• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.3
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• pp.321-327
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• 2007

This study presents a new gridless finite difference method for solving elastic crack problems. The method constructs the Taylor expansion based on the MLS(Moving Least Squares) method and effectively calculates the approximation and its derivatives without differentiation process. Since no connectivity between nodes is required, the modeling of discontinuity embedded in the domain is very convenient and discontinuity effect due to crack is naturally implemented in the construction of difference equations. Direct discretization of the governing partial differential equations makes solution process faster than other numerical schemes using numerical integration. Numerical results for mode I and II crack problems demonstrates that the proposed method accurately and efficiently evaluates the stress intensity factors.

• Journal of Ginseng Research
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• v.44 no.3
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• pp.413-423
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• 2020

Background: Ginseng berries (GBs) show temporal metabolic variations among different maturation stages, determining their organoleptic and functional properties. Methods: We analyzed metabolic variations concomitant to five different maturation stages of GBs including immature green (IG), mature green (MG), partially red (PR), fully red (FR), and overmature red (OR) using mass spectrometry (MS)-based metabolomic profiling and multivariate analyses. Results: The partial least squares discriminant analysis score plot based on gas chromatography-MS datasets highlighted metabolic disparity between preharvest (IG and MG) and harvest/postharvest (PR, FR, and OR) GB extracts along PLS1 (34.9%) with MG distinctly segregated across PLS2 (18.2%). Forty-three significantly discriminant primary metabolites were identified encompassing five developmental stages (variable importance in projection > 1.0, p < 0.05). Among them, most amino acids, organic acids, 5-C sugars, ethanolamines, purines, and palmitic acid were detected in preharvest GB extracts, whereas 6-C sugars, phenolic acid, and oleamide levels were distinctly higher during later maturation stages. Similarly, the partial least squares discriminant analysis based on liquid chromatography-MS datasets displayed preharvest and harvest/postharvest stages clustered across PLS1 (11.1 %); however, MG and PR were separated from IG, FR, and OR along PLS2 (5.6 %). Overall, 24 secondary metabolites were observed significantly discriminant (variable importance in projection > 1.0, p < 0.05), with most displaying higher relative abundance during preharvest stages excluding ginsenosides Rg1 and Re. Furthermore, we observed strong positive correlations between total flavonoid and phenolic metabolite contents in GB extracts and antioxidant activity. Conclusion: Comprehending the dynamic metabolic variations associated with GB maturation stages rationalize their optimal harvest time per se the related agroeconomic traits.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.44-44
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• 2017

The objective of this study was to evaluate firmness, and sweetness index (SI) of tomatoes (Lycopersicum esculentum) by using hyperspectral imaging (HSI) in the range of 1000-1400 nm. The mean spectra of the 95 matured tomato samples were extracted from the hyperspectral images, and the reference firmness and sweetness index of the same sample were measured and calibrated with their corresponding spectral data by partial least squares (PLS) regression with different preprocessing method. The results showed that the regression model developed by PLS regression based on Savitzky-Golay (S-G) second-derivative preprocessed spectra resulted in better performance for firmness, and SI of tomatoes compared to models developed by other preprocessing methods, with correlation coefficients (rpred) of 0.82, and 0.74 with standard error of prediction (SEP) of 0.86 N, and 0.63 respectively. Then, the feature wavelengths were identified using model-based variable selection method, i.e., variable important in projection (VIP), resulting from the PLS regression analyses and finally chemical images were derived by applying the respective regression coefficient on the spectral image in a pixel-wise manner. The resulting chemical images provided detailed information on firmness, and sweetness index (SI) of tomatoes. Therefore, these research demonstrated that HIS technique has a potential for rapid and non-destructive evaluation of the firmness and sweetness index of tomatoes.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.3
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• pp.211-215
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• 2004

Near infrared reflectance spectroscopy (NIRS) is a rapid and accurate analytical method for determining the composition of agricultural products and feeds. This study was conducted to determine tocopherol and tocotrienol contents in rice bran by using NIRS system. Total 80 rice bran samples previously analyzed by HPLC were scanned by NIRS and over 60 samples were selected for calibration and validation equation. A calibration equation calculated by MPLS(modified partial least squares) regression technique was developed and coefficient of determination for tocopheyol and tocotyienol content were 0.975 and 0.984, respectively, in calibration sets. Each calibration equation was fitted to validation set that was performed with the remaining samples not included is the calibration set, which showed high positive correlation both in tocopherol and tocotrienol content file. This results demonstrate that the developed NIRS equation can be practically used as a rapid screening method for quantification of tocopherol and tocotrienol contents in rice bran.

• Korean Journal of Medicinal Crop Science
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• v.10 no.5
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• pp.340-343
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• 2002

Near infrared reflectance spectroscopy (NIRS) has become widely accepted for rapid quantitative analysis of components in some crops. Our object was to determine icariin contents in whole plant of Epimedium koreanum by using an NIRS system. Total 150 plant samples previously analyzed by HPLC were scanned by NIRS and 68 samples were selected for calibration and validation equation. A calibration equation calculated by MPLS(modified partial least squares) regression technique was developed and a coefficient of determination in calibration and validation sets were 0.95 and 0.82, respectively. A comparison between NIRS estimation and HPLC value was performed with the remaining samples not included in the calibration and validation sets. Most of samples also showed a positive correlation like a validation set. Our results demonstrate that this developed NIRS equation can be practically used as a mass screening method for rapid quantification of icarin contents in Epimedium koreanum N.

• Journal of the Korean Wood Science and Technology
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• v.44 no.6
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• pp.852-863
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• 2016

Wood-plastic composite (WPC) is a promising and sustainable material, and refers to a combination of wood and plastic along with some binding (adhesive) materials. In comparison to pure wood material, WPCs are in general have advantages of being cost effective, high durability, moisture resistance, and microbial resistance. The properties of WPCs come directly from the concentration of different components in composite; such as wood flour concentration directly affect mechanical and physical properties of WPCs. In this study, wood powder concentration in WPC was determined by Fourier transform near-infrared (FT-NIR) and Fourier transform infrared (FT-IR) spectroscopy. The reflectance spectra from WPC in both powdered and tableted form with five different concentrations of wood powder were collected and preprocessed to remove noise caused by several factors. To correlate the collected spectra with wood powder concentration, multivariate calibration method of partial least squares (PLS) was applied. During validation with an independent set of samples, good correlations with reference values were demonstrated for both FT-NIR and FT-IR data sets. In addition, high coefficient of determination (${R^2}_p$) and lower standard error of prediction (SEP) was yielded for tableted WPC than powdered WPC. The combination of FT-NIR and FT-IR spectral region was also studied. The results presented here showed that the use of both zones improved the determination accuracy for powdered WPC; however, no improvement in prediction result was achieved for tableted WPCs. The results obtained suggest that these spectroscopic techniques are a useful tool for fast and nondestructive determination of wood concentration in WPCs and have potential to replace conventional methods.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1511-1511
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• 2001

Energy content, expressed as calories per gram, is an important part of the evaluation and marketing of foods in developed countries. Currently accepted methods of measurement of energy by U.S. food labeling legislation include measurement of gross calories by bomb calorimetry with an adjustment for undigested protein and by calculation using specific factors for the energy values of protein, carbohydrate less the amount of insoluble dietary fiber, and total fat. The ability of NIRS to predict the energy value of diverse, processed and unprocessed cereal food products was investigated. NIR spectra of cereal products were obtained with an NIR Systems monochromator and the wavelength range used for analysis was 1104-2494 nm. Gross energy of the foods was measured by oxygen bomb calorimetry (Parr Manual No. 120) and expressed as calories per gram (CPGI, range 4.05-5.49 cal/g). Energy value was adjusted for undigested protein (CPG2, range 3.99-5.38 cal/g) and undigested protein and insoluble dietary fiber (CPG3, range 2.42-5.35 cal/g). Using a multivariate analysis software package (ISI International, Inc.) partial least squares models were developed for the prediction of energy content. The standard error of cross validation and multiple coefficient of determination for CPGI using modified partial least squares regression (n=127) was 0.060 cal/g and 0.95, respectively, and the standard error of performance, coefficient of determination, bias and slope using an independent validation set (n=59) were 0.057 cal/g, 0.98, -0.027 cal/g and 1.05 respectively. The PLS loading for factor 1 (Pearson correlation coefficient 0.92) had significant absorption peaks correlated to C-H stretch groups in lipid at 1722/1764 nm and 2304/2346 nm and O-H groups in carbohydrate at 1434 and 2076 nm. Thus the model appeared to be predominantly influenced by lipid and carbohydrate. Models for CPG2 and CPG3 showed similar trends with standard errors of performance, using the independent validation set, of 0.058 and 0.088 cal/g, respectively, and coefficients of determination of 0.96. Thus NIRS provides a rapid and efficient method of predicting energy content of diverse cereal foods.

• The Journal of the Korea Contents Association
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• v.17 no.4
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• pp.247-255
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• 2017

The study figured out the preference factors which should be considered for investor on decision making of unsold apartment and analyzed by comparing the difference according to the type. Then, it investigated the preference factors through the previous studies to analyze the influence factor of decision making and demonstrated the effects through the PLS (Partial Least Squares) regression. In addition, it separated the target type to tenants and construction firms and carried out the survey for comparing the preference factors of investor type. The result of analysis found out that tenants emphasis on preference factors such as the internal factor (1.141), conditional relaxation (1.114), environment factor (1.107), social factor (1.048), external factor (1.030), educational environment factor (1.010) and etc. Then, construction firms emphasis on preference factors such as the social factor (1.401), environment factor (1.251), conditional relaxation (1.133) and etc. In addition, common preferences factors are the conditional relaxation, social factor, environment factor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2076-2082
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• 2017

Users of Smartphone in Korea are using the majority of the economically active population over 99% and experts have seen that they have reached saturation after the initial formation stages. The purpose of this study is to investigate the influencing factors of dominant design attributes on the intention of continuous use of Smartphone users. Predictor factors were selected perceived usefulness and perceived ease of use suggested on extended the technology acceptance model. The concept model was completed by selecting the dominant design attribute as a mediator. Participants of this study were 135 Smartphone users in Busan Gyeongnam and Iksan Jeonbuk province in accordance with convenience sampling. IBM SPSS Statistics 19 were employed for descriptive statistics, Smart PLS (partial least squares) was employed for confirmatory factor analysis and path analysis of casual relationship among variables. Therefore, when moderating mediated factor of dominant design and attitude, factor of continuous usage intention showed 76% explanatory power.

• 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.