• Title/Summary/Keyword: traditional algorithms

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An Algorithm for Detecting Leak of Defaced Confidential Information Based on SVDD (SVDD 기반 중요문서 변조 유출 탐지 알고리즘)

  • Ghil, Ji-Ho;Nam, Ki-Hyo;Kang, Hyung-Seok;Kim, Seong-In
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.20 no.1
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    • pp.105-111
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    • 2010
  • This paper proposes the algorithm which addresses the problem of detecting leak of defaced confidential documents from original confidential document. Generally, a confidential document is defaced into various forms by insiders and then they are trying to leak these defaced documents to outside. Traditional algorithms detecting leak of documents have low accuracy because they are based on similarity of two documents, which do not reflect various forms of defaced documents in detection. In order to overcome this problem, this paper proposes a novel v-SVDD algorithm which is based on SVDD, the novelty detection algorithm. The result of experiment shows that there is significant improvement m the accuracy of the v-SVDD in comparison with the traditional algorithms.

A Color Flame Region Segmentation Method Using Temperature Distribution Characteristics of Flame (화염의 온도 분포 특성을 이용한 컬러화염 영역분할 방법)

  • Lee, Hyun-Sul;Kim, Won-Ho
    • Journal of Satellite, Information and Communications
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    • v.9 no.2
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    • pp.33-37
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    • 2014
  • This paper propose a method to sort flame regions and non-flame regions in a color image based on temperature Characteristics of flame. The traditional algorithms simply detect flame regions those are colored between yellow and red and there are lot of false detection in this method. But the colors of real flame are fallen between white and red and flame color variation over the flame. In this paper, it reduce false detection by separating colors according to temperature Characteristics of flame. The proposed method firstly finds a color model to express the temperature Characteristics of fire and then the color model is non-linearly quantized based on color values and analyzed using histogram and finally detect the candidate flame regions. The proposed method has 71.8% of matching rate and if it is compared with non-matching rate of traditional algorithms, the non-matching rate is improved by 27 times than others.

A Study of the Representation and Algorithms of Western Mathematics Reflected on the Algebra Domains of Chosun-Sanhak in the 18th Century (18세기 조선산학서의 대수 영역에 나타난 서양수학 표현 및 계산법 연구)

  • Choi, Eunah
    • Journal of the Korean School Mathematics Society
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    • v.23 no.1
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    • pp.25-44
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    • 2020
  • This study investigated the representation and algorithms of western mathematics reflected on the algebra domains of Chosun-Sanhak in the 18th century. I also analyzed the co-occurrences and replacement phenomenon between western algorithms and traditional algorithms. For this purpose, I analyzed nine Chosun mathematics books in the 18th century, including Gusuryak and Gosasibijip. The results of this study are as follows. First, I identified the process of changing to a calculation by writing of western mathematics, from traditional four arithmetical operations using Sandae and the formalized explanation for the proportional concept and proportional expression. Second, I observed the gradual formalization of mathematical representation of the solution for a simultaneous linear equation. Lastly, I identified the change of the solution for square root from traditional Gaebangsul and Jeungseunggaebangbeop to a calculation by the writing of western mathematics.

A NEW ALGORITHM OF EVOLVING ARTIFICIAL NEURAL NETWORKS VIA GENE EXPRESSION PROGRAMMING

  • Li, Kangshun;Li, Yuanxiang;Mo, Haifang;Chen, Zhangxin
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.9 no.2
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    • pp.83-89
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    • 2005
  • In this paper a new algorithm of learning and evolving artificial neural networks using gene expression programming (GEP) is presented. Compared with other traditional algorithms, this new algorithm has more advantages in self-learning and self-organizing, and can find optimal solutions of artificial neural networks more efficiently and elegantly. Simulation experiments show that the algorithm of evolving weights or thresholds can easily find the perfect architecture of artificial neural networks, and obviously improves previous traditional evolving methods of artificial neural networks because the GEP algorithm imitates the evolution of the natural neural system of biology according to genotype schemes of biology to crossover and mutate the genes or chromosomes to generate the next generation, and the optimal architecture of artificial neural networks with evolved weights or thresholds is finally achieved.

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Sparse Representation Learning of Kernel Space Using the Kernel Relaxation Procedure (커널 이완절차에 의한 커널 공간의 저밀도 표현 학습)

  • 류재홍;정종철
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.60-64
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    • 2001
  • In this paper, a new learning methodology for Kernel Methods is suggested that results in a sparse representation of kernel space from the training patterns for classification problems. Among the traditional algorithms of linear discriminant function(perceptron, relaxation, LMS(least mean squared), pseudoinverse), this paper shows that the relaxation procedure can obtain the maximum margin separating hyperplane of linearly separable pattern classification problem as SVM(Support Vector Machine) classifier does. The original relaxation method gives only the necessary condition of SV patterns. We suggest the sufficient condition to identify the SV patterns in the learning epochs. Experiment results show the new methods have the higher or equivalent performance compared to the conventional approach.

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Half-pel Accuracy Motion Estimation Algorithm using Selective Interpolation in the Wavelet Domain (웨이블릿 영역에서의 선택적인 보간에 의한 반화소 단위 움직임 추정)

  • 이경환;정영훈;황희철
    • Journal of Korea Multimedia Society
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    • v.6 no.1
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    • pp.40-47
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    • 2003
  • In this paper, we propose a new method for reducing the computational overhead of fine-to-coarse multi-resolution motion estimation (MRME) at the finest resolution level by searching for the region to consider motion vectors of the coarsest resolution subband. At this time, if half-pel accuracy motion estimation (HPAME) is used in the baseband where influence a lot of effect to the reconstructed image, we can have the motion vector exactly But, this method causes to higher computational overhead. So we suggest the method to the computational overhead by using selective interpolation. Experimental results show that the proposed algorithm gives better results than the traditional algorithms from image quality.

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Robust Multidimensional Scaling for Multi-robot Localization (멀티로봇 위치 인식을 위한 강화 다차원 척도법)

  • Je, Hong-Mo;Kim, Dai-Jin
    • The Journal of Korea Robotics Society
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    • v.3 no.2
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    • pp.117-122
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    • 2008
  • This paper presents a multi-robot localization based on multidimensional scaling (MDS) in spite of the existence of incomplete and noisy data. While the traditional algorithms for MDS work on the full-rank distance matrix, there might be many missing data in the real world due to occlusions. Moreover, it has no considerations to dealing with the uncertainty due to noisy observations. We propose a robust MDS to handle both the incomplete and noisy data, which is applied to solve the multi-robot localization problem. To deal with the incomplete data, we use the Nystr$\ddot{o}$m approximation which approximates the full distance matrix. To deal with the uncertainty, we formulate a Bayesian framework for MDS which finds the posterior of coordinates of objects by means of statistical inference. We not only verify the performance of MDS-based multi-robot localization by computer simulations, but also implement a real world localization of multi-robot team. Using extensive empirical results, we show that the accuracy of the proposed method is almost similar to that of Monte Carlo Localization(MCL).

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An Adaptive Web Caching Method based on the Heterogeneity of Web Object (웹 객체 이질성 기반의 적응형 웹캐싱 기법)

  • Ko, Il-Suk;Na, Yun-Ji;Leem, Chun-Seong
    • Proceedings of the Korea Information Processing Society Conference
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    • pp.1379-1382
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    • 2004
  • The use of a cache for storing and processing of Web objects is becoming larger. Also, many studies on the efficient management of the storing scope of caches are being done. Web caching algorithms have many differences from traditional algorithms. Particularly, heterogeneity of Web objects that are processing units of Web caching, and a variation of Web object reference characteristic with time are the important causes of the decrease the performance of existing algorithms. In this study, we proposed the new web-caching algorithm. A heterogeneity variation of an object can be reduced as the proposed method dividedly managing Web objects and a cache scope with heterogeneity, and it is adaptively reflecting a variation of object reference characteristics with the flowing of time. In the experiments, we verified that the performance of the proposed method was more improved than existing algorithms through the two experiment models which considered heterogeneity of an object.

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A Study on Dijkstra Algorithm in Crossroad Including Left-turn Restriction, U-turn, and P-turn (교차로에서의 좌회전 금지, U-turn, P-turn을 고려한 개선된 Dijkstra Algorithm에 관한 연구)

  • Kim, Sung-Soo;Jun, Young-Joo;Cha, Young-Min
    • Journal of Industrial Technology
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    • v.21 no.A
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    • pp.231-240
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    • 2001
  • U-turn and P-turn as well as left-turn restriction exist in real traffic network. the optimal route should be selected for considering these using shortest path algorithms. But, the traditional algorithms have some limitations to use for considering there. The objective of this paper is to modify Dijkstra algorithm in order to find the optimal path in real traffic network. The continuous three nodes are used to check turn-restrictions and exclude these from and optimal path. A virtual connection is used to consider U-turn and P-turn.

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An Efficient Search Method for High Confidence Association Rules Using CP(Confidence Pattern)-Tree Structure (CP-Tree구조를 이용한 높은 신뢰도를 갖는 연관 규칙의 효율적 탐색 방법)

  • 송한규;김재련
    • Journal of the Society of Korea Industrial and Systems Engineering
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    • v.25 no.1
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    • pp.1-8
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    • 2002
  • The traditional approaches of association rule mining have relied on high support condition to find interesting rules. However, in some application such as analyzing the web page link and discovering some unusual combinations of some factors that have always caused some disease, we are interested in rules with high confidence that have very low support or need not have high support. In these cases, the traditional algorithms are not suitable since it relies on first satisfying high support. In this paper, we propose a new model, CP(Confidence Pattern)-Tree, to identify high confidence rule between 2-items without support constraint. constraint. In addition, we discuss confidence association rule between two more items without support constraint.