• The Journal of the Korea Contents Association
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• v.22 no.8
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• pp.274-287
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• 2022

Competition in the broadcasting market is intensifying as OTT services are spreading. And Korea is positioned as a competent international contents supply base. This can be helpful for the domestic contents production industry. However, it can result in being incorporated as a subcontractor in the global video industry. Therefore, it is necessary for Korean OTT operators to expand their market upto overseas and maintain competitiveness by linking content competitiveness to the sales expansion. This study was conducted to reduce the risk and encourage implementation through feasibility analysis of overseas business of domestic OTT operators. The North American market was selected as a region with high potential through in-depth interviews with experts and literatures review. And it was confirmed that the partnership with local platform is effective. Then, the sales and input costs were estimated, and business was evaluated using the net present value method. Totally 18 scenarios were created using multiple estimates for copyright cost, subscribers, and rate, which are highly uncertain. From the analyses, 8 scenarios were found to be acceptable. And copyright cost has the greatest impact on business success, followed by rates and subscribers.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.168-175
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• 2011

Construction accidents are major problem in Turkish Construction industry and especially fatally rates are very high. Current legislative system on occupational safety in Turkey enforces employers to implement safety measures as well as safety management systems. However level of consciousness in the industry is unsatisfactory and safety are perceived as extra cost and unnecessary expenditure. Moreover, especially in small residential building constructions which have a big share in the industry and unfortunately safety measures to mitigate or abate construction risks do not exist. The study focuses on small residential building construction sites and in the scope of this study, thirty building projects are examined. For each building project, project cost including labour and material costs, service and consultancy costs for mechanical, electrical systems as well as architectural and structural services, costs for supervision and finally general expenditures for construction site facilities were calculated. On the other hand, occupational safety costs for personal protective equipment, collective protective measures, consultancy and training were determined. Work breakdown structures were established and for each work item firstly occupational risks were evaluated and furthermore according to risk scores safety measures to be implemented were defined and related costs were calculated. The study gave results for total safety cost on average, in terms of percentage of total project cost (3.73% of total project cost), safety cost per man-hour (0.40 USD) and safety cost in terms of unit construction area (11.60 USD per square meter). Since safety management is a part of whole project management process, study gives suggestions and techniques to calculate safety costs and implement safety measures as a part of project management service for professionals. Authors believe that suggested approach may easily developed by the usage of more data to establish a model for estimation not only for building construction sites but also for all construction projects.

• Korean Journal of Environment and Ecology
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• v.34 no.1
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• pp.9-17
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• 2020

Domestic cats (Felis catus) introduced to insular environments can be invasive predators that often threaten endemic species and cause biodiversity loss or local extinction on the island. This study was conducted from March to July 2018 to understand the population size, home range, and spatial use of cats introduced to Mara Islet (N 33° 07', E 126° 16') in Jeju Special Governing Province, the Republic of Korea. Observation records based on their natural marks revealed that there were 20 adult cats on Mara Islet. A capture-recapture method also estimated 20 adult individuals (95% confidence interval: 20-24 individuals). According to our telemetry study on ten adults deployed with GPS-based telemetry units, the home range size was 12.05±6.99 ha (95% KDE: kernel density estimation), and the core habitat size was 1.60±0.77 ha (50% KDE). There were no significant differences in the home range and core habitat sizes by sex. The home range of domestic cats overlapped with the human residential area, where they might secure easy foods. Five of ten tracked cats were active at potential breeding colonies for the Crested Murrlet (Synthliboramphus wumizusume), and six approached potential breeding areas of the Styan's Grasshopper Warbler (Locustella pleskei), suggesting the predation risk of the two endangered species by cats. This study provides novel information on the population size and home range of introduced cats on Mara Islet which is an important stopover site of migratory birds as well as a breeding habitat of the two endangered avian species. Reducing the potential negative impacts of the introduced cats on migratory birds and the endangered species on Mara Islet requires monitoring of the predation rate of birds by cats, the population trends of cats and endangered breeding birds as well as the effective cat population control and management.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.8
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• pp.1177-1191
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• 2016

Estimation of food consumption details, such as portion size and frequency of consumption, is needed for exposure assessment step in microbiological risk assessment. This study investigated the amounts and frequencies of 50 kinds of consumed livestock products. A quantitative survey was performed by trained interviewers in face-to-face interviews with 1,500 adults aged over 19, who were randomly selected from seven major provinces in Korea. Respondents received a picture of one serving size for each of the 50 livestock products, including meats, processed meat products, milk and dairy products, and eggs and processed egg products. A t-test and general linear model were carried out using SPSS statistics. The most important factor affecting consumption of livestock products was residence area. The most frequently consumed food was milk (2.6 times/week), followed by pork (1.4 times/week), liquid yogurt (1.3 times/week), rolled omelet (1.2 times/week), semisolid yogurt (1.0 times/week), steamed egg (1.0 times/week), ice cream (0.9 times/week), chicken (0.8 times/week), low fat milk (0.7 times/week), and beef (0.6 times/week). In the case of consumption amount, people living in a city consumed meat (beef, pork, chicken, and duck) 1.5 times more than those living in a village, whereas milk and dairy products and eggs and processed egg products were consumed more frequently by people living in a town. When people eat meat, they consume twice the amount of one serving size. Students consumed livestock and processed livestock products more frequently with greater portions all at once. People living in Seoul, Incheon/Gyeonggi, and Busan/Ulsan/Gyeongnam consumed livestock products more frequently in large amounts. Data from this study can be used for risk assessment of livestock and processed livestock products as well as education for safe consumption of livestock products.

• The Journal of Korean Academy of Prosthodontics
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• v.57 no.1
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• pp.8-17
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• 2019

Purpose: The study analyzed the prevalence of peri-implantitis and factors which may have affected the disease. Materials and methods: This study based on medical records and radiographs of 422 patients (853 implant cases) who visited Ewha Womans University Mokdong Hospital Dental Center from January 1, 2012 to December 31, 2016. Generalized estimation equations (GEE) was utilized to determine the statistical relationship between peri-implantitis and each element, and the cumulative prevalence of peri-implantitis during the observation period was obtained by using the Kaplan Meier Method. Results: The prevalence rate of peri-implantitis at the patient level resulted in 7.3% (31 patients out of a total of 422 patients), and at the implant level 5.5% (47 implants out of a total of 853 implants). Sex, GBR, guided bone regeneration (GBR) and functional loading periods had statistical significance with the occurrence of peri-implantitis. Upon analysis of the cumulative prevalence of peri-implantitis in terms of implant follow-up period, the first case of peri-implantitis occurred at 9 months after the placement of an implant, and the prevalence of peri-implantitis showed a non-linear rise over time without a hint of a critical point. Conclusion: The prevalence of peri-implantitis at the patient level and the implant were 7.3% and 5.5%, respectively. Male, implant installed with GBR and longer Functional Loading Periods were related with the risk of peri-implantitis.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.

• Food Engineering Progress
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• v.14 no.4
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• pp.307-315
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• 2010

The safety and security of food supply should be one of the primary responsibilities of any government. Estimation of nation's food commodity intakes is important to control the potential risks in food systems since food hazards are often associated with quality and safety of food commodities. The food intake databases provided by Korea National Health and Nutrition Examination Survey (KNHANES) are good resources to estimate the demographic data of intakes of various food commodities. A limitation of the KNHANES databases, however, is that the food intakes surveyed are not based on commodities but ingredients and their mixtures. In this study, reasonable calculation strategies were applied to convert the food intakes of the ingredients mixtures from the KNHANES into food commodity intakes. For example, Perilla leaf consumed with meat, raw fish, and etc. in Korean diets was used to estimate its Korean intakes and develop algorithms for demographic analysis. Koreans have consumed raw, blanched, steamed, and canned perilla leaf products. The average daily intakes of the perilla leaf were analyzed demographically, for examples, the intakes by gender, age, and etc. The average daily intakes of total perilla leaf were 2.03${\pm}$0.27 g in 1998, 2.11${\pm}$0.26 g in 2001, 2.29${\pm}$0.27 g in 2005, 2.75${\pm}$0.35 g in 2007, and 2.27${\pm}$0.20 g in 2008. Generally, people equal to or over 20 years of age have shown higher perilla leaf intakes than people below 20. This study would be contributed to the estimation of intakes of possible chemical contaminants such as residual pesticides and subsequent analysis for their potential risk.

• Analytical Science and Technology
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• v.18 no.5
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• pp.419-424
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• 2005

In recent years, dioxins which were designated as persistent organic pollutants and endocrine disrupters are treated as substance of environmental pollution and studied about human health risk assessment, emission pollutants estimation, analytical methods and so on. It is easy that dioxins are accumulated to soil because of the atmosphere circulation of burning up the waste. This is the comparative studies on the distribution relationship of dioxin isomers in exhausted gas of industrial waste and urban waste incinerators, ambient air and soil. A basis of PCDDs and PCDFs based on OCDD was drawn up to the curve and they correspond to dioxin isomers in exhausted gas of industrial waste and urban waste incinerators and ambient air. On comparing these results, It was found that the ambient air and exhausted gas of industrial waste incinerators were very similar in curve and ratio. Consequently, environmental by exposed dioxin depends on the exhausted gas of industrial waste incinerators than urban waste incinerators. In case of soil, even though we can not completely rule out the possibility of pollution source bring on pesticide and other factors, and naturally biological dissociations, the curve shape is very similar to exhausted gas of industrial waste incinerators and ambient air. So, we inform here that it was mainly caused by these environmental factors.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.67-77
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• 2010

Growth of oil and chemical industries has been remarkable during recent years. Hazardous materials (Hazmat) make frequent use in the wide range of industries. It increases the frequency of Hazmat transport and it leads to increase the number of accidents. Optimal Hazmat routes can reduce damage. Thus, the objective of this study is to minimize the areas impacted by Hazmat accidents by adopting experts' opinion in planning the route. We calculated weights using AHP (Analytic Hierarchy Process) and deduced the best route by applying this weights. Results showed that in the case of shortest route versus weighted route, the percentage of population damage has been decreased by 33.4% in the comparison between shortest route and optimally weighted route. And the percentage of environmental damage also has been decreased by 21.8%. Social damage has been decreased by 1521.7%. In the case of none weighted route versus weighted route, the percentage of population damage has been decreased by 2.6% when we adopted weighted route. Consequently, the recommended route with weighted risk assessment avoids densely populated area comparing with none weighted route. Further research needs to be carried out in order to figure out the specific cost-effectiveness analysis applying the equal cost unit for each factor.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.93-101
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• 2017

The distribution of inter-annual variation in temperature would help evaluate the likelihood of a climatic risk and assess suitable zones of crops under climate change. In this study, we evaluated two methods to estimate the standard deviation of temperature in the areas where weather information is limited. We calculated the monthly standard deviation of temperature by collecting temperature at 0600 and 1500 local standard time from 10 automated weather stations (AWS). These weather stations were installed in the range of 8 to 1,073m above sea level within a mountainous catchment for 2011-2015. The observed values were compared with estimates, which were calculated using a geospatial correction scheme to derive the site-specific temperature. Those estimates explained 88 and 86% of the temperature variations at 0600 and 1500 LST, respectively. However, it often underestimated the temperatures. In the spring and fall, it tended to had different variance (e.g., increasing or decreasing pattern) from lower to higher elevation with the observed values. A regression analysis was also conducted to quantify the relationship between the standard deviation in temperature and the topography. The regression equation explained a relatively large variation of the monthly standard deviation when lapse-rate corrected temperature, basic topographical variables (e.g., slope, and aspect) and topographical variables related to temperature (e.g., thermal belt, cold air drainage, and brightness index) were used. The coefficient of determination for the regression analysis ranged between 0.46 and 0.98. It was expected that the regression model could account for 70% of the spatial variation of the standard deviation when the monthly standard deviation was predicted by using the minimum-maximum effective range of topographical variables for the area.