• Journal of Korea Game Society
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• v.19 no.6
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• pp.83-90
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• 2019

Heuristic based Genetic Algorithm Pathfinding(H-GAP), a method without the need for node and edge information, can compensate the disadvantages of existing pathfinding algorithm, and perform the path search at high speed. However, because the pathfinding by H-GAP is non-node-based, it may not be an optimal path when it includes unnecessary path information. In this paper, we propose an algorithm to optimize the search path using H-GAP. The proposed algorithm optimizes the path by removing unnecessary path information through ray-tracing algorithm after the H-GAP path search is completed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4220-4241
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• 2017

For the downlink energy-harvesting small cell network, this paper proposes an interference management algorithm based on distributed coalitional game. The cooperative interference management problem of the energy-harvesting small cells is modeled as a coalitional game with transfer utility. Based on the energy harvesting strategy of the small cells, the time sharing mode of the small cells in the same coalition is determined, and an optimization model is constructed to maximize the total system rate of the energy-harvesting small cells. Using the distributed algorithm for coalition formation proposed in this paper, the stable coalition structure, optimal time sharing strategy and optimal power distribution are found to maximize the total utility of the small cell system. The performance of the proposed algorithm is discussed and analyzed finally, and it is proved that this algorithm can converge to a stable coalition structure with reasonable complexity. The simulations show that the total system rate of the proposed algorithm is superior to that of the non-cooperative algorithm in the case of dense deployment of small cells, and the proposed algorithm can converge quickly.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.8
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• pp.726-732
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• 2005

This paper proposes an autolanding guidance and control algorithm with the lateral guidance law. This algorithm is basically formulated and designed in feedback linearization based on singular perturbation. Main features of this algorithm are two facts. One of those is that when a certain situation happens that airplane must realign to the runway suddenly assigned due to unexpected environment change around the landing site, the heading guidance in this algorithm is very valuable, and the other is the fact that the inner loop control of this algorithm is able to be designed directly based on the Handling Quality Requirements that most flight control systems must be satisfied with. To illustrate the potential of this algorithm, 6-DOF nonlinear simulation based on the nonlinear airplane model shown in Ref.[11] is carried out. The simulation results showed that the altitude response to the given landing trajectory is accurate, and the airplane heading alignment to the assigned runway from the lateral deviation is successful. It is noted that this algorithm is also applicable to unmanned aerial vehicle, which can be retrieved in autolanding technique, where the runway far retrieving the vehicle is in any direction for example at war field.

• Journal of the Korea Institute of Military Science and Technology
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• v.19 no.2
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• pp.252-260
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• 2016

Unlike terrestrial transportation, marine transportation should consider environment factors in order to optimize path planning. This is because, ship's path planning is greatly influenced by real-time ocean environment-sea currents, wave and wind. Therefore, in this study, we suggest a ship path planning algorithm based on real-time ocean environment using not only $A^*$ algorithm but also path smoothing method. Moreover, in order to improve objective function value, we also consider ship's moving distance based on ship's location and real-time ocean environment data on grid map. The efficiency of the suggested algorithm is proved by comparing with $A^*$ algorithm only. This algorithm can be used as a reasonable automatics control system algorithm for unmaned ship.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.41-48
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• 2013

An efficient encryption algorithm based on the Data Encryption Standard (DES) for personal cloud computing environments is presented. The proposed algorithm improves data privacy, security and also encryption speed, compared with the triple DES. The improvement of the proposed algorithm stems from enhanced privacy inherent from the use of spread random interleaver in the place of the known substitution table for initial and final permutations in the DES algorithm. The simulation results demonstrate that the interleaver based DES (I-DES) is found to run faster than the triple DES algorithm and also offer improved security. The proposed algorithm also offers encryption for variable-length data using the Cipher Block Chaining (CBC).

• ETRI Journal
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• v.42 no.6
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• pp.922-931
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• 2020

A hierarchical iterative algorithm for the canonical polyadic decomposition (CPD) of tensors is proposed by improving the traditional conjugate gradient least squares (CGLS) method. Methods based on algebraic operations are investigated with the objective of estimating the direction of arrival (DoA) and polarization parameters of signals impinging on an array with electromagnetic (EM) vector-sensors. The proposed algorithm adopts a hierarchical iterative strategy, which enables the algorithm to obtain a fast recovery for the highly collinear factor matrix. Moreover, considering the same accuracy threshold, the proposed algorithm can achieve faster convergence compared with the alternating least squares (ALS) algorithm wherein the highly collinear factor matrix is absent. The results reveal that the proposed algorithm can achieve better performance under the condition of fewer snapshots, compared with the ALS-based algorithm and the algorithm based on generalized eigenvalue decomposition (GEVD). Furthermore, with regard to an array with a small number of sensors, the observed advantage in estimating the DoA and polarization parameters of the signal is notable.

• Structural Engineering and Mechanics
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• v.32 no.5
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• pp.667-683
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• 2009

FE model-based dynamic analysis has been widely used to predict the dynamic characteristics of civil structures. In a physical point of view, an FE model is unavoidably different from the actual structure as being formulated based on extremely idealized engineering drawings and design data. The conventional model updating methods such as direct method and sensitivity-based parameter estimation are not flexible for model updating of complex and large structures. Thus, it is needed to develop a model updating method applicable to complex structures without restriction. The main objective of this paper is to present the model updating method based on the hybrid genetic algorithm (HGA) by combining the genetic algorithm as global optimization method and modified Nelder-Mead's Simplex method as local optimization method. This FE model updating method using HGA does not need the derivation of derivative function related to parameters and without application of complicated inverse analysis methods. In order to allow its application on diversified and complex structures, a commercial FEA tool is adopted to exploit previously developed element library and analysis algorithms. Moreover, an output-level objective function making use of measurement and analytical results is also presented to update simultaneously the stiffness and mass of the analysis model. The numerical examples demonstrated that the proposed method based on HGA is effective for the updating of the FE model of bridge structures.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.272-275
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• 2016

This paper presents a method of single image dehazing and surface-based feature detection for remote sensing images. In the conventional dark channel prior (DCP) algorithm, the resulting transmission map invariably includes some block artifacts because of patch-based processing. This also causes image blur. Therefore, a refined transmission map based on a hidden Markov random field and expectation-maximization algorithm can reduce the block artifacts and also increase the image clarity. Also, the proposed algorithm enhances the accuracy of image matching surface-based features in an remote sensing image. Experimental results confirm that the proposed algorithm is superior to conventional algorithms in image haze removal. Moreover, the proposed algorithm is suitable for the problem of image matching based on feature extraction.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.43-49
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• 2023

In modern wireless communication systems including beamformers or location-based services (LBS), which employ multiple antenna elements, estimating the number of signals is essential for accurately determining the quality of the communication service. Representative signal number estimation algorithms including the Akaike information criterion (AIC) and minimum description length (MDL) algorithms, which are information theoretical criterion models, determine the number of signals based on a reference value that minimizes each criterion. In general, increasing the number of elements mounted onto the array antenna enhances the performance of estimating the number of signals; however, it increases the computational complexity of the estimation algorithm. In addition, various configurations of array antennas for the increased number of antenna elements should be considered to efficiently utilize them in a limited location. In this paper, we introduce an efficient signal number estimation algorithm based on the beamspace based AIC and MDL techniques that reduce the computational complexity by reducing the dimension of a uniform circular array antenna. Since this algorithm is based on a uniform circular array antenna, it presents the advantages of a circular array antenna. The performance of the proposed signal number estimation algorithm is evaluated through computer simulation examples.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4364-4384
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• 2021

The dynamic network state and the mobility of the terminals make the service function chain (SFC) orchestration mechanisms based on static and deterministic assumptions hard to be applied in SDN/NFV mobile edge computing networks. Designing dynamic and online SFC orchestration mechanism can greatly improve the execution efficiency of compute-intensive and resource-hungry applications in mobile edge computing networks. In order to increase the overall profit of service provider and reduce the resource cost, the system running time is divided into a sequence of time slots and a dynamic orchestration scheme based on an improved column generation algorithm is proposed in each slot. Firstly, the SFC dynamic orchestration problem is formulated as an integer linear programming (ILP) model based on layered graph. Then, in order to reduce the computation costs, a column generation model is used to simplify the ILP model. Finally, a two-stage heuristic algorithm based on greedy strategy is proposed. Four metrics are defined and the performance of the proposed algorithm is evaluated based on simulation. The results show that our proposal significantly provides more than 30% reduction of run time and about 12% improvement in service deployment success ratio compared to the Viterbi algorithm based mechanism.