• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.209-216
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• 2005

The controller that can control the smart base isolation system consisting of M damper and friction pendulum systems(FPS) is developed in this study. A fuzzy logic controller (FLC) is used to modulate the M damper force because the FLC has an inherent robustness and ability to handle non-linearities and uncertainties. A genetic algorithm (GA) is used for optimization of the FLC. When earthquake excitations are applied to the structures equipped with smart base isolation system, the relative displacement at the isolation level as well as the acceleration of the structure should be regulated under appropriate level. Thus, NSGA-II(Non-dominated Sorting Genetic Algorithm) is employed in this study as a multi-objective genetic algorithm to meet more than two control objectives, simultaneously. NSGA-II is used to determine appropriate fuzzy control rules as well to adjust parameters of the membership functions. Effectiveness of the proposed method for optimal design of the FLC is judged based on computed responses to several historical earthquakes. It has been shown that the proposed method can efficiently find Pareto optimal sets that can reduce both structural acceleration and base drift from numerical studies.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.1
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• pp.122-130
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• 2001

In order to improve the efficiency of the design process and the quality of the resulting design, this study proposes a design method for determining design variables of an automotive wheel-bearing unit of double-row angular-contact ball bearing type by using a genetic algorithm. The desired performance of the wheel-bearing unit is to maximize system life while satisfying geometrical and operational constraints without enlarging mounting spae. The use of gradient-based optimization methods for the design of the unit is restricted because this design problem is characterized by the presence of discrete design variables such as the number of balls and standard ball diameter. Therefore, the design problem of rolling element bearings is a constrained discrete optimization problem. A genetic algorithm using real coding and dynamic mutation rate is used to efficiently find the optimum discrete design values. To effectively deal with the design constraints, a ranking method is suggested for constructing a fitness function in the genetic algorithm. A computer program is developed and applied to the design of a real wheel-bearing unit model to evaluate the proposed design method. Optimum design results demonstrate the effectiveness of the design method suggested in this study by showing that the system life of an optimally designed wheel-bearing unit is enhanced in comparison with that of the current design without any constraint violations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.997-1000
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• 2005

Dynamic job shop environment requires not only more flexible capabilities of a CAPP system but higher utility of the generated process plans. In order to meet the requirements, this paper develops an algorithm that can select machines for the machining operations to be performed by predicting the machine loads. The developed algorithm is based on the multiple objective genetic algorithm that gives rise to a set of optimal solutions (in general, known as Pareto-optimal solutions). The objective shows a combination of the minimization of part movement and the maximization of machine utility balance. The algorithm is characterized by a new and efficient method for nondominated sorting, which can speed up the running time, as well as a method of two stages for genetic operations, which can maintain a diverse set of solutions. The performance of the algorithm is evaluated by comparing with another multiple objective genetic algorithm, called NSGA-II.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.63-82
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• 2007

In this paper, we propose an adaptive hybrid genetic algorithm (ahGA) approach for effectively solving multistage-based scheduling problems in flexible manufacturing system (FMS) environment. The proposed ahGA uses a neighborhood search technique for local search and an adaptive scheme for regulation of GA parameters in order to improve the solution of FMS scheduling problem and to enhance the performance of genetic search process, respectively. In numerical experiment, we present two types of multistage-based scheduling problems to compare the performances of the proposed ahGA with conventional competing algorithms. Experimental results show that the proposed ahGA outperforms the conventional algorithms.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.164-169
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• 2003

In this paper, we propose the integrated Bayesian network framework to reconstruct genetic regulatory networks from genome expression data. The proposed model overcomes the dimensionality problem of multivariate analysis by building coherent sub-networks from confined gene clusters and combining these networks via intermediary points. Gene Shaving algorithm is used to cluster genes that share a common function or co-regulation. Retrieved clusters incorporate prior biological knowledge such as Gene Ontology, pathway, and protein protein interaction information for extracting other related genes. With these extended gene list, system builds genetic sub-networks using Bayesian network with MDL score and Sparse Candidate algorithm. Identifying functional modules of genes is done by not only microarray data itself but also well-proved biological knowledge. This integrated approach can improve there liability of a network in that false relations due to the lack of data can be reduced. Another advantage is the decreased computational complexity by constrained gene sets. To evaluate the proposed system, S. Cerevisiae cell cycle data [1] is applied. The result analysis presents new hypotheses about novel genetic interactions as well as typical relationships known by previous researches [2].

• Journal of Microbiology and Biotechnology
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• v.4 no.3
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• pp.204-209
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• 1994

The synthesis of N-(benzyloxycarbonyl)-L-aspartyl-L-phenylalanine methylester (Z-APM), a precursor of aspartame, from N-(benzyloxycarbonyl)-L-aspartic acid (Z-Asp) and L-phenylalanine methylester hydrochlolide($L-PM\cdot HCI$) was investigated in a saturated-ethylacetate single phase system using immobilized thermolysin. Among the various supports tested, glyceryl-CPG was found to be most efficient for retaining enzyme activity. The enzyme immobilized onto glyceryl-CPG also showed the highest activity for Z-APM synthesis in saturated ethyl acetate. Z-APM conversion yield in saturated ethylacetate was half of that obtained in an ethyl acetate-buffer two-phase system under the same reaction conditions. However, as the mole ratio of $L-PM \cdot HCI$ to Z-Asp was increased to 4.0, the conversion yield reached 95 %. When continuous synthesis of Z-APM was canied out in a plug flow reactor (PFR) with 80 mM of L-PMㆍHCI and 20 mM of Z-Asp in saturated ethylacetate (pH 5.5), more than 95 % of Z-Asp was converted to Z-APM with a space velocity of 1.16 $hr^{-1} at 40^{\circ}C$. Although the operational stability in PFR was reduced rapidly, more than 80% of initial activity was maintained in CSTR even after a week of operation.

• Journal of Microbiology and Biotechnology
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• v.3 no.3
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• pp.168-173
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• 1993

The expression kinetics of human lipocortin I (LCI), a potential anti-inflammatory agent, was studied in the shake-flask and fermenter cultures of Saccharomyces cerevisiae carrying a galactose-inducible expression system. The cell growth, expression level of LCI, and the plasmid stability were investigted under various galactose induction conditions. The expression of LCI was repressed by the presence of a very small amount of dextrose in the culture medium, but it was induced by galactose after dextrose became completely depleted. The optimal ratio of dextrose to galactose for lipocortin I production was found to be 1.0 (10 g/l dextrose and 10 g/l galactose). With optimal D/G ratio of 1.0 and the addition of galactose prior to dextrose depletion, LCI of about 100~130 mg/l was produced. LCI at a concentration of 174 mg/l was porduced in the fed-batch culture, which was nearly a twice as much of that produced in the batch culture. The plasmid stability was very high in all culture cases, and thus was considered to be not an important parameter in the expression of LCI.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.2
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• pp.9-15
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• 2001

This paper describes a new method of Genetic Algorithms for Adaptive Fuzzy Control System. Previous works using a Multi-population Genetic Algorithm have divided chromosome into two components, rule sets and membership functions. However, in this case bad rule sets disturb optimization in good rule sets and membership functions. A new method for a Multi population Genetic Algorithm suggests three components, good rule sets, bad rule sets, and membership functions. To show the effectiveness of this method, fuzzy controller is applied to a Truck Backing Problem. Results of the computer simulation show good adaptation of the proposed method.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.5
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• pp.361-368
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• 2015

This paper deals with a robust fine seek controller design problem with multiple constraints using a genetic algorithm. A robust $H\infty$ constraint is introduced to attenuate effectively velocity disturbance caused by the eccentric rotation of the disk. A weighting function is optimally selected based on the estimation of velocity disturbance and the estimated minimum velocity loop gain. A robust velocity loop constraint is considered to minimize the variances of the velocity loop gain and bandwidth against the uncertainties of fine actuator. Finally, a robust fine seek controller is obtained by solving a genetic algorithm with an LMI condition and an appropriate objective function. The proposed controller design method is applied to the fine seek control system of a DVD recording device and is evaluated through the experimental results.

• Journal of Korean Society of Steel Construction
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• v.18 no.6
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• pp.707-716
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• 2006

The optimization of the direct design system of semi-rigid steel frames using advanced analysis and genetic algorithm was presented. Advanced analysis can predict the combined nonlinear effects of connection, geometry, and material on the behavior and strength of semi-rigid frames. Geometric nonlinearity was determined using stability functions. On the other hand, material nonlinearity was determined using the Column Research Council (CRC) tangent modulus and parabolic function. The Kishi-Chen power model was used to describe the nonlinear behavior of semi-rigid connections. The genetic algorithm was used as the optimization technique. The objective function was assumed as the weight of the steel frame, with the constraint functions accounting for load-carrying capacities, deflections, inter-story drifts and ductility requirement. Member sizes determined by the proposed method were compared with those derived using the conventional method.