• Journal of Information Technology Services
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• v.9 no.1
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• pp.27-42
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• 2010

Recently, many organizations are actively adopting Enterprise Architecture (EA) as a methodology to manage IT assets and build IT-based business system. However, most existing studies on EA have focused on the adoption stage of EA. Now the research concerning effective management and utilization of EA after adopting EA is keenly required. This study intended to empirically examine how the role of EA operating unit and the EA utilization capability of organizational members impact on EA performance at the post-adoption stage of EA. Based on Resource Based View (RBV), this study proposed the model and the hypotheses describing that the impact of the role of EA operating unit on EA performance is mediated by the EA utilization capability of organizational members. In order to test the hypotheses, the field survey whose respondents were seventy four Korean public agencies which have adopted EA was conducted by means of questionnaire. Data analysis was done with partial least square (PLS), which is a structural equation modeling (SEM) technique that uses a component-based approach to estimation. The results of the empirical analyses showed that the organizational operation ability of EA operating unit significantly influenced EA performance via the EA utilization capability of organizational members, but that EA education and training performed by EA operating unit did not. The results of this study provided a lot of theoretical and practical implications regarding EA management activities at the post-adoption stage of EA to enhance EA performance.

• Journal of Biosystems Engineering
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• v.38 no.4
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• pp.312-317
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• 2013

Purpose: Conventional methods used to evaluate seeds viability are destructive, time consuming, and require the use of chemicals, which are not feasible to implement to process plant in seed industry. In this study, the effectiveness of Fourier transform near infrared (FT-NIR) spectroscopy to differentiate between viable and nonviable watermelon seeds was investigated. Methods: FT-NIR reflectance spectra of both viable and non-viable (aging) seeds were collected in the range of 4,000 - 10,000 $cm^{-1}$ (1,000 - 2,500 nm). To differentiate between viable and non-viable seeds, a multivariate classification model was developed with partial least square discrimination analysis (PLS-DA). Results: The calibration and validation set derived from the PLS-DA model classified viable and non-viable seeds with 100% accuracy. The beta coefficient of PLS-DA, which represented spectral difference between viable and non-viable seeds, showed that change in the chemical component of the seed membrane (such as lipids and proteins) might be responsible for the germination ability of the seeds. Conclusions: The results demonstrate the possibility of using FT-NIR spectroscopy to separate seeds based on viability, which could be used in the development of an online sorting technique.

• Journal of Biosystems Engineering
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• v.37 no.6
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• pp.411-419
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• 2012

Purpose: Nondestructive evaluation of seed viability is a highly demanded technique in the seed industry. In this study, hyperspectral imaging system was used for discrimination of viable and non-viable radish seeds. Method: The spectral data with the range from 400 to 1000 nm measured by hyperspectral reflectance imaging system were used. A calibration and a test models were developed by partial least square discrimination analysis (PLS-DA) for classification of viable and non-viable radish seeds. Either each data set of visible (400~750 nm) and NIR (750~1000 nm) spectra and the spectra of the combined spectral ranges were used for developing models. Results: The discrimination accuracy of calibration was 84% for visible range and 76.3% for NIR range. The discrimination accuracy of test was 84.2% for visible range and 75.8% for NIR range. The discrimination accuracies of calibration and test with full range were 92.2% and 92.5%, respectively. The resultant images based on the optimal PLS-DA model showed high performance for the discrimination of the nonviable seeds from the viable seeds with the accuracy of 95%. Conclusions: The results showed that hyperspectral reflectance imaging has good potential for discriminating nonviable radish seeds from massive amounts of viable seeds.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.469-477
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• 2020

The main objective of this paper is to examine the applicability of Linan and Chen's entrepreneurial intention model (EIM) in predicting the entrepreneurial intention. EIM is an adaptation of the Theory of Planned Behavior that focuses on entrepreneurial intention and hypothesizing slightly different patterns of relationship with regards to subjective norms. The model also includes human capital and demographic factors. Snowball sampling method was used to collect data using the entrepreneurial intention questionnaire (EIQ) through several social media platforms. The survey indicates that the overall entrepreneurial intention of Saudi students is high (mean = 5.41). Eight out of the seventeen hypothesized relationships were found to be significant. Among the demographic variables, gender-personal attitude was significant whereas self employment experience and years of business education were found to be significantly related with perceived behavioral control. The statistical analysis using partial least square structural equation modelling validated the model. All the three antecedents of entrepreneurial intention were significantly related with entrepreneurial intention. The results of this study will help policy makers to get deep understanding into the phenomenon of entrepreneurship among Saudi university students and thereby develop a conducive environment. This study also validates the entrepreneurial intention model in a different cultural context.

• Korean Journal of Food Science and Technology
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• v.38 no.2
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• pp.165-168
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• 2006

Fourier transform-near infrared spectroscopy (FT-NIRS) was evaluated for determination of total dietary fiber (TDF) content of brown rice. Enzymatic-gravimetric method was suitable to obtain reference values for calibration of NIR at 1,000-2,500 nm range. Standard error of laboratory procedure ranged 0.17 to 0.72%. Partial least square (PLS) regression was used to develop the calibration equations. Regression was performed automatically using NIRCal chemometric software. Accuracy of prediction model for TDF content was certified for regression coefficient (r), standard error of estimation (SEE) and standard error of prediction (SEP), showing 0.9780, 0.0636, and 0.0642, respectively. This prediction model can be used for determination of TDF in brown rice and would be useful for real-time analysis in food industry.

• Korean Journal of Food Science and Technology
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• v.34 no.3
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• pp.356-360
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• 2002

The honey samples harvested in 1996, 1997, and 1998 were used for calibration and validation. NIR spectra were obtained using NIR spectrometer and quartz glass device with gold coating diffuser. Multiple linear regression and partial least square were used for calibrations. The correlation coefficient (RSQ) and standard error of prediction (SEP) obtained for moisture were 0.997 and 0.1%, respectively. The RSQ and SEP for fructose and glucose were 0.926 and 0.951%, and the SEP were 0.54% and 0.52% respectively. The validation results for sucrose, maltose, HMF definition, and acidity of honey were considered to be sufficient for practical use RSQ and SEP for SCIR were 0.950 and $1.08%_{\circ}$, respectively. These results are indications of the rapid determination of purity of the honey through NIR analysis.

• Journal of Korea Port Economic Association
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• v.34 no.3
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• pp.75-92
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• 2018

The purpose of this study is to analyze whether innovation activities of logistics firms affect innovation performance and service quality improvement and whether innovation performance and service quality as a result of innovation activities affect these firm's business performance. First, I undertake a review of previous studies and theories related to innovation activity and innovation performance. Additionally, previous studies on improvement of service quality along through innovation performance were analyzed. Based on this, I set up a research structure and hypotheses. To this end, I used the workplace panel survey data of the Korea Labor Institute(KLI) and used a total of 88 samples. I use the Partial Least Square(PLS) approach to structural equation modeling. The results of the empirical analysis show that innovation activities of logistics firms have a positive effect on innovation performance and service quality improvement, and innovation performance and service quality have a positive effect on financial performance. Evidently, innovation activities bring a clear competitive advantage to the logistics firms and improve their service quality. This implies the ability of logistics firms to survive amidst competition while getting a competitive edge.

• Food Science and Preservation
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• v.24 no.1
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• pp.145-152
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• 2017

In this study, near infrared (NIR) spectroscopy known as a non-destructive analysis technique was applied to investigate peptide cleavage and consequent release of amino acids in soybean lumps as affected by its moisture content and incubation time during fermentation at 25 for 3 weeks. The NIR spectra of the soybean lump semi-dried and soaked in saline water showed that absorption intensity around 1,400 nm originating from hydrogen bonds of water decreased and absorption band shifted to 1,430 nm as moisture content decreased during incubation at 25 for 3 weeks. In addition, absorption around 2,050 nm which was assigned to amino groups increased as incubation time increased. NIR spectra data from 1,000 to 2,250 nm showed higher accuracy in the discriminant analysis between outside and inside parts of fermented soybean lumps than visible spectra result. NIR spectroscopy for the amino acid and moisture contents in traditional fermented soybean lumps showed relatively good accuracy with the multiple correlation coefficient ($R^2$) of 0.91 and 0.81, respectively, and root mean square error of cross validation (RMSECv) of 0.23 and 0.83%, respectively, in partial least square regression (PLSR). These results indicate that NIR spectral observations could be applicable to control the fermentation process for preparation of soybean products.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.147-165
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• 2008

IT education can be summarized as persuading the educatee to accept IT. The persuasion is made by delivering the messages for how-to-use and where-to-use to the educatee, which leads formulation of a belief structure for using IT. Therefore, message based persuasion theory, as well as IT acceptance theories such as technology acceptance model(TAM), would play a very important role for explaining IT education. According to elaboration likelihood model(ELM) that has been considered as one of the most influential persuasion theories, people change attitude or perception by two routes, central route and peripheral route. In central route, people would think critically about issue-related arguments in an informational message. In peripheral route, subjects rely on cues regarding the target behavior with less cognitive efforts. Moreover, such persuasion process is not a one-shot program but continuous repetition with feedbacks, which leads to changing a belief structure for using IT. An educatee would get more knowledge and experiences of using IT as following an education program, and be more dependent on a central route than a peripheral route. Such change would reformulate a belief structure which is different from the intial one. The objectives of this study are the following two: First, an identification of the relationship between ELM and belief structures for using IT. Especially, we analyze the effects of message interpretation through both of central and peripheral routes on perceived usefulness which is an important explaining variable in TAM and perceived use control which have perceived ease of use and perceived controllability as sub-dimensions. Second, a longitudinal analysis of the above effects. In other words, change of the relationship between interpretation of message delivered by IT education and beliefs of IT using is analyzed longitudinally. For achievement of our objectives, we suggest a research model, which is constructed as three-layered. While first layer has a dependent variable, use intention, second one has perceived usefulness and perceived use control that has two sub-concepts, perceived ease of use and perceived controllability. Finally, third one is related with two routes in ELM, source credibility and argument quality which are operationalization of peripheral route and central route respectively. By these variables, we suggest five hypotheses. In addition to relationship among variables, we suggest two additional hypotheses, moderation effects of time in the relationships between perceived usefulness and two routes. That is, source credibility's influence on perceived usefulness is decreased as time flows, and argument quality's influence is increased. For validation of it, our research model is tested empirically. With measurements which have been validated in the other studies, we survey students in an Excel class two times for longitudinal analysis. Data Analysis is done by partial least square(PLS), which is known as an appropriate approach for multi-group comparison analysis with a small sized sample as like this study. In result. all hypotheses are statistically supported. One of theoretical contributions in this study is an analysis of IT education based on ELM and TAM which are considered as important theories in psychology and IS theories respectively. A longitudinal analysis by comparison between two surveys based on PLS is also considered as a methodological contribution. In practice, finding the importance of peripheral route in early stage of IT education should be notable.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.11
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• pp.1633-1642
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• 2017

Objective: Evaluation of exercise effects in racehorses is important in horseracing industry and animal health care. In this study, we compared metabolic patterns between before and after exercise to screen metabolic biomarkers for exercise effects in thoroughbreds. Methods: The concentration of metabolites in muscle, plasma, and urine was measured by $^1H$ nuclear magnetic resonance (NMR) spectroscopy analysis and the relative metabolite levels in the three samples were compared between before and after exercise. Subsequently, multivariate data analysis based on the metabolic profiles was performed using orthogonal partial least square discriminant analysis (OPLS-DA) and variable important plots and t-test was used for basic statistical analysis. Results: From $^1H$ NMR spectroscopy analysis, 35, 25, and 34 metabolites were detected in the muscle, plasma, and urine. Aspartate, betaine, choline, cysteine, ethanol, and threonine were increased over 2-fold in the muscle; propionate and trimethylamine were increased over 2-fold in the plasma; and alanine, glycerol, inosine, lactate, and pyruvate were increased over 2-fold whereas acetoacetate, arginine, citrulline, creatine, glutamine, glutarate, hippurate, lysine, methionine, phenylacetylglycine, taurine, trigonelline, trimethylamine, and trimethylamine N-oxide were decreased below 0.5-fold in the urine. The OPLS-DA showed clear separation of the metabolic patterns before and after exercise in the muscle, plasma, and urine. Statistical analysis showed that after exercise, acetoacetate, arginine, glutamine, hippurate, phenylacetylglycine trimethylamine, trimethylamine N-oxide, and trigonelline were significantly decreased and alanine, glycerol, inosine, lactate, and pyruvate were significantly increased in the urine (p<0.05). Conclusion: In conclusion, we analyzed integrated metabolic patterns in the muscle, plasma, and urine before and after exercise in racehorses. We found changed patterns of metabolites in the muscle, plasma, and urine of racehorses before and after exercise.