• Title/Summary/Keyword: Polynomials

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Design of Optimized pRBFNNs-based Face Recognition Algorithm Using Two-dimensional Image and ASM Algorithm (최적 pRBFNNs 패턴분류기 기반 2차원 영상과 ASM 알고리즘을 이용한 얼굴인식 알고리즘 설계)

  • Oh, Sung-Kwun;Ma, Chang-Min;Yoo, Sung-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.6
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    • pp.749-754
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    • 2011
  • In this study, we propose the design of optimized pRBFNNs-based face recognition system using two-dimensional Image and ASM algorithm. usually the existing 2 dimensional face recognition methods have the effects of the scale change of the image, position variation or the backgrounds of an image. In this paper, the face region information obtained from the detected face region is used for the compensation of these defects. In this paper, we use a CCD camera to obtain a picture frame directly. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. AdaBoost algorithm is used for the detection of face image between face and non-face image area. We can butt up personal profile by extracting the both face contour and shape using ASM(Active Shape Model) and then reduce dimension of image data using PCA. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of RBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to real-time face image database and then demonstrated from viewpoint of the output performance and recognition rate.

Design of Data-centroid Radial Basis Function Neural Network with Extended Polynomial Type and Its Optimization (데이터 중심 다항식 확장형 RBF 신경회로망의 설계 및 최적화)

  • Oh, Sung-Kwun;Kim, Young-Hoon;Park, Ho-Sung;Kim, Jeong-Tae
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.3
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    • pp.639-647
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    • 2011
  • In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

Stereo Vision based on Planar Algebraic Curves (평면대수곡선을 기반으로 한 스테레오 비젼)

  • Ahn, Min-Ho;Lee, Chung-Nim
    • Journal of KIISE:Software and Applications
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    • v.27 no.1
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    • pp.50-61
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    • 2000
  • Recently the stereo vision based on conics has received much attention by many authors. Conics have many features such as their matrix expression, efficient correspondence checking, abundance of conical shapes in real world. Extensions to higher algebraic curves met with limited success. Although irreducible algebraic curves are rather rare in the real world, lines and conics are abundant whose products provide good examples of higher algebraic curves. We consider plane algebraic curves of an arbitrary degree $n{\geq}2$ with a fully calibrated stereo system. We present closed form solutions to both correspondence and reconstruction problems. Let $f_1,\;f_2,\;{\pi}$ be image curves and plane and $VC_P(g)$ the cone with generator (plane) curve g and vertex P. Then the relation $VC_{O1}(f_1)\;=\;VC_{O1}(VC_{O2}(f_2)\;∩\;{\pi})$ gives polynomial equations in the coefficient $d_1,\;d_2,\;d_3$ of the plane ${\pi}$. After some manipulations, we get an extremely simple polynomial equation in a single variable whose unique real positive root plays the key role. It is then followed by evaluating $O(n^2)$ polynomials of a single variable at the root. It is in contrast to the past works which usually involve a simultaneous system of multivariate polynomial equations. We checked our algorithm using synthetic as well as real world images.

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Free Vibration Analysis of Horizontally Curved I-Girder Bridges using the Finite Element Method (유한요소법을 이용한 수평곡선 I형교의 자유진동해석)

  • Yoon, Ki Yong;Kang, Young Jong
    • Journal of Korean Society of Steel Construction
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    • v.10 no.1 s.34
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    • pp.47-61
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    • 1998
  • The behavior of horizontally curved I-girder bridges is complex because the flexural and torsional behavior of curved girders are coupled due to their initial curvature. Also, the behavior is affected by cross beams. To investigate the behavior of horizontally curved I-girder bridges, it is necessary to consider curved girders with cross beams. In order to perform free vibration analyses of horizontally curved I-girder bridges, a finite element formulation is presented here and a finite element analysis program is developed. The formulation that is presented here consists of curved and straight beam elements, including the warping degree of freedom. Based on the theory of thin-walled curved beams, the shape functions of the curved beam elements are derived from homogeneous solutions of the static equilibrium equations. Third-order hermits polynomials are used to form the shape functions of the straight beam elements. In the finite element analysis program, global stiffness and mass matrix are composed, based on the Cartesian coordinate system. The Gupta method is used to efficiently solve the eigenvalue problem. Comparing the results of several examples here with those of previous studies, the formulation presented is verified. The validity of the program developed is shown by comparing results with those analyzed by the shell element.

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Failure Prediction and Behavior of Cut-Slope based on Measured Data (계측결과에 의한 절토사면의 거동 및 파괴예측)

  • Jang, Seo-Yong;Han, Heui-Soo;Kim, Jong-Ryeol;Ma, Bong-Duk
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.10 no.3
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    • pp.165-175
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    • 2006
  • To analyze the deformation and failure of slopes, generally, two types of model, Polynomial model and Growth model, are applied. These two models are focused on the behavior of the slope by time. Therefore, this research is more focused on predicting of slope failure than analyzing the slope behavior by time. Generally, Growth model is used to analyze the soil slope, to the contrary, Polynomial model is used for rock slope. However, 3-degree polynomial($y=ax^3+bx^2+cx+d$) is suggested to combine two models in this research. The main trait of this model is having an asymptote. The fields to adopt this model are Gosujae Danyang(soil slope) and Youngduk slope(rock slope), which are the cut-slope near national road. Data from Gosujae are shown the failure traits of soil slope, to the contrary, those of Youngduk slope are shown the traits of rock slope. From the real-time monitoring data of the slope, 3-degree polynomial is proved as excellent system to analyze the failure and behavior of slope. In case of Polynomial model, even if the order of polynomials is increased, the $R^2$ value and shape of the curve-fitted graph is almost the same.

Characteristic Polynomials of 90/150 CA <10 ⋯ 0> (90/150 CA <10 ⋯ 0>의 특성다항식)

  • Kim, Jin-Gyoung;Cho, Sung-Jin;Choi, Un-Sook;Kim, Han-Doo;Kang, Sung-Won
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.6
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    • pp.1301-1308
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    • 2018
  • 90/150 CA which are used as key generators of the cipher system have more randomness than LFSRs, but synthesis methods of 90/150 CA are difficult. Therefore, 90/150 CA synthesis methods have been studied by many researchers. In order to synthesize a suitable CA, the analysis of the characteristic polynomial of 90/150 CA should be preceded. In general, the characteristic of polynomial ${\Delta}_n$ of n cell 90/150 CA is obtained by using ${\Delta}_{n-1}$ and ${\Delta}_{n-2}$. Choi et al. analyzed $H_{2^n}(x)$ and $H_{2^n-1}(x)$, where $H_k(x)$ is the characteristic polynomial of k cell 90/150 CA with state transition rule <$10{\cdots}0$>. In this paper, we propose an efficient method to obtain $H_n(x)$ from $H_{n-1}(x)$ and an efficient algorithm to obtain $H_{2^n+i}(x)$ and $H_{2^n-i}(x)$ ($1{\leq}i{\leq}2^{n-1}$) from $H_{2^n}(x)$ by using this method.

Stress Intensity Factor of Cracked Plates with Bonded Composite Patch by p-Convergence Based Laminated Plate Theory (p-수렴 적층 평판이론에 의한 균열판의 팻취보강후 응력확대계수 산정)

  • Woo, Kwang-Sung;Han, Sang-Hyun;Yang, Seung-Ho
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.5A
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    • pp.649-656
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    • 2008
  • The enhancement of the service life of damaged or cracked structures is a major issue for researchers and engineers. The hierarchic void element based on the integrals of Legendre polynomials is used to characterize the fracture behaviour of unpatched crack as well as repaired crack with bonded composite patches by computing the stress intensity factors and stress contours at the crack tip. Since the equivalent single layer approach is adopted in this study, the proposed element is necessary to represent a discontinuous crack part as a continuum body with zero stiffness. Thus the aspect ratio of this element to represent the crack should be extremely slender. The sensitivity of numerical solution with respect to energy release rate, displacement and stress has been tested to show the robustness of zero stiffness element as the aspect ratio is increased up to 2000. The stiffness derivative method and displacement extrapolation method have been applied to calculate the stress intensity factors of Mode I problem. It is noted that the proposed hierarchical void element can be one of alternatives to analyze the patched crack problems.

State-Space Equation Model for Motion Analysis of Floating Structures Using System-Identification Methods (부유식 구조체 운동 해석을 위한 시스템 식별 방법을 이용한 상태공간방정식 모델)

  • Jun-Sik Seong;Wonsuk Park
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.37 no.2
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    • pp.85-93
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    • 2024
  • In this paper, we propose a method for establishing a state-space equation model for the motion analysis of floating structures subjected to wave loads, by applying system-identification techniques. Traditionally, the motion of floating structures has been analyzed in the time domain by integrating the Cummins equation over time, which utilizes a convolution integral term to account for the effects of the retardation function. State-space equation models have been studied as a way to efficiently solve floating-motion equations in the time domain. The proposed approach outlines a procedure to derive the target transfer function for the load-displacement input/output relationship in the frequency domain and subsequently determine the state-space equation that closely approximates it. To obtain the state-space equation, the method employs the N4SID system-identification method and an optimization approach that treats the coefficients of the numerator and denominator polynomials as design variables. To illustrate the effectiveness of the proposed method, we applied it to the analysis of a single-degree-of-freedom model and the motion of a six-degree-of-freedom barge. Our findings demonstrate that the presented state-space equation model aligns well with the existing analysis results in both the frequency and time domains. Notably, the method ensures computational accuracy in the time-domain analysis while significantly reducing the calculation time.

A Multi-Compartment Secret Sharing Method (다중 컴파트먼트 비밀공유 기법)

  • Cheolhoon Choi;Minsoo Ryu
    • The Transactions of the Korea Information Processing Society
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    • v.13 no.2
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    • pp.34-40
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    • 2024
  • Secret sharing is a cryptographic technique that involves dividing a secret or a piece of sensitive information into multiple shares or parts, which can significantly increase the confidentiality of a secret. There has been a lot of research on secret sharing for different contexts or situations. Tassa's conjunctive secret sharing method employs polynomial derivatives to facilitate hierarchical secret sharing. However, the use of derivatives introduces several limitations in hierarchical secret sharing. Firstly, only a single group of participants can be created at each level due to the shares being generated from a sole derivative. Secondly, the method can only reconstruct a secret through conjunction, thereby restricting the specification of arbitrary secret reconstruction conditions. Thirdly, Birkhoff interpolation is required, adding complexity compared to the more accessible Lagrange interpolation used in polynomial-based secret sharing. This paper introduces the multi-compartment secret sharing method as a generalization of the conjunctive hierarchical secret sharing. Our proposed method first encrypts a secret using external groups' shares and then generates internal shares for each group by embedding the encrypted secret value in a polynomial. While the polynomial can be reconstructed with the internal shares, the polynomial just provides the encrypted secret, requiring external shares for decryption. This approach enables the creation of multiple participant groups at a single level. It supports the implementation of arbitrary secret reconstruction conditions, as well as conjunction. Furthermore, the use of polynomials allows the application of Lagrange interpolation.

Experimental Design of S box and G function strong with attacks in SEED-type cipher (SEED 형식 암호에서 공격에 강한 S 박스와 G 함수의 실험적 설계)

  • 박창수;송홍복;조경연
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.8 no.1
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    • pp.123-136
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    • 2004
  • In this paper, complexity and regularity of polynomial multiplication over $GF({2^n})$ are defined by using Hamming weight of rows and columns of the matrix ever GF(2) which represents polynomial multiplication. It is shown experimentally that in order to construct the block cipher robust against differential cryptanalysis, polynomial multiplication of substitution layer and the permutation layer should have high complexity and high regularity. With result of the experiment, a way of constituting S box and G function is suggested in the block cipher whose structure is similar to SEED, which is KOREA standard of 128-bit block cipher. S box can be formed with a nonlinear function and an affine transform. Nonlinear function must be strong with differential attack and linear attack, and it consists of an inverse number over $GF({2^8})$ which has neither a fixed pout, whose input and output are the same except 0 and 1, nor an opposite fixed number, whose output is one`s complement of the input. Affine transform can be constituted so that the input/output correlation can be the lowest and there can be no fixed point or opposite fixed point. G function undergoes linear transform with 4 S-box outputs using the matrix of 4${\times}$4 over $GF({2^8})$. The components in the matrix of linear transformation have high complexity and high regularity. Furthermore, G function can be constituted so that MDS(Maximum Distance Separable) code can be formed, SAC(Strict Avalanche Criterion) can be met, and there can be no weak input where a fixed point an opposite fixed point, and output can be two`s complement of input. The primitive polynomials of nonlinear function affine transform and linear transformation are different each other. The S box and G function suggested in this paper can be used as a constituent of the block cipher with high security, in that they are strong with differential attack and linear attack with no weak input and they are excellent at diffusion.