• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.81-84
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• 2000

Cellular automata are discrete dynamical systems whose behaviour is completely specified in terms of a local relation. If cellular automata convergence to fixed points, then it can be used to image processing. From the generalized Potts automata point of view, we propose in this paper a cellular automata technique for reducing image noise. To minimize blurring effect, an algorithm based on neighborhood median computation is Preferred. Experimental results are reported.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10a
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• pp.767-770
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• 2001

Edge detection is one of issues with essential importance in the area of image process. An edge in image is a boundary or contour which a significant change occurs in image intensity. In the paper, we process edge detection algorithms which are based on Potts automata. The dynamical behavior of these automata is completely determined by Lyapunov operators for sequential and parallel update. If Potts Automata convergence to fixed points, then it can be used to image processing. From the generalized Potts automata point of view, we propose a Potts Automata technique for detecting edge. Based on the experimental results we discuss the advantage and efficiency.

• ETRI Journal
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• v.43 no.5
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• pp.787-798
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• 2021

This paper applies learning automata to improve the performance of a Q-learning based random access channel (QL-RACH) scheme in a cellular machine-to-machine (M2M) communication system. A prioritized learning automata QL-RACH (PLA-QL-RACH) access scheme is proposed. The scheme employs a prioritized learning automata technique to improve the throughput performance by minimizing the level of interaction and collision of M2M devices with human-to-human devices sharing the RACH of a cellular system. In addition, this scheme eliminates the excessive punishment suffered by the M2M devices by controlling the administration of a penalty. Simulation results show that the proposed PLA-QL-RACH scheme improves the RACH throughput by approximately 82% and reduces access delay by 79% with faster learning convergence when compared with QL-RACH.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2258-2274
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• 2020

In this paper we first propose a new cryptosystem based on our data hiding scheme (2,9,8) introduced in 2019 with high security, where encrypting and hiding are done at once, the ciphertext does not depend on the input image size as existing hybrid techniques of cryptography and steganography. We then exploit our automata approach presented in 2019 to design two algorithms for exact and approximate pattern matching on secret data encrypted by our cryptosystem. Theoretical analyses remark that these algorithms both have O(n) time complexity in the worst case, where for the approximate algorithm, we assume that it uses ⌈(1-ε)m)⌉ processors, where ε, m and n are the error of our string similarity measure and lengths of the pattern and secret data, respectively. In searchable encryption, our cryptosystem is used by users and our pattern matching algorithms are performed by cloud providers.

• Journal of International Society for Simulation Surgery
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• v.4 no.1
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• pp.21-23
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• 2017

Purpose In this paper, we proposed alternate neighborhood system and reverse spread-direction approach for accurate and fast cellular automata-based image segmentation method. Materials and Methods On the basis of a simple but effective interactive image segmentation technique based on a cellular automaton, we propose an efficient algorithm by using Moore and designed neighborhood system alternately and reversing the direction of the reference pixels for spreading out to the surrounding pixels. Results In our experiments, the GrabCut database were used for evaluation. According to our experimental results, the proposed method allows cellular automata-based image segmentation method to faster while maintaining the segmentation quality. Conclusion Our results proved that proposed method improved accuracy and reduced computation time, and also could be applied to a large range of applications.

• Proceedings of the Korean System Dynamics Society
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• 1999.08a
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• pp.133-157
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• 1999

시스템 다이나믹스는 전통적인 단선론적 인과론을 극복하고 시스템의 동태적 특성을 파악하는데 상당한 공헌을 하였다. 그러나 이러한 시스템의 특성을 방정식에 의존하는 시뮬레이션 기법(Equation-Based Simulation:EBS)을 이용하여 분석하는 경우 방정식으로 묘사하기 어려운 복잡적응시스템(Complex Adaptive System)에서는 한계를 갖고 있다. 따라서 시스템의 동태적 특성을 좀더 정확히 파악을 하기 위해서는 시스템을 구성하는 개체(agent)들의 행동이 시스템 전체에 미치는 영향들을 모형화 함으로써 파악하는 것이 바람직하다고 할 수 있다. 본 연구는 이러한 개체지향 시뮬레이션(Agent-eased Simulation: ABS)의 기법을 복잡성과학의 패러다임을 소개함으로써 그 중요성을 설명하고자 한다. 특히 카오스 이론으로부터 복잡성과학으로의 발전 과정을 개념을 중심으로 논의함으로서 복잡적응시스템의 이해를 돕고자 한다. 또한 ABS가 실제로 전통적인 EBS가 묘사하는 생태계 시스템의 변화를 잘 묘사할 수 있다는 사실을 보여주기 위하여 3개체가 있는 Lotka-Voltera 모형을 Cellular Automata 라는 ABS에 기반 한 시뮬레이션 기법을 활용하여 그 사용가능성을 제시하고자 한다.

• Proceedings of the KSRS Conference
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• 2007.03a
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• pp.55-60
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• 2007

The purpose of this study is to evaluate the temporal land cover change by gradual urbanization of Gyeongan-cheon watershed. This study used the five land use of Landsat TM satellite images(l987, 1991, 2001, 2004) which were classified by maximum likelihood method. The five land use maps examine its accuracy by error matrix and administrative district statistics. This study analyze land use patterns in the past using time.series Landsat satellite images, and predict 2004 year land use using a CA-Markov combined CA(Cellular Automata) and Markov process, and examine its appropriateness. Finally, predict 2030, 2060 year land use maps by CA-Markov model were constructed from the classified images.

• Journal of Computing Science and Engineering
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• v.3 no.2
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• pp.73-87
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• 2009

A hybrid system is a dynamical system in which states can be changed continuously and discretely. Simulation based on numerical methods is the widely used technique for analyzing complicated hybrid systems. Numerical simulation of hybrid systems, however, is subject to two types of numerical errors: truncation error and round-off error. The effect of such errors can make an impossible transition step to become possible during simulation, and thus, to generate a simulation behavior that is not allowed by the model. The possibility of an incorrect simulation behavior reduces con.dence in simulation-based analysis since it is impossible to know whether a particular simulation trace is allowed by the model or not. To address this problem, we define the notion of Instrumented Hybrid Automata (IHA), which considers the effect of accumulated numerical errors on discrete transition steps. We then show how to convert Hybrid Automata (HA) to IRA and prove that every simulation behavior of IHA preserves the discrete transition steps of some behavior in HA; that is, simulation of IHA is sound with respect to HA.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.158-163
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• 1998

This paper is our first attempt to construct a information processing system such as the living creatures' brain based on artificial life technique. In this paper, we propose a method of constructing neural networks using bio-inspired emergent and evolutionary concept, Ontogeny of living things is realized by cellular automata model and Phylogeny that is living things adaptation ability themselves to given environment, are realized by evolutionary algorithms. Proposing evolving cellular automata neural systems are calledin a word ECANS. A basic component of ECANS is 'cell' which is modeled on chaotic neuron with complex characteristics, In our system, the states of cell are classified into eight by method of connection neighborhood cells. When a problem is given, ECANS adapt itself to the problem by evolutionary method. For fixed cells transition rule, the structure of neural network is adapted by change of initial cell' arrangement. This initial cell is to become a network b developmental process. The effectiveness and the capability of proposed scheme are verified by applying it to pattern classification and robot control problem.

• Journal of Advanced Navigation Technology
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• v.18 no.2
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• pp.178-184
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• 2014

CMOS technology based on PCA is very efficient at an implementation of memory or ALU. However, there has been a growing interest in quantum-dot cellular automata (QCA) because of the limitation of CMOS scaling. In this paper, we propose a design of PCA architecture based on QCA. In the proposed PCA design, we utilize D flip-flop and XOR logic gate without wire crossing technique, and design a input and rule control switches. In experiment, we perform the simulation of the proposed PCA architecture by QCADesigner. As the result, we confirm the efficiency the proposed architecture.