• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.15-26
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• 2014

This study focus on a economic value of the Big Data technologies by real options model using big data technology company's stock price to determine the price of the economic value of incremental assessed value. For estimating stochastic process of company's stock price by big data technology to extract the incremental shares, Generalized Moments Method (GMM) are used. Option value for Black-Scholes partial differential equation was derived, in which finite difference numerical methods to obtain the Big Data technology was introduced to estimate the economic value. As a result, a option value of big data technology investment is 38.5 billion under assumption which investment cost is 50 million won and time value is a about 1 million, respectively. Thus, introduction of big data technology to create a substantial effect on corporate profits, is valuable and there are an effects on the additional time value. Sensitivity analysis of lower underlying asset value appear decreased options value and the lower investment cost showed increased options value. A volatility are not sensitive on the option value due to the big data technological characteristics which are low stock volatility and introduction periods.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.51-55
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• 2017

In this paper, we designed a LBS-based smart platform for Lifelog service that can utilize the other's lifelog information. The conventional Lifelog service means that the system records the daily activities of the smart device user so the user can retrieve the early-recorded information later. The proposed Lifelog service platform uses the GPS/UFID location information and the various information extracted from the image as the lifelog data. Further, the proposed Lifelog platform using DB can provide the user with the Lifelog data recorded by the other service user. The system usually provide the other's Lifelog data within the 500m distance from the user and the range of distance can be adjustable. The proposed smart platform based on image recognition for Lifelog can acquire the image from the smart device directly and perform the various image recognition processing to produce the useful image attributes. And it can store the location information, image data, image attributes and the relevant web informations on the database that can be retrieved by the other use's request. The attributes stored and managed in the image information database consist of the followings: Object ID, the image type, the capture time and the image GPS coordinates. The image type attribute has the following values: the mountain, the sea, the street, the front of building, the inside of building and the portrait. The captured image can be classified into the above image type by the pattern matching image processing techniques and the user's direct selection as well. In case of the portrait-attribute, we can choose the multiple sub-attribute values from the shirt, pant, dress and accessory sub-attributes. Managing the Lifelog data in the database, the system can provide the user with the useful additional services like a path finding to the location of the other service user's Lifelog data and information.

• Journal of Science and Technology Studies
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• v.13 no.1
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• pp.145-180
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• 2013

STS studies into science documentaries for television are rare, and they do not even reflect the constructivist fruits of STS. STS have been calling for the need of analyzing 'science-in-the-making' in order to understand science more deeply. Similarly, our starting point is the assumption that science documentary can be better understood when we look into its making process. Under this assumption, we adopted the method of participant observation in analyzing 'documentary practice', trying to open the 'black box' called 'science documentary'. We have here focused on the documentary named "Light" made by a scientific documentary team of EBS, who made "Culture and Mathematics" and "Life". Each of us worked as a main consultant and an assistant staff in making "Light". We will address two main points in this study. First, based on our participant observation and interviews, we will show that the members of documentary making team are thinking about 'science' in distinctive ways. The team tended to emphasize visualization, knowledge linked to people's everyday life, and the distinctive characters of scientists who appear in the documentary. Second, by looking closely into the interaction between the team members and the consultant in the process of completing the script of the documentary, it was possible to understand how the contents of the documentary was constructed more accurately. In the making process, consultant's idea was not simply accepted by the making team, but there were conflicts and compromises. By showing this, we will be able to bring up a reflexive question about the role of consultant in the process of making a science documentary.

• Journal of IKEEE
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• v.22 no.3
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• pp.822-828
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• 2018

Recently, energy issues such as massive blackout due to increase in power consumption have been emerged, and it is necessary to improve the accuracy of prediction of power consumption as a solution for these problems. In this study, we investigate the difference between the actual power consumption and the predicted power consumption through the deep learning- based power consumption forecasting experiment, and the possibility of adjusting the power reserve ratio. In this paper, the prediction of the power consumption based on the deep learning can be used as a basis to reduce the power reserve ratio so as not to excessively produce extra power. The deep learning method used in this paper uses a learning model of long-short-term-memory (LSTM) structure that processes time series data. In the computer simulation, the generated power consumption data was learned, and the power consumption was predicted based on the learned model. We calculate the error between the actual and predicted power consumption amount, resulting in an error rate of 21.37%. Considering the recent power reserve ratio of 45.9%, it is possible to reduce the reserve ratio by 20% when applying the power consumption prediction algorithm proposed in this study.

• Journal of The Korean Association For Science Education
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• v.33 no.4
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• pp.718-734
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• 2013

The purpose of the study is to investigate high school students' perception and understanding of old metaphorical science terminologies and new metaphorical science terminologies (highly metaphorical science terminologies). For the study, three old metaphorical terminologies and three new metaphorical terminologies have been chosen from the old and new Korean science curricula respectively, and 176 high school students who learned physics based on 7th science curriculum developed in 1997 and 175 highschool students who learned physics based on the science curriculum revised in 2009 were sampled from two high schools in a big city in Korea. The research results are as follows: First, for the old metaphorical terminologies, there are more students who give explanations using scientific terms than those who use the meaning of the metaphors that terminologies had. Second, for the new metaphorical terminologies, there are much less students who give explanations using scientific terms than those who explained using the meaning of the metaphors that the terminologies had. Therefore, it should be emphasized that, for the new metaphorical terminologies, the metaphorical meaning of the terminologies do not mean the concepts themselves in teaching science.

• Journal of KIISE:Software and Applications
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• v.37 no.12
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• pp.892-908
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• 2010

Services in SOA are typically perceived as black-box to service consumers, and can be dynamically evolved at runtime, and run on a number of unknown and heterogeneous environments. Because of these characteristics of the services, effective and efficient monitoring of various aspects on services is an essential functionality for autonomous management of service. But the problem with or limitation in conventional or existing approaches is, that they focus on services themselves, ignoring the effects by business processes. Consequently, there is a room for service monitoring which provides more useful information of business level by acquisition of only external monitoring data that depend on specific BPEL engine and middleware. Moreover, there is a strong demand to present effective methods to reduce monitoring overhead which can degrade quality of services. EDA can cope with such limitations in SOA by collecting and analyzing events efficiently. In this paper, we first describe EDA benefits in service monitoring, and classify monitorring target, and present an appropriate monitoring method for each monitoring target. Also to provide the applicability of our approach, an event meta-model is defined, and event processing model and architecture based on the meta-model are proposed. And, with the proposed architecture and method, we implement a prototype of an event-driven dynamic monitoring framework which can collect and process internal and external data at runtime. Finally, we present the result of a case study to demonstrate the effectiveness and applicability of the proposed approach.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.416-422
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• 2016

Lots of plastics are widely used in a variety of industrial field. And the amount of plastic waste is massively produced. In the study of waste recycling, it is emerged as an important issue to prevent the waste of potentially useful resource materials as well as to reduce ecological damage. So, the recycling of plastic waste has been currently paid attention to from the view point of reuse. Existing automatic sorting system consist of near infrared ray (NIR) sensors to classify the types of plastics. But the classification of black plastics still remains a challenge. Black plastics which contains carbon black are not almost classified by NIR because of the characteristic of the light absorption of black plastics. This study is focused on handling how to identify black plastics instead of NIR. Raman spectroscopy is used to get qualitative as well as quantitative analysis of black plastics. In order to improve the performance of identification, Support Vector Machine(SVM) classifier and Principal Component Analysis(PCA) are exploited to more preferably classify some kinds of the black plastics, and to analyze the characteristic of each data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.596-601
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• 2020

Silicon carbide is considered a potentially useful material for high-temperature electronic devices because of its large band gap energy and p-type or n-type conduction that can be controlled by impurity doping. Accordingly, the thermoelectric properties of -SiC powder prepared by refined diatomite were investigated for high value-added applications of natural diatomite. -SiC powder was synthesized by a carbothermal reduction of the SiO₂ in refined diatomite using carbon black. An acid-treatment process was then performed to eliminate the remaining impurities (Fe, Ca, etc.). n-Type semiconductors were fabricated by sintering the pressed powder at 2000℃ for 1~5h in an N2 atmosphere. The electrical conductivity increased with increasing sintering time, which might be due to an increase in carrier concentration and improvement in grain-to-grain connectivity. The carrier compensation effect caused by the remaining acceptor impurities (Al, etc.) in the obtained -SiC had a deleterious influence on the electrical conductivity. The absolute value of the Seebeck coefficient increased with increasing sintering time, which might be due to a decrease in the stacking fault density accompanied by grain or crystallite growth. On the other hand, the power factor, which reflects the thermoelectric conversion efficiency of the present work, was slightly lower than that of the porous SiC semiconductors fabricated by conventional high-purity -SiC powder, it can be stated that the thermoelectric properties could be improved further by precise control of an acid-treatment process.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.235-247
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• 2020

The Mutual Financial Cooperatives(MFCs) in Korea need to make efforts to increase efficiency and productivity in order to secure stable and sustainable growth and competitiveness. Therefore, this study analyzes the efficiency and productivity of MFCs from 2012 to 2018 and suggests some implications. The methodology employed is a Dynamic-Network Slacks-Based Measure(DNSBM) Model. The findings from an empirical study include that first, on average efficiency scores of the institutions, NH(0.225) showed the highest overall efficiency, and followed by SH(0.128) and MG(0.126). After 2015, most of the MFCs' efficiency scores had risen until to 2018. Second, in divisional analysis, the inefficiency in creating the high profitability-stage had been greater than establishing-funds-stage. Third, in projection analysis of Division 2, the inefficiency of the output factors such as interest income and operating income was severe. Fourth, the results from the Malmquist Productivity Index analysis of Division 1 of the fist-stage illustrate that all three MFCs showed minus catch-up effects. Also, a soundness from reducing bad loans and expansion of loans in combination with generating various ways of creating profits besides the interest income is urgently needed for Korean MFCs.

• Analytical Science and Technology
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• v.8 no.1
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• pp.63-68
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• 1995

For the preparation of pH-selectrode, tribenzylamine, polyvinylchloride, dioctylphthalate, sodium tetraphenylborate and tetrahydrofuran were mixed with 0.02, 0.62, 1.34, 0.02g and 10ml respectively, and added 1g of acetylene black, graphite, silicon carbide or tungsten carbide respectively to improve electric conductivity. The selectrodes of seven kinds were shown linear to hydrogen ion in the range of pH 2 and 9. The best electric conductor for preparation of pH-selectrode based on tribenzylamine as neutral carrier was acetylene black and responded potential of the selectrode to hydrogen ion was shown the values near to theoretical Nernstian slope at $20^{\circ}C$. The interfering effects of the selectrode on hydrogen ion in the presence of alkali and alkaline earth metal ions were shown the better results with less error than glass electrode. The reproducibility and stability were good for use as a selectrode, especially in the presence of fluoride ion.