• Journal of Agricultural Extension & Community Development
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• v.19 no.3
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• pp.699-727
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• 2012

Conditions of farm crop switching are affected by several important external factors such as agricultural products import opening, policy support, and climate change. Farming environment is always changing; barriers to imports are becoming lower and lower because of FTA and others, and climate change affects a boundary line of cultivation. Those situations give farmers motivation to change crops in order to cope with them. In addition, crop switching has been done in response to the local government measures about purchase of local agricultural products according to the local food and the expansion of organic agricultural products in school meal. Even though the favorable environment toward crop switching has been created, there are not many researches or outcomes regarding crop switching. Only few studies focus on the list of decision-making in crop switching, and locally suitable crop selection is not treated. In order to utilize crop switching as a farm management strategy, the proper frame should be studied and practical researches on application possibility also need. Therefore, study on crop switching is in a timely, proactive manner because farms catch the chance of expansion of school meal by changing crops. This paper applies HERO model used for venture foundation process to crop switching process. Success factors of HERO model are comprised of Habitate, Entrepreneurship, Resource, and Opportunity, and these phased application factors are applied to crop switching process. By doing so, each phase success factor of crop switching can be uncovered. Three farm organizations supplying organic agricultural products to schools are studied in Gyeonggi province. As a result, the stabilization stage cannot be achieved because of the habitate conditions and social conditions with low risk bearing of crop switching and current school meal systems are the main problems to block the diversification of risks. In order to succeed in crop switching, constructing the habitate in local districts or in systems of school meal is more effective than supporting each farm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.150-160
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• 2016

The quality of service in ERP services is a key issue in innovating the ERP performance as an IT service for corporations. Currently, most of the research works for this area are based on the existing quality models such as SERVQUAL, which are said not to measure service quality properly. Also, it does not consider the factor of the system acceptance, which is thought to be closely related to the quality of service in this type of IT services. Therefore, a research model is required, which can address the issues related to the ERP service quality measurements. In this paper, new research models have been proposed, and empirical data obtained from SME's ERP users have been applied to the proposed model to analyze the causal relationship between quality factors and to identify the most suitable quality measures. Also, the relationship between the service quality and the system acceptance was analyzed using a combined model. The results show that factors such as productivity and convenience affects the quality mostly and that the most appropriate measure for the service quality of ERP service is satisfaction. Also, for the system acceptance, the ease-of-use is the main factor. And, the service quality and system acceptance shows a strong correlation. This means that, in order to enhance the quality of ERP services, the service provider needs to provide customers with productivity-enhanced user-friendly IT services and active product support. The work of this research can help to improve the service quality and the user acceptance of ERP services and to lead further research works in this area.

• Food Science of Animal Resources
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• v.35 no.1
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• pp.108-113
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• 2015

The purpose of this study was to develop predictive models for the growth of Listeria monocytogenes in pork Bulgogi at various storage temperatures. A two-strain mixture of L. monocytogenes (ATCC 15313 and isolated from pork Bulgogi) was inoculated on pork Bulgogi at 3 Log CFU/g. L. monocytogenes strains were enumerated using general plating method on Listeria selective medium. The inoculated samples were stored at 5, 15, and $25^{\circ}C$ for primary models. Primary models were developed using the Baranyi model equations, and the maximum specific growth rate was shown to be dependent on storage temperature. A secondary model of growth rate as a function of storage temperature was also developed. As the storage temperature increased, the lag time (LT) values decreased dramatically and the specific growth rate of L. monocytogenes increased. The mathematically predicted growth parameters were evaluated based on the modified bias factor ($B_f$), accuracy factor ($A_f$), root mean square error (RMSE), coefficient of determination ($R^2$), and relative errors (RE). These values indicated that the developed models were reliably able to predict the growth of L. monocytogenes in pork Bulgogi. Hence, the predictive models may be used to assess microbiological hygiene in the meat supply chain as a function of storage temperature.

• Fashion & Textile Research Journal
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• v.7 no.3
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• pp.291-300
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• 2005

The purpose of this study is to investigate, analyze the purchasing behavior of fashion goods according to life style and role model of preteen generation, and provide manager or marketing planner for the reference data so that they can understand preteen generation and make proper strategy efficiently. So called, preteen market focusing on 1014 generation (from ten to fourteen years old) is highlighted. This generation created between the year 1989 to 1993 after Seoul Olympic monopolize parent's love in abundant economic environment and rise to the core of consumption subject. Products aiming at this preteen generation continuously though consumption mind was shrunk greatly due to recession. Only 2~3 years before preteen market was regarded as grey zone which doesn't belong to not only children (between six and nine years old) but also teenagers (between fifteen to eighteen years old). But in recent day their purchasing powers have increased rapidly and age group is divided on details, so that preteen market has become a niche market. Subjects were 333 persons consisting of students in the 4th~6th grade of primary school and the 1st~2nd grade of middle school in Daegu city. Measuring instruments are as follows: 5questions to differentiate preteen generation, 22 questions to measure life style, 17questions (which have six sub-factors such as purchase motive, factor of product selection, utilization of informant, purchase time, purchase place, and purchase method) to measure the purchase behavior of fashion goods measurement, and 16 questions (which have four sub-factors such as parent, entertainer & sports stars, brothers and sisters, friends) to measure model of role. Statistical data were processed by SPSS 10.0 programs. Frequencies, Factor analysis, Cluster analysis, ANOVA, Cross analysis, Multiplex regression analysis, and Duncan's multiple range test were carried out.

• KIISE Transactions on Computing Practices
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• v.22 no.12
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• pp.681-686
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• 2016

Software defect prediction is an important factor in efficient project management and success. The severity of the defect usually determines the degree to which the project is affected. However, existing studies focus only on the presence or absence of a defect and not the severity of defect. In this study, we proposed an ensemble model using FCM based on defect severity. The severity of the defect of NASA data set's PC4 was reclassified. To select the input column that affected the severity of the defect, we extracted the important defect factor of the data set using Random Forest (RF). We evaluated the performance of the model by changing the parameters in the 10-fold cross-validation. The evaluation results were as follows. First, defect severities were reclassified from 58, 40, 80 to 30, 20, 128. Second, BRANCH_COUNT was an important input column for the degree of severity in terms of accuracy and node impurities. Third, smaller tree number led to more variables for good performance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.10
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• pp.4543-4549
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• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The Burr distribution applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$.

• Journal of Biosystems Engineering
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• v.39 no.3
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• pp.151-157
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• 2014

Purpose: In order to develop strategies to prevent farm-work accidents relating to agricultural machinery, influential factors were examined in this paper. The effects of these factors were quantified using logistic regression. Methods: Based on the results of a survey on farm-work accidents conducted by the National Academy of Agricultural Science, 21 tentative independent variables were selected. To apply these variables to regression, the presence of multicollinearity was examined by comparing correlation coefficients, checking the statistical significance of the coefficients in a simple linear regression model, and calculating the variance inflation factor. A logistic regression model and determination method of its goodness of fit was defined. Results: Among 21 independent variables, 13 variables were not collinear each other. The results of a logistic regression analysis using these variables showed that the model was significant and acceptable, with deviance of 714.053. Parameter estimation results showed that four variables (age, power tiller ownership, cognizance of the government's safety policy, and consciousness of safety) were significant. The logistic regression model predicted that the former two increased accident odds by 1.027 and 8.506 times, respectively, while the latter two decreased the odds by 0.243 and 0.545 times, respectively. Conclusions: Prevention strategies against factors causing an accident, such as the age of farmers and the use of a power tiller, are necessary. In addition, more efficient trainings to elevate the farmer's consciousness about safety must be provided.

• Journal of Korean Society of Transportation
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• v.27 no.4
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• pp.127-135
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• 2009

Most traffic information that drivers receive while driving are stored in their short-term memory and disappear within a few seconds. Contemporary modeling approaches using a dummy variable can't fully explain this phenomenon. As such, this study proposes to use utility functions of real-time in-vehicle traffic safety information (IVTSI), analyzing its safety impacts based on empirical data from an on-site driving experiment at signalized intersection approach with a limited visibility. For this, a driving stability evaluation model is developed based on driver's driving speed choice, applying an ordered probit model. To estimate the specified utility functions, the model simultaneously accounts for various factors, such as traffic operation, geometry, road environment, and driver's characteristics. The results show three significant facts. First, a normal density function (exponential function) is appropriate to explain the utility of IVTSI proposed under study over time. Second, the IVTSI remains in driver's short-term memory for up to nearly 22 second after provision, decreasing over time. Three, IVTSI provision appears more important than the geometry factor but less than the traffic operation factor.

• Journal of the Korean Society of Radiology
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• v.11 no.3
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• pp.147-151
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• 2017

Potentially lethal damage repair (PLDR) in HFL-I was investigated by delayed plating experiments. The surviving fraction data were fitted to the linear Quadratic equation ($LogSn=-n{\gamma}({\alpha}d+{\beta}d^2$) where ${\gamma}=1$ for immediate plating). And a repair factor ${\gamma}$ was developed to compare survival for immediate and delayed plating. When we only took into account the repair factor of PLDR ${\gamma}$ which was derived from the delay assay, the cell survival response th fractionated carbon ion irradiation was not fully matched. This gap suggested that consideration of another repair process is necessary. So this suggests that the various repair process plays an important role in the fractionated irradiations.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.129-140
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• 2018

In this study, we analyzed the electric vehicle (EV) purchasing behavior with market segmentation in Seoul using the binary logit model. For the model estimation, the experimental design of SP survey generated 24 scenarios with purchase price, charging station availability, and driving range of EVs. The results of market segmentation analysis indicated that the owners of subcompact and compact size cars were primarily affected by the purchasing price while those of mid and full size cars were more sensitive to the charging station availability. By housing type, the charging station availability was the most important factor for the residents of apartment while the purchase price was the most important factor to choose the EVs. These results presented that the EV supply strategy of the automobile manufacturer should be diversified according to the marketing target and the expansion of the public charging infrastructure should be the top priority in the government policy.