• Proceedings of the KSR Conference
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• 2008.06a
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• pp.765-771
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• 2008

After the KTX operation Korail has been making great effort to reliability settlement through RCM. Also maintenance cycle and method optimization for normal speed rolling stock field are lively same as high-speed rolling stock. In this paper maintenance techniques for new model electric locomotive are introduced. To find the optimal maintenance method, locomotive inspection cycle for advanced country are examined and other electric locomotive inspection cycle are compared. As a result the present time inspection cycle is totally focusing on safety aspect so the economical efficiency is quite low. Through this research optimal maintenance technique will be accomplished in the end of year 2008.

• Journal of Korean Society of Water and Wastewater
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• v.30 no.6
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• pp.691-698
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• 2016

This study was carried out to investigate the characterization of iron oxide nanotubes (INTs) by anodization method and applied adsorption isotherms and kinetic models for phosphate adsorption. SEM analysis was conducted to examine the INTs surface formation. Further XRD and XPS analysis were performed to observe the crystal structure of INTs before and after phosphate adsorption. AFM analysis was conducted to determine of Fe foil surface before and after anodization. Phosphate stock solution for adsorption experiment was prepared by $KH_2PO_4$. The batch experiment was conducted using 20 ml phosphate stock solution and $40cm^3$ of INTs in 50 ml conical tube. Adsorption isotherms were applied Langmuir and Freundlich models for adsorption equilibrium test of INTs. Pseudo first order and pseudo second order models were applied for interpretation of adsorption rate by reaction time. The determination coefficient ($R^2$) values of Langmuir and Freundlich models were 0.9157 and 0.8876 respectively.

• Journal of the Korean Society for Nondestructive Testing
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• v.30 no.2
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• pp.116-120
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• 2010

The wheelset, an assembly of wheel and axle, is one of important parts in railway bogie, directly related with the running safety of railway rolling stock. In this investigation, the tensile failure behavior of railway axle materials was investigated. The tensile coupons were prepared from the actual rolling stock parts, which were operated over 20 years. The tensile testing was performed according to the KS guideline. During tensile testing, an infrared camera was employed to monitor temperature changes in specimen as well as demonstrate temperature contour in terms of infrared thermographic images. The thermographic images of tensile specimens showed comparable results with mechanical behavior of tensile materials. In this paper, the failure mode and behavior of railway axle materials were provided with the aid of infrared thermography technique.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Proceedings of the KSR Conference
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• 2003.10c
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• pp.322-326
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• 2003

Dae-gu subway accident raise whole points in connection with safety facilities and operating of national urban transit system like rolling stocks, facilities, management of human. Rolling stock is made every effort for improvement of performance, guarantee of comfortableness, insurance of economical efficiency. But Security like safety of fire is not thoroughgoing enough. Especially, interior material has used although it is not prove its degree of safety. it is a main cause of Dae-gu subway accident. Safety regulation of urban transit vehicle that legislate for security in March 2000 does not applied manufacturing vehicles before in 2000. It has be prescribed in the regulations that incombustibles must be used. But detailed test standard related with incombustibles is not prescribe. Thus that regulation be required reinforcement of detailed test standard. Main cause of Dae-Gu subway accident is a fire in vehicle. However, many defects are found in infrastructure and operating vehicle of urban transit, such as inexperienced disposal of driver and CCC in early stage of the fire accident, unskilled opening and closing doors, insufficient escape facilities and safety facilities of a station house and tunnel, and incomplete communication system between vehicle and CTC, extraordinary step. Thus the aims of this study are prevention of urban transit accident, improvement plan of safety driving, and proposal of quick action plan through analysis of total faculty of vehicle.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.132-137
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• 2011

Many studies are being conducted to improve high speed, light weight and safety of passenger. To improve safety of rolling stock, safety of running performance is most important, and optimizing flow lubrication in driving gear is essential. This study simulates lubricant flow change in driving gear casing which is splashed by the surface of low speed gear teeth following rotational direction of driving gear unit for EMU by using CFD analysis, and based on analysis detail, non-load actual test is conducted for similar driving condition to find out suitability of analysis, selection of lubricate and stability of driving gear.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.7
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• pp.1007-1016
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• 2017

This paper aims to analyze the safety evaluation of the existing transformer for the 0.85 millions of public rental apartments as EVs(Electric Vehicles) increase in order to overcome the environment pollution issue and maintain sustainable development. It is analyzed that the 56.4% capacity of power transformer could secure as EV charging infrastructure, based on the analysis of respective utilization patterns of the housing and power transformer. The acceptable number of EVs is 0.04~0.06 per household from the spare capacity of the power transformer. It is analyzed that EV stock is prospected less than 0.03 per household in 2030, considering the condition of the public rental apartments residents and the growth rate of EVs according to practical scenario. The power demand for EVs is within the allowable capacity range of the power transformer, so the research shows that there is no problem in the stability of the existing transformer until 2030.

• Journal of the Korea Safety Management & Science
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• v.26 no.1
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• pp.99-106
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• 2024

In the event of an emergency such as facility shutdown during process operation, the by-product gas must be urgently discharged to the vent stack to prevent leakage, fire, and explosion. At this time, the explosion drop value of the released by-product gas is calculated using ISO 10156 formula, which is 27.7 vol%. Therefore, it does not correspond to flammable gas because it is less than 13% of the explosion drop value, which is the standard for flammable gas defined by the Occupational Safety and Health Act, and since the explosion drop value is high, it can be seen that the risk of fire explosion is low even if it is discharged urgently with the vent stock. As a result of calculating the range of explosion hazard sites for hydrogen gas discharged to the Bent Stack according to KS C IEC 60079-10-1, 23 meters were calculated. Since hydrogen is lighter than air, electromechanical devices should not be installed within 23 meters of the upper portion of the Bent Stack, and if it is not possible, an explosion-proof electromechanical device suitable for type 1 of dangerous place should be installed. In addition, the height of the stack should be at least 5 meters so that the diffusion of by-product gas is facilitated in case of emergency discharge, and it should be installed so that there are no obstacles around it.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.195-220
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• 2018

In this study, we conducted an empirical analysis of the factors that affect the change of Bitcoin Closing Price. Previous studies have focused on the security of the block chain system, the economic ripple effects caused by the cryptocurrency, legal implications and the acceptance to consumer about cryptocurrency. In various area, cryptocurrency was studied and many researcher and people including government, regardless of country, try to utilize cryptocurrency and applicate to its technology. Despite of rapid and dramatic change of cryptocurrencies' price and growth of its effects, empirical study of the factors affecting the price change of cryptocurrency was lack. There were only a few limited studies, business reports and short working paper. Therefore, it is necessary to determine what factors effect on the change of closing Bitcoin price. For analysis, hypotheses were constructed from three dimensions of consumer, industry, and macroeconomics for analysis, and time series data were collected for variables of each dimension. Consumer variables consist of search traffic of Bitcoin, search traffic of bitcoin ban, search traffic of ransomware and search traffic of war. Industry variables were composed GPU vendors' stock price and memory vendors' stock price. Macro-economy variables were contemplated such as U.S. dollar index futures, FOMC policy interest rates, WTI crude oil price. Using above variables, we did times series regression analysis to find relationship between those variables and change of Bitcoin Closing Price. Before the regression analysis to confirm the relationship between change of Bitcoin Closing Price and the other variables, we performed the Unit-root test to verifying the stationary of time series data to avoid spurious regression. Then, using a stationary data, we did the regression analysis. As a result of the analysis, we found that the change of Bitcoin Closing Price has negative effects with search traffic of 'Bitcoin Ban' and US dollar index futures, while change of GPU vendors' stock price and change of WTI crude oil price showed positive effects. In case of 'Bitcoin Ban', it is directly determining the maintenance or abolition of Bitcoin trade, that's why consumer reacted sensitively and effected on change of Bitcoin Closing Price. GPU is raw material of Bitcoin mining. Generally, increasing of companies' stock price means the growth of the sales of those companies' products and services. GPU's demands increases are indirectly reflected to the GPU vendors' stock price. Making an interpretation, a rise in prices of GPU has put a crimp on the mining of Bitcoin. Consequently, GPU vendors' stock price effects on change of Bitcoin Closing Price. And we confirmed U.S. dollar index futures moved in the opposite direction with change of Bitcoin Closing Price. It moved like Gold. Gold was considered as a safe asset to consumers and it means consumer think that Bitcoin is a safe asset. On the other hand, WTI oil price went Bitcoin Closing Price's way. It implies that Bitcoin are regarded to investment asset like raw materials market's product. The variables that were not significant in the analysis were search traffic of bitcoin, search traffic of ransomware, search traffic of war, memory vendor's stock price, FOMC policy interest rates. In search traffic of bitcoin, we judged that interest in Bitcoin did not lead to purchase of Bitcoin. It means search traffic of Bitcoin didn't reflect all of Bitcoin's demand. So, it implies there are some factors that regulate and mediate the Bitcoin purchase. In search traffic of ransomware, it is hard to say concern of ransomware determined the whole Bitcoin demand. Because only a few people damaged by ransomware and the percentage of hackers requiring Bitcoins was low. Also, its information security problem is events not continuous issues. Search traffic of war was not significant. Like stock market, generally it has negative in relation to war, but exceptional case like Gulf war, it moves stakeholders' profits and environment. We think that this is the same case. In memory vendor stock price, this is because memory vendors' flagship products were not VRAM which is essential for Bitcoin supply. In FOMC policy interest rates, when the interest rate is low, the surplus capital is invested in securities such as stocks. But Bitcoin' price fluctuation was large so it is not recognized as an attractive commodity to the consumers. In addition, unlike the stock market, Bitcoin doesn't have any safety policy such as Circuit breakers and Sidecar. Through this study, we verified what factors effect on change of Bitcoin Closing Price, and interpreted why such change happened. In addition, establishing the characteristics of Bitcoin as a safe asset and investment asset, we provide a guide how consumer, financial institution and government organization approach to the cryptocurrency. Moreover, corroborating the factors affecting change of Bitcoin Closing Price, researcher will get some clue and qualification which factors have to be considered in hereafter cryptocurrency study.

• Journal of the Korea Safety Management & Science
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• v.13 no.4
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• pp.109-116
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• 2011

This study examined into property of flour dust explosion to get the basic data for safety of industry by protecting accident of dust explosion. The experiment was conducted to know the effect of distance between explodes in the experiment device, effect of flour dust concentration, effect of humidity, effect of explosion pressure to the dust concentration and effect of inactive substance additive. The study indicated that explosion was happened effectively at the optimum distance 100mm or less in inter-polar distance, and minimum ignition energy was measured at 6mm. The data of feed concentration to the probability of explosion showed that the smaller the particle diameter was, the larger probability of explosion was, and the higher the dust concentration was, the more increased the pressure of explosion was, but more than upper limit of dust concentration, then the explosion of pressure decreased. For the effect of humidity, the more it contained water, the more decreased the ignition energy of dust was, so increased minimum explosive concentration, and effective water content was minimum 10% or more. Inactive substance additive was effective in adding more than 15% CaCO3 and CaO as substance inhibiting dust explosion, in which CaCO3 was more effective than CaO. the analysis of the flame of dust explosion was performed by high-speed video camera, it showed the size of flame bacame smaller in order that sub feed, main feed, wheat powder. As a result, sub feed was expected to be less dangerous than others.