• Journal of the Society of Naval Architects of Korea
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• v.43 no.1 s.145
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• pp.96-102
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• 2006

In this study, an optimization routine with genetic algorithms is coupled for the selection of free variables for the production of a control signal for the motion of wave board in the numerical wave tank. An excitation function for the controlling of the wave board is formulated on basis of amplitude modulation for the generation of nonlinear wave packets. The found variables by the optimization serve for the determination of wave board motion both with the computation and with the experiment. The breaking criterion of the water waves is implemented as boundary condition for the optimization procedure. With the analysis of the time registration on the local position in the wave tank the optimization routine is accomplished until the given design wave with defined surface elevation is found. Water surface elevation and associated fields of velocity and pressure are numerically computed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4357-4378
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• 2017

In cooperative multi-relay networks, the relay nodes which are selected are very important to the system performance. How to choose the best cooperative relay nodes is an optimization problem. In this paper, multi-relay selection schemes which consider either single objective or multi-objective are proposed based on evolutionary algorithms. Firstly, the single objective optimization problems of multi-relay selection considering signal to noise ratio (SNR) or power efficiency maximization are solved based on the quantum bee colony optimization (QBCO). Then the multi-objective optimization problems of multi-relay selection considering SNR maximization and power consumption minimization (two contradictive objectives) or SNR maximization and power efficiency maximization (also two contradictive objectives) are solved based on non-dominated sorting quantum bee colony optimization (NSQBCO), which can obtain the Pareto front solutions considering two contradictive objectives simultaneously. Simulation results show that QBCO based multi-relay selection schemes have the ability to search global optimal solution compared with other multi-relay selection schemes in literature, while NSQBCO based multi-relay selection schemes can obtain the same Pareto front solutions as exhaustive search when the number of relays is not very large. When the number of relays is very large, exhaustive search cannot be used due to complexity but NSQBCO based multi-relay selection schemes can still be used to solve the problems. All simulation results demonstrate the effectiveness of the proposed schemes.

• Journal of Digital Contents Society
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• v.16 no.5
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• pp.805-813
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• 2015

Many researchers expect the compressive sensing and sparse recovery problem can overcome the limitation of conventional digital techniques. However, these new approaches require to solve the l1 norm optimization problems when it comes to signal reconstruction. In the signal reconstruction process, the transform computation by multiplication of a random matrix and a vector consumes considerable computing power. To address this issue, parallel processing is applied to the optimization problems. In particular, due to huge size of original signal, it is hard to store the random matrix directly in memory, which makes one need to design a procedural approach in handling the random matrix. This paper presents a new parallel algorithm to calculate random partial Haar wavelet transform based on Single Instruction Multiple Threads (SIMT) platform.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1755-1777
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• 2022

The development of wireless communication technology has led to the underutilization of radio spectra. To address this limitation, an intelligent cognitive radio network was developed. Specific emitter identification (SEI) is a key technology in this network. However, in realistic non-cooperative scenarios, the system may detect signal classes beyond those in the training database, and only a few labeled signal samples are available for network training, both of which deteriorate identification performance. To overcome these challenges, a meta-learning-based open-set identification system is proposed for SEI. First, the received signals were pre-processed using bi-spectral analysis and a Radon transform to obtain signal representation vectors, which were then fed into an open-set SEI network. This network consisted of a deep feature extractor and an intrinsic feature memorizer that can detect signals of unknown classes and classify signals of different known classes. The training loss functions and the procedures of the open-set SEI network were then designed for parameter optimization. Considering the few-shot problems of open-set SEI, meta-training loss functions and meta-training procedures that require only a few labeled signal samples were further developed for open-set SEI network training. The experimental results demonstrate that this approach outperforms other state-of-the-art SEI methods in open-set scenarios. In addition, excellent open-set SEI performance was achieved using at least 50 training signal samples, and effective operation in low signal-to-noise ratio (SNR) environments was demonstrated.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.9
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• pp.39-45
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• 2009

When Mobile IPv6 is deployed in commercial network, a mobile node needs AAA services for an authentication, authorization and accounting. AAA and Mobile IPv6 are protocols which are operated independently. Then schemes which merge these protocols have been emerged. These schemes can enable a mobile node to establish a security association between the mobile node and a home agent and to perform a binding update for the home agent using AAA authentication request. But these schemes introduce many signal messages and long handover latency during the handover, since Route Optimization mode for Mobile Ipv6 is performed using Return Routability procedure. To solve this problem, we propose a scheme for Route Optimization mode that the home agent performs the binding update for a correspondent node via the AAA infrastructure between the home agent and the correspondent node instead of Return Routability procedure. For performance evaluation, we analyze signal message transmission costs and handover latencies during handover. We show performance improvement of the proposed scheme which reduces handover latency as 61% compared with the existing scheme.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.4
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• pp.779-787
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• 2010

In this paper, We introduce electrical tracking generated from surface activity associated with flow of leakage current on insulator under wet and contaminated conditions and design electrical tracking pattern recognition system by using LabVIEW. We measure the leaking current of contaminated wire by using LabVIEW software and the NI-c-DAQ 9172 and NI-9239 hardware. As pattern recognition algorithm and optimization algorithm for electrical tracking system, neural networks, Radial Basis Function Neural Networks(RBFNNs) and particle swarm optimization are exploited. The designed electrical tracking recognition system consists of two parts such as the hardware part of electrical tracking generator, the NI-c-DAQ 9172 and NI-9239 hardware and the software part of LabVIEW block diagram, LabVIEW front panel and pattern recognition-related application software. The electrical tracking system decides whether electrical tracking generate or not on electrical wire.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.587-592
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• 2018

An adaptive beam forming system using a phased array antenna improves communication quality by beam forming adaptively to a communication environment having an interference signal. For adaptive beam forming, a good combination of the phases of the excited signals to each radiating element of the phased array antenna should be calculated. In this paper, improved particle swarm optimization algorithm that adds a re-spreading procedure according to particle density was proposed to increase the probability of good phase shift combination output.

• Journal of Power System Engineering
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• v.16 no.2
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• pp.54-59
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• 2012

In the present study, process optimization for thermal-sprayed Ni-based alloy coating has been performed using Taguchi method and analysis of variance(ANOVA). Ni-based alloy coatings were fabricated by flame spray process on steel substrate, and the hardness test and wear test were performed. Experiments were designed as per Taguchi's L9 orthogonal array and tests were conducted with different Oxygen gas flow, Acetylene gas flow, Powder feed rate and Spray distance. Multi response signal to noise ratio (MRSN) was calculated for the response variables and the optimum combination level of factors was obtained simultaneously using Taguchi's parametric design.

• Journal of Power System Engineering
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• v.17 no.6
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• pp.108-114
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• 2013

This paper describes process optimization for thermal-sprayed Co-based self-flux alloy coating by Taguchi method. Co-based self-flux alloy coatings were fabricated according to $L_9(3^4)$ orthogonal array using flame spray process. Hardness test and wear test were performed, the results were analyzed by analysis of variance(ANOVA) considering a multi response signal to noise ratio(MRSN). From the results of ANOVA, the optimal combination of the flame spray parameters on Co-based self-flux alloy coating could be predicted. The calculated hardness and wear rate of the coatings by ANOVA were found to be close to that of confirmation experimental result.

• Journal of international Conference on Electrical Machines and Systems
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• v.1 no.2
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• pp.58-63
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• 2012

The Test Signal Method is adopted to analyze the impact of thyristor controlled series capacitor (TCSC) on sub-synchronous oscillation. The results show that the simulation system takes the risk of Sub-synchronous Oscillation (SSO) while the TCSC is operating in the capacitive region. A supplementary excitation damping controller (SEDC) is used to mitigate SSO caused by the TCSC. A new optimization method which is aimed for optimal phase compensation is proposed. This method is realized by using the particle swarm optimization (PSO) algorithm. The simulation results show that the SEDC designed by this method has superior suitability, and that the secure operation scope of the TCSC is greatly increased.