• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.166-173
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• 2013

As the number of IPs and the communication volume among them have constantly increased, on-chip crossbar network is now the most widely-used on-chip communication backbone of contemporary SoCs. The on-chip crossbar network consists of multiple crossbars and the connections among the IPs and the crossbars. As the complexity of SoCs increases, it has also become more and more complex to determine the topology of the crossbar network. To tackle this problem, this paper proposes an on-chip crossbar network topology method for application-specific systems. The proposed method uses mixed integer linear programming to solve the topology synthesis problem, thus the global optimality is guaranteed. Unlike the previous MILP-based methods which represent the topology with adjacency matrixes of IPs and crossbar switches, the proposed method uses the communication edges among IPs as the basic element of the representation. The experimental results show that the proposed MILP formulation outperforms the previous one by improving the synthesis speed by 77.1 times on average, for 4 realistic benchmarks.

• Journal of Korean Association for Spatial Structures
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• v.7 no.4
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• pp.89-96
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• 2007

The fundamental frequency maximization of beam structures is carried out by using strain energy based topology optimization technique. It mainly uses the modal strain energy distributions induced by the mode shapes of the structures. The modal strain energy to be minimized is employed as the objective function and the initial volume of structures is adopted as the constraint function. The resizing algorithm devised from the optimality criteria method is used to update the hole size of the cell existing in each finite element. The beams with three different boundary conditions are used to investigate the optimum topologies against natural mode shapes. From numerical test, it is found to be that the optimum topologies of the beams produced by the adopted technique have hugh increases in some values of natural frequencies and especially the technique is very effective to maximize the fundamental frequency of the structures.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.414-424
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• 2012

Finding or automatically generating problem instance is useful for algorithm analysis/test. The topic has been of interest in the field of hardware/software engineering and theory of computation. We apply objective value-distance correlation analysis to problem spaces, as previous researchers applied it to solution spaces. According to problems, we define the objective function by (1) execution time of tested algorithm or (2) its optimality; this definition is interpreted as difficulty of the problem instance being solved. Our correlation analysis is based on the following aspects: (1) change of correlation when we use different algorithms or different distance functions for the same problem, (2) change of that when we improve the tested algorithm, (3) relation between a problem instance space and the solution space for the same problem. Our research demonstrates the way of problem instance space analysis and will accelerate the problem instance space analysis as an initiative research.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.4
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• pp.400-406
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• 2014

In this paper, we propose an approach to minimizing total power consumption by deploying multiple clean-up robots simultaneously in a given area. For this, we propose to use the cooperative game theoretic approaches (i.e., Nash bargaining solution (NBS)) such that the robots can optimally and fairly negotiate the area division based on available resources and characteristics of the area, thereby leading to the minimum total power consumption. We define a utility function that includes power consumptions for characteristics of areas and the robots can agree on a utility pair based on the NBS. Simulation results show that the proposed approach can reduce the total average power consumption by 15-30% compared to a random area division approach.

• Journal of Technology Innovation
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• v.5 no.1
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• pp.206-222
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• 1997

The conventional analysis with which justifies government intervention of the private sector's innovation activities is the market failure approach. According to such analysis, fund allocation through autonomous market mechanisms is not optimal in technology financing because of the disparity between the desirable level of investment for society as a whole and that for private firms. To optimize the fund allocation, public policies such as subsidy, preferencial loan and venture capital investment programs are designed for technology development projects performed by private firms. They, however, have not been effective in increasing private investment for such projects. In most cases, it was found that little considerations given to the relationship between uncertainty embodied in technology development projects and each types of financing. With respect to optimizing fund allocation, technology development projects should be financed by different means according to their probability of success and the expected value of technology. Employing various theoretical models on financing decision-making we verify here that technology development projects to be supported by commercial banks or venture capital institutions is limited contingent upon levels of uncertainty adn expected value. Under the assumption that financial institutions are risk averse, loan or investment can be available only if the probability of success of the project is higher than the probability premium and the current market rate of interest. Therefore, the projects that have lower probability of success and/or small expected return are excluded from commercial loan or investment programs. However, the remaining projects, whose probability of success is low but with high expected return, may be applied under government subsidy programs. To achieve optimality of fund allocation and to activate technology financing, we conclude that there should be a systematic division of role among financial institutions including government commercial banks, and venture capital institutions.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.6
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• pp.56-66
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• 1998

This paper investigates a neuro-controller combined in parallel with a conventional linear controller of PID type in order to control nonminimum phase systems more efficiently. The objective is to minimize overall position errors as well as to maintain small undershooting. A costfunction is proposed with two conflict objectives. The neuro-controller is trained off-line with evolutionary programming(EP) in such a way that it becomes optimal by minimizing the given cost function through global evaluation based on desired control performance during the whole training time interval. However, it is not easy to find an optimal solution which satisfies individual objective simultaneously. With the concept of Pareto optimality and EP, we train the proposed controller more effectively and obtain a valuable set of optimal solutions. Simulation results show the efficacy of the proposed controller in a viewpoint of improvement of performance of a step response like fast settling time and small undershoot or overshoot compared with that of a conventional linear controller.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.42 no.4
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• pp.7-14
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• 2005

Recently, images/videos have been preferred as the communication media because of their information-implication and easy recognizability. But the amount of their data is so large that it has been the major research area to compress their data. This paper is related to optimization in the image data format which can make a great effect in performance of data compression and is based on the wavelet transform and JPEG2000. This paper established a criterion to decide the data format to he used in wavelet transform which is on the bases of the data errors in frequency transform and quantization. This criterion has been used to extract the optimal data format experimentally. The result were (1, 9) of 10-bit fixed-point format for filter coefficients and (9, 7) of 16-bit fixed-point data format for wavelet coefficients and their optimality was confirmed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1487-1493
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• 2016

The susceptible, exposed, infectious, and recovered model (SEIR) is used extensively in the field of epidemiology. On the other hand, dissemination information among users through internet grows exponentially. This information spreading can be modeled as an epidemic. In this paper, we derive the mathematical model of SEIR in viral communication from the view of optimal control theory. Overall the methods based on classical calculus, In order to solve the optimal control problem, proved to be more efficient and accurate. According to Pontryagin's minimum principle (PMP) the Hamiltonian function must be optimized by the control variables at all points along the solution trajectory. We present our method based on the PMP and forward backward algorithm. In this algorithm, one should integrate forward in time for the state equations then integrate backward in time for the adjoint equations resulting from the optimality conditions. The problem is mathematically analyzed and numerically solved as well.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.7
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• pp.666-673
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• 2008

To construct the accurate radio satellite navigation system, the efficient communication each satellite with the ground station is very important. Throughout the communication, the orbit of each satellite can be corrected, and those information will be used to analyze the satellite satus by the operator. Since there are limited resources of ground station, the schedule of antenna's azimuth and elevation angle should be optimized. On the other hand, the satellite in the medium earth orbit does not pass the same point of the earth surface due to the rotation of the earth. Therefore, the antenna pass schedule must be updated at the proper moment. In this study, Q learning approach which is a form of model-free reinforcement learning and genetic algorithm are considered to find the optimal antenna schedule. To verify the optimality of the solution, numerical simulations are conducted.

• Journal of KIISE:Software and Applications
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• v.32 no.10
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• pp.963-973
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• 2005

Increasing attention is being recently devoted to various problems inherent in the topological design of networks systems. The topological structure of these networks can be based on service centers, terminals (users), and connection cable. Lately, these network systems are well designed with tiber optic cable, because the requirements from users become increased. But considering the high cost of the fiber optic cable, it is more desirable that the network architecture is composed of a spanning tree. In this paper, we present a GA (Genetic Algorithm) for solving bicriteria network topology design problems of wide-band communication networks connected with fiber optic cable, considering the connection cost, average message delay, and the network reliability We also employ the $Pr\ddot{u}fer$ number (PN) and cluster string in order to represent chromosomes. Finally, we get some experiments in order to certify that the proposed GA is the more effective and efficient method in terms of the computation time as well as the Pareto optimality.