• Proceedings of the Safety Management and Science Conference
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• 2005.05a
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• pp.379-392
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• 2005

The size of state in Korea is like Israel, this country's venture capital is ruled by government. This venture capital's character is below: the concentration on research of venturer affect positively at quality of products. This paper lies with venture capital's risk character & performance. The results show that Korean venture capitals have lager unsystematic risk than systematic risk, which implies they specialize in specific business and/or regional areas instead of diversification. The Sharpe & Jensen measures reveal that the performances of Korean venture capitals are very low relative to even the market portfolio(Kospi) and Kosdaq Venture Index. Contrary to this, Venture firm's performance according to Entrepreneurship will cause to push up stock price.

• Journal of the Korean Institute of Gas
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• v.25 no.1
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• pp.30-39
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• 2021

Natural gas is globally emerging as an important energy source for environmental, political and regional reasons. In Korea, natural gas imported from oversea natural gas resources as a LNG, it is increased for an applications as a fuel and feedstock which replace the coal and nuclear energy. Because it is relied on the import market in Korea, it is very important to analyze the security for supply. Therefore, this study suggested a method for reducing supply risk and for providing stable supply and demand through risk analysis of Korea's import structure. In order to reduce the supply risk, the concentration of importing countries should be lowered and it is necessary to lower the proportion of countries with relatively low GSSI and increase the imports from Russia. Finally increasing the number of importing countries or maintaining friendly relations with countries where the supply is stable could give us the positive impact in terms of total GSSI.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.57-62
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• 2023

This research is a comparative analysis of the U.S. S&P 500 index using the volatility breakout strategy against the Buy and Hold approach. The volatility breakout strategy is a trading method that exploits price movements after periods of relative market stability or concentration. Specifically, it is observed that large price movements tend to occur more frequently after periods of low volatility. When a stock moves within a narrow price range for a while and then suddenly rises or falls, it is expected to continue moving in that direction. To capitalize on these movements, traders adopt the volatility breakout strategy. The 'k' value is used as a multiplier applied to a measure of recent market volatility. One method of measuring volatility is the Average True Range (ATR), which represents the difference between the highest and lowest prices of recent trading days. The 'k' value plays a crucial role for traders in setting their trade threshold. This study calculated the 'k' value at a general level and compared its returns with the Buy and Hold strategy, finding that algorithmic trading using the volatility breakout strategy achieved slightly higher returns. In the future, we plan to present simulation results for maximizing returns by determining the optimal 'k' value for automated trading of the S&P 500 index using artificial intelligence deep learning techniques.

• Environmental and Resource Economics Review
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• v.20 no.4
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• pp.761-796
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• 2011

The purpose of this paper is to derive fuel mix of electricity generating system with the lowest cost considering energy security and climate change mitigations as the target of energy policy. Energy Security Price Index(ESPI), based on the measure of market concentration in fossil fuel market and political risk of exporting countries, is chosen to assess the level of energy security. The methodology of Energy Conservation Supply Curve(CSC) is applied to fuel mix to meet the carbon emission mitigation through increasing the alternatives participation and introduction of new technologies. These also represent an improvement on the level of energy security, having the complementarity between two objectives. The alternative measure for improving energy security is exploration and production(E&P) of fossil fuel for energy sufficiency. Fuel mix of electricity generating system to achieve certain objectives in 2020 can be derived with the lowest cost considering energy security and carbon emission mitigations.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.5
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• pp.384-390
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• 2005

The purpose of this study is to test empirically the effects of Entry Barriers for the stock prices of Venture Business using the Ohlson Model which is modifying and extending in terms of growth and the potential growth energy. Because the traditional Ohlson model(1995) on which the firm's value is determined only based on abnormal earnings and book value have numerous limitations when we evaluate the value of venture Businesses with high technology and new emerging market. In order to overcome these limitations, We can introduce items of net sales growth ratios and industrial property-to-net asset ratios into as proxy variables of the growth and potential growth energy. In the process of analyzing these research tests, we have set three kinds of hypotheses and tested then empirically compared with KOSDAQ ordinary listing business and KOSDAQ venture businesses between long-term analysis and short-term analysis. According to the degree of concentration reflecting HHI index, our empirical research were performed in depth. Therefore, the results of this study show us that all three kinds of Hypotheses are accepted.

• Journal of agriculture & life science
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• v.43 no.6
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• pp.117-127
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• 2009

There are worldwidely rising interests in food cluster as it has been perceived as a strategy for improving the competitiveness of food industry. This paper examines the potential of food industry at Gyeongsangnam-do for a regional clustering in terms of five cluster indices. These indices include the absolute size, the relative size of food industry, the level of its concentration, specialization, and market power exertion as an industrial cluster. The result shows that food industry at Gyeongsangnam-do has a potential for a regional clustering.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.27 no.3
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• pp.159-167
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• 2021

The need for biodegradable plastic continues to increase, improvement of physical properties is necessary for actual use in the market. In this study, composite film was produced by adding peroxide additives to bioplastic according to concentration to investigate changes in the melt index, elongation, morphology, and TGA of the composite film. The addition of peroxide compatibilizer showed superior elongation of film and TGA compared to those of control. The added amount of compatibilizer affected the extrusion process, and it was revealed that adding an appropriate amount of peroxidizer is important. Analysis of the composite film's morphology revealed a heterogeneous dispersion sequence due to different rates of crystallization depending on the resin, and surface physical properties were best in the group added with 4% peroxide. The results above showed that the test group added with 4% peroxide compatibilizer was superior in the production of composite biodegradable film.

• Journal of Korea Technology Innovation Society
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• v.17 no.1
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• pp.25-44
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• 2014

This study analyzed technological competitiveness of five major countries by using patent information that is typical intellectual property. Technological activity, patent competitiveness, market securement and patent concentration were designed as evaluation items for the technological competitiveness analysis, and the number of patent applications, family patents and triad patent families, and the paten concentration index were reflected as evaluation factors to be scored. For technologies to be analyzed, it referred to the energy harvesting technologies selected as 500 future technologies in the future technologic white paper 2013 published by KISTI. They were classified into technologies using thermoelectric, piezoelectric and photovoltaic elements, which are main detailed technologies of the energy harvesting technology, to investigate and analyze patent information for each detailed technology to understand their technological competitiveness. As a result, the United States ranked top with 75 and 70 points in the technology using thermoelectric and piezoelectric elements respectively, and Japan ranked top with 90 points in the energy harvesting technology using photovoltaic elements. It was analyzed that Korea held the second rank in the field using piezoelectric and photovoltaic elements, and the fifth in the technology using thermoelectric elements.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• Journal of Korea Port Economic Association
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• v.31 no.4
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• pp.75-89
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• 2015

This study examines 31 import and export cargo items handled in each port to investigate which items face the most competition among the ports and how many of them are transited to other ports. The study aims to suggest implications for the future port policy of Incheon Port. It was found that the volume concentration in the Western Coast region from 2005 to 2014 became increasingly decentralized. The decentralization began in earnest in 2009 in particular, and the value was 0.448 in 2014, indicating fierce competition among the regions. According to the static and dynamic positioning analyses results for Incheon Port, Pyeongtaek and Dangjin Port, and Gunsan Port, using BCG Matrix, the static positioning analysis showed that Incheon Port belongs to the 3rd quadrant (Cash Cows), Pyeongtaek and Dangjin Port belongs to the 2nd quadrant (Question Marks), and Gunsan Port belongs to the (Dogs) group. This implies that Incheon Port has maintained its position with large shares compared to those of other ports, despite its low growth rate. However, the market position and growth rate of Incheon Port decreased according to the dynamic positioning analysis results. The shift-share analysis results indicated that the volumes of Incheon Port and Gunsan Port were shifting to Pyeongtaek and Dangjin Port. Moreover, the ratio of absolute growth to potential growth of Incheon Port and Gunsan Port turned out to be significantly lower than that of Pyeongtaek and Dangjin Port, implying that Incheon Port and Gunsan Port are declining as compared to Pyeongtaek Port and Dangjin Port. According to the LQ index analysis results, specialized items from Incheon Port that do not overlap with other ports included the following ten items: meat, fish and crustaceans, bituminous coals, crude oil and petroleum, petroleum-refined products, plastic rubber and products, textiles, nonferrous metal and products, electric machinery, and aircrafts and ships. In particular, it was confirmed that the bulk cargo of Incheon Port was actually shifting to Pyeongtaek and Dangjin Port following the policy of re-establishing port functions.