• Journal of Korea Foundry Society
• /
• v.27 no.6
• /
• pp.237-242
• /
• 2007

To improve the quality of the product and the cost efficiency, the joining of A356 alloy to an Al-18wt%Si alloys has been performed by centrifugal casting. The influence of the mold preheating temperature, the pouring temperature and the rotational velocity of the mold on the microstructures of the shell in the centrifugal casting was investigated using the experimental and simulation methods. In the present study, the cellular automaton (CA) technique and the finite volume method (FVM) were adopted to simulate the evolution of the macro structures and to calculate the temperature profiles, respectively. The evolution of the microstructures was also simulated using a modified cellular automaton (MCA) model. The optimal rotational speed of the mold for obtaining the sound shape of the shell was estimated experimentally to be over 1200 rpm. For the uniform microstructure, the outer shell needs to be cast with higher preheated mold temperature and lower pouring temperature, and the melt was poured at lower temperature in the inner shell. In order to obtain the sound shape of the joining, the different materials were poured simultaneously.

• Journal of Korea Foundry Society
• /
• v.21 no.1
• /
• pp.41-47
• /
• 2001

Computer simulation of the solidification grain structure was applied to the casting process by using CA-DFDM. The Direct Finite Difference Method (DFDM) for temperature field calculation and latent heat treatment was coupled with Cellular Automaton (CA) method for the grain growth. 2-dimensional simulation of the solidification grain structures and calculation of the concentration fields were carried out and the calculated concentration distributions were compared with exact solution. Castings having complex geometries such as turbine blades were applied for 3-dimensional CA-DFDM. Effects of grain selector and mold extraction speed on the solidification grain structures in the turbine blade were examined.

• Journal of Information Processing Systems
• /
• v.8 no.1
• /
• pp.67-84
• /
• 2012

An important amount of clinical data concerning the medical history of a patient is in the form of clinical reports that are written by doctors. They describe patients, their pathologies, their personal and medical histories, findings made during interviews or during procedures, and so forth. They represent a source of precious information that can be used in several applications such as research information to diagnose new patients, epidemiological studies, decision support, statistical analysis, and data mining. But this information is difficult to access, as it is often in unstructured text form. To make access to patient data easy, our research aims to develop a system for extracting information from unstructured text. In a previous work, a rule-based approach is applied to a clinical reports corpus of infectious diseases to extract structured data in the form of named entities and properties. In this paper, we propose the use of a Boolean inference engine, which is based on a cellular automaton, to do extraction. Our motivation to adopt this Boolean modeling approach is twofold: first optimize storage, and second reduce the response time of the entities extraction.

• Korean Journal of Mathematics
• /
• v.18 no.4
• /
• pp.357-368
• /
• 2010

In this note, we will characterize group orders of hybrid CA configured with rules 60 and 195 and that configured with rules 102 and 153.

• Journal of the Chungcheong Mathematical Society
• /
• v.30 no.3
• /
• pp.305-311
• /
• 2017

We investigate periodicities of characteristic matrices of some hybrid cellular automata configured with rules 60 and 102 and an intermediate boundary condition.

• Korean Journal of Ecology and Environment
• /
• v.37 no.3 s.108
• /
• pp.297-303
• /
• 2004

Two dimensional cellular automaton (CA) models were developed to investigate growth of biofilms in aquatic ecosystems. Simple local rules on CA were applied to governing growth of bacterial populations in relation to different nutrient concentrations. Initial bacterial distribution played an important role in determining population size and morphology of biofilm at low concentrations of nutrition. With clumped distribution, population size increased slowly compared with uniform and random distributions, while the porosity tented to be higher with uniform distribution compared with other initial distributions.

• Journal of the Korean Mathematical Society
• /
• v.32 no.3
• /
• pp.573-582
• /
• 1995

J.Milnor[Mi2] has introduced the notion of directional entropy in his study of Cellular Automata. Cellular Automaton map can be considered as a continuous map from a space $K^Z^n$ to itself which commute with the translation of the lattice $Z^n$. Since the space $K^Z^n$ is compact, map S is uniformly continuous. Hence S is a block map(a finite code)[He]. (S is said to have a finite memory.) In the case of n = 1, we have a shift map, T on $K^Z$, and a block map S and they together generate a $Z^2$ action.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2000.05a
• /
• pp.236-240
• /
• 2000

A cellular automaton is well-known for self-organizing and dynamic behaviors in the field of artificial life. This paper addresses a new neuronic architecture called an evolvable cellular classifier which evolves with the genetic rules (chromosomes) in the non-uniform cellular automata. An evolvable cellular classifier is primarily based on cellular programing, but its mechanism is simpler because it utilizes only mutations for the main genetic operators and resembles the Hopfield network. Therefore, the desirable hi t-patterns could be obtained through evolutionary processes for just one individual agent. As a result, an evolvable hardware is derived which is applicable to classification of bit-string information.

• Journal of information and communication convergence engineering
• /
• v.11 no.1
• /
• pp.30-44
• /
• 2013

Traffic congestion has become a serious problem with the recent exponential increase in the number of vehicles. In urban areas, almost all traffic congestion occurs at intersections. One of the ways to solve this problem is road expansion, but it is difficult to realize in urban areas because of the high cost and long construction period. In such cases, traffic signal control is a reasonable method for reducing traffic jams. In an actual situation, the traffic flow changes randomly and its randomness makes the control of traffic signals difficult. A prediction of traffic jams is, therefore, necessary and effective for reducing traffic jams. In addition, an autonomous distributed (stand-alone) point control of each traffic light individually is better than the wide and/or line control of traffic lights from the perspective of real-time control. This paper describes a stochastic optimum control of crossroads and multi-way traffic signals. First, a stochastic model of traffic flows and traffic jams is constructed by using a Bayesian network. Secondly, the probabilistic distributions of the traffic flows are estimated by using a cellular automaton, and then the probabilistic distributions of traffic jams are predicted. Thirdly, optimum traffic signals of crossroads and multi-way intersection are searched by using a modified particle swarm optimization algorithm to realize real-time traffic control. Finally, simulations are carried out to confirm the effectiveness of the real-time stochastic optimum control of traffic signals.

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