• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.371-378
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• 1999

This paper presents an efficient algorithm for loss reduction of distribution system by automatic sectionalizing switch operation in large scale distribution systems of radial type. Simulated Annealing algorithm among optimization techniques can avoid escape from local minima by accepting improvements in cost, but the use of this algorithm is also responsible for an excessive computation time requirement. To overcome this major limitation of Simulated Annealing algorithm, we may use advanced Simulated Annealing algorithm. All constaints are divided into two constraint group by using perturbation mechanism and penalty factor, so all trail solutions are feasible. The polynomial-time cooling schedule is used which is based on the statistics calculation during the search. This approaches results in saving CPU time. Numerical examples demonstrate the validity and effectiveness of the proposed methodology.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.787-790
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• 1998

In this paper we consider strongly polynomial variations of the auction algorithm for the single origin/all destinations shortest path problem. These variations are based on the idea of graph reduction, that is, deleting unnecessary arcs of the graph by using certain bounds naturally obtained in the course of the algorithm. We study the structure of the reduced graph and we exploit this structure to obtain algorithm with O(n min{m, nlogn}) and O(n$^{2}$) running time.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.161-168
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• 2014

The optimal solution of minimum cost for aircraft landing problem(ALP) is very difficult problem because the approached aircraft are random time interval. Therefore this problem has been applied by various meta heuristic methods. This paper suggests O(nlog n) polynomial time heuristic algorithm to obtain the optimal solution for ALP. This algorithm sorts the target time of aircraft into ascending order. Then we apply the optimization of change the landing sequence take account of separation time and the cost of landing. For the Airland1 through Airland8 of benchmark data of ALP, we choose 25 data until the number of runway m that the total landing cost is 0. We can be obtain the optimal solution for all of the 25 data. Especially we can be improve the known optimal solution for m = 1of Airland8.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.11
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• pp.22-33
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• 1999

This paper presents the method for the automatic tuning of a design weighting polynomial parameters of a generalized minimum-variance stochastic ultivariable self-tuning controller which adapts to changes in the higher order nonminimum phase system parameters with time delays and noises. The self-tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing the design weighting polynomial parameters of the controller. The proposed multivariable self-tuning method is simple and effective compared with pole restriction method. The computer simulation results are presented to adapt the higher order multivariable system with nonminimum phase and with changeable system parameters.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.3
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• pp.87-95
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• 1998

This paper presents the method for the automatic tuning of a design weighting polynomial parameter of a generalized minimum-variance stochastic self tuning controller which adapts to changes in the system parameters with time delays and noises. The self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a design weighting polynomial parameters. The proposed self tuning method is simple and effective compared with other existing self tuning methods. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.

• Journal of the Korea Society of Computer and Information
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• v.20 no.2
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• pp.1-10
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• 2015

In this paper, we propose a new multiplication algorithm for primitive polynomial with all 1 of coefficient in case that m is odd and even on finite fields $GF(3^m)$, and design the multiplier with parallel input-output module structure using the presented multiplication algorithm. The proposed multiplier is designed $(m+1)^2$ same basic cells. Since the basic cells have no a latch circuit, the multiplicative circuit is very simple and is short the delay time $T_A+T_X$ per cell unit. The proposed multiplier is easy to extend the circuit with large m having regularity and modularity by cell array, and is suitable to the implementation of VLSI circuit.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.157-162
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• 2023

To NP-complete 3-SAT problem, this paper proposes a O(nm) polynomial time algorithm, where n is the number of literals and m is the total frequency of all literals in equation f. The algorithm firstly decides a truth value of a literal in sequence of previously-set priority. The priority order is as follows: a literal whose occurrence in a clause is 1(k=1), a literal which is k≥2 and whose truth value is either 0 or 1, and a literal with the minimum frequency. Then, literals whose truth value is determined are then deleted from clause T and the remaining clauses. This process is repeated l times, the number of literals. As a result, the proposed algorithm has been successful in accurately determining the satisfiability of a given equation f and in deciding the truth value of all the literals. This paper, therefore, provides not only a linear-time algorithm as a viable solution to the SAT problem, but also a basis for solving the P versus NP problem.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.7
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• pp.671-678
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• 2006

This article proposes a smooth path generation and time scheduling method for general tasks defined by non-smooth path segments in industrial robotic applications. This method utilizes a simple 3rd order polynomial function for smooth interpolation between non-smooth path segments, so that entire task can effectively maintain constant line speed of operation. A predictor-corrector type numerical mapping technique, which correlates time based speed profile to the smoothed path in Cartesian space, is also provided. Finally simulation results show the feasibility of the proposed algorithm.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 2003.12a
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• pp.299-306
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• 2003

본 논문에서는 현재 사용되고 있는 소수성 검정 알고리즘의 효율성을 비교하여 효과적인 알고리즘 사용에 관한 방향을 제시하려 한다. 현재 가장 일반적으로 사용하고 있는 Miller-Rabin 소수성검정법(Miller-Rabin primality test)에 대하여, Miller-Rabin 소수성 검정법 이외에 다른 확률적 소수성 검정법으로 제안된 Frobenius-Grantham 소수성 검정법(Frobenius-Grantham primality test) 이 있다. 그러나 합성수 판별에 대한 확률적 우세함에도 불구하고, Miller-Rabin 소수성 검정법을 대체하고 있지 못하는 이유는 시간복잡도(time complexity)가 Randomized polynomial time이기 때문에 같은 확률에 대한 평균 실행 속도가 Miller-Rabin 소수성 검정법보다 크게 효율적이지 못하기 때문이다. 또한, 2002년 Manindra Agrawal이 제시한 AKS 알고리즘(AKS algorithm)은 최초의 다항식 시간내 결정적 소수성 검정법(Polynomial time deterministic primality test)이지만, 시간 복잡도에서 다항식의 차수가 높기 때문에 현재 사용되고 있는 확률적 소수성 검정법(Probabilistic primality test)을 대체하지 못할 것으로 사료된다. 본 논문에서는 최근 발표된 소수성 검정법인 Frobenius-Grantham 소수성 검정법, AKS 알고리즘과 기존의 Miller-Rabin 소수성 검정법의 장단점을 비교·분석해 보고자 한다.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.2
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• pp.54-60
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• 2018

This paper contains the multi-mission scheduling optimization of UAV within a given operating time. Mission scheduling optimization problem is one of combinatorial optimization, and it has been shown to be NP-hard(non-deterministic polynomial-time hardness). In this problem, as the size of the problem increases, the computation time increases dramatically. So, we applied the genetic algorithm to this problem. For the application, we set the mission scenario, objective function, and constraints, and then, performed simulation with MATLAB. After 1000 case simulation, we evaluate the optimality and computing time in comparison with global optimum from MILP(Mixed Integer Linear Programming).