• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.4
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• pp.5-22
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• 2013

Institutional repository has been regarded as core facilities of research libraries to realize open access by collecting, preserving, distributing of intellectual asset what institution has created. In our country, many universities and research institutions are trying to introduce institutional repository system. But almost universities not only take the negative attitude to manage properly, but also never give basic training to staff members who take over institutional repository job. This study brightens up the current status of Korean training system and compares the British and Japanese cases what shows diverse advanced managing cases. Furthermore, by putting together demands of hands-on workers, suggest direction of future institutional repository staff training system. First, institutional repository staff training system has to suggest strategies to induce strong support from institution. Second, it has to give not only courses about content collecting and registering, but also practical training. Finally, the program for enhancing system management technology has to be provided, and the place where technical staffs can share their system information mutually has to be provided.

• Journal of KIISE:Software and Applications
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• v.28 no.12
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• pp.885-895
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• 2001

Existing system analysis models suggest various ideas to present entity relations and event flows for consistency between analysis and design paradigms. However, they are preferred to derive and arrange related entities on system flow than to identify entities. To identify entities systematically is a basic and important work of software development, and identified entities can be major assets of business system. In case of business systems the business rules or the computed or derived information like attendance lists of lecture system can be the most important system assets. The management information or meta data are also. In this paper, we suggest a business system analysis models to derive and present entities. System is identified entities, interfaces and event or behaviors through this model then entities are extended to independent entities, dependent entities, which are dependent to independent entities, constraint shows the physical and administrative notices. Various entity identification can reduce the incompleteness of entity analysis.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.157-176
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• 2018

The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.370-378
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• 2020

The Construction Operations Building Information Exchange (COBie) collects and documents a large amount of information from different paths in one place during design and construction projects. This documented information is readily available as a means of continuously transferring data to the facility management systems used by building engineers. In this process, the COBie Worksheet, an open standard form, is used to input the information by simplifying the list required by the user. As a result, COBie was developed to improve dramatically how relevant information is obtained and updated to support operations, maintenance, and asset management at the design and construction stages. On the other hand, to use COBie, a great deal of manual work is required for information linkage and quality inspection with heterogeneous data models. These issues become obstacles to COBie-based facility management system development. This study analyzed the COBie information system and defined the framework for simpler operating maintenance information from BIM (Building Information Modeling). Moreover, the rules for facility management information submission, quality inspection, role definition of framework components, and information linkage were derived. COBie DB schema and support data linkages could be generated effectively based on the proposed framework in prototype development.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.195-220
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• 2018

In this study, we conducted an empirical analysis of the factors that affect the change of Bitcoin Closing Price. Previous studies have focused on the security of the block chain system, the economic ripple effects caused by the cryptocurrency, legal implications and the acceptance to consumer about cryptocurrency. In various area, cryptocurrency was studied and many researcher and people including government, regardless of country, try to utilize cryptocurrency and applicate to its technology. Despite of rapid and dramatic change of cryptocurrencies' price and growth of its effects, empirical study of the factors affecting the price change of cryptocurrency was lack. There were only a few limited studies, business reports and short working paper. Therefore, it is necessary to determine what factors effect on the change of closing Bitcoin price. For analysis, hypotheses were constructed from three dimensions of consumer, industry, and macroeconomics for analysis, and time series data were collected for variables of each dimension. Consumer variables consist of search traffic of Bitcoin, search traffic of bitcoin ban, search traffic of ransomware and search traffic of war. Industry variables were composed GPU vendors' stock price and memory vendors' stock price. Macro-economy variables were contemplated such as U.S. dollar index futures, FOMC policy interest rates, WTI crude oil price. Using above variables, we did times series regression analysis to find relationship between those variables and change of Bitcoin Closing Price. Before the regression analysis to confirm the relationship between change of Bitcoin Closing Price and the other variables, we performed the Unit-root test to verifying the stationary of time series data to avoid spurious regression. Then, using a stationary data, we did the regression analysis. As a result of the analysis, we found that the change of Bitcoin Closing Price has negative effects with search traffic of 'Bitcoin Ban' and US dollar index futures, while change of GPU vendors' stock price and change of WTI crude oil price showed positive effects. In case of 'Bitcoin Ban', it is directly determining the maintenance or abolition of Bitcoin trade, that's why consumer reacted sensitively and effected on change of Bitcoin Closing Price. GPU is raw material of Bitcoin mining. Generally, increasing of companies' stock price means the growth of the sales of those companies' products and services. GPU's demands increases are indirectly reflected to the GPU vendors' stock price. Making an interpretation, a rise in prices of GPU has put a crimp on the mining of Bitcoin. Consequently, GPU vendors' stock price effects on change of Bitcoin Closing Price. And we confirmed U.S. dollar index futures moved in the opposite direction with change of Bitcoin Closing Price. It moved like Gold. Gold was considered as a safe asset to consumers and it means consumer think that Bitcoin is a safe asset. On the other hand, WTI oil price went Bitcoin Closing Price's way. It implies that Bitcoin are regarded to investment asset like raw materials market's product. The variables that were not significant in the analysis were search traffic of bitcoin, search traffic of ransomware, search traffic of war, memory vendor's stock price, FOMC policy interest rates. In search traffic of bitcoin, we judged that interest in Bitcoin did not lead to purchase of Bitcoin. It means search traffic of Bitcoin didn't reflect all of Bitcoin's demand. So, it implies there are some factors that regulate and mediate the Bitcoin purchase. In search traffic of ransomware, it is hard to say concern of ransomware determined the whole Bitcoin demand. Because only a few people damaged by ransomware and the percentage of hackers requiring Bitcoins was low. Also, its information security problem is events not continuous issues. Search traffic of war was not significant. Like stock market, generally it has negative in relation to war, but exceptional case like Gulf war, it moves stakeholders' profits and environment. We think that this is the same case. In memory vendor stock price, this is because memory vendors' flagship products were not VRAM which is essential for Bitcoin supply. In FOMC policy interest rates, when the interest rate is low, the surplus capital is invested in securities such as stocks. But Bitcoin' price fluctuation was large so it is not recognized as an attractive commodity to the consumers. In addition, unlike the stock market, Bitcoin doesn't have any safety policy such as Circuit breakers and Sidecar. Through this study, we verified what factors effect on change of Bitcoin Closing Price, and interpreted why such change happened. In addition, establishing the characteristics of Bitcoin as a safe asset and investment asset, we provide a guide how consumer, financial institution and government organization approach to the cryptocurrency. Moreover, corroborating the factors affecting change of Bitcoin Closing Price, researcher will get some clue and qualification which factors have to be considered in hereafter cryptocurrency study.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.8
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• pp.954-963
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• 2007

As RFID systems are applied to various fields and applications such as supply chain management, asset management, location based applications etc. the requirements becomes diverse. For example, Much higher performance, TCP/IP protocol stack are required in some applications. However, low end processors based systems such as 8051 processor can not meet such requirements due to their low processing capacity and limited size of memory. In this paper a UHF band RFID system which meets the EPC Class-1 Generation-2 specification with ARM920T-based processor is implemented and tested.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.71-82
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• 2021

In this study, a novel method for monitoring road pavements using the Mobile Mapping System (MMS) and a deep learning crack detection system was presented. Furthermore, an optimal maintenance method through economic analysis was presented targeting the pavement section of Sejong City. As a result of monitoring the pavement conditions, it was confirmed that the pavement ratings were good in the order of national highways, municipal roads, and roads of provinces. In addition, economic analysis using the pavement deterioration model showed that micro-surfacing, one of the preventive maintenance methods, is the most economical in terms of maintenance costs and user benefits. The results of this study are expected to be used as fundamental reference for local governments' infrastructure management plans.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.176-182
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• 2017

The housing market is divided into several sub-markets that operate independently. One of them is the distinction between rental and sales markets. Simultaneously, since the housing is a commodity as well as an asset, it has a close relationship between the rental market and the sales market. Due to the unique structure of Korea, it is difficult to apply the general method to analyze the housing market. This means there is a great deal of concern about side effects from the policy. Actually, the government's subsequent regulation of speculative demand in the future may be necessary to prevent market overheating, but at the same time, there is a fear that the rent will rise. Although changes in policy direction may be inevitable due to changes in market conditions, frequent and sudden changes in policy cause confusion in market participants, causing unrest in the housing market. This study aims to derive main factors and correlation with other housing market factor. These factors will be a base of qualitative housing market model to analyze the market effect of the demand-supply shift. Modeling is based on the system dynamics methodology, which is useful for identifying interactions between variables reflecting various variables in the housing market. The model discussed in this study is expected to provide integrated insight into the key variables of the housing market, away from the monopolistic thinking. It can also be useful as a means of assessing the effectiveness of policies.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.138-144
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• 2018

Inventory inspection is an important task to eliminate the inconsistency between real assets and inventory management systems, and it is performed periodically at the site. In the case of a large-sized property, it is mainly managed in an outdoor workshop or a warehouse. However, due to the large area of the outdoor area, it is relatively difficult to identify the quantity and location of the property and is also vulnerable to theft. To solve this problem, we proposed a method and system for performing a warehouse inventory inspection using an unmanned aerial vehicle (UAV) and Bluetooth low energy (BLE) beacons. The proposed method has the following advantages. First of all, if we carry out inventory inspection by utilizing UAV, we can minimize user's effort compared to existing methods. The method of recognizing the asset by attaching the BLE beacon is more costly than using the existing RFID technology, but it is advantageous because the recognition distance is increased and the battery life of the tag is drastically increased. We also designed a BLE beacon reader for the system and implemented a prototype to show the feasibility of the proposed system. The prototype is based on Genuino 101, which is a kind of arduino, and adds HM-10 and Neo-6m modules to provide Bluetooth and GPS functions. The BLE beacon reader was tested in outdoor, and attached in drone. We also developed an inventory checking system based on the web to display results of inventory checking. The proposed approach enables the users to automate the operation of inventory checking on an outdoor warehouse.

• Management & Information Systems Review
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• v.29 no.4
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• pp.169-186
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• 2010

This study aims to reveal the ways to sharpen the edges of Korean companies through the relativity analysis between knowledge management and innovational cluster in environmental changes in resent Busan. That is, according to the knowledge management approach, the methods and directions of strengthening industrial competition were established, while the strategy of innovational clusters was suggested as a way of expanding and encouraging knowledge management. The key words of innovational cluster are in this research are the framework of Cluster theory, the importance of innovational cluster, and the change of managerial strategy paradigm. This study provide the several implication for the practice of knowledge management and the researchers. Based on these theories of knowledge management and industrial clusters, their close relationships were analyzed. As a result, industrial clusters were found to be effectively utilized to enlarge and deepen knowledge management. In addition, this suggests the efficient operation guideline of knowledge management. this study indicates both knowledge and innovational cluster should be operated and handled together in the managerial strategy. but this research has limitations in generaling the study result because it collects data from local firms only in Busan.