• Journal of Semiconductor Engineering
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• v.3 no.1
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• pp.154-160
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• 2022

In this paper, we design a DC-DC boost converter with RF noise immunity to supply a stable positive output voltage for OLED displays. For RF noise immunity, an input voltage variation reduction circuit (IVVRC) is adopted to ensure display quality by reducing the undershoot and overshoot of output voltage. The boost converter for a positive voltage Vpos operates in the SPWM-PWM dual mode and has a dead-time controller using a dead-time detector, resulting in increased power efficiency. A chip was fabricated using a 0.18 um BCDMOS process. Measurement results show that power efficiency is 30% ~ 76% for load current range from 1 mA to 100 mA. The boost converter with the IVVRC has an overshoot of 6 mV and undershoot of 4 mV compared to a boost converter without that circuit with 18 mV and 20 mV, respectively.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.11
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• pp.1571-1574
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• 2014

In this paper, we propose a unidirectional transmission of critical information obtained by keyboard hacking or kernel and keyboard driver hacking even though the computer is not connected to the external network. We show the hacking can be attempted in the proposed method to show the way preventing such attempts in advance. Firewalls and other various methods are used to prevent the hacking from the external network but the hacking is also attempted in various ways to detour the firewall. One of the most effective way preventing from the hacking attack is physically disconnect the internal intranet systems from the external internet and most of the government systems, military systems and big corporate systems are using this way as on one of the protection method. In this paper, we show the feasibility of transmission of security codes, etc via the short message to the external network on the assumption that a hacking program such as Trojan Horse is installed on the computer systems separated from the external network. Previous studies showed that the letters on the monitor can be hijacked by electromagnetic analysis on the computer to obtain the information even though the system is not connected ti the network. Other studies showed that the security code hint can obtained by analyzing the power consumption distribution of CPU. In this paper, the power consumption distribution of externally accessible power line is analyzed to obtain the information and the information can be transmitted to the external network. Software controlling the CPU and GPU usage is designed to control the power supply of computer. The sensors such as the Rogowski coils can be used on the external power line to collect the data of power consumption change rates. To transmit the user password by short message, due to the capacitive components and the obstacle from other power supply, A very slow protocol are used.

• Korean System Dynamics Review
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• v.4 no.2
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• pp.153-171
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• 2003

In this study, we tried to build a model which can deal with the efficient and effective operation of electric power industry, especially focused on the nuclear industry. Here, SD(system Dynamics) approach is used to visualize the underlying phenomenon of the nuclear power industry. SD is a methodology for studying and managing complex feedback systems, such as one finds in business and other social systems, The span of SD applications has grown extensively and now encompasses work in corporate planning and policy design, public management and policy, biological and medical modeling, energy and the environment. Recently, according to the report from KEPCO(Korea Electric Power Corporation), they are considering delaying a new power plant construction. It may be based upon business fluctuation downsized from Korean economic crisis in 1997 and freezing of construction funds due to unstable foreign exchange rate. At this point, we need desperately a kind of strategic model that would contribute to cope with the current business situation, energy generation, Production, and resulting Pollution. Specifically, this model, using SD approach, starts with the detailed drawing of influence diagram, which describes those relevant key points on nuclear power generation systems in electric power industry of Korea. These include such (actors as the operation of nuclear industry and parameters related to the decision making for business policy. Based upon the above-mentioned influence diagram drawn, we developed SD simulation model to evaluate and analyze strategic management of KBPCO. Based on our analysis, we could demonstrate how simulation model can be applied to the real electric power generation in Korea.

• Korean Journal of Construction Engineering and Management
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• v.9 no.1
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• pp.107-117
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• 2008

In this study, surveys and interviews are used to evaluate technological competitiveness of each product with respect to that of foreign leading firms, for seven leading domestic construction products which have been determined to have competitive edge in offshore markets, Such evaluation provides a more in depth study than previously conducted research, and is meaningful in that corporate level, rather than industry level, perspective is projected. Major findings of such evaluations are the following. First, as expected, it has been evaluated that domestic technological competitiveness in desalination plant and power plant has reached the point where it can compete with foreign leading firms. Moreover, a noteworthy result of the evaluation is that development program sector, including urban development of satellite cities, has reached considerable level of competitiveness in offshore market. In the case of the development market, domestic firms have accumulated sufficient experience in domestic market and engineering technology is not a decisive factor as in plant sector, and these factors lead to such an evaluation. Second, in the cases of gas, oil refinery and petro-chemical plants, domestic products' technological competitiveness that can contest in offshore market is still centered around production and construction. On the other hand, there are still weaknesses in license technology and basic design capabilities, which constitute the "value added" area. Third, skyscrapers, a promising product in offshore construction market and a product group which domestic firms have much performance record and projects in progress both in domestic and offshore markets, are considered. While direct comparison between skyscrapers and plant sector is not feasible, with the exception of production and construction, overall domestic capability in this sector has been assessed to be the lowest amongst those products that were surveyed. Fourth, it has been indicated that competitiveness is relatively higher in common technology than in key technology. In project management capability, it has been assessed that there are weaknesses in procedure document area. Also, a characteristic is the point that low overall assessments have been given across all product groups for corporate and management areas, not technological areas. Especially, financing, contracting/claim, risk management and investment on research and development received low evaluations. Fifth, it has been assessed that overall corporate and governmental supports are weak. This result is especially evident for corporate management and support areas across all product groups surveyed.

• Journal of the Korean Electrochemical Society
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• v.12 no.3
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• pp.203-218
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• 2009

The development of lithium-ion battery (LIB) technologies and their application in the field of large-scale power sources, such as electric vehicles (EVs), hybrid EVs, and plug-in EVs require enhanced reliability and superior safety. The main components of LIBs should withstand to the inevitable heating of batteries during high current flow. Carbonate solvents that contribute to the dissociation of lithium salts are volatile and potentially combustible and can lead to the thermal runaway of batteries at any abuse conditions. Recently, an interest in nonflammable materials is greatly growing as a means for improving battery safety. In this review paper, novel approaches are described for designing highly safe electrolytes in detail. Non-flammability of liquid electrolytes and battery safety can be achieved by replacing flammable organic solvents with thermally resistive materials such as flame-retardants, fluorinated organic solvents, and ionic liquids.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.232-241
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• 2019

This study examines one of the conventional and controversial issues in modern finance. Specifically, this study identifies financial determinants of corporate R&D intensity for firms belonging to Korean Chaebols. Empirical estimation procedures are applied to derive more robust results of each hypothesis test. Static panel data, Tobit regression and stepwise regression models are employed to obtain significant financial factors of R&D expenditures, while logit, probit and complementary log-log regression models are used to detect financial differences between Chaebol firms and their counterparts not classified as Chaebols. Study results found the level of R&D intensity in the prior fiscal year, market-value based leverage ratio and firm size empirically showed their significance to account for corporate R&D intensity in the first hypothesis test, whereas the majority of explanatory variables had important power on a relative basis. Assuming that the current circumstances in the domestic capital market may necessitate gradual changes of Korean Chaebols in terms of their socio-economic function, the results of this study are expected to contribute to identifying financial antecedents that can be beneficial to attain optimal level of corporate R&D expenditures for Chaebol firms on a virtuous cycle.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.5
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• pp.352-362
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• 2019

The study investigates one of the long-standing, but still controversial issues in modern finance from the international and domestic perspectives. That is, financial components and differences on corporate profitability are identified and compared under the primary hypotheses. Empirical research settings include the sample data as KOSPI-listed chaebol firms, time reference covering the post-era of the global financial turmoil and two differently defined profitability indices measured by the market- and the book-value bases. A majority of total 7 explanatory variables except firm size and leverage ratio reveal their statistically significant power to explain profitability indices for the chaebol firms in the first hypothesis. The results are generally compatible with those obtained from their counterparts of non-chaebol firms. In the second hypothesis applying multinomial logistic model, the chaebol firms are classified into three groups according to the level of profitability. It is then confirmed that variables to represent the market-valued debt ratio, business risk and growth potential are financially discriminating factors among the three groups. The study may provide a new vision to identify financial factors of corporate profitability for Korean chaebol firms after the global financial crisis, which can enhance the benefits of interested parties at the government or corporate level in a virtuous cycle.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.2
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• pp.99-109
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• 2001

In this study, we tried to build a model which can deal with the efficient and effective operation of electric power industry, especially focused on the nuclear industry. Here, SD (System Dynamics) approach is used to visualize the underlying phenomenon of the nuclear power industry. SD is a methodology for studying and managing complex feedback systems, such as one finds in business and other social systems. The spend of SD applications has grown extensively and now encompasses work in corporate planning and policy design, public management and policy, biological and medical modeling, energy and the environment. Recently, according to the report from KEPCO (Korea Electric Power Corporation), they are considering delaying a new power plant construction. It may be based upon business fluctuation downsized from Korean economic crisis in 1997 and freezing of construction funds due to unstable foreign exchange rate. At this point, we need disparately a kind of strategic model that would contribute to cope with the current business situation, energy generation, production, and resulting pollution. Specifically, this model, using SD approach, starts with the detailed drawing of influence diagram, which describes those relevant key points on nuclear power generation systems in electric power industry of Korea. These include such factors as the operation of nuclear industry and parameters related to the decision making for business policy. Based upon the above-mentioned influence diagram drawn, we developed SD simulation model to evaluate and analyze strategic management of KEPCO. Based on our analysis, we could demonstrate how simulation model can be applied to the real electric power generation in Korea.

• 한국벤처창업학회:학술대회논문집
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• 2006.04a
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• pp.45-75
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• 2006

How much influence does a business plan have on a corporate performance? Whilst previous studies and literatures all assert a strong correlation between the two, very few have actually conducted practical analyses to support that. This study takes an empirical approach in its analysis of Korea' s small and medium-sized enterprises (SME) with the view to finding an answer to the question. A business plan' s components, which have to date been suggested only in theory and in concept, have been selected through the study of literatures and preliminary examination. The selected components were then narrowed down into five factors of productivity, implementation, operational direction, product/service and customer accessibility by applying factor analysis. With which items to measure corporate performance is also an important question as results differ depending on which measurement items were used. For the purpose of this study, corporate performance was classified into effectiveness, adaptability and efficiency to measure how greatly each is influenced by the components of a business plan. Results show that effectiveness and adaptability have a positive (+) influence on corporate performance. The regression model seems to explain effectiveness particularly well. However, different directions of influences were showed in explain power of the research model were not high. And it can be interpreted that implementation of the plan is as important as the establishment of it. Thus a good corporate performance is to be had only under an excellent plan and following an excellent implementation. In most of the companies surveyed, business plans were established regularly led by the intense involvement of the CEO. Such plans were then used in internal operations, such as guiding operational direction and measuring corporate performance. Unlike general expectations, relatively few companies used them in financing from external sources such as banks or venture capitals. These findings are different from previous studies conducted in this field. Also, as market uncertainty was pointed out as the biggest obstacle to business planning. a manager must pay more attention to acquiring external information and knowledge so as to minimize it.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.