• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.3-9
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• 2015

We investigate rate scheduling and power allocation problem for a delay constrained CDMA systems. Specifically, we determine an energy efficient scheduling policy, while each user maintains the short term (n time slots) average throughput. We consider a multirate CDMA system where multirate is achieved by multiple codes. Each code can be interpreted as a virtual user. The aim is to schedule the virtual users into each time slot, such that the sum of transmit energy in n time slots is minimized. We then show that the total energy minimization problem can be solved by a shortest path algorithm. We compare the performance of the optimum scheduling with that of TDMA-type scheduling.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.123-126
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• 1998

The theoretical foundations of GA are the Schema Theorem and the Building Block Hypothesis. In the Meaning of these foundational concepts, simple genetic algorithm(SGA) allocate more trials to the schemata whose average fitness remains above average. Although SGA does well in many applications as an optimization method, still it does not guarantee the convergence of a global optimum. Therefore as an alternative scheme, there is a growing interest in a co-evolutionary system, where two populations constantly interact and co-evolve in contrast with traditional single population evolutionary algorithms. In this paper, we propose a new design method of an optimal fuzzy logic controller using co-evolutionary concept. In general, it is very difficult to find optimal fuzzy rules by experience when the input and/or output variables are going to increase. So we propose a co-evolutionary method finding optimal fuzzy rules. Our algorithm is that after constructing two population groups m de up of rule vase and its schema, by co-evolving these two populations, we find optimal fuzzy logic controller. By applying the proposed method to a path planning problem of autonomous mobile robots when moving objects exist, we show the validity of the proposed method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3B
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• pp.188-195
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• 2002

In this paper, we consider efficient multiuser receiver structures using Hopfield neural network algorithm focused to construct a synchronous multi-rate code division multiple access (CDMA) system. Although the optimum receiver for multiuser detection can be realized attaining the best BER performance, it is too complex for practical implementation. Therefore, we propose near-optimal receivers of relatively low computationally complex multiuser detection structures for realizing multi-rate CDMA system and their performances are compared with conventional matched filter and other prominent multi-rate multiuser detectors, Computer simulations show that the Hopfield neural network based multiuser receiver achieves substantially better BER performance in Rayleigh fading environments.

• Structural Engineering and Mechanics
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• v.42 no.3
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• pp.335-352
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• 2012

Particle Swarm Optimization (PSO) is a stochastic population based optimization algorithm which has attracted attentions of many researchers. This method has great potentials to be applied to many optimization problems. Despite its robustness the standard version of PSO has some drawbacks that may reduce its performance in optimization of complex structures such as laminated composites. In this paper by suggesting a new variation scheme for acceleration parameters and inertial weight factors of PSO a novel optimization algorithm is developed to enhance the basic version's performance in optimization of laminated composite structures. To verify the performance of the new proposed method, it is applied in two multi-objective design optimization problems of laminated cylindrical. The numerical results from the proposed method are compared with those from two other conventional versions of PSO-based algorithms. The convergancy of the new algorithms is also compared with the other two versions. The results reveal that the new modifications inthe basic forms of particle swarm optimization method can increase its convergence speed and evade it from local optima traps. It is shown that the parameter variation scheme as presented in this paper is successful and can evenfind more preferable optimum results in design of laminated composite structures.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.256-263
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• 1998

Among process synthesis problems, the heat exchanger network (HEN) has been subjected to the most concentrated effort because this kind of problems was well defined for solving it and 20-30% energy savings could be realized in the present chemical processes. In this paper, we use an evolutionary approach for HEN synthesis because this approach can overcome the local optimum and combine some heuristic rules. The basic evolutionary approach is composed of three parts, that is, initialization step, growth step and mutation step, as in the simulated annealing and genetic algorithm. This algorithm uses the ecological rule that a better cell will live and worse cell should decompose after repeated generations. With this basic concept, a new procedure is developed and a more efficient method is proposed to generate initial solutions. Its effectiveness is shown using test examples.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.721-724
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• 2010

아웃리거 시스템은 고층건물의 구조설계 시에 횡변위를 제어하기 위해 사용되는 가장 효율적이고 널리 사용되는 구조시스템 중 하나이다. 아웃리거는 설치 위치의 최적성에 따라 횡변위 제어효과에 상당한 차이가 있으며, 1970년대 이후부터 아웃리거의 최적위치에 관한 연구가 활발히 진행되어 왔다. 아웃리거의 최적위치는 구조물의 전단벽, 아웃리거, 외각기둥의 요소간 강성비에 따라 변하는 값이므로, 아웃리거 시스템의 횡변위는 요소간 강성비와 아웃리거 위치 모두에 의해 영향을 받는다. 따라서 초기구조설계 단계에서 아웃리거의 위치에 대한 결정과, 각 요소간 강성비의 선택은, 전체 구조 시스템의 효율성에 상당한 영향을 미치게 된다. 하지만 아웃리거 시스템의 최적 효율을 보장하면서, 구조물의 초기 설계 시에 참고할 수 있는, 아웃리거의 최적위치와 요소간 강성비에 대한 연구는 미흡한 실정이다. 따라서 본 연구에서는 GA(genetic algorithm)을 이용하여 초기 설계 시에 참고할 수 있는 고층건물의 횡변위를 최소로 하는, 아웃리거의 최적 위치 및 요소간 강성비에 대한 연구를 진행하고자 한다. 이를 위해 시공된 예제 건물에 적용을 통해 그 효과를 검증해 본다.

• Proceeding of KASS Symposium
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• 2006.05a
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• pp.233-238
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• 2006

This paper provides a new topology optimization technique which is intended to maximize the fundamental frequency with simultaneous consideration of other natural frequencies in the form of multi-frequency problems. The modal strain energy is considered as the objective function to be minimized and the initial volume of structures is used as the constraint function. The resizing algorithm based on the optimality criteria is adopted to update the hole size existing inside the material. From numerical tests, the proposed technique is found to be very effective to maximize the fundamental frequency of the structure and it can also successfully consider several higher mode effects into the optimum topology of structure through the introduction of weights.

• Advances in Computational Design
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• v.1 no.3
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• pp.235-251
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• 2016

We have performed a design optimization of a stiffened panel with curvilinear stiffeners using an artificial neural network (ANN) residual kriging based surrogate modeling approach. The ANN residual kriging based surrogate modeling involves two steps. In the first step, we approximate the objective function using ANN. In the next step we use kriging to model the residue. We optimize the panel in an iterative way. Each iteration involves two steps-shape optimization and size optimization. For both shape and size optimization, we use ANN residual kriging based surrogate model. At each optimization step, we do an initial sampling and fit an ANN residual kriging model for the objective function. Then we keep updating this surrogate model using an adaptive sampling algorithm until the minimum value of the objective function converges. The comparison of the design obtained using our optimization scheme with that obtained using a traditional genetic algorithm (GA) based optimization scheme shows satisfactory agreement. However, with this surrogate model based approach we reach optimum design with less computation effort as compared to the GA based approach which does not use any surrogate model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.33-49
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• 1998

In order to improve the performance of relational databases, one has to reduce the number of disk accesses necessary to transfer data from disk to main memory. The paper proposes to reduce the number of disk I/O accesses by vertically partitioning relation into fragments and allowing attribute replication to fragments if necessary. When zero-one integer programming model is solved by the branch-and-bound method, it requires much computing time to solve a large sized problem. Therefore, heuristic solutions using genetic algorithm(GA) are presented. GA in this paper adapts a few ideas which are different from traditional genetic algorithms, for examples, a rank-based sharing fitness function, elitism and so on. In order to improve performance of GA, a set of optimal parameter levels is determined by the experiment and makes use of it. As relations are vertically partitioned allowing attribute replications and saved in disk, an attribute replicating vertical partition method by GA can attain less access cost than non-attribute-replication one and require less computing time than the branch-and-bound method in large-sized problems. Also, it can acquire a good solution similar to the optimum solution in small-sized problem.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.3B
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• pp.529-540
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• 2000

This is paper presents the semantic based rate-control method which is based on very low bit rate video coding standards H.263 plus, applied on very low bit rate applications. Previous rate control methods control the generated bit rates by setting the optimum quantization parameters per macro block unit on frame. But, in this paper, we added the pre-processing algorithm, semantic region recognition and assignment of priority algorithm, to obtain the subjective quality enhancement. This work aims to improve the subjective quality of skin color region or face by using unimportant background region's bit resources.