• Transactions of the Korean Society of Automotive Engineers
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• v.10 no.3
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• pp.61-69
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• 2002

To meet stringent LEV and ULEV emission standards, a considerable amount of development work was necessary to ensure suitable efficiency and durability of catalyst systems. The main challenge is to cut off the engine cold-start emissions. It is known that up to 80% of the total hydrocarbons(THC) are exhausted within the first five minutes in case of US FTP 75 cycle. Close-Coupled Catalyst(CCC) provides fast light-off temperature by utilizing the energy in the exhaust gas. However, if some malfunction occurred at engine operation and the catalyst temperature exceeds 1050$\^{C}$, the catalytic converter is deactivated and shows the poor conversion efficiency. This paper presents effEcts of engine operating conditions on catalytic converter temperature in a SI engine, which are the indications of catalytic deactivation. Exhaust gas temperature and catalyst temperature were measured as a function of air/fuel ratio, ignition timing and misfire rates. Additionally, light-off time was measured to investigate the effect of operating conditions. It was found that ignition retard and misfire can result in the deactivation of the catalytic converter, which eventually leads the drastic thermal aging of the converter. Significant reduction in light-off time can be achieved with proper control of ignition retard and misfire, which can reduce cold-start HC emissions as well.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.825-835
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• 2008

Multivariate GARCH(MGARCH) has been useful in financial studies and econometrics for modeling volatilities and correlations between components of multivariate time series. An obvious drawback lies in that the number of parameters increases rapidly with the number of variables involved. This thesis tries to resolve the problem by using dimension reduction technique. We briefly review both factor models for dimension reduction and the MGARCH models including EWMA (Exponentially weighted moving-average model), DVEC(Diagonal VEC model), BEKK and CCC(Constant conditional correlation model). We create meaningful portfolios obtained after reducing dimension through statistical factor models and fundamental factor models and in turn these portfolios are applied to MGARCH. In addition, we compare portfolios by assessing MSE, MAD(Mean absolute deviation) and VaR(Value at Risk). Various financial time series are analyzed for illustration.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.3
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• pp.10-17
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• 2007

Design of experiments (DOE) technique has been used to design an exhaust heat exchanger to reduce the exhaust gas temperature under high load conditions in a spark-ignition engine. The DOE evaluates the influence and the interaction of a selected eight design parameters of the heat exchanger affecting the cooling performance of the exhaust gas through a limited number of experiments. The heat exchanger was installed between the exhaust manifold and the inlet of the close-coupled catalytic converter (CCC) to reduce thermal aging. To maximize the heat transfer between exhaust gas and coolant, fins were implemented at the inner surface of the heat exchanger. The design parameters consist of the fin geometry (length, thickness, arrangement, and number of fin), coolant direction, heat exchanger wall thickness, and the length of the heat exchanger. The acceptable range of each design parameter is discussed by analyzing the DOE results.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.183-192
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• 2017

k-nearest neighbor (K-NN) is a well-known classification algorithm, being feature space-based on nearest-neighbor training examples in machine learning. However, K-NN, as we know, is a lazy learning method. Therefore, if a K-NN-based system very much depends on a huge amount of history data to achieve an accurate prediction result for a particular task, it gradually faces a processing-time performance-degradation problem. We have noticed that many researchers usually contemplate only classification accuracy. But estimation speed also plays an essential role in real-time prediction systems. To compensate for this weakness, this paper proposes correlation coefficient-based clustering (CCC) aimed at upgrading the performance of K-NN by leveraging processing-time speed and plurality rule-based density (PRD) to improve estimation accuracy. For experiments, we used real datasets (on breast cancer, breast tissue, heart, and the iris) from the University of California, Irvine (UCI) machine learning repository. Moreover, real traffic data collected from Ojana Junction, Route 58, Okinawa, Japan, was also utilized to lay bare the efficiency of this method. By using these datasets, we proved better processing-time performance with the new approach by comparing it with classical K-NN. Besides, via experiments on real-world datasets, we compared the prediction accuracy of our approach with density peaks clustering based on K-NN and principal component analysis (DPC-KNN-PCA).

• Journal of the Korean Society of Environmental Restoration Technology
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• v.7 no.2
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• pp.1-11
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• 2004

The purpose of this study was to determine usability as potted flowers and garden plants by controlled plant height using growth retardants. There was no significant difference on the dwarfing effect according to the degree of exposure the sun, but growth was well under full exposure to the sun. The plant height was decreased by application of Cycocel (CCC), Bonzi (paclobutrzol), Ancymidol, and Uniconazole compared to the control group, and treatment of Bonzi $5mg{\cdot}L^{-1}$ was most dwarfing effect for both full sun exposure or 70% controlled shading condition. No consistent different was found in stem diameter, leaf color change, the content of chlorophyll and anthocyanin when the concentration of plant growth retardants was altered. These factors were affected only by light intensity. In comparison to the results of the control group, leaf length, leaf width, plant width and petiole length were all reduced by the application of growth retardants.

• The Korean Journal of Food And Nutrition
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• v.30 no.4
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• pp.749-758
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• 2017

This study investigated the needs to improve the quality of foodservice management in community child centers (CCCs), in accordance to the area where the CCC was located. The people in charge of foodservice management of 466 community child centers undertook a web survey, between July to August 2016. Most centers used menus from the Headquarters of Community Child Center (50.0%) or Center for Children's Foodservice Management (34.1%). Factor analysis and multiple regression analysis were conducted to assess the requirement for improving the quality of foodservice management at the CCCs. Four factors were analyzed: 'food material and facility management', 'administration management', 'menu management', and 'human resources management'. In large cities, 'administration management' and 'menu management' were found to affect quality improvement. In small cities, none of the factors assessed were effective in improvement. 'human resources management' had a significant influence on improving the quality of the foodservice in rural areas. The results of this study show that there was a difference in the quality improvement of the foodservice management in the centers, with respect to the location of the center. Therefore, this study can be used as basic data to establish the support policy for improving the quality of foodservice management in community child centers.

• Smart Media Journal
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• v.1 no.1
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• pp.17-26
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• 2012

In cognitive radio networks (CRNs), unlicensed users sense the licensed spectrum bands and opportunistically access them without interfering operations of licensed users. Especially, in ad hoc networks, the MAC layer plays an important role in coordinating unlicensed users access to the spectrum and, thus, a number of MAC protocols have been studied recently. In this paper, we comparatively examine MAC protocols in cognitive radio ad hoc networks (CRAHNs). First, we categorize the protocols on the basis of common control channel (CCC) requirements and further review major implementations for each category. Then, we make a qualitative comparison of the protocols in terms of inherent characteristics and performance.

• International Commerce and Information Review
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• v.14 no.3
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• pp.381-403
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• 2012

The purpose of this study is to examine Technology Trade of Korea China for Korea China FTA. For this purpose, to analysis the present condition of technology trade and Trade Specialization Index(TSI), Technical Barriers to Trade(TBT). The Technology trade of Korea China is the surplus Technology trade of Korea but reducing to surplus scale. Also as a result of TSI analysis, Chemistry, plastic, primary metal, Medical precision industry, basic materials industries have weakened the Korea. In addition to Technical Barriers to Trade of China is very complexity for example, China Compulsory Certificate(CCC), China RoHS, China REACH. Therefore the Policy Technology Trade of Kore against China have to the centerpiece of Korea Technology export drive to expand in China.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1420-1422
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• 2016

In order to guarantee the multiuser transmission performance of a chirp spread spectrum system, the cross-correlation coefficient (CCC) among multiple users should be carefully considered. In this paper, we propose a chirp rate allocation scheme for reducing the multiple access interference based on the cross-correlation coefficient. The simulation results show that the proposed scheme can improve the multiple access interference performance.

• Journal of Microbiology and Biotechnology
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• v.21 no.2
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• pp.162-169
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• 2011

A dynamic model of lactic acid fermentation using Lactococcus lactis was constructed, and a metabolic flux analysis (MFA) and metabolic control analysis (MCA) were performed to reveal an intensive metabolic understanding of lactic acid bacteria (LAB). The parameter estimation was conducted with COPASI software to construct a more accurate metabolic model. The experimental data used in the parameter estimation were obtained from an LC-MS/MS analysis and time-course simulation study. The MFA results were a reasonable explanation of the experimental data. Through the parameter estimation, the metabolic system of lactic acid bacteria can be thoroughly understood through comparisons with the original parameters. The coefficients derived from the MCA indicated that the reaction rate of L-lactate dehydrogenase was activated by fructose 1,6-bisphosphate and pyruvate, and pyruvate appeared to be a stronger activator of L-lactate dehydrogenase than fructose 1,6-bisphosphate. Additionally, pyruvate acted as an inhibitor to pyruvate kinase and the phosphotransferase system. Glucose 6-phosphate and phosphoenolpyruvate showed activation effects on pyruvate kinase. Hexose transporter was the strongest effector on the flux through L-lactate dehydrogenase. The concentration control coefficient (CCC) showed similar results to the flux control coefficient (FCC).