• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2006.06a
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• pp.129-136
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• 2006

Although cleaner and cheaper deinking of ONP could be performed at the neutral or low alkaline condition excessive loss from froth-flotation is unavoidable and so reduction of alkali or caustic soda dosage sacrifices recycling yield. Now the new trade-off regarding alkali dosage versus flotation yield is urgently required in order to set the optimized neutral or low alkaline deinking process of ONP. Lipase from Thermomyces Lanuginosus has an effect on desizing and deacetylation reaction and it could be applied to the stock of pre flotation secondary stage in order to reduce the flotation reject without the sacrifice of optical properties of flotation accepts. Instead of inorganic base, lipase could be applied as a biochemical catalyst for the selective modification of valuable hydrophobic particles in deinking stock, for example cellulose fines and inorganic fillers covered by hydrophobic additives or contaminants. When the enzymatic hydrolysis of ester bond could be made on the surface of hydrophobic particulates, unwanted float of fine particles could be prevented. Now the enhancement of flotation selectivity or the modification of the hydrophobicity of deinking stock is expected to be promoted by the enzymatic pre treatment. And the reduction of recycling cost with the saves of raw material, recovered paper would be possible as a result.

• Transactions of the Korean Society of Automotive Engineers
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• v.16 no.6
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• pp.157-167
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• 2008

Through this study, the standard design guidelines for high speed train with power cars have been derived to meet the crashworthiness requirements of the Korean rollingstock safety regulation. The crashworthiness regulation requires some performance requirements for two heavy collision accident scenarios; a train-to-train collision at the relative speed of 36 kph, and a collision against a standard deformable obstacle of 15 ton at 110 kph. A standard high speed train composition was defined as 2PC-2ET-6T with 17ton axle load, similar to KTX-2 for the Honam express line. Using theoretical and numerical analyses, some crashworthy design guidelines were derived in terms of mean crush forces and energy absorptions for major crushable components. The derived design guidelines were evaluated and improved using one dimensional spring-mass dynamic simulation. It is shown from the simulation results that the suggested design guidelines can easily satisfy the domestic crashworthiness requirements.

• Journal of Forest and Environmental Science
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• v.33 no.4
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• pp.281-294
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• 2017

Tropical forests constitute almost half of the global forest cover, account for 35% of the global net primary productivity and thereby have potential to contribute substantially to sequester atmospheric $CO_2$ and offset climate change impact. However, deforestation and degradation lead by unsustainable management of tropical forests contribute to the unprecedented species losses and limit ecosystem services including carbon sequestration. Sustainable forest management (SFM) in the tropics may tackle and rectify such deleterious impacts of anthropogenic disturbances and climatic changes. However, the existing dilemma on the definition of SFM and lack of understanding of how tropical forest sustainability can be achieved lead to increasing debate on whether climate change mitigation initiatives would be successful. We reviewed the available literature with a view to clarify the concept of sustainability and provide with a framework towards the sustainability of tropical forests for enhanced carbon stock and climate change mitigation. We argue that along with securing forest tenure and thereby reducing deforestation, application of reduced impact logging (RIL) and appropriate silvicultural system can enhance tropical forest carbon stock and help mitigate climate change.

• Journal of the Korean Society of Safety
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• v.31 no.3
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• pp.28-33
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• 2016

Since defects in the wheels of railway vehicles, which occur due to wears with the rail, cause serious damage to the running device, the diagnostic monitoring system for condition-based maintenance is required to secure the driving safety. In this paper, we studied to apply a useful Cepstrum analysis to detect periodic structure in spectrum among the vibration signal processing techniques for the fault diagnosis of a rotating body such as wheel. In order to analyze in variations of train velocity, the Cepstrum analysis was performed after a domain change of the vibration signal from time domain to rotation angle domain. When domains change, it is important to use a interpolation for a uniform interval of the rotation angle. Finally, the Cepstrum analysis for wheel flat detection was verified by using the vibration signal including the disturbance resulting from the rail irregularities and the vibration of bogie components.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.27-37
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• 2011

Currently, in the course of introducing rolling stocks, RAMS standard and management by system engineering method apply to rolling stock system. Technical elements and results applied in system introduction phase are just used in acquisition stage, and these are not applied to the standard in railway site. Therefore, it is difficult to apply to standardized technology and quality assurance measure. Due to the establishment of the EU, railway operation system is internationalized and the international railway standards are being discussed in various ways. In addition, standardization is expanded from manufacture to operation and maintenance. It is to provide consistent standard in quality, cost calculation of maintenance technology, maintenance technology and quality assurance in case of international railway safety incidents. Therefore, this study is to find technology, quality and cost management model to be used for choosing railway-operation guidance by considering how technologies & quality have changed in system life cycle, compared with estimated standards, based on the technologies & quality-related result in the process of getting new rolling stocks and management guidance for operation & maintenance process.

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

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.2
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• pp.95-101
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• 2017

In this study, we derived theoretical equations for the zigzag movement of a leading vehicle, which is the most frequent behavior in train accidents, by using a simplified spring-mass model for the rolling stock. In order to solve the equations of motion, we applied the Runge-Kutta method, which is the typical numerical analysis method used for differential equations. Furthermore, the lateral displacement of the wheel-set at the wheel-rail interface was estimated using kinetic energy. In order to verify the derived equations, we compared the theoretical and simulated results under various collision conditions. The maximum relative deviations of the lateral displacements were 0.8 [%] ~ 4.7 [%] in light collisions and 0.6 [%] ~ 5.1 [%] under derailment conditions. When an accident is simulated, these theoretical equations can be used to predict the overall behavior and obtain the offset of the body-to-body link as the initial perturbation.

• Journal of Energy Engineering
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• v.24 no.1
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• pp.10-16
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• 2015

Recently, RCM(reliability centered maintenance) process is introduced and applied for the planning and implementing efficient and effective maintenance system in terms of optimal rolling stock maintenance. Particularly, cost-time benefits analysis associated with the implementation of RCM for rolling stock maintenance is necessary and required for railway operator in advance. The RCM process was primarily starting from military, airplane and nuclear industries and is now adapted in railway industry for local railway operators. This paper focuses on suggesting the way of connecting the RCM process with railway maintenance activities in the railway operation field. Thus, in order to introduce and establish reliability activities, it needs to review and evaluate the maintenance environment in the organizational point of view. Based on these reviews and evaluations, various maintenance methodologies are reviewed for customizing local railway field situations and establish specific process in the application of major systems on the reliability technology. In this paper, the railway RCM process is proposed for the establishment and construction of the systematic and optimal maintenance system.

• Food Science and Preservation
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• v.15 no.6
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• pp.832-839
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• 2008

The stock that is the first step for preparation of soups and purees links to the taste of food. Many types of vegetable have been used in stocks, but this study focused on stocks prepared with sweet pumpkin. The stock preparation conditions including the weight of sweet pumpkin, the water volume, and the boiling time at $97^{\circ}C$ were optimized by response surface methodology. The quality characteristics of the resulting stock were investigated. The color, flavor, taste and overall acceptability were dependent parameters. A model equation was proposed with regard to the sweet pumpkin weight, water volume, and boiling time at $97^{\circ}C$. A sweet pumpkin weight of 357.9 to 403.0 g, a water volume of 689.8 to 768.5 mL, and a boiling time of 9.9 to 10.3 min at $97^{\circ}C$ were found to be the optimal stock preparation conditions. The quality characteristics of the sweet pumpkin stock prepared under the optimized conditions were pH 6.64, total acidity 0.18%, soluble solids $2.39\;^{\circ}Brix$, color value (L, 99.07 a, -2.43 b, 11.82), total polyphenol 280.75 mg/L, and electron donating ability 21.32%.

• Journal of the Korean Society for Marine Environment & Energy
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• v.18 no.4
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• pp.263-273
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• 2015

We estimated the global inflow and stock of plastic marine debris. In South Korea, we estimated that the annual inflow of plastic marine debris (72,956 tons) was about 1.4% of annual plastics consumption (5.2 million tons) in 2012. By applying this 1.4% ratio to global plastics production from 1950 to 2013, we estimated that 4.2 million tons of plastic debris entered the ocean in 2013 and that there is a stock of 86 million tons of plastic marine debris as of the end of 2013, assuming zero outflow. In addition, with a logistic model, if 4% of petroleum is turned into plastics, the final stock of plastic marine debris shall be 199 million tons at the end. As the inflow and the stock are different units of measurement, better indicators to assess the effectiveness of inflow-reducing policies are needed. And, as the pollution from plastic marine debris is almost irreversible, countermeasures to prevent it should be valued more, and stronger preventive measures should be taken under the precautionary principle. As this is a preliminary study based on limited information, further research is needed to clarify the tendency of inflow and stock of plastic marine debris.