• Title/Summary/Keyword: chaotic

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An Analysis System for Whole Genomic Sequence Using String B-Tree (스트링 B-트리를 이용한 게놈 서열 분석 시스템)

  • Choe, Jeong-Hyeon;Jo, Hwan-Gyu
    • The KIPS Transactions:PartA
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    • v.8A no.4
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    • pp.509-516
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    • 2001
  • As results of many genome projects, genomic sequences of many organisms are revealed. Various methods such as global alignment, local alignment are used to analyze the sequences of the organisms, and k -mer analysis is one of the methods for analyzing the genomic sequences. The k -mer analysis explores the frequencies of all k-mers or the symmetry of them where the k -mer is the sequenced base with the length of k. However, existing on-memory algorithms are not applicable to the k -mer analysis because a whole genomic sequence is usually a large text. Therefore, efficient data structures and algorithms are needed. String B-tree is a good data structure that supports external memory and fits into pattern matching. In this paper, we improve the string B-tree in order to efficiently apply the data structure to k -mer analysis, and the results of k -mer analysis for C. elegans and other 30 genomic sequences are shown. We present a visualization system which enables users to investigate the distribution and symmetry of the frequencies of all k -mers using CGR (Chaotic Game Representation). We also describe the method to find the signature which is the part of the sequence that is similar to the whole genomic sequence.

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Multi-scale Progressive Fatigue Damage Model for Unidirectional Laminates with the Effect of Interfacial Debonding (경계면 손상을 고려한 적층복합재료에 대한 멀티스케일 피로 손상 모델)

  • Dongwon Ha;Jeong Hwan Kim;Taeri Kim;Young Sik Joo;Gun Jin Yun
    • Composites Research
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    • v.36 no.1
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    • pp.16-24
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    • 2023
  • This paper presents a multi-scale progressive fatigue damage model incorporating the model for interfacial debonding between fibers and matrix. The micromechanics model for the progressive interface debonding was adopted, which defined the four different interface phases: (1) perfectly bonded fibers; (2) mild imperfect interface; (3) severe imperfect interface; and (4) completely debonded fibers. As the number of cycles increases, the progressive transition from the perfectly bonded state to the completely debonded fiber state occurs. Eshelby's tensor for each imperfect state is calculated by the linear spring model for a damaged interface, and effective elastic properties are obtained using the multi-phase homogenization method. The fatigue damage evolution formulas for fiber, matrix and interface were proposed to demonstrate the fatigue behavior of CFRP laminates under cyclic loading. The material parameters for the fiber/matrix fatigue damage were characterized using the chaotic firefly algorithm. The model was implemented into the UMAT subroutine of ABAQUS, and successfully validated with flat-bar UD laminate specimens ([0]8,[90]8, [30]16) of AS4/3501-6 graphite/epoxy composite.

Detecting Nonlinearity of Hydrologic Time Series by BDS Statistic and DVS Algorithm (BDS 통계와 DVS 알고리즘을 이용한 수문시계열의 비선형성 분석)

  • Choi, Kang Soo;Kyoung, Min Soo;Kim, Soo Jun;Kim, Hung Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.2B
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    • pp.163-171
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    • 2009
  • Classical linear models have been generally used to analyze and forecast hydrologic time series. However, there is growing evidence of nonlinear structure in natural phenomena and hydrologic time series associated with their patterns and fluctuations. Therefore, the classical linear techniques for time series analysis and forecasting may not be appropriate for nonlinear processes. In recent, the BDS (Brock-Dechert-Scheinkman) statistic instead of conventional techniques has been used for detecting nonlinearity of time series. The BDS statistic was derived from the statistical properties of the correlation integral which is used to analyze chaotic system and has been effectively used for distinguishing nonlinear structure in dynamic system from random structures. DVS (Deterministic Versus Stochastic) algorithm has been used for detecting chaos and stochastic systems and for forecasting of chaotic system. This study showed the DVS algorithm can be also used for detecting nonlinearity of the time series. In this study, the stochastic and hydrologic time series are analyzed to detect their nonlinearity. The linear and nonlinear stochastic time series generated from ARMA and TAR (Threshold Auto Regressive) models, a daily streamflow at St. Johns river near Cocoa, Florida, USA and Great Salt Lake Volume (GSL) data, Utah, USA are analyzed, daily inflow series of Soyang dam and the results are compared. The results showed the BDS statistic is a powerful tool for distinguishing between linearity and nonlinearity of the time series and DVS plot can be also effectively used for distinguishing the nonlinearity of the time series.

The Target Searching Method in the Chaotic Mobile Robot Embedding BVP Model (BVP 모델을 내장한 카오스 로봇에서의 목표물 탐색)

  • Bae, Young-Chul;Kim, Yi-Gon;Koo, Young-Duk
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.2
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    • pp.259-264
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    • 2007
  • In this paper, we composed chaos mobile robot by embedding many type of chaos circuit including Arnold Equation and Chua's Equation and proposed method of evaluation of obstacles when it meets or approaches an obstacle while the mobile robot searches an any plane with chaos trajectory and method of concentrating search when it faces target and verified these results. For obstacles avoidance, we developed algorithm that evades an obstacles with chaos trajectory by assuming fixed obstacle, obstacles using VDP model, hidden obstacles using BVP model as obstacles and for searching an object, we developed algorithm of searching with a chaos trajectory by assuming BVP model as an object, verified the results and confirmed reasonability of them.

A Semantic Analysis of the Indeterminacy in Contemporary Fashion - Focusing on Fashion Since 2000 - (현대 패션에 나타난 불확정성의 의미해석 - 2000년대 이후 패션을 중심으로 -)

  • Hwang, Hye-Jin;Kim, Min-Ja
    • Journal of the Korean Society of Costume
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    • v.62 no.5
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    • pp.1-15
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    • 2012
  • In a fast changing postmodern society, contemporary fashion is becoming more complicated and ambiguous along with other genres of art than ever before. This phenomenon reigning as a sociocultural paradigm can be defined as 'indeterminacy' and it means 'undecidability'. The purpose of this study is to clarify and analyze the indeterminate characteristics of contemporary fashion reviewing the theoretical background and the architectural formativeness as a comparative research. The core idea of deconstructivism dismantles a causal relationship between function and form in fashion and the conventional notion about clothes. Complexity theory, which is the study of chaotic dynamical systems, suggests the creative idea and concept of infinite possibilities on a formative method. Meanwhile, catastrophe theory of discontinuous change can be used as interpretative strategies for the process of deconstruction and reconstruction. As a result of this study, the indeterminacy of fashion can be analyzed into five semantic categories: irregularity, immateriality, randomness, complexity and changeability. The intrinsic value of the indeterminacy in contemporary fashion is the interaction with a sociocultural ideology and a technological environment as well as an expansion of formative expression. To conclude, it can be said that the indeterminacy in fashion is a new interpretation of the relationship among body and space, clothes and society.

Prediction of Wind Power by Chaos and BP Artificial Neural Networks Approach Based on Genetic Algorithm

  • Huang, Dai-Zheng;Gong, Ren-Xi;Gong, Shu
    • Journal of Electrical Engineering and Technology
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    • v.10 no.1
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    • pp.41-46
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    • 2015
  • It is very important to make accurate forecast of wind power because of its indispensable requirement for power system stable operation. The research is to predict wind power by chaos and BP artificial neural networks (CBPANNs) method based on genetic algorithm, and to evaluate feasibility of the method of predicting wind power. A description of the method is performed. Firstly, a calculation of the largest Lyapunov exponent of the time series of wind power and a judgment of whether wind power has chaotic behavior are made. Secondly, phase space of the time series is reconstructed. Finally, the prediction model is constructed based on the best embedding dimension and best delay time to approximate the uncertain function by which the wind power is forecasted. And then an optimization of the weights and thresholds of the model is conducted by genetic algorithm (GA). And a simulation of the method and an evaluation of its effectiveness are performed. The results show that the proposed method has more accuracy than that of BP artificial neural networks (BP-ANNs).

Multi-objective optimization of foundation using global-local gravitational search algorithm

  • Khajehzadeh, Mohammad;Taha, Mohd Raihan;Eslami, Mahdiyeh
    • Structural Engineering and Mechanics
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    • v.50 no.3
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    • pp.257-273
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    • 2014
  • This paper introduces a novel optimization technique based on gravitational search algorithm (GSA) for numerical optimization and multi-objective optimization of foundation. In the proposed method, a chaotic time varying system is applied into the position updating equation to increase the global exploration ability and accurate local exploitation of the original algorithm. The new algorithm called global-local GSA (GLGSA) is applied for optimization of some well-known mathematical benchmark functions as well as two design examples of spread foundation. In the foundation optimization, two objective functions include total cost and $CO_2$ emissions of the foundation subjected to geotechnical and structural requirements are considered. From environmental point of view, minimization of embedded $CO_2$ emissions that quantifies the total amount of carbon dioxide emissions resulting from the use of materials seems necessary to include in the design criteria. The experimental results demonstrate that, the proposed GLGSA remarkably improves the accuracy, stability and efficiency of the original algorithm.

On the Dynamics of Multi-Dimensional Lotka-Volterra Equations

  • Abe, Jun;Matsuoka, Taiju;Kunimatsu, Noboru
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1623-1628
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    • 2004
  • In the 3-dimensional cyclic Lotka-Volterra equations, we show the solution on the invariant hyperplane. In addition, we show the existence of the invariant hyperplane by the center manifold theorem under the some conditions. With this result, we can lead the hyperplane of the n-dimensional cyclic Lotka-Volterra equaions. In other section, we study the 3- or 4-dimensional Hamiltonian Lotka-Volterra equations which satisfy the Jacobi identity. We analyze the solution of the Hamiltonian Lotka- Volterra equations with the functions called the split Liapunov functions by [4], [5] since they provide the Liapunov functions for each region separated by the invariant hyperplane. In the cyclic Lotka-Volterra equations, the role of the Liapunov functions is the same in the odd and even dimension. However, in the Hamiltonian Lotka-Volterra equations, we can show the difference of the role of the Liapunov function between the odd and the even dimension by the numerical calculation. In this paper, we regard the invariant hyperplane as the important item to analyze the motion of Lotka-Volterra equations and occur the chaotic orbit. Furtheremore, an example of the asymptoticaly stable and stable solution of the 3-dimensional cyclic Lotka-Volterra equations, 3- and 4-dimensional Hamiltonian equations are shown.

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Dynamic System Identification Using a Recurrent Compensatory Fuzzy Neural Network

  • Lee, Chi-Yung;Lin, Cheng-Jian;Chen, Cheng-Hung;Chang, Chun-Lung
    • International Journal of Control, Automation, and Systems
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    • v.6 no.5
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    • pp.755-766
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    • 2008
  • This study presents a recurrent compensatory fuzzy neural network (RCFNN) for dynamic system identification. The proposed RCFNN uses a compensatory fuzzy reasoning method, and has feedback connections added to the rule layer of the RCFNN. The compensatory fuzzy reasoning method can make the fuzzy logic system more effective, and the additional feedback connections can solve temporal problems as well. Moreover, an online learning algorithm is demonstrated to automatically construct the RCFNN. The RCFNN initially contains no rules. The rules are created and adapted as online learning proceeds via simultaneous structure and parameter learning. Structure learning is based on the measure of degree and parameter learning is based on the gradient descent algorithm. The simulation results from identifying dynamic systems demonstrate that the convergence speed of the proposed method exceeds that of conventional methods. Moreover, the number of adjustable parameters of the proposed method is less than the other recurrent methods.

A Provable One-way Authentication Key Agreement Scheme with User Anonymity for Multi-server Environment

  • Zhu, Hongfeng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.2
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    • pp.811-829
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    • 2015
  • One-way authenticated key agreement protocols, aiming at solving the problems to establish secure communications over public insecure networks, can achieve one-way authentication of communicating entities for giving a specific user strong anonymity and confidentiality of transmitted data. Public Key Infrastructure can design one-way authenticated key agreement protocols, but it will consume a large amount of computation. Because one-way authenticated key agreement protocols mainly concern on authentication and key agreement, we adopt multi-server architecture to realize these goals. About multi-server architecture, which allow the user to register at the registration center (RC) once and can access all the permitted services provided by the eligible servers. The combination of above-mentioned ideas can lead to a high-practical scheme in the universal client/server architecture. Based on these motivations, the paper firstly proposed a new one-way authenticated key agreement scheme based on multi-server architecture. Compared with the related literatures recently, our proposed scheme can not only own high efficiency and unique functionality, but is also robust to various attacks and achieves perfect forward secrecy. Finally, we give the security proof and the efficiency analysis of our proposed scheme.