• Economic and Environmental Geology
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• v.27 no.5
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• pp.459-467
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• 1994

The Gadaeri granite near Ulsan mine is an oval-shape isolated granitic body, and is genetically related to the iron-tungsten mineralization. The Gadaeri granite exhibits calc-alkaline and I-type characteristics, and generally shows the micrographic texture which indicates the shallow depth of emplacement. Consideration of the stratigraphic thickness of Ulsan formation and minimum-melt compositions suggests that the bulk magma crystallized at pressure of 0.5~2.0 kbar under water saturated condition. The evolutionary trend observed in the studied rocks represents that feldspar fractional crystallization has been a major magmatic process at the Gadaeri granite pluton. Different chemical characteristics between the Gadaeri and the Masan-Kimhae granites cannot be explained by fractional crystallization or different degrees of partial melting, and it reflects that the magma source for Gadaeri granite was different from that of the Masan and Kimhae granites.

• Parasites, Hosts and Diseases
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• v.37 no.4
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• pp.215-228
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• 1999

To choose one or more appropriate molecular markers or gene regions for resolving a particular systematic question among the organisms at a certain categorical level is still a very difficult process. The primary goal of this review, therefore, is to provide a theoretical information in choosing one or more molecular markers or gene regions by illustrating general properties and phylogenetic utilities of nuclear ribosomal DNA (rDNA) and mitochondrial DNA (mtDNA) that have been most commonly used for phylogenetic researches. The highly conserved molecular markers and/or gene regions are useful for investigating phylogenetic relationships at higher categorical levels (deep branches of evolutionary history). On the other hand, the hypervariable molecular markers and/or gene regions are useful for elucidating phylogenetic relationships at lower categorical levels (recently diverged branches). In summary, different selective forces have led to the evolution of various molecular markers or gene regions with varying degrees of sequence conservation. Thus, appropriate molecular markers or gene regions should be chosen with even greater caution to deduce true phylogenetic relationships over a broad taxonomic spectrum.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.43 no.3
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• pp.1-10
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• 2011

Proportional.Integral.Derivative control schemes continue to provide the simplest and effective solutions to most of the control engineering applications today. However PID controller is poorly tuned in practice with most of the tuning done manually which is difficult and time consuming. This research comes up with a soft computing approach involving Genetic Algorithm, Evolutionary Programming, and Particle Swarm Optimization and Ant colony optimization. The proposed algorithm is used to tune the PID parameters and its performance has been compared with the conventional methods like Ziegler Nichols and Lambda method. The results obtained reflect that use of heuristic algorithm based controller improves the performance of process in terms of time domain specifications, set point tracking, and regulatory changes and also provides an optimum stability. This research addresses comparison of tuning of the PID controller using soft computing techniques on Machine Direction of basics weight control in pulp and paper industry. Compared to other conventional PID tuning methods, the result shows that better performance can be achieved with the soft computing based tuning method. The ability of the designed controller, in terms of tracking set point, is also compared and simulation results are shown.

• Journal of Korea Game Society
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• v.11 no.2
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• pp.19-28
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• 2011

Level design is one of the important factors in tower defense game development. The difficulty of tower defense game depends on its wave design. In general, it requires a lot of manual labor to generate well-balanced waves with fun. In this paper, we propose a new automated wave generation system by using a genetic algorithm. With our system, a game designer can easily generate an optimized wave by designating the difficulty level in the initial stage of game design. Our system can be useful in reducing the trial-errors in the initial level design process of tower defense game development.

• The KSFM Journal of Fluid Machinery
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• v.16 no.6
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• pp.32-39
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• 2013

In the present study, three-dimensional aerodynamic optimization of high pressure turbine nozzle for turbofan engine was performed. For this, Kriging surrogate model was built and refined iteratively by supplying additional experimental points until the surrogate model and CFX result has effective difference on objective function. When the surrogate model satisfied this reliability condition and developed enough, optimum point was investigated. Commercial program PIAnO was used for optimization process and evolutionary algorithm was used for searching optimum point. As a result, difference between estimated value from Kriging surrogate model and CFD result converges within 0.01% and the optimized nozzle shape has 0.83% improved aerodynamic efficiency.

• 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.

• Journal of the Korea Computer Graphics Society
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• v.15 no.4
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• pp.13-21
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• 2009

Game level design is one of the important parts in the commercial game development. Because of its complexity in combining game components, game design work could be classified into a non-linear problem. In this paper, we propose a new automated game level design system by using genetic algorithms. With our system, a game designer easily generates an optimized game level by designating the key parameters m the initial stage of game design. Our system can be useful in reducing the trial-errors in the initial game level design process.

• International Journal of Fluid Machinery and Systems
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• v.3 no.4
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• pp.352-359
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• 2010

In recent years, the market has shown increasing interest in pump-turbines. The prompt availability of pumped storage plants and the benefits to the power system achieved by peak lopping, providing reserve capacity, and rapid response in frequency control are providing a growing advantage. In this context, there is a need to develop pumpturbines that can reliably withstand dynamic operation modes, fast changes of discharge rate by adjusting the variable diffuser vanes, as well as fast changes from pumping to turbine operation. In the first part of the present study, various flow patterns linked to operation of a pump-turbine system are discussed. In this context, pump and turbine modes are presented separately and different load cases are shown in each operating mode. In order to create modern, competitive pump-turbine designs, this study further explains what design challenges should be considered in defining the geometry of a pump-turbine impeller. The second part of the paper describes an innovative, staggered approach to impeller development, applied to a low head pump-turbine project. The first level of the process consists of optimization strategies based on evolutionary algorithms together with 3D in-viscid flow analysis. In the next stage, the hydraulic behavior of both pump mode and turbine mode is evaluated by solving the full 3D Navier-Stokes equations in combination with a robust turbulence model. Finally, the progress in hydraulic design is demonstrated by model test results that show a significant improvement in hydraulic performance compared to an existing reference design.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1864-1873
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• 2018

Energy shifting is an innovative method used to obtain the highest profit from the operation of energy storage systems (ESS) by controlling the charge and discharge schedules according to the electricity prices in a given period. Therefore, in this study, we propose an optimal charge and discharge scheduling method that performs energy shift operations derived from an ESS efficiency model. The efficiency model reflects the construction of power conversion systems (PCSs) and lithium battery systems (LBSs) according to the rated discharge time of a MWh-scale ESS. The PCS model was based on measurement data from a real system, whereas for the LBS, we used a circuit model that is appropriate for the MWh scale. In addition, this paper presents the application of a genetic algorithm to obtain the optimal charge and discharge schedules. This development represents a novel evolutionary computation method and aims to find an optimal solution that does not modify the total energy volume for the scheduling process. This optimal charge and discharge scheduling method was verified by various case studies, while the model was used to realize a higher profit than that realized using other scheduling methods.

• Industrial Engineering and Management Systems
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• v.7 no.1
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• pp.51-56
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• 2008

With growing demand for zero defects, predicting reliability of software systems is gaining importance. Software reliability models are used to estimate the reliability or the number of latent defects in a software product. Most reliability models to estimate the reliability of software in the literature are based on the development lifecycle stages. However, in the maintenance phase, the software needs to be corrected for errors and to be enhanced for the requests from users. These decrease the reliability of software. Software Reliability Growth Models (SRGMs) have been applied successfully to model software reliability in development phase. The software reliability in maintenance phase exhibits many types of systematic or irregular behaviors. These may include cyclic behavior as well as long-term evolutionary trends. The cyclic behavior may involve multiple periodicities and may be asymmetric in nature. In this paper, SGRM has been adapted to develop a reliability prediction model for the software in maintenance phase. The model is established using maintenance data from a commercial shop floor control system. The model is accepted to be used for resource planning and assuring the quality of the maintenance work to the user.