• Journal of Microbiology and Biotechnology
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• v.30 no.6
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• pp.793-803
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• 2020

Adaptive laboratory evolution (ALE) is an evolutionary engineering approach in artificial conditions that improves organisms through the imitation of natural evolution. Due to the development of multi-level omics technologies in recent decades, ALE can be performed for various purposes at the laboratory level. This review delineates the basics of the experimental design of ALE based on several ALE studies of industrial microbial strains and updates current strategies combined with progressed metabolic engineering, in silico modeling and automation to maximize the evolution efficiency. Moreover, the review sheds light on the applicability of ALE as a strain development approach that complies with non-recombinant preferences in various food industries. Overall, recent progress in the utilization of ALE for strain development leading to successful industrialization is discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.399-404
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• 2012

Evolutionary algorithms such as genetic algorithm (GA) have been proven their effectiveness when applying to the design of fuzzy models. However, it tends to suffer from computationally expensWive due to the slow convergence speed. In this study, we propose an approach to develop fuzzy models by means of an improved differential evolution (IDE) to overcome this limitation. The improved differential evolution (IDE) is realized by means of an orthogonal approach and differential evolution. With the invoking orthogonal method, the IDE can search the solution space more efficiently. In the design of fuzzy models, we concern two mechanisms, namely structure identification and parameter estimation. The structure identification is supported by the IDE and C-Means while the parameter estimation is realized via IDE and a standard least square error method. Experimental studies demonstrate that the proposed model leads to improved performance. The proposed model is also contrasted with the quality of some fuzzy models already reported in the literature.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.221-224
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• 2009

In this paper, we deal with the development of an optimal design program for a dual-band of 0.92 GHz and 2.45 GHz with shorting pin and slot by using evolution strategy. the optimal shorting pin, coaxial feed and H-shaped patch are determined by using an optimal design program based on the evolution strategy. To achieve this, an interface program between a commercial EM analysis tool and the optimal design program is constructed for implementing the evolution strategy technique that seeks a global optimum of the objective function through the iterative design process consisting of variation and reproduction. The resonance frequencies of the dual-band antenna yielded by the optimal design program are 0.92 GHz and 2.45 GHz that show a good agreement to the design target values.

• Genomics & Informatics
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• v.1 no.1
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• pp.7-19
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• 2003

The latest measure of the relative evolutionary age of protein structure families was applied (based on taxonomic diversity) using the protein structural interactome map (PSIMAP). It confirms that, in general, protein domains, which are hubs in this interaction network, are older than protein domains with fewer interaction partners. We apply a hypothesis of 'biological network evolution' to explain the positive correlation between interaction and age. It agrees to the previous suggestions that proteins have acquired an increasing number of interaction partners over time via the stepwise addition of new interactions. This hypothesis is shown to be consistent with the scale-free interaction network topologies proposed by other groups. Closely co-evolved structural interaction and the dynamics of network evolution are used to explain the highly conserved core of protein interaction pathways, which exist across all divisions of life.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.165.1-165
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• 2001

The evolution strategy is a good evolutionary algorithm to find the global optimum of a real-valued function. Since many engineering problems can be formulated as real valued function optimization, the evolution strategy is frequently employed in engineering fields. However, in many engineering optimization problems, an optimization parameter is often restricted in the bounded region between two specified values, the minimum and the maximum limit, respectively. Since an offspring individual is generated randomly around a parent individual during mutation process of the evolution strategy, an individual outside the search region can be generated even if the parent is inside the search region. This paper proposes two new boundary-handling techniques for evolution strategies. One is the ...

• The Bulletin of The Korean Astronomical Society
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• v.42 no.1
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• pp.53.1-53.1
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• 2017

The YONSEI (YOnsei Nearby Supernova Evolution Investigation) project is to investigate the luminosity evolution of Type Ia supernovae (SNe Ia) by using their early-type host galaxies. As a part of this project, we have constructed our own SN catalogue. SALT2 and MLCS2k2 light-curve fitters implemented in SNANA package are employed to analyze the light-curve data. The catalogue provides a rest-frame peak magnitude in B-band or distance modulus, a light-curve shape parameter, and a color or an extinction value of each SN in the redshift range from 0.01 to 1.4. In this poster, we will present our progress in the detailed systematic tests for this catalogue.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.1
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• pp.31.3-31.3
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• 2017

The presence of a bar in disk galaxies indicates that galaxies reached their dynamical maturity, and secular evolution has started to play key roles in the evolution of disk galaxies. Numerical simulations predicted that as a barred galaxy evolves, the bar becomes longer by capturing its immediate neighbor disk stars. We test the hypothesis by exploring bar lengths and measuring the light deficit around the bar at various redshift. Supplementing already classified barred galaxies in later type disk galaxies ($$T{\geq_-}2$$, Sheth et al. 2008), we classify barred galaxies among earlier type disk galaxies (T<2) up to z~0.8 using F814W images from the Cosmic Evolution Survey (COSMOS). We estimate the length of bars analytically for ~400 galaxies, and find that there is a slight decrease in bar length with redshift. We also find that longer bars show more prominent light deficit around the bar and this trend is stronger for nearby galaxies. Our results are consistent with the predictions from numerical simulations, and imply that the bar induced secular evolution is already in place since z~0.8. 

• Journal of the Korea Society for Simulation
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• v.13 no.4
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• pp.17-29
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• 2004

The focus of this study is to represent a methodology of analysis for integrated logistic system by means of the Evolution Strategies and Data Envelopment Analysis(DEA). The integrated logistic system is composed of AS/RS (Automated Storages and Retrieval System), AGVs(Automated Guided Vehicle System) and Conveyor System. We design the simulation alternatives with choosing the qualitative critical factors for the each subsystem. Evolution Strategies is used to optimize the quantitative critical factors and responses of each alternative. DEA is applied to measure the efficiency of the alternatives in order to select the optimal operation efficiency scheme. The method of analysis which combines Evolution Strategies with DEA can be used to analyze the qualitative and quantitative critical factors in the integrated logistic systems.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.282-287
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• 2008

In distributed mobile robot systems, autonomous robots accomplish complicated tasks through intelligent cooperation with each other. This paper presents behavior learning and online distributed evolution for cooperative behavior of a group of autonomous robots. Learning and evolution capabilities are essential for a group of autonomous robots to adapt to unstructured environments. Behavior learning finds an optimal state-action mapping of a robot for a given operating condition. In behavior learning, a Q-learning algorithm is modified to handle delayed rewards in the distributed robot systems. A group of robots implements cooperative behaviors through communication with other robots. Individual robots improve the state-action mapping through online evolution with the crossover operator based on the Q-values and their update frequencies. A cooperative material search problem demonstrated the effectiveness of the proposed behavior learning and online distributed evolution method for implementing cooperative behavior of a group of autonomous mobile robots.

• Journal of the East Asian Society of Dietary Life
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• v.7 no.3
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• pp.325-329
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• 1997

The optimum temperature and pH for growth and hydrogen evolution of the organism were observed at 30-35$^{\circ}C$, and around pH 7.0, respectively. The efficiency of various sugars and organic acids on hydrogen evolution as electron donors by the organism was examined. Among them, higher rates of hydrogen evolution were observed with sugars such as glucose or fructose and organic acids such as alate or pyruvate. From the result, it was evident that Rhodobacter sphaeroides KS56 had a great capacity of utilizing various kinds of reduced carbon compounds as electron donors.