• 소성∙가공
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• 제21권7호
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• pp.441-446
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• 2012

A sequential coupled field analysis of electromagnetic free bulging was performed by using FEM. A 2D axi-symmetric electromagnetic model based on the magnetic vector potential is proposed for the calculation of magnetic field and Lorentz's forces. The Newmark integration method is used to calculate the transient dynamic plastic deformation of sheet during free bulging. In the finite element model, the effect of sheet deformation on the electromagnetic field analysis is taken into consideration. In order to confirm the sequential electromagnetic-mechanical coupling analysis, an experiment with an electromagnetic forming apparatus was conducted. The results showed that the final bulge height of the sheet predicted from the proposed method is in good agreement with experimentally measured height.

• 한국신뢰성학회:학술대회논문집
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• 한국신뢰성학회 2005년도 학술발표대회 논문집
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• pp.131-137
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• 2005

In this paper, we propose a Bayesian approach to determine the adaptive preventive maintenance(PM) policy for a general sequential imperfect PM model proposed by Lin, Zuo and Yam(2000) that PM not only reduces the effective age of the system but also changes the hazard rate function. Assuming that the failure times follow Weibull distribution, we adopt a Bayesian approach to update unknown parameters and determine the Bayesian optimal sequential PM policies. Finally, numerical examples of the optimal adaptive PM policy are presented for illustrative purposes.

• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.116-122
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• 2023

Sentiment categorization technique be commonly isolated interested in threes significant classifications name Machine Learning Procedure (ML), Lexicon Based Method (LB) also finally, the Hybrid Method. In Machine Learning Methods (ML) utilizes phonetic highlights with apply notable ML algorithm. In this paper, in classification and identification be complete base under in optimizations technique called sequential minimal optimization with Random Forest algorithm (SMORF) for expanding the exhibition and proficiency of sentiment classification framework. The three existing classification algorithms are compared with proposed SMORF algorithm. Imitation result within experiential structure is Precisions (P), recalls (R), F-measures (F) and accuracy metric. The proposed sequential minimal optimization with Random Forest (SMORF) provides the great accuracy.

• 한국터널지하공간학회 논문집
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• 제10권2호
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• pp.177-184
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• 2008

본 연구에서는 발파 진동 및 소음에 관한 문제를 최소화하기 위해 발파진동 파형합성과 발파 시뮬레이션을 통해 진동을 최소화시킬 수 있는 전자뇌관의 최적초시를 찾고, 또한 전단면 분할 발파의 감쇄특성에 대한 연구를 토대로 하여 전단면 다단시차 분할 발파기법을 개발하였다. 경부고속철도 OO공구 수직구 시공현장에서 전자뇌관을 이용한 파형합성 최적초시적용과 전단면 다단시차 분할발파를 동시에 수행하는 발파기법을 현장에 적용함으로써 그 타당성을 검토하였다.

• 한국컴퓨터정보학회논문지
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• 제15권9호
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• pp.35-46
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• 2010

순차 패턴 탐색은 데이터 마이닝의 주요 기법 중의 하나로서 웹기반 시스템, 전자상거래, 생물정보학 및 USN 환경 등과 같은 여러 컴퓨터 응용 분야에서 생성되는 데이터를 효율적으로 분석하기 위하여 널리 활용되고 있다. 한편 이들 응용 분야에서 생성되는 정보들은 근래들어 한정적인 데이터 집합이 아닌 구성요소가 지속적으로 생성되는 데이터 스트림 형태로 생성되고 있다. 이러한 상황을 고려하여 데이터 스트림에서 순차패턴 탐색에 대한 연구들도 활발히 진행되고 있다. 하지만 이전의 연구들은 주로 분석 대상 데이터 스트림에서 단순 순차패턴을 구하는 과정에서 마이닝 수행 시간이나 메모리 사용량 등을 줄이는데 초점을 맞추고 있으며, 따라서 해당 데이터 스트림의 특성을 효율적으로 표현할 수 있는 보다 중요하고 의미있는 패턴들을 탐색하기 위한 연구는 거의 진행되지 못하고 있다. 본 논문에서는 데이터 스트림에서 보다 의미있는 순차패턴을 탐색하기 위한 방법으로 구성요소의 발생 간격 제한 조건을 활용한 빈발 순차패턴 탐색 방법을 제안한다. 먼저 발생 간격 정의 기준 및 발생 간격제한 빈발 순차패턴의 개념을 제시하고, 이어서 데이터 스트림에서 발생 간격 제한 조건을 적용하여 빈발 순차패턴을 효율적으로 탐색할 수 있는 마이닝 방법을 제안한다.

• 대한기계학회논문집A
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• 제33권9호
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• pp.892-902
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• 2009

An efficient sequential optimization approach for metamodel was presented by Choi et al. This paper describes a new approach of the multilevel optimization method studied in Refs. [2] and [20,21]. The basic idea is concerned with multilevel iterative methods which combine a descent scheme with a hierarchy of auxiliary problems in lower dimensional subspaces. After fitting a metamodel based on an initial space filling design, this model is sequentially refined by the expected improvement criterion. The advantages of the method are that it does not require optimum sensitivities, nonlinear equality constraints are not needed, and the method is relatively easy to understand and use. As a check on effectiveness, the proposed method is applied to an engineering example.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.867-877
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• 2004

The sequential sampling inspection method is an extension of the multiple-sampling methods, and its theory is based on the sequential probability ratio test (SPRT) of Wald. In this paper, the characteristics of SPRT for testing the number of defects are approximated by using the estimated excess over the boundaries. The use of the estimated excess shows good performances in estimating the operating characteristic function and the average sample number of SPRT compared to the method by neglecting the excess. It also makes it possible to determine the boundary values which satisfy the desired error probabilities.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2008년도 춘계 학술논문 발표대회
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• pp.15-19
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• 2008

The use of Precast Concrete (PC) stairways is increasing to replace existing Reinforced Concrete (RC) stairways for the faster construction and the better quality control. Among several already developed PC stairway construction methods, RC Core Sequential Construction Method by Using PC Stairways (COSEC) has advantages of 1) allowing core of a building to be built prior to PC stairways so that two different procedures will not interfere with each other, and 2) having a newly developed joint connection with the core so that the RC core and PC stairways can be easily put together. In this paper, cases of several construction sites with the PC stairways method are analyzed. The elements of the developed method are described for further application and improvement.

• 산업경영시스템학회지
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• 제21권45호
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• pp.101-112
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• 1998

Data mining, which is also referred to as knowledge discovery in database, means a process of nontrivial extraction of implicit, previously unknown and potentially useful information (such as knowledge rules, constraints, regularities) from data in databases. The discovered knowledge can be applied to information management, decision making, and many other applications. In this paper, a new data mining problem, discovering sequential patterns, is proposed which is to find all sequential patterns using sampling method. Recognizing that the quantity of database is growing exponentially and transaction database is frequently updated, sampling method is a fast algorithm reducing time and cost while extracting the trend of customer behavior. This method analyzes the fraction of database but can in general lead to results of a very high degree of accuracy. The relaxation factor, as well as the sample size, can be properly adjusted so as to improve the result accuracy while minimizing the corresponding execution time. The superiority of the proposed algorithm will be shown through analyzing accuracy and efficiency by comparing with Apriori All algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.61-64
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• 2003

A band function model paired comparison method (BMPC method) is a kind of a paired comparison methods. Considering the human ambiguities, the BMPC method expressing the human judgment characteristics as a monotonous increase function with some width. Since function types are not specified in a BMPC method, the solution is obtained from inequalities, and the solution is given as a domain. To solve the simultaneous inequalities, the sequential renew method is used in the previous BMPC method. However, the sequential renew method requires much computational effort and memories. Generally, in BMPC method, it is able to solve only a paired comparison table which has less 12-13 samples. For that purpose, a new fast solution algorithm is required. In this paper, we proposed a new “search vector method” which renews the solution domain without creating new edge vectors. By using the method, it is able to decrease the necessary memory spaces and time to solve. The proposed method makes it able to solve more than 15 samples paired comparison inspections which are impossible to solve by previous method.