• Journal of the Society of Disaster Information
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• v.17 no.1
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• pp.60-67
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• 2021

Purpose: Traditional markets often have irregular space utilization patterns because the spaces are created and divided as time passed. Internally, there is high risk of fire due to problems such as aging facilities and high-density of stores and externally, there is high risk of fire spread since it is often adjacent to deteriorated residential and commercial facilities. Method: In this paper, on-site investigations were carried out to check fire risk factors and fire spread risk, and fire occurrence and expansion risk factors were investigated for traditional markets in Hwanghak-dong and Dong-daemun by using large-scale fire data from existing traditional markets. Result: As a result of the analysis, there are likely to be various problems such as high fire load and lack of safety awareness due to aging facilities and high-density of stores. In particular, it is necessary to prepare countermeasures because deteriorated residential facilities with narrow alleys around traditional markets have high fire spread. It is situation that while traditional markets mainly are managing for fire and disaster centering on the merchant association, the surrounding residential areas are not properly managed. Conclusion: It is necessary to manage deteriorated residential facilities with traditional markets, also to be linked early warning system and information to evacuate rapidly in case of fire there.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.93-103
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• 2021

S&OP(Sales and Operations Planning) is an ongoing process of periodic planning, reviewing, and evaluation through the involvement of all key stakeholders. Within this process, performance is regularly reviewed and early warning signals are generated, so that the company can react quickly to changing market and operational environment. This paper presents a framework for effective S&OP for fair alignment, accountability, teamwork, visibility, and risk management. This framework focuses on supply chain information governance, level of information sharing through S&OP, role of S&OP as coordination mechanism, APS effectivesness as a planning tool and SCM performance. In addition, a brief case study on the operating characteristics of S&OP at three Korean firms is presented. Implications of the study finding are also provided. It will also make companies that are considering the introduction of S&OP aware of the importance of S&OP, which will provide practical guidelines for the introduction of S&OP.

• Tuberculosis and Respiratory Diseases
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• v.84 no.2
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• pp.125-133
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• 2021

Background: The coronavirus disease (COVID-19) can manifest in a range of symptoms, including both asymptomatic systems which appear nearly non-existent to the patient, all the way to the development of acute respiratory distress syndrome (ARDS). Specifically, COVID-19-associated pneumonia develops into ARDS due to the rapid progression of hypoxia, and although arterial blood gas analysis can assist in halting this deterioration, the current environment provided by the COVID-19 pandemic, which has led to an overall lack of medical resources or equipment, has made it difficult to administer such tests in a widespread manner. As a result, this study was conducted in order to determine whether the levels of oxygen saturation (SpO₂) and the fraction of inhaled oxygen (FiO₂) (SF ratio) can also serve as predictors of ARDS and the patient's risk of mortality. Methods: This was a retrospective cohort study conducted from February 2020 to Mary 2020, with the study's subjects consisting of COVID-19 pneumonia patients who had reached a state of deterioration that required the use of oxygen therapy. Of the 100 COVID-19 pneumonia cases, we compared 59 pneumonia patients who required oxygen therapy, divided into ARDS and non-ARDS pneumonia patients who required oxygen, and then investigated the different factors which affected their mortality. Results: At the time of admission, the ratios of SpO₂, FiO₂, and SF for the ARDS group differed significantly from those of the non-ARDS pneumonia support group who required oxygen (p<0.001). With respect to the predicting of the occurrence of ARDS, the SF ratio on admission and the SF ratio at exacerbation had an area under the curve which measured to be around 85.7% and 88.8% (p<0.001). Multivariate Cox regression analysis identified that the SF ratio at exacerbation (hazard ratio [HR], 0.916; 95% confidence interval [CI], 0.846-0.991; p=0.029) and National Early Warning Score (NEWS) (HR, 1.277; 95% CI, 1.010-1.615; p=0.041) were significant predictors of mortality. Conclusion: The SF ratio on admission and the SF ratio at exacerbation were strong predictors of the occurrence of ARDS, and the SF ratio at exacerbation and NEWS held a significant effect on mortality.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.17-27
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• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.

• Economic and Environmental Geology
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• v.55 no.4
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• pp.421-428
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• 2022

This study analyzes emerging earthquake and space use technologies from the latest Korean and Japanese scientific and technological foresights in 2022 and 2019, respectively. Unlike the earthquake prediction and early warning technologies presented in the 2017 study, the emerging earthquake technologies in 2022 in Korea was described as an earthquake/complex disaster information technology and public data platform. Many detailed future technologies were presented in Japan's 2019 survey, which includes largescale earthquake prediction, induced earthquake, national liquefaction risk, wide-scale stress measurement; and monitoring by Internet of Things (IoT) or artificial intelligence (AI) observation & analysis. The latest emerging space use technology in Korea and Japan were presented in more detail as robotic mining technology for water/ice, Helium-3, and rare earth metals, and manned station technology that utilizes local resources on the moon and Mars. The technological realization year forecasting in 2019 was delayed by 4-10 years from the prediction in 2015, which could be greater due to the Corona 19 epidemic, the declaration of carbon neutrality in Korea and Japan in 2020 and the Russo-Ukrainian War in 2022. However, it is required to more active research on earthquake and space technologies linked to information technology.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.120-128
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• 2022

There are 17,000 reservoir dams in Korea, of which more than 85% were built over 50 years ago. Old embankment dams are weakened by internal erosion and suffusion phenomena due to preferential leakage paths and this ongoing weakening can cause their failure. Therefore, early warning associated with leakage in an embankment dam is crucial to prevent its failure. An electrical resistivity survey is a non-destructive, real-time and in-situ technique for detecting the development of leakage zones and general conditions of embankment dams. Because of its advantages, the electrical resistivity survey is widely used for reservoir safety inspections. However, the electrical resistivity survey is still not officially included in the precise safety inspection of reservoir dams because it cannot present a quantitative index of dam safety. In this study, we propose a method for calculating the leak index according to the water content evaluated from the electrical resistivity survey and/or induced polarization survey. Particularly, by proposing a quantitative leak index calculation method from monitoring surveys and independent surveys, we provide a theoretical basis for including electrical resistivity and induced polarization surveys as components of the precise safety inspection of reservoirs dams.

• Journal of the Korean GEO-environmental Society
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• v.24 no.2
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• pp.31-40
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• 2023

We installed temporary strong motion seismometers at the ground surface, 1 m, 2 m, and 9 m at an existing seismic station that houses permanent seismometers installed at 20 m and 100 m, to investigate the influence of installation depth on the recorded ambient and anthropogenic noise level and the characteristics of earthquake signals. Analysis of the ambient noise shows that anthropogenic noise dominates where vibration period T < 1 s at the studied site, whereas wind speed appears to be strongly correlated with the noise level at T > 1 s. Frequency-wavenumber analysis of 2D seismometer array suggests that ambient noise in short periods are predominantly body waves, rather than surface waves. The level of ambient noise was low at 9 m and 20 m, but strong amplification of noise level at T < 0.1 s was observed at the shallow seismometers. Both the active-source test result and the recorded earthquake data demonstrated that the signal level is decreased with the increase of depth. Our result also shows that recorded motions at the ground and 1 m are strongly amplified at 20 Hz (T = 0.05 s), likely due to the resonance of the 3 m thick soil layer. This study demonstrates that analysis of ambient and active-source vibration may help find optimal installation depth of strong motion seismometers. We expect that further research considering various noise environments and geological conditions will be helpful in establishing a guideline for optimal installation of strong motion seismometers.

• Korean Journal of Ecology and Environment
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• v.56 no.1
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• pp.1-13
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• 2023

Targeting Microcystin (MC), which is most abundantly detected in the North-Han River water area, we analyzed the relationship between the MC biosynthesis gene (mcyA gene), cyanobacteria cell density, and MC concentration, derived an RNA-MC conversion formula, and derived the cyanobacteria. The concentration of MC present in cells was predicted. In the North-Han River waters, the mcyA gene was found mainly at downstream sites of the North-Han River after Muk-Hyeon Stream junction, and higher copy numbers were found on average than other sites. In the Uiam Lake waters upstream of the North-Han River, the mcyA gene copy number increased at the Kong-Ji Stream point, and after September, the mcyA gene copy number decreased throughout the North-Han River waters. The expression of the mcyA gene was concentrated in the short period of summer due to the spatio-temporal difference between upstream and downstream water bodies. The mcyA gene expression level was not only highly correlated with MC concentration, but also correlated with the cell density of Microcystis aeruginosa and Dolichospermum circinale, which are known to biosynthesize MC. Six conversion formulas derived based on the RNA-MC relationship showed statistical significance (p<0.05) and exhibited high correlation coefficients (r) of 0.9 or higher. The expression level of MC biosynthesis gene present in eRNA determines the synthesis of cyanotoxin substances in water, quickly quantifies gene activity, and can be fully utilized for early warning of MC development.

• Korean Journal of Clinical Laboratory Science
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• v.54 no.1
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• pp.61-67
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• 2022

Intraoperative neurophysiological monitoring (INM) ensures the stability and safety of specific surgeries in high-risk groups. As part of INM, intensive tests are conducted during the surgical process. When INM tests are applied during surgery, a delay in notifying the operating surgeon in cases of neurological defects can cause serious irreversible sequelae to the patient. Aortic replacement, which is necessitated due to aortic aneurysms and aortic dissection, is a complicated procedure that blocks the blood flow to the heart. When arteries that branch out from the aorta and supply blood to the spinal cord are replaced, blood flow to the spinal cord decreases, resulting in spinal ischemia. In aortic surgery, INM plays an important role in preventing spinal ischemia and serious complications by quickly detecting the early signs of spinal ischemia during cross-clamping and reporting it to the surgeon. Therefore, this paper was prepared to help examiners who conduct INM by detailing the process, method, time, and warning criteria for INM. This paper identifies the need for INM in aortic surgery and the process flow for a smooth test, accurate and rapid examination, and subsequent reporting.

• Convergence Security Journal
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• v.23 no.2
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• pp.27-36
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• 2023

In recent years, ransomware attacks have become more organized and specialized, with the sophistication of attacks targeting specific individuals or organizations using tactics such as social engineering, spear phishing, and even machine learning, some operating as business models. In order to effectively respond to this, various researches and solutions are being developed and operated to detect and prevent attacks before they cause serious damage. In particular, honeypots can be used to minimize the risk of attack on IT systems and networks, as well as act as an early warning and advanced security monitoring tool, but in cases where ransomware does not have priority access to the decoy file, or bypasses it completely. has a disadvantage that effective ransomware response is limited. In this paper, this honeypot is optimized for the user environment to create a reliable real-time dynamic honeypot file, minimizing the possibility of an attacker bypassing the honeypot, and increasing the detection rate by preventing the attacker from recognizing that it is a honeypot file. To this end, four models, including a basic data collection model for dynamic honeypot generation, were designed (basic data collection model / user-defined model / sample statistical model / experience accumulation model), and their validity was verified.