• Journal of Korean Public Health Nursing
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• v.35 no.3
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• pp.430-447
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• 2021

Purpose: The purpose of this study was to analyze the role and tasks of nurses who were working for the elderly in the visiting health services at the public health centers. Methods: Literature reviews, two rounds of meetings with 5 experts and a two-round Delphi technique with 15 experts were performed in this study. Results: The nurses' role and job analysis revealed 5 roles, 16 duties and, 71 tasks. The nurses' roles, including discovery and registration of households/groups in visiting health service in the community, case manager, administrative management, program planning, operation and evaluation, and development of job competency. Sixteen duties included client registration and management, need assessment and plan establishment, education, consultation and support, seasonal health care, prevention and monitoring of infectious diseases, basic nursing care, chronic disease management, linkage and utilization of resources, team cooperation and coordination, home environment management, monitoring and support for intervention outcomes, evaluation, administrative management, program planning, operation and evaluation, development of professional competency and, adoption of fourth industrial revolution technology. Conclusions: Based on the results, the government should provide sufficient nursing personnel to provide universal preventive health services for the elderly and a job training program to perform these roles well.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.105-116
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• 2023

Purpose: The purpose of this study is to present the preemptive prevention and improvement measures for aviation safety management by examining the current status of the aviation industry and the operation system of the aviation safety management system and identifying the shortcomings of the currently operating aviation safety management system. Method: A plan to improve aviation safety management was proposed through an analysis of recent incidents and accidents, current status of domestic laws, and analysis of overseas operating institutions and safety management systems. Result: Through the recent aircraft safety-related incidents, deficiencies of currently operating aviation safety management, and response cases of advanced countries in overseas aviation, improvement points in terms of management systems and laws and preventive aviation safety management plans were derived. Conclusion: The method for improving aviation safety management was presented based on the technique using data, and it should be materialized through additional related research.

• Journal of Korean Society on Water Environment
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• v.39 no.1
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• pp.1-8
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• 2023

Monitoring and prediction of water quality are essential for effective river pollution prevention and water quality management. In this study, a multi-classification model was developed to predict chlorophyll-a (Chl-a) level in rivers. A model was developed using CatBoost, a novel ensemble machine learning algorithm. The model was developed using hourly field monitoring data collected from January 1 to December 31, 2015. For model development, chl-a was classified into class 1 (Chl-a≤10 ㎍/L), class 2 (10<Chl-a≤50 ㎍/L), and class 3 (Chl-a>50 ㎍/L), where the number of data used for the model training were 27,192, 11,031, and 511, respectively. The macro averages of precision, recall, and F1-score for the three classes were 0.58, 0.58, and 0.58, respectively, while the weighted averages were 0.89, 0.90, and 0.89, for precision, recall, and F1-score, respectively. The model showed relatively poor performance for class 3 where the number of observations was much smaller compared to the other two classes. The imbalance of data distribution among the three classes was resolved by using the synthetic minority over-sampling technique (SMOTE) algorithm, where the number of data used for model training was evenly distributed as 26,868 for each class. The model performance was improved with the macro averages of precision, rcall, and F1-score of the three classes as 0.58, 0.70, and 0.59, respectively, while the weighted averages were 0.88, 0.84, and 0.86 after SMOTE application.

• Archives of Craniofacial Surgery
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• v.24 no.1
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• pp.10-17
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• 2023

Background: Lipomas are common benign tumors of mesenchymal origin that are composed of mature adipocytes. Giant lipomas have a diameter ≥ 10 cm in one or more dimensions or weigh at least 1,000 g. The surgical excision of a giant lipoma requires extensive dissection, increasing the risk of a seroma, which can cause surgical site complications such as wound infection and necrosis. Sclerotherapy with Abnobaviscum (Viscum album extract) is a relatively new technique used to reduce malignant pleural effusion. In this study, we evaluated the effectiveness of prophylactic sclerotherapy using Abnobaviscum to decrease seroma after giant lipoma excision. Methods: We conducted a retrospective medical record review of patients who underwent surgical excision for giant lipoma of the neck from January 2019 to December 2022. Sclerotherapy was performed on the first postoperative day in patients who consented to the procedure, and Abnobaviscum was instilled through the existing Hemovac drain. We compared the clinical course between those who underwent postoperative sclerotherapy and those who did not. Results: Among the 30 patients who underwent giant lipoma excision, we applied sclerotherapy with Abnobaviscum to 15 patients. The average time from surgery to Hemovac removal was statistically shorter in patients who underwent sclerotherapy (p= 0.004). Furthermore, seroma formation was significantly reduced in patients receiving sclerotherapy (p= 0.003). Conclusion: In patients undergoing giant lipoma excision, sclerotherapy using Abnobaviscum helps reduce postoperative seroma formation during the initial postoperative period. It can be an excellent method to reduce complications related to seroma and attenuate patients' postoperative burden.

• Smart Media Journal
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• v.11 no.2
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• pp.31-38
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• 2022

Promptly predicting changes in the salinity in rivers is an important task to predict the damage to agriculture and ecosystems caused by salinity infiltration and to establish disaster prevention measures. Because machine learning(ML) methods show much less computation cost than physics-based hydraulic models, they can predict the river salinity in a relatively short time. Due to shorter training time, ML methods have been studied as a complementary technique to physics-based hydraulic model. Many studies on salinity prediction based on machine learning have been studied actively around the world, but there are few studies in South Korea. With a massive number of datasets available publicly, we evaluated the performance of various kinds of machine learning techniques that predict the salinity of the Nakdong River Estuary Basin. As a result, LightGBM algorithm shows average 0.37 in RMSE as prediction performance and 2-20 times faster learning speed than other algorithms. This indicates that machine learning techniques can be applied to predict the salinity of rivers in Korea.

• Journal of Korean Society of Rural Planning
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• v.28 no.1
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• pp.99-108
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• 2022

This study measured the importance and satisfaction of the values related to 'New Ruralism' using the IPA(Importance-Performance Analysis) technique by the rural leaders' group. In the result, the satisfaction value was evaluated lower in the importance of 'landscape and ecological resource conservation', 'settlement environment', and 'population' related items. On the other hand, the items of 'tourism resource management', 'landscape damage', and 'landscape and ecological resource conservation' showed high satisfaction. Therefore, the leaders' group of Gochang-gun perceived the importance of local tourism image, landscape damage prevention, settlement environment, and rural landscape in 'New Ruralism' management. However, the leaders' group valued lower in the items of population, ecological value and natural and historical tourist sites. This seems to be a characteristic of the leaders' group mainly engaged in agriculture. Through factor analysis, the six items excluded from the analysis were considered important factors in 'New Ruralism' in Gochang-gun through a review of previous studies. Still, the leaders' group of Gochang-gun did not recognize them as important items in the rural resource. However, these items will be able to contribute to the development of 'New Ruralism' in Gochang-gun, and it is necessary to improve the awareness of the leader group. Even if local governments or experts present an ideal goal for rural development, it is difficult to achieve the goals if there is a difference from the perception of residents. Therefore, it is important to understand the perception of 'New Ruralism' of the leaders' group who plays an important role in regional development projects.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.1C
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• pp.17-25
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• 2010

Electrophoresis may offer a new technique to repair in service leaking geomembrane liner of municipal solid waste (MSW) impoundment. The method involves introducing a suspended clay particles, which are charged negatively, into the leakage in geomembrane liners by electrokinetic phenomena and formation of clay cake around leakage for prevention of leachate outflows. Therefore, the 3-dimensional leakage simulation experiments are conducted to evaluate the field applicability of sealing leaks of waste impoundment. In addition, the adequateness of optimum influence factors deduced from 1-dimensional experiments is evaluated. After the test, the total size (width, length) of clay cake formation around leak is increased with enlargement of leakage diameter and distance decrease detween anode and cathode.

• Convergence Security Journal
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• v.22 no.2
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• pp.9-19
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• 2022

As the expansion of digital transformation, we are more exposed to the threat of cyber attacks, and many institution or company is operating a signature-based intrusion prevention system at the forefront of the network to prevent the inflow of attacks. However, in order to provide appropriate services to the related ICT system, strict blocking rules cannot be applied, causing many false events and lowering operational efficiency. Therefore, many research projects using artificial intelligence are being performed to improve attack detection accuracy. Most researches were performed using a specific research data set which cannot be seen in real network, so it was impossible to use in the actual system. In this paper, we propose a technique for classifying major attack keywords in the security event log collected from the actual system, assigning a weight to each key keyword, and then performing a similarity check using TF-IDF to determine whether an actual attack has occurred.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.208-208
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• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.

• Korean Journal of Hazardous Materials
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• v.2 no.1
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• pp.31-37
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• 2014

Since the unprecedented hydrogen fluoride leak accident in 2012, there has been growing demand for customized technical information for rapid response and chemical accident management agencies including the Ministry of Environment, the National Emergency Management Agency, and the National Police Agency need more information on chemicals and accident management. In this regard, this study aims to provide reliable technical data and guidelines to initial response agencies, similar to accident management technical reports of the US and Canada. In this study, we conducted a questionnaire survey and interviews on initial response agencies like fire stations, police stations, and local governments to identify new information items for appropriate initial response and improvements of current guidelines. We also collected and reviewed the Canada's TIPS, US EPA's hydrogen fluoride documents, domestic and foreign literature on applicability tests of control chemicals, and interview data, and then produced items to be listed in the technical guidelines. In addition, to establish database of on-site technical information, we carried out applicability tests for accident control data including ① emergency shut down devide, safety guard, shut down valve, ground connection, dyke, transfer pipe, scrubber, and sensor; ② literature and field survey on distribution type and transportation/storage characteristics (container identification, valve, ground connection, etc.); ③ classification and identification of storage/transportation facilities and emergency management methodslike leak prevention, chemicals control, and cutoff or bypass of rain drainage; ④ domestic/foreign analysis methods and environmental standards including portable detection methods, test standards, and exposure limits; and ⑤ comparison/evaluation of neutralization efficiency of control chemicals on toxic substances.