• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.91-94
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• 2012

This paper describes an efficient implementation of ARIA crypto algorithm which is a KS (Korea Standards) block cipher algorithm. The ARIA crypto-processor supports three master key lengths of 128/192/256-bit specified in the standard. To reduce hardware complexity, a hardware sharing is employed, which shares round function in encryption/decryption module with key initialization module. It reduces about 20% of gate counts when compared with straightforward implementation. The ARIA crypto-processor is verified by FPGA implementation, and synthesized with a 0.13-${\mu}m$ CMOS cell library. It has 33,218 gates and the estimated throughput is about 640 Mbps at 100 MHz.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.2
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• pp.406-414
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• 2002

A new approach, referred to as a successive zooming genetic algorithm (SZGA), is Proposed for identifying a global solution for continuous optimization problems. In order to improve the local fine-tuning capability of GA, we introduced a new method whereby the search space is zoomed around the design point with the best fitness per 100 generation. Furthermore, the reliability of the optimized solution is determined based on the theory of probability. To demonstrate the superiority of the proposed algorithm, a simple genetic algorithm, micro genetic algorithm, and the proposed algorithm were tested as regards for the minimization of a multiminima function as well as simple functions. The results confirmed that the proposed SZGA significantly improved the ability of the algorithm to identify a precise global minimum. As an example of structural optimization, the SZGA was applied to the optimal location of support points for weight minimization in the radial gate of a dam structure. The proposed algorithm identified a more exact optimum value than the standard genetic algorithms.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.10 s.241
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• pp.1369-1376
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• 2005

In structural design, the design variables are frequently selected from certain discrete values. Various optimization algorithms have been developed fDr discrete design. It is well known that many function evaluations are needed in such optimization. Recently, sequential algorithm with orthogonal arrays (SOA), which is a search algorithm for a local minimum in a discrete space, has been developed. It considerably reduces the number of function evaluations. However, it only finds a local minimum and the final solution depends on the initial values of the design variables. A new algorithm is proposed to adopt a genetic algorithm (GA) in SOA. The GA can find a solution in a global sense. The solution from the GA is used as the initial design of SOA. A sequential usage of the GA and SOA is carried out in an iterative manner until the convergence criteria are satisfied. The performance of the algorithm is evaluated by various examples.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.285-287
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• 2014

This paper describes a design of area-efficient/low-power cryptographic processor for lightweight block cipher algorithm HIGHT which was approved as a cryptographic standard by KATS and ISO/IEC. The HIGHT algorithm which is suitable for the security of IoT(Internet of Things), encrypts a 64-bit plain text with a 128-bit cipher key to make a 64-bit cipher text, and vice versa. For area-efficient and low-power implementation, we adopt 32-bit data path and optimize round transform block and key scheduler to share hardware resources for encryption and decryption.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.4
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• pp.537-545
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• 2013

The elastic recovery of a metal seal is a factor that can be used to assess its sealing performance. In this study, a compliant mechanism topology optimization has been performed to find a structure of a metal O-ring seal that can maintain excellent sealing performance with a maximized elastic recovery over extended operation. An evolutionary structural optimization (ESO) was used as a topology optimization algorithm with two different types of objective functions considering both flexibility and stiffness. In particular, a circular design domain was adopted to consider the outer shape of the metal O-ring seal. The elastic recovery of the optimal topology was calculated and compared to that of a commercial product.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.16 no.1
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• pp.59-68
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• 2003

An optimization Program is developed to produce new topologies of plane structures under multiload case. A four-node finite element is used in the response analysis to reduce the computation time and to ultimately achieve practical topology optimization. The bilinear finite element is prone to produce chequer-boarding phenomenon and a simple filtering process is therefore adopted. An artificial material model is employed to represent the structural material and the resizing algorithm based on the optimality criteria is adopted to update the material density parameter during optimization process. With newly developed optimization program, the comparison study has been made between single and multiload cases and its results are described in this paper. From numerical results, it appears that multiload case should be considered to achieve the practical topology optimization.

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.253-260
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• 1997

Various algorithms are investigated with respect to finding the best model-based samples according to criteria such as D-optimality and minimum mean square error. These two criteria are slightly different, but related to each other. Therefore, it is not surprising that these two are producing the almost identical samples. Some simple examples follow and critiques are provided along with directions for further research.

• Proceedings of the KSME Conference
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• 2001.06c
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• pp.559-564
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• 2001

The design of an automobile mirror actuator system needs a systematic optimization due to several variables, constraints, geometric limitations, moving angle, and so on. Therefore, this article provides the procedure of a genetic algorithm(GA) based optimization with finite element analysis for design of a mirror actuator considering design constraints, geometric limitations, moving angle. Local optimum problem in optimization design with sensitivity analysis is overcome by using zero-order overall searching method which is new optimization design method using a genetic algorithm.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.6
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• pp.1008-1015
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• 2002

This paper proposes a combinatorial method to compute the global and local solutions of optimization problem. The present hybrid algorithm is the synthesis of a genetic algorithm and a local concentrate search algorithm (simplex method). The hybrid algorithm is not only faster than the standard genetic algorithm, but also gives a more accurate solution. In addition, this algorithm can find both the global and local optimum solutions. An optimization result is presented to demonstrate that the proposed approach successfully focuses on the advantages of global and local searches. Three numerical examples are also presented in this paper to compare with conventional methods.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.1
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• pp.158-166
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• 2003

The paper describes the development and application of advanced evolutionary computing techniques referred to as micro genetic algorithms ($\mu$GA) in the context of engineering design optimization. The basic concept behind $\mu$GA draws from the use of small size of population irrespective of the bit string length in the representation of design variable. Such strategies also demonstrate the faster convergence capability and more savings in computational resource requirements than simple genetic algorithms (SGA). The paper first explores ten-bar truss design problems to see the optimization performance between $\mu$GA and SGA. Subsequently, $\mu$GA is applied to a realistic engineering design problem in the injection molding process optimization.