• Journal of the Korea Institute of Building Construction
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• v.10 no.2
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• pp.75-80
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• 2010

With the intensifying of price competition and structural diversifications, the uncertainty of the domestic housing market has been increased. This highlights the importance of the planning stage of construction projects, and the increased need for a higher level of accuracy in approximate estimates. Currently, a number of research and development programs to calculate construction cost at the initial planning stage are being conducted. However, there are few cases in which local characteristics are considered in deriving the results. If local calibration can be conducted during estimates, more accurate cost estimates will be enabled. This could also play a major role in ensuring the success of a project. Therefore, the purpose of this research is to develop a calculation methodology and a model for a local index based on the historical data of public apartment buildings, and to derive a local index that supports accurate construction cost estimates.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.461-475
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• 2021

Hidden Markov model (HMM) is a statistical model in which the system consists of two elements, hidden states and observable results. HMM has been actively used in various fields, especially for time series data in the financial sector, since it has a variety of mathematical structures. Based on the HMM theory, this research is intended to apply the domestic KOSPI200 stock index as well as the prediction of global stock indexes such as NIKKEI225, HSI, S&P500 and FTSE100. In addition, we would like to compare and examine the differences in results between the HMM and support vector regression (SVR), which is frequently used to predict the stock price, due to recent developments in the artificial intelligence sector.

• Korean Journal of Community Nutrition
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• v.29 no.1
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• pp.34-50
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• 2024

Objectives: Transformation through a sustainable food system to provide healthy diets is essential for enhancing both human and planetary health. This study aimed to explain about sustainable diets and illustrate appropriate measurement of adherence to sustainable diets using a pre-existing index. Methods: For literature review, we used PubMed and Google Scholar databases by combining the search terms "development," "validation," "sustainable diet," "sustainable diet index," "planetary healthy diet," "EAT-Lancet diet," and "EAT-Lancet reference diet." For data presentation, we used data from National Health and Nutrition Examination Survey, 2017-2018, among adults aged 20 years and older (n = 3,920). Sustainable Diet Index-US (SDI-US), comprising four sub-indices corresponding to four dimensions of sustainable diets (nutritional quality, environmental impacts, affordability, and sociocultural practices), was calculated using data from 24-hour dietary recall interview, food expenditures, and food choices. A higher SDI-US score indicated greater adherence to sustainable diets (range: 4-20). This study also presented SDI-US scores according to the sociodemographic status. All analyses accounted for a complex survey design. Results: Of 148 papers, 16 were reviewed. Adherence to sustainable diets fell into 3 categories: EAT-Lancet reference diet-based (n = 8), Food and Agriculture Organization (FAO) definition-based (n = 4), and no specific guidelines but including the sustainability concept (n = 4). Importantly, FAO definition emphasizes on equal importance of four dimensions of diet (nutrition and health, economic, social and cultural, and environmental). The mean SDI-US score was 13 out of 20 points, and was higher in older, female, and highly educated adults than in their counterparts. Conclusions: This study highlighted that sustainable diets should be assessed using a multidimensional approach because of their complex nature. Currently, SDI can be a good option for operationalizing multidimensional sustainable diets. It is necessary to develop a Korean version of SDI through additional data collection, including environmental impact of food, food price, food budget, and use of ready-made products.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.352-361
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• 2013

The purpose of this study is to analyse the impact of macroeconomic and non-macroeconomic forces on the management performance of the air transport firms and offer the useful information to the managers. To conduct the regression analysis, eight macroeconomic and non-macroeconomic variables were selected individually as an independent variable. Macroeconomic variables were the return of corporate bond, West Texas Intermediate, the unemployment rate, the money supply, the trade balance, the won to USD exchange rate, the consumer price index and the index of industrial production. And non-macroeconomic variables were Taiwan earthquake, the Asian economic crisis, the 911 terrorist attacks in the US, the Iraq war, Beijing Olympic, the outbreak of a swine flu epidemic, the 1st presidential election and the 2nd presidential election. And ROA was selected as a dependent variable. As the result of analysis, it was found that the changing rates of won to USD exchange rate and consumer price index affected the changing rate of ROA significantly. And also as the result of analysing the impact of two significant macroeconomic variables and eight non-macroeconomic variables on the changing rate of ROA, it was found that the Asian economic crisis and the outbreak of a swine flu epidemic had a negative impact on it. Therefore managers should take note of a change in macroeconomic and non-macroeconomic variables carefully to improve the management performance.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.133-141
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• 2021

Governments of each country are actively implementing fiscal expansion policies to recover the real economy after Corona 19. In Korea, the stock market and housing market are greatly affected as liquidity in the market increases due to the implementation of disaster subsidies and welfare policies. The purpose of this study is to analyze the relationship between stock market and housing market trends and liquidity. Data were collected by the Bank of Korea and Kookmin Bank. The analysis period is from January 2000 to December 2020, and monthly data are used. For empirical analysis, the rate of change from the same month of the previous year was calculated for each variable, and numerical analysis, index analysis, and model analysis were performed. As a result of the analysis, it was found that the stock index showed a positive(+) relationship with the house price, while a negative(-) relationship with M2. Previous studies have suggested that, in general, an increase in liquidity affects the stock market and the housing market, and inflation also rises. In this study, it was found that the stock market and the housing market had an effect on each other. However, it was investigated that liquidity showed an inverse relationship with the stock market and had no relationship with the housing market. Through this, this study estimated that there is a time difference in the relationship between liquidity and the stock market & housing market.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1423-1431
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• 2022

Volatility is one of the variables that the Black-Scholes model requires for option pricing. It is an unknown variable at the present time, however, since the option price can be observed in the market, implied volatility can be derived from the price of an option at any given point in time and can represent the market's expectation of future volatility. Although volatility in the Black-Scholes model is constant, when calculating implied volatility, it is common to observe a volatility smile which shows that the implied volatility is different depending on the strike prices. We implement supervised learning to target implied volatility by adding V-KOSPI to ease volatility smile. We examine the estimation performance of KOSPI200 index options' implied volatility using various Machine Learning algorithms such as Linear Regression, Tree, Support Vector Machine, KNN and Deep Neural Network. The training accuracy was the highest(99.9%) in Decision Tree model and test accuracy was the highest(96.9%) in Random Forest model.

• Journal of Korean Society of Forest Science
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• v.79 no.2
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• pp.187-195
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• 1990

The following conclusions have been obtained with special reference to the walnut marketing system in Cheonwongun districts 1. The marketing channel of walnut in the producing areas was mainly depended on the individual selling by 89.58%. and sale through farmer's coops and forest owner's association by 10.42%, and share of walnut through fatmer's coops was 84.58%. 2. The market structure in assembling stage of walnut can be represented as oligopoly considering the market share of 86.26% derived by CR3 method. 3. Direct selling from producers to consumers would be recommendable to reduce marketing margin considering the 77.20% of sale's dependency on assembler-commisioner. 4. Two major reasons to follow the marketing channel of assembler-commissioner were the convieniency (45.00%) and dealing with small quantity of walnut (20.00%). Let the walnut producers follow the institutional marketing channels such as farmer's coops and forest owner s association, special actions including better conveniency, smaller quantity and the procedures should be improved. 5. Farmer's share of walnut was estimated as 54.93% and total marketing margin was 45.0% of which 36.70% destined to the retail stage. 6. The price index in November was the lowest(83.63) due to the flood and hunger sale and the index in April was the highest(115.74). To cope with the severe price fluctuation and to stabilize seasonal walnut price, sale's in advance, credit supply and provision of storage facilities must be considered in policy-making decision for forest farmers.

• The Korean Journal of Applied Statistics
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• v.23 no.1
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• pp.63-71
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• 2010

Business entrepreneurs reflect their views of domestic and foreign economic activities on their operation for the growth of their business. The decision, forecasting, and planning based on their economic sentiment affect business operation such as production, investment, and hiring and consequently affect condition of national economy. Business survey index(BSI) is compiled to get the information of business entrepreneurs' economic sentiment for the analysis of business condition. BSI has been used as an important variable in the short-term forecasting models for business cycle analysis, especially during the the period of extreme business fluctuations. Recent financial crisis has arised extreme business fluctuations similar to those caused by currency crisis at the end of 1997, and brought back the importance of BSI as a variable for the economic forecasting. In this paper, the meaning of BSI as an economic sentiment index is reviewed and a GUIDE regression tree is constructed to find out the factors which affect on BSI. The result shows that the variables related to the stability of financial market such as kospi index(Korea composite stock price index) and exchange rate as well as manufacturing operation ratio and consumer goods sales are main factors which affect business entrepreneurs' economic sentiment.

• Journal of the Korean Society of Combustion
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• v.12 no.1
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• pp.38-47
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• 2007

The diversification of import districts of natural gas is trying to prepare an increase in the demand and price. The interchangeability of natural gases should be examined prior to supply to gas appliances, although compositional differences among natural gases are not large. The object of this study is to investigate numerically the thermodynamic and transport properties as well as information on combustion of 6 natural gases. Comparing the properties of BOG1 with those of standard gas, the maximum differences of heating value, Wobbe index, air-fuel ratio, and specific heat are 10%, 4%, 10% and 5.54%, respectively. That is, the BOG1 is required careful application. However, all gases except for BOG1 show the similar properties with standard gas. Finally, the combustion information such as flame temperature and burning velocity are examined. These results will provide the useful information related to the interchangeability of various natural gases in practical combustion appliances.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.251-253
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• 2018

As the prices of agricultural, fishery, and dairy products have been fluctuating due to recent instability on commodity prices, so consumers have been more inclined to make purchase without specific criteria by relying on marketing or their personal experiences and senses of market. The core function of this application is precisely and conveniently telling the consumption index to consumers who are waved by unstable commodity prices by helping users to easily understand the price index of agricultural, fishery, and dairy products in real time using public data. And, it also includes the AI Chatbot and voice recognition function, and meets the convenience of natural language processing and hands-free etc..