• Journal of Digital Convergence
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• v.14 no.8
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• pp.293-303
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• 2016

Analysis of bargaining games utilizing evolutionary computation in recent years has dealt with important issues in the field of game theory. In this paper, we investigated interaction and coevolution process among heterogeneous artificial agents using evolutionary computation in the bargaining game. We present three kinds of evolving-strategic agents participating in the bargaining games; genetic algorithms (GA), particle swarm optimization (PSO) and differential evolution (DE). The co-evolutionary processes among three kinds of artificial agents which are GA-agent, PSO-agent, and DE-agent are tested to observe which EC-agent shows the best performance in the bargaining game. The simulation results show that a PSO-agent is better than a GA-agent and a DE-agent, and that a GA-agent is better than a DE-agent with respect to co-evolution in bargaining game. In order to understand why a PSO-agent is the best among three kinds of artificial agents in the bargaining game, we observed the strategies of artificial agents after completion of game. The results indicated that the PSO-agent evolves in direction of the strategy to gain as much as possible at the risk of gaining no property upon failure of the transaction, while the GA-agent and the DE-agent evolve in direction of the strategy to accomplish the transaction regardless of the quantity.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.4
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• pp.29-43
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• 2017

Innovation Cosystems are Conceptualized as Organizational Networks of Economic Actors, Technologies and Social Contexts that Interact for Knowledge Production, use, and Adaptation. This Paper Proposed a Conceptual Framework to Describe Value Co-creation of Organizational Networks Engaged in Technology Innovation. We Adopted Theory-Based Approach by Integrating the Perspective of Service-Dominant (S-D) Logic Into the Evolutionary Model of the Triple Helix. The Framework Gives a Plausible Explanation on how Actors Collaborate to Create Value in Dynamic Contexts of an Innovation Ecosystem. The Innovation Ecosystem can be Considered as a Composite of Sub-Ecosystems, Including Knowledge, Sectoral, and Business Ecosystems. When these Sub-Ecosystems are Recursively Transformed by Coordination of Functional Mechanisms that Serve Value Co-creation in the Innovation Process, the Innovation Ecosystem will be Re-Organized and Evolve. The case of the Digital Living Network Alliance (DLNA) was Examined to Demonstrate the Fundamental Mechanisms for Value Co-creation that was Described in the Framework. The case Study Indicates Features of Value Co-creation when Implementing Innovation in Organizational Networks.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.223-226
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• 1997

Usually, the Evolutionary Algorithms(EAs) are considered more efficient for optimal, system design because EAs can provide higher opportunity for obtaining the global optimal solution. This paper presents a mechanism of co-evolution consists of the two genetic algorithms(GAs). This mechanism includes host populations and parasite populations. These two populations are closely related to each other, and the parasite populations plays an important role of searching for useful schema in host populations. Host population represented by feedforward neural network and the result of co-evolution we will find the optimal structure of the neural network. We used the genetic algorithm that search the structure of the feedforward neural network, and evolution strategies which train the weight of neuron, and optimize the net structure. The validity and effectiveness of the proposed method is exemplified on the stabilization and position control of the inverted-pendulum system.

• BMB Reports
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• v.50 no.12
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• pp.597-598
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• 2017

Mitochondria have evolutionarily, functionally and structurally distinct outer- (OMM) and inner-membranes (IMM). Thus, mitochondrial morphology is controlled by independent but coordinated activity of fission and fusion of the OMM and IMM. Constriction and division of the OMM are mediated by endocytosis-like machineries, which include dynamin-related protein 1 with additional cytosolic vesicle scissoring machineries such as actin filament and Dynamin 2. However, structural alteration of the IMM during mitochondrial division has been poorly understood. Recently, we found that the IMM and the inner compartments undergo transient and reversible constriction prior to the OMM division, which we termed CoMIC, ${\underline{C}}onstriction$ ${\underline{o}}f$ ${\underline{M}}itochondrial$ ${\underline{I}}nner$ ${\underline{C}}ompartment$. In this short review, we further discuss the evolutionary perspective and the regulatory mechanism of CoMIC during mitochondrial division.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.54.1-54.1
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• 2015

We observed 38 Planck Cold Clumps (PCCs) in the $850{\mu}m$ dust continuum emission using the JCMT/SCUBA-2, and detected the emission in 15 clumps containing dense cores. In this poster we present the preliminary results. The PCCs are cold, dense, and thus, they are considered as objects in the early evolutionary stages of star formation. The sources in our sample were selected based on the Purple Mountain Observatory (PMO) 13CO (1-0) integrated intensity maps. In order to examine whether these cores detected in $850{\mu}m$ continuum have potential to be prestellar cores, we compare each core mass estimated from the $850{\mu}m$ continuum with the Virial mass and Bonnor-Ebert (BE) mass calculated from the 13CO (1-0) or C18O (1-0) spectra. By comparing the two column densities from the dust continuum and the 13CO (1-0) or C18O (1-0) line, we also derive the CO depletion factor, which could be an indicator of core evolution. The moment maps of the 13CO (1-0) line are used to study the physical properties (e.g. kinematics, turbulence) of PCCs. We investigate difference between the sources with and without detectable $850{\mu}m$ emission to study the formation conditions of dense cores.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.4
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• pp.67-75
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• 1998

In general, Evoluationary Algorithm(EAs) are refered to as methods of population-based optimization. And EAs are considered as very efficient methods of optimal sytem design because they can provice much opportunity for obtaining the global optimal solution. This paper presents a co-evolution scheme of artifical neural networks, which has two different, still cooperatively working, populations, called as a host popuation and a parasite population, respectively. Using the conventional generatic algorithm the host population is evolved in the given environment, and the parastie population composed of schemata is evolved to find useful schema for the host population. the structure of artificial neural network is a diagonal recurrent neural netork which has self-feedback loops only in its hidden nodes. To find optimal neural networks we should take into account the structure of the neural network as well as the adaptive parameters, weight of neurons. So we use the genetic algorithm that searches the structure of the neural network by the co-evolution mechanism, and for the weights learning we adopted the evolutionary stategies. As a results of co-evolution we will find the optimal structure of the neural network in a short time with a small population. The validity and effectiveness of the proposed method are inspected by applying it to the stabilization and position control of the invered-pendulum system. And we will show that the result of co-evolution is better than that of the conventioal genetic algorithm.

• Journal of the Society of Naval Architects of Korea
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• v.48 no.4
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• pp.325-329
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• 2011

Floating, production, storage and offloading (FPSO) is a production facility that refines and saves the drilled crude oil from a drilling facility in the ocean. The flare system in the FPSO is a major part of the pressure relieving system for hydrocarbon processing plants. The flare system consists of a number of pipes and complicated connection systems. Decision of pipe support types is important since the load on the support and the stress in the pipe are influenced by the pipe support type. In this study, we optimally determined the pipe support types that minimized the support cost while satisfying the design constraints on maximum support load, maximum nozzle load and maximum pipe stress ratio. Performance indices included in the design constraints for a specified design were evaluated by pipe structural analysis using CAESAR II. Since pipe support types were all discrete design variables, an evolutionary algorithm (EA) was used as an optimizer. We successfully obtained the optimal solution that reduced the support cost by 27.2% compared to the initial support cost while all the design requirements were satisfied.

• Journal of the Earthquake Engineering Society of Korea
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• v.15 no.2
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• pp.1-9
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• 2011

An optimal design method for a structural control system considering load variations due to their uncertain characteristics is studied in this paper. The conventional design problem for a control system generally deals with the optimization problem of a structural control system and interaction between the structure and the control device. This study deals with the optimization problem of a load-structure-control system and the more complicated interactions with each other. The problem of finding the load that maximizes the structural responses and the structural control system that minimizes the responses simultaneously is formulated as the min-max problem. In order to effectively obtain the optimal design variables, a co-evolutionary algorithm is adopted and, as a result, an optimal design procedure for the linear structural control system with uncertain dynamic characteristics is proposed. The example design and simulated results of an earthquake excited structure validates the proposed method.

• Nuclear Engineering and Technology
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• v.41 no.2
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• pp.143-148
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• 2009

The increasing power and other demands on PWR fuel is leading to a demand for cladding that has low corrosion but that should also be robust with regard to mechanical behavior, impact of the irradiation environment and the coolant chemistry. The Optimized $ZIRLO^{TM}$ cladding is an evolutionary development of $ZIRLO^{TM}$ taking advantage of the long experience of the ZIRLO cladding but has significantly improved corrosion behavior. Recently, operation of Optimized ZIRLO to above 73 kWd/kgU has shown a reduction of the corrosion of almost 50%.

• Nuclear Engineering and Technology
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• v.41 no.8
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• pp.995-1004
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• 2009

The Advanced Power Reactor 1400 (APR1400) is an evolutionary advanced light water reactor (ALWR) based on the Optimized Power Reactor 1000 (OPR1000), which is in operation in Korea. The APR1400 incorporates a variety of engineering improvements and operational experience to enhance safety, economics, and reliability. The advanced design features and improvements of the APR1400 design include a pilot operated safety relief valve (POSRV), a four-train safety injection system with direct vessel injection (DVI), a fluidic device (FD) in the safety injection tank, an in-containment refueling water storage tank (IRWST), an external reactor vessel cooling system, and an integrated head assembly (IHA). Development of the APR1400 started in 1992 and continued for ten years. The APR1400 design received design certification from the Korean nuclear regulatory body in May of2002. Currently, two construction projects for the APR1400 are in progress in Korea.