• Journal of the Korea Institute of Building Construction
• /
• v.24 no.5
• /
• pp.565-575
• /
• 2024

This research was initiated to establish quality standards and testing methods for fine dust in aggregates, a component currently not regulated under the Korean Industrial Standards(KS) KS F 2527 for Concrete Aggregates. With limited existing research and no definitive quality or testing standards for fine dust, this study sought to provide a quantitative analysis of fine dust in aggregates and to set forth quality standards based on the dust content through a concrete performance evaluation. The experimental findings showed that the primary chemical constituents of the fine dust were aluminum oxide(Al₂O₃), iron oxide(Fe₂O₃), and silicon dioxide(SiO₂). It was observed that increasing levels of fine dust in the aggregates led to higher values of the fine dust index(Al₂O₃+Fe₂O₃). This escalation in the fine dust index corresponded with an increase in the unit water content of the concrete and a consequent decline in compressive strength. Based on these observations, a maximum allowable limit for the fine dust index in aggregates was proposed at 23%. This limit was derived from the correlation between fine dust content and a 15% reduction in compressive strength of standard concrete specimens. The proposed evaluation method for the fine dust index based on its content in aggregates is expected to enhance concrete performance and ensure structural stability. This contribution to the field addresses a significant gap in the standards and provides a foundation for further research and standardization in the construction materials industry.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2002.06a
• /
• pp.148-155
• /
• 2002

Multithreaded models improve the efficiency of parallel systems by combining inner parallelism, asynchronous data availability and the locality of von Neumann model. This model executes thread code which is generated by compiler and of which quality is given by the method of generation. But multithreaded models have the demerit that execution model is restricted to a specific platform. On the contrary, Java has the platform independency, so if we can translate from threads code to Java bytecode, we can use the advantages of multithreaded models in many platforms. Java executes Java bytecode which is intermediate language format for Java virtual machine. Java bytecode plays a role of an intermediate language in translator and Java virtual machine work as back-end in translator. But, Java bytecode which is translated from multithreaded models have the demerit that it is not secure. This paper, multhithread code whose feature of platform independent can execute in java virtual machine. We design and implement translator which translate from thread code of multithreaded code to Java bytecode and which check secure problems from Java bytecode.

• The Korean Journal of Air & Space Law and Policy
• /
• v.29 no.1
• /
• pp.3-32
• /
• 2014

Safety Management System is the aviation industry policy for while operating the aircraft, to ensure the safety crew, aircraft and passengers. For operating a safe aircraft, in order to establish the international technical standards, the International Civil Aviation Organization has established the Annex 19 of the Convention on International Civil Aviation. As a result, member country was supposed to be in accordance with the policy of the International Civil Aviation Organization, to accept the international standard of domestic air law. The South Korean government announced that it would promote active safety management strategy in primary aviation policy master plan of 2012. And, by integrating and state safety programmes(ssp) and safety management system(sms) for the safe management of Annex 19 is to enforce the policy on aviation safety standards. State safety programmes(ssp) is a system of activities for the aim of strengthening the safety and integrated management of the activities of government. State safety programmes(ssp) is important on the basis of the data of the risk information. Collecting aviation hazard information is necessary for efficient operation of the state safety programmes(ssp) Korean government must implement the strategy required to comply with aviation methods and standards of the International Civil Aviation Organization. Airlines, must strive to safety features for safety culture construction and improvement of safety management is realized. It is necessary to make regulations on the basis of the aviation practice, for aviation safety regulatory requirements, aviation safety should reflect the opinion of the aviation industry.

• Journal of Korea Port Economic Association
• /
• v.34 no.4
• /
• pp.1-16
• /
• 2018

The standard shift-share analysis decomposes a region's sectoral growth into three components: national, industry-mix, and regional-shift effects. Nevertheless, the three components of the traditional shift-share are not related to the behavior of the regional economies that are neighbors of the region under analysis. We incorporate a spatial structure within this basic formulation, and consider spatial interaction in the decomposition analysis. Daesan Port's export grew steadily at an annualized average rate of 4.0% during 2011-2017, and its rank, in terms of export performance, was 13 in 2010; this rose to 6 in 2016, then declined slightly to 7 in 2017 before reaching 6 as of June, 2018. However, not all ports have a similar growth path. The Onsan Port's share declined from 27.4% in 2011 to 21.0% to 2017, whereas the share of petroleum product exports of Daesan Port increased rapidly, from approximately 8.5% in 2011 to 16.0% in 2017. The standard shift-share analysis shows that petroleum products and basic petrochemicals have a positive regional in dustry-mix effect, but petrochemistry materials and synthetic resins have a negative sign, indicating that the former's exports grow faster than national export, while the increase of the latter's export is slower than national one. The spatial shift-share model indicates that for both petroleum products and basic petrochemicals, Incheon and Ulsan Ports have a positive value for the neighbor-nation regional shift effect and a positive value for the region-neighbor regional shift effect. This paper also shows that Yeosu Port for petroleum products; Ulsan Port for basic petrochemicals; Ulsan, Onsan and Yeosu Ports for petrochemistry materials; and Ulsan, Busan, and Incheon Ports for synthetic resins have a positive value for the neighbor-nation regional shift effect but a negative value for the region-neighbor regional shift effect.

• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.1-17
• /
• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• Journal of Bio-Environment Control
• /
• v.28 no.1
• /
• pp.78-85
• /
• 2019

This study was designed to examine the performance of an aspirated radiation shield(ARS), which was made at the investigator's lab and characterized by relatively easier making and lower costs based on survey data and reports on errors in its measurements of temperature and relative humidity. The findings were summarized as follows: the ARS and the Jinju weather station made measurements and recorded the range of maximum, average, and minimum temperature at $2.0{\sim}34.1^{\circ}C$, $-6.1{\sim}22.2^{\circ}C$, $-14.0{\sim}15.1^{\circ}C$ and $0.4{\sim}31.5^{\circ}C$, $-5.8{\sim}22.0^{\circ}C$, $-14.1{\sim}16.3^{\circ}C$, respectively. There were no big differences in temperature measurements between the two institutions except that the lowest and highest point of maximum temperature was higher on the campus by $1.6^{\circ}C$ and $2.6^{\circ}C$, respectively. The measurements of ARS were tested against those of a standard thermometer. The results show that the temperature measured by ARS was lower by $-2.0^{\circ}C$ or higher by $1.8^{\circ}C$ than the temperature measured by a standard thermometer. The analysis results of its correlations with a standard thermometer reveal that the coefficient of determination was 0.99. Temperature was compared between fans and no fans, and the results show that maximum, average, and minimum temperature was higher overall with no fans by $0.5{\sim}7.6^{\circ}C$, $0.3{\sim}4.6^{\circ}C$ and $0.5{\sim}3.9^{\circ}C$, respectively. The daily average relative humidity measurements were compared between ARS and the weather station of Jinju, and the results show that the measurements of ARS were a little bit higher than those of the Jinju weather station. The measurements on June 27, July 26 and 29, and August 20 were relatively higher by 5.7%, 5.2%, 9.1%, and 5.8%, respectively, but differences in the monthly average between the two institutions were trivial at 2.0~3.0%. Relative humidity was in the range of -3.98~+7.78% overall based on measurements with ARS and Assman's psychometer. The study analyzed correlations in relative humidity between the measurements of the Jinju weather station and those of Assman's psychometer and found high correlations between them with the coefficient of determination at 0.94 and 0.97, respectively.

• KDI Journal of Economic Policy
• /
• v.13 no.1
• /
• pp.65-113
• /
• 1991

Korea's rapid economic growth of the past thirty years was led by extremely fast export growth under extensive government intervention. Until very recently, the political regimes were authoritarian and oppressed human rights and labor movements. Because of these characteristics, many inside and outside Korea are under the impression that the rapid economic growth was made possible by the government's relentless push for export growth through industrial targetjng. Whether or not the government intervention was pivotal in Korean economic growth is an important issue because of its normative implications on the role of government and the degree of economic policy intervention in a market economy. A good example of industrial targeting policy in Korea is the "Heavy and Chemical Industry (HCI)" policy, which began in the early 1970s and lasted for one decade. Under the HCI policy the government intervened in resource allocation through preferential tax, trade, and credit and interest rate policies for "key industries" which included iron and steel, non-ferrous metals, shipbuilding, general machinery, chemicals, and electronics. This paper investigates the effects of. the HCI policy on the efficiency of capital and the export competitiveness of manufacturing industries. For individual three-digit KSIC (Korea Standard Industrial Classification) industries and for two industry groups, one favored by HCI Policy and the other not, this paper: (1) computes capital intensities and discusses the impact of the HCI policy on the changes in the intensities over time, (2) estimates the capital efficiencies and examines them on the basis of optimal condition of resource allocation, and (3) compares the Korean and Taiwanese shares of total imports by the OECD countries as a way of weighing the effects of the policy on the industries' export competitiveness. Taiwan is a good reference, as it did not adopt the kind of industrial targeting policy that Korea did, while the Taiwanese and Korean economies share similar characteristics. In the 1973-78 period, the capital intensity rose rapidly for the "HC Group" the group of industries favored by the policy, while it first declined and later showed an anemic rise for the "Light Group," the remaining manufacturing industries. Capital efficiency was much lower in the HC Group than in the Light Group, at least until the late 1970s. This paper acribes these results to excess investments in the favored industries and concludes that growth could have been faster in the absence of the HCI policy. The Korean Light Group's share in total imports by the OECD was larger than that of its Taiwanese counterpart but has become much smaller since 1978. For the HC Group Korea's market share was smaller than Taiwan's and has declined even more since the mid-1970s. This weakening in the export competitiveness of Korea's industries relative to Taiwan's lasted until the mid-1980s. This paper concludes that the HCI policy had either no positive effect on the competitiveness of the Korean manufacturing industries or negative effects.

• 한국벤처창업학회:학술대회논문집
• /
• 2008.04a
• /
• pp.179-208
• /
• 2008

In this research, an empirical analysis was performed to determine the correlation between management performance and R&D investment for domestic venture businesses in each industry. Specifically, an empirical analysis for each industry was attempted not only to clarify the general hypothesis on the relationship between management performance and R&D investment for venture businesses but also to demonstrate that differences exist for each industry. Empirical analysis was conducted for eight industries with respect to the $2002{\sim}2006$ panel data extracted as investigative results from the "Investigation Report on Science and Technology R&D Activities" published by the Ministry of Science and Technology. Industrial classification was limited to the middle-level classification (2-digit) in the Korea Standard Industry Code (KSIC) owing to the limited number of panels. Although this research only verified the overall positive effect of R&D activities and funds for existing research on corporate value or productivity and management performance, it was able to document the difference for each individual industry and each business size unlike existing research.Furthermore, the reliability of the research results was enhanced by targeting companies that have been continuously conducting R&D and management activities using consistent 5-year panel data in the analysis. Again, this was something that existing research did not have. Finally, through the use of recent data from 2002 after the IMF economic crisis up to 2006 in the empirical analysis, this research proposed the problems due to the prevailing circumstances at the time of entering the advanced nation stage based on an empirical analysis; the prevailing problems during the pursuit of advanced nation status before the IMF crisis broke out were not tackled. The key empirical analysis yielded several results. First, capital and size of the labor force have a positive correlation with the management performance for the entire company or the venture business. This applies to all eight industries as the subjects of the analysis. Second, although the number of years since a company has been established can have positive or negative correlation with management performance for the entire company or venture business in specific industries, a definite overall trend cannot be identified. Third, R&D investment can be said to have an overall positive effect on corporate management performance. Fourth, the size of the research staff cannot be said to be a factor unilaterally affecting the management performance of the entire company or the venture business. Fifth, the number of years a research institute has been in operation, which was assumed to have a positive effect on the management performance of a company because of the accumulated R&D know-how -- definitely acts as a positive factor contributing to the management performance of a company.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.3 no.1
• /
• pp.1-28
• /
• 2008

In this research, an empirical analysis was performed to determine the correlation between management performance and Empirical Research on the R&D investment for domestic venture businesses in each industry. Specifically, an empirical analysis for each industry was attempted not only to clarify the general hypothesis on the relationship between management performance and R&D investment for venture businesses but also to demonstrate that differences exist for each industry. Empirical analysis was conducted for eight industries with respect to the $2002{\sim}2006$ panel data extracted as investigative results from the "Investigation Report on Science and Technology R&D Activities" published by the Ministry of Science and Technology. Industrial classification was limited to the middle-level classification (2-digit) in the Korea Standard Industry Code (KSIC) owing to the limited number of panels. Although this research only verified the overall positive effect of R&D activities and funds for existing research on corporate value or productivity and management performance, it was able to document the difference for each individual industry and each business size unlike existing research. Furthermore, the reliability of the research results was enhanced by targeting companies that have been continuously conducting R&D and management activities using consistent 5-year panel data in the analysis. Again, this was something that existing research did not have. Finally, through the use of recent data from 2002 after the IMF economic crisis up to 2006 in the empirical analysis, this research proposed the problems due to the prevailing circumstances at the time of entering the advanced nation stage based on an empirical analysis; the prevailing problems during the pursuit of advanced nation status before the IMF crisis broke out were not tackled. The key empirical analysis yielded several results. First, capital and size of the labor force have a positive correlation with the management performance for the entire company or the venture business. This applies to all eight industries as the subjects of the analysis. Second, although the number of years since a company has been established can have positive or negative correlation with management performance for the entire company or venture business in specific industries, a definite overall trend cannot be identified. Third, R&D investment can be said to have an overall positive effect on corporate management performance. Fourth, the size of the research staff cannot be said to be a factor unilaterally affecting the management performance of the entire company or the venture business. Fifth, the number of years a research institute has been in operation, which was assumed to have a positive effect on the management performance of a company because of the accumulated R&D know-how -- definitely acts as a positive factor contributing to the management performance of a company.

• Journal of Korea Port Economic Association
• /
• v.26 no.4
• /
• pp.188-206
• /
• 2010

Data Envelopment Analysis(DEA) is an operations research-based method for measuring the performance efficiency of decision units that are characterized by multiple inputs and outputs. DEA has been applied successfully as a performance evaluation tool in many fields. However, it has not been extensively applied in the shipbuilding industry. This paper applied the input-oriented DEA model, and Malmquist indices to the 7 shipbuilding firms to measure the efficiency and productivity changes during the period of 2004 to 2009. The Malmquist indices will be decomposed into three components such as pure efficiency change, scale efficiency change, and technical change. The empirical results show the following findings. First, the DEA findings indicate that main source of inefficiency is scale rather than pure technical. Second, the Malmquist indices show that an overall decrease in productivity.