• Communications for Statistical Applications and Methods
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• v.26 no.6
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• pp.575-582
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• 2019

The problem of selecting variables in the presence of outliers is considered. Variable selection and outlier detection are not separable problems because each observation affects the fitted regression equation differently and has a different influence on each variable. We suggest a simultaneous method for variable selection and outlier detection in a linear regression model. The suggested procedure uses a sequential method to detect outliers and uses all possible subset regressions for model selections. A simplified version of the procedure is also proposed to reduce the computational burden. The procedures are compared to other variable selection methods using real data sets known to contain outliers. Examples show that the proposed procedures are effective and superior to robust algorithms in selecting the best model.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.4
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• pp.396-407
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• 2015

The literature about intelligence assets allocation focused on mainly single or partial assets such as TOD and GSR. Thus, it is limited in application to the actual environment of operating various assets. In addition, field units have generally vulnerabilities because of depending on qualitative analysis. Therefore, we need a methodology to ensure the validity and reliability of intelligence asset allocation. In this study, detection probability was generated using digital geospatial data in MGIS (Military Geographic Information System) and simulation logic of BCTP (Battle Commander Training Programs) in the R.O.K army. Then, the optimal allocation mathematical model applied concept of simultaneous integrated management, which was developed based on the partial set covering model. Also, the proposed GA (Genetic Algorithm) provided superior results compared to the mathematical model. Consequently, this study will support effectively decision making by the commander by offering the best alternatives for optimal allocation within a reasonable time.

• Atmosphere
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• v.23 no.1
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• pp.33-37
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• 2013

In meteorology, exploitation of Kalman filter as a data assimilation system is virtually impossible due to simultaneous requirements of adjoint model and large computer resource. The other substitute of utilizing ensemble Kalman filter is only affordable by compensating an enormous usage of computing resource. Furthermore, the latter employs ensemble integration sets for evolving the background error covariance matrix by compensating the dynamical feature of the temporal evolution of weather conditions. We propose a new implementation method that works without the adjoint model by utilizing the explicit expression of the background error covariance matrix in backward evolution. It will also break a barrier in the evolution of the covariance matrix. The method may be applied with a slight modification to the real time assimilation or the retrospective analysis.

• Journal of Institute of Convergence Technology
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• v.2 no.2
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• pp.40-48
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• 2012

A small domestic desiccant dehumidifier is modelled using effectiveness models for a desiccant wheel and a wet-air condenser. The desiccant wheel and condenser models are used to compose a system model in the form of a set of simultaneous linear algebraic equations, which is solved by Gauss method. The system model is used to simulate the behaviour of a dehumidifier with a 1kW electric air heater. It is found that the maximu COP is about 0.5 and dehumidification capacity is 18kg/day when the ratio of dehumidification area is 0.7. The optimum wheel thickness and face velocity are found 100mm and 1.5m/s, respectively.

• Journal of the Korea Society for Simulation
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• v.3 no.1
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• pp.17-28
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• 1994

A statistical procedure is developed to estimate the relative difference between two parameters each obtained from either true model or approximate model. Double sample procedure is applied to find the additional number of simulation runs satisfying the preassigned absolute precision of the confidence interval. Two types of parameters, mean and standard deviation, are considered as the performance measures and tried to show the validity of the model by examining both queues and inventory systems. In each system it is assumed that there are three distinct means and their own standard deviations and they form the simultaneous confidence intervals but with control in the sense that the absolute precision for each confidence interval is bounded on the limits with preassigned confidence level. The results of this study may contribute to some situations, for instance, first, we need a statistical method to compare the effectiveness between two alternatives, second, we find the adquate number of replications with any level of absolute precision to avoid the unrealistic cost of running simulation models, third, we are interested in analyzing the standard deviation of the output measure, ..., etc.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.11a
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• pp.689-694
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• 2000

The traditional concept after Terzaghi was that consolidation was the dissipation process of pore water pressure compatible to external loading which was generated immediately after the loading. However, a theory of one-dimensional consolidation based on elasto-viscous liquid model proposed by Yoshikuni(1994) explained that the process of primary and secondary consolidation was considered to be not a simple process of dissipation of pore water pressure but a simultaneous process of dissipation and generation by external loading. This study attempts to demonstrate general consolidation behaviour of clayey soils including effects of consolidation history, load increment and thickness of cohesive layer by one-dimensional Finite Difference Method(F.D.M) analysis from the viewpoint of elasto-viscous consolidation theory.

• Proceedings of the International Microelectronics And Packaging Society Conference
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• 2000.11a
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• pp.23-27
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• 2000

Simultaneous Switching Noise (SSN) propagated through parallel power and ground planes in high-speed multilayer printed circuit boards (PCBs) causes malfunction of both digital and analog circuits. To reduce SSN, decoupling capacitors are generally used in the PCBs. In this paper, we improve the equivalent circuit model of decoupling capacitor in high-frequency range to analyze the effect of SSN reduction accurately. The analysis is performed by the microwave and RF design system (MDS) method and the finite difference time domain (FDTD) method. We compared the results by the ideal capacitor model with those by the proposed model.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.3
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• pp.124-133
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• 1995

A theoretical self-consistent thermoelectric model has been developed for optimal thermal design in the self-signal processing infraed detectors. The model is achived by employing the coupled thermoelectric equation which allows which allows the simultaneous investigation of the termal and electrical aspects of device behavior. The thermal limitation of detectivity and responsivity are determined by the enegy gap, carrier concentration, lifetime, and mobility as a function of the temperature. The calculated results indicate that the detectivity is decreased at bias fields above about 50 V/cm, because the performence is limiting by temperature when the bias voltage reached the level associated with Joule heating. It has been also found that the improvement in the mid-band modulation transfer function(MTF) may be restricted by increasing the bias fields. Further, the important paramerers in the thermal optimization of SPIR detector, such as temperature in the device, ambipolar velocity, element thickness and length, are also considered. The analytical study provides a mathematical basis for optimal design of such a photoconductive IR detector and the agreement between the experimental and theoretical results are seen to be good.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.2
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• pp.33-49
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• 2002

CBM (Condition-Based Maintenance) has increasingly drawn attention in industry because of its many benefits. CBM Problem Is characterized as a state-dependent scheduling model that demands simultaneous maintenance actions, each for an attribute that influences on machine condition. This problem is very hard to solve within conventional Markov decision process framework. In this paper, we present an intelligent machine maintenance scheduler, for which a new incremental decision tree learning method as evolutionary system identification model and shortest path problem as schedule generation model are developed. Although our approach does not guarantee an optimal scheduling policy in mathematical viewpoint, we verified through simulation based experiment that the intelligent scheduler is capable of providing good scheduling policy that can be used in practice.

• Korean Journal of Hydrosciences
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• v.10
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• pp.59-72
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• 1999

FIAS(Flood Inundation Analysis System) using Arc/Info is developed and applied to the Namhan River basin. The DWOPER model is revised and expanded to handle simultaneous multiple overtopping and/or breaking, and to estimate the inundated depth and extents. The model is applied to an actual levee overtopping case, which occurred on August 23∼27, 1995 in the Namhan River. Stage hydrographs inside and outside of the levee are compared, then inundated discharges from overbank spilling are computed. The Graphic User interface is developed with AML. Two- and three-dimensional inundation map by Arc/Info are presented. The computed inundation extends agree with observations in terms of inundated depth and flooded area. The FIAS is useful for the analysis of flood hazards and preparation of inundation map for river basins.