• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1960-1965
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• 2005

This paper presents theory for stability analysis and design of a servo system for a MIMO Wiener system with nonlinear uncertainty. The Wiener system consists of a linear time-invariant system(LTI) in cascade with a static nonlinear part ${\psi}$(y) at the output. We assume that the uncertain static nonlinear part is sector bounded and decoupled. In this research, we treat the static nonlinear part as multiplicative uncertainty by dividing the nonlinear part ${\psi}$(y) into ${\phi}$(y) := ${\psi}$(y)-y and y, and then we reduce this stabilizing problem to a Lur'e problem. As a result, we show that the servo system with no steady state error for step references can be constructed for the Wiener system.

• Journal of National Security and Military Science
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• s.8
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• pp.239-270
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• 2010

This thesis is to make an appropriate national defense policy of Republic of Korea through studying the Hegemony Strategy of United States. I searched the theory of hegemony. The hegemony was differently defined by the point of time and region. The strong power nations with the hegemony have been making efforts to maintain their hegemony everytime. I have conclusion that the presence of hegemony once emerged, it brought regional stability in place whether it is coercive or beneficial. The stability and instability of international order IS not exclusively dependent on hegemony. Even if the safety of hegemony cannot guarantee absolute stability of international order, there IS on doubt that the hegemony has enormous impact on that. According to the hegemonic theory, the history of mankind equals to the history of rising and falling hegemony. The international order was changed as the hegemony changes. The United States has been making efforts to maintain her global hegemony during the post cold-war era as well. Taking all these into consideration, relevant military strategy direction able to pursue national interest is that to make up for the relative weakness in the strategic environment. South Korea have to prepare security policy response as following. First, South Korea should build the military force equipped with advanced weapons in military technology sector and solidify military diplomatic relation able to form cooperative relation in wartime. Second, South Korea should make solid Alliance of Korea and U.S. Third, develop and maintain multilateral security cooperation of East Asia. Forth, we could realize that there are means that can neutralize opponent's strong point by seeking one or two and more asymmetry in the aspect of strategy, tactics, and means through asymmetric strategy. Than the military force of South Korea should develop into a force that is able to overcome to the traditional North Korea's threat and new type of conflicts. And the force should have sufficient strength and be deployed to effectively defend the Korean Peninsula. So, we need to establish a denial and defense system against any hostile neighboring country. Therefore, ROK military forces preparing for the future should try to construct a future military power to gradually establish enough strength for self-defense to prepare for a uncertain security environment and when the Korean Peninsula is unified in a future.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.431-444
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• 2023

Purpose - This study applies the traditional Structure-Conduct-Performance (SCP) model from industrial organization theory to investigate the relationship between market structure and performance in China's banking industry. Design/methodology/approach - For analysis, financial data from the People's Bank of China's "China Financial Stability Report" and financial reports of 6 state-owned banks and 11 joint-stock banks for the period 2010 to 2021 were collected to create a balanced panel dataset. The study employs panel fixed-effects regression analysis to assess the impact of changes in market structure and ownership structure on performance variables including return on asset, profitability, costs, and non-performing loan ratios. Findings - Empirical findings highlight significant differences in the effects of market structure between state-owned and joint-stock banks. Notably, increased market competition positively correlates with higher profits for state-owned banks and with lower costs for joint-stock banks. Research implications or Originality - State-owned banks demonstrate larger scale and stability, yet they struggle to respond effectively to market shifts. Conversely, joint-stock banks face challenges in raising profitability against competitive pressures. Additionally, the study emphasizes the importance for Chinese banks to strengthen risk management due to the increase of non-performing loans with competition. The results provide insights into reform policies for Chinese banks regarding the involvement of private sector in the context of market liberalization process in China.

• Steel and Composite Structures
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• v.19 no.5
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• pp.1115-1144
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• 2015

Current climate conditions along with advances in technology make further design and verification methods for structural strength and reliability of wind turbine towers imperative. Along with the growing interest for "green" energy, the wind energy sector has been developed tremendously the past decades. To this end, the improvement of wind turbine towers in terms of structural detailing and performance result in more efficient, durable and robust structures that facilitate their wider application, thus leading to energy harvesting increase. The wind tower industry is set to expand to greater heights than before and tapered steel towers with a circular cross-section are widely used as more capable of carrying heavier loads. The present study focuses on the improvement of the structural response of steel wind turbine towers, by means of internal stiffening. A thorough investigation of the contribution of stiffening rings to the overall structural behavior of the tower is being carried out. These stiffening rings are placed along the tower height to reduce local buckling phenomena, thus increasing the buckling strength of steel wind energy towers and leading the structure to a behavior closer to the one provided by the beam theory. Additionally to ring stiffeners, vertical stiffening schemes are studied to eliminate the presence of short wavelength buckles due to bending. For the purposes of this research, finite element analysis is applied in order to describe and predict in an accurate way the structural response of a model tower stiffened by internal stiffeners. Moreover, a parametric study is being performed in order to investigate the effect of the stiffeners' number to the functionality of the aforementioned stiffening systems and the improved structural behavior of the overall wind converter.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.