• 대한방사선기술학회지:방사선기술과학
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• 제46권2호
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• pp.151-157
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• 2023

The purpose of this study was to develop an assist device that could correct and support patient position during biopsy on computed tomography (CT) using 3D printing technology. The development method was conducted in the order of 3D design, 3D output, intermediate evaluation for product, final assist device evaluation. The 3D design method was conducted in the order of prior research data survey, measurement, primary modeling, 3D printing, output evaluation, and supplementary modeling. The 3D output was the 3D printer (3DWOX 2X, Sindoh, Korea) with additive manufacturing technology and the polylactic acid (PLA) materials. At this time, the optimal strength was evaluated to infill degree of product as the 3D printing factors into 20%, 40%, 60%, and 80%. The intermediate evaluation and supplementation was measured noise in the region of interest (ROI) around the beam hardening artifact on the CT images. We used 128-channel MDCT (Discovery 75 HD, GE, USA) to scan with a slice thickness of 100 kVp, 150 mA, and 2.5 mm on the 3D printing product. We compared the surrounding noise of the final 3D printing product with the beginning of it. and then the strength of it according to the degree of infill was evaluated. As a result, the surrounding noise of the final and the early devices were measured at an average of 3.3 ± 0.5 HU and 7.1 ± 0.1 HU, respectively, which significantly reduced the noise of the final 3D printing product (p<0.001). We found that the percentage of infill according to the optimal strength was found to be 60%. Finally, development of assist devices for CT biopsy will be able to minimize artifacts and provide convenience to medical staff and patients.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.1391-1392
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• 2013

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.795-797
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• 1998

This paper suggests a design method of the optimal PD control system having robust performance. This PD control system is designed by applying genetic algorithm(GA) with reference model to the optimal determination of proportional(P) gain and derivative(D) gain that are given by PD servo controller. These proportional and derivative gains are simultaneously optimized in the search domain guaranteeing the robust performance of closed-loop system. This PD control system is applied to the fuel-injection control system of diesel engine and compared with ${\mu}$ -synthesis control system for robust performance. The effectiveness of this PD control system is verified by computer simulation.

• 산업경영시스템학회지
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• 제14권23호
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• pp.57-64
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• 1991

The preliminary, advanced and final evaluation of R&D project is essential in order to reduce loss of resource and opportunity and to minimize uncertainty resulting from optimal selection and efficient progress of R&D project. This thesis examined characteristics of deterministic evaluation, economical evaluation, and OR-approach evaluation as theoretical methodology of evaluation of R&D project applicable to food industry in Korea by using scoring method, one of deterministic evaluations. In addition, this thesis divided the evaluation factors for preliminary evaluation of R&D project into 5 groups and 30 factors on basis of the environment of domestic companies and set up the standard of each evaluation factors and contains marking-selecting way. But, generally, the evaluation model by this thesis, as the conditions of the business company environment are different to each other, contents to be set up evaluation factors, evaluation standard and decision method conforming to each the environment of the business companies with referring to as one standard of evaluation project for selecting R&D project.

• 한국공작기계학회논문집
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• 제16권3호
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• pp.96-102
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• 2007

An Optimal shape design of the boom system in high ladder vehicles is performed using 3-D finite element method (FEM). Results of structural analyses providing displacements, stresses are implemented for the optimum shape design. Lanzcos algorithm is used for the modal analysis in order to find natural frequencies. The optimal shape including cross sectional thickness and length of the boom system is controlled by the subproblem method besed on displacement and Von Mises stress. It is found that a plenty of materials can be saved by using shape design optimization in high ladder vehicles. It is also found that the natural frequency is increased until 6th mode and maintained similarly or decreased after 6th mode.

• 품질경영학회지
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• 제24권4호
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• pp.59-69
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• 1996

The criteria for construction of D-optimal design in nonlinear models are derived. The procedures for finding these optimal designs using the simulated annealing algorithm are presented. It is claimed that the advantages of this method are its ability to make the given data useful by adding new observations as well as to obtain a new set of appropriate data when the model and parameters are known. Research so far indicates that there has never been a case in which there is more than one independent variable but this method can be used for such cases. The result indicates the effectiveness of the method using simulated annealing algorithm for situations in which there are many independent variables and the ranges of design spaces are wide.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2014년도 추계학술대회 논문집
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• pp.84-89
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• 2014

Data-driven method for fault diagnostics system often use machine learning technique. To use such technique proper signal processing should be implemented such as time synchronous averaging (TSA) for ball bearing systems. However, for journal bearing diagnostics systems not much has been researched, and yet a proper signal processing method has not been studied. Therefore, in this research an optimal datum unit for a reliable journal bearing diagnostics system along with angular resampling process is being suggested. Before extracting time and frequency domain features, angular resampling is applied to each cycle of vibration data. As to preserve the characteristics of vibration signal, averaging method is replaced by finding the optimal datum unit which strengthens statistical characteristics of vibration signal. Then 20 features were extracted for various cases, and those features are being evaluated by two criteria, separability and classification accuracy.

• 대한전자공학회논문지TC
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• 제41권11호
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• pp.9-15
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• 2004

다중 안테나를 사용한 다중 반송파 대역확산 다중접속 (MIMO MC-CDMA) 시스템에 대한 V-BLAST의 수신 성능을 개선하기 위해 기존에 제안된 다단계 병렬 널링 및 병렬 부분 간섭 제거 수신기 (MPN-PPIC)의 성능을 보다 향상시키기 위한 방법으로, 최적의 간섭 제거 가중치를 구하는 방법을 제안한다. [1]에서 제안된 MPN-PPIC 방법은 병렬 간섭 제거 기법과 실험적으로 구한 최적의 간섭 제거 가중치를 이용하여 다중 사용자 환경에서 기존의 V-BLAST의 단점을 효과적으로 개선할 수 있었다. 하지만, 실험적으로 구한 가중치는 시스템에 적응적으로 적용할 수 없다는 단점이 있기 때문에, 본 논문에서는 수신신호의 신호대 간섭 및 잡음비 (SINR)을 이용한 최적의 간섭 제거 가중치를 구하는 방법을 보이고, 이를 [1]에서의 결과와 비교하기 위해 컴퓨터 모의 실험을 수행한다. 컴퓨터 모의 실험 결과, 제안한 방법이 기존의 방법에 비해 10/sup -3/의 BER에 대해서 2.5～5dB 정도의 성능 이득을 얻을 수 있음을 확인할 수 있었다.

• 한국생산제조학회지
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• 제22권1호
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• pp.63-69
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• 2013

In order to find the optimum design of structures that have characteristic natural frequency range, a numerical optimization method to solving eigenvalue problems is a widely used approach. However in the most cases, it is difficult to decide the accurate thickness and shape of structures that have allowable natural frequency in design constraints. Parallel analysis algorithm involving the feasible direction optimization method and Rayleigh-Ritz eigenvalue solving method is developed. The method is implemented by using finite element method. It calculates the optimal thickness and the thickness ratio of individual elements of the 2-D plane element through a parallel algorithm method which satisfy the design constraint of natural frequency. As a result this method of optimization for natural frequency by using finite element method can determine the optimal size or its ratio of geometrically complicated shape and large scale structure.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권7호
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• pp.339-349
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• 2001

This paper suggests an optimal identification method for complex and nonlinear system modeling that is based on Fuzzy-Neural Networks(FNN). The proposed Hybrid Identification Algorithm is based on Yamakawa's FNN and uses the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. In this paper, the FNN modeling implements parameter identification using HCM algorithm and hybrid structure combined with two types of optimization theories for nonlinear systems. We use a HCM(Hard C-Means) clustering algorithm to find initial apexes of membership function. The parameters such as apexes of membership functions, learning rates, and momentum coefficients are adjusted using hybrid algorithm. The proposed hybrid identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregated objective function(performance index) with weighting factor is introduced to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity(distribution of I/O data), we show that it is available and effective to design an optimal FNN model structure with mutual balance and dependency between approximation and generalization abilities. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.