• Journal of KIISE
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• v.44 no.8
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• pp.760-766
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• 2017

Repetitive strings have been studied in diverse fields such as data compression, bioinformatics and so on. Recently, two problems of approximate periods of strings over integer alphabets were introduced, finding minimum ${\delta}-approximate$ periods and finding minimum ${\gamma}-approximate$ periods. Both problems can be solved in $O(n^2)$ time when n is the length of the string. In this paper, we present two parallel algorithms for solving the above two problems in O(n) time using $O(n^2)$ threads, respectively. The experimental results show that our parallel algorithms for finding minimum ${\delta}-approximate$ (resp. ${\gamma}-approximate$) periods run approximately 19.7 (resp. 40.08) times faster than the sequential algorithms when n = 10,000.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1211-1219
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• 2013

Recently, the usage of skew-normal distribution, instead of classical normal distribution, is rising up in many statistical theories and applications. In this paper, we deal with saddlepoint approximation for the distribution function of sample mean of skew-normal distribution. Comparing to normal approximation, saddlepoint approximation provides very accurate results in small sample sizes as well as for large or moderate sample sizes. Saddlepoint approximations related to the skew-normal distribution, suggested in this paper, can be used as a approximate approach to the classical method of Gupta and Chen (2001) and Chen et al. (2004) which need very complicate calculations. Through simulation study, we verified the accuracy of the suggested approximation and applied the approximation to Robert's (1966) twin data.

• The Korean Journal of Applied Statistics
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• v.29 no.1
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• pp.181-192
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• 2016

We consider several methods to approximate option prices with correction terms to the Black-Scholes option price. These methods are able to compute option prices from various risk-neutral distributions using relatively small data and simple computation. In this paper, we compare the performance of Edgeworth expansion, A-type and C-type Gram-Charlier expansions, a method of using Normal inverse gaussian distribution, and an asymptotic method of using nonlinear regression through simulation experiments and real KOSPI200 option data. We assume the variance gamma model in the simulation experiment, which has a closed-form solution for the option price among the pure jump $L{\acute{e}}vy$ processes. As a result, we found that methods to approximate an option price directly from the approximate price formula are better than methods to approximate option prices through the approximate risk-neutral density function. The method to approximate option prices by nonlinear regression showed relatively better performance among those compared.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.11
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• pp.1603-1611
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• 2010

The comparative study of regression-model-based approximate optimization techniques used in the strength design of an automotive knuckle component that will be under bump and brake loading conditions is carried out. The design problem is formulated such that the cross-sectional sizing variables are determined by minimizing the weight of the knuckle component that is subjected to stresses, deformations, and vibration frequency constraints. The techniques used in the comparative study are sequential approximate optimization (SAO), sequential two-point diagonal quadratic approximate optimization (STDQAO), and approximate optimization based on enhanced moving least squares method (MLSM), such as CF (constraint feasible)-MLSM and Post-MLSM. Commercial process integration and design optimization (PIDO) tools are utilized for the application of SAO and STDQAO. The enhanced MLSM-based approximate optimization techniques are newly developed to ensure constraint feasibility. The results of the approximate optimization techniques are compared with those of actual non-approximate optimization to evaluate their numerical performances.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.7_8
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• pp.387-396
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• 2003

This paper provides an approximation algorithm for STP-MSP(Steiner Tree Problem with minimum number of Steiner Points).Because it seems to be impossible to have a PTAS(Polynomial Time Approximation Schemes), which gives the near optimal solutions, for the problem, the algorithm of this paper is an alternative that has the approximation ratio 2 with $n^{O(1)}$ run time. The importance of this paper is the potential to solve other related unsolved problems. The idea of this paper is to distribute the error allowance over the problem instance so that we may reduce the run time to polynomial bound out of infinitely many cases. There are earlier works[1,2] that show the approximations that have practical run times with the ratio of bigger than 2, but this paper shows the existence of a poly time approximation algorithm with the ratio 2.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.10A
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• pp.1566-1575
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• 2000

This paper studies mismatched scalar quantization of a generalized gamma source by a quantizer that is optimally (in the mean square error sense) designed for another generalized gamma source. Specifically, it considers variance-mismatched quantization which occurs when the variance of the source to be quantized differs from tat of the designed-for source. The main result is the two distortion formulas derived from Bennett's integral. The first formula is an approximation expression that uses the outermost threshold of an optimum scalar quantizer, and the second formula, in turn, uses an approximation formula for this outermost threshold. Numerical results are obtained for Laplacian sources, which are example of a generalized gamma source, and comparisons are made between actual mismatched distortions and the two formulas. These numerical results show that the two formulas become more accurate, as the number of quantization points gets larger and the ratio of the source variance to that of the designed-for source gets bigger. For example, the formulas are within 2~4% of the actual distortion for approximately 64 quantization points or more. In conclusion, the proposed approximation formulas are considered to have contribution as closed formulas and for their accuracy.

• Solar Energy
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• v.15 no.2
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• pp.25-37
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• 1995

This paper presents an approximate analytical solution to one-dimensional model of the charging process for stratified thermal storage tanks, in which variation of the inlet temperature as well as the momemtum-induced mixing is taken into accout. The mixing is incorporated into the model as a constant-depth perfectly mixed layer above the plug flow region. Based on the superposition principle, the variable inlet temperature is approximated by a number of step functions. Temperature distributions for the thermocline corresponding to three types of interfacial condition arr successfully derived in terms of well-defined functions, so that a linear combination of them constitutes the final solution. Validity and utility of this work is examined through the comparison of the approximate solution with an exact solution available for the case of linearly increasing inlet temperature. With increasing the number of steps, the present solution asymptotically approaches to the exact one. Even with a limited number of steps, the present results favorably agree with those by the exact solution for a wide range of the mixing depth. Also, it is revealed that fewer steps are needed for meaningful predictions as the mixing. depth becomes larger.

• Korean Chemical Engineering Research
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• v.50 no.5
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• pp.830-836
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• 2012

Dead times appear often in describing process dynamics and raise some difficulties in simulating process dynamics or analyzing process control systems. To relieve these difficulties, it is needed to approximate the infinite dimensional dead time by the finite dimensional transfer function and, for this, the Pade approximation method is often used. For the accurate approximation of the dead time, high order Pade approximation is needed and the high order Pade approximation is not easy to memorize and is not stable numerically. We propose a method based on the continued fraction expansion that provides the same transfer functions. The method is excellent numerically as well as systematic to be memorized easily. It can be used conveniently for the process control lecture and computations.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2009.04a
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• pp.97-100
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• 2009

신뢰성 분석은 불확실성으로 인한 제품의 성능 변동을 안전확률이나 파괴확률로 정량화 하여 설계에 이용하기 위해 연구되어 왔다. 불확실성은, 데이터의 양에 따라-물질의 본질적인 특성으로서의 많은 데이터가 주어진 경우의 물리적 불확실성과 부족한 데이터에서의 인식론적 불확실성으로 구분되고, 불확실성을 갖는 대상에 따라-입력변수 및 근사모델 불확실성으로 구분된다. 물리적 불확실성에 대한 연구는 많이 진행되어 왔지만, 실제 산업현장에는 부족한 데이터로 인한 인식론적 불확실성이 지배적이며 이에 대한 연구는 최근에서야 진행되고 있다. 불확실성을 고려하는 신뢰성 기반 설계에는 효율성을 위해 실제모델을 대체하는 근사모델이 이용되는데, 근사모델법 자체에 대한 연구는 많이 진행되어 왔으나, 근사모델 이기 때문에 존재하는 불확실성을 고려한 연구는 최근에서야 연구되기 시작하였다. 본 연구에서는 베이지안 접근법에 기반하여 입력변수 및 근사모델 불확실성을 통합 고려하는 새로운 신뢰성 분석 기법을 제시하고 수치예제를 통해 타당성을 증명한 후, 이를 공학문제에 적용한다.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.18 no.4
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• pp.360-371
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• 2006

In order to calculate waves propagating into the shallow water region, a generalized parabolic approximate model is presented. The model is derived from the modified mild slope equation and includes all the existing parabolic models presented in the paper. Numerical results are presented in comparison to laboratory data of Berkhoff et al.(1982). The existing parabolic model shows almost same accuracy against the modified parabolic model and both results of models stand in closer agreement to the laboratory data. Therefore the existing parabolic model based on mild slope equation is a useful tool to compute shallow water waves which turns out to be more fast and stable in computational aspect.