• Title/Summary/Keyword: process margin

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Geochemical Characteristics of Precambrian, Jurassic and Cretaceous Granites in Korea (한국(韓國)에 분포(分布)하는 선(先)캠브리아기(紀), 쥬라기(紀) 및 백악기화강암(白堊紀花崗岩)의 지화학적(地化學的) 특징(特徵))

  • Hong, Young Kook
    • Economic and Environmental Geology
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    • v.20 no.1
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    • pp.35-60
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    • 1987
  • The geochemical characteristics including minerals, major and trace elements chemistries of the Proterozoic, Jurassic and Cretaceous granites in Korea are systematically summarized and intended to decipher the origin and crystallization process in connection with the tectonic evolution. The granites in Korea are classified into three different ages of the granites with their own distinctive geochemical patterns: 1) Proterozoic granitoids; 2) Jurassic granites(cratonic and mobile belt); 3) Cretaceous-Tertiary granites. The Proterozoic granite gneisses (I-type and ilmenite-series) formed by metamorphism of the geochemically evolved granite protolith. The Proterozoic granites (S-type and ilmenite-series) produced by remobilization of sialic crust. The Jurassic granites (S-type and ilmenite-series) were mainly formed by partial melting of crustal materials, possibly metasedimentary rocks. The Cretaceous granites (I-type and magnetite-series) formed by fractional crystallization of parental magmas from the igneous protolith in the lower crust or upper mantle. The low temperature ($315{\sim}430^{\circ}C$) and small temperature variations (${\pm}20{\sim}30^{\circ}C$) in the cessation of exsolution of perthites for the Proterozoic and Jurassic granites might have been caused by slow cooling of the granites under regional metamorphic regime. The high ($520^{\circ}C$) and large temperature variations (${\pm}110^{\circ}C$) of perthites for the Cretaceous granites postulate that the rapid cooling of the granitic magma. In terms of the oxygen fugacity during the feldspar crystallization in the granite magmas, the Jurassic mobile belt granites were crystallized in the lowest oxygen fugacity condition among the Korean granites, whereas the Cretaceous granites in the Gyeongsang basin at the high oxygen fugacity condition. The Jurassic mobile belt granites are located at the Ogcheon Fold Belt, resulting by closing-collision situation such as compressional tectonic setting, and emplaced into a Kata-Mesozonal ductile crust. The Jurassic cratonic granites might be more evolved either during intrusion through thick crust or owing to lower degree of partial melting in comparison with the mobile belt granites. The Cretaceous granites are possibly comparable with a continental margin of Andinotype. Subduction of the Kula-Pacific ridge provided sufficient heat and water to trigger remelting at various subcrustal and lower crustal igneous protoliths.

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Negligence theory of Aviation accident with reference to the japanese aviation accident precedent (항공 사고에서의 과실 이론 - 일본 항공 사고 판례를 중심으로 -)

  • Hwang, Ho-Won;Ham, Se-Hun
    • The Korean Journal of Air & Space Law and Policy
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    • v.23 no.2
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    • pp.115-136
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    • 2008
  • The development of the aviation technology is beyond the people's imagination. For example, with some exaggeration, If the autopilot engage upon take off, You will realize that you are on the centerline of the foggy JFK runway 13R after 15 hours with only once or twice of intervention. But the more aviation technology develops, the more responsible the pilot will be who has the final authority of the aviation safety. In the JAL 706 accident caused by unidentified reason, the pilot increased pitch abruptly and overrode the control from the autopilot. The result of this process made the death of a flight attendant and some injuries of a few passengers. The district court found the pilot not guilty at the first trial on the ground that the control override was not connected to the possibility of foresight and avoidance of the human death. The pilot was proved to be innocent through the analysis of the DFDR and ADAS that the override did not precede the unidentified pitch up motion. The judicial precedent related to aviation accidents in Korea requires pilots' absolute and extended care compared to the ordinarily prudent or reasonably careful behaviors in the vehicle and medical accidents. Although there is some controversy about the standard care, the care required in the actual operation of high tech aircraft by a pilot should include objective and standard care and be judged by analysis of the scientific data. Although the pilot maintained the unusual hi speed that doesn't have safety margin and descended under turbulence in case of the JAL 706 accident, the court negatived its relation to the cause of pitch up. Also, the override of the control after initial pitch up might have caused the possibility of the death and injury, but the court denied it. Because of this complex cause of the aviation accidents, it is important for a court to figure out the core reason of the event and casual relationship with the pilot Now, It is required that the judgement of negligence in the aviation accidents should include an objective care with scientific data from simulated circumstances(or a simulator) as the Japanese court not from the theory of vehicle's negligence.

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Geophysical Studies on Major Faults in the Gyeonggi Massif : Gravity and Electrical Surveys In the Gongju Basin (경기육괴내 주요 단층대의 지구물리학적 연구: 공주분지의 중력 및 지전기 탐사)

  • Kwon Byung-Doo;Jung Gyung-Ja;Baag Chang-Eob
    • The Korean Journal of Petroleum Geology
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    • v.2 no.2 s.3
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    • pp.43-50
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    • 1994
  • The geologic structure of Gongju Basin, which is a Cretaceous sedimentary basin located on the boundary of Gyeonggi Massif and Ogcheon Belt, is modeled by using gravity data and interpreted in relation with basin forming tectonism. The electrical survey with dipole-dipole array was also conducted to uncover the development of fractures in the two fault zones which form the boundaries of the basin. In the process of gravity data reduction, the terrain correction was performed by using the conic prism model, which showed better results specially for topography having a steep slope. The gravity model of the geologic structure of Gongju basin is obtained by forward modeling based on the surface geology and density inversion. It reveals that the width of the basin at its central part is about $4{\cal}km$ and about $2.5{\cal}km$ at the southern part. The depth of crystalline basement beneath sedimentary rocks of the basin is about $700{\~}400{\cal}m$ below the sea level and it is thinner in the center than in margin. The fault of the southeastern boundary appears more clearly than that of the northwestern boundary, and its fracture zone may extended to the depth of more than $1{\cal}km$. Therefore, it is thought that the tectonic movement along the fault in the southeastern boundary was much stronger. These results coincide with the appearance of broad low resistivity anomaly at the southeastern boundary of the basin in the resistivity section. The fracture zones having low density are also recognized inside the basin from the gravity model. The swelling feature of basement and the fractures in sedimentary rocks of the basin suggest that the compressional tectonic stress had also involved after the deposition of the Cretaceous sediments.

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Ensemble Learning with Support Vector Machines for Bond Rating (회사채 신용등급 예측을 위한 SVM 앙상블학습)

  • Kim, Myoung-Jong
    • Journal of Intelligence and Information Systems
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    • v.18 no.2
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    • pp.29-45
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    • 2012
  • Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

Factors Affecting International Transfer Pricing of Multinational Enterprises in Korea (외국인투자기업의 국제이전가격 결정에 영향을 미치는 환경 및 기업요인)

  • Jun, Tae-Young;Byun, Yong-Hwan
    • Korean small business review
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    • v.31 no.2
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    • pp.85-102
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    • 2009
  • With the continued globalization of world markets, transfer pricing has become one of the dominant sources of controversy in international taxation. Transfer pricing is the process by which a multinational corporation calculates a price for goods and services that are transferred to affiliated entities. Consider a Korean electronic enterprise that buys supplies from its own subsidiary located in China. How much the Korean parent company pays its subsidiary will determine how much profit the Chinese unit reports in local taxes. If the parent company pays above normal market prices, it may appear to have a poor profit, even if the group as a whole shows a respectable profit margin. In this way, transfer prices impact the taxable income reported in each country in which the multinational enterprise operates. It's importance lies in that around 60% of international trade involves transactions between two related parts of multinationals, according to the OECD. Multinational enterprises (hereafter MEs) exert much effort into utilizing organizational advantages to make global investments. MEs wish to minimize their tax burden. So MEs spend a fortune on economists and accountants to justify transfer prices that suit their tax needs. On the contrary, local governments are not prepared to cope with MEs' powerful financial instruments. Tax authorities in each country wish to ensure that the tax base of any ME is divided fairly. Thus, both tax authorities and MEs have a vested interest in the way in which a transfer price is determined, and this is why MEs' international transfer prices are at the center of disputes concerned with taxation. Transfer pricing issues and practices are sometimes difficult to control for regulators because the tax administration does not have enough staffs with the knowledge and resources necessary to understand them. The authors examine transfer pricing practices to provide relevant resources useful in designing tax incentives and regulation schemes for policy makers. This study focuses on identifying the relevant business and environmental factors that could influence the international transfer pricing of MEs. In this perspective, we empirically investigate how the management perception of related variables influences their choice of international transfer pricing methods. We believe that this research is particularly useful in the design of tax policy. Because it can concentrate on a few selected factors in consideration of the limited budget of the tax administration with assistance of this research. Data is composed of questionnaire responses from foreign firms in Korea with investment balances exceeding one million dollars in the end of 2004. We mailed questionnaires to 861 managers in charge of the accounting departments of each company, resulting in 121 valid responses. Seventy six percent of the sample firms are classified as small and medium sized enterprises with assets below 100 billion Korean won. Reviewing transfer pricing methods, cost-based transfer pricing is most popular showing that 60 firms have adopted it. The market-based method is used by 31 firms, and 13 firms have reported the resale-pricing method. Regarding the nationalities of foreign investors, the Japanese and the Americans constitute most of the sample. Logistic regressions have been performed for statistical analysis. The dependent variable is binary in that whether the method of international transfer pricing is a market-based method or a cost-based method. This type of binary classification is founded on the belief that the market-based method is evaluated as the relatively objective way of pricing compared with the cost-based methods. Cost-based pricing is assumed to give mangers flexibility in transfer pricing decisions. Therefore, local regulatory agencies are thought to prefer market-based pricing over cost-based pricing. Independent variables are composed of eight factors such as corporate tax rate, tariffs, relations with local tax authorities, tax audit, equity ratios of local investors, volume of internal trade, sales volume, and product life cycle. The first four variables are included in the model because taxation lies in the center of transfer pricing disputes. So identifying the impact of these variables in Korean business environments is much needed. Equity ratio is included to represent the interest of local partners. Volume of internal trade was sometimes employed in previous research to check the pricing behavior of managers, so we have followed these footsteps in this paper. Product life cycle is used as a surrogate of competition in local markets. Control variables are firm size and nationality of foreign investors. Firm size is controlled using dummy variables in that whether or not the specific firm is small and medium sized. This is because some researchers report that big firms show different behaviors compared with small and medium sized firms in transfer pricing. The other control variable is also expressed in dummy variable showing if the entrepreneur is the American or not. That's because some prior studies conclude that the American management style is different in that they limit branch manger's freedom of decision. Reviewing the statistical results, we have found that managers prefer the cost-based method over the market-based method as the importance of corporate taxes and tariffs increase. This result means that managers need flexibility to lessen the tax burden when they feel taxes are important. They also prefer the cost-based method as the product life cycle matures, which means that they support subsidiaries in local market competition using cost-based transfer pricing. On the contrary, as the relationship with local tax authorities becomes more important, managers prefer the market-based method. That is because market-based pricing is a better way to maintain good relations with the tax officials. Other variables like tax audit, volume of internal transactions, sales volume, and local equity ratio have shown only insignificant influence. Additionally, we have replaced two tax variables(corporate taxes and tariffs) with the data showing top marginal tax rate and mean tariff rates of each country, and have performed another regression to find if we could get different results compared with the former one. As a consequence, we have found something different on the part of mean tariffs, that shows only an insignificant influence on the dependent variable. We guess that each company in the sample pays tariffs with a specific rate applied only for one's own company, which could be located far from mean tariff rates. Therefore we have concluded we need a more detailed data that shows the tariffs of each company if we want to check the role of this variable. Considering that the present paper has heavily relied on questionnaires, an effort to build a reliable data base is needed for enhancing the research reliability.