• Journal of the Korea Academia-Industrial cooperation Society
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• v.3 no.1
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• pp.49-57
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• 2002

The possibility of a transmission noise reduction of piezoelectric smart panels using piezoelectric shunt damping is experimentally studied. Piezoelectric smart panel is basically a plate structure on which piezoelectric patch with shunt circuits is mounted and sound absorbing materials are bonded on the surface of the structure. Sound absorbing materials can absorb the sound transmitted at mid frequency region effectively while the use of piezoelectric shunt damping can reduce the transmission at resonance frequencies of the panel structure. To be able to reduce the sound transmission at low panel resonances, piezoelectric damping using the measured electrical impedance model is adopted. Resonant shunt circuit for piezoelectric shunt damping is composed of register and inductor in series, and they are determined by maximizing the dissipated energy throughout the circuit. The transmitted noise reduction performance of smart panels is investigated using an acoustic tunnel. The tunnel is a tube with square crosses section and a loud-speaker is mounted at one side of the tube as a sound source. Panels are mounted in the middle of the tunnel and the transmitted sound pressure across panels is measured. Noise reduction performance of a smart panels possessing absorbing material and/or air gap shows a good result at mid frequency region but little effect in the resonance frequency. By enabling the piezoelectric shunt damping, noise reduction of 10dB, 8dB is achieved at the resonance frequencise as well. Piezoelectric smart panels incorporating passive method and piezoelectric shunt damping are a promising technology for noise reduction in a broadband frequency.

• The KIPS Transactions:PartD
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• v.9D no.3
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• pp.365-380
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• 2002

Temporal data mining, the incorporation of temporal semantics to existing data mining techniques, refers to a set of techniques for discovering implicit and useful temporal knowledge from large quantities of temporal data. Temporal knowledge, expressible in the form of rules, is knowledge with temporal semantics and relationships, such as cyclic pattern, calendric pattern, trends, etc. There are many examples of temporal data, including patient histories, purchaser histories, and web log that it can discover useful temporal knowledge from. Many studies on data mining have been pursued and some of them have involved issues of temporal data mining for discovering temporal knowledge from temporal data, such as sequential pattern, similar time sequence, cyclic and temporal association rules, etc. However, all of the works treated data in database at best as data series in chronological order and did not consider temporal semantics and temporal relationships containing data. In order to solve this problem, we propose a theoretical framework for temporal data mining. This paper surveys the work to date and explores the issues involved in temporal data mining. We then define a model for temporal data mining and suggest SQL-like mining language with ability to express the task of temporal mining and show architecture of temporal mining system.

• Journal of Soil and Groundwater Environment
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• v.11 no.5
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• pp.1-8
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• 2006

The objective of this study is to assess impacts of sorption heterogeneity on the transport of leachate leaked from unlined landfill sites and is accomplished by examining the results from a series of Monte-Carlo simulations. For random distribution coefficient ($K_{d}$) fields with four different levels of heterogeneity ranging from homogeneous to highly heterogeneous, the transport of leachate was investigated by linking a saturated flow model with a contaminant transport model. Impacts of a chemical heterogeneity were evaluated using point statistics values such as mean, standard deviation, and coefficient of variation of the concentration obtained at monitoring wells from 100 Monte-Carlo trials. Inspection of point statistics shows that the distribution of distribution coefficient in the landfill site proves to be an important parameter in controlling leachate concentrations. In comparison to homogeneous sorption, heterogeneous $K_{d^-}$ fields produce the variability in the leachate concentration for different realizations. The variability increases significantly as the variance in the $K_{d^-}$ field and the travel time between source and monitoring well increase. These outcomes indicate that use of a constant homogeneous $K_{d}$ value for predicting the transport of leachate can result in significant error, especially when variability in $K_{d}$ is high.

• Journal of Preventive Medicine and Public Health
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• v.22 no.4 s.28
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• pp.542-554
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• 1989

The skyrocketing inflation of medical costs has become a major health problem among most developed countries. Korea, which recently covered the entire population with National Health Insurance, is facing the same problem. The proportion of health expenditure to GNP has increased from 3% to 4.8% during the last decade. This was remarkable, if we consider the rapid economic growth during that time. A few policy analysts began to raise cost containment as an agenda, after recognizing the importance of medical cost inflation. In order to Prepare an appropriate alternative for the agenda, it is necessary to find out reasons for the cost inflation. Then, we should focus on the reasons which are controllable, and those whose control are socially desirable. This study is designed to articulate the theory of medical cost inflation through literature reviews, to find out reasons for cost inflation, by analyzing aggregated data with a deterministic model. Finally to identify determinants of changes in both medical demand and service intensity which are major reasons for cost inflation. The reasons for cost inflation are classified into cost push inflation and demand pull inflation, The former consists of increases in price and intensity of services, while the latter is made of consumer derived demand and supplier induced demand. We used a time series (1983-1987), and cross sectional (over regions) data of health insurance. The deterministic model reveals, that an increase in service intensity is a major cause of inflation in the case of inpatient care, while, more utilization, is a primary attribute in the case of physician visits. Multiple regression analysis shows that an increase in hospital beds is a leading explanatory variable for the increase in hospital care. It also reveals, that an introduction of a deductible clause, an increase in hospital beds and degree of urbanization, are statistically significant variables explaining physician visits. The results are consistent with the existing theory, The magnitude of service intensity is influenced by the level of co-payment, the proportion of old age and an increase in co-payment. In short, an increase in co-payment reduced the utilization, but it induced more intensities or services. We can conclude that the strict fee regulation or increase in the level of co-payment can not be an effective measure for cost containment under the fee for service system. Because the provider can react against the regulation by inducing more services.

• Nuclear Engineering and Technology
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• v.19 no.2
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• pp.85-98
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• 1987

To analyze the aerosol dynamics in severe accidents of LMFBR, a new computer code entitled MCAD (Multicomponent Aerosol Dynamics) has been developed. The code can treat two component aerosol system using relative collision probability of each particles as sequences of accident scenarios. Coagulation and removal mechanisms incorporating Brownian diffusion and gravitational sedimentation are included in this model. In order to see the effect of particle geometry, the code makes use of the concept of density correction factor and shape factors. The code is verified using the experimental result of NSPP-300 series and compared to other code. At present, it fits the result of experiment well and agrees to the existing code. The input variables included are very uncertain. Hence, it requires uncertainty and sensitivity analysis as a supplement to code development. In this analysis, 14 variables are selected to analyze. The input variables are compounded by experimental design method and Latin hypercube sampling. Their results are applied to Response surface method to see the degree of regression. The stepwise regression method gives an insight to which variables are significant as time elapse and their reasonable ranges. Using Monte Carlo Method to the regression model of LHS, the confidence level of the results of MCAD and their variables is improved.

• The Korean Journal of Archival Studies
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• no.10
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• pp.145-194
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• 2004

Church archives are the evidential instruments to remember church activity and important information aggregate which has administrative, legal, financial, historical, faithful value as the collective memory of church community. So it must be managed necessarily and the management orders are based on the Bible. The western churches which have a correct understanding about the importance of church records and management order have taken multilateral endeavor to create, manage church archives systematically. On the other hand, korean churches don't have the records management systems. Therefore, Records created in individual church are mostly managed unsystematically and exist as 'backlogs', finally, they are destructed without reasonable formalities. In those problems, the purpose of this study is to offer the way of records classification and disposition instrument with recognition that records management should be done from the time of creation or previous to it. As a concrete device for them, I tried to embody the function-based classification method and disposal schedule. I prefer the function-based classification and disposal schedule to the organization and function-based classification to present stable classification and disposal schedule, as we can say the best feature of the modern organization is multilateral and also churches have same aspect. For this study, I applied DIRKS(Designing and Implementing Recordkeeping Systems) manual which National Archives of Australia provide and guidelines in ICA/IRMT series to construct the theory of the function-based classification in individual churches. Through them, it was possible to present a model for preliminary investigation, analysis of business activity, records survey, disposal schedule. And I took an example of 'Myong Sung Presbyterian Church' which belong to 'The Presbyterian church in Korea'. I explained in detail codifying process and results of preliminary investigation in 'Myong Sung Presbyterian Church', analysis of business activity based on it, process of presenting the function-based classification and disposal schedule got from all those steps. For establishing disposal schedule, I planned 'General Disposal Schedule' and 'Agency Disposal Schedule' which categorized 'general function' and 'agency function' of an agency, according to DIRKS in Australia and ICA/IRMT. And for estimation of disposal date I had a thorough grasp of important records category presented in 'Constitution of General Assembly', interview to know the importance of tasks, and added examples of disposal schedule in western church archives. This study has significance that it was intended to embody 'the function-based classification' and 'disposal schedule' suitable for individual church, applying DIRKS in Australia and ICA/IRMT on absence of the theory or example which tried to present the function-based classification and disposal schedule for individual church. Also it is meaningful to present a model that can classify and disposal real records according to the function in individual church which has no recognition or way about records management.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.4
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• pp.44-57
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• 2019

Various studies have been conducted to solve traffic congestions in many metropolitan cities through accurate traffic flow prediction. Most studies are based on the assumption that past traffic patterns repeat in the future. Models based on such an assumption fall short in case irregular traffic patterns abruptly occur. Instead, the approaches such as predicting traffic pattern through big data analytics and artificial intelligence have emerged. Specifically, deep learning algorithms such as RNN have been prevalent for tackling the problems of predicting temporal traffic flow as a time series. However, these algorithms do not perform well in terms of long-term prediction. In this paper, we take into account various external factors that may affect the traffic flows. We model the correlation between the multi-dimensional context information with temporal traffic speed pattern using deep neural networks. Our model trained with the traffic data from TOPIS system by Seoul, Korea can predict traffic speed on a specific date with the accuracy reaching nearly 90%. We expect that the accuracy can be improved further by taking into account additional factors such as accidents and constructions for the prediction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.2
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• pp.458-468
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• 2019

This research attempted to estimate monthly sales of food and beverage at the passenger terminal of Incheon int'l airport from June of 2015 to December 2020. This paper used ARIMA-Intervention model which can estimate the change of the sales amount suggesting the predicted monthly food and beverage sales revenue. The intervention variable was travel-ban policy against south Korea from P.R. China since July 2016 to December 2017 due to THAAD in south Korea. According to ARIMA, it was found normal predicted sales amount showed the slow growth increase rate until 2020 due to the effect of intervened variable. However, the monthly food sales in July and August 2019 was 20.3 and 21.2 billion KRW respectively. Each amount would increase even more in 2020 and the amount would increase to 21.4 and 22.1 billion KRW. The sales amount in 2019 would be 7.7 and 8.1 billion KRW and climb up 7.9 and 8.2 billion KRW in 2020. It was expected LCC passengers tend to spend more money for F&B at airport due to no meal or drink service of LCC or the paid-in meal and beverage service of LCC. The growth of sales of food and beverate will be accompanied with the growth of LCC according to estimated data.

• Tribology and Lubricants
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• v.35 no.1
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• pp.44-51
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• 2019

The paper presents the rotordynamic performance measurements and model predictions of a fuel cell electric vehicle (FCEV) air compressor supported on gas foil bearings (GFBs). The rotor has an impeller on one end and a thrust runner on the other end. The front (impeller side) and rear (thrust side) gas foil journal bearings (GFJBs) are located between the impeller and thrust runner to support the radial loads, and a pair of gas foil thrust bearings are located on both sides of the thrust runner to support the axial loads. The test GFJBs have a partial arc shim foil installed between the top foil and bump strip layers to enhance hydrodynamic pressure generation. During the rotordynamic performance tests, two sets of orthogonally installed eddy-current displacement sensors measure the rotor radial motions at the rotor impeller and thrust ends. A series of speed-up and coast-down tests to 100k rpm demonstrates the dominant synchronous (1X) rotor responses to imbalance masses without noticeable subsynchronous motions, which indicates a rotordynamically stable rotor-GFB system. Finite element analysis of the rotor determines the rotor free-free (bending) natural modes and frequencies well beyond the maximum rotating frequency. The predicted damped natural frequencies and damping ratios of the rotor-GFB system reveal rotordynamic stability over the speeds of interest. The imbalance response predictions show that the predicted critical speeds and rotor amplitudes strongly agree with the test measurements, thus validating the developed rotordynamic model.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.581-588
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• 2018

The aim of this study is to propose a fine co-registration approach for multi-temporal satellite images acquired from RapidEye, which has an advantage of availability for time-series analysis. To this end, we generate multitemporal ortho-rectified images using RPCs (Rational Polynomial Coefficients) provided with RapidEye images and then perform fine co-registration between the ortho-rectified images. A DEM (Digital Elevation Model) extracted from the digital map was used to generate the ortho-rectified images, and the RNCC (Registration Noise Cross Correlation) was applied to conduct the fine co-registration. Experiments were carried out using 4 RapidEye 1B images obtained from May 2015 to November 2016 over the Yeonggwang area. All 5 bands (blue, green, red, red edge, and near-infrared) that RapidEye provided were used to carry out the fine co-registration to show their possibility of being applicable for the co-registration. Experimental results showed that all the bands of RapidEye images could be co-registered with each other and the geometric alignment between images was qualitatively/quantitatively improved. Especially, it was confirmed that stable registration results were obtained by using the red and red edge bands, irrespective of the seasonal differences in the image acquisition.