• Animal cells and systems
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• 제16권2호
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• pp.121-126
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• 2012

In this study, a neural network (NN) modeling approach has been used to predict the mechanical and geometrical behaviors of mouse embryo cells. Two NN models have been implemented. In the first NN model dimple depth (w), dimple radius (a) and radius of the semi-circular curved surface of the cell (R) were used as inputs of the model while indentation force (f) was considered as output. In the second NN model, indentation force (f), dimple radius (a) and radius of the semi-circular curved surface of the cell (R) were considered as inputs of the model and dimple depth was predicted as the output of the model. In addition, sensitivity analysis has been carried out to investigate the influence of the significance of input parameters on the mechanical behavior of mouse embryos. Experimental data deduced by Fl$\ddot{u}$ckiger (2004) were collected to obtain training and test data for the NN. The results of these investigations show that the correlation values of the test and training data sets are between 0.9988 and 1.0000, and are in good agreement with the experimental observations.

• International Journal of Railway
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• 제4권4호
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• pp.97-102
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• 2011

In an EMS (Electromagnetic suspension)-type Maglev (Magnetically-levitated) vehicle, the flexibility of the bogie frame may affect the acceleration of the electromagnet that is input into the control system, which could lead to instability in some cases. For this reason, it is desirable to consider bogie frame flexibility in air gap simulations, for the optimization of bogie structure. The objective of this paper is to develop a flexible multibody dynamic model of 1/2 of an EMS-type Maglev vehicle that is under testing, and to compare the air gap responses obtained from the rigid and the flexible body model. The feedback control system and electromagnet models that are unique to the EMS-type maglev vehicle must be included in the model. With this model, dynamics simulations are carried out to predict the air gap responses from the two models, of the rigid and flexible model, and the air gaps are compared. Such a comparative study could be useful in the prediction of the air gap in the design stage, and in designing an air gap control system.

• 대한산업공학회지
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• 제28권3호
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• pp.331-343
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• 2002

This paper proposes a fuzzy rule-based model as a means to build usability models between emotional satisfaction and design variables of consumer products. Based on a subtractive clustering algorithm, this model obtains partially overlapping rules from existing data and builds multiple local models each of which has a form of a linear regression equation. The best subset procedure and cross validation technique are used to select appropriate input variables. The proposed technique was applied to the modeling of luxuriousness, balance, and attractiveness of office chairs. For comparison, regression models were built on the same data in two different ways; one using only potentially important variables selected by the design experts, and the other using all the design variables available. The results showed that the fuzzy rule-based model had a great benefit in terms of the number of variables included in the model. They also turned out to be adequate for predicting the usability of a new product. Better yet, the information on the product classes and their satisfaction levels can be obtained by interpreting the rules. The models, when combined with the information from the regression models, are expected to help the designers gain valuable insights in designing a new product.

• 산업공학
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• 제16권1호
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• pp.70-84
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• 2003

Recently, object-oriented techniques have been used more and more for developments of an information system. But, established object-oriented methodologies are hard to express a business process of various abstract degrees in the analysis level and independent components of the system. They have difficulties in developing a large-scale information system of manufacturing industry such as PDM and CIM. This paper proposes an information system development methodology that imports the object-oriented IDEF0 (OOIDEF0) function model in analysis level. This methodology is made up of requirements gathering, system analysis, system design, and implementation. In requirements gathering level, organization diagram and interview technique are used for input data of OOIDEF0 function model. The OOIDEF0 function model, the interface model and function descriptions are made out in analysis level. Information objects and implementation objects are designed on the basis of the OOIDEF0 function model in design level. The database is built and programming is accomplished in implementation level. In order to prove the consistency and efficiency of the proposed methodology, the PDM system for ship production is modeled and prototyped.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2008년도 춘계 종합학술대회 논문집
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• pp.788-791
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• 2008

본 연구에서는 한강수계의 소유역을 24개로 분할하였고 강우의 공간 분포를 작성하기 위해 151개의 강우관측소를 이용하여 강우자료를 정리하였다. 한강수계의 주요 제어지점으로 소양강댐, 충주댐, 충주조정지댐, 횡성댐, 화천댐, 춘천댐, 의암댐, 청평댐, 팔당댐을 선정하였다. SSARR(Streamflow Synthesis and Reservoir Regulation) 모형을 기반모형으로 선정하여 모형의 입력자료를 작성하고 2002년의 수문자료를 이용하여 매개변수의 민감도분석을 수행하였다. 민감도 분석 결과, 유역유출과 관련된 매개변수 중 토양습윤상태별 유출율, 침투량별 지하수유입률 및 지표수와 복류수를 분리하는 매개변수가 비교적 큰 민감도를 나타내었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.170-170
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• 2020

Due to the development of technologies, complex computation of huge data set is possible with a prevalent personal computer. Therefore, machine learning methods have been widely applied in the hydrologic field such as regression-based regional frequency analysis (RFA). The main purpose of this study is to compare two frameworks of RFA based on the artificial neural network (ANN) models: quantile regression technique (QRT-ANN) and parameter regression technique (PRT-ANN). As an output layer of the ANN model, the QRT-ANN predicts quantiles for various return periods whereas the PRT-ANN provides prediction of three parameters for the generalized extreme value distribution. Rainfall gauging sites where record length is more than 20 years were selected and their annual maximum rainfalls and various hydro-meteorological variables were used as an input layer of the ANN model. While employing the ANN model, 70% and 30% of gauging sites were used as training set and testing set, respectively. For each technique, ANN model structure such as number of hidden layers and nodes was determined by a leave-one-out validation with calculating root mean square error (RMSE). To assess the performances of two frameworks, RMSEs of quantile predicted by the QRT-ANN are compared to those of the PRT-ANN.

• 동력기계공학회지
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• 제17권3호
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• pp.82-88
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• 2013

For commercialized servo drives of the motion stage to include embedded controller, external terminal is provided for tracking command and encoder output, but internal terminal is not for control input. Thus, it is difficult to combine out signal of embedded controller with that of external compensator such as disturbance observer. In this study, for precise tracking control of motion stage without hardware change of the servo drive, tacking control system is composed of an inner loop of servo drive and an outer loop of disturbance observer. Then, the control system is designed so that the output response of actual plant corresponds with nominal model's in transient state as well as in steady state. Finally, the experiment results show that the designed control system is effective to reconcile actual plant behavior with nominal model under nonlinear friction and parameter perturbation.

• 한국CDE학회논문집
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• 제10권4호
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• pp.284-292
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• 2005

This paper presents a new framework of kinematic tolerance synthesis and describes the implemented algorithm for planar mechanical systems comprised of higher kinematic pairs. Input to the synthesis algorithm is a parametric model of the mechanical system with allowed parameter ranges (tolerance ranges). The model is specified as the part profiles consisting of line and arc segments and the motion axes along which each part moves. The algorithm analyzes tolerance in generalized configuration space, called contact zones bounding the worst-case variations, and identifies bad system variations. The bad system variations then are removed out of the parameter ranges by adjusting the nominal parameter values if possible and then shrinking the ranges otherwise. This cycle is repeated until no more bad variations we found. I show the effectiveness of the algorithm by case studies on several mechanisms.

• 한국농공학회:학술대회논문집
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• 한국농공학회 1998년도 학술발표회 발표논문집
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• pp.299-304
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• 1998

Flood control of the Mekong delta should be developed over time for rural as well as urban areas. The hydraulic modelling effort is aimed an investigating flow distribution and water level. For the flood control study the flood model made with the VRSAP program is used. Concerning future improvement of the models it is recommended to improve the quality of water level and discharge, extend the number of the measuring locations needed for input for the models, systematically review and analyze future measurement campaigns in order to obtain better understanding of the complex hydraulic aspects, verify and update the topographical data used to model the rivers and cannals, carry out detailed calibration and verification of the models on water levels, discharges etc.

• 전기학회논문지
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• 제62권9호
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• pp.1264-1269
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• 2013

In this paper, we study a disturbance observer (DOB) based controller for an EMS(Electro-Magnetic Suspension) system in presence of mass uncertainty and input disturbance. The DOB based controller is employed in order to compensate the modeling uncertainty and attenuate disturbance signals. For the design of DOB based controller, the Jacobain linearization of nonlinear system model equation is used. Computer simulation is carried out for nonlinear model in order to compare the performance of the proposed DOB controller with that of the conventional PID controller. The simulation results show that the substantial improvement in the performance can be achieved by the proposed DOB controller.