• 한국농공학회논문집
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• 제46권7호
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• pp.23-32
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• 2004

A spatial simulation model for rural and urban sprawl phenomena was developed with GIS and cellular automata techniques. The model finds out built-up areas invading toward rural areas required for development of existing urban area. Probability of land use change for optimizing the development area was determined using a land suitability analysis method interfaced with GIS methods, based on several criteria in terms of geographic and accessibility factors such as slope of land and distance from city center. Weighting values of the criteria were quantified by an analytic hierarchy process method. For model applicability test, the parameters of criteria were calibrated based on the changes in time series land use data of the test city for 1986, 1996, and 2000, which were classified by remote sensing techniques. Simulated and observed areas in land use maps for city shape of 1996 showed good similarities with each other through a morphology verification method. The model enabled us to evaluate the spatial expansion phenomena of cities considering boundary conditions, and also to simulate land use planning for rural areas in urban fringe.

• International Journal of Precision Engineering and Manufacturing
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• 제9권4호
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• pp.66-70
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• 2008

The propagation of a mixed-mode crack in soda-lime silica glass is modeled by movable cellular automata (MCA). In this model, a special fracture criterion is used to describe the process of crack initiation and propagation. The results obtained using the MCA criterion are compared to those obtained from other crack initiation criteria, The crack resistance curves and bifurcation angles are determined for various loading angles. The MCA results are in close agreement with results obtained using the maximum circumferential tensile stress criterion.

• 한국컴퓨터정보학회논문지
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• 제23권5호
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• pp.15-23
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• 2018

Recently, convergence engineering is emerged technology to make a whole new conceptual methodology attractively more than we previously developed the distinct technology for engineering college students particularly. Based on convergence methodology, we utilize the open-source electronic prototyping platform named Arduino enabling users to create interactive electronic objects and the automata that is generally referred to a wooden moving, mechanical device or art of work in order to develop the creative convergence education program. We have confidence that our education program can lead the development of automata and information technology simultaneously and can nurture talented students who have creativity and originality in engineering college.

• ETRI Journal
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• 제34권2호
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• pp.284-287
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• 2012

Quantum-dot cellular automata (QCA) is one of the few alternative computing platforms that has the potential to be a promising technology because of higher speed, smaller size, and lower power consumption in comparison with CMOS technology. This letter proposes an optimized full comparator for implementation in QCA. The proposed design is compared with previous works in terms of complexity, area, and delay. In comparison with the best previous full comparator, our design has 64% and 85% improvement in cell count and area, respectively. Also, it is implemented with only one clock cycle. The obtained results show that our full comparator is more efficient in terms of cell count, complexity, area, and delay compared to the previous designs. Therefore, this structure can be simply used in designing QCA-based circuits.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 G
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• pp.2193-2196
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• 1998

Cellular automata are dynamical systems in which space and time are discrete, where each cell has a finite number of states and updates its states by interactive rules among the cell-neighborhood. From the characteristics of self-reproduction and self- organization, it is possible to create a neural network which has the specific patterns or structures dynamically. CAM-Brain is a kind of such neural network system which evolves its structure by adopting evolutionary computations like genetic algorithms (GA). In this paper, we suggest the evolution strategies for the structure of neural networks based on cellular automata.

• Journal of applied mathematics & informatics
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• 제9권1호
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• pp.135-150
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• 2002

The present paper discusses non-deterministic finite Rabin-scott's automate. The majority of works recently dealing with this subject were, in fact, concerned only with properties of a canonical term automata or of some objects equivalent to it. This article continues the series of works in which the authors state a different point of view, describing the finite automata as just another invariant of the given regular language called basis finite automaton. In this article the authors argue on some new properties for the basis finite automaton. One of them is included into basis automaton's table of binary relations. It is stated that this table can not contain either identical strings or identical columns. Another property depicts a possibility to obtain any finite automaton for a given regular language by the process of duplicating or combining some of its states.

• 한국전자통신학회논문지
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• 제5권3호
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• pp.315-320
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• 2010

다중 클래스로 이루어진 패턴을 분류하는 것은 데이터 베이스 시스템에서 기록을 그룹화하거나 VLSI 회로에서 어디에 결함이 있는지를 찾는 것 등에서 중요한 역할을 한다. 본 논문에서는 주어진 다중 클래스 패턴을 MACA(Multiple Attractor Cellular Automata)와 부분공간의 개념을 이용하여 가능한 최소 메모리량을 필요로 하는 다중 클래스 패턴 분류기를 구성하는 알고리즘을 제안한다.

• 한국정보통신학회논문지
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• 제7권7호
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• pp.1551-1555
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• 2003

본 논문은 뇌 자기공명영상에 대해 셀룰러 오토마타를 이용하여 뇌 영역을 추출한 연구이다. 입력된 뇌 자기공명영상의 배경영상을 임계값으로 제거한다. 임계값은 히스토그램 분석기법으로 설정된다. 분리된 영상정보는 셀룰러 오토마타 규칙을 적용하여 뇌 영역을 추출한다. 실험결과 평균 PSNR은 42㏈이상 향상되었으며, 상관도 측정 결과 98%이상 일치되었다. 본 연구 결과는 의료 뇌 영상의 자동 진단 시스템 등에 활용 할 수 있다.

• ETRI Journal
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• 제42권6호
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• pp.912-921
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• 2020

Quantum-dot cellular automata (QCA) is an alternative complementary metal-oxide-semiconductor (CMOS) technology that is used to implement high-speed logical circuits at the atomic or molecular scale. In this study, an optimal 2-to-4 decoder in QCA is presented. The proposed QCA decoder is designed using a new formulation based on the MV32 gate. Notably, the MV32 gate has three inputs and two outputs, which is equivalent two 3-input majority gates, and operates based on cellular interactions. A multilayer design is suggested for the proposed decoder. Subsequently, a new and efficient 3-to-8 QCA decoder architecture is presented using the proposed 2-to-4 QCA decoder. The simulation results of the QCADesigner 2.0.3 software show that the proposed decoders perform well. Comparisons show that the proposed 2-to-4 QCA decoder is superior to the previously proposed ones in terms of cell count, occupied area, and delay.

• ETRI Journal
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• 제44권1호
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• pp.155-167
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• 2022

The Internet of Things (IoT) is a new paradigm that connects physical and virtual objects from various domains such as home automation, industrial processes, human health, and monitoring. IoT sensors receive information from their environment and forward it to their neighboring nodes. However, the large amounts of exchanged data are vulnerable to attacks that reduce the network performance. Most of the previous security methods for IoT have neglected the energy consumption of IoT, thereby affecting the performance and reducing the network lifetime. This paper presents a new multistep routing protocol based on cellular learning automata. The network lifetime is improved by a performance-based adaptive reward and fine parameters. Nodes can vote on the reliability of their neighbors, achieving network reliability and a reasonable level of security. Overall, the proposed method balances the security and reliability with the energy consumption of the network.