• Journal of Applied Biological Chemistry
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• v.43 no.2
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• pp.109-111
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• 2000

Effect of the two-stage operation and cell concentration on indirubin production was investigated using bioreactor culture of Polygonum tinctorium. Two-stage culture was operated successfully for 110 days without any adverse effects on continuous indirubin production. Maximum indirubin concentration was found to be at 80 mg/bioreactor. Initial cell concentration significantly affected indirubin production. The indirubin production at 29.2% PCV was improved by 845%, compared to that at 5% PCV. For high-density bioreactor culture of P. tinctorium, a maximum production rate of 10.2 mg indirubin/L day was obtained. Indirubin recovery for bioreactor operation was also examined using XAD-2, XAD-4, XAD-7, and solid silicon. XAD-4 was 1.6-fold more effective than that for solid silicon in indirubin recovery.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.6
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• pp.242-248
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• 2006

This paper proposes a coordinated control method for under-load tap changers (ULTCs) with shunt capacitors to reduce the operation numbers of both devices. The proposed method consists of two stages. In the first stage, the dispatch schedule is determined using a genetic algorithm with forecasted loads to reduce the power loss and to improve the voltage profile during a day. In the second stage, each capacitor operates according to this dispatch schedule and the ULTCs are controlled in real time with the modified reference voltages considering the dispatch schedule of the capacitors. The performance of the method is evaluated for the modified IEEE 14-bus system. Simulation results show that the proposed method performs better than a conventional control method.

• Journal of Korean Association for Spatial Structures
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• v.5 no.3 s.17
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• pp.117-122
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• 2005

This paper investigated the optimum design of truss structures based on Genetic Algorithms (GA's). With GA's characteristic of running side by side, the overall optimization and feasible operation, the optimum design model of truss structures was established. Elite models were used to assure that the best units of the previous generation had access to the evolution of current generation. Using of non-uniformity mutation brought the obvious mutation at earlier stage and stable mutation in the later stage; this benefited the convergence of units to the best result. In addition, to avoid GA's drawback of converging to local optimization easily, by the limit value of each variable was changed respectively and the genetic operation was performed two times, so the program could work more efficiently and obtained more precise results. Finally, by simulating evolution process of nature biology of a kind self-organize, self-organize, artificial intelligence, this paper established continuous structural optimization model for ten bars cantilever truss, and obtained satisfactory result of optimum design. This paper further explained that structural optimization is practicable with GA's, and provided the theoretic basis for the GA's optimum design of structural engineering.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.524-524
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• 2000

We have been developing a method to build one-step-ahead prediction models for time series using genetic programming (GP). Our model building method consists of two stages. In the first stage, functional forms of the models are inherited from their parent models through crossover operation of GP. In the second stage, the parameters of the newborn model arc optimized based on an iterative method just like the back propagation. The proposed method has been applied to various kinds of time series problems. An application to the seismic ground motion was presented in the KACC'99, and since then the method has been improved in many aspects, for example, additions of new node functions, improvements of the node functions, and new exploitations of many kinds of mutation operators. The new ideas and trials enhance the ability to generate effective and complicated models and reduce CPU time. Today, we will present a couple of financial applications, espc:cially focusing on gold price prediction in Tokyo market.

• Journal of Microbiology and Biotechnology
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• v.10 no.1
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• pp.75-80
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• 2000

An improved method of refolding recombinant human proinsulin from E. coli was presented. It was based on a two-stage stirred tank reactor in which denatured proinsulin-s-sulfonate was mixed instantaneously with a reaction buffer in the first stage reactor, and then fed to the second stage reactor. The mixture was stirred further for a total of 30h in the second stage reactor. In this system, unfavorable effects present due to the increase in reaction volume and protein concentration for protein refolding, which becomes significant in a large-scale operation, were avoided. Refolding yields of over 80% was obtained for achieving reaction volume of upto 50 l at protein concentration of 1 mg/ml. The optimum urea concentration was 1M. Refolding yield at the 1-1 reaction volume and protein concentration of 0.5mg/ml was increased about 2.5-fold, compared to that in a batch reactor. By increasing protein concentration in a two-stage refolding reaction, the cost for insulin production could be reduced, therefore, making this process economical.

• Industrial Engineering and Management Systems
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• v.8 no.4
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• pp.228-238
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• 2009

This paper first presents two supply chain design problems: 1) a factory location setting and factory selection problem, and 2) a factory location setting and factory/supplier selection problem. The first involves a number of location known retailers choosing one factory to supply their demands from a number of factories whose locations are to be determined. The goal is to minimize the transportation and manufacturing cost to satisfy the demands. The problem is then augmented into the second problem, where the procurement cost of the raw materials from a chosen material supplier (from a number of suppliers) is considered for each factory. Economic beneficial is taken into account in the cost evaluation. Therefore, the partner selections will influence the cost of the supply chain significantly. To solve these problems, an agent gaming and genetic algorithm hybrid method (AGGAHM) is proposed. The AGGAHM consecutively and alternatively enable and disable the advancement of agent gaming and the evolution of genetic computation. Computation results on solving a number of examples by the AGGAHM were compared with those from methods of a general genetic algorithm and a mutual frozen genetic algorithm. Results showed that the AGGAHM outperforms the methods solely using genetic algorithms. In addition, various parameter settings are tested and discussed to facilitate the supply chain designs.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.53-63
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• 2017

The increasing of wind power penetration level presents challenges in classical optimal reactive power dispatch (ORPD) which is usually formulated as a deterministic optimization problem. This paper proposes a two-stage stochastic programming model for ORPD by considering the uncertainties of wind speed and load in a specified time interval. To avoid the excessive operation, the schedule of compensators will be determined in the first-stage while accounting for the costs of adjusting the compensators (CACs). Under uncertainty effects, on-load tap changer (OLTC) and generator in the second-stage will compensate the mismatch caused by the first-stage decision. The objective of the proposed model is to minimize the sum of CACs and the expected energy loss. The stochastic behavior is formulated by three-point estimate method (TPEM) to convert the stochastic programming into equivalent deterministic problem. A hybrid Genetic Algorithm-Interior Point Method is utilized to solve this large-scale mixed-integer nonlinear stochastic problem. Two case studies on IEEE 14-bus and IEEE 118-bus system are provided to illustrate the effectiveness of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.11 no.3
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• pp.551-559
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• 2016

The present trend of increasing the penetration levels of Distributed Generator (DG) in the distribution network has made the issue of Islanding crucial for the reliable operation of the network. The islanding, if not detected early may lead to the collapse of the system as it can drive the distribution system to the cascaded failure. In this paper, an extensive study of the effect of DG placement and sizing is performed by dividing the system into different zones to obtain a reduced effect of islanding. The siting and sizing of DG is carried out to improve the overall voltage profile or/and reduction in active power loss using two stage Genetic Algorithm (GA). In the first stage a basic knockout selection is considered and the best population is taken for next stage, where roulette selection for crossover and mutation is performed for optimal placement and sizing of DGs. The effect of the islanding, due to load variations is reduced by optimal siting and sizing of DG. The effectiveness of the proposed scheme is tested on the IEEE 33 and 69 radial bus systems and the results obtained are promising.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.28 no.7
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• pp.299-304
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• 2016

In recent years, heat source systems which have a principal effect on the performance of buildings are difficult to design optimally as a great number of design factors and constraints in large and complicated buildings need to be considered. On the other hand, it is necessary to design an optimum system combination and operation planning for energy efficiency considering Life Cycle Cost (LCC). This study suggests a multi-level and multi-objective optimization method to minimize both LCC and investment cost using a genetic algorithm targeting an office building which requires a large cooling load. The optimum method uses a two stage process to derive the system combination and the operation schedule by utilizing the input data of cooling and heating load profile and system performance characteristics calculated by dynamic energy simulation. The results were assessed by Pareto analysis and a number of Pareto optimal solutions were determined. Moreover, it was confirmed that the derived operation schedule was useful for operating the heat source systems efficiently against the building energy requirements. Consequently, the proposed optimization method is determined by a valid way if the design process is difficult to optimize.

• Journal of Microbiology and Biotechnology
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• v.4 no.2
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• pp.146-150
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• 1994

Production of poly-$\beta$-hydroxybutyrate (PHB) in fed-batch fermentation was studied. Utilization of carbon for PHB biosynthesis was investigated by using feeding solutions with different ratios of carbon to nitrogen (C/N). It was observed that at a high C/N ratio carbon source was more preferably utilized for PHB accumulation while its consumption for cellular metabolism appeared to be more favored at a low C/N value. A high cell concentration (184 g/l) was achieved when ammonium hydroxide solution was fed to control the pH, which was also utilized as the sole nitrogen source. For the mass production of PHB, two-stage fed-batch operations were carried out where PHB accumulation was observed to be stimulated by switching the ammonium feeding mode to the nitrogen limiting condition. A large amount of PHB (108 g/l) was obtained with cellular content of 80% within 50 hrs of operation.