• Journal of Electrical Engineering and information Science
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• 제2권3호
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• pp.14-21
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• 1997

In delay-optimized designs, timing failures due to manufacturing delay defects are more likely to occur because the average timing slacks of paths decrease and the system becomes more sensitive to smaller delay defect sizes. In this paper, the impact of delay optimized logic circuits on delay fault testing will be discussed and compared to the case for non-optimized designs. First, we provide a timing optimization procedure and show that the resultant density function of path delays is a delta function. Next we also discuss the impact of timing optimization on the yield of a manufacturing process and the defect level for delay faults. Finally, we will give some recommendations on the determination of the system clock time so that the delay-optimized design will have the same manufacturing yield as the non-optimized design and on the determination of delay fault coverage in the delay-optimized design in order to have the same defect-level for delay faults as the non-optimized design, while the system clock time is the same for both designs.

• 한국환경과학회지
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• 제22권12호
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• pp.1625-1631
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• 2013

In manufacturing of flatfish skin collagen peptide (FSCP) and flatfish protein hydrolysate (FPH) by reuse of dead flatfish from fish farm in Jeju island, the industrial process was optimized with the laboratory scale research and the on-field process. Segmented unit processes from raw material incoming to shipment were established to produce commercial product of FSCP and FPH. Total plate counts of FSCP were twenty five times of FPH, but food poisoning bacteria were not detected in two samples. FSCP and FPH were safe from heavy metal such as Pb(II), Cd(II) and Hg(II). The residual contents of antibiotics and disinfection matter in FSCP and FPH were not detected. The optimized process for mass production made the one-third of the running time and two times of the yield. From economic analysis, the production cost was estimated to 22,000 and 12,000 won/kg for FSCP and FPH, respectively. Therefore the product from the reuse of dead flatfish was expected to have a considerable competitive price and high added-value functional food material compared with other commercially available fish products.

• 정보처리학회논문지A
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• 제8A권3호
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• pp.209-216
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• 2001

복잡한 언어 처리에 점진적 속성 문법을 적용하기 위해서는 최적화 알고리즘을 사용하는 것이 효과적이다. 점진적 속성문법의 최적화 알고리즘에서는 새로운 입력 속성 트리가 기존 입력 속성 트리와 정확히 비교되어서 새로운 속성 트리를 구성할 대 기존 속성 트리의 어떤 서브트리를 사용해야 하는가를 결정한다. 본 논문에서는 Carle과 Pollock에 의해 제안된 알고리즘을 분석하여 효과적인 최적화 알고리즘으로 재구성하고, 새로은 속성 트리 d'copy의 생성 과정과, 속성트리 d'copy의 새로운 최적화 알고리즘을 추가하였다. 이 논문에서 제안한 매칭 알고리즘의 성능평가를 통하여 기존의 알고리즘 보다 제안한 최적화 알고리즘의 실행 시간을 약 19.5% 향상 시킬 수 있었다.

• 한국생산제조학회지
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• 제18권6호
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• pp.590-597
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• 2009

The final quality of the workpiece is affected by the grinding process that has been conducted in final manufacturing stage. However the quality-satisfaction of ground workpiece depends on the skill of an expert in this process. Therefore, the process models of grinding have been developed to predict the states according to grinding process. In this paper, in order to find the optimized grinding condition to reduce the manufacturing expense and to meet requirements of ground workpiece optimization algorithm using E.S.(Evolutionary Strategy) is proposed. The proposed algorithm has been employed to find the optimal grinding and dressing condition using the grinding process models and nonlinear grinding constraints. The optimized results also presents the guide line of grinding process. The effectiveness of the proposed algorithm is verified through the experimental results.

• 한국주조공학회지
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• 제29권5호
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• pp.198-203
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• 2009

In order to manufacture copper ultra fine wire used for bonding wire in integrated circuit package, continuous casting process, which can produce high purity copper rod with small cross section, and wiredrawing process have to be optimized to prevent wire brakeage during entire manufacturing process of fine wire. The optimum condition for producing copper rod with mirror surface has to established by investigation of the effects of several parameters such as withdrawal speed, superheat and rod diameter on grain morphology of the cast rod and on its drawing characteristics to fine wire. The purpose of this study is to propose the optimized process parameters in continuous casting process in order to produce cast rod without internal defects, and to predict microstructure orientation suitable for wire drawing process.

• 대한전기학회논문지
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• 제43권6호
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• pp.1020-1026
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• 1994

This paper presents a technique to optimize the shape of waveguide components in H-plane. The technique utilizes the numerical optimization process which employs the vector finite element method. In the optimization process, the sensitivity of an objective function with respect to design variables is computed by introducting adjoint variables, which makes the computation easy. The steepest descent method is then employed to update design variables. As a numerical example, an H-plane waveguide teejunction was considered to obtain optimized shape. Comparison between the initial and optimized shape was made.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.152-154
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• 2005

In this paper, we propose a new architecture of Fuzzy Polynomial Neural Networks(FPNN) by means of genetically optimized Fuzzy Polynomial Neuron(FPN) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially Genetic Algorithms(GAs). The design of the network exploits the extended Group Method of Data Handling(GMDH) with some essential parameters of the network being provided by the designer and kept fixed throughout the overall development process. This restriction may hamper a possibility of producing an optimal architecture of the model. The proposed FPNN gives rise to a structurally optimized network and comes with a substantial level of flexibility in comparison to the one we encounter in conventional FPNNs. It is shown that the proposed genetic algorithms-based Fuzzy Polynomial Neural Networks is more useful and effective than the existing models for nonlinear process. We experimented with Medical Imaging System(MIS) dataset to evaluate the performance of the proposed model.

• Biotechnology and Bioprocess Engineering:BBE
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• 제6권1호
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• pp.6-10
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• 2001

The production of chitosan from the mycelia of Absidia coerulea was studied to improve cell growth and chitosan productivity. Culture conditions were optimized in batch cultivation (pH 4.5, agitator speed of 250 rpm, and aeration rate of 2 vvm) and the maximum chitosan concentration achieved was 2.3g/L under optimized conditions. Continuous culture was carried out successfully by the formation of new growth spots under optimized conditions, with a chitosan productivity of 0.052g/L(sup)-1 h(sup)-1, which is the highest value to date, and was obtained at a dulution rate of 0.05h(sup)-1. Cell chitosan concentrations reached about 14% in the steady state, which is similar to that achieved in batch culture. This study shows that for the continuous culture of Absidia coerulea it is vital to control the medium composition.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권1호
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• pp.33-38
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• 2006

In this paper, we propose a new architecture of Fuzzy Polynomial Neural Networks(FPNN) by means of genetically optimized Fuzzy Polynomial Neuron(FPN) and discuss its comprehensive design methodology involving mechanisms of genetic optimization, especially Genetic Algorithms(GAs). The conventional FPNN developed so far are based on mechanisms of self-organization and evolutionary optimization. The design of the network exploits the extended Group Method of Data Handling(GMDH) with some essential parameters of the network being provided by the designer and kept fixed throughout the overall development process. This restriction may hamper a possibility of producing an optimal architecture of the model. The proposed FPNN gives rise to a structurally optimized network and comes with a substantial level of flexibility in comparison to the one we encounter in conventional FPNNs. It is shown that the proposed advanced genetic algorithms based Fuzzy Polynomial Neural Networks is more useful and effective than the existing models for nonlinear process. We experimented with Medical Imaging System(MIS) dataset to evaluate the performance of the proposed model.

• 전기학회논문지P
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• 제63권4호
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• pp.290-294
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• 2014

PID(Proportional, Integral, Derivative) controller is the most popular process controllers in nuclear power plants. The optimized parameter setting of the process controller contributes to the stable operation and the efficiency of the operating nuclear power plants. PID parameter setting is tuned when new process control systems are installed or current process control systems are changed. When the nuclear plant is shut down, a lot of PID tuning methods such as the Trial and Error method, Ultimate Oscillation method operation, Ziegler-Nichols method, frequency method are used to tune the PID values. But inadequate PID parameter setting can be the cause of the unstable process of the operating nuclear power plant. Therefore the results of PID parameter setting should be simulated, optimized and finally verified. This paper introduces the simulation method of PID tuning to optimize the PID parameter setting and confirms them of the actual PID controller in the operating nuclear power plants. The simulation method provides the accurate process modeling and optimized PID parameter setting of the multi-loop control process in particular.