• Korean Journal of Remote Sensing
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• v.34 no.2_1
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• pp.301-306
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• 2018

Urbanization causes urban floods and urban heat island in the summer, so it is necessary to understanding the changes of the thermal environment through urban climate and energy balance. This can be explained by the energy balance, but in urban areas, unlike the typical energy balance, the storage heat flux saved in the building or artificial land cover should be considered. Since the environment of each city is different, there is a difficulty in applying the method of retrieving the storage heat flux of the previous research. Especially, most of the previous studies are focused on the overseas cities, so it is necessary to study the storage heat retrieval suitable for various land cover and building characteristics of the urban areas in Korea. Therefore, the object of this study, it is to derive the regression formula which can quantitatively retrieve the storage heat using the data of the area where various surface types exist. To this end, nonlinear regression analysis was performed using net radiation and surface temperature data as independent variables and flux tower based storage heat estimates as dependent variables. The retrieved regression coefficients were applied to each independent variable to derive the storage heat retrieval regression formula. As a result of time series analysis with flux tower based storage heat estimates, it was well simulated high peak at day time and the value at night. Moreover storage heat retrieved in this study was possible continuous retrieval than flux tower based storage heat estimates. As a result of scatter plot analysis, accuracy of retrieved storage heat was found to be significant at $50.14Wm^{-2}$ and bias $-0.94Wm^{-2}$.

• KDI Journal of Economic Policy
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• v.13 no.2
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• pp.69-96
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• 1991

Economic circumstances of enterprise began to change after a series of democratization measures in 1987. Accompanied with it, competitive advantage of enterprise began to change as well. By that time Korean enterprises had a competitive advantage based on low wages of labor. Abrupt and steady upsurge in wage, however, weakened competitive advantage based on low wages, upward revaluation of won currency caused by surplus in BOP strengthened upward trend in price increase of export products. An urgent problem in Korea economy is, therefore, to find 'new' competitive advantage. For the time being preserving competitiveness based on cost advantage must inevitably remain our basic strategy in industrial policy. While cost advantage in the past referred to low wage level, this cost advantage must have foundation on the improvment in producing technology, which will increase labor productivity and decrease unit cost of products. Besides, other measure to improve competitiveness can be considered such as increasing the extent of production automation, self-development of new products, and spread and strengthening subcontracting system among various enterprises. In this paper we tried to perceive how subcontracting system as a form of intercompany division of labor operates and to which direction this system proceeds responding to the recent changes in economic circumstances. Speaking more concretly, we tried to perceive how large the gap of bargaining power between mother-company and subcontracting company is and how effectively subcontracting company's technical power contributes to mother-company. Facing up to weakeening of competitiveness, how stably is the partnership between mother-company and subcontracting company established and what measures are being prepared to retore the weakened competitiveness. In conclusion the result of investigation through the questionaire on subcontracting system is positive, from which we can infer the optimistic view of restoring Korean economy's competitiveness.

• 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.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.65-82
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• 2015

Recently, there has been a surge of interest in finding core issues and analyzing emerging trends for the future. This represents efforts to devise national strategies and policies based on the selection of promising areas that can create economic and social added value. The existing studies, including those dedicated to the discovery of future promising fields, have mostly been dependent on qualitative research methods such as literature review and expert judgement. Deriving results from large amounts of information under this approach is both costly and time consuming. Efforts have been made to make up for the weaknesses of the conventional qualitative analysis approach designed to select key promising areas through discovery of future core issues and emerging trend analysis in various areas of academic research. There needs to be a paradigm shift in toward implementing qualitative research methods along with quantitative research methods like text mining in a mutually complementary manner. The change is to ensure objective and practical emerging trend analysis results based on large amounts of data. However, even such studies have had shortcoming related to their dependence on simple keywords for analysis, which makes it difficult to derive meaning from data. Besides, no study has been carried out so far to develop core issues and analyze emerging trends in special domains like the aviation industry. The change used to implement recent studies is being witnessed in various areas such as the steel industry, the information and communications technology industry, the construction industry in architectural engineering and so on. This study focused on retrieving aviation-related core issues and emerging trends from overall research papers pertaining to aviation through text mining, which is one of the big data analysis techniques. In this manner, the promising future areas for the air transport industry are selected based on objective data from aviation-related research papers. In order to compensate for the difficulties in grasping the meaning of single words in emerging trend analysis at keyword levels, this study will adopt topic analysis, which is a technique used to find out general themes latent in text document sets. The analysis will lead to the extraction of topics, which represent keyword sets, thereby discovering core issues and conducting emerging trend analysis. Based on the issues, it identified aviation-related research trends and selected the promising areas for the future. Research on core issue retrieval and emerging trend analysis for the aviation industry based on big data analysis is still in its incipient stages. So, the analysis targets for this study are restricted to data from aviation-related research papers. However, it has significance in that it prepared a quantitative analysis model for continuously monitoring the derived core issues and presenting directions regarding the areas with good prospects for the future. In the future, the scope is slated to expand to cover relevant domestic or international news articles and bidding information as well, thus increasing the reliability of analysis results. On the basis of the topic analysis results, core issues for the aviation industry will be determined. Then, emerging trend analysis for the issues will be implemented by year in order to identify the changes they undergo in time series. Through these procedures, this study aims to prepare a system for developing key promising areas for the future aviation industry as well as for ensuring rapid response. Additionally, the promising areas selected based on the aforementioned results and the analysis of pertinent policy research reports will be compared with the areas in which the actual government investments are made. The results from this comparative analysis are expected to make useful reference materials for future policy development and budget establishment.

• 기호학연구
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• no.56
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• pp.45-70
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• 2018

Criticism of the postmodern philosophy of the system of representation, which has continued since the Renaissance, is based on a critique of the dichotomy that separates the subjects and objects and the environment from the human being. Interactivity, highlighted in a series of works emerging as postmodern trends in the 1960s, was transmitted to an interactive aspect of digital art in the late 1990s. The key feature of digital art is the possibility of infinite variations reflecting unpredictable changes based on public participation on the spot. In this process, the importance of computer programs is highlighted. Instead of using the existing program as it is, more and more artists are creating and programming their own algorithms or creating unique algorithms through collaborations with programmers. We live in an era of paradigm shift in which programming itself must be considered as a creative act. Simulation technology and VR technology draw attention as a technique to represent the meaning of reality. Simulation technology helps artists create experimental works. In fact, Baudrillard's concept of Simulation defines the other reality that has nothing to do with our reality, rather than a reality that is extremely representative of our reality. His book Simulacra and Simulation refers to the existence of a reality entirely different from the traditional concept of reality. His argument does not concern the problems of right and wrong. There is no metaphysical meaning. Applying the concept of simulation to algorithmic art, the artist models the complex attributes of reality in the digital system. And it aims to build and integrate internal laws that structure and activate the world (specific or individual), that is to say, simulate the world. If the images of the traditional order correspond to the reproduction of the real world, the synthesized images of algorithmic art and simulated space-time are the forms of art that facilitate the experience. The moment of seeing and listening to the work of Ian Cheng presented in this article is a moment of personal experience and the perception is made at that time. It is not a complete and closed process, but a continuous and changing process. It is this active and situational awareness that is required to the audience for the comprehension of post-representation's forms.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.436-445
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• 2023

Methane (CH₄) emissions from rice paddies are mainly observed using the closed chamber method or the eddy covariance method. In this study, a new observation technique combining a portable gas analyzer (Model LI-7810, LI-COR, Inc., USA) and an automatic opening/closing chamber (Model Smart Chamber, LI-COR, Inc., USA) was introduced based on the strengths and weaknesses of the existing measurement methods. A cylindrical collar was manufactured according to the maximum growth height of rice and used as an auxiliary measurement tool. All types of measured data can be monitored in real time, and CH₄ flux is also calculated simultaneously during the measurement. After the measurement is completed, all the related data can be checked using the software called 'SoilFluxPro'. The biggest advantage of the new observation technique is that time-series changes in greenhouse gas concentrations can be immediately confirmed in the field. It can also be applied to small areas with various treatment conditions, and it is simpler to use and requires less effort for installation and maintenance than the eddy covariance system. However, there are also disadvantages in that the observation system is still expensive, requires specialized knowledge to operate, and requires a lot of manpower to install multiple collars in various observation areas and travel around them to take measurements. It is expected that the new observation technique can make a significant contribution to understanding the CH₄ emission pathways from rice paddies and quantifying the emissions from those pathways.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.51-69
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• 2020

Now, it is a stylized fact that a small number of technology firms such as Apple, Alphabet, Microsoft, Amazon, Facebook and a few others have become larger and dominant players in an industry. Coupled with the rise of these leading firms, we have also observed that a large number of young firms have become an acquisition target in their early IPO stages. This indeed results in a sharp decline in the number of new entries in public exchanges although a series of policy reforms have been promulgated to foster competition through an increase in new entries. Given the observed industry trend in recent decades, a number of studies have reported increased concentration in most developed countries. However, it is less understood as to what caused an increase in industry concentration. In this paper, we uncover the mechanisms by which industries have become concentrated over the last decades by tracing the changes in industry concentration associated with a firm's status change in its early IPO stages. To this end, we put emphasis on the case in which firms are acquired shortly after they went public. Especially, with the transition to digital-based economies, it is imperative for incumbent firms to adapt and keep pace with new ICT and related intelligent systems. For instance, after the acquisition of a young firm equipped with AI-based solutions, an incumbent firm may better respond to a change in customer taste and preference by integrating acquired AI solutions and analytics skills into multiple business processes. Accordingly, it is not unusual for young ICT firms become an attractive acquisition target. To examine the role of M&As involved with young firms in reshaping the level of industry concentration, we identify a firm's status in early post-IPO stages over the sample periods spanning from 1990 to 2016 as follows: i) being delisted, ii) being standalone firms and iii) being acquired. According to our analysis, firms that have conducted IPO since 2000s have been acquired by incumbent firms at a relatively quicker time than those that did IPO in previous generations. We also show a greater acquisition rate for IPO firms in the ICT sector compared with their counterparts in other sectors. Our results based on multinomial logit models suggest that a large number of IPO firms have been acquired in their early post-IPO lives despite their financial soundness. Specifically, we show that IPO firms are likely to be acquired rather than be delisted due to financial distress in early IPO stages when they are more profitable, more mature or less leveraged. For those IPO firms with venture capital backup have also become an acquisition target more frequently. As a larger number of firms are acquired shortly after their IPO, our results show increased concentration. While providing limited evidence on the impact of large incumbent firms in explaining the change in industry concentration, our results show that the large firms' effect on industry concentration are pronounced in the ICT sector. This result possibly captures the current trend that a few tech giants such as Alphabet, Apple and Facebook continue to increase their market share. In addition, compared with the acquisitions of non-ICT firms, the concentration impact of IPO firms in early stages becomes larger when ICT firms are acquired as a target. Our study makes new contributions. To our best knowledge, this is one of a few studies that link a firm's post-IPO status to associated changes in industry concentration. Although some studies have addressed concentration issues, their primary focus was on market power or proprietary software. Contrast to earlier studies, we are able to uncover the mechanism by which industries have become concentrated by placing emphasis on M&As involving young IPO firms. Interestingly, the concentration impact of IPO firm acquisitions are magnified when a large incumbent firms are involved as an acquirer. This leads us to infer the underlying reasons as to why industries have become more concentrated with a favor of large firms in recent decades. Overall, our study sheds new light on the literature by providing a plausible explanation as to why industries have become concentrated.

• Korean Journal of Environmental Agriculture
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• v.29 no.1
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• pp.54-60
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• 2010

We have researched the changes in nutrient content in each phase of fermentation in crops treated with liquefied pig fertilizer, and have determined the best method for applying livestock excrement to cultured crops. In the execution of this experiment, rice was cultivated to full maturity at a paddy field in Jeollabuk-Do Agriculture Research and Extension Services(Jeon-buk series) from 2007 to 2008. The rice plant nitrogen absorption quantity change, according to the growth stages of the cultivated rice, was 20.3% in the rice treated with the liquid pig manure and 22.2% the chemical fertilizer at highest congelation. The chemical fertilizer showed a higher absorption quantity than the liquid manure compost. The nitrogen density at highest congelation was 1.5% in the chemical fertilizer, and 1.8% in the pig manure liquid compost not a significant difference. The stem height at harvest time was 73.8 cm in the crops treated with the liquid pig manure compost. Those treated with the chemical fertilizer, yielded a height of 4.2 cm less than the crops treated with the liquid pig manure compost. The yield was 507 kg/10a in the liquid pig manure compost treated rice, compared with the chemical fertilizer, which showed a value of 1.2% lower. The protein content was 6.3% in the rice treated with the chemical fertilizer, but 6.4% in the rice treated with the liquid pig manure compost. This is not a significant difference. However, the lodging rice plant treated with the chemical fertilizer control showed a protein content of 6.8%, which was even higher than the normal rice. The head rice ratio in the brown rice and the polished rice ended up to be lower in the crop treated with the liquid pig manure than that treated with the chemical fertilizer, Quality, the palatability value, was similar in both groups. The above result indicate that, the effect of liquid pig manure compost corresponds to the effect of chemical fertilizer, when each are scattered uniformly.