• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.99-106
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• 2022

In this paper, we proposes digital content management technology in a cloud computing environment. proposes digital content management technology in a cloud computing environment. Computing services using networks are basic infrastructure services that cannot be missed in the era of the 4th Industrial Revolution. Financial services, digital content services, and industrial and home network services using smartphones are changing from services in the local area to a cloud service environment where the entire service is possible. Therefore, this study proposed a system to safely support digital content services suitable for cloud computing environments. The proposed system provides convenience and safety for users to access the system, protects the copyright of digital content authors, and provides a secure digital content distribution and management system. The purpose of this study is to stabilize and revitalize the digital content market by providing a digital content distribution structure suitable for the cloud computing environment.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.6
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• pp.39-48
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• 2018

Despite the fact that Daejeon has excellent technology infrastructures such as government-funded research institutes, Daedeok Innopolis, and KAIST, the infrastructure for initial investment and growth support for technological start-ups is not sufficient. In particular, the amount of venture capital supply in Daejeon is relatively low compared to other innovation infrastructures. The purpose of this study is to suggest the implications of the venture capital ecosystem in Daejeon area through the analysis of what evolution process has been undergoing and what improvements and complementary points are needed in the future. First, the role of public finance system should be strengthened in order to stimulate angel investment and private capital inflows to start-up companies. Second, in order to cultivate investment professionals in the region, it is necessary to grant local funds to local institutions, and to run investment expert training courses in universities. Third, cooperation between related agencies is needed to add accelerator functions to existing incubators and to foster new accelerators. Fourth, in order to expand the role of local governments, it is necessary to establish funds, to open innovation mindset of public officials, and to communicate effectively with the central government. Fifth, basic venture ecosystem infrastructures such as inflow of excellent manpower, prevention of technology deception, improvement of rechallenge environment should be expanded. Sixth, it is necessary to reorganize the step-by-step start-up financing policy of 'Establishment - Growth - Exit - Rechallenge'. This study is meaningful in that it has grasped the current status of venture start-up financial ecosystem in Daejeon, which is changing rapidly. In particular, it is different in that it identifies financial difficulties venture companies in Daejeon and finds ways to utilize existing financial ecosystem efficiently.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.143-148
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• 2022

The subject of this paper is the practical examples of technoculture that critically thinks network technology, a strong material foundation in the era of data capitalism in the 21st century, and appropriates its socio-cultural metaphor as an artistic potential. In order to analyze its alternatives and the meaning of cultural politics, this paper examines the properties and influence of data capitalism after the 2008 global financial crisis, and the cultural and artistic context formed by its reaction. The first case considered in this paper, Furtherfield's workshop, provided a useful example of how citizens can participate in social change through learning and education in which art and technology are interrelated. The second case, Greek hackerspace HSGR, developed network technology as a tool to overcome the crisis by proposing a new progressive cultural commons due to Greece's financial crisis caused by the global financial crisis and a decrease in the state's creative support. The third case, Paolo Cirio's project, promoted a critical citizenship towards the state and community systems as dominant types of social governance. These technoculture cases can be evaluated as efforts to combine and rediscover progressive political ideology and its artistic realization tradition in the context of cultural politics, paying attention to the possibility of signifying practices of network technology that dominates the contemporary economic system.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.177-192
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• 2016

Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.

• Korean Journal of Human Ecology
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• v.18 no.4
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• pp.841-855
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• 2009

The main objective of this study is to examine the situations of group-homes for the elderly and clarify the problems of them. This study investigates the present conditions of welfare facilities and supply conditions. 4 group-homes were surveyed in Jeonju and Kwangju cities. Data was collected through various ways including the survey conducted by facility operators, the measurement of living space, and photo-takings. The major results of this study are as follows: 1) With the introduction of nursing care insurance in 2008, the increase of the demand and supply to group-home will be expected, due to less cost for recuperation. The care of elderly in homelike atmosphere is effective to the elderly suffering from dementia. Therefore, it is proper that the supply of group-homes for dementia will be needed. 2) Group-homes for the elderly are being supplied under the standards of welfare facilities in the present. Separate supply standards, however, are needed because they are not suitable for small scale group-homes. 3) To supply Group-homes for the elderly on a one-unit basis would cause various problems such as economical unreality, personnel distribution and so on. It is necessary to supply more than two units for more efficient management. 4) The management of group-homes for the elderly is financially unstable because the operating funds heavily depend on the users or people who are connected with the facilities through private networks. Therefore, additional support is needed to settle the financial problem. It would be helpful to build the public networking that provides information about the group-home for the elderly for the public. 5) In case of the increase in the supply of the group-home in a residential area, it could be helpful to promote the group-home to the public. 6) The operators state that the main problems of group homes for the elderly lie in financial difficulties and the shortage of professionals and volunteers. The financial, personnel, and material support for personnel and the supervision of management are required for the transparency and effectiveness of the facility management. In addition, the closer network and cooperation system with the community is required. 7) The present living environments for group-homes for the elderly leave much room for improvement, considering the physical condition of the elderly. The more careful selections in the color, shape, material, and equipment of the facilities should be made for the convenience of the elderly users.

• Journal of Climate Change Research
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• v.9 no.2
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• pp.181-195
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• 2018

On December 12, 2015, the Conference of the Parties to the United Nations Framework Convention on Climate Change (UNFCCC) adopted the Paris Agreement, in which several developed and developing countries all committed to participating in the reduction of greenhouse-gas (GHG) emissions. South Korea has submitted an intended nationally determined contribution (INDC) proposal with a target to cut down 37% greenhouse gas business as usual (BAU) until 2030 in preparation for the 2030 GHG BAU. Under the post-2020 regime, which will be launched from 2021 as the agreement entered into force early, it is expected that efforts to support GHG reduction and adaptation to climate change in developing countries will be accelerated with the utilization of technologies and financial resources of developed countries. South Korea has established the Basic Plan for Climate Change Response and the Basic National Roadmap for Greenhouse Gas Reductions by 2030 to promote the response to climate change at the government level. The Ministry of Science and ICT, as the National Designated Entity designated by the UNFCCC, has come up with middle and long-term strategies for climate technology cooperation. South-Korea has an abundance of energy-consuming industries to support its export-oriented industrial structure; it is thus expected that achieving the GHG reduction target will incur a considerable cost. Moreover, in order to meet the reduction target (11.3%) of the intended nationally determined contribution proposed by South Korea, it is necessary for South Korea to actively promote projects that can achieve GHG reduction achievements, and financial resources are needed as leverage to reduce risks that can occur in the early stages of projects and attract private sector investment. This paper summarizes the theoretical discussions on climate finance and conducted a comparative analysis on the status of the funds related to climate change response in the UK, Germany, Japan and Denmark. Through this, we proposed the legal and policy tasks that should be carried forward to raise public funds that can be used for creation of new industries related to climate change as well as to reduce GHG emissions in South Korea. The Climate Change Countermeasures Act, which has been proposed by the National Assembly of South-Korea, stipulates the establishment of funds but there is no additional funding except for general account. In this regard, it is also possible to take measures such as the introduction of carbon tax or the collection and use of royalties through technology research and development projects for climate change, such as Industrial Technology Innovation Promotion Act. In addition, since funds are used in various fields such as domestic greenhouse gas reduction, technology development, and overseas projects, it is necessary to establish a system in which various ministries cooperate with the operation of the fund.

• Knowledge Management Research
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• v.22 no.4
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• pp.157-172
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• 2021

Information security companies were established in earnest from the mid-late 1990s to early 2000s, far shorter than other national key industries. Nevertheless, the information security industry has made rapid progress. It is expected that the proportion of the information security industry will increase rapidly with the development of advanced technology along with the 4th industrial revolution. As COVID-19, which occurred at the end of 2019, spreads around the world in 2020, non-face-to-face services and digital transformation are accelerating, and cyber threats to users are also increasing. However, there are limitations in responding to new Cyber Security threats due to the shortage of information protection manpower, insufficient security capabilities of domestic companies, and the narrow domestic information protection market. This study examines the external environmental factors of information security companies such as government information protection system operation, government influence, government support, partnership between information security companies, and internal environmental factors such as top management support, financial status, human resources, organizational capability, This study was conducted using empirical data to analyze whether it affects innovation capability and whether organizational capability and innovation capability affect financial and non-financial performance. The results of this study can be used as basic data to suggest policies and implications for information security, and to strengthen the competitiveness of the information security industry.

• KDI Journal of Economic Policy
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• v.30 no.1
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• pp.71-130
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• 2008

Using data from the Korean Labor & Income Panel Study (KLIPS), this study investigates private income transfers in Korea, where adult children have undertaken the most responsibility of supporting their elderly parents without well-established social safety net for the elderly. According to the KLIPS data, three out of five households provided some type of support for their aged parents and two out of five households of the elderly received financial support from their adult children on a regular base. However, the private income transfers in Korea are not enough to alleviate the impact of the fall in the earned income of those who retired and are approaching an age of needing financial assistance from external source. The monthly income of those at least the age of 75, even with the earning of their spouses, is below the staggering amount of 450,000 won, which indicates that the elderly in Korea are at high risk of poverty. In order to analyze microeconomic factors affecting the private income transfers to the elderly parents, the following three samples extracted from the KLIPS data are used: a sample of respondents of age 50 or older with detailed information on their financial status; a five-year household panel sample in which their unobserved family-specific and time-invariant characteristics can be controlled by the fixed-effects model; and a sample of the younger split-off household in which characteristics of both the elderly household and their adult children household can be controlled simultaneously. The results of estimating private income transfer models using these samples can be summarized as follows. First, the dominant motive lies on the children-to-parent altruistic relationship. Additionally, another is based on exchange motive, which is paid to the elderly parents who take care of their grandchildren. Second, the amount of private income transfers has negative correlation with the income of the elderly parents, while being positively correlated with the income of the adult children. However, its income elasticity is not that high. Third, the amount of private income transfers shows a pattern of reaching the highest level when the elderly parents are in the age of 75 years old, following a decreasing pattern thereafter. Fourth, public assistance, such as the National Basic Livelihood Security benefit, appears to crowd out private transfers. Private transfers have fared better than public transfers in alleviating elderly poverty, but the role of public transfers has been increasing rapidly since the welfare expansion after the financial crisis in the late 1990s, so that one of four elderly people depends on public transfers as their main income source in 2003. As of the same year, however, there existed and occupied 12% of the elderly households those who seemed eligible for the National Basic Livelihood benefit but did not receive any public assistance. To remove elderly poverty, government may need to improve welfare delivery system as well as to increase welfare budget for the poor. In the face of persistent elderly poverty and increasing demand for public support for the elderly, which will lead to increasing government debt, welfare policy needs targeting toward the neediest rather than expanding universal benefits that have less effect of income redistribution and heavier cost. Identifying every disadvantaged elderly in dire need for economic support and providing them with the basic livelihood security would be the most important and imminent responsibility that we all should assume to prepare for the growing aged population, and this also should accompany measures to utilize the elderly workforce with enough capability and strong will to work.

• Journal of the Korean Society for Library and Information Science
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• v.7
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• pp.3-67
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• 1980

Because of the changes made in the modes of cataloguing and classification in its long history, the present catalogue of the National Central Library has become complicated and provides an inadequate guide to its collection. There can be no doubt that this is a serious deficiency in a closed access library since materials housed in the library are virtually inaccessible to unskilled readers. The whole breakdown of the efficiency of the catalogue is emminent and will ultimately create the most serious problems for the library. The main purpose of this survey is: (a) to identify problem areas created by the frequent changes in the cataloguing and classifying principles in the library and (b) to grope a rational direction for the future development. Analysing the various classification schemes and cataloguing rules adopted in processing materials (mainly books) in the library, the following conclusions have been made. A. The library adopted five different clasification schemes in different periods, of which KDCP was used for the most part of its collection. KDCP is recommended to use for the future colletion. A classification development office is recommended to be established within the library, of which the main function is to revise the KDCP in collaboration with the appropriate committee of the Korean Library Association. B. The present practice in the library is to apply three different cataloguing rules and two different author notation tables to the Oriental, classical, and Western collections. Efforts should be made to find out an efficient system so that this variety is simplified. An alphabetical index should be added to the classified catalogue, and improvements are required in the Japanese collection. C. The technical services division is inadequately staffed. The staff should be sufficiently numerous and specially qualified. D. The present financial support for the technical services of the library is inadequate. Sufficient financial provision should be made to ensure the effective work. E. A feasibility study should be carried out to develop a computer processing system for providing machine-readable catalogue records on magnetic tape for use by the library community in Korea.