• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.1931-1938
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• 2012

A by-pass path in wireless sensor networks is the alternative path which be able to forward data when a routing path is being broken. One reason of depleting energy is occurred by the path. The method for solving prior to addressed the problem is proposed. However, this method may deplete radio resource. The best path has advantage that network lifetime of sensor nodes is prolonged; on the contrary, in order to maintain the best path it have to share their information between the entire nodes. In this paper, we propose the best path searching algorithm in the distributed three dimensional sensor networks. Through the neighboring informations sharing in the proposed method, the proposed algorithm can decide the best k-path as well as the extension of network lifetime.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.587-595
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• 2015

A by-pass path in wireless sensor networks is the alternative path which be able to forward data when a routing path is being broken. One reason of depleting energy is occurred by the path. The method for solving prior to addressed the problem is proposed. However, this method may deplete radio resource. The best path has advantage that network lifetime of sensor nodes is prolonged; on the contrary, in order to maintain the best path it have to share their information between the entire nodes. In this paper, we propose the best path searching algorithm in the distributed three dimensional sensor networks. Through the neighboring informations sharing in the proposed method, the proposed algorithm can decide the best k-path as well as the extension of network lifetime.

• Journal of Digital Contents Society
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• v.8 no.3
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• pp.279-288
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• 2007

Recently, Baruah et. al. proposed an optimal Pfair scheduling algorithm in the real-time multiprocessor system environments, and several variants of it were presented. All these algorithms assume the fixed unit quantum size. However, under Pfair based scheduling algorithms that are global scheduling technique, quantum size has direct influence on the scheduling overheads such as task switching and cache reload. We proposed a method for deciding the optimal quantum size[2] and an improved method for the task set whose utilization e is less than or equal to $e\;{\leq}\;p/3+1$[3]. However, these methods use repetitive computation of the task's utilization to determine the optimal quantum size. In this paper, we propose a more efficient method that can determine the optimal quantum size in constant time.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.73-80
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• 2003

The Java programming language is designed for developing effective applications in a heterogeneous network environment. Major problem in Java is its performance. many attractive features of Java make the development of software easy, but also make it expensive to support ; applications written in Java are often much slower than their counterparts written in C or C++. To use Java`s attractive features without the performance penalty, sophisticated optimizations and runtime systems are required. Optimising Java bytecode has several advantages. First, the bytecode is independent of any compiler that is used to generate it. Second, the bytecode optimization can be performed as a pre=pass to Just-In-Time(JIT) compilation. Many attractive features of Java make the development of software easy, but also make it expensive to support. The goal of this work is to develop automatic construction of code optimizer for Java bytecode. We`ve designed and implemented a Bytecode Optimizer that performs the peephole optimization, bytecode-specific optimization, and method-inlining techniques. Using the Classfile optimizer, we see up to 9% improvement in speed and about 20% size reduction in Java class files, when compared to average code using the interpreter alone.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.112-112
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• 2011

오늘날 우리 사회의 생활과 문화의 질이 향상됨에 따라 공공 및 개인의 안전과 건강에 대한 관심이 증대되고 있다. 특히, 재난과 비상사태는 생명에 대한 희생뿐만 아니라 훨씬 더 심각한 경제적인 결과를 초래한다. 이러한 응급사태에 개비하여 적절히 준비되지 않았거나 재난의 예방 및 완화시킬 방법을 가지고 있지 못한다면 도시의 발전적인 프로젝트는 예고 없이 도시를 강타하는 재난 및 비상사태에 의해 무산되고 만다. 이러한 여건 하에 재난과 응급사고를 효율적으로 대처하는 응급처치와 서비스에 대한 급격한 관심과 함께 일정한 결정적 대응시간 내에 각종사고와 재해로부터 방어할 수 있는 공공서비스에 대한 필요성이 크게 증가되었다. 본 연구에서는 신고, 응급구조, 환자이송 등 도시의 병원 전 단계 의료환경에 대해서 조사하였다. 본 연구의 목적은 반응시간과 출동거리를 분석함으로써, 응급사고에 즉시 응급구조서비스를 제공하기 위해 안전센터(119센터)의 최적 입지를 확인하는 것이다. 이를 위해서 사고발생, 반응시간, 출동거리 등을 응급의료 활동과 관련된 연구논문, 대상지 전역의 소방기록물과 출동일지 등의 통계자료를 활용하여 신속한 응급의료 서비스를 위한 패턴을 분석 하였다. 또한 응급구조대의 조직과 활동의 분석을 통해 응급의료시설의 최적 입지설정을 위한 제도적 개선대안을 마련해 보았다. 대상지 연구를 위해, 구조활동 및 소방서비스의 최근 통계자료의 조사를 통해 진주시의 모든 119센터의 입지와 응급의료서비스 및 사고발생 현황을 나타내었다. 자료 분석을 위해서 SPSS14.0을 사용하였으며, 지역의 특성 분포, 안전센터별 대응시간, 이송시간 등을 소방 GPS시스템과 입지할당모형 중 Center Point Model(CPM)을 적용하였다. 결과적으로 본 연구를 통해 대상지역의 119안전센터의 서비스 질이 나쁜 지역을 지리학적인 관점에서 최적 입지/배분 패턴의 설정을 통해 확인할 수 있었으며, 이를 통해 미래 응급의료서비스의 효율적인 입지/배분을 통해 공공 및 개인의 안전과 건강에 기여할 수 있을 것으로 기대된다.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.527-531
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• 2012

In this paper, a novel DPSO-QI (Distributed PSO with quantum-infusion mechanism) algorithm improving one of the fatal defect, the so-called premature convergence, that degrades the performance of the conventional PSO algorithms is proposed. The proposed scheme has the following two distinguished features. First, a concept of neighborhood of each particle is introduced, which divides the whole swarm into several small groups with an appropriate size. Such a strategy restricts the information exchange between particles to be done only in each small group. It thus results in the improvement of particles' diversity and further minimization of a probability of occurring the premature convergence phenomena. Second, a quantum-infusion (QI) mechanism based on the quantum mechanics is introduced to generate a meaningful offspring in each small group. This offspring in our PSO mechanism improves the ability to explore a wider area precisely compared to the conventional one, so that the degree of precision of the algorithm is improved. Finally, some numerical results are compared with those of the conventional researches, which clearly demonstrates the effectiveness and reliability of the proposed DPSO-QI algorithm.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.11
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• pp.787-794
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• 2019

In this paper, a Mixed Integer Linear Programming(MILP) approach for solving optimal Weapon-Target Assignment(WTA) problem of multiple dissimilar Closed-In Weapon Systems (CIWS) is proposed. Generally, WTA problems are formulated in nonlinear mixed integer optimization form, which often requires impractical exhaustive search to optimize. However, transforming the problem into a structured MILP problem enables global optimization with an acceptable computational load. The problem of interest considers defense against several threats approaching the asset from various directions, with different time of arrival. Moreover, we consider multiple dissimilar CIWSs defending the asset. We derive a MILP form of the given nonlinear WTA problem. The formulated MILP problem is implemented with a commercial optimizer, and the optimization result is proposed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.34 no.1
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• pp.42-48
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• 2006

In this study, a repetitive response surface enhancement technique (RRSET) is proposed as a new system approximation method for the efficient multidisciplinary design and optimization (MDO). In order to represent the highly nonlinear behavior of the response with second order polynomials, RRSET introduces a design space transformation using stretching functions and repetitive response surface improvement. The tentative optimal point is repetitively included to the set of experimental points to better approximate the response surface of the system especially near the optimal point, hence a response surface with significantly improved accuracy can be generated with very small experimental points and system iterations. As a system optimizer, the simulated annealing, which generates a global design solution is utilized. The proposed technique is applied to several numerical examples, and demonstrates the validity and efficiency of the method. With its improved approximation accuracy, the RRSET can contribute to resolve large and complex system design problems under MDO environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3B
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• pp.183-198
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• 2006

We define the incomplete medium sharing system as a multi-channel shared medium communication system where constraints are imposed to the set of channels that may be allocated to some transmitter-receiver node pairs. To derive a centralized MAC scheme of a incomplete medium sharing system, we address the problem of optimal channel allocation The optimal channel allocation problem is then translated into a max-flow problem in a multi-commodity flow graph, and it is shown that the optimal solution can then be obtained by solving a linear programming problem. In addition, two suboptimal channel allocation schemes are proposed to bring down the computational complexity to a practical/feasible level; (1) one is a modified iSLIP channel allocation scheme, (2) the other is sequential channel allocation scheme. From the results of a extensive set of numerical experiments, it is found that the suboptimal schemes evaluate channel utilization close to that of the optimal schemes while requiring much less amount of computation than the optimal scheme. In particular, the sequential channel allocation scheme is shown to achieve higher channel utilization with less computational complexity than . the modified iSLIP channel allocation scheme.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.1 s.71
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• pp.27-37
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• 2006

A Metropolis genetic algorithm (MGA) is developed and applied for the structural design optimization. In MGA, favorable features of Metropolis criterion of simulated annealing (SA) are incorporated in the reproduction operations of simple genetic algorithm (SGA). This way, the MGA maintains the wide varieties of individuals and preserves the potential genetic information of early generations. Consequently, the proposed MGA alleviates the disadvantages of premature convergence to a local optimum in SGA and time consuming computation for the precise global optimum in SA. Performances and applicability of MGA are compared with those of conventional algorithms such as Holland's SGA, Krishnakumar's micro GA, and Kirkpatrick's SA. Typical numerical examples are used to evaluate the computational performances, the favorable features and applicability of MGA. The effects of population sizes and maximum generations are also evaluated for the performance reliability and robustness of MGA. From the theoretical evaluation and numerical experience, it is concluded that the proposed MGA Is a reliable and efficient tool for structural design optimization.