• Smart Structures and Systems
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• v.26 no.3
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• pp.263-275
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• 2020

This research is dedicated to slope stability analysis using novel intelligent models. By coupling a neural network with spotted hyena optimizer (SHO), salp swarm algorithm (SSA), shuffled frog leaping algorithm (SFLA), and league champion optimization algorithm (LCA) metaheuristic algorithms, four predictive ensembles are built for predicting the factor of safety (FOS) of a single-layer cohesive soil slope. The data used to develop the ensembles are provided from a vast finite element analysis. After creating the proposed models, it was observed that the best population size for the SHO, SSA, SFLA, and LCA is 300, 400, 400, and 200, respectively. Evaluation of the results showed that the combination of metaheuristic and neural approaches offers capable tools for estimating the FOS. However, the SSA (error = 0.3532 and correlation = 0.9937), emerged as the most reliable optimizer, followed by LCA (error = 0.5430 and correlation = 0.9843), SFLA (error = 0.8176 and correlation = 0.9645), and SHO (error = 2.0887 and correlation = 0.8614). Due to the high accuracy of the SSA in properly adjusting the computational parameters of the neural network, the corresponding FOS predictive formula is presented to be used as a fast yet accurate substitution for traditional methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.6B
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• pp.1100-1105
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• 2000

The most widely used radar pulse compression technique is correlation processing using Barker code. This technique enhances detection sensitivity but, unfortunately, suffers from the addition of range sidelobes which sometimes will degrade the performance of radar systems. In this paper, our proposed optimal algorithm eliminates the sidelobes at the cost of additional processing and is evaluated in the presence of Doppler shift. We then propose optimal codes with regard to the proposed algorithm and the performance is compared against the traditional correlation processing with Barker codes. The proposed processing using optimal codes will be shown to be superior over the traditional processing in the presence of Doppler shift.

• The KIPS Transactions:PartC
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• v.16C no.3
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• pp.357-362
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• 2009

Summation generator can be easily made as a simple hardware or software and it's period and linear complexity are very high. So it is appropriate to mobile security system for ubiquitous environment. But it showed us the weakness by Golic's correlation attack and Meier's fast correlation attack. In this paper, we proposed a Nonlinear Summation Generator(NSG), which is improved by using LFSR and NFSR(nonlinear feedback shift register), is different from $E_0$ algorithm which use only LFSR in summation generator. It enhanced nonlinearity and is hard to decipher even though the correlation attack or fast correlation attack. We also analyzed the security aspects and the performances for the proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.11 no.3
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• pp.107-115
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• 2006

This paper presents a new class of activation functions for Cascade Correlation learning algorithm, which herein will be called CosGauss function. This function is a cosine modulated gaussian function. In contrast to the sigmoidal, hyperbolic tangent and gaussian functions, more ridges can be obtained by the CosGauss function. Because of the ridges, it is quickly convergent and improves a pattern recognition speed. Consequently it will be able to improve a learning capability. This function was tested with a Cascade Correlation Network on the two spirals problem and results are compared with those obtained with other activation functions.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.5
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• pp.17-24
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• 2009

Zhang et al. proposed a improved fast correlation attack on stream ciphers at SAC'08[8]. This attack is based on the fast correlation attack proposed at Crypto'00 and combined with FWT(fast Walsh transform). Given various attack environments, they presented complexities and success probabilities of the proposed attack algorithm. However, we found that our simulation results of the proposed attack algorithm are different from them presented in [8]. In this paper, we correct results of the proposed attack algorithm by analyzing it theoretically. And we propose a threshold of valid bias.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.12
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• pp.1797-1805
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• 1993

An algorithm for the threshold decision from the maximum mismatching correlation value in a direct-sequence spread-spectrum system is presented. This algorithm is named the TDMMC(Threshold Decision from the Maximum Mismatching Correlation value). The purpose of the algorithm is to set the decision threshold in the system which will provide large probability of signal detection. Using this algorithm, the proper setting of the threshold for various SNRs is possible. An additional block called the Threshold Block is used to improve the system performance. The result from the computer simmulation has shown that appling the TDMMC to the noncoherent DS/SS-CSK system can achieve performance improvement.

• Journal of information and communication convergence engineering
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• v.3 no.3
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• pp.119-121
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• 2005

This paper aims to estimate the delay time of multiple signals in a multi-path environment. It also seeks to carry out a comparative analysis with the existing delay time under the proposed algorithm to develop a new algorithm that applies the space average method in a MUSIC algorithm. Unlike the existing delay time estimation algorithm, the developed algorithm was able to estimate the delay time in 5ns low. Therefore, the algorithm proposed in this paper improved the existing delay time estimated algorithm.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.28A no.5
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• pp.347-354
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• 1991

In this paper, the Automatic Tracking Window(ATW) algorithm is applied to the Generalized Cross-Correlation(GCC) time delay estimation algorithm as a preprocessing. The Linear Prediction(LP) algorithm, which is a pararmetric spectral estimation algorithm, is applied to the time delay estimation. And the ATW, a preprocessing algorithm is applied to this algorithm too. This paper shows that the ATW algorithm attenuates the sidelobes very much and improves the resolution of the timedelay estimation.

• Journal of Communications and Networks
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• v.11 no.6
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• pp.556-563
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• 2009

A side channel analysis is a very efficient attack against small devices such as smart cards and wireless sensor nodes. In this paper, we propose an efficient key detection method using a peak selection algorithm in order to find the advanced encryption standard secret key from electromagnetic signals. The proposed method is applied to a correlation electromagnetic analysis (CEMA) attack against a wireless sensor node. Our approach results in increase in the correlation coefficient in comparison with the general CEMA. The experimental results show that the proposed method can efficiently and reliably uncover the entire 128-bit key with a small number of traces, whereas some extant methods can reveal only partial subkeys by using a large number of traces in the same conditions.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.390-395
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• 2000

We present a fingerprint identification algorithm using the wavelet transform and correlation. The wavelet transform is used because of its simple operation to extract fingerprint minutiaes features for fingerprint classification. We perform the rowwise 1-D wavelet transform for a $256\times256$ fingerprint image to get a $1\times256$ column vector using the Haar wavelet and repeat 1-D wavelet transform for a 1$\times$256 column vector to get a $1\times4$ feature vector. Using PNN(Probabilistic Neural Network), we select the possible candidates from the stored feature vectors for fingerprint images. For those candidates, we compute the correlation between the input binary image and the target binary image to find the most similar fingerprint image. The proposed algorithm may be the key to a low cost fingerprint identification system that can be operated on a small computer because it does not need a large memory size and much computation.