• ETRI Journal
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• v.30 no.5
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• pp.634-643
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• 2008

One of the ubiquitous technology fields that have received the most attention recently from technology communities worldwide is mobile radio frequency identification (RFID). Mobile handsets loaded with RFID readers enable the identification and retrieval of information on RFID tagged objects. In Korea, a variety of mobile RFID services are currently being piloted, and their commercial roll-out looks imminent. The goal of this study is to propose, ahead of the commercial launch of mobile RFID services, a customer satisfaction index (CSI) model for this service category and to then measure the CSI to derive practical implications for their providers and pointers related to the improvement of service. A web survey was conducted on Korean mobile phone subscribers who had participated in a mobile RFID pilot program. Using the results of this survey, we tested the CSI model and its hypotheses by employing a partial least-squares-based structural equation model analysis and calculated the index. We further conducted an importance-performance analysis in order to provide insights that may be useful for improving the quality of mobile RFID services.

• Journal of the Korean Institute of Gas
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• v.1 no.1
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• pp.14-20
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• 1997

Pipeline network analysis requires fluid mechanics. A lot of equations have been used for flow analysis according to the behavior of fluid in pipelines and the operative situations. In this paper, simulation and analysis have been performed for the pipeline network system in Kyungin area using a steady-state mathematical model. Then, a statistical model using partial least squares(PLS) method has been developed with the data obtained from the developed mathematical model. The results showed that it is possible to simulate and analyze pipeline network systems using statistical approach.

• YAKHAK HOEJI
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• v.49 no.2
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• pp.115-121
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• 2005

In this study, the performance of a portable NIR system and a FT NIR spectrometer were compared to determine water content of hairless mouse skin. The stratum corneum parts wer e separated from the epidermal tissues by trypsin solution. NIR diffuse reflectance spectra of hairless mouse skin were acquired using a fiber optic probe. In the near infrared, water molecules show two clear absorption bands at 1450 nm from first overtone of O-H stretching and 1940 nm from the combination involving O-H stretching and O-H deformation. It was found that the variations of O-H absorption band according to water content. Partial least squares regression (PLSR) was applied to develop a calibration model. The PLS model showed a good correlation between NIR predicted value and the absolute water content of separated hairless mouse skin, in vitro. For both the portable and the FT NIR spectrometer, These studies showed the possibility of a rapid and nondestructive skin moisture measurement using NIR spectroscopy. The portable NIR spectrometer with a photodiode arrays-microsensor could be more rapidly applied for the determination of water content with comparable accuracy with the performance of a FT spectrometer .

• Journal of Environmental Science International
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• v.29 no.5
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• pp.445-455
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• 2020

Fine dust is one of the most critical environmental issues in Korea, and the government recognizes the need to establish customized reduction policies based on regional characteristics. Several studies on air pollutants investigate whether factories affect the distribution of fine dust in a particular region. However, understanding the impact of the entire industry sector requires further investigation. This study identifies the impacts of industrial characteristics on fine dust levels of 141 municipalities across Korea in 2016. A total of 23 variables were used, of which 12 referred to industries and 11 to general characteristics of each city. Due to the high correlation between independent variables, partial least squares (PLS) regression models were used. The analysis identified 14 significant variables for PM10 and 13 for PM2.5. Therefore, the results suggest that local industrial characteristics can significantly influence fine dust levels and provide suggestions for establishing customized reduction policies based on local characteristics.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.63 no.4
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• pp.360-377
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• 2018

The levels of 12 isoflavones were measured in soybean (Glycine max (L.) Merrill) sprouts of 68 genetic varieties from three countries (China, Japan, and Korea). The isoflavone profile differences were analyzed using data mining methods. A principal component analysis (PCA) revealed that the CSRV021 variety was separated from the others by the first two principal components. This variety appears to be most suited for functional food production due to its high isoflavone levels. Partial least squares discriminant analysis (PLS-DA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA) showed that there are meaningful isoflavone compositional differences in samples that have different countries of origin. Hierarchical clustering analysis (HCA) of these phytochemicals resulted in clusters derived from closely related biochemical pathways. These results indicate the usefulness of metabolite profiling combined with chemometrics as a tool for assessing the quality of foods and identifying metabolic links in biological systems.

• Korean Journal of Food Science and Technology
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• v.47 no.1
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• pp.20-26
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• 2015

This study aimed to establish a rapid system for discriminating the cultivation origins and cultivars of dry persimmons, using metabolite fingerprinting by Fourier transform infrared (FT-IR) spectroscopy combined with multivariate analysis. Whole-cell extracts from the sepals of four Korean cultivars and two different Chinese dry persimmons were subjected to FT-IR spectroscopy. Principle component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) of the FT-IR spectral data successfully discriminated six dry persimmons into two groups depending on their cultivation origins. Principal component loading values showed that the 1750-1420 and $1190-950cm^{-1}$ regions of the FT-IR spectra were significantly important for the discrimination of cultivation origins. The accuracy of prediction of the cultivation origins and cultivars by PLS regression was 100% (p<0.01) and 85.9% (p<0.05), respectively. These results clearly show that metabolic fingerprinting of FT-IR spectra can be applied for rapid discrimination of the cultivation origins and cultivars of commercial dry persimmons.

• Asia pacific journal of information systems
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• v.14 no.1
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• pp.101-123
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• 2004

User satisfaction has been widely used by information system(IS) researchers as the most appropriate surrogate variable for the systems success since Bailey and Pearson(1983) provided their user satisfaction measurement. Because user satisfaction is a perceived performance measure by users, not a real or objective measure for systems success, however, perceived user satisfaction by users may not be exactly identical with the real systems performance. In this regard, if the user's ultimately perceived satisfaction is different from the real systems performance, we need to investigate why these two measures are different and which factors may cause the difference. From the perspective of disconfirmation of user expecations, this study examined why user satisfaction and real systems performance may not be identical each other. Expectaion-disconfirmation theory which has had a central role in marketing in explaining the effects of expectation and disconfirmation on consumer satisfaction was similarly adopted in this study to explain the role of expectation and disconfirmation in user satisfaction in the IS environment. Based on the expectation-disconfirmation theory, the current study developed a research model to examine the effects of expectation, system performance, and disconfirmation on user satisfaction in particular. Six research hypotheses derived from the research model were empirically tested using the partial least squares(PLS) method. The results of the statistical analysis indicate that the effects of system performance and disconfirmation were fairly strong on user satisfaction, while the user's expectation has shown insignificant influences on user satisfaction.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.553-562
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• 2016

Then, it investigated the investment preference through the previous studies to analyze the influence factor of investment satisfaction and demonstrated the effects through the PLS (Partial Least Squares) regression. In addition, it separated the target type to institutional investors and retail investors and carried out the survey for comparing the investment preference of investor type. The result of analysis found out that institutional investors emphasis on investment preference such as the Inflation hedge, Early payback, Financial stability, Leverage risk and etc. Then, general investors emphasis on investment preference such as the Rental income, Facilities and Equipment, Business area and population, Ease of use, Leverage risk, Early payback and etc. In addition, common investment preferences are the Leverage risk, Early payback and Facility accessibility.

• Analytical Science and Technology
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• v.33 no.2
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• pp.98-107
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• 2020

Methamphetamine (MA) is currently the most abused illicit drug in Korea. MA is produced by chemical synthesis, and the final target drug that is produced contains small amounts of the precursor chemicals, intermediates, and by-products. To identify and quantify these trace compounds in MA seizures, a practical and feasible approach for conducting chromatographic fingerprinting with a suite of traditional chemometric methods and recently introduced machine learning approaches was examined. This was achieved using gas chromatography (GC) coupled with a flame ionization detector (FID) and mass spectrometry (MS). Following appropriate examination of all the peaks in 71 samples, 166 impurities were selected as the characteristic components. Unsupervised (principal component analysis (PCA), hierarchical cluster analysis (HCA), and K-means clustering) and supervised (partial least squares-discriminant analysis (PLS-DA), orthogonal partial least squares-discriminant analysis (OPLS-DA), support vector machines (SVM), and deep neural network (DNN) with Keras) chemometric techniques were employed for classifying the 71 MA seizures. The results of the PCA, HCA, K-means clustering, PLS-DA, OPLS-DA, SVM, and DNN methods for quality evaluation were in good agreement. However, the tested MA seizures possessed distinct features, such as chirality, cutting agents, and boiling points. The study indicated that the established qualitative and semi-quantitative methods will be practical and useful analytical tools for characterizing trace compounds in illicit MA seizures. Moreover, they will provide a statistical basis for identifying the synthesis route, sources of supply, trafficking routes, and connections between seizures, which will support drug law enforcement agencies in their effort to eliminate organized MA crime.

• Journal of Digital Convergence
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• v.14 no.4
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• pp.209-220
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• 2016

Although organizations are providing information security policy, education and support to guide their employees in security policy compliance, accidents by non-compliance is still a never ending problem to organizations. This study investigates the factors that influence employees' information security policy compliance behavior using elements of Triandis model. We analyzed the relationships among Triandis model's factors using PLS(Partial Least Squares). The result of the hypothesis tests shows that organization can induce individual's information security policy compliance intention and behavior by information security policy and facilitating conditions that support it, and proves the importance of members' expected value, habit and affect about information security compliance. This study is significant in a way that it applies Triandis model in the field of information security, and presents direction for members' information security behavior, and will be able to provide measures to establish organization's information security policy and increase members' compliance behavior.