• 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.

• Archives of design research
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• v.16 no.4
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• pp.185-196
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• 2003

The demand for an environment-friendly transportation system, equipped with low energy consumption, and low-or zero-pollution has been on the increase since the beginning of the World Trade Organization era. Simultaneously, the consistent growth of high-speed tram technology, combined with market share, has sparked a fierce competition among technologically-advanced countries like France, Germany, and Japan in an effort to keep the lead in high-speed train technology via extensive Research and development(R＆D) expenses. These countries are leaders in the race to implement the next-generation transportation system, build intercontinental rail way networks and export the high-speed train as a major industry commodity. The need to develop our own(Korean) 'high-speed train' technology and its core system technology layouts including original technology serves a few objectives: They boost the national competitive edge; they develop an environmental friendly rail road system that can cope with globalization and minimize the social and economic losses created by the growing traffic-congested delivery costs, environment pollution, and public discomforts. In turn, the 'G7 Project-Development of High Speed Railway Technology' held between 1996 and 2002 for a six-year period was focused on designing a domestic train capable of traveling at a speed of 350km/h combined and led to the actual implementation of engineering and producing the '2000 high-speed train:' This paper summarizes and introduces one of the G7 Projects-specifically, the design segment achievement within the development of train system engineering technology. It is true that the design aspect of the Korean domestic railway system program as a whole was lacking when compared with the advanced railroad countries whose early phase of train design emphasized the design aspect. However, having allowed the active participation of expert designers in the early phase of train design in the current project has led to a new era of domestic train development and the implementation of a way to meet demand flexibly with newly designed trains. The idea of a high-speed train in Korea and its design concept is well-conceived: a faster, more pleasant, and silent based Korean high-speed train that facilitates a new travel culture. A Korean-type of high-speed train is acknowledged by passengers who travel in such trains. The Korean high-speed prototype train has been born, combining aerodynamic air-cushioned design, which is the embodiment of Korean original design of forehead of power car minimized aerodynamic resistance using a curved car body profile, and the improvement of the interior design with ergonomics and the accommodation of the vestibule area through the study of passenger behavior and social culture that is based on the general passenger car.

• Economic and Environmental Geology
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• v.18 no.1
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• pp.65-92
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• 1985

A total of 12 mineral commodities significant in domestic output, economy and/or strategy of the Republic of Korea are chosen to examine the structural changes in production and demand-supply of these minerals during the last two decades of her industrialization. These include iron and manganese ores as the raw materials for iron and steel making, copper, zinc and tungsten ores among other non-ferrous metallic minerals, limestone (cement), kaolin, talc, pyrophyllite and graphite among other non-metallic minerals, and anthracite coal as the only domestic source of fossil energy. These are reviewed historically in time-series based on the statistical data which are tabulated and graphed in terms of domestic output, export, import, apparent demand-supply, its increasing rate, and self-sufficiency rate of each commodity. The increasing rates of demand-supply (IRDS) of some more important commodities are compared with those of Gross Domestic Production (GDP) and Economic Growth Rate (EGR) to evaluate how the IRDS contributed to the GDP and EGR. The major results revealed are as follows: Among the 12 commodities, the domestic output of 8 commodities appeared to have grown with steady upward trends: they are ores of lead, zinc and tungsten, limestone (cement), kaolin, talc, pyrophyllite and anthracite coal. Two commodities, ores of iron and copper, continued with unchanging or slightly declining trends and varied fluctuations, in spite of their cardinal importance to the heavy industry and strategy of Korea. The remaining two, graphite and manganese ore, have gradualy declined in domestic output in which the former has still enough resource potential but the latter has not and virtually ceased its domestic output. Trade patterns for mineral commodities in the Republic of Korea during the last two decades have changed greatly, being marked by a shift from mineral-exporting to mineral importing, mainly because of increasing consumption of mineral raw materials for industrialization rather than beceuse of decreasing output of domestic mineral commodities in quantity. In terms of trade patterns, the 12 commodities concerned in this study can be classified into the following four groups. The 1st group - ores of lead and tungsten have only been exported without imports. The 2nd group - amorphous graphite, and pyrophyllite have mainly been exported but partly been imported. The 3rd group - kaolin, talc and crystalline graphite have equally been exported and imported, but quantity of imports have rapidly been increased with time. The 4th group - ores of iron, manganese and zinc have shifted from exports to imports during the industrialization, particularly owing to the initiation of iron and steel making by the Pohang Iron and Steel Company in the middle 1970' s and the new establishment of the Onsan Zinc Refinery in the late 1970' s. All of the 12 commodities under considerations were far above 100% in self-sufficiency rate before or in the early 1960' s. Recently, however, most of them have been declined to below 100% except for those of limestone (cement) and pyrophyllite. It is particularly serious to identify that the self-sufficiency rates of the three important metallic minerals, iron, copper and manganese ores in 1982 appeared to be 5.1%, 0.5%, and 0.01%, respectively. The average self-sufficiency rate of the total domestic minerals produced in 1982 was 14.4% (in value) for that year. Mining industry appeared to be extremely high in its intermediate demand rate whereas its intermediate input rate to be quite low indicating that mineral raw materials have been exerted strong forward linkage effects upon the other industries rather than backward linkage effects. In comparing the curves of increasing rates of demand-supply of several major minerals - iron ore, manganese ore, copper ore, limestone (cement), kaolin, and anthracite coal - with those of Gross Domestic Production and Economic Growth Rate drawn on every graph, it is clearly shown that the curves of increasing rates of demand-supply comprise around 6 to 7 periods of cycles which roughly harmonious with those of the curves of GDP and EGR, except for the curve of anthracite coal of which the configuration seems to have resulted from the (artificial) government's mineral policy rather than from economic free market mechanism. The harmonic feature of these curves well suggests that the increasing rates of demand-supply of major minerals have been significantly contributed to the GDP and EGR. In addition, the wider amplitudes of the iron, manganese and copper curves than those of the limestone (cement) and kaolin curves indicate that the contribution of the former, metallic commodities, has been greater than that of the latter, non-metallic commodities.

• Korean Journal of Environmental Agriculture
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• v.25 no.2
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• pp.180-189
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• 2006

This survey was done to investigate the pesticide residues on agricultural products on the markets in Incheon area from 2003 to 2005. A total of 10,431 samples was analyzed the residues by GC. The violation rates of the samples over maximum residue limits (MRLs) of pesticide residues established by Korean Food and Drug Administration (KFDA) in the survey of 2003, 2004 and 2005 were 1.3%, 0.9%, and 1.2%, respectively. The rate from the samples of 2005 surveyed in general wholesale markets was 3.1%, whereas that from agricultural wholesale market was 0.93%. Of the total violated samples, more than 70% of the rates were recorded from the samples of Gyeonggi-do and Incheon area in 2003 and 2004. However, the rates from Gyeonggi-do and Incheon in 2005 were remarkably reduced to 25.6% and 23.3%, respectively. Most commonly encountered agricultural commodity over MRLs was crown daisy. Positively detected pesticides were 12, 17 and 32 in the survey of 2003, 2004 and 2005, respectively. The pesticides detected yearly over MRLs during three years were chlorothalonil, chlorpyrifos, diazinon, endosulfan, procymidone. Decreasing tendency in detected and violated rates of the residues was observed in chlorpyrifos and diazinon, while increasing tendency in detected rates was recorded in chlorothalonil, endosulfan, procymidone.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.