• 대한산업공학회지
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• 제36권3호
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• pp.154-163
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• 2010

Process monitoring of output variables affecting final performance have been mainly executed in semiconductor manufacturing process. However, even earlier detection of causes of output variation cannot completely prevent yield loss because a number of wafers after detecting them must be re-processed or cast away. Semiconductor manufacturers have put more attention toward monitoring process inputs to prevent yield loss by early detecting change-point of the process. In the paper, we propose the method to efficiently monitor functional input variables in multi-phase semiconductor manufacturing process. Measured input variables in the multi-phase process tend to be of functional structured form. After data pre-processing for these functional input data, change-point analysis is practiced to the pre-processed data set. If process variation occurs, key variables affecting process variation are selected using contribution plot for monitoring efficiency. To evaluate the propriety of proposed monitoring method, we used real data set in semiconductor manufacturing process. The experiment shows that the proposed method has better performance than previous output monitoring method in terms of fault detection and process monitoring.

• 한국정보처리학회논문지
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• 제6권3호
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• pp.781-791
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• 1999

DD(Decision Diagrams) is an efficient operational data structure for an optimal expression of boolean functions. In a graph-based synthesis using DD, the goal of optimization decreases representation space for boolean functions. This paper represents boolean functions using OPKFDD(Ordered Pseudo-Kronecker Functional Decision Diagrams) for a graph-based synthesis and is based on the number of nodes as the criterion of DD size. For a property of OPKFDD that is able to select one of different decomposition types for each node, OPKFDD is variable in its size by the decomposition types selection of each node and input variable order. This paper proposes a method for generating OPKFDD efficiently from the current BDD(Binary Decision Diagram) Data structure and an algorithm for minimizing one. In the multiple output functions, the relations of each function affect the number of nodes of OPKFDD. Therefore this paper proposes a method to decide the input variable order considering the above cases. Experimental results of comparing with the current representation methods and the reordering methods for deciding input variable order are shown.

• 산업공학
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• 제12권4호
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• pp.551-556
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• 1999

In this paper, we compare the performance of three data mining classification algorithms(neural network, decision tree, logistic regression) in consideration of various characteristics of categorical input and output data. $2^{4-1}$. 3 fractional factorial design is used to simulate the comparison situation where factors used are (1) the categorical ratio of input variables, (2) the complexity of functional relationship between the output and input variables, (3) the size of randomness in the relationship, (4) the categorical ratio of an output variable, and (5) the classification algorithm. Experimental study results indicate the following: decision tree performs better than the others when the relationship between output and input variables is simple while logistic regression is better when the other way is around; and neural network appears a better choice than the others when the randomness in the relationship is relatively large. We also use Taguchi design to improve the practicality of our study results by letting the relationship between the output and input variables as a noise factor. As a result, the classification accuracy of neural network and decision tree turns out to be higher than that of logistic regression, when the categorical proportion of the output variable is even.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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• pp.367-369
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• 1986

Guaranteed cost control is a method applicable to a class of systems with uncertain parameters that guarantees an upper bound of the cost functional. This paper is concerned with a matrix decomposition technique used to yield a reasonable upper bound of the cost functional for a finite-time LQ regulator problem. The uncertain linear systems dealt with in this paper are described by a set of state equations of single-input phase-variable canonical form which contain unknown but bounded uncertain parameters.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1994년도 FIFTH WESTERN PACIFIC REGIONAL ACOUSTICS CONFERENCE SEOUL KOREA
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• pp.686-691
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• 1994

For evaluating the response fluctuation of the actual environmental acoustic system excited by arbitrary random inputs, it is important to predict a whole probability distribution form closely connected with evaluation indexes Lx, Leq and so on. In this paper, a new type evaluation method is proposed by introducing three functional models matched to the prediction of the response probability distribution from a problem-oriented viewpoint. Because of the positive variable of the sound intensity, the response probability density function can be reasonably expressed theoretically by a statistical Laguerre expansion series form. The relationship between input and output is described by the regression relationship between the distribution parameters(containing expansion coefficients of this expression) and the stochastic input. These regression functions are expressed in terms of the orthogonal series expansion and their parameters are determined based on the least-squares error criterion and the measure of statistical independency.

• 한국정보과학회논문지:소프트웨어및응용
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• 제27권4호
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• pp.342-356
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• 2000

주어진 프로그램에서 예외상황(exception)을 발생시키는 테스트 데이타를 자동으로 생성해주는 분석 방법을 제안한다. 분석 결과로 얻은 테스트 데이타를 사용하여, 프로그램 내에서 발생한 예외상황들이 프로그래머의 의도대로 처리되는지를 검사할 수 있다. 본 논문에서 제안하는 분석 방법은 입력으로 받은 프로그램에서 특정 예외상황이 발생한다는 조건을 시작으로 하여, 프로그램의 입력 값에 대한 제약식(constraints)을 만들어간다. 이 분석 방법이 옳다는 증명에 의해서, 분석 결과로 얻은 테스트 데이타를 입력으로 하여 프로그램을 수행시키면 지정한 예외상황이 항상 발생한다는 것을 보장할 수 있다.함수를 인수나 결과값으로 전달하지 않고(first-order) ML 스타일의 예외상황 관리 방법을 제공하는 언어를 대상으로 하여 테스트 데이타 생성 방법을 제안하고, 이 분석 방법이 옳다는 것을 증명한 후 몇 가지 예를 사용하여 분석 과정을 설명한다.

• International Journal of Advanced Culture Technology
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• 제6권4호
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• pp.71-79
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• 2018

For 299 patients who had undergone cataract surgeries we investigated the difference in visual acuity and refractive power before and after cataract surgery and the clinical change of the visual acuity and the refractive power according to age, gender, hospital visit time and specific medical history. We found the factors affecting preoperative and postoperative outcomes of the cataract patients in metropolitan hospitals by input, process, and outcome and analyzed medical characteristics and patient characteristics as the input variables. T-test and ANOVA have been performed for statistical analysis of functional status, and general status and the technical characteristic as the process variable and the outcome variable of diagnosis. Visual acuity improved significantly in patients who had undergone cataract surgery. However, the change in refractive power did not show a statistically significant difference but only a slight difference. The improvement of male patients was greater than that of female patients. The difference in age was more effective in patients under 50 years old and the effect of cataract surgery was relatively high in patients without the presence of specific medical history. Cataract surgery did not seem to help all of the patients, but it is more effective in improving visual acuity and refractive power. We conclude that simultaneous cataract surgery in both eyes is reasonable in order to have at least the better effect.

• 한국세라믹학회지
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• 제44권3호
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• pp.169-174
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• 2007

TRISO coated fuel particle is one of the most important materials for hydrogen production using HTGR (high temperature gas cooled reactors). It is composed of three isotropic layers: inner pyrolytic carbon (IPyC), silicon carbide (SiC), outer pyrolytic carbon (OPyC) layers. In this study, TRISO coated fuel particle layers were deposited through CVD process in a horizontal hot wall deposition system. Also the computational simulations of input gas velocity, temperature profile and pressure in the reaction chamber were conducted with varying process variable (i.e temperature and input gas ratios). As deposition temperature increased, microstructure, chemical composition and growth behavior changed and deposition rate increased. The simulation showed that the change of reactant states affected growth rate at each position of the susceptor. The experimental results showed a close correlation with the simulation results.

• 한국조경학회지
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• 제27권1호
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• pp.54-63
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• 1999

The Landscape drawing is used as main media in landscape design process like the language in daily life for human. Designers input many intentions and meaningful words in design process through landscape drawing. The common purpose of landscape drawing is to represent reality effectively, even though it has variable visual forms and materiality. The representation in landscape drawing in metaphorical as well as visual and functional. But current tendency is inclined to use landscape drawing in a functional aspect for visual representation and the landscape drawing is utilized straight-forwardly rather than metaphorically for clear communication. Such recognition on landscape drawing results from the difficulty to accept the symbolic aspect of the drawing. The difficulty makes the utilization and the interpretation of landscape drawing stay at conventional level in following visible factors. For the sake of solving the difficulty this study considers landscape drawing as the text that contains readable objects and symbolic words. This study presents layer-methods for reading a landscape drawing as a text; situational and contextural reading, iconological reading and reading the subject of drawing.

• 한국지능시스템학회논문지
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• 제23권5호
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• pp.412-417
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• 2013

태양광 발전 시스템의 해석적 모델링은 시스템의 동특성을 예측하거나 고장검출 및 진단 등과 같은 고급 공학 기술에 중요하게 적용할 수 있어 최근 많은 각광을 받고 있다. 본 논문은 대용량 학습 데이터를 갖는 태양광 발전 시스템에 대한 확률론적 모델링을 제시한다. 우선 태양광 일사량과 온도 입력 변수에 대한 태양광 시스템의 출력 전력과의 입출력 함수관계를 정의한다. 이 함수관계를 바탕으로 세 확률변수(일사량, 온도, 전력)에 대하여 조건부 확률 식으로 표현한다. 조건부 확률 분포 추정은 대용량 데이터 시스템에 적합한, 전체 표본 데이터 수 대비 관련 변수의 경우의 수에 대한 비율로 나타내었다. 추정한 확률분포를 통해 평균값 이론을 적용하여 시스템의 출력을 추정하게 된다. 본 논문에서 제안한 모델링 기법은 두 태양광 발전 단지의 사례 연구를 통해 성능을 검증하였다.