• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.3
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• pp.53-62
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• 1994

Complex decision-making problems are often characterized by multicriteria phenomena and fuzziness inherent in the structure of information and therefore suitable scientific solution methods. Especially, when similar dependent criteria are introduced, the problems become more complex. This paper presents a fuzzy intersectional dependence relation model for this kind of multicriteria decision-making problems. The model we propose is based on the fuzzy relation from fuzzy systems theory. In ths case of introducing similar dependent criteria, the rank reversal by distortion of weights is hard to occur by our proposed method. A numerical example is presented to illustrate the use of the model.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.714-717
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• 1996

This paper presents a fault detection and diagnosis methodologies based on weighted symptom model and pattern matching between the coming fault propagation trend and the simulated one. At the first step, backward chaining is used to find the possible cause candidates for the faults. The weighted symptom model(WSM) is used to generate those candidates. The weight is determined from dynamic simulation. Using WSMs, the methodology can generate the cause candidates and rank them according to the probability. Secondly, the fault propagation trends identified from the partial or complete sequence of measurements are compared to the standard fault propagation trends stored a priori. A pattern matching algorithm based on a number of triangular episodes is used to effectively match those trends. The standard trends have been generated using dynamic simulation and stored a priori. The proposed methodology has been illustrated using two case studies and showed satisfactory diagnostic resolution.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.33 no.12
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• pp.1000-1006
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• 2009

Integrated Coal Gasification Combined Cycle (IGCC) power plants have been developed to reduce carbon dioxide emissions and to increase the efficiency of electricity generation. A devolatilization process of entrained coal gasification is predicted by CPD model which could describe the devolatilization behavior of rapidly heated coal based on the chemical structure of the coal. This paper is intended to compare the mass release behavior of char, tar and gas(CO, $CO_2,\;H_2O,\;CH_4$) for three different coals. The influence of coal structure on gas evolution is examined over the pressure range of 10${\sim}$30atm.

• Journal of the Korea Safety Management & Science
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• v.5 no.3
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• pp.133-143
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• 2003

Even in the present situation where any general criterion on CRM dose not exist, utilization of CRM is expected to be actively continued, which will cause many problems. In this regard, evaluating CRM counts. As the result, projects are being suspended and budgets cut, plans for introducing CRM suspended or cancelled and many CRM software vendors and technical consulting firms are facing serious management crisis. Yet, this phenomenon can be regarded as an interim one. In fact, some cases that successfully introduced CRM show that CRM is migrating from small scale which is typical when introduced to larger scale through various tests. Therefore, this study tries to segment customer for the sloving the problem. And it make efficient customer management. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for customer. A example is presented to illustrate the model and to show a rank reversal when compared to a model that does not eliminate extreme values and eliminates the highest and lowest experts' values allocating the weights and the subjective factors.

• Journal of Electrical Engineering and Technology
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• v.6 no.5
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• pp.706-712
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• 2011

Necessary and sufficient conditions for the existence of diagonal, block-diagonal, and triangular decoupling controllers in linear multivariable systems for the most general setting are presented. The plant model in this study is sufficiently general to accommodate non-square plant and non-unity feedback cases with one-degree-of-freedom (1DOF) or two-degree-of-freedom (2DOF) controller configuration. The existence condition is described in terms of rank conditions on the coefficient matrices in partial fraction expansions.

• Communications for Statistical Applications and Methods
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• v.22 no.4
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• pp.313-320
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• 2015

In this research, we compare the efficiency of two test procedures proposed by Prentice and Gloeckler (1978) and Park and Hong (2009) for grouped data with possible right censored observations. Both test statistics were derived using the likelihood ratio principle, but under different semi-parametric models. We review the two statistics with asymptotic normality and consider obtaining empirical powers through a simulation study. The simulation study considers two types of models the location translation model and the scale model. We discuss some interesting features related to the grouped data and obtain null distribution functions with a re-sampling method. Finally we indicate topics for future research.

• Computers and Concrete
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• v.32 no.3
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• pp.313-326
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• 2023

The seismic safety of the shear wall structure can be assessed through seismic fragility analysis, which requires high computational costs in estimating seismic demands. Accordingly, machine learning methods have been applied to such fragility analyses in recent years to reduce the numerical analysis cost, but it still remains a challenging task. Therefore, this study uses the ensemble machine learning method to present an improved framework for developing a more accurate seismic demand model than the existing ones. To this end, a rank-based selection method that enables determining an excellent model among several single machine learning models is presented. In addition, an index that can evaluate the degree of overfitting/underfitting of each model for the selection of an excellent single model is suggested. Furthermore, based on the selected single machine learning model, we propose a method to derive a more accurate ensemble model based on the bagging method. As a result, the seismic demand model for which the proposed framework is applied shows about 3-17% better prediction performance than the existing single machine learning models. Finally, the seismic fragility obtained from the proposed framework shows better accuracy than the existing fragility methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.7
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• pp.723-731
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• 2016

A core technological base to provide enhanced data rates required by 5G mobile wireless communications is the improved bandwidth efficiency using massive multiple-input multiple-output (MIMO) transmission. MIMO transmission requires the channel estimation using the channel state information reference signaling (CSI-RS) and appropriate beamforming, thus the design of the codebook defining proper beamforming vectors is an important issue. In this paper, we propose a multi-rank codebook based on the discrete Fourier transform (DFT) matrix, by utilizing statistical properties of the channel generated by the spatial channel model (SCM). The proposed method includes a structural change of the precoding matrix indicator (PMI) by considering the phase difference distributions between adjacent antenna elements, as well as the selected codevector characteristics of each transmission layer. Performance gain of the proposed method is evaluated and verified by making the performance comparison to the 3GPP standard codebooks adopted by Long-Term Evolution (LTE) systems.

• Atmosphere
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• v.22 no.4
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• pp.415-427
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• 2012

$CO_2$ is the most important trace gas related to climate change. Therefore, understanding surface carbon sources and sinks is important when seeking to estimate the impact of $CO_2$ on the environment and climate. CarbonTracker, developed by NOAA, is an inverse modeling system that estimates surface carbon fluxes using an ensemble Kalman filter with atmospheric $CO_2$ measurements as a constraint. In this study, to investigate the capability of CarbonTracker as an analysis tool for estimating surface carbon fluxes in Asia, an experiment with a nesting domain centered in Asia is performed. In general, the results show that setting a nesting domain centered in Asia region enables detailed estimations of surface carbon fluxes in Asia. From a rank histogram, the prior ensemble spread verified at observational sites located in Asia is well represented with a relatively flat rank histogram. The posterior flux in the Eurasian Boreal and Eurasian Temperate regions is well analyzed with proper seasonal cycles and amplitudes. On the other hand, in tropical regions of Asia, the posterior flux does not differ greatly from the prior flux due to fewer $CO_2$ observations. The root mean square error of the model $CO_2$ calculated by the posterior flux is less than the model $CO_2$ calculated by the prior flux, implying that CarbonTracker based on the ensemble Kalman filter works appropriately for the Asia region.

• Annals of Laboratory Medicine
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• v.38 no.6
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• pp.495-502
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• 2018

Background: Molecular genetic abnormalities are observed in over 90% of chronic myelomonocytic leukemia (CMML) cases. Recently, several studies have demonstrated the negative prognostic impact of ASXL1 mutations in CMML patients. We evaluated the prognostic impact of ASXL1 mutations and compared five CMML prognostic models in Korean patients with CMML. Methods: We analyzed data from 36 of 57 patients diagnosed as having CMML from January 2000 to March 2016. ASXL1 mutation analysis was performed by direct sequencing, and the clinical and laboratory features of patients were compared according to ASXL1 mutation status. Results: ASXL1 mutations were detected in 18 patients (50%). There were no significant differences between the clinical and laboratory characteristics of ASXL1-mutated ($ASXL1^+$) CMML and ASXL1-nonmutated ($ASXL1^-$) CMML patients (all P >0.05). During the median follow-up of 14 months (range, 0-111 months), the overall survival (OS) of $ASXL1^+$ CMML patients was significantly inferior to that of $ASXL1^-$ CMML patients with a median survival of 11 months and 19 months, respectively (log-rank P =0.049). An evaluation of OS according to the prognostic models demonstrated inferior survival in patients with a higher risk category according to the Mayo molecular model (log-rank P =0.001); the other scoring systems did not demonstrate a significant association with survival. Conclusions: We demonstrated that ASXL1 mutations, occurring in half of the Korean CMML patients examined, were associated with inferior survival. ASXL1 mutation status needs to be determined for risk stratification in CMML.