• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.4
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• pp.187-194
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• 2008

This paper proposes an effective countermeasure to an intrinsic hardware vulnerability of the keyboard controller that causes sniffing problem on the password authentication system based on the keyboard input string. Through the vulnerability, some possible attacker is able to snoop whole the password string input from the keyboard even when any of the existing keyboard protection software is running. However, it will be impossible for attackers to gather the exact password strings if the proposed policy is applied to the authentication system though they can sniff the keyboard hardware protocol. It is expected that people can use secure Internet commerce after implementing and applying the proposed policy to the real environment.

• The Korean Journal of Applied Statistics
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• v.36 no.6
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• pp.529-545
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• 2023

This paper introduces the Banded-VHAR model suitable for high-dimensional long-memory time series with band structure. The Banded-VHAR model has nonignorable correlations only with adjacent dimensions due to data features, for example, geographical information. Row-wise estimation method is adapted for fast computation. Also, two estimation methods, namely BIC and ratio methods, are proposed to estimate the width of band. We demonstrate asymptotic consistency of our proposed estimation methods through simulation study. Real data applications to pm2.5 and apartment trading volume substantiate that our Banded-VHAR model outperforms traditional sparse VHAR model in forecasting and easy to interpret model coefficients.

• The Journal of Society for e-Business Studies
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• v.4 no.3
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• pp.25-42
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• 1999

As todays manufacturers and business organizations are struggling to compete in the global marketplace, they are concentrating on the efficient use of numerous information on design, development production, testing, distribution, and maintenance of products throughout their whole life cycles. To meet these organizations demands on information integration, the CALS has been recently focused as a dominant philosophy. In this paper, we introduce the computer supports for engineering CALS in which the engineering process at an initial phase of product development is simultaneously and collaboratively peformed. The proposed system supports the following functions: a virtual prototyping, a distributed collaborative design, and engineering information management. We have conformed to CORBA (Common Object Request Broker Architecture) standard to support interoperability between distributed objects and have used JAVA to support cross-platform and distributed user access to the system on the Web. Under this system, multidisciplinary design teams in engineering CALS environment can collaboratively perform their tasks, share design information and communicate with each other on the Web.

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.63-76
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• 2020

In the 21st century, informatization is playing a huge role in people's lives. Korea is experiencing the tremendous changes in social structure and lifestyle caused by informatization. This paper focuses on economic phenomena rather than discussion on social structure due to informatization. We check whether the Goodwin model, which can comprehensively express economic growth, economic cycle, and income distribution, is suitable for the Korean economy in the information age. This model is simulated by selecting a quantitative economic methodology that estimates coefficients from time series data of the Korean economy. The simulation results confirmed that the Goodwin model is suitable for analyzing functional income distribution in Korea.

• The Journal of Society for e-Business Studies
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• v.11 no.3
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• pp.89-108
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• 2006

This study is to survey on the status of human resource training programs related to ubiquitous technologies and services of domestic universities. So, this study develop a classification system about human resource related to ubiquitous technologies and services. We propose the implications and plans which are based on the status of human resource training programs related to ubiquitous technologies and services. Human resources related to ubiquitous technology are classified by the flow of information in ubiquitous environment. And human resources related to ubiquitous service are classified by ubiquitous user view. This study can be used to find collaboration alternatives for breeding up ubiquitous human resources and referred to analyzing on the supply and demand of ubiquotous human resources.

• The Korean Journal of Financial Management
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• v.24 no.4
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• pp.107-134
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• 2007

This paper tests the relationship among returns, volatilities, contracts and open interests of KOSPI 200 futures markets with the various dynamic models such as granger-causality, impulse response, variance decomposition and ARMA(1, 1)-GJR-GARCH(1, 1)-M. The sample period is from July 7, 1998 to December 29, 2005. The main empirical results are as follows; First, both contract change and open interest change of KOSPI 200 futures market tend to lead the returns of that according to the results of granger-causality, impulse response and variance decomposition with VAR. These results are likely to support the KOSPI 200 futures market seems to be inefficient with rejecting the hypothesis 1. Second, we also find that the returns and volatilities of the KOSPI 200 futures market are effected by both contract change and open interest change of that due to the results of ARMA(1,1)-GJR-GARCH(1,1)-M. These results also reject the hypothesis 1 and 2 suggesting the evidences of inefficiency of the KOSPI 200 futures market. Third, the study shows the asymmetric information effects among the variables. In addition, we can find the feedback relationship between the contract change and open interest change of KOSPI 200 futures market.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.2
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• pp.155-163
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• 2014

At gas stations, liquid fuels expand and contract in volume owing to temperature variations. In Korea, the ambient temperature varies between $-15^{\circ}C$ in winter and $35^{\circ}C$ in summer. The volume expansion coefficients of liquid fuels are about $0.1%/^{\circ}C$. To investigate this issue, we measured daily changes in fuel temperature and the delivered fuel temperature at gas stations. In addition, we scrutinized the daily, monthly, and annual changes in temperature over past 50 years in Korea. The results show that the temperature of the fuel in the storage tank was maintained at a stable value(summer or winter). Many factors, such as the surrounding conditions, fuel filling frequency, and gas station location, influence the delivered fuel temperature. The results of this study can be applied for establishing a national regulation and will contribute to fair transactions.

• Journal of IKEEE
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• v.23 no.3
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• pp.852-857
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• 2019

In order to manage the demand resources of project participants and to provide appropriate strategies in the virtual power plant's power trading platform for consumers or operators who want to participate in the distributed resource collective trading market, it is very important to forecast the next day's demand of individual participants and the overall system's electricity demand. This paper developed a power demand forecasting model for the next day. For the model, we used LSTM algorithm of deep learning technique in consideration of time series characteristics of power demand forecasting data, and new scheme is applied by applying one-hot encoding method to input/output values such as power demand. In the performance evaluation for comparing the general DNN with our LSTM forecasting model, both model showed 4.50 and 1.89 of root mean square error, respectively, and our LSTM model showed high prediction accuracy.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.10
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• pp.126-133
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• 2007

This paper proposes information technology based data mining to forecast short term power demand. A time-series analyses have been applied to power demand forecasting, but this method needs not only heavy computational calculation but also large amount of coefficient data. Therefore, it is hard to analyze data in fast way. To overcome time consuming process, the author take advantage of universally easily available information technology based data-mining technique to analyze patterns of days and special days(holidays, etc.). This technique consists of two steps, one is constructing decision tree, the other is estimating and forecasting power flow using decision tree analysis. To validate the efficiency, the author compares the estimated demand with real demand from the Korea Power Exchange.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.785-799
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• 2018

With the development of renewable energy sector, the importance of solar energy is continuously increasing. Solar radiation forecasting is essential to accurately solar power generation forecasting. In this paper, we used time series models (ARIMA, ARIMAX, seasonal ARIMA, seasonal ARIMAX, ARIMA GARCH, ARIMAX-GARCH, seasonal ARIMA-GARCH, seasonal ARIMAX-GARCH). We compared the performance of the models using mean absolute error and root mean square error. According to the performance of the models without exogenous variables, the Seasonal ARIMA-GARCH model showed better performance model considering the problem of heteroscedasticity. However, when the exogenous variables were considered, the ARIMAX model showed the best forecasting accuracy.