• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.509-519
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• 2021

This study was conducted in order to acquire useful information regarding the resilience of childcare educators amidst an emergency pandemic to adjust their job stress, job burnout, and turnover intention. A questionnaire was conducted for analysis from August 19th to the 30th in 2020 and 201 responses ended up being used for analysis. The analysis results revealed that job stress, job burnout, and turnover intention of childcare educators were low while resilience was high and it was acknowledged that all of them mostly differed according to the types of personal traits. Although the job stress of childcare educators had a positive (+) influence on job burnout at a statistically significant level, it turns out that job stress does not have an influential relationship with turnover intention. Furthermore, the emotion regulation ability, impulse control, and active conductivity among resilience displayed a moderating effect in the relationship between job stress and job burnout. Amidst an emergency pandemic known as the COVID-19 virus, it has been confirmed that job stress and turnover intention of childcare educators deteriorated, and the prominent reason for this was identified as the difficulty in carrying out smooth job performances. Accordingly, measures to strengthen resilience such as countermeasures against quarantine-based job stress and turnover intent, daily management over job burnout and resilience, as well as counseling or programs based on self-focused attention have been suggested.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.116-131
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• 2022

With the recent progress of the 4th industrial revolution, the logistics industry is also making efforts to introduce smart logistics, and various attempts are being made to spread logistics informatization, which is the core of smart logistics. Among these, blockchain technology is considered as a technology that will contribute to the spread of logistics informatization and is being applied to various fields. Accordingly, in this study, to discuss the applicability of blockchain technology to the logistics industry, the characteristics of blockchain technology were defined, related cases were reviewed, and a survey was conducted on the possibility of application in the industry. Blockchain technology can be defined as having the characteristics of economic feasibility, speed, transparency in terms of work efficiency, and scalability, decentralization (decentralization), reliability (security) in terms of added value creation. It was confirmed that many are being introduced in the fields of distribution, finance, personal information, and public services. As a result of the survey on the logistics industry, it was confirmed that the level of informatization of the logistics industry had entered the stage of generating profits by using information, but the industry was passive in sharing and utilizing information due to concerns about information leakage. Nevertheless, the awareness and expectation of the need for informatization is high, and it is expected that the informatization of the logistics industry and realizing smart logistics based on it will advance one step further with the introduction of blockchain technology in the future.

• Korean journal of applied entomology
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• v.61 no.1
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• pp.197-210
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• 2022

Entomopathogenic fungi can be used to control a variety of sucking and chewing insects, with little effect on beneficial insects and natural enemies. Approximately 170 entomopathogenic fungal insecticides have been registered and used worldwide, with the recent focus being on the mode of action and mechanism of insect-fungal interactions. During the initial period of research and development, the industrialization of entomopathogenic fungi focused on the selection of strains with high virulence. However, improvement in productivity, including securing resistance to environmental stressors, is a major issue that needs to be solved. Although conidia are the primary application propagules, efforts are being made to overcome the limitations of blastospores to improve the economic feasibility of the production procedure. Fungal transformation is also being conducted to enhance insecticidal activity, and molecular biology is being used to investigate functions of various genes. In the fungi-based pest management market, global companies are setting up cooperative platforms with specialized biological companies in the form of M&As or partnerships with the aim of implementing a tank-mix strategy by combining chemical pesticides and entomopathogenic fungi. In this regard, understanding insect ecology in the field helps in providing more effective fungal applications in pest management, which can be used complementary to chemicals. In the future, when fungal applications are combined with digital farming technology, above-ground applications to control leaf-dwelling pests will be more effective. Therefore, for practical industrialization, it is necessary to secure clear research data on intellectual property rights.

• Journal of Korea Port Economic Association
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• v.38 no.3
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• pp.69-86
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• 2022

This study analyses the necessity of the large-size shipyard and explores competitiveness factors of it. Furthermore, the competitiveness is evaluated and the economic feasibility of building and operation of shipyard is examined. As a result of AHP analysis of the determining factors of the competitiveness of the repairing shipyard, the importance of the factors was found in the order of arrival and departure safety, repair technology, dock and wharf facilities, repair cost, repair period (on time delivery), and repair parts supply. Moving distance, repair service quality, repair parts supply, arrival and departure safety, repair technology, dock and quay wall facilities, and repair period (on time delivery) were identified as key factors in the AHP analysis for competitiveness of the Busan Port repair shipyard to be built in the future. As a result of the analysing economic feasibility, the net present value of the Busan Port repair shipyard construction and operation investment project was KRW 435.6 billion, and the internal rate of return was 9.8%, higher than the social discount rate (4.5%), and the cost-benefit ratio (B/C) was high at 1.167. As a result of the study, the necessity and economic feasibility of the Busan Port repair shipyard are sufficiently ensured, and the competitiveness assessment was highly positive.

• Korea Journal of Hospital Management
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• v.27 no.2
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• pp.16-33
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• 2022

Purposes: Prompt evaluation of routes and contact tracing are very important for epidemiological investigations of coronavirus disease 2019 (COVID-19). To ensure better adoption of contact tracing apps, it is necessary to understand users' expectations, preferences, and concerns. This study aimed to identify main reasons why people use the apps, appropriate services, and basis for voluntary app services that can improve app participation rates and data sharing. Methodology/Approach: This study conducted an online survey from November 11 to December 6, 2020, and received a total of 1,048 survey responses. This study analyzed the questionnaire survey findings of 883 respondents in areas with many confirmed cases of COVID-19. This study used a multiple regression analysis. Findings: Respondents who had experience of using related apps showed a high intention to use contact-tracing apps. Participants wished for the contact tracking apps to be provided by the government or public health centers (74%) and preferred free apps (93.88%). The factors affecting the participants' intention to use these apps were their preventive value, performance expectancy, perceived risk, facilitative ability, and effort expectancy. The results highlighted the need to ensure voluntary participation to address participants' concerns regarding privacy protection and personal information exposure. Practical Implications: The results can be used to accurately identify user needs and appropriate services and thereby improve the development of contact tracking apps. The findings provide the basis for voluntary app that can enhance app participation rates and data sharing. The results will also serve as the basis for developing trusted apps that can facilitate epidemiological investigations.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.685-690
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• 2023

It was analyzed that the volume of deep excavation works adjacent to existing underground structures is increasing according to the population growth and density of cities. Currently, many underground structures and tracks are damaged by external factors, and the cause is analyzed based on the measurement results in the tunnel, and measurements are being made for post-processing, not for prevention. The purpose of this study is to analyze the effect on the deformation of the structure due to the excavation work adjacent to the urban railway track in use. In addition, the safety of structures is evaluated through machine learning techniques for displacement of structures before damage and destruction of underground structures and tracks due to external factors. As a result of the analysis, it was analyzed that the model suitable for predicting the structure management standard value time in the analyzed dataset was a polynomial regression machine. Since it may be limited to the data applied in this study, future research is needed to increase the diversity of structural conditions and the amount of data.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.241-265
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• 2023

A corporate insolvency prediction model serves as a vital tool for objectively monitoring the financial condition of companies. It enables timely warnings, facilitates responsive actions, and supports the formulation of effective management strategies to mitigate bankruptcy risks and enhance performance. Investors and financial institutions utilize default prediction models to minimize financial losses. As the interest in utilizing artificial intelligence (AI) technology for corporate insolvency prediction grows, extensive research has been conducted in this domain. However, there is an increasing demand for explainable AI models in corporate insolvency prediction, emphasizing interpretability and reliability. The SHAP (SHapley Additive exPlanations) technique has gained significant popularity and has demonstrated strong performance in various applications. Nonetheless, it has limitations such as computational cost, processing time, and scalability concerns based on the number of variables. This study introduces a novel approach to variable selection that reduces the number of variables by averaging SHAP values from bootstrapped data subsets instead of using the entire dataset. This technique aims to improve computational efficiency while maintaining excellent predictive performance. To obtain classification results, we aim to train random forest, XGBoost, and C5.0 models using carefully selected variables with high interpretability. The classification accuracy of the ensemble model, generated through soft voting as the goal of high-performance model design, is compared with the individual models. The study leverages data from 1,698 Korean light industrial companies and employs bootstrapping to create distinct data groups. Logistic Regression is employed to calculate SHAP values for each data group, and their averages are computed to derive the final SHAP values. The proposed model enhances interpretability and aims to achieve superior predictive performance.

• Journal of the Korean GEO-environmental Society
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• v.24 no.12
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• pp.47-52
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• 2023

In order to efficiently maintain heat pipes operated by district heating operators, the facility history and damage history data built by the operator are used to identify key independent variables that are related to the occurrence of damage. Afterwards, the correlation with the frequency of damage was analyzed, and a basic model for estimating the frequency of damage was derived. Considering the correlation with the estimation model based on the use time currently being used by domestic and foreign district heating operators, a simple regression analysis basic model was presented as the independent variable with the highest correlation between continuous variables such as the use time, pipe diameter, burial depth, and insulation level of monitoring system, and the frequency of damage. The remaining independent variables were reflected as factors that modify and supplement the basic model. As a result of the analysis, as in previous research cases, it was confirmed that the analysis model between use time and frequency of damage had the highest correlation between the two variables and could be used as a basic model. Pipe diameter, burial depth, and insulation level of monitoring system information have also been confirmed to have a correlation with the frequency of damage, so they can be used as factors to supplement the basic model.

• Information Systems Review
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• v.24 no.3
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• pp.43-68
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• 2022

With the growing demand for online food delivery (OFD) services via Online to Offline (O2O) platforms, it is required for academic researchers to identify the success factors of OFD businesses. In line with this, this research examines the impact of the core service attributes of a restaurant (hygiene, interactivity, trust,and popularity) on business success in the OFD platform context from the perspective of information asymmetry. Furthermore, the moderating effects of hygiene factor between the core service attributes and the success of restaurants are evaluated. We utilize 1,146 restaurants registered on the largest OFD platform in Korea. The results of this study demonstrate that hygiene (certification), trust (franchise), popularity (favorite) factors have positive impacts on the success of OFD businesses. Moreover, we find that franchise restaurants with high response rates to customer reviews and inquiries achieve higher sales when they have hygiene certifications than those without the certification do. The key findings bear significant contributions to prior literature by empirically substantiating the pivotal role of service quality signals in fostering restaurant success on the OFD platforms. In addition, this study provides business implications for restaurants in O2O platform.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.2
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• pp.147-156
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• 2024

The sustainable management and enhancement of marine resources are becoming increasingly important issues worldwide. This study was conducted in response to these challenges, focusing on the development and performance comparison of fish detection and classification models as part of a deep learning-based technique for assessing the effectiveness of marine resource enhancement projects initiated by the Korea Fisheries Resources Agency. The aim was to select the optimal model by training various sizes of YOLOv8-Seg models on a fish image dataset and comparing each performance metric. The dataset used for model construction consisted of 36,749 images and label files of 12 different species of fish, with data diversity enhanced through the application of augmentation techniques during training. When training and validating five different YOLOv8-Seg models under identical conditions, the medium-sized YOLOv8m-Seg model showed high learning efficiency and excellent detection and classification performance, with the shortest training time of 13 h and 12 min, an of 0.933, and an inference speed of 9.6 ms. Considering the balance between each performance metric, this was deemed the most efficient model for meeting real-time processing requirements. The use of such real-time fish detection and classification models could enable effective surveys of marine resource enhancement projects, suggesting the need for ongoing performance improvements and further research.