• Korean Journal of Clinical Laboratory Science
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• v.54 no.1
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• pp.49-60
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• 2022

This study attempted to provide the basic data for developing a system to identify the role of medical technologists and ensure an efficient response for quick and accurate diagnostic tests in the COVID-19 era. The research method involved using focus group interviews for a survey and analysis of 15 medical institutions. Eleven sample collection institutions, 10.4 medical technologists, 2.1 minutes of collection time, 5.4 hours of test time, 9,670 tests, 6.2 member test workforce size, and 7 screening center operating institutions were surveyed. The results of the focus group interview analysis revealed that there were no standardized guidelines covering working hours, area, and environment to protect sample collectors and testers in relation to the COVID-19 tests. Also, legal protection measures were insufficient in the event of accidental infections and there were no personnel regulations related to COVID-19. In addition, the professional training of sample collectors and molecular diagnostic testers was required for reliable COVID-19 testing. In conclusion, it is necessary to provide professional education through special test short-term training institutions to cope with emergency infectious diseases such as COVID-19. Legal systems should be put in place to protect the workforce and ensure stability.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.159-167
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• 2010

The purpose of this study is to get the adjusted radar rainfalls by ANN(Artificial Neural Network) method. In the case of radar rainfall, it has an advantage of spatial distribution characteristics of rainfall while point rainfall has an advantage at the point. Therefore we adjusted the radar rainfall by ANN method considering the advantages of two rainfalls of radar and point. This study constructed two ANN models of Model I and Model II for radar rainfall adjustment. We collected the three rainfall events and adjusted the radar rainfall for Anseong-cheon basin. The two events were inputted into the Modeland Model to derive the optimum parameters and the rest event was used for validation. The adjusted radar rainfalls by ANN method and the raw radar rainfall were used as the input data of ModClark model which is a semi-distributed model to simulate the runoff. As the results of the simulation, the runoff by raw radar rainfall were overestimated but the peak time and peak runoff from the adjusted rainfall by ANN were well fitted to the observed hydrograph.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.485-493
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• 2008

The Artificial Neural Network (ANN) model was suggested for predicting probability of precipitation (PoP) using RDAPS NWP model, observation at AWS and upper-air sounding station. The prediction work was implemented for flood season and the data period is the July, August of 2001 and June of 2002. Neural network input variables (predictors) were composed of geopotential height 500/750/1000 hPa, atmospheric thickness 500-1000 hPa, X & Y-component of wind at 500 hPa, X & Y-component of wind at 750 hPa, wind speed at surface, temperature at 500/750 hPa/surface, mean sea level pressure, 3-hr accumulated precipitation, occurrence of observed precipitation, precipitation accumulated in 6 & 12 hrs previous to RDAPS run, precipitation occurrence in 6 & 12 hrs previous to RDAPS run, relative humidity measured 0 & 12 hrs before RDAPS run, precipitable water measured 0 & 12 hrs before RDAPS run, precipitable water difference in 12 hrs previous to RDAPS run. The suggested ANN has a 3-layer perceptron (multi layer perceptron; MLP) and back-propagation learning algorithm. The result shows that there were 6.8% increase in Hit rate (H), especially 99.2% and 148.1% increase in Threat Score (TS) and Probability of Detection (POD). It illustrates that the suggested ANN model can be a useful tool for predicting rainfall event prediction. The Kuipers Skill Score (KSS) was increased 92.8%, which the ANN model improves the rainfall occurrence prediction over RDAPS.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4B
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• pp.383-392
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• 2008

It is not always easy to estimate the parameters in hydrologic models due to insufficient hydrologic data when hydraulic structures are designed or water resources plan are established. Therefore, uncertainty analysis are inevitably needed to examine reliability for the estimated results. With regard to this point, this study applies a Bayesian Markov Chain Monte Carlo scheme to the NWS-PC rainfall-runoff model that has been widely used, and a case study is performed in Soyang Dam watershed in Korea. The NWS-PC model is calibrated against observed daily runoff, and thirteen parameters in the model are optimized as well as posterior distributions associated with each parameter are derived. The Bayesian Markov Chain Monte Carlo shows a improved result in terms of statistical performance measures and graphical examination. The patterns of runoff can be influenced by various factors and the Bayesian approaches are capable of translating the uncertainties into parameter uncertainties. One could provide against an unexpected runoff event by utilizing information driven by Bayesian methods. Therefore, the rainfall-runoff analysis coupled with the uncertainty analysis can give us an insight in evaluating flood risk and dam size in a reasonable way.

• Economic and Environmental Geology
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• v.56 no.5
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• pp.533-545
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• 2023

In this study, an investigation was conducted on the features, events, and processes (FEP) that could impact the long-term safety of the natural barriers constituting high-level radioactive waste geological repositories. The FEP list was developed utilizing the IFEP list 3.0 provided by the Nuclear Energy Agency (NEA) as foundational data, supplemented by geological investigations and research findings from leading countries in this field. A total of 49 FEPs related to the performance of the natural barrier were identified. For each FEP, detailed definitions, classifications, impacts on long-term safety, significance in domestic conditions, and feasibility of quantification were provided. Moreover, based on the compiled FEP list, three scenarios that could affect the long-term safety of the disposal facility were developed. Geological factors affecting the performance of the natural barrier in each scenario were selected and their relationships were visualized. The constructed FEP list and the visualization of interrelated factors in various scenarios are anticipated to provide essential information for selecting and organizing factors that must be considered in the development of mathematical models for quantitatively evaluating the long-term safety of deep geological repositories. In addition, these findings could be effectively utilized in establishing criteria related to the key performance of natural barriers for the confirmation of repository sites.

• International Journal of High-Rise Buildings
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• v.12 no.3
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• pp.225-234
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• 2023

Even at this point in the era of digital transformation, we are still facing many problems in the safety sector that cannot prevent the occurrence or spread of human casualties. When you are in an unexpected emergency, it is often difficult to respond only with human physical ability. Human casualties continue to occur at construction sites, manufacturing plants, and multi-use facilities used by many people in everyday life. If you encounter a situation where normal judgment is impossible in the event of an emergency at a life site where there are still many safety blind spots, it is difficult to cope with the existing manual guidance method. New variable guidance technology, which combines artificial intelligence and digital twin, can make it possible to prevent casualties by processing large amounts of data needed to derive appropriate countermeasures in real time beyond identifying what safety accidents occurred in unexpected crisis situations. When a simple control method that divides and monitors several CCTVs is digitally converted and combined with artificial intelligence and 3D digital twin control technology, intelligence augmentation (IA) effect can be achieved that strengthens the safety decision-making ability required in real time. With the enforcement of the Serious Disaster Enterprise Punishment Act, the importance of distributing a smart location guidance system that urgently solves the decision-making delay that occurs in safety accidents at various industrial sites and strengthens the real-time decision-making ability of field workers and managers is highlighted. The smart location guidance system that combines artificial intelligence and digital twin consists of AIoT HW equipment, wireless communication NW equipment, and intelligent SW platform. The intelligent SW platform consists of Builder that supports digital twin modeling, Watch that meets real-time control based on synchronization between real objects and digital twin models, and Simulator that supports the development and verification of various safety management scenarios using intelligent agents. The smart location guidance system provides on-site monitoring using IoT equipment, CCTV-linked intelligent image analysis, intelligent operating procedures that support workflow modeling to immediately reflect the needs of the site, situational location guidance, and digital twin virtual fencing access control technology. This paper examines the limitations of traditional fixed passive guidance methods, analyzes global technology development trends to overcome them, identifies the digital transformation properties required to switch to intelligent variable smart location guidance methods, explains the characteristics and components of AI-based public facility smart fire safety integrated system (ISFS).

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.163-171
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• 2024

Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.192-198
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• 2024

Purpose: In order to establish a safety management system led by an orderer in the construction industry, the orderer should be positioned at the peak of the construction industry safety management system and a system that can effectively support safety supervisors who can assist the orderer's role should be reflected. Method: This study collected and analyzed data on the status of safety management of construction business owners through prior research on safety management of construction business owners and a survey on the actual condition of those involved in the construction business. Results: The top priority is to improve the safety awareness and safety management capabilities of the orderer, and through these efforts, the orderer-led safety management system will be established when a national consensus on the responsibility of the orderer, such as the Serious Accident Punishment Act and the Occupational Safety and Health Act, is formed in the event of an accident such as a serious accident. Conclusion: In order to establish a safety management system led by an orderer in the construction industry, it contributes to disaster prevention by positioning the orderer at the peak of the construction safety management system and reflecting a system that can effectively support safety supervisors who can assist the orderer's role.

• Journal of Radiation Industry
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• v.18 no.1
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• pp.35-42
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• 2024

Demand for RW transportation is expected to increase due to the continuous generation of RW from nuclear power plants and facilities, decommissioning of plants, and saturation of spent fuel temporary storage facilities. The locational aspect of plants and radiation protection optimization for the public have led to an increasing demand for maritime transportation, necessitating to apprehend the overseas and domestic current status. Given the potential long-term radiological impact on the public in the event of a sinking accident, a pre-transportation exposure assessment is necessary. The objective of this study is to investigate the overseas and domestic RW maritime transportation current status and overseas dose assessment cases for the public in sinking accident. Selected countries, including Japan, UK, Sweden, and Korea, were examined for transport cases, Japan and the U.S were chosen for dose assessment case in sinking accidents. As a result of the maritime transportation case analysis, it was performed between nuclear power plants and reprocessing facilities, from plants to disposal or intermediate storage facilities. HLW and MOX fuel were transported using INF 3 shipments, and all transports were performed low speed of 13 kn or less. As a result of the dose assessment for the public in sinking accident, japan conducted an assessment for the sinking of spent fuel and vitrified HLW, and the U.S conducted for the sinking of spent fuel. Both countries considered external exposure through swimming and working at seashore, and internal exposure through seafood ingestion as exposure pathway. Additionally, Japan considered external exposure through working on board and fishing, and the U.S considered internal exposure through spray inhalation and desalinized water and salt ingestion. Internal exposure through seafood ingestion had the largest dose contribution. The average public exposure dose was 20 years after the sinking, 0.04 mSv yr^-1 for spent fuel and 5 years after the sinking, 0.03 mSv yr^-1 for vitrified HLW in Japan. In the U.S, it was 1.81 mSv yr^-1 5 years after the sinking of spent fuel. The results of this study will be used as fundamental data for maritime transportation of domestic RW in the future.

• Clinical Endoscopy
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• v.55 no.6
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• pp.801-809
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• 2022

Background/Aims: Current society guidelines recommend antibiotic prophylaxis for 3 to 5 days after endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) of pancreatic cystic lesions (PCLs). The overall quality of the evidence supporting this recommendation is low. In this study, we aimed to assess cyst infection and adverse event rates after EUS-FNA of PCLs among patients treated with or without postprocedural prophylactic antibiotics. Methods: We retrospectively reviewed all patients who underwent EUS-FNA of PCLs between 2015 and 2019 at two large-volume academic medical centers with different practice patterns of postprocedural antibiotic prophylaxis. Data on patient demographics, cyst characteristics, fine-needle aspiration technique, periprocedural and postprocedural antibiotic prophylaxis, and adverse events were retrospectively extracted. Results: A total of 470 EUS-FNA procedures were performed by experienced endosonographers for the evaluation of PCLs in 448 patients, 58.7% of whom were women. The mean age was 66.3±12.8 years. The mean cyst size was 25.7±16.9 mm. Postprocedural antibiotics were administered in 274 cases (POSTAB+ group, 58.3%) but not in 196 cases (POSTAB- group, 41.7%). None of the patients in either group developed systemic or localized infection within the 30-day follow-up period. Procedure-related adverse events included mild abdominal pain (8 patients), intra-abdominal hematoma (1 patient), mild pancreatitis (1 patient), and perforation (1 patient). One additional case of pancreatitis was recorded; however, the patient also underwent endoscopic retrograde cholangiopancreatography. Conclusions: The incidence of infection after EUS-FNA of PCLs is negligible. Routine use of postprocedural antibiotics does not add a significant benefit.