• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.11
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• pp.4153-4169
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• 2014

To recognize F5-like (such as F5 and nsF5) steganographic algorithm from multi-class stego images, a recognition algorithm based on the identifiable statistical feature (IDSF) of F5-like steganography is proposed in this paper. First, this paper analyzes the special modification ways of F5-like steganography to image data, as well as the special changes of statistical properties of image data caused by the modifications. And then, by constructing appropriate feature extraction sources, the IDSF of F5-like steganography distinguished from others is extracted. Lastly, based on the extracted IDSFs and combined with the training of SVM (Support Vector Machine) classifier, a recognition algorithm is presented to recognize F5-like stego images from images set consisting of a large number of multi-class stego images. A series of experimental results based on the detection of five types of typical JPEG steganography (namely F5, nsF5, JSteg, Steghide and Outguess) indicate that, the proposed algorithm can distinguish F5-like stego images reliably from multi-class stego images generated by the steganography mentioned above. Furthermore, even if the types of some detected stego images are unknown, the proposed algorithm can still recognize F5-like stego images correctly with high accuracy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.177-183
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• 2022

There is no known polynomial time algorithm for QAP that is a NP-complete problem. This paper suggests O(n²) polynomial time algorithm for random type quadratic assignment problem (QAP). The proposed algorithm suggests incremental augmenting matching strategy that is to set the matching set M={(l_i,f_j)} from l_i with minimum sum of distance in location matrix L and f_j with maximum sum of quantity in facility matrix F, and incremental augmenting of matching set M from M to l_i with minimum sum of distance and to f_j with maximum sum of quantity. Finally, this algorithm performs swap strategy that is to reflect the complex correlations of distances in locations and quantities in facilities. For the experimental data, this algorithm, in spite of O(n²) polynomial time algorithm, can be improve the solution than genetic algorithm a kind of metaheuristic method.

• ETRI Journal
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• v.41 no.3
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• pp.348-357
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• 2019

Fog radio access network (F-RAN) architectures provide markedly improved performance compared to conventional approaches. In this paper, an efficient genetic algorithm-based content distribution scheme is proposed that improves the throughput and reduces the transmission delay of a F-RAN. First, an F-RAN system model is presented that includes a certain number of randomly distributed fog access points (F-APs) that cache popular content from cloud and other sources. Second, the problem of efficient content distribution in F-RANs is described. Third, the details of the proposed optimal genetic algorithm-based content distribution scheme are presented. Finally, simulation results are presented that show the performance of the proposed algorithm rapidly approaches the optimal throughput. When compared with the performance of existing random and exhaustive algorithms, that of the proposed method is demonstrably superior.

• The KIPS Transactions:PartB
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• v.16B no.3
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• pp.233-238
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• 2009

This paper presents an approach to the classifications of small size document using the instance-based feature filtering Relief-F algorithm. In the document classifications, we have not always good classification performances of small size document included a few features. Because total number of feature in the document set is large, but feature count of each document is very small relatively, so the similarities between documents are very low when we use general assessment of similarity and classifiers. Specially, in the cases of the classification of web document in the directory service and the classification of the sectors that cannot connect with the original file after recovery hard-disk, we have not good classification performances. Thus, we propose the Extended Relief-F(ERelief-F) algorithm using instance-based feature filtering algorithm Relief-F to solve problems of Relief-F as preprocess of classification. For the performance comparison, we tested information gain, odds ratio and Relief-F for feature filtering and getting those feature values, and used kNN and SVM classifiers. In the experimental results, the Extended Relief-F(ERelief-F) algorithm, compared with the others, performed best for all of the datasets and reduced many irrelevant features from document sets.

• Journal of applied mathematics & informatics
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• v.12 no.1_2
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• pp.1-20
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• 2003

A modified ABS algorithm for solving a class of singular non-linear systems, $F(x) = 0, $F\;\in \;R^n$, constructed by combining the discreted ABS algorithm and a method of Hoy and Schwetlick (1990), is presented. The second differential operation of F at a point is not required to be calculated directly in this algorithm. Q-quadratic convergence of this algorithm is given.

• Journal of applied mathematics & informatics
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• v.9 no.1
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• pp.167-183
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• 2002

A modified discretization ABS algorithm for solving a class of singular nonlinear systems, F($\chi$)=0, where $\chi$, F $\in$ $R^n$, is presented, constructed by combining a discretization ABS algorithm arid a method of Hoy and Schwetlick (1990). The second order differential operation of F at a point is not required to be calculated directly in this algorithm. Q-quadratic convergence of this algorithm is given.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.40-48
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• 2002

Three-Dimensional scene reconstruction from images acquired with different viewpoints is possible as estimating Fundamental matrix(F-matrix) that indicates the epipolar geometry of two images. Correspondence points required to calculate F-matrix of two images include noise such as miss matches, so generally it is hard to calculate F-matrix accurately. In this paper, we classify noise into two types; outlier and minute noise. we propose SSOR algorithm that estimate F-matrix effectively. SSOR algorithm is rejecting outlier step by step in a noise environment. To evaluate the performance of proposed algorithm we simulated with synthetic images and real images. As a result of simulation we show that proposed algorithm is better than conventional algorithms.

• Journal of applied mathematics & informatics
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• v.31 no.3_4
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• pp.565-575
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• 2013

Let H be a real Hilbert space and let T : H ${\rightarrow}$ H be a Lipschitz pseudocontractive mapping. We introduce a modified Ishikawa iterative algorithm and prove that if $F(T)=\{x{\in}H:Tx=x\}{\neq}{\emptyset}$, then our proposed iterative algorithm converges strongly to a fixed point of T. No compactness assumption is imposed on T and no further requirement is imposed on F(T).

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.5_6
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• pp.187-194
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• 2007

A local alignment algorithm does comparing two strings and finding a substring pair with size l and similarity s. To find a pair with both sufficient size and high similarity, existing normalization approaches maximize the ratio of the similarity to the size. In this paper, we introduce normalization by functions that maximizes f(s)/g(l), where f and g are non-decreasing functions. These functions, f and g, are determined by experiments comparing DNA sequences. In the experiments, our normalization by functions finds appropriate local alignments. For the previous algorithm, which evaluates the similarity by using the longest common subsequence, we show that the algorithm can also maximize the score normalized by functions, f(s)/g(l) without loss of time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.9
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• pp.759-764
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• 2013

We present a square root algorithm in $F_q$ which generalizes Atkin's square root algorithm [9] for finite field $F_q$ of q elements where $q{\equiv}5$ (mod 8) and Kong et al.'s algorithm [11] for the case $q{\equiv}9$ (mod 16). Our algorithm precomputes ${\xi}$ a primitive $2^s$-th root of unity where s is the largest positive integer satisfying $2^s|q-1$, and is applicable for the cases when s is small. The proposed algorithm requires one exponentiation for square root computation and is favorably compared with the algorithms of Atkin, M$\ddot{u}$ller and Kong et al.