• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.395-397
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• 2010

AWS that exist in Pusan is watching local meteorological phenomena established in place that the weather observatory does not exist by real time, and is used usefully to early input data of numerical weather forecasting model. I wished to display downtown of Pusan and air temperature change of peripheral area using this AWS data. Analyzed volatility using AWS observation data for 5 years to recognize air temperature change of Pusan area through data about temperature among them. Drew air temperature distribution chart by season of recapitulative Pusan area applying IDW linear interpolation with this.

• Journal of Korean Society of Water and Wastewater
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• v.22 no.5
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• pp.523-529
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• 2008

Algal blooms in a local eutrophic lake often produces the musty and earthy taste & odor problems. Since the odor causing compounds(OCCs) including geosmin and 2-MIB have their own volatility, the OCCs can be removed from water by air stripping methods. Removal of TON(threshold odor number) as an index for OCCs could be fitted well with the first order equations($R^2=0.9$ above), where the air stripping coefficient of TON, k was in the range between 0.0055 and 0.0097 according to the aeration time. k within 30min aeration tests was 0.0097, while it was 0.0055 where the aeration time extended to 150min. With 15 mg/L of PAC, removal of TON was not simulated with 1st order equation within 30min aeration. Within 30min aeration, OCCs rather than geosmin and/or 2-MIB could be removed easily by air stripping or PAC adsorption, while OCCs such as geosmin and/or 2-MIB could be removed slowly by air stripping after 30min aeration. Geosmin and 2-MIB were not readily removed by air stripping(k of them were 0.0018~0.0047 and 0.0018~0.0034, respectively at different air flow rates). Geosmin could be removed by air stripping a little better than 2-MIB.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.64-71
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• 2017

Considering the volatility, intermittent and random of photovoltaic (PV) generation systems, accurate forecasting of PV power output is important for the grid scheduling and energy management. In order to improve the accuracy of short-term power forecasting of PV systems, this paper proposes a prediction model based on environmental factors and support vector machine optimized by genetic algorithm (GA-SVM). In order to improve the prediction accuracy of this model, weather conditions are divided into three types, and the gray correlation coefficient algorithm is used to find out a similar day of the predicted day. To avoid parameters optimization into local optima, this paper uses genetic algorithm to optimize SVM parameters. Example verification shows that the prediction accuracy in three types of weather will remain at between 10% -15% and the short-term PV power forecasting model proposed is effective and promising.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2011.04a
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• pp.285-289
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• 2011

he purpose of this study is to assess the effects of real estate policy on apartment price index in Seoul. To meet the research goal, this research reviewed real estate policy of the government from January of 1986 to August of 2010, and then it collected monthly apartment price index in 25 local districts of Seoul from January of 2003 to August of 2010. After 25 districts were grouped into 2 areas (14 districts in Gangnam and 11 districts in Gangbuk), the data of two areas were analyzed by using the SAS program, Cluster analysis with Ward method showed 3 clusters on each area, and with 6 clusters in total, the effects of real estate policy in the period were examined by using residual analysis. The analysis indicated two major shocks (one was from May to October of 2003, and the other was from March of 2006 to January of 2007), and the results showed that the intervention of government in the market had the asymmetric effects in bullish and bearish times. It implies that the market volatility is substantially influenced by irrational sentiments. Thus, it's suggested to devise the consumer sentiment index suitable in real estate market.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.63-74
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• 2020

This study investigates the behavior of foreign investors in the Stock Exchange of Thailand (SET) in the time of coronavirus disease 2019 (COVID-19) as to whether trading is abnormal, what strategy is followed, whether herd behavior is present, and whether the actions destabilize the market. Foreign investors' trading behavior is measured by net buying volume divided by market capitalization, whereas the stock market behavior is measured by logged return on the SET index portfolio. The data are daily from Tuesday, August 28, 2018, to Monday, May 18, 2020. The study extends the conditional-regression model in an event-study framework and extracts the unobserved abnormal trading behavior using the Kalman filtering technique. It then applies vector autoregressions and impulse responses to test for the investors' chosen strategy, herd behavior, and market destabilization. The results show that foreign investors' abnormal trading volume is negative and significant. An analysis of the abnormal trading volume with stock returns reveals that foreign investors are not positive-feedback investors, but rather, they self-herd. Although foreign investors' abnormal trading does not destabilize the market, it induces stock-return volatility of a similar size to normal trade. The methodology is new; the findings are useful for researchers, local authorities, and investors.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.1-9
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• 2021

This paper investigates the impact of the domestic and global outbreak of the coronavirus (COVID-19) pandemic on the trading size of the Malaysian stock (MS) market. The theoretical model posits that stock markets are affected by their response to disasters and events that arise in the international or local environments, as well as to several financial factors such as stock volatility and spread bid-ask prices. Using daily time-series data from 27 January to 12 May 2020, this paper utilizes the traditional Augmented Dickey and Fuller (ADF) technique and Zivot and Andrews with structural break' procedures for a stationarity test analysis, while the autoregressive distributed lag (ARDL) method is applied according to the trading size of the MS market model. The analysis considered almost all 789 listed companies investing in the main stock market of Malaysia. The results confirmed our hypotheses that both the daily growth in the active domestic and global cases of coronavirus (COVID-19) has significant negative effects on the daily trading size of the stock market in Malaysia. Although the COVID-19 has a negative effect on the Malaysian stock market, the findings of this study suggest that the COVID-19 pandemic may have an asymmetric effect on the market.

• Journal of Cadastre & Land InformatiX
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• v.47 no.1
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• pp.143-160
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• 2017

Since officially assessed land price system was introduced, it has functioned as the criterion for establishing and implementing real estate policies. However, there is a controversial issue about the adequacy of the officially assessed land price system. The problem is that it is difficult to establish a statistical model due to too many land characteristics. Also, local economy, macroeconomic environments and development plans are not reflected in the land price evaluation model. Considering longitudinal and cross-sectional variables, a two-way error component panel model was used in this study. This analysis model includes variables reflecting land characteristics, macroeconomic volatility, and development project. The Paju LCD Industrial Complex was selected as a analysis area and an empirical analysis was performed. According to the analysis, the number of significant land characteristic variables were 14(31%) under 5% significance level. Macroeconomic volatility has had an influence on the land price and year variable reflecting development project has consistently been significant since the industrial complex was designated. Therefore, this study suggests that the land price evaluation model should be improved by simplifying land characteristic variables and including macroeconomic and regional economic variables.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.357-368
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• 2018

For well over 100 years, oil has enabled remote communities to generate electricity and enjoy the benefits of a consistent electrical supply. Relying solely on oil for electricity generation has left island and remote communities exposed to several risks and drawbacks. Oil-based electricity generation is often more expensive and subject to price volatility, which can result in the use of risky fuel hedging strategies. The residents of islands and remote communities express concern over the future impacts of climate change or insist on their opinions for the corresponding action with reduction of carbon emissions. These risks and drawbacks can be overcomed with continuing cost reductions in solar, wind, and energy storage technologies by maker. Reducing costs is not always a straightforward process, relying on more diversely and renewably arranged renewable energy sources led to reduced local construction cost in every situation reviewed in this study. In this paper, a convenient and simple design solution which will facilitate the optimum location and transmission route of renewable energy facility using GIS(Geographic Information System) is proposed. The suggested solutions exercised to the case of geomoon island using GIS and identified by local site survey.

• Journal of the Korea Institute of Building Construction
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• v.24 no.2
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• pp.273-284
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• 2024

This study investigates the impact of international oil price fluctuations on overseas construction orders secured by domestic and foreign companies. The analysis employs statistical data spanning the past 20 years, encompassing international oil prices, overseas construction orders from domestic firms, and new overseas construction orders from the top 250 global construction companies. The correlation between these variables is assessed using correlation coefficients(R), determination coefficients(R²), and p-values. The results indicate a strong positive correlation between international oil prices and overseas construction orders. The correlation coefficient between domestic overseas construction orders and oil prices is found to be 0.8 or higher, signifying a significant influence. Similarly, a high correlation coefficient of 0.76 is observed between oil prices and new orders from leading global construction companies. Further analysis reveals a particularly strong correlation between oil prices and overseas construction orders in Asia and the Middle East, potentially due to the prevalence of oil-related projects in these regions. Additionally, a high correlation is observed between oil prices and orders for industrial facilities compared to architectural projects. This suggests an increase in plant construction volumes driven by fluctuations in oil prices. Based on these findings, the study proposes an entry strategy for navigating oil price volatility and maintaining competitiveness in the overseas construction market. Key recommendations include diversifying project locations and supplier bases; utilizing hedging techniques for exchange rate risk management, adapting to local infrastructure and market conditions, establishing local partnerships and securing skilled local labor, implementing technological innovations and digitization at construction sites to enhance productivity and cost reduction The insights gained from this study, coupled with the proposed overseas expansion strategies, offer valuable guidance for mitigating risks in the global construction market and fostering resilience in response to international oil price fluctuations. This approach is expected to strengthen the competitiveness of domestic and foreign construction firms seeking success in the international arena.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.301-309
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• 2020

Defense exports have overgrown in a short period, and items have been diversified with advanced high-end equipment, but exports have been stagnant due to the global economic recession and fierce competition. Weapons importers in the global market are diversified, volatility is higher, and global defense companies are also expanding their global value chain (GVC) By participating in the GVC of a global defense company, the defense SME can grow into a competitive company with specialized technology, rather than participating as a partner of a domestic system company. It is time to prepare an export promotion support plan. In this study, we selected five global companies with high value for the implementation of offset and general considerations on domestic SMEs' entry into the international parts supply chain and related cases, and investigated GVC entry requirements, the current status of cooperation partners, and the perceptions of GVC entry, through local surveys in Korea and overseas. Also, by considering the export target comprehensively, GVC stage, and the level of export competitiveness of domestic SMEs, strategies for promoting GVC participation of defense SMEs and improvements in government policies were derived and presented.