• Journal of Korean Society of societal Security
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• v.4 no.2
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• pp.73-78
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• 2011

In order to resolve the problem of change in global climate which is worsening as days go by and to preemptively cope with strengthened restriction on carbon emission, the government enacted 'Framework Act on Low Carbon Green Growth' in 2010 and selected green technology and green industry as new national growth engines. For this reason, the necessity to use the un-utilized waste heat across the whole industrial system has become an issue, and studies on and applications of recycling in the agricultural and fishery fields such as cultivation of tropical crops and flatfishes by utilizing the waste heat and thermal effluent generated by large industrial complexes including power plants are being actively carried out. In this study, we looked into the domestic and overseas examples of having utilized waste heat abandoned in the form of power plant thermal effluent, and carried out economic efficiency evaluation of sturgeon aquaculture utilizing thermal effluent of Yeongwol LNG Combined Cycle Power Plant in Gangwon-do. In this analysis, we analyzed the economic efficiency of a model business plan divided into three steps, starting from a small scale in order to minimize the investment risk and financial burden, which is then gradually expanded. The business operation period was assumed to be 10 years (2012~2021), and the NVP (Net Present Value) and economic efficiency (B/C) for the operation period (10 years) were estimated for different loan size by dividing the size of external loan by stage into 80% and 40% based on the basic statistics secured through a site survey. Through the result of analysis, we can see that reducing the size of the external loan is an important factor in securing greater economic efficiency as, while the B/C is 1.79 in the case the external loan is 80% of the total investment, it is presumed to be improved to 1.81 when the loan is 40%. As the findings of this study showed that the economic efficiency of sturgeon aquaculture utilizing thermal effluent of power plant can be secured, it is presumed that regional development project items with high added value can be derived though this, and, in addition, this study will greatly contribute to reinforcement of the capability of local governments to cope with climate change.

• Geophysics and Geophysical Exploration
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• v.9 no.4
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• pp.279-290
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• 2006

The borehole radar methods used to tunnel detection are mainly classified into borehole radar reflection, directional antenna, crosshole scanning, and radar tomography methods. In this study, we have investigated the feasibility and limitation of each method to tunnel detection through case studies. In the borehole radar reflection data, there were much more clear diffraction signals of the upper wings than lower wings of the hyperbolas reflected from the tunnel, and their upper and lower wings were spreaded out to more than 10m higher and lower traces from the peaks of the hyperbolas. As the ratio of borehole diameter to antenna length increases, the ringing gets stronger on the data due to the increase in the impedance mismatching between antennas and water in the boreholes. It is also found that the reflection signals from the tunnel could be enhanced using the optimal offset distance between transmitter and receiver antennas. Nevertheless, the borehole radar reflection data could not provide directional information of the reflectors in the subsurface. Direction finding antenna system had a advantage to take a three dimensional location of a tunnel with only one borehole survey even though the cost is still very high and it required very high expertise. The data from crosshole scanning could be a good indicator for tunnel detection and it could give more reliable result when the borehole radar reflection survey is carried out together. The images of the subsurface also can be reconstructed using travel time tomography which could provide the physical property of the medium and would be effective for imaging the underground structure such as tunnels. Based on the results described above, we suggest a cost-effective field procedure for detection of a tunnel using borehole radar techniques; borehole radar reflection survey using dipole antenna can firstly be applied to pick up anomalous regions within the borehole, and crosshole scanning or reflection survey using directional antenna can then be applied only to the anomalous regions to detect the tunnel.

• Journal of the Korean earth science society
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• v.30 no.6
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• pp.721-733
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• 2009

A pattern of tropical cyclone (TC) movement in the western North Pacific area was studied using the empirical orthogonal function (EOF) and the best track data from 1951 to 2007. The independent variable used in this study was defined as the frequency of tropical cyclone passage in 5 by 5 degree grid. The $1^{st}$, $2^{nd}$ and $3^{rd}$ modes were the east-west, north-south and diagonal variation patterns. Based on the time series of each component, the signs of first and second mode changed in 1997 and 1991, respectively, which seems to be related to the fact that the passage frequency was higher in the South China Sea for 20 years before 1990s, and recent 20 years in the East Asian area. When the eigen vectors were negative values in the first and second modes and TC moves into the western North Pacific, TC was formed mainly at the east side relatively compared to the case of the positive eigen vectors. The first mode seems to relate to the pressure pattern at the south of Lake Baikal, the second mode the variation pattern around $30^{\circ}N$, and the third mode the pressure pattern around Japan. The first mode was also closely related to the ENSO and negatively related to the $Ni\tilde{n}o$-3.4 index in the correlation analysis with SST anomalies.

• Journal of the Korean earth science society
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• v.38 no.1
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• pp.24-34
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• 2017

The westerly waves generation is described in the advanced earth science textbook used at high school as follows: as westerly wind approaches and blows over large mountains, the air flow shows wave motions in downwind side, which can be explained by the conservation of potential vorticity. However, there has been no case study showing the phenomena of the mesoscale westerly waves with observational data in the area of small mountains in Korea. And thus the wind speed and time persistency of westerly winds along with the width and length of mountains have never been studied to explain the generation of the westerly waves. As a first step, we assured the westerly waves generated in the downwind side of Sobaek mountains based on surface station wind data nearby. Furthermore, the critical or minimum wind velocity of the westerly wind over Sobaek mountains to generate the downwind wave were derived and calcuated tobe about $0.6m\;s^{-1}$ for Sobaek mountains, which means that the westerly waves could be generated in most cases of westerly blowing over the mountains. Using surface station data and 4-dimensional assimilation data of RDAPS (Regional Data Assimilation and Prediction System) provided by Korea Meteorological Agency, we also analyzed cases of westerly waves occurrence and life cycle in the downwind side of Sobaek mountains for a year of 2014. The westerly waves occurred in meso-${\beta}$ or -${\gamma}$ scales. The westerly waves generated by the mountains disappeared gradually with wind speed decreasing. The occurrence frequency of the vorticity with meso-${\beta}$ scale got to be higher when the stronger westerly wind blew. When we extended the spatial range of the analysis, phenomena of westerly waves were also observed in the downwind side of Yensan mountains in Northeastern China. Our current work will be a study material to help students understand the atmospheric phenomena perturbed by mountains.

• The Korean Journal of Financial Studies
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• v.3 no.1
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• pp.233-265
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• 1996

We examine the impact of public and private information on price movements using the thirty DJIA stocks and twenty-one NASDAQ stocks. We find that the standard deviation of daily returns on information days (dividend announcement, earnings announcement, insider purchase, or insider sale) is much higher than on no-information days. Both public information matters at the NYSE, probably due to masked identification of insiders. Earnings announcement has the greatest impact for both DJIA and NASDAQ stocks, and there is some evidence of positive impact of insider asle on return volatility of NASDAQ stocks. There has been considerable debate, e.g., French and Roll (1986), over whether market volatility is due to public information or private information-the latter gathered through costly search and only revealed through trading. Public information is composed of (1) marketwide public information such as regularly scheduled federal economic announcements (e.g., employment, GNP, leading indicators) and (2) company-specific public information such as dividend and earnings announcements. Policy makers and corporate insiders have a better access to marketwide private information (e.g., a new monetary policy decision made in the Federal Reserve Board meeting) and company-specific private information, respectively, compated to the general public. Ederington and Lee (1993) show that marketwide public information accounts for most of the observed volatility patterns in interest rate and foreign exchange futures markets. Company-specific public information is explored by Patell and Wolfson (1984) and Jennings and Starks (1985). They show that dividend and earnings announcements induce higher than normal volatility in equity prices. Kyle (1985), Admati and Pfleiderer (1988), Barclay, Litzenberger and Warner (1990), Foster and Viswanathan (1990), Back (1992), and Barclay and Warner (1993) show that the private information help by informed traders and revealed through trading influences market volatility. Cornell and Sirri (1992)' and Meulbroek (1992) investigate the actual insider trading activities in a tender offer case and the prosecuted illegal trading cased, respectively. This paper examines the aggregate and individual impact of marketwide information, company-specific public information, and company-specific private information on equity prices. Specifically, we use the thirty common stocks in the Dow Jones Industrial Average (DJIA) and twenty one National Association of Securities Dealers Automated Quotations (NASDAQ) common stocks to examine how their prices react to information. Marketwide information (public and private) is estimated by the movement in the Standard and Poors (S & P) 500 Index price for the DJIA stocks and the movement in the NASDAQ Composite Index price for the NASDAQ stocks. Divedend and earnings announcements are used as a subset of company-specific public information. The trading activity of corporate insiders (major corporate officers, members of the board of directors, and owners of at least 10 percent of any equity class) with an access to private information can be cannot legally trade on private information. Therefore, most insider transactions are not necessarily based on private information. Nevertheless, we hypothesize that market participants observe how insiders trade in order to infer any information that they cannot possess because insiders tend to buy (sell) when they have good (bad) information about their company. For example, Damodaran and Liu (1993) show that insiders of real estate investment trusts buy (sell) after they receive favorable (unfavorable) appraisal news before the information in these appraisals is released to the public. Price discovery in a competitive multiple-dealership market (NASDAQ) would be different from that in a monopolistic specialist system (NYSE). Consequently, we hypothesize that NASDAQ stocks are affected more by private information (or more precisely, insider trading) than the DJIA stocks. In the next section, we describe our choices of the fifty-one stocks and the public and private information set. We also discuss institutional differences between the NYSE and the NASDAQ market. In Section II, we examine the implications of public and private information for the volatility of daily returns of each stock. In Section III, we turn to the question of the relative importance of individual elements of our information set. Further analysis of the five DJIA stocks and the four NASDAQ stocks that are most sensitive to earnings announcements is given in Section IV, and our results are summarized in Section V.

• Journal of the Korean Geographical Society
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• v.40 no.3 s.108
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• pp.296-309
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• 2005

In this study, we investigated the change of future land-surface and relationships of land-surface change with geo-spatial information, using a Bayesian prediction model based on a likelihood ratio function, for analysing the land-surface change of the Gongju area. We classified the land-surface satellite images, and then extracted the changing area using a way of post classification comparison. land-surface information related to the land-surface change is constructed in a GIS environment, and the map of land-surface change prediction is made using the likelihood ratio function. As the results of this study, the thematic maps which definitely influence land-surface change of rural or urban areas are elevation, water system, population density, roads, population moving, the number of establishments, land price, etc. Also, thematic maps which definitely influence the land-surface change of forests areas are elevation, slope, population density, population moving, land price, etc. As a result of land-surface change analysis, center proliferation of old and new downtown is composed near Gum-river, and the downtown area will spread around the local roads and interchange areas in the urban area. In case of agricultural areas, a small tributary of Gum-river or an area of local roads which are attached with adjacent areas showed the high probability of change. Most of the forest areas are located in southeast and from this result we can guess why the wide chestnut-tree cultivation complex is located in these areas and the capability of forest damage is very high. As a result of validation using a prediction rate curve, a capability of prediction of urban area is $80\%$, agriculture area is $55\%$, forest area is $40\%$ in higher $10\%$ of possibility which the land-surface change would occur. This integration model is unsatisfactory to Predict the forest area in the study area and thus as a future work, it is necessary to apply new thematic maps or prediction models In conclusion, we can expect that this way can be one of the most essential land-surface change studies in a few years.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.45-67
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• 2016

Given the recent development of smart devices, users are producing, sharing, and acquiring a variety of information via the Internet and social network services (SNSs). Because users tend to use multiple media simultaneously according to their goals and preferences, domestic SNS users use around 2.09 media concurrently on average. Since the information provided by such media is usually textually represented, recent studies have been actively conducting textual analysis in order to understand users more deeply. Earlier studies using textual analysis focused on analyzing a document's contents without substantive consideration of the diverse characteristics of the source medium. However, current studies argue that analytical and interpretive approaches should be applied differently according to the characteristics of a document's source. Documents can be classified into the following types: informative documents for delivering information, expressive documents for expressing emotions and aesthetics, operational documents for inducing the recipient's behavior, and audiovisual media documents for supplementing the above three functions through images and music. Further, documents can be classified according to their contents, which comprise facts, concepts, procedures, principles, rules, stories, opinions, and descriptions. Documents have unique characteristics according to the source media by which they are distributed. In terms of newspapers, only highly trained people tend to write articles for public dissemination. In contrast, with SNSs, various types of users can freely write any message and such messages are distributed in an unpredictable way. Again, in the case of newspapers, each article exists independently and does not tend to have any relation to other articles. However, messages (original tweets) on Twitter, for example, are highly organized and regularly duplicated and repeated through replies and retweets. There have been many studies focusing on the different characteristics between newspapers and SNSs. However, it is difficult to find a study that focuses on the difference between the two media from the perspective of supply and demand. We can regard the articles of newspapers as a kind of information supply, whereas messages on various SNSs represent a demand for information. By investigating traditional newspapers and SNSs from the perspective of supply and demand of information, we can explore and explain the information dilemma more clearly. For example, there may be superfluous issues that are heavily reported in newspaper articles despite the fact that users seldom have much interest in these issues. Such overproduced information is not only a waste of media resources but also makes it difficult to find valuable, in-demand information. Further, some issues that are covered by only a few newspapers may be of high interest to SNS users. To alleviate the deleterious effects of information asymmetries, it is necessary to analyze the supply and demand of each information source and, accordingly, provide information flexibly. Such an approach would allow the value of information to be explored and approximated on the basis of the supply-demand balance. Conceptually, this is very similar to the price of goods or services being determined by the supply-demand relationship. Adopting this concept, media companies could focus on the production of highly in-demand issues that are in short supply. In this study, we selected Internet news sites and Twitter as representative media for investigating information supply and demand, respectively. We present the notion of News Value Index (NVI), which evaluates the value of news information in terms of the magnitude of Twitter messages associated with it. In addition, we visualize the change of information value over time using the NVI. We conducted an analysis using 387,014 news articles and 31,674,795 Twitter messages. The analysis results revealed interesting patterns: most issues show lower NVI than average of the whole issue, whereas a few issues show steadily higher NVI than the average.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.11a
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• pp.225-227
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• 2018

This research paper examines the history and present of 'temporary passengers' prescribed in Paragraph 9 of Article 5 of the Ships Safety Act Enforcement Regulations and suggests improvement plans referring to the examples of legislation of other countries. In 2015, Ministry of Ocean and Fisheries made authoritative interpretation that Paragraph 9 of Article 5 of the Ships Safety Act Enforcement Regulations, which prescribes special cargo drivers such as agricultural, marine or livestock vehicles as temporary passengers, is applied only to passenger ships and not to cargo ships such including Ro-Ro cargo ships. As the authoritative interpretation of the Ministry does not agree with not only the traditional interpretational methodology but also the interpretational methodology that are commonly used today, it lacks logical basis and looks unpersuasive. Paragraph 9 of Article 5 of the Ships Safety Act Enforcement Regulations can be applied not only on passenger ships but also on cargo ships. Also in case of Ro-Ro cargo ships, it is logically contradictory and against fairness not to acknowledge special cargo vehicle drivers as temporary passengers when there is no problem with safe navigation and safety of passengers on board even when the sailor, the sailor's family and the ship owner may be acknowledged as temporary passengers. To avoid unnecessary disputes and lawsuits, improvement plans using theory of legislation through statutory reform is more desirable. Therefore, the P aragraph should be amended to "Supercargo who deals with cargo that requires special care due to the characteristics of the cargo, such as transportation vehicles for agricultural products, marine products, livestock, explosives or flammable materials (drivers can serve as supercargos)" to reflect the distinct characteristics of cargo and ship navigation in Korea including the current distribution system, while setting an objective standard based on common sense of ordinary people and not on arbitrary interpretation.

• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.383-392
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• 2007

Karstic features and mining-related cavities not only lead to severe restrictions in land utilizations, but also constitute serious concern about geohazard and groundwater contamination. A microgravity survey was applied for detecting, mapping and monitoring karstic cavities in the test site at Muan prepared by KIGAM. The gravity data were collected using an AutoGrav CG-3 gravimeter at about 800 stations by 5 m interval along paddy paths. The density distribution beneath the profiles was drawn by two dimensional inversion based on the minimum support stabilizing functional, which generated better focused images of density discontinuities. We also imaged three dimensional density distribution by growing body inversion with solution from Euler deconvolution as a priori information. The density image showed that the cavities were dissolved, enlarged and connected into a cavity network system, which was supported by drill hole logs. A time-lapse microgravity was executed on the road in the test site for monitoring the change of the subsurface density distribution before and after grouting. The data were adjusted for reducing the effects due to the different condition of each survey, and inverted to density distributions. They show the change of density structure during the lapsed time, which implies the effects of grouting. This case history at the Muan test site showed that the microgravity with accuracy and precision of ${\mu}Gal$ is an effective and practical tool for detecting, mapping and monitoring the subsurface cavities.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.77-92
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• 2014

Recently, numerous documents including unstructured data and text have been created due to the rapid increase in the usage of social media and the Internet. Each document is usually provided with a specific category for the convenience of the users. In the past, the categorization was performed manually. However, in the case of manual categorization, not only can the accuracy of the categorization be not guaranteed but the categorization also requires a large amount of time and huge costs. Many studies have been conducted towards the automatic creation of categories to solve the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorizing complex documents with multiple topics because the methods work by assuming that one document can be categorized into one category only. In order to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, they are also limited in that their learning process involves training using a multi-categorized document set. These methods therefore cannot be applied to multi-categorization of most documents unless multi-categorized training sets are provided. To overcome the limitation of the requirement of a multi-categorized training set by traditional multi-categorization algorithms, we propose a new methodology that can extend a category of a single-categorized document to multiple categorizes by analyzing relationships among categories, topics, and documents. First, we attempt to find the relationship between documents and topics by using the result of topic analysis for single-categorized documents. Second, we construct a correspondence table between topics and categories by investigating the relationship between them. Finally, we calculate the matching scores for each document to multiple categories. The results imply that a document can be classified into a certain category if and only if the matching score is higher than the predefined threshold. For example, we can classify a certain document into three categories that have larger matching scores than the predefined threshold. The main contribution of our study is that our methodology can improve the applicability of traditional multi-category classifiers by generating multi-categorized documents from single-categorized documents. Additionally, we propose a module for verifying the accuracy of the proposed methodology. For performance evaluation, we performed intensive experiments with news articles. News articles are clearly categorized based on the theme, whereas the use of vulgar language and slang is smaller than other usual text document. We collected news articles from July 2012 to June 2013. The articles exhibit large variations in terms of the number of types of categories. This is because readers have different levels of interest in each category. Additionally, the result is also attributed to the differences in the frequency of the events in each category. In order to minimize the distortion of the result from the number of articles in different categories, we extracted 3,000 articles equally from each of the eight categories. Therefore, the total number of articles used in our experiments was 24,000. The eight categories were "IT Science," "Economy," "Society," "Life and Culture," "World," "Sports," "Entertainment," and "Politics." By using the news articles that we collected, we calculated the document/category correspondence scores by utilizing topic/category and document/topics correspondence scores. The document/category correspondence score can be said to indicate the degree of correspondence of each document to a certain category. As a result, we could present two additional categories for each of the 23,089 documents. Precision, recall, and F-score were revealed to be 0.605, 0.629, and 0.617 respectively when only the top 1 predicted category was evaluated, whereas they were revealed to be 0.838, 0.290, and 0.431 when the top 1 - 3 predicted categories were considered. It was very interesting to find a large variation between the scores of the eight categories on precision, recall, and F-score.