• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.27-31
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• 2006

GNSS Services and Applications are today in permanent evolution in all the market sectors. This evolution comprises: ${\bullet}$ New constellations and systems, being GALILEO probably the most relevant example, but not the only one, as other regions of the world also dwell into developing their own elements (e.g. the Chinese Beidou system). ${\bullet}$ Modernisation of existing systems, as is the case of GPS and GLONASS ${\bullet}$ New Augmentation services, WAAS, EGNOS, MSAS, GRAS, GAGAN, and many initiatives from other regions of the world ${\bullet}$ Safety of Life services based on the provision of integrity and reliability of the navigation solutions through SBAS and GBAS systems, for aeronautical or maritime applications ${\bullet}$ New Professional applications, based on the unprecedented accuracies and integrity of the positioning and timing solutions of the new navigation systems with examples in science (geodesy, geophysics), Civil engineering (surveying, construction works), Transportation (fleet management, road tolling) and many others. ${\bullet}$ New Mass-market applications based on cheap and simple GNSS receivers providing accurate (meterlevel) solutions for daily personal navigation and information needs. Being on top of this evolving market requires an active participation on the key elements that drive the GNSS development. Early access to the new GNSS signals and services and appropriate testing facilities are critical to be able to reach a good market position in time before the next evolution, and this is usually accessible only to the large system developers as the US, Europe or Japan. Jumping into this league of GNSS developers requires a large investment and a significant development of technology, which may not be at range for all regions of the world. Bearing in mind this situation, MAGIC appears as a concept initiated by a small region within Europe with the purpose of fostering and supporting the development of advanced applications for the new services that can be enabled by the advent of SBAS systems and GALILEO. MAGIC is a low cost platform based on the application of technology developed within the EGNOS project (the SBAS system in Europe), which encompasses the capacity of providing real time EGNOS and, in the near future, GALILEO-like integrity services. MAGIC is designed to be a testing platform for safety of life and liability critical applications, as well as a provider of operational services for the transport or professional sectors in its region of application. This paper will present in detail the MAGIC concept, the status of development of the system within the Madrid region in Spain, the results of the first on-field demonstrations and the immediate plans for deployment and expansion into a complete SBAS+GALILEO regional augmentation system.

• Journal of the Korean Society of Floral Art and Design
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• no.40
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• pp.77-96
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• 2019

This study was conducted to grasp distribution of native plants in flower market and uses of native plants in floral decoration. This study was investigated native plants sold in flower market(2017.01-2017.12) and their monthly sales. Also, this study analyzed the use of native plants, frequency of native plants classified by form and color of native plants used for floral decoration in flower magazines 'Fleur' and 'The Flower'. Among 172 species distributed cut-flower, native plants in Korea flower market are only 24 species(14.0%). Number of filler flower(15 species) is more than other forms. Native plants used in 'Fleur' and 'The Flower' were 14 species(10.2%) and 17 species(9.6%), it is meaning that native plants were less used than foreign plants. The number of filler flower was the highest in both magazines, but form flower(299 works) in 'Fleur' and mass flower(571 works) in 'The Flower' are used most frequently. According to color analysis of native plants used for floral decoration, P(purple), PB(navy) and RP(reddish purple) were 57% of the total. It can be increased native plants uses in flower decoration with developing form and mass flower considering color preference.

• The Journal of Industrial Distribution & Business
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• v.2 no.2
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• pp.5-14
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• 2011

Opening agricultural market expansion, reduced purchases through wholesale markets, expanding the influence large retailers of consumer's market such as changes in the distribution system to the farmer's market conditions are changing rapidly. Because of this, retailers of the scaled and chain-store operations was centered on distribution environmental changes of the consumer market place. In producing area due to changes in market conditions in the agricultural production of in producing area distribution organization and the size distribution can not be put off no longer challenge is imminent. If it do not raise forces banded together, the producer is bound to remain as the weak. To support the distribution of this production was introduced in 2000 enable the Activation Project of in producing area distribution. Recent in producing area Changes of Agricultural conditions in order to cope with the Small-scale farmers and small individual farmers are becoming Scaled and specialized. Also, is specific to each item and regional is showing aspects. Government support for Activation Project of in producing area distribution is greatly improved, but in terms of competitiveness on the market still is showing the limitations. The most common of these problems, the market response if in producing area producer's organization and scale of the problem. Equipped for the purpose of consumer market place responsiveness unreasonable propelled outward from the Painter-sized weakens the organizational power. also, Difficult to succeed organizational size is a dissolution or anything within a few years, farmers around the best producer organizations, such as deviation occurs is exposed to a variety of issues. In this study, previous studies refer to the recent changes in agricultural retail environment, background and needs of organization·scaled, Determine the status of the domestic in producing area organizations and derived Problems, look into Domestic and overseas of in producing area organization with best practices for enhancing the competitiveness of the proposed improvement are intended to. In the future, in producing area distribution policy would like to provide direction to the development. The results of the study showed the follwing : 1) enhance utilization and orrganized through the diversification of the agricultural Collection systems. 2) Scaled to achieve through Items of specialized a wide area marketing. 3) Management operating units, such as installation and operating that overseas the best practices " Comite Economique Agricole Regional 'Fruits et Legumes' de Bretagne". 4) To establish a support system that in producing area distribution organization model development for appropriate domestic. In particular, in case of domestic in producing area distribution organization, through the analysis of various case study that a successful organization and scaled. The process of the various challenges arising in organizational scaled and generalization, and by the way he goes about trying to overcome is required. At the end of the study's limitations and future research directions suggested.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.187-201
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• 2011

KOSPI200 index is the Korean stock price index consisting of actively traded 200 stocks in the Korean stock market. Its base value of 100 was set on January 3, 1990. The Korea Exchange (KRX) developed derivatives markets on the KOSPI200 index. KOSPI200 index futures market, introduced in 1996, has become one of the most actively traded indexes markets in the world. Traders can make profit by entering a long position on the KOSPI200 index futures contract if the KOSPI200 index will rise in the future. Likewise, they can make profit by entering a short position if the KOSPI200 index will decline in the future. Basically, KOSPI200 index futures trading is a short-term zero-sum game and therefore most futures traders are using technical indicators. Advanced traders make stable profits by using system trading technique, also known as algorithm trading. Algorithm trading uses computer programs for receiving real-time stock market data, analyzing stock price movements with various technical indicators and automatically entering trading orders such as timing, price or quantity of the order without any human intervention. Recent studies have shown the usefulness of artificial intelligent systems in forecasting stock prices or investment risk. KOSPI200 index data is numerical time-series data which is a sequence of data points measured at successive uniform time intervals such as minute, day, week or month. KOSPI200 index futures traders use technical analysis to find out some patterns on the time-series chart. Although there are many technical indicators, their results indicate the market states among bull, bear and flat. Most strategies based on technical analysis are divided into trend following strategy and non-trend following strategy. Both strategies decide the market states based on the patterns of the KOSPI200 index time-series data. This goes well with Markov model (MM). Everybody knows that the next price is upper or lower than the last price or similar to the last price, and knows that the next price is influenced by the last price. However, nobody knows the exact status of the next price whether it goes up or down or flat. So, hidden Markov model (HMM) is better fitted than MM. HMM is divided into discrete HMM (DHMM) and continuous HMM (CHMM). The only difference between DHMM and CHMM is in their representation of state probabilities. DHMM uses discrete probability density function and CHMM uses continuous probability density function such as Gaussian Mixture Model. KOSPI200 index values are real number and these follow a continuous probability density function, so CHMM is proper than DHMM for the KOSPI200 index. In this paper, we present an artificial intelligent trading system based on CHMM for the KOSPI200 index futures system traders. Traders have experienced on technical trading for the KOSPI200 index futures market ever since the introduction of the KOSPI200 index futures market. They have applied many strategies to make profit in trading the KOSPI200 index futures. Some strategies are based on technical indicators such as moving averages or stochastics, and others are based on candlestick patterns such as three outside up, three outside down, harami or doji star. We show a trading system of moving average cross strategy based on CHMM, and we compare it to a traditional algorithmic trading system. We set the parameter values of moving averages at common values used by market practitioners. Empirical results are presented to compare the simulation performance with the traditional algorithmic trading system using long-term daily KOSPI200 index data of more than 20 years. Our suggested trading system shows higher trading performance than naive system trading.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• The Korean Journal of Air & Space Law and Policy
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• v.33 no.2
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• pp.3-34
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• 2018

Korea's air transport industry has a 70-year history since Korea National Airline was establishment in October 1948. Korea has 9 airlines which have international air transport business licenses, and as of 2017, air transport performance(Domestic & International) is ranked 8th in the world. Through analysis of Korea's air transport industry, this paper examines the essential problems of the domestic air transport industry and what policies and laws should be supplemented, and presents an "Policy Directions for the Air Transport Industry" that can continue to grow into a global aviation leading country in the future. Analysis of aviation statistics shows that the nation's air transport industry has a very high growth rate, and national airlines continue to invest in sustainable growth. Furthermore, new companies are also trying to enter the market. As of November 2018, four companies applied for licenses for international air transport business, one for international air transport business (cargo) license, and the Ministry of Land, Infrastructure and Transport is expected to decide whether to issue the license by first quarter of 2019. While some expect price reductions and consumer benefits through competition promotion, others worry about worsening airline financial structures and reducing safety investment due to competition. To sum up the problems of the nation's air transport industry, first, low-cost airlines focus only on attracting domestic demand, and thus have a weak foundation for continued growth. Second, the rapid growth in recent years has led to the lack of aviation professionals such as pilots and technicians and the saturation of slots at major airports. Third, since the financial soundness of airlines is not systematically managed, the financial situation of airlines can quickly deteriorate and the damage can be attributed to consumers. In order for the national airlines to continue to develop, the first is to focus on the endless demand of the global aviation market and to secure international competitiveness. Second, the government should support the airline infrastructure according to the size of the air transport industry, third, we will systematically nurture aviation experts who will lead the future of the nation's air transport industry, and finally, the government will have to continuously manage the financial status of airlines to prevent consumer damage in advance. Nowadays the air transport industry has become very competitive. Not only do airlines have to work hard for the sustainable development of national airlines, but all government agencies must support our airline companies in policy to win international competition.

• Journal of Navigation and Port Research
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• v.32 no.1
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• pp.109-114
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• 2008

This study is about the status and comparison of recreational scuba diving certification system in Southeast Asia countries. For the collection of the information, the contents of the numerous corresponding Internet sites were utilized, related documents were surveyed. And to supplement the information extensive interviews were held with the representatives of tourism department of many countries as well as staffs of diving associations, resort operators and diving instructors during various 2007 Dive Expos held in Southeast countries. In this paper, the relation between scuba certification and international standards were introduced for better understanding of the certification system. The research result shows that the scuba diving industry plays an important role in their country's tourism and the certification market of the Southeast Asia has grown to be greater than 30% of the world total market. However due to the facts that the scuba activity is originated from the western world and the controlling headquarters of the most certification agency are also located there, Southeast countries cannot take any leading roles in the scuba diving policies and systematic issues. Accordingly any modifications or improvements are expected to be very difficult. Also while Europeans and Americans have launched the programs and organizations for the quality assurance by cooperating with the international standards, but no such activity has yet appeared on the surface in Southeast Asia. According to the investigation the necessity will become bigger in near future.

• Parasites, Hosts and Diseases
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• v.30 no.3
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• pp.157-162
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• 1992

Although the sea eel (Astroconger myriaster) is suspected as one of the most important fish host for human anisakiasis in Korea, no report has been made on the infection status of the sea eel with anisakid larvae. In the present study, 26 sea eels (Astroconger myriaster) were purchased from the Noryangjin 6sh market in Seoul, and anisakid larvae were collected from their viscera, muscle, head and skin. The collected larvae were classified by their morphological types. A total of 1,351 anisakid larvae were collected from 15 of 26 fish examined. Among them, 1,269 were recovered from the viscera, 66 from the muscle, and 16 from the head and skin. Morphologically, most of the anisakids were classified into 6 known larval types, Anisakis type I (564 larvae) of Berland(1961) , Contracaecum type A(409) and type D(5) of Koyama et at. (1969), Contracaecum type C'(83) and type D'(117) of Chai et at. (1986), and Contracaecum type V(1) of Yamaguti (1935). Remaining 172 specimens were new in the available literature, hence, designated as Centracaecum type A'(new type). The present results revealed that the sea eels caught in the Korean waters are heavily infected with anisakid larvae, not only in their viscera but also in the muscle, and Anisakis type I was the most common among the 7 larval types.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.8
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• pp.679-686
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• 2018

In previous paper[1], the authors had compared the current status of European and US rotorcraft development status. In this paper, more detailed procedures have been studied how the European rotorcraft technologies are developed preparing for 21 st century to be more competitive to US. For the systematic procedure to develop next generation aviation technologies including rotorcraft, the pan-European organization, ACARE, was established, and proposed major research agenda for next generation aviation technologies and businesses. Based on the proposed research agenda, all the R&D programs supported by EU are reorganized to be more efficient and competitive. The procedures for the rotorcraft technologies are, first, cabin noise/vibration reduction program (FRIENDCOPTER), second, core technologies to increase of rotor efficiencies and reduce rotor noise (GRC), and then finally to develop fast/long-range next generation rotorcraft (Fast Rotorcraft). As mentioned in previously, all the R&D procedure has to satisfy basic research agenda especially the environmental impact. With theses procedure, the European rotorcraft business had successful achievements not only in current and future market share, but also preparing for next generation rotorcraft platform such as compound and tilt-rotor rotorcraft satisfying market needs.