• Proceedings of the KIEE Conference
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• summer
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• pp.85-87
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• 2004

Supervisory control and data acquisition (SCADA) systems are essential parts of power system which employ a wide range of computers and communication technologies. The traditional SCADA system is mainly for information exchange in only one company, and the information is provided only to the operator or administrator. But in the deregulated environment, we need much more information, which can be exchanged among different companies. With the rapid development of internet, we can use it to access information easily. This paper proposes web technologies to be applied in power system in order to display some important information through accessing data from database, and to realize the real time control of the substation. The functions of SCADA system will be implemented by a set of Web-based components. The monitoring and control of standard 154[kV] substation model is already realized in the laboratory test. The Web-based SCADA system is able to provide sufficient information and control for pow or system through an efficient and economical way.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.125-131
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• 2023

OVO is a digital platform that provides simple payments and smart financial services, as well as one of the largest digital payment platforms in Indonesia. It has wide coverage and security when making payments, and supports multiple settlement currencies. The purpose of this study is to explore the history, business model, and future strategic direction of OVO, an Indonesian e-wallet. To date, OVO has built its own mobile payment ecosystem covering a wide range of consumer scenarios including e-commerce, travel, offline shopping and finance. And it supports mobile banking, online banking, debit cards or selected partner merchants. Its three largest transaction categories are in the transportation, retail and e-commerce sectors. With over 110 million consumers and 1.3 million merchant users, it is one of the dominant e-wallets in Indonesian market and has become the country's e-payment market leader. OVO eWallet's 'One Card' model offers convenience and choice for users, thus contributing to the rapid growth of OVO eWallet. And OVO eWallet competes fiercely with other competitors, but OVO eWallet continues to grow in terms of the number of users and market share. Finally, this study analyzes the strategic goals and plans of OVO eWallet, predicts its future direction. OVO eWallet has a huge success, but there are still competition and challenges to face.

• Korean Journal of Labor Studies
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• v.17 no.1
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• pp.177-208
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• 2011

This article examines that how in-house subcontract has been introduced and developed in metal industry in 1970s, focusing typical workplaces in steel industry. That was essential for the capital to insure control mechanism for large number of laborer because of mobilizing a large scale of capital in industrialization of heavy metal industry. In case of Pohang steel industry, this necessity was fulfilled by introduction and imitation of Japanese personnel management by being included of Japanese economic hinterland. This was embodied in both constructing internal labor market for regular workers and introducing in-house subcontracting system for contingent workers at workplaces. This was exceptional comparing in-house subcontracting system in Korean steel industry with in-house subcontracting system in advanced economies, because of disappearing in-house subcontracting system by making internal labor market. And this was closely linked by late development of Korea. Implications of Pohang steel company's case are as follows : first, late development effect in formation of employment system, second, in linking informality of Korean employment system. This implications mean that in-house subcontracting in steel industry is structured as mechanism for personnel management in large factory being influenced by industrialization of heavy industry. In this point, improvements which include wide economic solution beyond labor solution for present problem of in-house subcontracting system is desirable.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.1007-1012
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• 2005

Although the design-build (DB) delivery system has been taking great strides in the world and relevant researches have also been quite abundant, few studies have dealt with its potential impacts on the construction industry as a whole. This research first identified the potential entry barrier factors, which may hinder the market access, based on the theory of industrial economics and characteristics of DB project. Then through a nation-wide questionnaire survey involving 103 construction contractors and engineering consultants, the influences of each factor on company's competitiveness and corporate strategies were scrutinized, and consequently, the evolution of the construction industry was examined. It is found that as opposed to the traditional design-bid-build delivery system, the DB delivery system elevates competitive advantages of large organizations in terms of the financial capability, working experience, human resource, and administrative strength, and among them, the financial strength was concluded to be the most significant force in differentiating corporate strategies and widening the gap of competitiveness between companies. It is inferred if the government extensively adopts DB delivery system, large organizations that already possess the competitive advantage tend to obtain both design and construction abilities, and dominate the DB market. Small and medium sized companies will find little room to maneuver and be forced to become specialty sub-contractors.

• Korean Journal of Organic Agriculture
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• v.22 no.4
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• pp.593-610
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• 2014

The whole world concentrates on the reduction of greenhouse gas to effectively cope with policy toward global climate change. To effectively react to climate change, even the agricultural sector requires construction of new farming systems that utilizes new and renewable energy because of rising oil prices and regulations for greenhouse gas emissions. For this reason, we need to fuse the new and renewable energy with the horticulture sector of which the light and heat energy cost accounts for great part, moreover, efforts and researches should me done which can increase income of farmers through reducing carbon dioxide and energy cost in agricultural production expenses. Therefore, this study analyzes economic feasibility and applicability of fusing geothermal heat pump and solar power facilities with high-tech glass greenhouse. As a result, it is concluded that there surely are an applicability and economic feasibility if we apply new development system that can be an alternative for problems of securing premises of existing geothermal heat pump and the RPS system as a power generation company in case of solar power. Therefore, using this analysis data, if new empirical studies fusing and implementing agriculture sector with new and renewable energy fields proliferate and be applied to actual rural and agricultural field, it will increase actual income and will become a new advanced agricultural system that effectively deals with world-wide environmental problems.

• Journal of Advanced Navigation Technology
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• v.24 no.2
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• pp.61-66
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• 2020

Since the ocean accounts for 70.8 percent of the earth's surface, the success of IoT technology in the marine industry is to collect information from devices placed in a wider range. LPWA is a feature with a wide range of communication and is very suitable for deployment in the ocean. In this paper, the real-sea performance distance experiment was carried out based on Private LoRa, a key technology for executing the electronic phrase real-name system. A private LoRa module based on sx1276 was developed, and Gateway was developed to transfer data received by private LoRa to the server using SKT Cat. M1. After installing gateways at 599 meters above sea level and experimenting with data transmission and reception at 25 km, 40 km and 60 km, we were able to see that the communication success rate was obtained to be 96.1%. 97.1% and 96.2% respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.527-536
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• 2018

This study examined the success factors of six sigma innovation in small- and medium-sized venture companies. The findings are summarized as follows. The importance of 20 items in a total of 4 factors showed that corporate vision was number one in the manager's support, followed by program composition, passionate support, high performance guarantee, and quality activity continuity. This suggests that all members can operate the program by the structured system with a sense of united goal under the company-offered vision as a community when the goal, idea or vision of six sigma activities are shared to members of the entire organization. In addition, high success can be achieved when supported by company-wide enthusiasm and high compensation for sharers' innovative efforts of six sigma at the same time. Small- and medium-sized venture companies should develop brisk six sigma activities of advanced precision parts in such an environment that the technology competition is becoming increasingly fierce. The six sigma movement should be developed as a niche strategy for small organizations with united vision sharing by company-wide operational commitment and high self-esteem for the organizational characteristics of small- and medium-sized venture companies run by key minority organizations and members.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.301-306
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• 2007

The people information is distributed in various forms such as database, web page, text, and so on, where the world wide web is one of the main sources of publicly-available people information. It has a characteristic that the information on people is intrinsically temporal. Therefore, the reconstruction of the information is needed for an individual or a company to use it efficiently. In order to maintain or manage the temporal people information, it must distinguish the variable information from invariable information of people. In this paper, we propose a method that constructs an ontology based on events to manage the variable people information efficiently. In addition, we present a system which reconstructs people information that satisfies the users' demand with the ontology.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.113-124
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• 2004

Customer satisfaction is becoming an increasingly salient topic in many firms and in academic research. One main rationale behind this interest is that customer satisfaction is believed to be associated with fruitful customer re-visit from the firm's point of view. Some country already had index models which can measure the degree of customer satisfaction. But, such models are ordinary models which used generally the scope of nation-wide /industry. Therefore, we needs some modifications to measure customer satisfaction for specific product & service and to provide the valuable feedback to specific firms. In this Perspectives, this study will evaluate the customer satisfaction index about automobile company and analyze it's result for valuable feedback. This study will present a model for an integrated customer satisfaction evaluation system which used structural equation modeling. Through this study, we anticipate that it will offer the measuring method about customer satisfaction and some guideline for product design process.