• 한국공작기계학회논문집
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• 제15권5호
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• pp.1-6
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• 2006

The purpose of this study is to develop to portable near infrared analyzer measuring the sugar content of the fruits on a tree before harvesting ones. The portable near infrared system consists of a tungsten lamp, a coaxial optical fiber bundle and a multi-channel detector, which has 256 pixels and a concave transmission grating. Reflectance NIR spectra of orange were recorded by using a coaxial optical fiber bundle. The spectra were collected over the spectral range $400{\sim}1100nm$. Partial least squares regression(PLSR) was applied for a calibration and validation for determination of sugar contents. The multiple correlation coefficient was 0.99 and standard errors of calibration(SEC) was 0.069 brix. The calibration model predicted the sugar content for validation set with standard errors of prediction(SEP) of 0.092 brix. The sugar content in fruits was successfully quantified using the portable near infrared analyzer.

• 센서학회지
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• 제17권2호
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• pp.120-126
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• 2008

Glucose concentrations in the interstitial fluid were measured based on optical spectroscopy. Prediction of glucose concentrations was made using partial least squares regression and accuracy improvement was achieved by data preprocessing as well as by selecting an optimal wavelength region. For this purpose, artificial interstitial fluid samples were prepared where their glucose levels varied between 0 and 10 g/dl. Infrared spectral regions where glucose absorption lies were investigated. A region of 1000 - 1500 $cm^{-1}$ produced the best accuracy among the regions of 1000 - 1500 $cm^{-1}$, 4000 - 4545 $cm^{-1}$1 and 5500 - 6500 $cm^{-1}$. Further accuracy improvement in 1000 - 1500 $cm^{-1}$ was achieved by selecting specific wavelength bands based on a loading vector analysis method. For the samples whose glucose concentrations ranged between 0 and 0.5 g/dl, SEP= 0.0266 g/dl and R =0.9863 were achieved with 1000 - 1500 $cm^{-1}$. However, the loading vector optimized band of 1002 - 1095 $cm^{-1}$ reduced the prediction error up to 47 % (SEP =0.0125 g/dl and R=0.9970).

• 산경연구논집
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• 제10권5호
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• pp.7-20
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• 2019

Purpose - This study provides appropriate procedures for EFA to help researchers conduct empirical studies by using PLS-SEM. Research design, data, and methodology - This study addresses the absolute and relative sample size criteria, sampling adequacy, factor extraction models, factor rotation methods, the criterion for the number of factors to retain, interpretation of results, and reporting information. Results - The factor analysis procedure for PLS-SEM consists of the following five stages. First, it is important to look at whether both the Bartlett test of sphericity and the KMO MSA meet the qualitative criteria. Second, PAF is a better choice of methodology. Third, an oblique technique is a suitable method for PLS-SEM. Fourth, a combined approach is strongly recommended to factor retention. PA should be used at the onset. Next, it is recommended using the K1 criterion. In addition, it is necessary to extract factors that increase the total variance explanatory power through the PVA-FS. Finally, it is appropriate to select an item with a factor loading into 0.5 or higher and a communality of 0.5. Conclusions - It is expected that the accurate factor analysis processed for PLS-SEM as previously presented will help us extract more precise factors of the structural model.

• Asia pacific journal of information systems
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• 제21권1호
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• pp.49-80
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• 2011

E-government needs to be successfully implemented and assimilated into organizations to take advantage of its potential values and benefits for organizations. This study examines factors for e-government assimilation in Indonesia and employs the TOE (Technology-Organization-Environment) framework to develop a theoretical model to explain e-government assimilation. It also investigates how organizational type (central vs. local) plays a role in the assimilation of e-government. One hundred eighteen respondents from the central and local governments in Indonesia participated in the survey and an in-depth analysis based on partial least squares (PLS) was carried out. The results show that ICT infrastructure has the strongest significant relationship with e-government assimilation, Top management support, regulatory environment, ICT expertise, and competitive environment are also significant factors to explain e-government assimilation in Indonesia. Central and local governments Significantly differ in terms of e-government assimilation, so organizational type can be a moderator in the process of e-government assimilation. These findings present the efficacy of the proposed model for analyzing e-government assimilation and contribute additional insights for academia as well as practitioners and policy makers.

• 한국식품영양학회지
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• 제29권5호
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• pp.605-609
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• 2016

This study aimed to find the optimum instrumental test conditions for the Texture Profile Analysis (TPA) of cooked rice in order to predict the sensory texture attributes (hardness, adhesiveness, chewiness). Sensory evaluation was performed for three kinds of instant cooked rice with university students in their twenties and the results of the sensory evaluation were compared to instrumental TPA patterns. Using partial least squares regression, the instrumental TPA results at a cross-head speed of 1.0 mm/sec and a compression ratio of 70% proved to be an excellent predictor of the sensory attributes of hardness ($R^2=0.99$) and chewiness ($R^2=0.99$). The results at a cross-head speed of 0.5 mm/sec and compression ratio of 30% provided an excellent model for the prediction of sensory adhesiveness ($R^2=0.83$). In this experimental range, sensory hardness and chewiness showed a high correlation with instrumental TPA parameters (hardness, cohesiveness, adhesiveness, springiness, chewiness) with a high cross-head speed and compression ratio, while sensory adhesiveness showed a high correlation with the TPA parameters with a low cross-head speed and compression ratio.

• Food Science and Biotechnology
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• 제18권1호
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• pp.60-65
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• 2009

Near infrared reflectance spectroscopy (NIRS) was used as a rapid and non-destructive method to determine the protein content in intact and ground seeds of pea (Pisum sativum L.) germplasms grown in Korea. A total of 115 samples were scanned in the reflectance mode of a scanning monochromator at intact seed and flour condition, and the reference values for the protein content was measured by auto-Kjeldahl system. In the developed ground and intact NIRS equations for analysis of protein, the most accurate equation were obtained at 2, 8, 6, 1 math treatment conditions with standard normal variate and detrend scatter correction method and entire spectrum (400-2,500 nm) by using modified partial least squares regression (n=78). External validation (n=34) of these NIRS equations showed significant correlation between reference values and NIRS estimated values based on the standard error of prediction (SEP), $R^2$, and the ratio of standard deviation of reference data to SEP. Therefore, these ground and intact NIRS equations can be applicable and reliable for determination of protein content in pea seeds, and non-destructive NIRS method could be used as a mass analysis technique for selection of high protein pea in breeding program and for quality control in food industry.

• 약학회지
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• 제47권3호
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• pp.148-153
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• 2003

Skin moisture is an important factor in skin health. Measurement of moisture content can provide diagnostic information on the condition of skin. In this study, a portable near-infrared (NIR) system was newly integrated with a photo diode array detector that has no moving parts, and this system has been successfully applied for the evaluation of human skin moisture. Diffuse reflectance spectra were collected and transformed to absorbance using 1 nm step size over the wavelength range of 1100 nm to 2200 nm. Partial least squares regression (PLSR) was applied to develop a calibration model. For practical use for the evaluation of human skin moisture, the PLS model for human skin moisture was developed in vivo using the portable NIR system on the basis of the relative water content values of stratum corneum from the conventional capacitance method. The PLS model showed a good correlation. The calibration with the use of PLS model predicted human moisture with a standard error of prediction (SEP) of 3.5 at 1120∼1730 nm range. This study showed the possibility of skin moisture measurement using portable NIR system.

• 경영과정보연구
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• 제27권
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• pp.71-99
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• 2008

This study investigates the relationships between three BSC communication attributes(support of organizational culture, message valid, and knowledge sharing) and organizational learning and how that translates into relationship organizational performance in public organization. In this paper, first, past studies on BSC communication and organizational learning that identify the attributes of effective communication and organizational learning in organizational performance are reviewed. Second, a research model, key variables, and three hypotheses tested by PLS(partial least squares) are presented. The data was collected from BSC champions and managers of 53 public organizations in Korea. The results indicate, first, BSC communication (except for support of organizational culture) have not significant related to organizational performance. Therefore, H1 was not supported. Second, the structural path coefficient between support of organizational culture and message valid and organizational learning are statistically significant and in the hypothesized direction. But the knowledge sharing has not significant relationship with organizational learning. Therefore, H2 was partially supported. Third, organizational learning was significantly positively related to organizational performance. H3 was supported. Finally, organizational learning play a significantly positive role in mediating the relationship between BSC communication and organizational performance. The theoretical contributions, limitations, as well as future research directions are discussed at the end of the paper.

• Bulletin of the Korean Chemical Society
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• 제31권4호
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• pp.825-828
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• 2010

To classify Glycyrrhiza species, samples of different species were analyzed by $^1H$ NMR-based metabolomics technique. Partial least squares discriminant analysis (PLS-DA) was used as the multivariate statistical analysis of the 1H NMR data sets. There was a clear separation between various Glycyrrhiza species in the PLS-DA derived score plots. The PLS-DA model was validated, and the key metabolites contributing to the separation in the score plots of various Glycyrrhiza species were lactic acid, alanine, arginine, proline, malic acid, asparagine, choline, glycine, glucose, sucrose, 4-hydroxy-phenylacetic acid, and formic acid. The compounds present at relatively high levels were glucose, and 4-hydroxyphenylacetic acid in G. glabra; lactic acid, alanine, and proline in G. inflata; and arginine, malic acid, and sucrose in G. uralensis. This is the first study to perform the global metabolomic profiling and differentiation of Glycyrrhiza species using $^1H$ NMR and multivariate statistical analysis.

• 대한인간공학회지
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• 제19권3호
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• pp.23-37
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• 2000

Usability is one of the most important factors that affect customers' decision to purchase a product. Several studies have been conducted to model the relationship between the product design variables and the product usability. Since there could be hundreds of design variables to be considered in the model, a variable screening method is required. Traditional variable screening methods are based on expert opinions (Expert screening) in most Kansei engineering studies. Suggested in this study are statistical methods for screening important design variables by using the principal component regression(PCR), cluster analysis, and partial least squares(PLS) method. Product variables with high effect (PCR screening and PLS screening) or representative variables (Cluster screening) can be used to model the usability. Proposed variable screening methods are used to model the usability for 36 audio/visual products. The three analysis methods (PCR, Cluster, and PLS) show better model performance than the Expert screening in terms of $R^2$, the number of variables in the model, and PRESS. It is expected that these methods can be used for screening the product design variables efficiently.