• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.11
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• pp.53-58
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• 2015

Systemic heating and cooling air conditioning systems are popular in various industrial fields and even home. Recently, the rate of supply of this kind of multi-heat pump has been increased under ESCO financing supporting system. Generally the heat pumping system has a structural simplicity and easy installation benefits. and has good running efficiency under normal designed condition. But under extreme climate condition (over $+30^{\circ}C$, under $-10^{\circ}C$), this system exposes abnormal power consumption. It causes high progressive electric power rates and resultant peak power capacity of power plant. In this paper, a novel system concept of buffering refrigerant accumulator and constant pressure control system to relieve peak power load is proposed and this system's utility is verified with an prototype experimental system.

• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.473-481
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• 2010

Forecasting for air demand such as international passengers and freight has been one of the main interests for air industries. This research has mainly focus on the comparison of the performances of the multivariate time series models. In this paper, we used real data such as exchange rates, oil prices and export amounts to predict the future demand on international passenger and freight.

• International Area Studies Review
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• v.15 no.2
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• pp.77-100
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• 2011

The Korean economy have experienced the remarkable decreases in factor prices such as bond yields, real wage since the IMF foreign exchange crisis. This paper investigates the effects of the price changes in the factor markets on determining the level and cyclicality of industrial markups in the manufacturing industry. For this purpose, we construct a markup equation in the small open economy based on the production function including foreign intermediate goods and assuming constant returns to scale technology and AR(1) process of technological coefficient. Empirical results are summarized as the followings. The empirical results shows that the increased markups after the IMF crisis can be explained by the price decreases in the factor markets which result in lowering marginal costs. And we also observed counter cyclicality of markup, labor share and interest rates while real wages, technical coefficients, and production price index proved to be pro-cyclical. In conclusion, the price changes in factor market have contributed to the stickiness in markup fluctuation in the manufacturing industry.

• The Korean Journal of Financial Management
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• v.8 no.2
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• pp.165-208
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• 1991

This paper develops an intertemporal general equilibrium model of asset pricing with taxes under the noisy and the incomplete information structure and examines theoretically the stochastic behavior of general equilibrium asset prices in a one-good, production, and exchange economy in continuous time markets. The important features of the model are its integration of real and financial markets and the analysis of the effects of differential tax rates between ordinary income and capital gains. The model developed here can provide answers to a wide variety of questions about stochastic structure of asset prices and the effect of tax on them.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.64-76
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• 2009

Recently, the ubiquitous environment and the practical technology associated with it become more popular topic along with the rapid development of wireless technologies. The necessity of the automated system based on the ubiquitous environment has been increasing when the concept of the ubiquitous is integrated into the fields of existing IT. Also, the necessity of formulating a power-saving plan on large buildings and public institutions is gathering strength because of a raise in exchange rates and high oil prices. In this paper, to efficiently manage the power consumption of the electronic machine such as electric lights, electric heaters, and air conditioners in a building, power-saving manage- ment system using RFID/USN technologies is proposed. Proposed system controls the electric machine and monitor it's condition by RFID and collects the real time information about the surrounding and the power consumption of the electric machine by USN. Especially, proposed system analyzes the real time information and supports the intelligent scheduler with the best power-saving. Finally, this paper shows the difference between proposed system and existing system and establishes thereality of our system through experiments in variety environments.

• Journal of Soil and Groundwater Environment
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• v.21 no.6
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• pp.179-191
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• 2016

In addition to the measurement of the concentration of soil contaminants, the new idea of indicative parameters was proposed to validate the remedial works through the monitoring for the changes of soil characteristics after applying the clean up technologies. The parameters like CFU (colony forming unit), pH and soil texture were recommended as indicative parameters for land farming. In case of soil washing, water content and the particle size distribution of the sludge were recommended as indicative parameters. The sludge is produced through the particle separation process in soil washing and it is usually treated as a waste. The parameters like water content, organic matter content, CEC (cation exchange capacity) and CFU were recommended as indicative parameters for the low temperature thermal desorption method. Besides the indicative parameter, sampling methods in stock pile and the optimal minimum amount of composite soil sample were proposed. The rates of sampling error in regular grid, zigzag, four bearing, random grid methods were 17.3%, 17.6%, 17.2% and 16.5% respectively. The random grid method showed the minimum sampling error among the 4 kinds of sampling methods although the differences in sampling errors were very little. Therefore the random grid method was recommended as an appropriate sampling method in stock pile. It was not possible to propose a value of optimal minimum amount of composite soil sample based on the real analytical data due to the dynamic variation of $CV_{fund{\cdot}error}$. Instead of this, 355 g of soil was recommended for the optimal minimum amount of composite soil sample under the assumption of ISO 10381-8.

• KDI Journal of Economic Policy
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• v.32 no.3
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• pp.1-32
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• 2010

The global financial crisis has exerted enormous impacts on the attainment of inflation target in Korea. The annual average CPI inflation was 3.3% during the targeting period of 2007-2009 and the target was $3.0{\pm}0.5%$. Thus Korea has succeeded in keeping annual average CPI inflation just below the upper limit of the 2007-2009 target under the global crisis. This paper intends to evaluate the performance of the inflation targeting system in Korea. First, it estimates the conventional call rate reaction equation under the global crisis and finds that the policy interest rates never reacted to expected inflation, output gap, and won/dollar exchange rate, as expected by theory. Second, it identifies the shock of global financial crisis into core and non-core, applying the structural VAR model. The core shock was defined to have no (medium- to) long-run impact on real output. The core shock was identified to have the character of the demand shock, since it has the positive impact on the inflation and output in the short run. The structural core inflation due to core shock was an attractor of headline inflation, not vice versa. Therefore, the structural core inflation that reflects the demand-side shock would be the better intermediate target for the final headline inflation target than the official core inflation that excludes the volatile inflation of agricultural and oil-related products. During the inflation targeting period of 2007-2009, the structural core inflation was more volatile than the official core inflation, because the global crisis has very large negative impacts on the domestic demand as well as the prices of agricultural and oil-related products. This paper shows that the negative core shock during the fourth quarter of 2008 was larger than that in the financial crisis in 1998. But the core shock turned into positive very quickly in 2009, as the Korean economy recovered very quickly from crisis. The volatile changes in structural core inflation suggests that the Bank of Korea barely managed to attain the 2007-2009 inflation target, owing to the very large negative impacts of the global financial crisis on the domestic demand. It also suggests that the rapid rise in core inflation with the rapid recovery of the Korean economy will lead to rapid rise in headline inflation.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.233-253
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• 2014

Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.