• 품질경영학회지
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• 제23권4호
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• pp.58-63
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• 1995

To access the quality of a fit to a set of data it is always useful to conduct a posteriori analysis involving the examination of residuals, detection of influential data values, etc. Smoothing splines are a type of nonparametric regression estimators for the diagnostic problem. And leverage value, Cook's distance, and DFFITS are used for detecting influential data. Since high leverage points will always have small residuals, the new diagnostic measures including of properties of leverage and residuals are needed. In this paper, we propose FVARATIO version as diagnostic measure in nonparametric regression. Also we consider the rough bound as analogy with linear regression case.

• 품질경영학회지
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• 제35권2호
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• pp.106-112
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• 2007

In statistical process control, it is assumed that the process data are independent. However, most of chemical processes such as semi-conduct processes do not satisfy the assumption because of presence of autocorrelation between process data. It causes abnormal out of control signal in the process control and misleading estimation in process capability. In this study, we adopted Shore's method to solve the problem and propose an optimal subgroup size to estimate the variance correctly for AR(1) processes. Especially, we focus on finding an actual subgroup size for small samples based on simulation study.

• 대한인간공학회:학술대회논문집
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• 대한인간공학회 1995년도 춘계학술대회논문집
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• pp.25-29
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• 1995

When we design a product, we need to consider human sensibility for the product. In this study, we developed a technique to measure human sensibility for a product. Because human sensibility for a product is very subjective and fuzzy, it is hard to measure easily. To deal with this difficulty effectively, we used fuzzy-weighted checklist to this problem. The fuzzy- weighted checklist presents a fuzzy version of the weighted checklist technique computerized for evaluating or comparing complex system (or subjects). In this technique, we used pairwise comparison to get the relative weights of wensibility factors. Also, we used linguistic ratings to get the scores of sensibility factors for a product. Then, we synthesize the scores of sensi- bility factors to get fuzzy composite score (and linguistic approximation). If there are several alternatives, we can conduct alternative comparison. Finally, we wrote the program of this technique by Quick Basic software. As an example, this technique applied to car. The results show that we can use this technique effectively to the quantitative evaluation of human sensibility

• 제어로봇시스템학회논문지
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• 제5권3호
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• pp.370-378
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• 1999

KOMPSAT is a three-axis stabilized light weight satellite, and one of the main mission objectives of the KOMPSAT is to conduct scientific and technological analysis in the areas of high resolution imaging and ocean color imaging. This kind of mission requires the satellite to roll up to 45 degrees. Bang-bang control for this rolling maneuver may activate the flexible modes, and therefore cause satellite pointing performance degradation. To deal with this problem, the roll attitude control system, especially for the science mode and maneuver mode of the KOMPSAT, is first verified by numerical simulation. And the open-loop control law for roll maneuver is proposed by use of series expansion and optimization. The proposed control law is applied to KOMPSAT to see its effectiveness.

• 전기학회논문지
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• 제61권10호
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• pp.1536-1541
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• 2012

The study analyzed problems by iron core structure of the three phased transformer on asymmetric three phase lines, which included line disconnections, ground faults, COS OFF, and unbalanced loads on the power distribution system. In particular, by analyzing PT combustion cases within the MOF, the study was able to analyze the combustion cause of the core-type transformer and its effect on the system, conduct simulations and practice demonstrations on the characteristics for each iron core structure of the three phase transformer using PSCAD/EMTDC, and suggest measures to prevent the combustion of the core-type transformer.

• 대한산업공학회지
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• 제17권1호
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• pp.75-82
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• 1991

This research is concerned with Machine-Part Group Formation(MPGF) methodology for Flexible Manufacturing Systems(FMS). The purpose of the research is to develop a new heuristic algorithm for effectively solving MPGF problem. The new algorithm is proposed and evaluated by 100 machine-part incidence matrices generated. The performance measures are (1) grouping ability of mutually exclusive block-diagonal form. (2) number of unit group and exceptional elements, and (3) grouping time. The new heuristic algorithm has the following characteristics to effectively conduct MPGF : (a) The mathematical model is presented for rapid forming the proper number of unit groups and grouping mutually exclusive block-diagonal form, (b) The simple and effective mathematical analysis method of Rank Order Clustering(ROC) algorithm is applied to minimize intra-group journeys in each group and exceptional elements in the whole group. The results are compared with those from Expert System(ES) algorithm and ROC algorithm. The results show that the new algorithm always gives the group of mutually exclusive block-diagonal form and better results(85%) than ES algorithm and ROC algorithm.

• 한국경영과학회지
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• 제34권1호
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• pp.11-28
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• 2009

Intelligent investment in setup cost reduction and process reliability improvement is crucial to an emerging integrated lean six sigma practice today. This study examines a cost-minimizing problem of jointly determining production lot size, setup cost reduction, and process reliability improvement decisions for a manufacturer with an imperfect production process. We develop models for previously untapped discrete shipping in a supply chain context as well as continuous shipping and solve them optimally using differential calculus and nonlinear programming. We also conduct analytic and numerical sensitivity analyses to provide various important managerial insights into practices.

• 정보관리학회지
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• 제19권4호
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• pp.35-51
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• 2002

본 논문에서는 다중 모델 기계학습 기법을 이용하여 자동 문서 분류의 성능과 신뢰도를 향상시킬 수 있는 연구와 실험 결과를 기술하였다. 기존의 다중 모델 기계 학습법들이 훈련 데이터 또는 학습 알고리즘의 편향에 의한 오류를 극복하고자 한 것인데 비해 본 논문에서 제안한 메타 학습을 이용한 하이브리드 다중 모델 방식은 이 두 가지의 오류 원인을 동시에 해소하고자 하였다. 다양한 문서 집합에 대한 실험 결과. 본 논문에서 제안한 하이브리드 다중 모델 학습법이 전반적으로 기존의 일반 다중모델 학습법들에 비해 높은 성능을 보였으며, 다중 모델의 결합 방식으로서 메타 학습이 투표 방식에 비해 효율적인 것으로 나타났다.

• 한국경영과학회지
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• 제33권1호
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• pp.117-129
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• 2008

Make-to-order manufacturers with multiple plants at multiple sites need to have the ability to quickly determine which plant will produce which customer order to meet the due date and minimize the transportation cost from the plants to the customer. Balancing the work loads and minimizing setups and make-span are also of great concern. Solving such scheduling problems usually takes a long time. We propose a new approach, which we call 'preprocessing', for resolving such complex problems. In preprocessing scheme, a 'good' a priori schedule is prepared and maintained using unconfirmed order information. Upon the confirmation of orders. the preprocessed schedule is quickly modified to obtain the final schedule. We present a preprocessing solution algorithm for multi-site constraint scheduling problem (MSCSP) using genetic algorithm; and conduct computational experiments to evaluate the performance of the algorithm.

• 한국멀티미디어학회논문지
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• 제19권1호
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• pp.80-85
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• 2016

It costs high in both memory usage and time consuming to sample the space to compute charge density and calculate electric field on that with large size of plasma data. In real-time and interactive application, accelerating the compute time is critical problem. In this paper, we suggest new method to visualize electric field by using convolution theorem, and the parallel computing to accelerate computing time by using GPGPU. We conduct a simulation that compare running time between the methods with convolution and without convolution. We discussed the method of visualization of multivariate data in three dimensional space using colored volume rendering and surface construction.