• Proceedings of the Acoustical Society of Korea Conference
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• 한국음향학회 1994년도 제11회 음성통신 및 신호처리 워크샵 논문집 (SCAS 11권 1호)
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• pp.188-194
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• 1994

Code excited linear prediction speech coders exhibit good performance at data rates as low as 4800bps. But the major drawback to CELP type coders is their large computational requirements. Therefore, in this paper a comparative performance study of three pitch searching algorithms for the CELP vocoder was conducted. For each of the algorithms, a standard pitch searching algorithm was used by the full pitch searching algorithm that was implimented in the QCELP vocoder. The algorithms used in this study is to reduce the pitch searching time 1) using the skip table, 2) using the symmetrical property of the autocorrelation , and 3) using the preprocessing autocorrelation, 4) using the positive autocorrelation, 5) using the preliminary pitch. Performance scores are presented for each of the five pitch searching algorithms based on computation speed and on pitch prediction error.

• Journal of the Korean Mathematical Society
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• 제52권4호
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• pp.797-819
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• 2015

A trapdoor discrete logarithm group is a cryptographic primitive with many applications, and an algorithm that allows discrete logarithm problems to be solved faster using a pre-computed table increases the practicality of using this primitive. Currently, the distinguished point method and one extension to this algorithm are the only pre-computation aided discrete logarithm problem solving algorithms appearing in the related literature. This work investigates the possibility of adopting other pre-computation matrix structures that were originally designed for used with cryptanalytic time memory tradeoff algorithms to work as pre-computation aided discrete logarithm problem solving algorithms. We find that the classical Hellman matrix structure leads to an algorithm that has performance advantages over the two existing algorithms.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 대한산업공학회/한국경영과학회 1993년도 춘계공동학술대회 발표논문 및 초록집; 계명대학교, 대구; 30 Apr.-1 May 1993
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• pp.343-352
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• 1993

In this study, a modified algorithm for the exchange heuristic is developed and applied to a resource-constrained scheduling problem. The problem involves multiple projects and multiple resource categories and allows flexible resource allocation to each activity. The objective is to minimize the maximum completion time. The exchange heuristkc is a multiple pass algorithm which makes improvements upon a given initial feasible schedule. Four different modified algorithms are proposed. The original algorithm and the new algorithms were compared through an experimental investigation. All the proposed algorithms reduce the maximum completion time much more effectively than the original algorithm. Especially, one of four proposed algorithms obviously outperforms the other three algorithms. The algorithm of the best performance produces significantly shorter schedules than the original algorithm, though it requires up to three times more computation time. However, in most situations, a reduction in schedule length means a significant reduction in the total cost.

• Journal of Ocean Engineering and Technology
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• 제17권6호
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• pp.53-57
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• 2003

Optimum design of most structural system requires that design variables are regarded as discrete quantities. This paper presents the use of Genetic Algorithm for determining the optimum design for truss with discrete variables. Genetic Algorithm are know as heuristic search algorithms, and are effective global search methods for discrete optimization. In this paper, Elitism and the method of conferring penalty parameters in the design variables, in order to achieve improved fitness in the reproduction process, is used in the Genetic Algorithm. A 10-Bar plane truss and a 25-Bar space truss are used for discrete optimization. These structures are designed for stress and displacement constraints, but buckling is not considered. In particular, we obtain continuous solution using Genetic Algorithms for a 10-bar truss, compared with other results. The effectiveness of Genetic Algorithms for global optimization is demonstrated through two truss examples.

• The Transactions of the Korea Information Processing Society
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• 제7권7호
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• pp.2060-2071
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• 2000

Scheduling parallel tasks, represented as a Directed Acyclic Graph (DAG) or task graph, on a multiprocessor system has been an important research area in the past decades. List scheduling algorithms assign priorities to a node or an edge in an input DAG, and then generate a schedule according to the assigned priorities. This appear proposes a list scheduling algorithms with effective method of priority assignments. The paper also analyzes the worst case performance and optimality condition for the proposed algorithm. The performance comparison study shows that the proposed algorithms outperforms existing scheduling algorithms especially for input DAGs with high communication overheads. The performance improvement over existing algorithms becomes larger as the input DAG becomes more dense and the level of parallelism in the DAG is increased.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 한국소음진동공학회 1998년도 춘계학술대회논문집; 용평리조트 타워콘도, 21-22 May 1998
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• pp.670-677
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• 1998

Many of the adaptive noise control systems utilize a form of the least mean square (LMS) algorithm. In the active control of noise, it is common practice to locate an error microphone far from the control source to avoid the near-field effects by evanescent waves. Such a distance between the control source and the error microphone makes a certain level of time-delay inevitable and, hence, may yield undesirable effects on the convergence properties of control algorithms such as filtered-x LMS. This paper discusses the dependence of the convergence rate on the acoustic error path in these popular algorithms and introduces new algorithms which increase the convergence region regardless of the time-delay in the acoustic error path. Performances of the new LMS algorithms are presented in comparison with those by the conventional algorithms based on computer stimulations and experiments.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 대한산업공학회/한국경영과학회 2000년도 춘계공동학술대회 논문집
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• pp.239-242
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• 2000

Symbiotic evolutionary algorithms are stochastic search algorithms that imitate the biological coevolution process through symbiotic interactions. In the algorithms, the fitness evaluation of an individual requires first selecting symbiotic partners of the individual. The symbiotic partner effects the change of individual's fitness and search direction. In this study we are to analyze how much partnering strategies can influence the performance of the algorithms. For this goal extensive experiments are carried out to compare the performance of partnering strategies. The NKC model and the binary string covering problem are used as the test-bed problems. The experimental results indicate that there does not exist statistically significant difference in their performance.

• Journal of the Korean Operations Research and Management Science Society
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• 제34권3호
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• pp.125-136
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• 2009

The container packing problem Is one of the traditional optimization problems, which is very related to the knapsack problem and the bin packing problem. In this paper, we deal with the quadratic multiple container picking problem (QMCPP) and it Is known as a NP-hard problem. Thus, It seems to be natural to use a heuristic approach such as evolutionary algorithms for solving the QMCPP. Until now, only a few researchers have studied on this problem and some evolutionary algorithms have been proposed. This paper introduces a new efficient evolutionary algorithm for the QMCPP. The proposed algorithm is devised by improving the original network random key method, which is employed as an encoding method in evolutionary algorithms. And we also propose local search algorithms and incorporate them with the proposed evolutionary algorithm. Finally we compare the proposed algorithm with the previous algorithms and show the proposed algorithm finds the new best results in most of the benchmark instances.

• Journal of the Korean Society for Aviation and Aeronautics
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• 제19권4호
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• pp.83-90
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• 2011

The evaluation of Conflict detection and Resolution Algorithms require the use of analytical that describe encounter flight safety and the costs and benefits of optimization maneuver. A number of such algorithms have been applied in the past to the free flight. Each algorithm has benefits and limitations, and flight safety may be facilitated by combining the best features of various techniques. This paper studied a summary of conflict detection and resolution algorithm approaches. Algorithm techniques are categorized and the fundamental assumptions, capabilities, and limitations of each approach are described. The Algorithms are evaluated and compared based on their applicability to free flight airspace conflict situations.

• Korean Management Science Review
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• 제12권2호
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• pp.105-127
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• 1995

This paper solves different machine-part group formation (MPGF) problems using genetic algorithms to demonstrate that it can be a new robust alternative to the conventional heuristic approaches for optimization problems. We first give an overview of genetic algorithms: Its principle, various considerations required for its implementation, and the method for setting up parameter values are explained. Then, we describe the MPGF problem which are critical to the successful operation of cellular manufacturing or flexible manufacturing systems. We concentrate on three models of the MPGF problems whose forms of the objective function and/or constraints are quite different from each other. Finally, numerical examples of each of the models descibed above are solved by using genetic algorithms. The result shows that the solutions derived by genetic algorithms are comparable to those obtained through problem-specific heuristic methods.