• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.382-392
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• 2023

Recent reports have indicated a rapid increase in the frequency of sediment disasters due to climate change and other changes in the geological environment. Given this alarming situation and the recent increase in the frequency of land creep in Korea, systematic and efficient recovery and management of land creep areas is essential. The purpose of this study is to identify disaster vulnerability by conducting a physical exploration of land creep in San 4-1, Jayeon-ri, Gaegun-myeon, Yangpyeong-gun, Gyeonggi-do, and examine stability by identifying the overall geological structure of the affected ground. In addition, drilling surveys are conducted to verify the reliability of the measured data. The results of the study reveal that low specific resistance abnormalities are distributed in the upper part of the soil layer and weathering zone and that this section is a 50-120 m exploration line. It is also confirmed to be a low-hardness ground area where tensile cracks are observed. Therefore, there is a need for research focused on developing measures to reduce economic and social damage within the domestic context by continuously monitoring indicators of land creep and identifying land creep risks.

• Journal of Navigation and Port Research
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• v.47 no.4
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• pp.231-238
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• 2023

The position of a light buoy is always flexible due to the influence of external forces such as tides and wind. The position can be checked through AIS (Automatic Identification System) or RTU (Remote Terminal Unit) for AtoN. As a result of analyzing the position data for the last five years (2017-2021) of a light buoy, the average position error was 15.4%. It is necessary to detect position error data and obtain refined position data to prevent navigation safety accidents and management. This study aimed to detect position error data and obtain refined position data by DBSCAN Clustering position data obtained through AIS or RTU for AtoN. For this purpose, 21 position data of Gunsan Port No. 1 light buoy where RTU was installed among western waters with the most position errors were DBSCAN clustered using Python library. The minPts required for DBSCAN Clustering applied the value commonly used for two-dimensional data. Epsilon was calculated and its value was applied using the k-NN (nearest neighbor) algorithm. As a result of DBSCAN Clustering, position error data that did not satisfy minPts and epsilon were detected and refined position data were acquired. This study can be used as asic data for obtaining reliable position data of a light buoy installed with AIS or RTU for AtoN. It is expected to be of great help in preventing navigation safety accidents.

• Journal of Service Research and Studies
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• v.12 no.3
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• pp.45-59
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• 2022

This study attempted to investigate how the transformational leadership perceived by flowers of telemarketing organizations. In particular, this study explored the moderating effect of followership in the relationship between transformational leadership and organizational performance. To verify the research model, 321 surveys collected from 10 domestic call centers were analyzed. Reliability, correlation, factor analysis, and hierarchical regression analysis were performed, and as a result of the analysis, it was found that the transformational leadership in the telemarketing organizations had a positive effect on organizational performance. In addition, it was confirmed that goal consistency, proactive participation, critical thinking, and team spirit, which are the four sub-variables of followership, all have a positive (+) effect on organizational performance, and both goal consistency and proactive participation moderate the relationship between transformational leadership and organizational performance. Considering the special working environment of telemarketing organizations, the results of this study suggest the need for a corporate educational role to increase transformational leadership and followership and the need to build environments by setting up an atmosphere for members to exercise follow-up, and opening up communication structures for members to follow.

• Journal of the Korean Geotechnical Society
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• v.25 no.5
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• pp.53-64
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• 2009

Many slope failures are induced by rainfall infiltration. A lot of recent researches are therefore focused on rainfall-induced slope instability and the rainfall infiltration is recognized as the important triggering factor. The rainfall infiltrates into the soil slope and makes the matric suction lost in the slope and even the positive pore water pressure develops near the surface of the slope. They decrease the resisting shear strength. In Korea, a few public institutions suggested conservative slope design guidelines that assume a fully saturated soil condition. However, this assumption is irrelevant and sometimes soil properties are misused in the slope design method to fulfill the requirement. In this study, a more relevant slope stability evaluation method is suggested to take into account the real rainfall infiltration phenomenon. Unsaturated soil properties such as shear strength, soil-water characteristic curve and permeability for Korean weathered soils were obtained by laboratory tests and also estimated by artificial neural network models. For real-time assessment of slope instability, failure warning criteria of slope based on deterministic and probabilistic analyses were introduced to complement uncertainties of field measurement data. The slope stability evaluation technique can be combined with field measurement data of important factors, such as matric suction and water content, to develop an early warning system for probably unstable slopes due to the rainfall.

• Journal of Industrial Convergence
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• v.21 no.3
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• pp.139-148
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• 2023

This study was conducted through Google online survey from November 24 to November 26, 2021 targeting 276 students from the department of dental hygiene at a university in Gangwon-do. The purpose of this study was to investigate the infection awareness of uniforms, recognition of washing rules, and the intention to prevent infectious diseases through individualism and collectivist self-esteem. Statistical methods were analyzed using SPSS Statistics 24.0 and AMOS 21.0 as follows. For analysis, frequency analysis, exploratory factor analysis, confirmatory factor analysis, reliability analysis, structural equation, and ANOVA analysis were performed. As a result, it was confirmed that the models of uniform infection awareness, uniform washing rule recognition(p<.001), self-esteem, individualism, and collectivist intention to prevent infectious diseases were suitable(p<.001). Collectivism was found to affect the perception of uniform infection, the recognition of uniform washing rules, and the intention to prevent infectious diseases, confirming that self-esteem and collectivism had an effect on the change of perception for infection prevention. In the future, it will be possible to use the uniform washing method considering collectivism in infection control education of the dental hygiene.

• The Journal of Engineering Geology
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• v.32 no.1
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• pp.173-191
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• 2022

In this study, the shear wave velocity of the ground was measured using Flat TDR, and the precision analysis of the measured value and the verification of field applicability were performed. The shear wave velocity measurement value was derived in the field using the piezo-stack combined in the Flat TDR. analyzed. As a result of the experiment, the average value of the change in shear wave speed at the time of grout material injection was 10.15 m/s at the beginning of age, and the average value of the change in shear wave speed after the 7th to 14th days was 65.99 m/s, showing a tendency to increase with age. Also, it was found that dry density and shear wave speed increased as the water content increased on the dry side, and that the dry density and shear wave rate decreased as the water content increased on the wet side as the water content increased. The shear modulus value derived from the field test was confirmed to be a minimum of 17.36 MPa and a maximum of 28.13 MPa, confirming a measurement value similar to the reference value. Through this, it can be seen that the measured value of the shear modulus using Flat TDR is reliable data, and it can be determined that the compaction management of the site can be effectively managed in the future.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.325-331
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• 2022

As IoT devices are used in various ways in an edge network environment, multiple studies are being conducted that utilizes the information collected from IoT devices in various applications. However, it is not easy to apply accurate IoT data immediately as IoT data collected according to network environment (interference, interference, etc.) are frequently missed or error occurs. In order to minimize mistakes in IoT data collected in an edge network environment, this paper proposes a management technique that ensures the reliability of IoT data by randomly generating signature values of IoT data and allocating only Security Information (SI) values to IoT data in bit form. The proposed technique binds IoT data into a blockchain by applying multiple hash chains to asymmetrically link and process data collected from IoT devices. In this case, the blockchainized IoT data uses a probability function to which a weight is applied according to a correlation index based on deep learning. In addition, the proposed technique can expand and operate grouped IoT data into an n-layer structure to lower the integrity and processing cost of IoT data.

• Korea Trade Review
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• v.43 no.6
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• pp.161-192
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• 2018

The hotel industry in China has shown great growth both in terms of quantity and quality, but management of the most important element of the success of the hotel company is still not enough. The purpose of this study is to investigate the effects of emotional intelligence including self emotional appraisal, others' emotional appraisal, regulation of emotion, use of emotion on Chinese hotel employees' resilience to improve job satisfaction, organizational commitment, and to reduce turnover intention. Also, the relationship between job satisfaction, organizational commitment, and turnover intention was investigated. In order to analyze this, we surveyed 322 employees of Shanghai 4, 5star hotel in China. Empirical analysis showed that self emotional appraisal, regulation of emotion, and use of emotion of Chinese hotel employees had a positive effect on resilience, but others' emotional appraisal did not affect resilience. In addition, the resilience showed a positive effect on job satisfaction and organizational commitment, but not on turnover intention. Also, job satisfaction has a significant negative effect on organizational commitment and turnover intention, and organizational commitment has a significant negative impact on turnover intention. This study aims to provide a better understanding of emotional intelligence and resilience, and to provide effective management of human resources management.

• Korea Science and Art Forum
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• v.19
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• pp.417-424
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• 2015

The healthcare service industry has become one of the business industries in South Korea where service design is most actively being researched on and applied. In accordance with the recent upsurge of the interest in health, healthcare service is expanding its area including disease prevention, patient management, and rehabilitation treatment as well as cure and nursing care. The health manpower is the supplier, and their professional knowledge and ability and the patients' trust in medical technology are the most important factors for their customers. In addition, service design has come into the spotlight given that the medical institute system, health manpower attitude, and information delivery system and touch point are considered important factors contributing to customer satisfaction. It is very hard to satisfy customers only through professionalism, the environment, and product improvement because healthcare service deals with much more sensitive and emotional customers compared to other service industries. This means that a change in the service mind-set and the attitude of the health manpower as emotional labourers have practical effects. Therefore, the fundamental solution is to establish a system that provides related education with manpower and that settles various problems by itself. This paper introduces several solutions, such as education for health manpower and a service design system applied to a national-university-affiliated hospital in South Korea, and takes a close look at its effects.

• 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.