• Industrial Engineering and Management Systems
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• v.11 no.2
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• pp.165-169
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• 2012

There has been a growing interest in firms' environmental sustainability activities to improve environmental practices in their supply chain. This study aims to deal with supplier evaluation of firm's green supply chain management (GSCM) criteria with incomplete information. Nevertheless, the suitable supplier is a key strategic direction in eliminating environmental impact on supply chain management for manufacturing firms. The firm's GSCM criteria and supplier selection need to be unified as a system to improve the firm's performance.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.105-113
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• 2002

The statistical analysis of incomplete data sometimes requires handling of incomplete observations. Towards this end, each case with some missing values generally should be deleted, namely, resulting in only use of non-missing cases. EM algorithm(Dempster et al., 1977) which involves prediction and estimation steps is a general method among others. In this article, we use the free software NORM developed for multiple imputation, which uses DA(Data Augmentation) algorithm in its imputation, and evaluate its efficiency through a numerical example.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.148-150
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• 2003

본 논문은 재공학 환경에서 기존의 디자인 패턴을 적용성 향상을 위해 UML로 표현하였으며, 대상으로는 디자인 패턴 중에서 Strategy Pattern과 Visitor Pattern을 이용해 보았다. Strategy Pattern에서는｛variation｝과 ｛incomplete｝를 이용하였다.｛variation｝은 메소드 구현시 패턴을 캡슐화하여 다양하게 변경될 수 있도록 하였다. 또한,｛incomplete｝는 주어진 관계를 만족하는 새로운 클래스가 패턴 인스턴스화 동안에 추가될 수 있도록 하였다. Visitor pattern에서의｛extensible｝은 클래스 인터페이스가 패턴을 캡슐화하고 있는 개념으로 다양하게 변경될 수 있도록 하였다. 즉, 클래스 인터페이스는 패턴 인스턴스화에 의존적이며 새로운 메소드와 속성을 클래스가 기능적으로 확장할 수 있는 기능을 갖는다.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.19-21
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• 2000

This paper presents a game theory application for analyzing power transactions and market design in a deregulated energy marketplace such as PoolCo. The conventional least-cost approaches for the generation resource schedule can not exactly handle recent real-world situations. A systematic tool using game theory for the market participants is presented such that it determines the net profits through the optimal bidding strategies including the strategies for the bidding prices and bidding generations. We treat this power transaction game as incomplete information one, which means each market participants does not know other's cost function. And the demand elasticity of the energy price is considered for the realistic modeling of the deregulated marketplace.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5C
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• pp.700-705
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• 2004

Clustering of incomplete data using the Autoencoder and the Fuzzy c-Means(PCM) is proposed in this paper. The Proposed algorithm, called Optimal Completion Autoencoder Fuzzy c-Means(OCAEFCM), utilizes the Autoencoder Neural Network (AENN) and the Gradiant-based FCM (GBFCM) for optimal completion of missing data and clustering of the reconstructed data. The proposed OCAEFCM is applied to the IRIS data and a data set from a financial institution to evaluate the performance. When compared with the existing Optimal Completion Strategy FCM (OCSFCM), the OCAEFCM shows 18％-20％ improvement of performance over OCSFCM.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.2
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• pp.49-66
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• 2014

This paper studies optimal consumption and investment behaviors of an individual when risky asset returns and her income are affected by the business cycle. The investor considers the incomplete information risk of unobservable macroeconomic conditions and updates her belief of expected risky asset returns through Bayesian learning. We find that the optimal investment strategy, certainty equivalent wealth, and portfolio hedging demand significantly depend on the belief about the macroeconomic conditions.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1547-1555
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• 2015

We study the problem of nonignorable nonresponse in a two-way contingency table and there may be one or two missing categories. We describe a nonignorable nonresponse model for the analysis of two-way categorical table. One approach to analyze these data is to construct several tables (one complete and the others incomplete). There are nonidentifiable parameters in incomplete tables. We describe a hierarchical Bayesian model to analyze two-way categorical data. We use a nonignorable nonresponse model with Bayesian uncertainty analysis by placing priors in nonidentifiable parameters instead of a sensitivity analysis for nonidentifiable parameters. To reduce the effects of nonidentifiable parameters, we project the parameters to a lower dimensional space and we allow the reduced set of parameters to share a common distribution. We use the griddy Gibbs sampler to fit our models and compute DIC and BPP for model diagnostics. We illustrate our method using data from NHANES III data to obtain the finite population proportions.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.123-124
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• 2014

무선 센서 네트워크는 센서들을 근거리 네트워크로 연결하여 사용자와 현장의 정보를 실시간으로 연결해 주는 매개체 역할을 한다. 이러한 무선 센서 네트워크는 기존의 컴퓨팅 시스템과는 달리 제한된 자원과 환경 속에서 동작을 해야 하고, 접근이 힘든 곳이나 지속적인 관리가 필요한 지역에서 효율적으로 사용된다. 본 논문에서는 무선 센서네트워크의 제한된 자원 속에서 불완전 스트림 데이터를 효율적으로 정제하고 처리하여 빠르고 정확한 질의어 처리가 가능한 질의 시스템을 제안하였다.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1117-1125
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• 2014

In a longitudinal study, subjects can experience same type of events repeatedly. Also, there may exist intermittent dropouts resulting in repeated observation gaps during which no recurrent events are observed. Furthermore, when such observation gaps have incomplete forms caused by the unknown termination times of observation gaps, ordinary approaches result in biased estimates. In this study, we investigate the effect of ignoring observation gaps and propose methods to overcome this problem. For estimating the distribution of unknown termination times, an interval-censored mechanism is applied and two cases are considered. Simulation studies are carried out to evaluate the performance of the proposed method. Conviction data of young drivers with several suspensions are analyzed to illustrate the suggested approach.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.494-497
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• 1999

Neural networks are shown to be effective in being able to distinguish incomplete penetration-like weld defects by directly analyzing the plasma which is generated on each impingement of the laser on the materials. The performance is similar to that of existing methods based on extracted feature parameters. In each case around 93% of the defects in a database derived from 100 artificially produced defects of known types can be placed into one of two classes: incomplete penetration and bubbling. Especially we present simulator for weld defects classification and data analysis. The present method based on classification using plasma is faster, and the speed is sufficient to allow on-line classification during data collection.