• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.4
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• pp.894-903
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• 2014

Insertion loss prediction of large acoustical enclosures using Statistical Energy Analysis (SEA) method is presented. The SEA model consists of three elements: sound field inside the enclosure, vibration energy of the enclosure panel, and sound field outside the enclosure. It is assumed that the space surrounding the enclosure is sufficiently large so that there is no energy flow from the outside to the wall panel or to air cavity inside the enclosure. The comparison of the predicted insertion loss to the measured data for typical large acoustical enclosures shows good agreements. It is found that if the critical frequency of the wall panel falls above the frequency region of interest, insertion loss is dominated by the sound transmission loss of the wall panel and averaged sound absorption coefficient inside the enclosure. However, if the critical frequency of the wall panel falls into the frequency region of interest, acoustic power from the sound radiation by the wall panel must be added to the acoustic power from transmission through the panel.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.342-347
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• 1999

This study was initiated to develop a precast polymer concrete panel production method and to describe some engineering properties of FRP (Fiberglass Reinforced Plastics) reinforced polymer mortar. Specimens with different panel thickness and FRP reinforcement were prepared and tested and analyzed with respect to structural behaviors. Cracking moment was mostly affected by the thickness and reinforced FRP. Data of the study could be widely applied to the designing and planning of production processes of many polymer concrete products of which all or some of the components are composed with thin panels.

• The Korean Journal of Applied Statistics
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• v.32 no.3
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• pp.375-389
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• 2019

Sample attrition according to a long-term tracking reduces the representativeness of the sample data in a panel study. Most panel surveys in South Korea and other countries have prepared response adjustment weights in order to solve problems regarding representativeness due to sample attrition. In this paper, we divided the panel data into continuous response group and non-continuous response group according to response patterns and considered a weighting adjustment method to reduce the bias of the non-continuous response group. A simulation indicated that the proposed composite estimation type weighting method, which reflected the characteristics of non-continuous response groups, could be more efficient than other weighting methods in terms of reducing non-response bias. As a case study, the proposed methods are applied to the Korean Longitudinal Study of Ageing (KLoSA) data of the Korea Employment Information Service.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.3 s.147
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• pp.392-398
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• 2006

A prototype of MES(Manufacturing Execution System) applied to panel assembly shop is implemented by using PDA(Personal Digital Assistant) and wireless database web server. The system is developed based on the Dot Net framework. The prototype can exchange the manufacturing execution data between production managers in the control room and workers in the factory through wireless internet communication. Manufacturing model of the panel shop is designed by using IDEF0 and UML method to understand the characteristics of the information and the data entities from the PPR-S view. Several issues in the shop were revealed from the manufacturing model analysis. The most typical problem was the lack of information sharing between the managing workers and the assembly workers. The problem prevents the workers and labors from sharing the process information and continuous workpiece flow In interactive way. To increase the information and data flow, a wireless internet based system is implemented and PDAs are linked together to exchange the process planning data and in-process data between the workers. It is anticipated that PDA and the implemented system can enable the process control at each process stages to obtain the well-organized operation.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.697-710
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• 2021

Relative error prediction is preferred over ordinary prediction methods when relative/percentile errors are regarded as important, especially in econometrics, software engineering and government official statistics. The relative error prediction techniques have been developed in linear/nonlinear regression, nonparametric regression using kernel regression smoother, and stationary time series models. However, random effect models have not been used in relative error prediction. The purpose of this article is to extend relative error prediction to some of generalized linear mixed model (GLMM) with panel data, which is the random effect models based on gamma, lognormal, or inverse gaussian distribution. For better understanding, the real auto insurance data is used to predict the claim size, and the best predictor and the best relative error predictor are comparatively illustrated.

• Journal of the Korean Statistical Society
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• v.30 no.3
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• pp.511-527
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• 2001

This paper consider the testing problem of variance component for the unbalanced tow=-way error component model. We provide a conditional LM test statistic for testing zero individual(time) effects assuming that the other time-specific(individual)efefcts are present. This test is extension of Baltagi, Chang and Li(1998, 1992). Monte Carlo experiments are conducted to study the performance of this LM test.

• Journal of the Korean Statistical Society
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• v.28 no.4
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• pp.489-501
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• 1999

In this paper, we consider the panel data regression model in which the disturbances have nested error component. We derive a Lagrange Multiplier(LM) test which is jointly testing for the presence of random individual effects and nested effects under the normality assumption of the disturbances. This test extends the earlier work of Breusch and Pagan(1980) and Baltagi and Li(1991). Further, it is shown that this LM test has the same asymptotic distribution without normality assumption of the disturbances.

• Proceedings of the Korean Society of Computer Information Conference
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• 2012.01a
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• pp.263-264
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• 2012

본 논문은 여러 개의 독립적인 시계열로 구성된 시계열 패널 자료를 이용하여 비선형 모형인 GRCA모형과 신경망을 이용하여 예측값을 구하여 서로 비교 분석하고자 한다. 먼저 GRCA모형에 대하여 연구하고 신경망의 구조와 예측값을 구하기 위한 여러 가지 변환함수를 유도한다. 단기 예측에서는 신경망 방법의 예측값이 더 좋았고, 장기예측에서는 비선형모형을 이용한 예측값이 더 좋은 것으로 나타났다.

• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.469-482
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• 2002

This paper suggests a new method of compensating for wave nonresponse in panel survey, which combines weighting adjustment and imputation. By deleting less frequent nonresponse patterns, we can get simplicity. A new mean estimator under the new combining method is provided and a limited simulation study employing a real data is conducted.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.667-676
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• 1999

We investigate the effects of omission of initial observations in each individuals in the panel data regression model when the disturbances follow a serially correlated one way error components. We show that the first transformed observation can have a relative large hat matrix diagonal component and a large influence on parameter estimates when the correlation coefficient is large in absolute value.