• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.58-68
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• 2010

Particle Swarm Optimization (PSO) which has been well known to solve continuous problems can be applied to discrete combinatorial problems. Several DPSO (Discrete Particle Swarm Optimization) algorithms have been proposed to solve discrete problems such as traveling salesman, vehicle routing, and flow shop scheduling problems. They are different in representation of position and velocity vectors, operation mechanisms for updating vectors. In this paper, the performance of 5 DPSOs is analyzed by applying to traditional Traveling Salesman Problems. The experiment shows that DPSOs are comparable or superior to a genetic algorithm (GA). Also, hybrid PSO combined with local optimization (i.e., 2-OPT) provides much improved solutions. Since DPSO requires more computation time compared with GA, however, the performance of hybrid DPSO is not better than hybrid GA.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.3
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• pp.155-166
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• 2010

I review research on self-sensing and structural optimizations of laminated carbon/epoxy composites in Japan. Self-sensing is one of the multiple functions of composites; i.e., carbon fiber is used as a sensor as well as reinforcement. I present a controversial issue in self-sensing and detail research results. Structural optimization of laminated CFRP composites is indispensable in reducing the weights of modern aerospace structural components. I present a modified efficient global search method using the multi-objective genetic algorithm and fractal branch and bound method. My group has focused its research on these subjects and our research results are presented here.

• Journal of Electrical Engineering and Technology
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• v.6 no.2
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• pp.202-207
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• 2011

Numerous methodologies have been developed in an effort to reduce cogging torque. However, most of these methodologies have side effects that limit their applications. One approach is the optimization methodology that determines an optimized design variable within confined conditions. The response surface methodology (RSM) and the genetic algorithm (GA) are powerful instruments for such optimizations and are matters of common interest. However, they have some weaknesses. Generally, the RSM cannot accurately describe an object function, whereas the GA is time consuming. The current paper describes a novel GA and RSM hybrid algorithm that overcomes these limitations. The validity of the proposed algorithm was verified by three test functions. Its application was performed on a surface-mounted permanent magnet.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06c
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• pp.505-509
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• 2007

Static Single Assignment (SSA) form is an intermediate representation which encodes information about data and control flow that is use used to facilitate program analysis and optimization. SSA form simplifies this process with its size linear to program size. Thus we use SSA form to efficiently facilitate bytecode level analysis and optimizations in our CTOC program processor project. In this paper, we illustrate the application and implement implementation of SSA form using an example. We give the conclusion after experimental results.

• 한국전산유체공학회:학술대회논문집
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• 2005.10a
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• pp.99-104
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• 2005

For the efficient reliability analysis, Bi-direction two-point approximation(BTPA) method is developed which solves shortcomings of conventional two-point approximation(TPA) methods that generate an approximate surface with low accuracy or sometimes do an unstable approximate surface. The conventional reliability based design optimization(RBDO) methods require high computational cost compared with the deterministic design optimization(DO) methods. To overcome the computational inefficiency of RBDO, the approximate reliability analysis approaches on the TPA surface are proposed. Using these FORM and SORM analysis strategies, multi-point aerodynamic-structure interacted shape design optimizations with uncertainty are performed very efficiently.

• Journal of computational fluids engineering
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• v.17 no.2
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• pp.28-34
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• 2012

In this study, the reliability-based design optimization of the airfoil was performed. PARSEC function was used to consider the uncertainty of the aerodynamic shape for the reliability-based shape optimization of airfoils. Among various reliability analysis methods, the moment method was used to compute the probability of failure of the aerodynamic performance. The accuracy of the reliability analysis was compared with other methods and it was found that the moment method predicts the probability of failure accurately. Deterministic and reliability-based optimizations were performed for the shape of the airfoil and it was demonstrated that reliability-based optimum assures the aerodynamic performances under uncertainties of the shape of the airfoil.

• Journal of Mechanical Science and Technology
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• v.14 no.11
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• pp.1206-1215
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• 2000

This paper introduces the application of evolutionary fuzzy modeling (EFM) in constructing global function approximations to subsequent use in non-gradient based optimizations strategies. The fuzzy logic is employed for express the relationship between input training pattern in form of linguistic fuzzy rules. EFM is used to determine the optimal values of membership function parameters by adapting fuzzy rules available. In the study, genetic algorithms (GA's) treat a set of membership function parameters as design variables and evolve them until the mean square error between defuzzified outputs and actual target values are minimized. We also discuss the enhanced accuracy of function approximations, comparing with traditional response surface methods by using polynomial interpolation and back propagation neural networks in its ability to handle the typical benchmark problems.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.8
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• pp.1236-1241
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• 2017

We deposited Al-doped ZnO (ZnO:Al) thin films on glass substrates ($200mm{\times}200mm$) by using in-line magnetron sputtering system. Effects of various deposition parameters such as working pressure, deposition power and substrate temperature on optoelectronic characteristics including surface-texture etching profiles were carefully investigated in this study. We found that relatively low working pressure and high deposition power offered to obtain enhanced conductivity and optical transmittance. Haze properties showed similar trend with the transmittance. Furthermore, surface-texture etching study exhibited good morphologies when the films were deposited at $200-300^{\circ}C$. On the basis of these optimizations, we could find the deposition region that produces highly transparent and conductive properties including efficient light scattering capability.

• Journal of Microbiology and Biotechnology
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• v.20 no.1
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• pp.39-44
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• 2010

Acidithiobacillus caldus is an acidophilic, chemolithotrophic bacterium that plays an important role in bioleaching. Gene transformation into A. caldus is difficult, and only the conjugation method was reported successful, which was a relatively sophisticated method. In this research, electrotransformation of A. caldus species was achieved for the first time using A. caldus Y-3 and plasmid pJRD215. Transformants were confirmed by colony PCR specific to the str gene on pJRD215, and the recovery of the plasmid from the presumptive transformants. Optimizations were made and the transformation efficiency was increased from 0.8 to $3.6{\times}10^4$ transformants/${\mu}g$ plasmid DNA. The developed electrotransformation method was convenient in introducing foreign genes into A. caldus.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.11a
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• pp.10-11
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• 2014

In a 2-dimensional (2D) Discrete Cosine Transform (DCT) hardware, a significant fraction of the total hardware area is contributed by the combinational logic used to perform 1-dimensional (2D) transform. The size of the non-combinational logic i.e. the transpose memory is dictated by the size of the largest transform supported. Hence, the optimization of hardware area is performed mainly for 1D-transform combinational logic. This paper demonstrates the use of Multiple Constant Multiplication (MCM) algorithm to reduce the combinational logic area. Partial optimizations are also described for the cases where the direct use of MCM algorithm doesn't meet the timing constraint. Experimental results show that 46% improvement in gate count is achieved for 32 point 1D DCT transform logic after using MCM optimization.