• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.761-770
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• 2011

Robust principal components regression is suggested to deal with both the multicollinearity and outlier problem. A main aspect of the robust principal components regression is the selection of an optimal set of principal components. Instead of the eigenvalue of the sample covariance matrix, a selection criterion is developed based on the condition index of the minimum volume ellipsoid estimator which is highly robust against leverage points. In addition, the least trimmed squares estimation is employed to cope with regression outliers. Monte Carlo simulation results indicate that the proposed criterion is superior to existing ones.

• The KIPS Transactions:PartC
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• v.10C no.7
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• pp.885-890
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• 2003

The Core Base Tree (CBT) multicast routing architecture is a multicast routing protocol for the internet. The CBT establishes a single shared tree for a multicast connection. The shared tree Is rooted at a center node called core. The location of the core may affect the cost and performance of the CBT. The core placement method requires the knowledge of the network topology In this Paper, we propose a simple and effective method for selecting the core. This method requires the distance vector information. in addition, we used results that calculated sample correlation coefficient. And then we select suitable routing algorithm according to member's arrangement states in muliticast group. we select core node that have minimum average cost or PIM-SM protocol is selected. The performance of this method is compared with several other methods by extensive simulations (i.e mean delay, maximum delay, and total cost). Our results shows that this method for Selecting Core is very effective.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.109-120
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• 2004

Since the late of 1990, there have been number of studies on the required number of probe vehicles and/or optimal aggregation interval sizes for travel time estimation and forecasting. However, in general one to five minutes are used as aggregation intervals for the travel time estimation intervals for the travel time estimation and/or forecasting of loop detector system without a reasonable validation. The objective of this study is to deveop models for identifying optimal aggregation interval sizes of loop detector data for travel time estimation and prediction. This study developed Cross Valiated Mean Square Error (CVMSE) model for the link and route travel time forecasting, The developed models were applied to the loop detector data of Kyeongbu expressway. It was found that the optimal aggregation sizes for the travel time estimation and forecasting are three to five minutes and ten to twenty minutes, respectively.

• Journal of the Society of Disaster Information
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• v.18 no.3
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• pp.672-686
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• 2022

Purpose: This study derived the planning factors affecting the evacuation route of facilities for the disabled and to identify the planning factors that affect each facility. Method: The PLS(Partial Least Square)Regression analysis was used to solve the problem of multicollinearity and number of samples. Result: As a result of analysis, The most important planning elements for each facility were derived as door: closing time (1.131), corridor: ramp for wheelchairs (1.227), stairs: emergency lighting for stairs (1.117), and evacuation space: evacuation space convenience facilities (1.106). Conclusion: In order to plan an effective evacuation route for the disabled, a universal design should be applied to consider the perception, needs, and satisfaction of the disabled, rather than a comprehensive reflection.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1A
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• pp.45-52
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• 2009

In conventional structural design, deterministic optimization which satisfies codified constraints is performed to ensure safety and maximize economical efficiency. However, uncertainties are inevitable due to the stochastic nature of structural materials and applied loads. Thus, deterministic optimization without considering these uncertainties could lead to unreliable design. Recently, there has been much research in reliability-based design optimization (RBDO) taking into consideration both the reliability and optimization. RBDO involves the evaluation of probabilistic constraint that can be estimated using the RIA (Reliability Index Approach) and the PMA(Performance Measure Approach). It is generally known that PMA is more stable and efficient than RIA. Despite the significant advancement in PMA, RBDO still requires large computation time for large-scale applications. In this paper, A new reliability-based design optimization (RBDO) method is presented to achieve the more stable and efficient algorithm. The idea of the new method is to integrate a response surface method (RSM) with PMA. For the approximation of a limit state equation, the moving least squares (MLS) method is used. Through a mathematical example and ten-bar truss problem, the proposed method shows better convergence and efficiency than other approaches.

• Journal of the Korea Society for Simulation
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• v.23 no.3
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• pp.11-17
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• 2014

The central composite design (CCD) is often used to estimate the second-order linear model. This paper uses a correlation induction strategy of common random numbers (CRN) in simulation experiment and utilizes the induced correlations to obtain better estimates for the second-order linear model. This strategy assigns the CRN to all design points in the CCD. An appropriate selection of the axial points in CCD makes the weighted least squares (WLS) estimator be equivalent to ordinary least squares (OLS) estimator in estimating the linear model parameters of CCD. We analytically investigate the efficiency of this strategy in estimation of model parameters. Under certain conditions, this correlation induction strategy yields better results than independent random number strategy in estimating model parameters except intercept. The simulation experiment on a selected model supports such results. We expect a suggested random number assignment is useful in application of CCD in simulation experiments.

• Journal of Environmental Impact Assessment
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• v.27 no.4
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• pp.394-401
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• 2018

Tendency in ratio of biotope area of environmental impact assessment (EIA) according to population, location, project type, and total project area was analyzed by type of the projects. According to EIA, biotope area ratio is the ratio of the weighted biotope areas and total project area. biotope area is important to resident's health and quality of their life. Ministry of Environment recommends to meet the biotope area ratio standard presented by each project type. The analysis is based on 4 types of project, urban development, industrial comlpex deveopment, tourism development, and waste and sewerage treatment facility, and 55 data extracted from them. It is needed that new standard that the population is reflected, adjustment that region and frequency are considered, and regulation strengthening according to achievement of 'the minimum achievable goals' to improve biotope area policy. The research includes more data and improvements of specific system are needed as a further research.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.23 no.2
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• pp.271-294
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• 2012

This study is designed to evaluate the service quality of public libraries according to managing entities by LibQUAL+ and to devise ways to improve problems based on comparison and analysis of the differences in the service qualities. To achieve this, four public libraries in Seoul according to the managing entities were investigated. They consisted of libraries of public corporations, cultural centers, foundations and universities. Minimum service quality level, desired service quality level and perceived service quality was analyzed based on nine-point Lickertis scale. A survey was employed and consisted of twenty-two items. The results showed that current level of service met the minimum level, yet failed to reach their desired service level. The study suggested that public libraries contracting out to private sector need to actively apply users' demands and the changing environment of libraries, and continue to strive to provide public library users with high quality service through efforts of evaluating and improving the services for their users.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.4
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• pp.435-442
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• 2007

To reduce damage from high concentration ozone in the air, we have researched how to predict high concentration ozone before it occurs. High concentration ozone is a rare event and its reaction mechanism has nonlinearities and complexities. In this paper, we have tried to apply and consider as many methods as we could. We clustered the data using the fuzzy c-mean method and took a rejection sampling to fill in the missing and abnormal data. Next, correlations of the input component and output ozone concentration were calculated to transform more correlated components by modified log transformation. Then, we made the prediction models using Dynamic Polynomial Neural Networks. To select the optimal model, we adopted a minimum bias criterion. Finally, to evaluate suggested models, we compared the two models. One model was trained and tested by the transformed data and the other was not. We concluded that the modified transformation effected good to ideal performance In some evaluations. In particular, the data were related to seasonal characteristics or its variation trends.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.2
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• pp.63-72
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• 2016

An expected-discounted cost model based on RRP(Renewal Reward Process), referred to as a stochastic decision model, has been developed to estimate the optimal period of in-depth inspection which is one of critical issues in the life-cycle maintenance management of harbor structures such as rubble-mound breakwaters. A mathematical model, which is a function of the probability distribution of the service-life, has been formulated by simultaneously adopting PIM(Periodic Inspection and Maintenance) and CBIM(Condition-Based Inspection and Maintenance) policies so as to resolve limitations of other models, also all the costs in the model associated with monitoring and repair have been discounted with time. From both an analytical solution derived in this paper under the condition in which a failure rate function is a constant and the sensitivity analyses for the variety of different distribution functions and conditions, it has been confirmed that the present solution is more versatile than the existing solution suggested in a very simplified setting. Additionally, even in that case which the probability distribution of the service-life is estimated through the stochastic process, the present model is of course also well suited to interpret the nonlinearity of deterioration process. In particular, a MCS(Monte-Carlo Simulation)-based sample path method has been used to evaluate the parameters of a damage intensity function in stochastic process. Finally, the present stochastic decision model can satisfactorily be applied to armor units of rubble mound breakwaters. The optimal periods of in-depth inspection of rubble-mound breakwaters can be determined by minimizing the expected total cost rate with respect to the behavioral feature of damage process, the level of serviceability limit, and the consequence of that structure.