• Industry Promotion Research
• /
• v.4 no.1
• /
• pp.57-66
• /
• 2019

The extant research literature is scant in telling us how organizations actually implement lifelong learning practices and policies. Hence, the purpose of this paper is to describe how lifelong learning is grounded in practice. We do this by introducing a new conceptual framework that was developed on the basis of interviews with a number of leading edge corporations from Canada, the USA, India and Korea. At the heart of our model, and any effective lifelong learning system, is a performance management system. The performance management system allows for an ongoing interaction between managers and employees whereby challenging performance and learning goals are set, and concrete plans are made to achieve them. Those plans involve three types of learning activities. First, employees may be encouraged to engage in formal learning. This could be provided in-house, or the employee may take a leave of absence and return to school. Second, managers may deploy their subordinates to different departments or teams, so that they can take part in new work-based learning opportunities. Finally, employees may be encouraged to learn on their own time. By this we mean learning after organizational hours through firm-sponsored 5 programs, such as e-learning courses. Fueled by the performance management system, we posit that these three learning outlets lead to effective lifelong learning in organizations.

• Journal of Internet of Things and Convergence
• /
• v.8 no.6
• /
• pp.99-113
• /
• 2022

This study is descriptive research to investigate the effects of COVID-19 stress, interpersonal (caregiver-patient) stress, and emotional labor on burnout in emergency room (ER) nurses during the COVID-19 pandemic. The data collection of this study was conducted from December 9 to 23, 2021 with ER nurses working at five tertiary general hospitals and general hospitals of Medical Center H. The data was collected with a questionnaire using tools measuring the subjects' general & job-related characteristics, COVID-19 stress, interpersonal(caregiver-patient) stress, emotional labor and burnout. The collected data was analyzed using the SPSS/WIN 25.0 statistical program for frequency analysis, descriptive statistical analysis, independent sample t-test, one-way ANOVA, Scheffé test, correlation analysis, and multiple regression analysis. The average score of COVID-19 stress in ER nurses was 3.64, interpersonal(caregiver-patient) stress 4.35, emotional labor 3.38, and burnout 3.44. As a result of analyzing differences according to general & job-related characteristics, burnout showed a significant difference according to gender, marital status, total clinical experience, and working organization. And burnout showed a significant positive correlation with COVID-19 stress, interpersonal stress and emotional labor. As a result of multiple linear regression analysis, regional emergency medical centers and local emergency medical centers among the work organization types, interpersonal stress, COVID-19 stress, and gender and the explanatory power was 28.6%. Through these results, we intend to provide basic data for the development of an intervention program to prevent burnout of emergency room nurses and improve nursing performance at the time of a new infectious disease pandemic.

• The Journal of the Korea Contents Association
• /
• v.21 no.6
• /
• pp.639-652
• /
• 2021

In accordance with the rapidly changing social environment, it is becoming more important to cultivate creative and convergent practical talents with flexible thinking skills and problem-solving skills. Therefore, it is necessary for universities to provide educational experiences that enable students to cooperate and converge multidisciplinaryly to carry out on-the-job projects based on what they have learned at school. Therefore, this study designed, developed, and operated with the aim of cultivating creative talents with integrated problem-solving ability through a multidisciplinary capstone design curriculum based on industry-academia cooperation. To this end, the curriculum was developed together by recruiting participating companies and forming a convergence professor team, and it was operated for 15 weeks for students majoring in cosmetics engineering at D University. After the education was over, learning satisfaction and perceived academic achievement were surveyed, and as a result of the analysis, it was found to be above average with 3.77 points and 3.86 points, respectively. And as a result of the in-depth interview on the participation experience, five themes related to the positive experience and three themes related to the negative experience were derived. This study will be able to provide basic data when operating a multidisciplinary convergence capstone design curriculum based on industry-academia cooperation in the future.

• Journal of the Korean Applied Science and Technology
• /
• v.37 no.6
• /
• pp.1678-1686
• /
• 2020

This study attempted to derive the possibility of using wood pellet using rice husk, which is an agricultural byproduct, and tried to improve the lower calorific value of rice hulls thorough expansion technology and combustion additives. In the physical and chemical analysis of rice husk, the result was obtained that the chlorine content was 0.09%, which did not meet the wood pellet quality standard of Korea. When making rice hulls into expanded rice husk through the expansion technology, the chlorine content decreased, resulting in a product of 0.02%, which is equivalent to the wood pellet standard of Korea, and the calorific value was also increased to 4,280 kcal/kg compared to the existing 3,780 kcal/kg. To obtain a product of 5,000 kcal/kg or more, borax, hydrogen peroxide, and sodium hydroxide was used as combustion improver. However the improvement in calorific value was insufficient. After conversion to coffee oil path using coffee grounds, which is a waste resource biomass, it is mixed into an expanded rice husk, and when the product is analyzed, the coffee oil 15 wt% mixed product shows an excess of 4,949 kcal/kg. When using rice husk, an agricultural byproduct, as wood pellets, it is considered desirable to use waste resources to improve the calorific value, and according to the results of this study, when mixing coffee oil, rice husk can be sufficiently used as wooden pellets.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.26 no.3
• /
• pp.111-119
• /
• 2022

The increasing sectional stiffness and inducing prestress method of continuous steel box girder using modular CFT members use the restoring force of the CFT module generated from removing the prestressing bars in the CFT module after integrating the prestressed CFT module with the lower steel plate of the steel box girders as a prestressing force. The integrated CFT module in the steel box girder can improve the sectional stiffness of the continuous steel box girder section. To examine the applicability of the introduction of prestressing to the integrated steel box girder using the CFT module, in this study, inducing prestressing tests were conducted using CFT modules for steel plate specimens simulating the lower steel plate of the continuous steel box girder, and FE analyses were conducted for inducing prestressing tests. In addition, to confirm the effect of inducing prestress to the actual steel box girder and increasing sectional stiffness by the CFT modules, FE analyses for the actually applicable continuous steel box section were carried out depending on prestressing force and sectional conditions of the CFT modules, FE analysis results were compared.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.1
• /
• pp.16-24
• /
• 2023

Accidents are greatly reduced through projects to improve frequent traffic accidents. These results show that safety facilities play a big role. Traffic accidents are caused by various causes and various environmental factors, and it is difficult to achieve improvement effects by installing one safety facility or facilities without standards. Therefore, this study analyzed the improvement effect of each accident type by combining the two safety facilities, and suggested a method of predicting the combination of safety facilities suitable for a specific point, including environmental factors such as road type, road type, and traffic. The prediction was carried out by selecting an XGBoost technique that creates one strong prediction model by combining prediction models that can be simple classification. Through this, safety facilities that have had positive effects through improvement projects and safety facilities to be installed at points in need of improvement were derived, and safety facilities effect analysis and prediction methods for future installation points were presented.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.11 no.4
• /
• pp.373-385
• /
• 2009

A new indexing methodology so called KTH-index was developed to quantitatively evaluate a potential level for tunnel collapse hazard, which has been successfully applied to tunnel construction sites to date. In this study, an attempt is made to apply this methodology for validating an outcome of tunnel design by checking the variation of KTH-index along longitudinal tunnel section. In this KTH-index simulation, it is the most important to determine the input factors reasonably. The design factor and construction condition are set up based on the designed outcome. Uncertain ground conditions are arranged based on borehole test and electro-resistivity survey data. Two scenarios for ground conditions, best and worst scenarios, are set up. From this simulation, it is shown that this methodology could be successfully applied for providing quantitative validity of a tunnel design and also potential hazard factors which should be carefully monitored in construction stage. The hazard factors would affect sensitively the hazard level of the tunnel site under consideration.

• Journal of the Korean Society for information Management
• /
• v.39 no.4
• /
• pp.99-125
• /
• 2022

In order to understand a record, not only the contents of the record but also the production background and work context of the record must be grasped. It also requires a function that makes it easy to find related records scattered across various departments and agencies. Accordingly, the 'linkage' of information in archival information services is becoming more important. NAK also emphasizes 'linkage' as a search service function of the archives management system, but some problems were identified at the National Archives Portal Service (NAPS) such as a lack of linkage with authority data, disruption of internal service, and absence of linkage with other related organizations. To solve the limitations of the NAPS, we selected and analyzed advanced record management institutions that have built an ideal linkage service; checked the overall linkage structure of these institutions; and identified characteristics that could not be seen by other institutions. Also, elements that can be adopted from the NAPS were derived. Next, the current status of the NAPS linkage structure was analyzed to identify the parts that were not linked and the items that need to be improved in the linkage method, and specific advancement plans were suggested to solve these problems. The purpose of this study is to increase users' satisfaction with search and to advance the accessibility and utilization of records and internal services through improved linkage services of NAPS.

• Journal of the Korean Geotechnical Society
• /
• v.40 no.4
• /
• pp.69-79
• /
• 2024

Field geotechnical data are obtained from various field and laboratory tests and are documented in geotechnical investigation reports. For efficient design and construction, digitizing these geotechnical parameters is essential. However, current practices involve manual data entry, which is time-consuming, labor-intensive, and prone to errors. Thus, this study proposes an automatic data extraction method from geotechnical investigation reports using image-based deep learning models and text-mining techniques. A deep-learning-based page classification model and a text-searching algorithm were employed to classify geotechnical investigation report pages with 100% accuracy. Computer vision algorithms were utilized to identify valid data regions within report pages, and text analysis was used to match and extract the corresponding geotechnical data. The proposed model was validated using a dataset of 205 geotechnical investigation reports, achieving an average data extraction accuracy of 93.0%. Finally, a user-interface-based program was developed to enhance the practical application of the extraction model. It allowed users to upload PDF files of geotechnical investigation reports, automatically analyze these reports, and extract and edit data. This approach is expected to improve the efficiency and accuracy of digitizing geotechnical investigation reports and building geotechnical databases.

• Korean Journal of Remote Sensing
• /
• v.39 no.3
• /
• pp.297-309
• /
• 2023

The degradation of coastal ecosystems and fishery environments is accelerating due to the recent phenomenon of invertebrate grazers. To effectively monitor and implement preventive measures for this phenomenon, the adoption of remote sensing-based monitoring technology for extensive maritime areas is imperative. In this study, we compared and analyzed the robustness of deep learning-based object detection modelsfor detecting and monitoring invertebrate grazersfrom underwater videos. We constructed an image dataset targeting seven representative species of invertebrate grazers in the coastal waters of South Korea and trained deep learning-based object detection models, You Only Look Once (YOLO)v7 and YOLOv8, using this dataset. We evaluated the detection performance and speed of a total of six YOLO models (YOLOv7, YOLOv7x, YOLOv8s, YOLOv8m, YOLOv8l, YOLOv8x) and conducted robustness evaluations considering various image distortions that may occur during underwater filming. The evaluation results showed that the YOLOv8 models demonstrated higher detection speed (approximately 71 to 141 FPS [frame per second]) compared to the number of parameters. In terms of detection performance, the YOLOv8 models (mean average precision [mAP] 0.848 to 0.882) exhibited better performance than the YOLOv7 models (mAP 0.847 to 0.850). Regarding model robustness, it was observed that the YOLOv7 models were more robust to shape distortions, while the YOLOv8 models were relatively more robust to color distortions. Therefore, considering that shape distortions occur less frequently in underwater video recordings while color distortions are more frequent in coastal areas, it can be concluded that utilizing YOLOv8 models is a valid choice for invertebrate grazer detection and monitoring in coastal waters.