• Journal of Preventive Medicine and Public Health
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• v.56 no.3
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• pp.221-230
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• 2023

Objectives: The second wave of coronavirus disease 2019 (COVID-19) cases in Indonesia, during which the Delta variant predominated, took place after a vaccination program had been initiated in the country. This study was conducted to assess the impact of COVID-19 vaccination on unfavorable clinical outcomes including hospitalization, severe COVID-19, intensive care unit (ICU) admission, and death using a real-world model. Methods: This single-center retrospective cohort study involved patients with COVID-19 aged ≥18 years who presented to the COVID-19 emergency room at a secondary referral teaching hospital between June 1, 2021 and August 31, 2021. We used a binary logistic regression model to assess the effect of COVID-19 vaccination on unfavorable clinical outcomes, with age, sex, and comorbidities as confounding variables. Results: A total of 716 patients were included, 32.1% of whom were vaccinated. The elderly participants (≥65 years) had the lowest vaccine coverage among age groups. Vaccination had an effectiveness of 50% (95% confidence interval [CI], 25 to 66) for preventing hospitalization, 97% (95% CI, 77 to 99) for preventing severe COVID-19, 95% (95% CI, 56 to 99) for preventing ICU admission, and 90% (95% CI, 22 to 99) for preventing death. Interestingly, patients with type 2 diabetes had a 2-fold to 4-fold elevated risk of unfavorable outcomes. Conclusions: Among adults, COVID-19 vaccination has a moderate preventive impact on hospitalization but a high preventive impact on severe COVID-19, ICU admission, and death. The authors suggest that relevant parties increase COVID-19 vaccination coverage, especially in the elderly population.

• Smart Structures and Systems
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• v.32 no.3
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• pp.153-166
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• 2023

Health monitoring of civil infrastructures, in particular, old bridges that are still in service, has become more than necessary, given the risk that a possible degradation or failure of these infrastructures can induce on the safety of users in addition to the resulting commercial and economic impact. Bridge integrity assessment has attracted significant research efforts over the past forty years with the aim of developing new damage identification methods applicable to real structures. The bridge of Ouled Mimoun (Tlemcen, Algeria) is one of the oldest railway structure in the country. It was built in 1889. This bridge, which is too low with respect to the level of the road, has suffered multiple shocks from various machines that caused considerable damage to its central part. The present work aims to analyze the stability of this bridge by identifying damages and evaluating the damage rate in different parts of the structure on the basis of a finite element model. The applied method is based on an inverse analysis of the normal stress responses that were calculated from the corresponding recorded strains, during the passage of a real train, by means of a set of strain gauges placed on certain elements of the bridge. The results obtained from the inverse analysis made it possible to successfully locate areas that were really damaged and to estimate the damage rate. These results were also used to detect an excessive rigidity in certain elements due to the presence of plates, which were neglected in the numerical reference model. In the case of the continuous bridge monitoring, this developed method will be a very powerful tool as a smart health monitoring system, allowing engineers to take in time decisions in the event of bridge damage.

• The Journal of Engineering Geology
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• v.34 no.1
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• pp.107-115
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• 2024

This study assesses forest fire susceptibility in Gangwon-do, South Korea, which hosts the largest forested area in the nation and constitutes ~21% of the country's forested land. With 81% of its terrain forested, Gangwon-do is particularly susceptible to wildfires, as evidenced by the fact that seven out of the ten most extensive wildfires in Korea have occurred in this region, with significant ecological and economic implications. Here, we analyze 480 historical wildfire occurrences in Gangwon-do between 2003 and 2019 using 17 predictor variables of wildfire occurrence. We utilized three machine learning algorithms—random forest, logistic regression, and support vector machine—to construct wildfire susceptibility prediction models and identify the best-performing model for Gangwon-do. Forest and soil map data were integrated as important indicators of wildfire susceptibility and enhanced the precision of the three models in identifying areas at high risk of wildfires. Of the three models examined, the random forest model showed the best predictive performance, with an area-under-the-curve value of 0.936. The findings of this study, especially the maps generated by the models, are expected to offer important guidance to local governments in formulating effective management and conservation strategies. These strategies aim to ensure the sustainable preservation of forest resources and to enhance the well-being of communities situated in areas adjacent to forests. Furthermore, the outcomes of this study are anticipated to contribute to the safeguarding of forest resources and biodiversity and to the development of comprehensive plans for forest resource protection, biodiversity conservation, and environmental management.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.6
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• pp.105-114
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• 2022

The purpose of this study is to analyze the influence of the nation's institutional environment on start-up intention of employees and the mediating role of risk-taking propensity in the relationship between these variables. This study classified the institutional environment into institutional profile regulation, institutional profile norms, and institutional profile recognition. The research data were collected through questionnaires for office workers belonging to domestic companies, and 322 copies of questionnaire data were used for hypothesis verification, except for questionnaires that were omitted or unfaithful. The results of this study are as follows. First, institutional profile regulations and norms were positively related to start-up intention of office workers, while institutional profile cognition had no significant effect on the start-up intention. Second, institutional profile regulations and norms were positively related to risk taking, while institutional profile cognition had no significant effect on risk taking. Finally, risk taking was found to partially mediate the relationship between institutional profile regulation and start-up intention, and completely mediate the relationship between institutional profile norms and start-up intention. The theoretical implications of this study are as follows. First, this study makes a theoretical contribution in that it revealed that the country institutional profile regulation and norms are important prerequisites for start-up intention and risk taking. Next, unlike previous studies, this study makes a theoretical contribution by presenting a start-up intention model of office workers consisting of perception of the institutional environment and risk taking, which is the individual characteristic of entrepreneurs. The practical implications of this study are as follows. First, the government and local governments should strengthen regulations on institutional profiles so that start-ups can be activated. Second, the government and local governments should strengthen the norms for institutional profiles so that start-ups can be activated. Finally, the government, local governments, and educational institutions should devise measures to strengthen the risk taking of start-ups.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9453-9458
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• 2014

Background: Breast cancer is the second leading cause of cancer death for women in the United States. Differences in survival of breast cancer have been noted among racial and ethnic groups, but the reasons for these disparities remain unclear. This study presents the characteristics and the survival curve of two racial and ethnic groups and evaluates the effects of race on survival times by measuring the lifetime data-based half-normal model. Materials and Methods: The distributions among racial and ethnic groups are compared using female breast cancer patients from nine states in the country all taken from the National Cancer Institute's Surveillance, Epidemiology, and End Results cancer registry. The main end points observed are: age at diagnosis, survival time in months, and marital status. The right skewed half-normal statistical probability model is used to show the differences in the survival times between black Hispanic (BH) and black non-Hispanic (BNH) female breast cancer patients. The Kaplan-Meier and Cox proportional hazard ratio are used to estimate and compare the relative risk of death in two minority groups, BH and BNH. Results: A probability random sample method was used to select representative samples from BNH and BH female breast cancer patients, who were diagnosed during the years of 1973-2009 in the United States. The sample contained 1,000 BNH and 298 BH female breast cancer patients. The median age at diagnosis was 57.75 years among BNH and 54.11 years among BH. The results of the half-normal model showed that the survival times formed positive skewed models with higher variability in BNH compared with BH. The Kaplan-Meir estimate was used to plot the survival curves for cancer patients; this test was positively skewed. The Kaplan-Meier and Cox proportional hazard ratio for survival analysis showed that BNH had a significantly longer survival time as compared to BH which is consistent with the results of the half-normal model. Conclusions: The findings with the proposed model strategy will assist in the healthcare field to measure future outcomes for BH and BNH, given their past history and conditions. These findings may provide an enhanced and improved outlook for the diagnosis and treatment of breast cancer patients in the United States.

• Journal of the Korea Institute of Building Construction
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• v.18 no.2
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• pp.151-159
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• 2018

Accident rate in the construction industry of South Korea is increasing every year, and it represents the highest percentage among industries. This shows that activities performed to prevent safety accidents in the country are not efficient when it comes to reduce the accident rate. In order to resolve this issue, a model for the prediction of human accidents should be established. In addition, it is required a quantification study based on pattern of human accidents. Therefore, the objective of this study is to quantify uncertainty of human accidents risk and predict how to change in various circumstances by using Monte Carlo Simulation. To achieve the objective, first, pattern of human accidents was defined. Second, insurance claim payout and information of human accidents during 14 years in construction site were collected. Third, descriptive analysis is conducted to determine the characteristics of the accident pattern. Fourth, to quantitatively analyze the pattern of the human accidents, the population of each accident occurrence and payout were estimated. Finally, estimated populations was analyzed according to characteristics of distribution by using Monte carlo simulation. In the future, this study can be used as a reference for developing the safety management checklist in construction site and development of prediction models of human accident.

• International Commerce and Information Review
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• v.13 no.3
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• pp.377-401
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• 2011

Under the WTO system, direct export support system that provides financial and tax related support is altogether prohibited. This presented an obstacle in strengthening competitiveness of Korean export business and in increasing exports continuously. One of the methods used to solve this problem was to actively leverage export insurance. In Korea, export insurance services have been conducted by the Korea Trade Insurance Corporation (k-sure) to promote export. Korea has been among the world's active users of the export insurance system. Given this situation, this paper examines the effectiveness of the Korea export insurance system in the promotion of export. In particular, this study analyzed about discriminating effects of the export insurance on the export of big and small-medium business. In order to analyze, We introduce a Export Supply Function model. In this paper, We construct two model. The one is about big business, the other is small-medium business. For empirical analysis, unit-root test was conducted to understand the safety of time series. The results show that all variables are not I(0) time series. Instead, they are I(1) time series. To this, cointegration verification was conducted based on the use of Johansen verification method to define the existence (or non-existence) of long-term balance relationship among variables. The results come out as follows. The export insurance of big business has a stronger effect on export than that of small-medium business. The cause of these results is due to the distinct structure of Korea industries. In view of the fact that the insurance can make the risk decreased. We can say that the export insurance affects the export of a high-risk country.

• Research in Plant Disease
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• v.26 no.4
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• pp.229-238
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• 2020

Field validation of PBcast, an infection risk model for Phytophthora blight of pepper, was conducted through a designed field experiment in 2012 and 2013. Conduciveness of weather conditions at 26 locations in Korea in 2014-2017 was also evaluated using PBcast. The PBcast estimated daily infection risk (IR) of Phytophthora capsici based on weather and soil texture data. In the designed filed experiment, four treatments including routine sprays at 7-day intervals (RTN7), forecast-based sprays when IR reached 200 (IR200) and 224 (IR224), and no spray (CTRL) were compared in terms of disease incidence and number of sprays recommended for disease control. In 2012, IR had reached over 200 twice, but never reached 224. In 2013, IR had reached over 200 three times and once higher than 224. The RTN7 plots were sprayed 17 and 18 times in 2012 and 2013, respectively. Weather conditions throughout the country were generally conducive for Phytophthora blight and 3-4 times of fungicide sprays would have been reduced if the PBcast forecast information was adopted in the decision-making for fungicide sprays. In conclusion, the PBcast forecast would be useful to reduce fungicide applications without losing the disease control efficacy to protect pepper crop from Phytophthora blight.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.4
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• pp.1289-1298
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• 2014

Pavement crack sealing method, which is one of the methods to maintain and repair the road, prevents the extending of cracks by repairing cracks in its early occurrence and has already been applied to many roadworks in advanced foreign country for a long time. But in the conventional crack sealing method, traffic accidents occur frequently during the repair because it's commonly performed on the heavy traffic road or highway. It also has some difficulties in securing the safety of workers from the risk of burns caused by heated sealant. In an effort to solve these problems, automated pavement crack sealing machines such as ARMM, OCCSM, TTLS have been developed in advanced foreign country since early 1990s. Also APCS in 2004 and ACSTM in 2013 were already developed domestically. However, since these automated crack sealers developed from a number of research institutions have different test-bed conditions and productivity measurement models, it's difficult to compare and evaluate them objectively. In this study, the image processing time of the respective machines and the movement time of each motion on the work process were estimated by using fully autonomous mapping and semi-automatic mapping in order to measure the productivity in the same environmental conditions. In addition, the productivity measurement test-bed reflected domestic road characteristics was designed to estimate and compare the productivity of the automated crack sealing machines.

• Asia Marketing Journal
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• v.15 no.2
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• pp.75-97
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• 2013

While good return policies are suggested as one of the critical services for e-commerce, ambivalence between the burden of the cost and shoppers' satisfaction may prevent e-tailers from increasing their level of leniency. Based on the S-O-R model, this study has attempted to develop a grounded theory to explain how lenient return policies shape online shoppers' perceptions and responses, with a focus on cultural influences in the relationship. In order to check the cultural effects of the lenient return policy, thirty two female and eleven male undergraduate students in South Korean shoppers, who are accustomed to strict return policies, participated in the semi-structured interview. A series of open-ended questions were designed to explore consumers' reactions toward four different levels of the lenient return policy: from the strict type in South Korea to the lenient type in the U.S. Using qualitative research methods, this research has defined three types of dimensions of lenient return policy: return possible period, complexity of progress, and other restrictions. While previous researchers did not pay much attention, the last dimension, other restrictions, is shown to be the most significant in influencing online shoppers' perceptions, especially in South Korea. Also, the impacts on online shoppers' perceptions from the three types of sub-dimensions of return policy were somewhat different. Whereas a longer return possible period was considered more favorable, a medium level of complexity and restrictions were considered more desirable. In summary, this result showed that shoppers in Eastern cultures, i.e. South Korean online shoppers, seem favorable to a medium level of lenient return policies, while allowing for taking precautions against possible fraudulent behaviors and setting other restrictions. Therefore, most of retailers in South Korea recommended that e-tailers who adopt the most lenient return policies raise the bar to guard ethical shoppers from fraudulent users. Next, lenient return policies can enhance ease of use, usefulness, affect, and trust while relieving perceived risk, which is connected to intention to purchase, satisfaction, and loyalty. Interestingly, lenient return policies are more likely to change the behavioral responses of online shoppers, such as return and purchase, rather than change their attitudes or beliefs such as image, satisfaction, and loyalty. This tendency can be seen more clearly in the direct influences of return policy on responses. The reaction to lenient return policy is mostly the intention to return or to purchase. This suggests that return policy serves the e-tailers as a powerful tool in increasing online shoppers' purchase intention at the moment of purchase. Therefore, e-tailers who plan to expand their market to eastern countries, including South Korea, have to build a shield of restrictions around their lenient return policy, rather than immediately applying their original liberalized return policy. Also, e-tailers in South Korea need to review their strict and undifferentiated return policies to deal with the unsatisfied reactions of online shoppers toward their normal return policies. Although the present study was confined to the return policies currently being practiced by popular e-tailers, it would be worthwhile to develop effective return policies separately for each country, especially South Korea, keeping the culture of the relevant country in mind.