• Journal of Korea Trade
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• v.27 no.2
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• pp.96-114
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• 2023

Purpose - This paper elucidates a nexus between the occurrence of rare disaster events and the volatility of economic growth by distinguishing the likelihood of rare events from stochastic volatility. We provide new empirical facts based on a quarterly time series. In particular, we focus on the role of financial liberalization in spreading the economic crisis in developing countries. Design/methodology - We use quarterly data on consumption expenditure (real per capita consumption) from 44 countries, including advanced and developing countries, ending in the fourth quarter of 2020. We estimate the likelihood of rare event occurrences and stochastic volatility for countries using the Bayesian Markov chain Monte Carlo (MCMC) method developed by Barro and Jin (2021). We present our estimation results for the relationship between rare disaster events, stochastic volatility, and growth volatility. Findings - We find the global common disaster event, the COVID-19 pandemic, and thirteen country-specific disaster events. Consumption falls by about 7% on average in the first quarter of a disaster and by 4% in the long run. The occurrence of rare disaster events and the volatility of gross domestic product (GDP) growth are positively correlated (4.8%), whereas the rare events and GDP growth rate are negatively correlated (-12.1%). In particular, financial liberalization has played an important role in exacerbating the adverse impact of both rare disasters and financial market instability on growth volatility. Several case studies, including the case of South Korea, provide insights into the cause of major financial crises in small open developing countries, including the Asian currency crisis of 1998. Originality/value - This paper presents new empirical facts on the relationship between the occurrence of rare disaster events (or stochastic volatility) and growth volatility. Increasing data frequency allows for greater accuracy in assessing a country's specific risk. Our findings suggest that financial market and institutional stability can be vital for buffering against rare disaster shocks. It is necessary to preemptively strengthen the foundation for financial stability in developing countries and increase the quality of the information provided to markets.

• Transactions of the Korean Society of Automotive Engineers
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• v.1 no.3
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• pp.12-21
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• 1993

In recent years, high efficiency, high performance, and low pollutant emmision engines have been developed. Knock phenomenon has drawn interests because it became an hinderance to engine power and efficiency increase through higher compression ratio. Knock phenomenon is an abnormal combustion originated from autoignition of unburned gas in the end-gas region during the later stage of combustion process and accompanied a high pitched metallic noise. And this phenomenon is characterized by knock occurrence percentage, knock occurrence angle and knock intensity. A four cylinder spark ignition engine is used in our experiment, and its combustion chamber pressure is measured at various engine speeds, ignition timing. The data are analyzed by numerous methods in order to select the optimum methods and to achieve better understanding of knock characteristics. Methods using band-pass filter, third derivative and step method are shown to be the most suitable, while methods using frequency analysis are shown to be unsuitable. Because step method only uses signals above threshold value during knocking condition, pressure signal analyses with this method show good signal-to-noise ratio.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.153-158
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• 2016

As the number of social network users increases, the information on event such as social issues and disasters receiving attention in each region is promptly posted by the bucket through social media site in real time, and its social ripple effect becomes huge. This study proposes a detection method of events that draw attention from users in specific region at specific time by using twitter data with regional information. In order to collect Twitter data, we use Twitter Streaming API. After collecting data, We implemented event detection system by analyze the frequency of a keyword which contained in a twit in a particular time and clustering the keywords that describes same event by exploiting keywords' co-occurrence graph. Finally, we evaluates the validity of our method through experiments.

• Journal of Digital Convergence
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• v.17 no.2
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• pp.313-318
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• 2019

The purpose of this study is to investigate whether there is a difference in the incidence of the black circle border of iris(skin disease) according to the iris constitution. Iris was taken for 100 adults living in Seoul. Iris was photographed using the iris camera DV-2H, a blue focus development product. Statistical significance was tested by correlation analysis, and the occurrence of black circle border of iris was low negative correlation(p<0.01). As mentioned above, we know that the occurrence of black circle border of iris differs according to the iris constitution, and by using it actively, it will help health promotion about skin. There is a need to study the changes of iris in the cause of skin disease by using a blood test to analyze the cause of the skin disease in the future.

• Journal of Plant Biotechnology
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• v.47 no.2
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• pp.179-184
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• 2020

Embryogenic calli from Codonopsis lanceolata L. were cultured in MS liquid media and supplemented with various concentrations of primary carbon sources to study the effects of carbohydrates and osmoticum on somatic embryogenesis and somatic embryo morphology. Sucrose, glucose, and a combination of 3% sucrose and various concentrations of sorbitol or mannitol as osmoticum were used as carbon supplements. The maximum number of somatic embryos per flask was greater in media exclusively supplemented with 3% sucrose (128.29) than exclusively glucose-supplemented media (47.67) and either supplement combination of 3% sucrose and osmoticum (95.67 with mannitol and 114.00 with sorbitol). The number of somatic embryos gradually decreased in media with increasing concentrations of combined osmoticum supplement. Decreases also occurred in the highest concentrations of sucrose- and glucose-supplemented media. The total frequency of somatic embryos with two cotyledons was slightly higher in medium with 3% + mannitol (24.09%) compared with exclusively sucrose (21.52%), glucose (21.22%), or 3% sucrose + sorbitol (22.13%). As concentrations of sucrose and glucose increased, the occurrence of two cotyledons and trumpet cotyledons gradually decreased and the occurrence of polycotyledon and globular stage embryos increased. Furthermore, as concentrations of 3% sucrose and osmoticum increased, the occurrence of trumpet cotyledon and globular stage embryos increased and the occurrence of polycotyledon gradually decreased. These results demonstrated that the somatic embryogenesis and occurrence of cotyledon morphology were influenced by the concentration of carbohydrates and combinations of 3% sucrose and osmoticum supplements.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.79-98
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• 2018

The purpose of this study is to suggest a model analysing spatio-temporal characteristics of the civil complaints for the officially assessed land price based on big data mining. Specifically, in this study, the underlying reasons for the civil complaints were found from the spatio-temporal perspectives, rather than the institutional factors, and a model was suggested monitoring a trend of the occurrence of such complaints. The official documents of 6,481 civil complaints for the officially assessed land price in the district of Jung-gu of Incheon Metropolitan City over the period from 2006 to 2015 along with their temporal and spatial poperties were collected and used for the analysis. Frequencies of major key words were examined by using a text mining method. Correlations among mafor key words were studied through the social network analysis. By calculating term frequency(TF) and term frequency-inverse document frequency(TF-IDF), which correspond to the weighted value of key words, I identified the major key words for the occurrence of the civil complaint for the officially assessed land price. Then the spatio-temporal characteristics of the civil complaints were examined by analysing hot spot based on the statistics of Getis-Ord $Gi^*$. It was found that the characteristic of civil complaints for the officially assessed land price were changing, forming a cluster that is linked spatio-temporally. Using text mining and social network analysis method, we could find out that the occurrence reason of civil complaints for the officially assessed land price could be identified quantitatively based on natural language. TF and TF-IDF, the weighted averages of key words, can be used as main explanatory variables to analyze spatio-temporal characteristics of civil complaints for the officially assessed land price since these statistics are different over time across different regions.

• Journal of Korea Water Resources Association
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• v.50 no.4
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• pp.233-239
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• 2017

In this study, we analyzed typhoon affecting Korean Peninsula and runoff characteristic changes according to the typhoon based on Sumjin river dam, a representative multi-purpose dam. We quantified typhoon flow by applying the typhoon domain, and will provide base data for climate change adaptation and counterstrategy through correlation analysis of the change of typhoon statistical data and Indicators of Hydrologic Alterations (IHA). Korean Peninsula impact typhoon has a great effect on the scale of peak flow and the change of occurrence time. The occurrence frequency and duration of the peak flow were analyzed to be relatively unrelated to the typhoon affected by the Korean peninsula. These changes were also confirmed in the correlation analysis results. Correlation coefficient between the peak flow (0.41) and peak flow occurrence time (correlation coefficient = 0.83) was positively correlated with the Korean peninsula influenced typhoon.

• Biomedical Science Letters
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• v.21 no.2
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• pp.84-91
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• 2015

To provide guidelines for the empirical treatment of urinary tract infections, we observed annual changes in the occurrence frequency and antimicrobial susceptibility of urinary isolates in a university hospital in the Chungbuk province, South Korea, over a period of 10 years (2004~2013). Escherichia coli (38.2%), Enterococcus faecalis (11.7%), Klebsiella pneumoniae (7.3%), Pseudomonas aeruginosa (4.3%), E. faecium (4.3%), and Staphylococcus aureus (4.1%) were commonly isolated urinary pathogens. The prevalence of E. coli, E. faecium and Streptococcus agalactiae were significantly higher in females (P < 0.001), whereas E. faecalis, P. aeruginosa and S. aureus were significantly more common in male patients (P < 0.001). E. coli mostly frequently showed resistance to ampicillin (67.94%), followed by trimethoprim/sulfamethoxazole (36.06%) and ciprofloxacin (26.84%). Over the studied time period, resistance rates of E. coli to ciprofloxacin significantly increased (20.44% to 33.55%). Moreover, extended-spectrum $\beta$-lactamase (ESBL) producing isolates also significantly increased in E. coli (4.2% to 18.3%) and K. pneumoniae (9.6% to 26.9%). In addition, the proportion of vancomycin-resistant Enterococcus facium (VRE) also increased (15.7% to 25.0%). In conclusion, over the last 10 years, the proportions of ciprofloxacin resistant E. coli and multidrug-resistant bacteria, such as ESBL and VRE have significantly increased. This trend must be strictly controlled and demonstrates the need for more updated guidelines for the treatment of urinary tract infections.

• Korean Journal of Artificial Intelligence
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• v.10 no.1
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• pp.21-25
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• 2022

Korea has relatively less crime than other countries. However, the crime rate is steadily increasing. Many people think the crime rate is decreasing, but the crime arrest rate has increased. The goal is to check the relationship between CCTV and the crime rate as a way to lower the crime rate, and to identify the correlation between areas without CCTV and areas without CCTV. If you see a crime that can happen at any time, I think you should use a random forest algorithm. We also plan to use machine learning random forest algorithms to reduce the risk of overfitting, reduce the required training time, and verify high-level accuracy. The goal is to identify the relationship between CCTV and crime occurrence by creating a crime prevention algorithm using machine learning random forest techniques. Assuming that no crime occurs without CCTV, it compares the crime rate between the areas where the most crimes occur and the areas where there are no crimes, and predicts areas where there are many crimes. The impact of CCTV on crime prevention and arrest can be interpreted as a comprehensive effect in part, and the purpose isto identify areas and frequency of frequent crimes by comparing the time and time without CCTV.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.841-851
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• 2019

This study presents risk ranking by accident types at intersections, crosswalk and tunnel sections. An ordered logit model was used to estimate the accident severity of traffic accidents based on 58,868 accident records that have occurred on the Seoul and Gyeonggi-do over the period 2014-2017. The factors affecting the injury severity were identified by the estimated model first, and risk ranking was proposed according to conditions of accident occurrence using relative ratio analysis later. The analysis results showed that the injury severity dramatically depends on the location and time of the accident. The analysis results showed that the injury severity dramatically depends on the location and time of the accident. Furthermore, there are severe injury cases in terms of the injury severity despite the small number of occurrence of traffic accident, or there are severe injury cases in terms of the injury severity despite the high frequency of occurrence of traffic accident.