• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.158-166
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• 2013

This study gave attention to the people who has resistance of the social media that tens to be the use as innovations. Therefore, this study examined the determinant factors of psychological resistance of the social media such as Twitter focused on students as none-users of social media. Total of 268 none-users participated in this study. The results were as follows. First, relative advantage influenced negatively on innovation resistance. Second, perceived complexity influenced significantly not on innovation resistance. Third, perceived risk influenced positively on innovation resistance. Therefore, social media related to social relationship should improve relative advantage, the other way, decrease perceived risk such as defamation and personal attack.

• Human Ecology Research
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• v.57 no.2
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• pp.171-183
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• 2019

Convergence between technology and financial services is ubiquitous and widespread. Virtual banks represent an important aspect of financial markets that can generate value added for consumers and enhance the quality of financial services. This study explores the effect of innovation characteristics (relative advantage, compatibility, and perceived risk), consumer characteristics (status quo bias), and social mechanisms (network externality: complementarity, numbers of peers) on consumers' adoption intention and resistance to virtual banks. This study adopted an innovation resistance model with two dependent variables: adoption intention and resistance to virtual banks. An online self-administered survey was conducted and 532 or non-users of virtual banks aged 20 to 69 years old were analyzed. Frequency analysis, descriptive analysis, and hierarchical multiple regression indicated that status quo bias, relative advantage, perceived risk, complementarity, and number of peers insignificantly influence the adoption intention regarding virtual banks. Furthermore, status quo bias, relative advantage, perceived risk, and number of peers insignificantly influence the resistance to virtual banks. Female respondents have a lower adoption intention and higher resistance to virtual banks than male respondents. The findings suggest that the innovation resistance model can be useful in understanding consumers'adoption and resistance behavior as well as reveal that innovation characteristics, consumer characteristics, and social mechanism are important antecedent variables of the innovation adoption decision.

• Journal of Korean Academy of Nursing
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• v.44 no.6
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• pp.743-750
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• 2014

Purpose: The objective of this study was to provide a trend analysis of the prevalence of diabetes relative to the socioeconomic, lifestyle, and physiologic risk factors among Korean adults aged over 30 years for a 10-year period using data from the Korean National Health and Nutrition Examination Survey. Methods: Prevalence difference and the slope index of inequality were calculated for each risk factors using binomial regression by considering the repeated cross-sectional features of the data. The prevalence ratio and the relative index of inequality were calculated using log-binomial regression. Linear trend tests were performed using SAS 9.2. Results: Crude prevalence of diabetes increased over the 10-year period, and was higher for men than for women. It was very high for adults 60 years or over, consistently increasing over time. The prevalence among unemployed men, women with higher level of stress, women with hypertension, and adults with serum triglyceride levels over 135 mg/dL increased over the 10-year period in comparison with the respective control group. Conclusion: Considering the rapid economic development and associated lifestyle changes in Korea, action should be taken to control the prevalence of diabetes by both preventing and consistently monitoring these identified risk factors using a public-health approach.

• Journal of Industrial Technology
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• v.22 no.A
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• pp.127-135
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• 2002

In this study, the preliminary risk assessment for the underground storage tanks(UST) in Chunchon city was implemented using the geographical information system(GIS). The estimation variables, such as the installation year, storage capacity, the distances from streams, and from groundwater pumping wells, were selected to estimate the relative risk levels. The weighting factors were given to all the estimation variables. Cumulative scores were induced by the combination of all the scores of the corresponding variables using the buffering technique and the overlay analysis in ArcView. Using the these process, the relative risk level of each UST was estimated. Some sites in this study are simplified and reduced because the number of useable data are limited or too enormous. Thus the selection of the comprehensive estimation variables and the proper weighting values are required for the future study. The methodology in this study could be served not only for the preliminary risk assessment of UST but also for the selection of the proper location of new and old UST. And, it can be used for the effective management system of UST.

• The Plant Pathology Journal
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• v.36 no.5
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• pp.406-417
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• 2020

Early warning services for crop diseases are valuable when they provide timely forecasts that farmers can utilize to inform their disease management decisions. In South Korea, collaborative disease controls that utilize unmanned aerial vehicles are commonly performed for most rice paddies. However, such controls could benefit from seasonal disease early warnings with a lead time of a few months. As a first step to establish a seasonal disease early warning service using seasonal climate forecasts, we developed the EPIRICE Daily Risk Model for rice blast by extracting and modifying the core infection algorithms of the EPIRICE model. The daily risk scores generated by the EPIRICE Daily Risk Model were successfully converted into a realistic and measurable disease value through statistical analyses with 13 rice blast incidence datasets, and subsequently validated using the data from another rice blast experiment conducted in Icheon, South Korea, from 1974 to 2000. The sensitivity of the model to air temperature, relative humidity, and precipitation input variables was examined, and the relative humidity resulted in the most sensitive response from the model. Overall, our results indicate that the EPIRICE Daily Risk Model can be used to produce potential disease risk predictions for the seasonal disease early warning service.

• The Plant Pathology Journal
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• v.28 no.2
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• pp.172-184
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• 2012

An infection risk model for Phytophthora blight on chili pepper was developed to estimate the first date of disease occurrence in the field. The model consisted of three parts including estimation of zoosporangium formation, soil water content, and amount of active inoculum in soil. Daily weather data on air temperature, relative humidity and rainfall, and the soil texture data of local areas were used to estimate infection risk level that was quantified as the accumulated amount of active inoculum during the prior three days. Based on the analysis on 190 sets of weather and disease data, it was found that the threshold infection risk of 224 could be an appropriate criterion for determining the primary infection date. The 95% confidence interval for the difference between the estimated date of primary infection and the observed date of first disease occurrence was $8{\pm}3$ days. In the model validation tests, the observed dates of first disease occurrence were within the 95% confidence intervals of the estimated dates in the five out of six cases. The sensitivity analyses suggested that the model was more responsive to temperature and soil texture than relative humidity, rainfall, and transplanting date. The infection risk model could be implemented in practice to control Phytophthora blight in chili pepper fields.

• Journal of the Korean Operations Research and Management Science Society
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• v.28 no.1
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• pp.63-77
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• 2003

Group buying is one of the most popular transaction patterns on the internet at least in Korea. Nevertheless, it is hard to find academic researches for it in view of consumer behavior. In this paper, we analyze factors which determine consumer's attitude toward and intention of participation in Internet group buying by comparison of Internet individual one. For this purpose, we propose “lowering price”, “decreasing risk” and “reducing transaction cost” as relative advantages and "lack of product assortment" and "delay of time" as relative disadvantages over individual buying on the Internet. For empirical test, Internet users who have some experiences of individual buying but not group ones on the Internet are surveyed and analyzed. In result, a satisfying model fitness for structural equation model is derived and most hypotheses except the relationship between "decreasing risk" and "attitude toward Internet group buying" are accepted. Our results provide not only academic contribution by suggestion of a research framework but also practical insight by discussion of diverse features in Internet group buying.verse features in Internet group buying.

• Journal of the Korean Statistical Society
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• v.35 no.1
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• pp.63-77
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• 2006

Maximum product of spacings estimator is proposed in this paper as a competent alternative of maximum likelihood estimator for the parameters of exponentiated-Weibull distribution, which does work even when the maximum likelihood estimator does not exist. In addition, a Bayes type estimator known as generalized maximum likelihood estimator is also obtained for both of the shape parameters of the aforesaid distribution. Though, the closed form solutions for these proposed estimators do not exist yet these can be obtained by simple appropriate numerical techniques. The relative performances of estimators are compared on the basis of their relative risk efficiencies obtained under symmetric and asymmetric losses. An example based on simulated data is considered for illustration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.385-405
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• 2019

High Efficiency Video Coding (HEVC) enables significantly improved compression performance relative to existing standards. However, the advance also requires high computational complexity. To accelerate the intra prediction mode decision, a minimum risk Bayesian classification framework is introduced. The classifier selects a small number of candidate modes to be evaluated by a rate-distortion optimization process using the sum of absolute Hadamard transformed difference (SATD). Moreover, the proposed method provides a loss factor that is a good trade-off model between computational complexity and coding efficiency. Experimental results show that the proposed method achieves a 31.54% average reduction in the encoding run time with a negligible coding loss of 0.93% BD-rate relative to HEVC test model 16.6 for the Intra_Main common test condition.

• The Journal of Engineering Geology
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• v.28 no.3
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• pp.379-395
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• 2018

A walking trail environment can be divided into the upper part of the trail, the trail itself, and the lower part of the trail. In this study, based on field investigations, we developed a risk index for trails by considering human/societal factors that affect each of these three trail environments. A checklist was developed for field investigations, and checklist items were scored through relative importance analysis. The relative weights of items were analyzed using the AHP (Analytic Hierarchy Process) technique, revealing that the upper environment of a trail is twice as important as the rest of the environment. The importance and score of items belonging to each environment were determined. We define the risk index as the sum of the item scores. Weights were added using data from existing investigations including landslides risk rating and designated risk steep slopes. The risk index has a maximum value of 200, and the maximum and minimum calculated scores of 335 risk sections were 159 and 64.2, respectively. As a result of comparative analysis between field observations and risk index calculations, most sections at relatively low risk had risk values less than 100, and sections with high risks or that had been the site of accident yielded scores that exceeded 140.