• Management Science and Financial Engineering
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• v.9 no.1
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• pp.29-49
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• 2003

This paper develops channel reallocation methodologies for survival transmission networks, Any failure on a high-speed telecommunication network needs to be restored rapidly and a channel real-location methodology has an important role for the fast restoration. This paper considers the channel reallocation problems under a line restoration with distributed control, where the line restoration restores the failed channels by rerouting the channels along the two alternative routes. The objective is to determine the optimal number of rerouting channels on the alternative rerouting paths of a given transmission network, where the optimality criteria are the first, the last and the mean restoration times. For each criterion, the problem is formulated as a mixed integer programming and the optimal channel reallocation algorithm is suggested based upon the characterization of the optimal solution.

• Journal of Environmental Science International
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• v.13 no.10
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• pp.863-870
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• 2004

The main objectives of this research are to analyse and evaluate the demolishing walls initiative in Daegu city as the collaborative urban environment improvement initiative in South Korea using the actor network theory concept. Local authorities are unable to effectively and efficiently improve urban environment because of their limited statutory and financial powers. This inability crucially led to the formation of the demolishing walls initiative in Daegu city with building a coalition of the local people, interest groups and public and non-governmental organisations in the operational processes in order to improve the physical and social urban environments. Furthermore, co-ordination between local authorities and landscape architecture specialists not only to change the way in which they tackle urban environmental problems but also to make the local people aware of their potential ability in positively improving the urban environment.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.489-497
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• 2000

After IMF situation, the money market environment is changing rapidly. Therefore, many companies including financial institutions and many individual investors are concerned about forecasting the money market, and they make an effort to insure the various profit and hedge methods using derivatives like option, futures and swap. In this research, we developed a prototype of forecasting system for KOSPI 200 option, especially call option, trading using artificial neural networks(ANN), To avoid the overfitting problem and the problem involved int the choice of ANN structure and parameters, we employed the ANN ensemble approach. We conducted two types of simulation. One is conducted with the hold signals taken into account, and the other is conducted without hold signals. Even though our models show low accuracy for the sample set extracted from the data collected in the early stage of IMF situation, they perform better in terms of profit and stability than the model that uses only the theoretical price.

• Asia pacific journal of information systems
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• v.11 no.4
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• pp.99-111
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• 2001

The prediction of stock price index is a very difficult problem because of the complexity of stock market data. It has been studied by a number of researchers since they strongly affect other economic and financial parameters. The movement of stock price index has a series of change points due to the strategies of institutional investors. This study presents a two-stage forecasting model of stock price index using change-point detection and artificial neural networks. The basic concept of this proposed model is to obtain intervals divided by change points, to identify them as change-point groups, and to use them in stock price index forecasting. First, the proposed model tries to detect successive change points in stock price index. Then, the model forecasts the change-point group with the backpropagation neural network(BPN). Finally, the model forecasts the output with BPN. This study then examines the predictability of the integrated neural network model for stock price index forecasting using change-point detection.

• Proceedings of the KIEE Conference
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• summer
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• pp.105-106
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• 2004

This paper explains a network for various participants of the electricity market to make bids on the power exchange. The power exchange accepts bids for various markets such as day-ahead, realtime, and financial over this interface. It exists on the IT plane of the market hierarchy and the participants are able to access it over the internet.

• International Journal of Advanced Culture Technology
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• v.7 no.3
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• pp.58-64
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• 2019

Background: Communication is important for the elderly to maintain existing social relationships while creating new relationships based on good communication skills to lessen psychological and emotional distress and lead a healthy life in advanced age. Aims: This study identifies the difference between the social network-based quality of communication life and the overall quality of life in the elderly and how much the quality of communication life affects the overall quality of life. Methods: This research includes a survey of the elderly aged 65 and over living in small cities of South Korea. Data sets of 201 elderly were analyzed. Results: This study found a significant correlation between the quality of communication life and the overall quality of life. Religion also influences the elderly's quality of communication life. The elderly's quality of communication life has 40% explanatory power of the overall quality of life. Conclusion: Consequently, senior citizens' quality of life will be improved through the enhanced quality of communication in addition to financial and health conditions by participating in various community activities similar to those provided by religion to increase opportunities for communication.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.10-14
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• 2019

The number of security incidents is increasing as the Internet of Things(IoT) is distributed widely. The security incidents of IoT can cause financial damages. Moreover, It can become direct threats to humans. In order to prevent these problems, the security installation for IoT devices is important. This paper describes the definition of IoT devices, security incident case, architecture, and the security threats that can occur when a device is connected to network without security installation.

• Journal of the Korean Physical Society
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• v.73 no.10
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• pp.1431-1436
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• 2018

We study the scaling of the price fluctuation in the Korean housing market. From the numerical analysis, we show that the normalized return distribution of the housing price, P(r), has a fat-tail and is well approximated by a power-law, $P(r){\sim}r^{-({\alpha}+1)}$, with ${\alpha}{\simeq}3$ for the whole data set. However, if we divide the data into groups based on the trading patterns, then the value of ${\alpha}$ for positive tail and negative tail can be different depending on the trading patterns. We also find that the autocorrelation function of the housing price decays much slower than that of the stock exchange markets, which shows a unique feature of the housing market distinguished from the other financial systems.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.93-102
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• 2021

This paper aims to study the influence of environmental attitudes on the choice of non-professional investors. It highlights the role of environmental performance assurance on investment judgments. This choice is due to the motivation and importance that investors place on the disclosure of environmental information. The main purpose of the research is focused on the empirical approach justified by the use of a questionnaire addressed to 200 non-professional investors. The results show that attitudes towards the environment do not correlate with the importance that gives this category of investors to the environmental information.. Subsequently, the results prove that the disclosure of an environmental assurance report has a positive impact on investment judgments independently of their appreciation of the environmental information concerning that of financial order.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.185-192
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• 2022

Forecasting and time series modelling plays a vital role in the data analysis process. Time Series is widely used in analytics & data science. Forecasting stock prices is a popular and important topic in financial and academic studies. A stock market is an unregulated place for forecasting due to the absence of essential rules for estimating or predicting a stock price in the stock market. Therefore, predicting stock prices is a time-series problem and challenging. Machine learning has many methods and applications instrumental in implementing stock price forecasting, such as technical analysis, fundamental analysis, time series analysis, statistical analysis. This paper will discuss implementing the stock price, forecasting, and research using prophet and LSTM models. This process and task are very complex and involve uncertainty. Although the stock price never is predicted due to its ambiguous field, this paper aims to apply the concept of forecasting and data analysis to predict stocks.