• Proceedings of the Korean Society of Disaster Information Conference
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• 2023.11a
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• pp.167-168
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• 2023

에너지분야 국가핵심기반시설에서 산업재해 및 업무중단 사고예방을 위해 재해경감활동관리체계(BCMS)에서 일일위험지수 재난안전관리 프로그램을 자체개발 운용하여 정부의 중대재해 감축 로드맵의 핵심적인 4대 전략 중 하나인 사업장에서 유해위험요인에 대한 자기규율적인 예방관리체계의 확립한 사례를 제시하였다. 이에 대한 신뢰성 검증을 위해 중대산업재해 감축효과에 영향을 미친 사업장의 BCMS, 일일위험지수 및 중대재해처벌법 간의 관계성을 연구한 결과, 제도 간 개념의 관련성이 높으며, 상호 보완적이고 영향을 미치는 것으로 확인되었다. 따라서 동종 사업장에서 재해경감활동관리체제의 일일위험지수를 활용한다면 중대재해예방관리에 도움이 될 것으로 기대된다.

• Proceedings of the Korean Society of Disaster Information Conference
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• 2022.10a
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• pp.251-252
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• 2022

국가핵심기반은 국가 운영을 위하여 사업의 중단 없이 연속적으로 운영될 필요가 있다. 본 연구에서는 에너지관련 기관을 대상으로 재해를 예방하기 위하여 위험작업의 위험도 평가와 위험수준에 맞는 적절한 관리순찰 강화방안을 중심으로 개발된 일일안전지수 제도를 소개하고 그 효과성에 대하여 검토하였다. 그 결과 일일안전지수는 중대재해를 효과적으로 감소시키는 것으로 분석되었다. 일일안전지수제도는 다른 국가핵심기반에서도 적합하게 응용 적용하여 재해를 예방할 수 있다.

• International Area Studies Review
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• v.14 no.2
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• pp.25-40
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• 2010

Accurate forecasting of volatility is of considerable interest in financial volatility research, particularly in regard to portfolio allocation, option pricing and risk management because volatility is equal to market risk. So, we attempted to delineate a model with good ability to forecast and identified stylized features of volatility, with a focus on volatility persistence or long memory in the Australian futures market. In this context, we assessed the long-memory property in the volatility of index futures contracts using three conditional volatility models, namely the GARCH, IGARCH and FIGARCH models. We found that the FIGARCH model better captures the long-memory property than do the GARCH and IGARCH models. Additionally, we found that the FIGARCH model provides superior performance in one-day-ahead volatility forecasts. As discussed in this paper, the FIGARCH model should prove a useful technique in forecasting the long-memory volatility in the Australian index futures market.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.1
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• pp.1-10
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• 2012

Digital Forecast of the Korea Meteorological Administration (KMA) represents 5 km gridded weather forecast over the Korean Peninsula and the surrounding oceanic regions in Korean territory. Digital Forecast provides 12 weather forecast elements such as three-hour interval temperature, sky condition, wind direction, wind speed, relative humidity, wave height, probability of precipitation, 12 hour accumulated rain and snow, as well as daily minimum and maximum temperatures. These forecast elements are updated every three-hour for the next 48 hours regularly. The objective of this study was to construct Forest Fire Danger Rating Systems on the Korean Peninsula (FFDRS_KORP) based on the daily weather index (DWI) and to improve the accuracy using the digital forecast data. We produced the thematic maps of temperature, humidity, and wind speed over the Korean Peninsula to analyze DWI. To calculate DWI of the Korean Peninsula it was applied forest fire occurrence probability model by logistic regression analysis, i.e. $[1+{\exp}\{-(2.494+(0.004{\times}T_{max})-(0.008{\times}EF))\}]^{-1}$. The result of verification test among the real-time observatory data, digital forecast and RDAPS data showed that predicting values of the digital forecast advanced more than those of RDAPS data. The results of the comparison with the average forest fire danger rating index (sampled at 233 administrative districts) and those with the digital weather showed higher relative accuracy than those with the RDAPS data. The coefficient of determination of forest fire danger rating was shown as $R^2$=0.854. There was a difference of 0.5 between the national mean fire danger rating index (70) with the application of the real-time observatory data and that with the digital forecast (70.5).

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.87-87
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• 2021

이상기후 현상으로 기후변화가 사회와 경제에 미치는 영향이 뚜렷한 추세로 변화되고 있다. 현재 기후변화에 관련된 연구는 사회 시스템에서 위험관리를 위해 기온과 강수량에 따라 다양한 분야에 미치는 영향에 대한 연구를 중점으로 이뤄지고 있다. 본 연구는 여름철 폭염에 의한 기후변화가 하천수질에 미치는 영향을 평가하기 위한 것으로, 우리나라 기상청 91개의 기상관측소에서 일일온도 33℃ 이상의 이벤트를 대상으로 환경부 수질관측망 918개에 대한 14개의 하천수질인자인 DO, BOD, COD, TOC, DOC, TN, DTN, NH4-N, NO2-N, NO3-N, TP, DTP, PO4-P, Chl-a를 분석하였다. 이를 우리나라 117개 중권역별 하천수질과 폭염강도와 지속시간을 나타내는 폭염 지수를 산정하여 분석하였다. 폭염 관련 뉴스 데이터는 2013년부터 2019년까지 Python 기반 뉴스 크롤러를 이용해 폭염 취약지수(Heat Wave Vulnerability Index, HWVI)를 기준으로 분류하여 키워드를 수집하였으며 HWVI 중 '기후노출' 키워드와 관련된 기사는 총 22,514건으로 69.9%로 수집되었다. 공간적 영향 평가를 위해 Getis-Ord Gi*를 이용하여 폭염지수와 하천수질인자간 핫스팟 분석을 실시하고 폭염관련 빅데이터가 하천수질에 미치는 영향을 평가하였다. 폭염지수는 낙동강유역 하류에 대해 Chl-a, TN, TP 항목에서 높은 밀도를 보였다. 분석대상지역 내 폭염이 발생한 확률과 반경 밖에서 발생할 확률의 우도비를 분석하기 위해 SaTScan을 이용한 공간검색통계분석을 실시하였다. 분석결과 폭염지수와 DO의 공간상관성이 높은 것으로 나타났다.

• Korean journal of food and cookery science
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• v.29 no.6
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• pp.699-707
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• 2013

This study was conducted to examine the effects of Cheonggukjang powder made using black foods on liver function and lipid composition in streptozotocin(STZ)-induced diabetic rats. The experimental animals were divided into 5 groups and fed the following for 7 weeks; normal diet(control), STZ+normal diet(Diabetic), STZ+50% soybean Cheonggukjang supplementation(DSC), STZ+44.5% yakkong Cheonggukjang supplementation(DYC), and STZ+supplementation with 50% yakkong black food(black rice, black sesame seeds, and sea tangle) Cheonggukjang(DYCB). The results showed that the body weight gain and food efficiency ratio of the STZ-induced diabetic groups were significantly lower than those of the control group. In the Diabetic group, glutamic oxaloacetic transaminase(GOT) and glutamic pyruvic transaminase(GPT) activities and total bilirubin content in serum were significantly greater than those in the control group. However, supplementation with Cheonggukjang reduced these values. In the Diabetic group, the triglyceride, total cholesterol, and low-density lipoprotein(LDL)-cholesterol contents in the serum and liver tissue, as well as the atherogenic index(AI) and cardiac risk factors(CRF) were significantly higher than the corresponding values in the control group, although the high-density lipoprotein(HDL)-cholesterol and phospholipid contents were significantly lower than those in the control group. However, supplementation with Cheonggukjang normalized the changed lipid composition in the STZ-induced diabetic rats. Further, yakkong Cheonggukjang and black food contaning yakkong Cheonggukjang normalized AI and CRF.

• Korea Trade Review
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• v.48 no.2
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• pp.27-43
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• 2023

The maritime industry is playing an increasingly vital part in global economic expansion. Specifically, the Baltic Dry Index is highly correlated with global commodity prices. Hence, the importance of BDI prediction research increases. But, since the global situation has become more volatile, it has become methodologically more difficult to predict the BDI accurately. This paper proposes an integrated machine-learning strategy for accurately forecasting BDI trends. This study combines the benefits of a convolutional neural network (CNN) and long short-term memory neural network (LSTM) for research on prediction. We collected daily BDI data for over 27 years for model fitting. The research findings indicate that CNN successfully extracts BDI data features. On this basis, LSTM predicts BDI accurately. Model R2 attains 94.7 percent. Our research offers a novel, machine-learning-integrated approach to the field of shipping economic indicators research. In addition, this study provides a foundation for risk management decision-making in the fields of shipping institutions and financial investment.

• Advanced Industrial SCIence
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• v.2 no.3
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• pp.22-28
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• 2023

In this study, we conducted research on the automated trading of U.S. stocks through a volatility strategy using the Fear and Greed index. Volatility in the stock market is a common phenomenon that can lead to fluctuations in stock prices. Investors can capitalize on this volatility by implementing a strategy based on it, involving the buying and selling of stocks based on their expected level of volatility. The goal of this thesis is to investigate the effectiveness of the volatility strategy in generating profits in the stock market.This study employs a quantitative research methodology using secondary data from the stock market. The dataset comprises daily stock prices and daily volatility measures for the S&P 500 index stocks. Over a five-year period spanning from 2016 to 2020, the stocks were listed on the New York Stock Exchange (NYSE). The strategy involves purchasing stocks from the low volatility group and selling stocks from the high volatility group. The results indicate that the volatility strategy yields positive returns, with an average annual return of 9.2%, compared to the benchmark return of 7.5% for the sample period. Furthermore, the findings demonstrate that the strategy outperforms the benchmark return in four out of the five years within the sample period. Particularly noteworthy is the strategy's performance during periods of high market volatility, such as the COVID-19 pandemic in 2020, where it generated a return of 14.6%, as opposed to the benchmark return of 5.5%.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.97-108
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• 2024

This research delves into the escalating concerns of accidents and fatalities in the construction industry over the recent five-year period, focusing on the development of a Safety Perception Model to augment safety measures. Given the rising percentage of elderly workers and the concurrent drop in productivity within the sector, there is a pronounced need for leveraging Fourth Industrial Revolution technologies to bolster safety protocols. The study comprises an in-depth analysis of statistical data regarding construction-related fatalities, aiming to shed light on prevailing safety challenges. Central to this investigation is the formulation of a Safety Perception Model tailored for small-scale construction projects. This model facilitates the quantification of safety risks by evaluating safety grades across construction sites. Utilizing the DWM1000 module, among an array of wireless communication technologies, the model enables the real-time tracking of worker locations and the assessment of safety levels on-site. Furthermore, the deployment of a safety management system allows for the evaluation of risk levels associated with individual workers. Aggregating these data points, the Safety Climate Index(SCLI) is calculated to depict the daily, weekly, and monthly safety climate of the site, thereby offering insights into the effectiveness of implemented safety measures and identifying areas for continuous improvement. This study is anticipated to significantly contribute to the systematic enhancement of safety and the prevention of accidents on construction sites, fostering an environment of improved productivity and strengthened safety culture through the application of the Safety Perception Model.

• Journal of Life Science
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• v.20 no.12
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• pp.1812-1819
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• 2010

Skipping breakfast is a risk factor closely related to metabolic syndrome and obesity. We analyzed the relationship between breakfast size, metabolic syndrome and obesity. The study included 5,548 adults who visited a health promotion center at Pusan National University from January to November of 2006. Subjects were divided into four groups according to breakfast size - skipper group (no breakfast), small intake group, medium intake group and large intake group. 959 (17.3%) of the 5548 subjects were included in the Skipper group. Intake of daily calories, proteins, carbohydrates and fats was the lowest in the Skipper group. Breakfast size increased linearly with an increased intake of daily calories, proteins, carbohydrates and fats. Body mass index ($23.4\;kg/m^2$) and waist circumference (79.6 cm) were the lowest in the Small intake group. In the Small intake group, triglycerides, fasting plasma glucose, systolic blood pressure and diastolic blood pressure were the lowest, and high density lipoprotein cholesterol levels were the highest. The number of metabolic risk factors was the lowest in Small intake group. Odds ratio of metabolic syndrome (Odds ratio=0.612) was the lowest in Small intake group. Along with increasing breakfast size, the odds ratio also increased. In this study, breakfast size was found to influence metabolic risk factors. Skipping breakfast worsened metabolic risk factors, while a small breakfast size had a favorable effect on metabolic risk factors.