• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2128-2147
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• 2021

Cognitive radio systems are being implemented recently to tackle spectrum underutilization problems and aid efficient data traffic. Spectrum sensing is the crucial step in cognitive applications in which cognitive user detects the presence of primary user (PU) in a particular channel thereby switching to another channel for continuous transmission. In cognitive radio systems, the capacity to precisely identify the primary user's signal is essential to secondary user so as to use idle licensed spectrum. Based on the inherent capability, a new spectrum sensing technique is proposed in this paper to identify all types of primary user signals in a cognitive radio condition. Hence, a spectrum sensing algorithm using improved convolutional neural network and long short-term memory (CNN-LSTM) is presented. The principle used in our approach is simulated annealing that discovers reasonable number of neurons for each layer of a completely associated deep neural network to tackle the streamlining issue. The probability of detection is considered as the determining parameter to find the efficiency of the proposed algorithm. Experiments are carried under different signal to noise ratio to indicate better performance of the proposed algorithm. The PU signal will have an associated modulation format and hence identifying the presence of a modulation format itself establishes the presence of PU signal.

• Steel and Composite Structures
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• v.49 no.1
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• pp.1-17
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• 2023

Based on Ahmadzadeh-Varvani hardening rule (A-V model), multiaxial ratcheting effect of Z2CND18.12N austenitic stainless steel is simulated by ABAQUS with user subroutine UMAT. The results show that the predicted results of the origin multiaxial A-V model are lower than the experimental data, and it is difficult to control ratcheting strain rate. In order to improve the predicted capability of A-V model, the A-V model is modified. In this study. Moreover, under the assumption of the von Mises yield criterion and normal plasticity flow rule, we develop a numerical algorithm of plastic strain with the improved model to implement the finite element calculation of the model. Internal iteration in the numerical algorithm was implemented with the Euler backward method, which calculated the trial strain for each equilibrium iteration using the consistent tangent matrix. With a user subroutine, the proposed model is programmed into ABAQUS for a user - executable version. By simulating the uniaxial ratcheting of a round bar made of Z2CND18.12N austenitic stainless steel, we observe that the predicted results simulated by ABAQUS with UMAT are compared with the experimental data. The predicted results of the improved multiaxial A-V model are consistent well with the experimental data.

• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.77-88
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• 2015

In this paper, we consider a two-agent single-machine scheduling problem with exponential job-dependent position-based learning effects. The objective is to minimize the total weighted completion time of one agent with the restriction that the makespan of the other agent cannot exceed an upper bound. First, we propose a branch-and-bound algorithm by developing some dominance /feasibility properties and a lower bound to find an optimal solution. Second, we design an efficient simulated annealing (SA) algorithm to search a near optimal solution by considering six different SAs to generate initial solutions. We show the performance superiority of the suggested SA using a numerical experiment. Specifically, we verify that there is no significant difference in the performance of %errors between different considered SAs using the paired t-test. Furthermore, we testify that random generation method is better than the others for agent A, whereas the initial solution method for agent B did not affect the performance of %errors.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.164-167
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• 2002

This paper presents the design of Rijndael crypto-processor with 128 bits, 192 bits and 256 bits key size. In October 2000 Rijndael cryptographic algorithm is selected as AES(Advanced Encryption Standard) by NIST(National Institute of Standards and Technology). Rijndael algorithm is strong in any known attacks. And it can be efficiently implemented in both hardware and software. We implement Rijndael algorithm in hardware, because hardware implementation gives more fast encryptioN/decryption speed and more physically secure. We implemented Rijndael algorithm for 128 bits, 192 bits and 256 bits key size with VHDL, synthesized with Synopsys, and simulated with ModelSim. This crypto-processor is implemented using on-the-fly key generation method and using lookup table for S-box/SI-box. And the order of Inverse Shift Row operation and Inverse Substitution operation is exchanged in decryption round operation of Rijndael algorithm. It brings about decrease of the total gate count. Crypto-processor implemented in these methods is applied to mobile systems and smart cards, because it has moderate gate count and high speed.

• Transactions of Materials Processing
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• v.4 no.1
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• pp.48-58
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• 1995

In this study, a contact algorithm for the finite element analysis of free surface contact problem in materials forming is presented. The proposed contact algorithm consists of two parts. The first is the contact searching part, and the second, the constraint part. The contact searching algorithm does not require any a priori knowledge of the pairs of contact nodes or segments and the impenetrability constraint is satisfied using the penalty function scheme. void colsure in open-die forging was simulated to verify the accuracy and capability of the currently developed contact algorithm. The simulation results, obtained from ABAQUS simulation, were compared well to the experimental data available in the literature.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.446-452
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• 2008

To design a spiral inductor a genetic algorithm is applied with fast computing technique. For the inductance extraction of the given geometry the fast multipole method is used, also the distributed computing technique using 10 personal computers is introduced for the massive computation of the genetic algorithm. A few important design parameters are used as genes for the optimization in the genetic algorithm. The target function is chosen as mean square error of the inductance at several sampling frequency points. A large-scaled inductor is fabricated and compared with the simulated data.

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1689-1699
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• 2006

A nonlinear channel blind equalizer by using a hybrid genetic algorithm, which merges a genetic algorithm with simulated annealing, and a RBF network is presented. In this study, a hybrid genetic algorithm is used to estimate the output states of a nonlinear channel, based on the Bayesian likelihood fitness function, instead of the channel parameters. From these estimated output states, the desired channel states of the nonlinear channel are derived and placed at the center of a RBF equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a conventional genetic algorithm(GA) and a simplex GA, and the relatively high accuracy and fast convergence of the method are achieved.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.14-15
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• 2006

A saturation of magnetic flux in the core may occur when a large primary current flows when the iron-cored current transformer is used. This saturation makes the distorted secondary current of the CT. the distorted secondary current may cause the mal-operation or operation time delay of protective relays. CT compensation algorithm using The LSQ(Least Square) fitting method has a problem. It needs to acquire enough data for executing this algorithm without an error. In this paper, an enhanced algorithm using interpolation based LSQ(Least Square) Fitting Method is proposed. The Lagrange Interpolation Method is used for the interpolation and CT is simulated by EMTP. The results show that the proposed algorithm can accurately compensate a distorted secondary current more than existing Algorithm when the saturation severely occurs.

• Journal of the Optical Society of Korea
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• v.19 no.1
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• pp.45-54
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• 2015

In this study, a novel parallel wavefront correction system architecture is proposed, and a model-based tabu search (MBTS) algorithm is introduced for this new system to compensate wavefront aberration caused by atmospheric turbulence in a free-space optical (FSO) communication system. The algorithm flowchart is presented, and a simple hypothetical design for the parallel correction system with multiple adaptive optical (AO) subsystems is given. The simulated performance of MBTS for an AO-FSO system is analyzed. The results indicate that the proposed algorithm offers better performance in wavefront aberration compensation, coupling efficiency, and convergence speed than a stochastic parallel gradient descent (SPGD) algorithm.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.54 no.4
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• pp.163-170
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• 2005

This paper deals with an improved fault location algorithm with compensation ground capacitance through distributed parameter for a long parallel T/L. For the purpose of fault locating algorithm non-influenced by source impedance and fault resistance, the loop method was used in the system modeling analysis. This algorithm uses a positive and negative sequence of the fault current for high accuracy of fault locating calculation. Power system model of 160km and 300km long parallel T/L was simulated using EMTP software. To evaluate of the proposed algorithm, we used the several different cases 64 sampled data per cycle. The test results show that the proposed algorithm was minimized the error factor and speed of fault location estimation.