• 대한산업공학회지
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• 제39권5호
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• pp.361-366
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• 2013

Prediction of process parameters is very important in parameter design. If predictions are fairly accurate, the quality improvement process will be useful to save time and reduce cost. The concept of dual response approach based on response surface methodology has widely been investigated. Dual response approach may take advantages of optimization modeling for finding optimum setting of input factor by separately modeling mean and variance responses. This study proposes an alternative dual response approach based on machine learning techniques instead of statistical analysis tools. A hybrid neural network-genetic algorithm has been proposed for the purpose of parameter design. A neural network is first constructed to model the relationship between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Using empirical process data, process parameters can be predicted without performing real experimentations. A genetic algorithm is then applied to find the optimum settings of input factors, where the neural network is used to evaluate the mean and variance response. A drug formulation example from pharmaceutical industry has been studied to demonstrate the procedures and applicability of the proposed approach.

• Earthquakes and Structures
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• 제12권6호
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• pp.653-663
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• 2017

A seismic margin assessment evaluates how much margin exists for the system under beyond design basis earthquake events. Specifically, the seismic margin for the entire system is evaluated by utilizing a systems analysis based on the sub-system and component seismic fragility data. Each seismic fragility curve is obtained by using empirical, experimental, and/or numerical simulation data. The systems analysis is generally performed by employing a fault tree analysis. However, the current practice has clear limitations in that it cannot deal with the uncertainties of basic components and accommodate the newly observed data. Therefore, in this paper, we present a Bayesian-based seismic margin assessment that is conducted using seismic fragility data and fault tree analysis including Bayesian inference. This proposed approach is first applied to the pooltype nuclear research reactor system for the quantitative evaluation of the seismic margin. The results show that the applied approach can allow updating by considering the newly available data/information at any level of the fault tree, and can identify critical scenarios modified due to new information. Also, given the seismic hazard information, this approach is further extended to the real-time risk evaluation. Thus, the proposed approach can finally be expected to solve the fundamental restrictions of the current method.

• Earthquakes and Structures
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• 제12권5호
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• pp.489-499
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• 2017

The effects of past earthquakes have demonstrated the seismic vulnerability of confined masonry structures (CMSs) to earthquakes. The results of experimental analysis indicate that damage to these structures depends on lateral displacement applied to the walls. Seismic evaluation lacks an analytical approach because of the complexity of the behavior of this type of structure; an empirical approach is often used for this purpose. Seismic assessment and risk analysis of CMSs, especially in area have a large number of such buildings is difficult and could be riddled with error. The present study used analytical and numerical models to develop a simplified nonlinear displacement-based approach for seismic assessment of a CMS. The methodology is based on the concept of ESDOF and displacement demand and is compared with displacement capacity at the characteristic period of vibration according to performance level. Displacement demand was identified using the nonlinear displacement spectrum for a specified limit state. This approach is based on a macro model and nonlinear incremental dynamic analysis of a 3D prototype structure taking into account uncertainty of the mechanical properties and results in a simple, precise method for seismic assessment of a CMS. To validate the approach, a case study was considered in the form of an analytical fragility curve which was then compared with the precise method.

• 경영과학
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• 제29권3호
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• pp.81-89
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• 2012

Since introduced by Vining and Myers in 1990, the concept of dual response approach based on response surface methodology has widely been investigated and adopted for the purpose of robust design. Separately estimating mean and variance responses, dual response approach may take advantages of optimization modeling for finding optimum settings of input factors. Explicitly assuming functional relationship between responses and input factors, however, it may not work well enough especially when the behavior of responses are poorly represented. A sufficient number of experimentations are required to improve the precision of estimations. This study proposes an alternative to dual response approach in which additional experiments are not required. An artificial neural network has been applied to model relationships between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Training, validating, and testing a neural network with empirical process data, an artificial data based on the neural network may be generated and used to estimate response functions without performing real experimentations. A drug formulation example from pharmaceutical industry has been investigated to demonstrate the procedures and applicability of the proposed approach.

• 대한기계학회논문집A
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• 제33권12호
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• pp.1464-1470
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• 2009

RBDO approach based on a sampling method with the Kriging metamodel and Constraint Boundary Sampling (CBS), which is sequential sampling method to generate metamodels is proposed. The major advantage of the proposed RBDO approach is that it does not require Most Probable failure Point (MPP) which is essential for First-Order Reliability Method (FORM)-based RBDO approach. The Monte Carlo Sampling (MCS), most well-known method of the sampling methods for the reliability analysis is used to assess the reliability of constraints. In addition, a Cumulative Distribution Function (CDF) of the constraints is approximated using Moving Least Square (MLS) method from empirical distribution function. It is possible to acquire a probability of failure and its analytic sensitivities by using an approximate function of the CDF for the constraints. Moreover, a concept of inactive design is adapted to improve a numerical efficiency of the proposed approach. Computational accuracy and efficiency of the proposed RBDO approach are demonstrated by numerical and engineering problems.

• 영어어문교육
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• 제10권3호
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• pp.89-112
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• 2004

This article examines the ways in which language can be exploited in the manipulation of the reader's interpretation of a text to make him/her take certain lines of thought according to the writer's persuasive intents. Such functions of language provide valid foundations to support the teaching of critical reading skills and to explore an adequate approach to discourse analysis. A pilot study was conducted to find out the extent to which the reader can be coaxed into thinking in some fashions guided by specific linguistic devices employed for ideological texts. Forty-seven subjects divided into two groups (humanities majors and natural science majors at undergraduate level) joined the two-fold questionnaire surveys intended to look at their critical reading abilities. The empirical results indicate that college students whose majors are humanities were more inclined to take a holistic approach in processing commercial advertisement texts and their abilities for critical interpretation appeared to be lower than those of the subjects whose majors are natural sciences, who showed a relatively high tendency to take an analytical approach in decoding the textual facts. As a consequence, pedagogic implications for increasing critical reading abilities have resulted in a set of analytical procedures concerning ideological texts which is linked with instructional guidelines to emphasize the importance of the reader's logical and analytical reasoning power, entirely accepted as a general prerequisite for cracking the covert language gambits.

• ETRI Journal
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• 제39권5호
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• pp.718-728
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• 2017

Empirical modeling of wireless fading channels using common schemes such as autoregression and the finite state Markov chain (FSMC) is investigated. The conceptual background of both channel structures and the establishment of their mutual dependence in a confined manner are presented. The novel contribution lies in the proposal of a new approach for deriving the state transition probabilities borrowed from economic disciplines, which has not been studied so far with respect to the modeling of FSMC wireless fading channels. The proposed approach is based on equal portioning of the received signal-to-noise ratio, realized by using an alternative probability construction that was initially highlighted by Tauchen. The associated statistical procedure shows that a first-order FSMC with a limited number of channel states can satisfactorily approximate fading. The computational overheads of the proposed technique are analyzed and proven to be less demanding compared to the conventional FSMC approach based on the level crossing rate. Simulations confirm the analytical results and promising performance of the new channel model based on the Tauchen approach without extra complexity costs.

• Smart Structures and Systems
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• 제13권5호
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• pp.869-890
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• 2014

In this study, a damage detection approach using train-induced vibration response of the bridge is proposed, utilizing only direct structural analysis by means of introducing soft computing methods. In this approach, the possible damage patterns of the bridge are assumed according to theoretical and empirical considerations at first. Then, the running train-induced dynamic response of the bridge under a certain damage pattern is calculated employing a developed train-bridge interaction analysis program. When the calculated result is most identical to the recorded response, this damage pattern will be the solution. However, owing to the huge number of possible damage patterns, it is extremely time-consuming to calculate the bridge responses of all the cases and thus difficult to identify the exact solution quickly. Therefore, the soft computing methods are introduced to quickly solve the problem in this approach. The basic concept and process of the proposed approach are presented in this paper, and its feasibility is numerically investigated using two different train models and a simple girder bridge model.

• 한국실내디자인학회논문집
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• 제39호
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• pp.116-123
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• 2003

The purpose of this study is to demonstrate the relationship between the results of the analysis of the overseas railroad station buildings, which was conducted using the factors of environmental cognition for the purpose of designing an interior environment for the Incheon International Airport Railroad station that will be newly constructed, and the plan that could be applied to the design of interior environment for the airport railroad station. The station with a complex interior space layout and relatively larger space tends to be difficult to predict or forecast passenger's needs or recognition element in approaching stage of intoner environment design since the human's biological memory system is greatly affected by such factors. Cognitive approach at empirical standpoint would possibly create the design, of which elements will Implement the functions of their own as such approach enables necessary information to be structured in a systematical way and manner In implementing interior environment design for such stations to be built for the first time in Korea, behavioral approach based on systematic theory proved to be very crucial. Under such a background, the study was aimed at extracting the assessment elements for interior environment design, then setting the frame of cognitive approach to eventually propose the guideline in approaching to interior environment design.

• 한국방재학회 논문집
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• 제2권3호
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• pp.109-117
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• 2002

저수지를 설계 및 계획함에 있어서 저수지의 설계수명 기간동안 예상되는 퇴사량을 위한 퇴사공간을 배분하는 것은 가장 중요한 절차중의 하나이다. 특히 퇴사공간의 배분과 관련된 해석 및 연구는 저수지 운영, 흐름의 수리학적 특성, 유입 유사량과 연관된 매우 다양한 변수들간의 상호작용으로 인하여 매우 복잡하고 쉽지 않은 문제이다. 퇴적물들의 공간적인 분포를 알아보기 위한 접근방법은 경험적인 방법에 의존하고 있으며 이와 같은 경험적인 방법의 적용은 대부분 실제의 퇴적현상을 엄청나게 단순화시켜야만 가능하다 본 연구에서는 소양강댐을 대상으로 하여 경험적면적감소법(Empirical Area Reduction Method)에 의해 저수지 퇴사량을 계산하고 계산된 결과를 실측자료와 비교하여 봄으로써 경험적면적감소법의 적용성을 알아보았으며 그 결과 매우 적용성이 우수한 것으로 나타났다.