속사용의도에 미치는 영향을 알아보고자 하였다. 예측변수로는 확장 기술수용모델에서 제시된 인지된 유용성, 인지된 사용 용이성을 선택하였고 지배적 디자인 속성을 매개변수로 선택하여 개념모델을 완성하였다. 연구대상은 부산경남과 익산전북지역에 거주하는 스마트폰 사용자 150명이며 설문을 통해 기초 데이터를 수집하였다. 인구통계학적인 분석은 IBM SPSS Statistics 19로 하였고 Smart PLS를 사용하여 확인적 요인분석과 변수 간의 인과관계에 대한 경로 분석을 실시하였다. 분석결과 모든 경로가 유의미한 영향을 미치는 것으로 나타났다. 결과를 바탕으로 연구의 한계와 시사점을 제시하고자 한다.

• 한국토양비료학회지
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• 제47권4호
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• pp.275-283
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• 2014

The ${\gamma}$-oryzanol, ferulic acid esters, which are well-known for their function on cholesterol lowering and prevention of inflammation, diabetes and cancer, are found in the seeds of cereal crops such as rice, corn, wheat and rye. Among them, rice has been reported to contain the highest ferulic acid esters. Since rice cultivation with green manure as a N source is an environmental friendly agricultural practice, it is necessary to identify and quantify as well as evaluate the variations in these compounds in rice samples as affected by different green manure conditions. A total of ten components of ${\gamma}$-oryzanol were isolated and cycloartenyl ferulate, 24-methylenecycloartanyl ferulate, campesteryl ferulate and sitosteryl ferulate were identified as the major components in Korean rice cultivars, 'Unkwang' and 'Hopum'. Comparing the ${\gamma}$-oryzanol contents of these varieties, 'Unkwang' showed clearly similar pattern with conventional type. With the PLS-DA (partial least squares of discriminant analysis) using SIMCA 11.0 ver., the specific pattern and cluster of ${\gamma}$-oryzanol scores with green manure conditions were confirmed, and thus distinguishing green manure effects were possible.

• 한국IT서비스학회지
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• 제20권4호
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• pp.95-111
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• 2021

Recently, many organizations are actively adopting VDI (Virtual Desktop Infrastructure), an IT-based business system, to build a non-face-to-face business environment for smart-work. However, most of the existing research on VDI has focused on the satisfaction of system service quality or the use of IT resources and investment for VDI introduction. However, research on effective management and utilization of factors according to the characteristics of VDI technology is urgently required. This study is an empirical research study on how VDI technology characteristics affect interactions and work performance by identifying differences in utilization factors between general organization members and IT managers, presenting standards for business utilization and management. This study proposed a model and hypothesis that the system technology characteristics for VDI use are mediated by interactions in which users respond to functions appropriate to their work. In order to verify the hypothesis, a questionnaire survey was conducted on 188 people of companies and institutions that have adopted and used VDI through a questionnaire survey. Data analysis was performed with partial least squares (PLS), a structural equation modeling (SEM) technique that uses a component-based approach to estimation. As a result of the empirical analysis, the same environmental function for performing work, N-th security, and remote access function factors for non-face-to-face work have a significant effect on interactivity, and IT managers have an additional significant effect on the management technology characteristics of resource reallocation. Has been shown to affect. The results of this study aim to minimize trial and error due to new introduction by presenting considerations for future VDI introduction through case analysis.

• 산업경영시스템학회지
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• 제41권4호
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• pp.228-237
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• 2018

The importance of eWOM (electronic word-of-mouth) communication through online communities is increasing on a daily basis. This study analyzed how the relationship between eWOM (electronic Word-Of-Mouth) factor and eWOM communication depends on the cultural orientation of users in the online community. The research model was developed based on four cultural orientations of individual affect Social tie and usefulness. The model consists of variables such as social tie and perceived usefulness as predecessors of eWOM, four dimensions of cultural orientation (Horizontal Individualism, Horizontal Collectivism, Vertical Individualism, Vertical Collectivism), and eWOM. The model was tested empirically using the PLS (partial least squares) structure equation model. Survey was conducted for online community users in South Korea. Data was statistically validated whether fits on research model. The study results reveal that Social Tie have a positive effect on Perceived Usefulness. Social Tie and Perceived Usefulness have a positive effect on eWOM. 3 of cultural orientations (HC, VI, VC) have a positive effect on Social Tie. Only one of cultural orientations (HC) have an negative effect on Perceived Usefulness. Especially, horizontal collectivism (HC) shows strong correlation with perceived usefulness, whereas vertical collectivism (VC) shows weak correlation with perceived usefulness andvertical individualism (VI) shows strongly correlation with social tie, whereas horizontal individualism (HI) shows weak correlation with social tie. Based on the study results, customized service strategy could be formulated according to the different vertical styles and various eWOM factors.

• 농업과학연구
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• 제46권2호
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• pp.257-271
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• 2019

The use of food grade hexane (FGH) for edible oil extraction is responsible for the presence of benzene in the crude oil. Benzene is a Group 1 carcinogen and could pose a serious threat to the health of consumer. However, its detection still depends on classical methods using chromatography which requires a rapid non-destructive detection method. Hence, the aim of this study was to investigate the feasibility of using Fourier transform infrared (FTIR) spectroscopy combined with multivariate analysis to detect and quantify the benzene residue in edible oil (sesame and cottonseed oil). Oil samples were adulterated with varying quantities of benzene, and their FTIR spectra were acquired with an attenuated total reflectance (ATR) method. Optimal variables for a partial least-squares regression (PLSR) model were selected using the variable importance in projection (VIP) and the selectivity ratio (SR) methods. The developed PLS models with whole variables and the VIP- and SR-selected variables were validated against an independent data set which resulted in $R^2$ values of 0.95, 0.96, and 0.95 and standard error of prediction (SEP) values of 38.5, 33.7, and 41.7 mg/L, respectively. The proposed technique of FTIR combined with multivariate analysis and variable selection methods can detect benzene residuals in edible oils with the advantages of being fast and simple and thus, can replace the conventional methods used for the same purpose.

• 농업생명과학연구
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• 제53권3호
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• pp.147-157
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• 2019

In this study, we tried to find out the most appropriate pre-processing method and to verify the feasibility of developing a low-price sensing system for predicting the hardy kiwis sugar content based on VNIRS and subsequent spectral analysis. A total of 495 hardy kiwi samples were collected from three farms in Muju, Jeollabukdo, South Korea. The samples were scanned with a spectrophotometer in the range of 730-2300 nm with 1 nm spectral sampling interval. The measured data were arbitrarily separated into calibration and validation data for sugar content prediction. Partial least squares (PLS) regression was performed using various combinations of pre-processing methods. When the latent variable (LV) was 8 with the pre-processing combination of standard normal variate (SNV) and orthogonal signal correction (OSC), the highest R2 values of calibration and validation were 0.78 and 0.84, respectively. The possibility of predicting the sugar content of hardy kiwi was also examined at spectral sampling intervals of 6 and 10 nm in the narrower spectral range from 730 nm to 1200 nm for a low-price optical sensing system. The prediction performance had promising results with R2 values of 0.84 and 0.80 for 6 and 10 nm, respectively. Future studies will aim to develop a low-price optical sensing system with a combination of optical components such as photodiodes, light-emitting diodes (LEDs) and/or lamps, and to locate a more reliable prediction model by including meteorological data, soil data, and different varieties of hardy kiwi plants.

• 한국정보시스템학회지:정보시스템연구
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• 제31권1호
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• pp.197-218
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• 2022

Purpose This study examines the roles of firm-level smart factory implementation in the relationship between organizational competence and organizational performance in the context of Korean small and medium Enterprises (SMEs). To achieve this goal, this study presents and empirically tests a research model with evaluation data conducted by industrial experts on how organizational competence can be exploited to positively influence organizational performance through smart factory implementation. Design/methodology/approach Organizational competence are based on the research construct developed by Odważny et al.(2018). Research constructs on smart factory are based on the measurement model developed by Korea Technology and Information Promotion Agency for Korea small and medium Enterprises (TIPA) (2020) and organizational performance are based on the performance construct developed by Kwon(2019). To complete the investigation, we collected 31 firm data conducted by industrial experts in Korea from Dec 2018 to Dec 2020. Most of firm was implemented officially by government budget granted for smart factory of Korea SMEs. To test our hypotheses, partial least squares (PLS) method was employed. Findings The findings indicate that organizational competence is antecedent to influence smart factory implementation, while smart factory implementation has significant relationship with organizational performance. This study provides a better understanding of the connection between organizational competence and organizational performance through smart factory implementation. So companies should focus on enhancing organizational competence and implementing smart factory to obtain sustainable competitiveness.