• Journal of Distribution Science
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• v.18 no.1
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• pp.107-121
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• 2020

Purpose: Shared mobility services are the most notable in the shared economy; however, they have yet to be activated in Korea due to various regulations and conflicts amongst stakeholders. Nevertheless, shared mobility has become an irresistible trend of the times, as it can cause a great deal of economic and environmental benefits. In this vein, the purpose of this study is to contribute to the revitalization of shared mobility services in Korea and to provide service providers with implications for developing consumer-oriented marketing strategies. Research design, data and methodology: Based on the reasons that the users do not use shared mobility service, the factors influencing the behaviors of shared mobility users are structured and analyzed in a reliable, technical and procedural manner. To this end, the theory of reasoned action (TRA) of Ajzen and Fisbbein, the initial trust model (ITM), task technology fit (TTF) and switching cost (SC) are adopted. A total of 202 questionnaires were collected from the respondents who were aware of shared mobility. Then statistical processing of the collected data used SmartPLS(v.3.2.8), a PLS-SEM (Partial Least Squares Structural Equation Modeling) analysis program. The steps of the analysis are as follows. First, a PLS-Algorithm analysis was performed to evaluate the measurement model, and a Bootstraping and Blindfolding analysis was performed to evaluate the structural model and verify the hypotheses. Second, a multi-group analysis (PLS-MGA) was conducted to further analyze the differences depending on whether or not users experienced shared mobility service. Results: The results showed that initial trusts model (ITM) and task technology fit (TTF) have positive effects on users' behaviors through the mediation of the intention to use. As opposed to the assumption, switching costs did not have negative moderating effects in relation to the intention to use and users' behaviors. The influence of IT self-efficacy was significant, depending on the prior experience to use shared mobility services. Conclusions: This study will contribute to the revitalization of domestic shared mobility services and the formulation of service providers' marketing strategies. In future studies, there is a need to explore, reconstruct, and validate factors other than the impact factors of the shared mobility services used in this research model.

• Environmental Engineering Research
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• v.15 no.2
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• pp.63-70
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• 2010

In this study, the response surface method and experimental design were applied as an alternative to conventional methods for the optimization of coagulation tests. A central composite design, with 4 axial points, 4 factorial points and 5 replicates at the center point were used to build a model for predicting and optimizing the coagulation process. Mathematical model equations were derived by computer simulation programming with a least squares method using the Minitab 15 software. In these equations, the removal efficiencies of turbidity and total organic carbon (TOC) were expressed as second-order functions of two factors, such as alum dose and coagulation pH. Statistical checks (ANOVA table, $R^2$ and $R^2_{adj}$ value, model lack of fit test, and p value) indicated that the model was adequate for representing the experimental data. The p values showed that the quadratic effects of alum dose and coagulation pH were highly significant. In other words, these two factors had an important impact on the turbidity and TOC of treated water. To gain a better understanding of the two variables for optimal coagulation performance, the model was presented as both 3-D response surface and 2-D contour graphs. As a compromise for the simultaneously removal of maximum amounts of 92.5% turbidity and 39.5% TOC, the optimum conditions were found with 44 mg/L alum at pH 7.6. The predicted response from the model showed close agreement with the experimental data ($R^2$ values of 90.63% and 91.43% for turbidity removal and TOC removal, respectively), which demonstrates the effectiveness of this approach in achieving good predictions, while minimizing the number of experiments required.

• Food Science and Preservation
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• v.18 no.2
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• pp.156-164
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• 2011

This study was conducted to develop a portable quality evaluation system of bee-honey by near infrared spectroscopic technique. Two kinds of bee-honeys from acacia and polyflower sources were tested in this study. The system consists of power supply, tungsten-halogen lamp, detector, and optical fiber probe. Performance of the system was analyzed by comparing the prediction accuracy of the laboratory spectrophotometer. Total of 346 spectra was divided into a calibration set and a prediction set. The PLS (Partial Least Squares) models were developed to predict the quality parameters of bee-honeys. Reflectance spectra, moisture contents, ash, invert sugar, sucrose, F/G ratio, HMF(hydroxy methyl furfural), and $C^{12}/C^{13}$ ratio of honeys were measured. The PLS models of the laboratory spectrophotometer showed good relationships between predicted and measured quality parameters of honeys in the wavelength range of 1.100~2.200 nm. The PLS analysis of the portable quality evaluation system showed good relationships between predicted and measured quality parameters of honeys in the wavelength range of 1.100~1.300 nm and 1.400~1.700 nm. The results showed the feasibility of the portable quality evaluation system to determine the quality parameters of bee-honey in the field during harvesting.

• Korean Journal of Construction Engineering and Management
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• v.13 no.2
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• pp.128-136
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• 2012

In this study, we investigated the macroeconomic variables that affect housing prices thus creating a large impact on people's lives as well as the real estate market. For the study, the macroeconomic variables able to influence the House Rental Price (housing price by lease or deposit) were used for an analysis as follows: housing sales price index, household loans rate, total household savings, the number of employees and a multiple regression analysis was performed using a time series for each macroeconomic variable. As a result of the analysis, the House Rental Price was affected by all of four macroeconomic variables. The House Rental Price increased as each variable enlarged. In conclusion, this study may be useful for finding a solution for stabilizing the House Rental Price as well as for the establishment of efficient and sustainable policies for the housing market.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.149-158
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• 2009

Tsutsugamushi fever occupies more than 80% of total fall epidemic diseases and has an incubation period of 1 or 2 weeks as well. We have assumed that the incubation period distribution is gamma and therefore, reach an agreement that the infected distribution is normal with ${\hat{\mu}}=309.92$, ${\hat{\sigma}}=14.154$ by back calculation method. The infection cases are found severely large around the month of October. The infection case distribution demonstrates the incidence number increasing rapidly and progresses fast during the month of November. In this study, we have calculated the future prevalence number of maximum 1,200 people by inferred infection probability and incubation period distribution with some sort of limitation that the trend of increasing incidence number is not taking into an account. We considered the SIRS model which is also known as epidemic model, familiar to interaction between epidemiological classes. Our estimated parameters converged well with the initial parameter values.

• Current Optics and Photonics
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• v.1 no.3
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• pp.186-195
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• 2017

Obtaining accurate visibility measurements is a common atmospheric optical problem, and of vital significance to civil aviation. To effectively evaluate and improve the accuracy of visibility measurements, an outdoor atmospheric simulation chamber with dimensions of $1.8{\times}1.6{\times}55.7m^3$ was constructed. The simulation chamber could provide a relatively homogeneous haze environment, in which the visibility varied from 10 km to 0.2 km over 5 hours. A baseline-changing visibility measurement system was constructed in the chamber. A mobile platform (receiver) was moved from 5 m to 45 m, stopping every 5 m, to measure and record the transmittance. The total least-squares method was used to fit the extinction coefficient. During the experiment conducted in the chamber, the unit weight variance was as low as $1.33{\times}10^{-4}$ under high-visibility conditions, and the coefficient of determination ($R^2$) was as high as 0.99 under low-visibility conditions, indicating high stability and accuracy of the system used to measure the extinction coefficients and strong consistency between repeated measurements. A Grimm portable aerosol spectrometer (PAS) was used to record the aerosol distribution, and then Mie theory was used to calculate the extinction coefficients. The theoretical results were found to be consistent with the measurements and exhibited a positive correlation, although they were higher than the measured values.

• Journal of Agricultural Extension & Community Development
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• v.15 no.4
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• pp.659-681
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• 2008

The purpose of this study is to empirically analyze factors that influence farm managers' intentions to use an agricultural farm management information systems. It focused on "LFcenter System," a leading information system operated by the Rural Development Administration for farm management. Participants of this study are classified into two groups: a group of leading farm managers and a group fo regular farm managers. A total of 192 survey samples on users' intentions are collected; 85 samples from leading farm managers and 107 from regular farm managers. The theoretical background of this study is developed based on Theory of Reasoned Action(TRA), Technology Acceptance Model(TAM), Diffusion of Innovation(DOI), Social Cognitive Theory(SCT), and Theory of Planned Behavior(TPB). Partial Least Squares(PLS) method is used to test a proposed Structural Equation Model(SEM), including nine hypotheses. The differences between two groups are investigated using Smith-Satterthwait test. The findings from this study are: First of all, in terms of average comparison of most variables used in this study, a group of leading farm managers shows higher value that the other group in most cases. Second, hypothesis tests how that "subjective norms", "goal to study", "perceived usefulness", "perceived enjoyment", and "intention to use" significantly influence the intention to use an agricultural management information system in the group of leading farm managers. However, "subjective norms", "goal to study", "perceived ease of use", "perceived usefulness", "perceived enjoyment", and "intention to use" turned out to significantly influence the intention to use an agricultural management information system in the group of regular farms managers. Based on the results of Smith-Satterthwait test, compared with a group of leading farms managers, the impact of "goal to study" on "intention to use" is significantly stronger. On the other hand, in the group of leading farms managers, "perceived usefulness" and "perceived enjoyment" turned out to be main drivers of "intention to use."

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.12
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• pp.1948-1956
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• 2020

Objective: The purpose of this study was to reveal the metabolic shift in the fungus cocultured with the methanogen (Methanobrevibacter thaueri). Methods: Gas chromatography-mass spectrometry was used to investigate the metabolites in anaerobic fungal (Pecoramyces sp. F1) cells and the supernatant. Results: A total of 104 and 102 metabolites were detected in the fungal cells and the supernatant, respectively. The partial least squares-discriminant analysis showed that the metabolite profiles in both the fungal cell and the supernatant were distinctly shifted when co-cultured with methanogen. Statistically, 16 and 30 metabolites were significantly (p<0.05) affected in the fungal cell and the supernatant, respectively by the co-cultured methanogen. Metabolic pathway analysis showed that co-culturing with methanogen reduced the production of lactate from pyruvate in the cytosol and increased metabolism in the hydrogenosomes of the anaerobic fungus. Citrate was accumulated in the cytosol of the fungus co-cultured with the methanogen. Conclusion: The co-culture of the anaerobic fungus and the methanogen is a good model for studying the microbial interaction between H₂-producing and H₂-utilizing microorganisms. However, metabolism in hydrogenosome needs to be further studied to gain better insight in the hydrogen transfer among microorganisms.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.1
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• pp.79-90
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• 2020

Objective: In the present study, an liquid chromatography/mass spectrometry (LC/MS) metabolomics approach was performed to investigate potential biomarkers of milk production in high- and low-milk-yield dairy cows and to establish correlations among rumen fluid metabolites. Methods: Sixteen lactating dairy cows with similar parity and days in milk were divided into high-yield (HY) and low-yield (LY) groups based on milk yield. On day 21, rumen fluid metabolites were quantified applying LC/MS. Results: The principal component analysis and orthogonal correction partial least squares discriminant analysis showed significantly separated clusters of the ruminal metabolite profiles of HY and LY groups. Compared with HY group, a total of 24 ruminal metabolites were significantly greater in LY group, such as 3-hydroxyanthranilic acid, carboxylic acids, carboxylic acid derivatives (L-isoleucine, L-valine, L-tyrosine, etc.), diazines (uracil, thymine, cytosine), and palmitic acid, while the concentrations of 30 metabolites were dramatically decreased in LY group compared to HY group, included gentisic acid, caprylic acid, and myristic acid. The metabolite enrichment analysis indicated that protein digestion and absorption, ABC transporters and unsaturated fatty acid biosynthesis were significantly different between the two groups. Correlation analysis between the ruminal microbiome and metabolites revealed that certain typical metabolites were exceedingly associated with definite ruminal bacteria; Firmicutes, Actinobacteria, and Synergistetes phyla were highly correlated with most metabolites. Conclusion: These findings revealed that the ruminal metabolite profiles were significantly different between HY and LY groups, and these results may provide novel insights to evaluate biomarkers for a better feed digestion and may reveal the potential mechanism underlying the difference in milk yield in dairy cows.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.46 no.5
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• pp.401-406
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• 2001

The applicability of non-destructive near infrared reflectance spectroscopic (NIRS) method was tested to determine the protein and oil contents of intact soybean [Glycine max (L.) Merr.] seeds. A total of 198 soybean calibration samples and 101 validation samples were used for NIRS equation development and validation, respectively. In the developed non-destructive NIRS equation for analysis of protein and oil contents, the most accurate equation was obtained at 2, 8, 6, 1(2nd derivative, 8 nm gap, 6 points smoothing, and 1 point second smoothing) and 2, 1, 20, 10 math treatment conditions with Standard Normal Variate and Detrend (SNVD) scatter correction method and entire spectrum (400-2500 nm) by using Modified Partial Least Squares (MPLS) regression, respectively. Validation of these non-destructive NIRS equations showed very low bias (protein: 0.060%, oil: -0.017%) and standard error of prediction (SEP, protein: 0.568 %, oil : 0.451 %) as well as high coefficient of determination ($R^2$, protein: 0.927, oil: 0.906). Therefore, these non-destructive NIRS equations can be applicable and reliable for determination of protein and oil content of intact soybean seeds, and non-destructive NIRS method could be used as a mass screening technique for selection of high protein and oil soybean in breeding programs.