• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.47
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• pp.263-298
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• 2010

The global trading system is vulnerable to terrorist exploitation while the international trade is an essential element for the economic development. Customs has a unique role in the international trade to provide increased security while ensuring facilitation of the legitimate flow of goods and the role of Customs has become more and more indispensable these days. In response to this trend, the World Customs Organization(WCO), the organization of more than 170 Customs administrations all over the world, adopted an international framework("SAFE Framework") in 2005, which includes the Authorized Economic Operator(AEO) concept, whereby a party involved in the international movement of goods would be approved by Customs as complying with the supply chain security standards, and given benefits, such as simplified Customs procedure and less Customs intervention. In this stream, the Japanese government has developed and promoted AEO Program in close cooperation with the business sector, aiming at ensuring security while facilitating legitimate trade. For that purpose, Japan Customs, as a main entity in the field of international trade, has developed comprehensive AEO program with combination of programs for importers, exporters, warehouse operators, Customs brokers and logistics operators, such as forwarders and carriers, which are consistent with the "SAFE Framework" developed by the WCO. The purpose of this paper aims to analyse the introduction plans of AEO program for the trade security and trade facilitation with Japanese AEO system.

• Journal of Hydrogen and New Energy
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• v.21 no.3
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• pp.241-247
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• 2010

An Energy Efficiency Resource Standards (EERS) is a simple, market-based mechanism to encourage more efficient generation, transmission, and use of electricity, natural gas and heat. An EERS consists of electric, gas and/or heating energy savings targets for utilities, often with flexibility to achieve the target through a market-based trading system. In this paper, we make persons acquainted with EERS programs of foreign countries in these days. And we analyze domestic energy demand side management (DSM) programs in order to introduce an EERS program into the country successfully. Energy efficiency potential calculated in 2007 is one of the important factors for establishing an EERS program domestically. This study may provide basic data to set the amount of energy saving when an EERS program would be phased in.

• Asia-Pacific Journal of Business
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• v.11 no.2
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• pp.15-25
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• 2020

Purpose - The purpose of this study is to examine whether the change of settlement procedures have an impact on the distribution of day of the week effect in the UK and French markets or not. U.K and France changed their systems from fixed settlement date systems to fixed settlement lag systems Design/methodology/approach - This study adopted the data of the specific stock market indices such as FTSE 100 in the U.K market and FRCAC 40 in the French market, This study constructs a test of the differences in mean returns across the days of the week by computing the regression equations for each country index. Findings - First, this study found that the evolving settlement procedures in stock exchanges have an effect on stock return of day of the week. Second, long-run improvements in market efficiency may have diminished the effects of certain anomalies in recent periods. Improvements in market efficiency and evolving settlement systems may cause the disappearance of the weekend effect. Research implications or Originality - The Implication of this study is that recent settlement systems contributed to the disappearance of the weekend effect and explains improvements in market efficiency and diminishments of market anomaly. This study may be the first study which examines whether evolving settlement systems have an effect on the disappearance of the weekend effect in the market or not.

• Management & Information Systems Review
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• v.30 no.2
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• pp.237-255
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• 2011

This empirical study is focused on practical application of Range-Based Volatility which is estimated by opening, high, low, closing price of overall asset. Especially proper forecasting period is what I want to know. There is four useful Range-Based Volatility(RV) such as Parkinson(1980; PK), Garman and Klass(1980; GK) Rogers and Satchell(1991; RS), Yang and Zhang(2008; YZ). So, four RV of KOPSI 200 index during 2000.5.22-2009.9.18 was used for empirical test. The emprirical result as follows. First, the best RV which shows the best forecasting performance is PK volatility among PK, GK, RS, YZ volatility. According to estimating period forcasting performance of RV shows delicate difference. PK has better performance in the period with financial crisis of sub-prime mortgage loan. if not, RS is better. Second, almost result shows better performance on forecasting volatility without sub-prime mortgage loan period. so we can say that forecasting performance is lower when historical volatiltiy is comparatively high. Finally, I find that longer estimating period in AR(1) and MA(1) model can reduce forecasting error. More interesting point is that the result shows rapid decrease form 60 days to 90 days and there is no more after 90 days. So, if we forecast the volatility using Range-Based volaility it is better to estimate with 90 trading period or over 90 days.

• Microbiology and Biotechnology Letters
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• v.45 no.2
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• pp.162-167
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• 2017

For the production of bioethanol by the synchronous saccharification and fermentation (SSF) process, bio-capsule formation was attempted. Many saccharifying fungal strains and fermentative yeast strains were first screened. Aspergillus sp. BCNU 6200, Penicillium sp. BCNU 6201, and P. chrysogenum KACC 44363 were found to be excellent producers of saccharifying enzymes such as ${\alpha}$-amylase and glucoamylase. Saccharomyces cerevisiae IFO-M-07 showed the highest ethanol productivity among the tested strains. Secondly, we determined the optimal conditions for pellet formation, and those for bio-capsule formation. All the tested fungal strains formed pellets, and the optimal conditions for bio-capsule formation were $28^{\circ}C$ and 120 rpm. Lastly, SSF process was performed using a bio-capsule. An ethanol yield of 3.9% was achieved by using the Aspergillus sp. BCNU 6200 bio-capsule (Aspergillus sp. BCNU 6200 + S. cerevisiae IFO-M-07) at $30^{\circ}C$ with shaking at 120 rpm during the 10 days of incubation. The results provide useful information on the application of a bio-capsule in bioethanol production under the SSF process.

• Korean Business Review
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• v.16
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• pp.169-184
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• 2003

IR(Investor Relation) is an active management activity to provide well balanced information to investors which can reduce asymmetry of information between investors and management. This activity could contribute to the long-term development of corporation with increased mutual trust between investors and management. Consequently, in these days, ill is widely recognized as an effective measure of securing corporate transparency, maximization corporate value, and stock-holder oriented management. The purpose of this study is to examine the effect of corporate IR activity on investment behavior as well as stock price. It is assumed that if asymmetry of information between investors and management is cured by active ill activity from a corporation, with more transparent and reliable information of the firm at hand investors would more actively involved in trading. Statistically speaking, I assumed that the more information provided by ill activities, the higher value of a corporation at the stock trading.

• Journal of Korea Port Economic Association
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• v.25 no.1
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• pp.63-86
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• 2009

With increasing uncertainty of energy market in the world, the policies for the energy resource security have become crucial Several countries with poor energy resource like Netherlands and Singapore have pursued the policy for becoming an oil hub in the region. Singapore has been an oil hub in East Asia for a long time not only because it is well located with a large number of countries exporting and importing oil but it has also pursued strong policies to become an oil hub while establishing favourable institutional, regulatory and business environment for accommodating major refineries and petro-chemical companies. However with growing trading volume of petroleum products in Northeast Asia and a record high price of oil in these days, the necessities of another oil hub in the region are considered in order to reap benefits of the security of economical and stable oil. South Korea is situated astride the main North Pacific shipping route, with deep water ports and proximity to Chinese and Japanese industrial centres that make tank terminal operators Ideal choices for the oil hub in Northeast Asia although it has several disadvantages such as lack of independent storage facilities, underdeveloped oil trading market and unfavourable business friendly climates etc. This study is focused on examining the globalization strategies of tank terminal operators such as Vopak, Oiltanking and Odfjell in order to suggest the policy implications for becoming an oil tub in Northeast Asia.

• 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.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.623-632
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• 2018

Both investors and researchers are attentive to the prediction of stock price movement directions since the accurate prediction plays an important role in strategic decision making on stock trading. According to previous studies, taken together, one can see that different factors are considered depending on stock markets and prediction periods. This paper aims to analyze what data mining techniques show better performance with some representative index and stock price datasets in the Korea stock market. In particular, extreme gradient boosting technique, proving itself to be the fore-runner through recent open competitions, is applied to the prediction problem. Its performance has been analyzed in comparison with other data mining techniques reported good in the prediction of stock price movement directions such as random forests, support vector machines, and artificial neural networks. Through experiments with the index/price datasets of 12 years, it is identified that the gradient boosting technique is the best in predicting the movement directions after 1 to 4 days with a few partial equivalence to the other techniques.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.48 no.5
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• pp.655-660
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• 2015

This study investigated the effects of freezing storage temperature and thawing time on the separation of leg meat of the red snow crab Chionoecetes japonicus. Crabs were stored at -20, -30, -40, or -50°C for 2 days and thawed for either 5, 10, 20, 30, or 40 seconds. While thawing, there were no significant differences in pH or acidity among the experimental groups, while the volatile basic nitrogen content increased continuously. The redness of samples stored at -20°C was higher than that of the other groups. The overall acceptance of samples stored at -20°C was also the best. These results demonstrate that no-heating methods may be useful for separating red snow crab leg meat.