Inferring the Limit Behavior of Some Elementary Cellular Automata

NASA Astrophysics Data System (ADS)

Ruivo, Eurico L. P.; de Oliveira, Pedro P. B.

Cellular automata locally define dynamical systems, discrete in space, time and in the state variables, capable of displaying arbitrarily complex global emergent behavior. One core question in the study of cellular automata refers to their limit behavior, that is, to the global dynamical features in an infinite time evolution. Previous works have shown that for finite time evolutions, the dynamics of one-dimensional cellular automata can be described by regular languages and, therefore, by finite automata. Such studies have shown the existence of growth patterns in the evolution of such finite automata for some elementary cellular automata rules and also inferred the limit behavior of such rules based upon the growth patterns; however, the results on the limit behavior were obtained manually, by direct inspection of the structures that arise during the time evolution. Here we present the formalization of an automatic method to compute such structures. Based on this, the rules of the elementary cellular automata space were classified according to the existence of a growth pattern in their finite automata. Also, we present a method to infer the limit graph of some elementary cellular automata rules, derived from the analysis of the regular expressions that describe their behavior in finite time. Finally, we analyze some attractors of two rules for which we could not compute the whole limit set.

A Cellular Automata-based Model for Simulating Restitution Property in a Single Heart Cell.

PubMed

Sabzpoushan, Seyed Hojjat; Pourhasanzade, Fateme

2011-01-01

Ventricular fibrillation is the cause of the most sudden mortalities. Restitution is one of the specific properties of ventricular cell. The recent findings have clearly proved the correlation between the slope of restitution curve with ventricular fibrillation. This; therefore, mandates the modeling of cellular restitution to gain high importance. A cellular automaton is a powerful tool for simulating complex phenomena in a simple language. A cellular automaton is a lattice of cells where the behavior of each cell is determined by the behavior of its neighboring cells as well as the automata rule. In this paper, a simple model is depicted for the simulation of the property of restitution in a single cardiac cell using cellular automata. At first, two state variables; action potential and recovery are introduced in the automata model. In second, automata rule is determined and then recovery variable is defined in such a way so that the restitution is developed. In order to evaluate the proposed model, the generated restitution curve in our study is compared with the restitution curves from the experimental findings of valid sources. Our findings indicate that the presented model is not only capable of simulating restitution in cardiac cell, but also possesses the capability of regulating the restitution curve.

Asynchronous adaptive time step in quantitative cellular automata modeling

PubMed Central

Zhu, Hao; Pang, Peter YH; Sun, Yan; Dhar, Pawan

2004-01-01

Background The behaviors of cells in metazoans are context dependent, thus large-scale multi-cellular modeling is often necessary, for which cellular automata are natural candidates. Two related issues are involved in cellular automata based multi-cellular modeling: how to introduce differential equation based quantitative computing to precisely describe cellular activity, and upon it, how to solve the heavy time consumption issue in simulation. Results Based on a modified, language based cellular automata system we extended that allows ordinary differential equations in models, we introduce a method implementing asynchronous adaptive time step in simulation that can considerably improve efficiency yet without a significant sacrifice of accuracy. An average speedup rate of 4–5 is achieved in the given example. Conclusions Strategies for reducing time consumption in simulation are indispensable for large-scale, quantitative multi-cellular models, because even a small 100 × 100 × 100 tissue slab contains one million cells. Distributed and adaptive time step is a practical solution in cellular automata environment. PMID:15222901

Nonsynchronous updating in the multiverse of cellular automata

NASA Astrophysics Data System (ADS)

Reia, Sandro M.; Kinouchi, Osame

2015-04-01

In this paper we study updating effects on cellular automata rule space. We consider a subset of 6144 order-3 automata from the space of 262144 bidimensional outer-totalistic rules. We compare synchronous to asynchronous and sequential updatings. Focusing on two automata, we discuss how update changes destroy typical structures of these rules. Besides, we show that the first-order phase transition in the multiverse of synchronous cellular automata, revealed with the use of a recently introduced control parameter, seems to be robust not only to changes in update schema but also to different initial densities.

Nonsynchronous updating in the multiverse of cellular automata.

PubMed

Reia, Sandro M; Kinouchi, Osame

2015-04-01

In this paper we study updating effects on cellular automata rule space. We consider a subset of 6144 order-3 automata from the space of 262144 bidimensional outer-totalistic rules. We compare synchronous to asynchronous and sequential updatings. Focusing on two automata, we discuss how update changes destroy typical structures of these rules. Besides, we show that the first-order phase transition in the multiverse of synchronous cellular automata, revealed with the use of a recently introduced control parameter, seems to be robust not only to changes in update schema but also to different initial densities.

Failover in Cellular Automata

NASA Astrophysics Data System (ADS)

Kumar, Shailesh; Rao, Shrisha

This paper studies a phenomenon called failover, and shows that this phenomenon (in particular, stateless failover) can be modeled by Game of Life cellular automata. This is the first time that this sophisticated real-life system behavior has been modeled in abstract terms. A cellular automata (CA) configuration is constructed that exhibits emergent failover. The configuration is based on standard Game of Life rules. Gliders and glider-guns form the core messaging structure in the configuration. The blinker is represented as the basic computational unit, and it is shown how it can be recreated in case of a failure. Stateless failover using the primary-backup mechanism is demonstrated. The details of the CA components used in the configuration and its working are described, and a simulation of the complete configuration is also presented.

Using cellular automata to generate image representation for biological sequences.

PubMed

Xiao, X; Shao, S; Ding, Y; Huang, Z; Chen, X; Chou, K-C

2005-02-01

A novel approach to visualize biological sequences is developed based on cellular automata (Wolfram, S. Nature 1984, 311, 419-424), a set of discrete dynamical systems in which space and time are discrete. By transforming the symbolic sequence codes into the digital codes, and using some optimal space-time evolvement rules of cellular automata, a biological sequence can be represented by a unique image, the so-called cellular automata image. Many important features, which are originally hidden in a long and complicated biological sequence, can be clearly revealed thru its cellular automata image. With biological sequences entering into databanks rapidly increasing in the post-genomic era, it is anticipated that the cellular automata image will become a very useful vehicle for investigation into their key features, identification of their function, as well as revelation of their "fingerprint". It is anticipated that by using the concept of the pseudo amino acid composition (Chou, K.C. Proteins: Structure, Function, and Genetics, 2001, 43, 246-255), the cellular automata image approach can also be used to improve the quality of predicting protein attributes, such as structural class and subcellular location.

Cellular Automata Simulation for Wealth Distribution

NASA Astrophysics Data System (ADS)

Lo, Shih-Ching

2009-08-01

Wealth distribution of a country is a complicate system. A model, which is based on the Epstein & Axtell's "Sugars cape" model, is presented in Netlogo. The model considers the income, age, working opportunity and salary as control variables. There are still other variables should be considered while an artificial society is established. In this study, a more complicate cellular automata model for wealth distribution model is proposed. The effects of social welfare, tax, economical investment and inheritance are considered and simulated. According to the cellular automata simulation for wealth distribution, we will have a deep insight of financial policy of the government.

Construction of phase diagrams for nanoscaled Ising thin films on the honeycomb lattice using cellular automata simulation approach

NASA Astrophysics Data System (ADS)

Ghaemi, Mehrdad; Javadi, Nabi

2017-11-01

The phase diagrams of the three-layer Ising model on the honeycomb lattice with a diluted surface have been constructed using the probabilistic cellular automata based on Glauber algorithm. The effects of the exchange interactions on the phase diagrams have been investigated. A general mathematical expression for the critical temperature is obtained in terms of relative coupling r = J1/J and Δs = (Js/J) - 1, where J and Js represent the nearest neighbor coupling within inner- and surface-layers, respectively, and each magnetic site in the surface-layer is coupled with the nearest neighbor site in the inner-layer via the exchange coupling J1. In the case of antiferromagnetic coupling between surface-layer and inner-layer, system reveals many interesting phenomena, such as the possibility of existence of compensation line before the critical temperature.

An image encryption algorithm based on 3D cellular automata and chaotic maps

NASA Astrophysics Data System (ADS)

Del Rey, A. Martín; Sánchez, G. Rodríguez

2015-05-01

A novel encryption algorithm to cipher digital images is presented in this work. The digital image is rendering into a three-dimensional (3D) lattice and the protocol consists of two phases: the confusion phase where 24 chaotic Cat maps are applied and the diffusion phase where a 3D cellular automata is evolved. The encryption method is shown to be secure against the most important cryptanalytic attacks.

A cellular automata model of SARS epidemic spreading

NASA Astrophysics Data System (ADS)

Xu, Tian; Zhang, Peipei; Su, Beibei; Jiang, Yumai; He, Da-Ren

2004-03-01

We suggest a cellular automata model for a simulation on the process of SARS spreading in Beijing. Suppose a number of people are located in a two-dimensional lattice, in which a certain portion belongs to immune and others belong to acceptive. In every time step each of the acceptive people may become ill with a certain probability if one of his 8 neighbors is a SARS patient. At same time all the people have another possibility to change their positions. Each patient will recover or die after different number of days. A recovered patient becomes immune. The numerical simulation by this model leads to the results, which are in a good agreement with the practical statistical data.

Self-organisation in Cellular Automata with Coalescent Particles: Qualitative and Quantitative Approaches

NASA Astrophysics Data System (ADS)

Hellouin de Menibus, Benjamin; Sablik, Mathieu

2017-06-01

This article introduces new tools to study self-organisation in a family of simple cellular automata which contain some particle-like objects with good collision properties (coalescence) in their time evolution. We draw an initial configuration at random according to some initial shift-ergodic measure, and use the limit measure to describe the asymptotic behaviour of the automata. We first take a qualitative approach, i.e. we obtain information on the limit measure(s). We prove that only particles moving in one particular direction can persist asymptotically. This provides some previously unknown information on the limit measures of various deterministic and probabilistic cellular automata: 3 and 4-cyclic cellular automata [introduced by Fisch (J Theor Probab 3(2):311-338, 1990; Phys D 45(1-3):19-25, 1990)], one-sided captive cellular automata [introduced by Theyssier (Captive Cellular Automata, 2004)], the majority-traffic cellular automaton, a self stabilisation process towards a discrete line [introduced by Regnault and Rémila (in: Mathematical Foundations of Computer Science 2015—40th International Symposium, MFCS 2015, Milan, Italy, Proceedings, Part I, 2015)]. In a second time we restrict our study to a subclass, the gliders cellular automata. For this class we show quantitative results, consisting in the asymptotic law of some parameters: the entry times [generalising K ůrka et al. (in: Proceedings of AUTOMATA, 2011)], the density of particles and the rate of convergence to the limit measure.

A full computation-relevant topological dynamics classification of elementary cellular automata.

PubMed

Schüle, Martin; Stoop, Ruedi

2012-12-01

Cellular automata are both computational and dynamical systems. We give a complete classification of the dynamic behaviour of elementary cellular automata (ECA) in terms of fundamental dynamic system notions such as sensitivity and chaoticity. The "complex" ECA emerge to be sensitive, but not chaotic and not eventually weakly periodic. Based on this classification, we conjecture that elementary cellular automata capable of carrying out complex computations, such as needed for Turing-universality, are at the "edge of chaos."

Configurable Cellular Automata for Pseudorandom Number Generation

NASA Astrophysics Data System (ADS)

Quieta, Marie Therese; Guan, Sheng-Uei

This paper proposes a generalized structure of cellular automata (CA) — the configurable cellular automata (CoCA). With selected properties from programmable CA (PCA) and controllable CA (CCA), a new approach to cellular automata is developed. In CoCA, the cells are dynamically reconfigured at run-time via a control CA. Reconfiguration of a cell simply means varying the properties of that cell with time. Some examples of properties to be reconfigured are rule selection, boundary condition, and radius. While the objective of this paper is to propose CoCA as a new CA method, the main focus is to design a CoCA that can function as a good pseudorandom number generator (PRNG). As a PRNG, CoCA can be a suitable candidate as it can pass 17 out of 18 Diehard tests with 31 cells. CoCA PRNG's performance based on Diehard test is considered superior over other CA PRNG works. Moreover, CoCA opens new rooms for research not only in the field of random number generation, but in modeling complex systems as well.

Lempel-Ziv complexity analysis of one dimensional cellular automata.

PubMed

Estevez-Rams, E; Lora-Serrano, R; Nunes, C A J; Aragón-Fernández, B

2015-12-01

Lempel-Ziv complexity measure has been used to estimate the entropy density of a string. It is defined as the number of factors in a production factorization of a string. In this contribution, we show that its use can be extended, by using the normalized information distance, to study the spatiotemporal evolution of random initial configurations under cellular automata rules. In particular, the transfer information from time consecutive configurations is studied, as well as the sensitivity to perturbed initial conditions. The behavior of the cellular automata rules can be grouped in different classes, but no single grouping captures the whole nature of the involved rules. The analysis carried out is particularly appropriate for studying the computational processing capabilities of cellular automata rules.

Lempel-Ziv complexity analysis of one dimensional cellular automata

NASA Astrophysics Data System (ADS)

Estevez-Rams, E.; Lora-Serrano, R.; Nunes, C. A. J.; Aragón-Fernández, B.

2015-12-01

Lempel-Ziv complexity measure has been used to estimate the entropy density of a string. It is defined as the number of factors in a production factorization of a string. In this contribution, we show that its use can be extended, by using the normalized information distance, to study the spatiotemporal evolution of random initial configurations under cellular automata rules. In particular, the transfer information from time consecutive configurations is studied, as well as the sensitivity to perturbed initial conditions. The behavior of the cellular automata rules can be grouped in different classes, but no single grouping captures the whole nature of the involved rules. The analysis carried out is particularly appropriate for studying the computational processing capabilities of cellular automata rules.

The two populations’ cellular automata model with predation based on the Penna model

NASA Astrophysics Data System (ADS)

He, Mingfeng; Lin, Jing; Jiang, Heng; Liu, Xin

2002-09-01

In Penna's single-species asexual bit-string model of biological ageing, the Verhulst factor has too strong a restraining effect on the development of the population. Danuta Makowiec gave an improved model based on the lattice, where the restraining factor of the four neighbours take the place of the Verhulst factor. Here, we discuss the two populations’ Penna model with predation on the planar lattice of two dimensions. A cellular automata model containing movable wolves and sheep has been built. The results show that both the quantity of the wolves and the sheep fluctuate in accordance with the law that one quantity increases while the other one decreases.

Hybrid lattice gas simulations of flow through porous media

NASA Astrophysics Data System (ADS)

Becklehimer, Jeffrey Lynn

1997-10-01

This study introduces a suite of models designed to investigate transport phenomena in simulated porous media such as rigid or quenched sediment and clay-like deformable environments. This is achieved by using a variety of techniques that are borrowed from the field of statistical physics. These techniques include percolation, lattice gas, and cellular automata. A percolation-based model is used to study a porous medium by using rods and chains of various shapes and sizes to model the porous media formed by sediments. This is further extended to model clay-like deformable media by interacting heavy sediment particles. An interacting lattice gas computer simulation model based on the Metropolis algorithm is used to study the transport properties of fluid particles and permeability of a porous sediment. Finally, a hybrid lattice gas model is introduced by combining the Metropolis Monte Carlo method with a direct simulation which involves the collision rules as in cellular automata. This model is then used to study shock propagation in a fluid filled porous medium. This study is then extended to study shock propagation through in a fluid filled elastic porous medium. Several interesting and new results were obtained. These results show that for rigid chain percolation the percolation threshold shows a dependence on the chain length of pc~ Lc-1/2 and the jamming coverage decreases with the chain length as Lc- 1/3. For the random SAW-like chains the percolation threshold decays with the chain length as Lc- 0.01 and the jamming coverage as Lc-1/3. The fluid flow model shows that permeability depends nonmonotonically on the concentration of the fluid. For some fluids at a fixed porosity, the permeability increases on increasing the bias until a certain value Bc above which it decreases. Also, it was found that a shock propagates in a drift-like fashion when in a rigid porous medium when the porosity is high; low porosity damps out the shock front very quickly. For a shock

Minimal entropy approximation for cellular automata

NASA Astrophysics Data System (ADS)

Fukś, Henryk

2014-02-01

We present a method for the construction of approximate orbits of measures under the action of cellular automata which is complementary to the local structure theory. The local structure theory is based on the idea of Bayesian extension, that is, construction of a probability measure consistent with given block probabilities and maximizing entropy. If instead of maximizing entropy one minimizes it, one can develop another method for the construction of approximate orbits, at the heart of which is the iteration of finite-dimensional maps, called minimal entropy maps. We present numerical evidence that the minimal entropy approximation sometimes outperforms the local structure theory in characterizing the properties of cellular automata. The density response curve for elementary CA rule 26 is used to illustrate this claim.

Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity

USGS Publications Warehouse

Louis, S.J.; Raines, G.L.

2003-01-01

We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.

Cellular Automata and the Humanities.

ERIC Educational Resources Information Center

Gallo, Ernest

1994-01-01

The use of cellular automata to analyze several pre-Socratic hypotheses about the evolution of the physical world is discussed. These hypotheses combine characteristics of both rigorous and metaphoric language. Since the computer demands explicit instructions for each step in the evolution of the automaton, such models can reveal conceptual…

The 3-dimensional cellular automata for HIV infection

NASA Astrophysics Data System (ADS)

Mo, Youbin; Ren, Bin; Yang, Wencao; Shuai, Jianwei

2014-04-01

The HIV infection dynamics is discussed in detail with a 3-dimensional cellular automata model in this paper. The model can reproduce the three-phase development, i.e., the acute period, the asymptotic period and the AIDS period, observed in the HIV-infected patients in a clinic. We show that the 3D HIV model performs a better robustness on the model parameters than the 2D cellular automata. Furthermore, we reveal that the occurrence of a perpetual source to successively generate infectious waves to spread to the whole system drives the model from the asymptotic state to the AIDS state.

Generic framework for mining cellular automata models on protein-folding simulations.

PubMed

Diaz, N; Tischer, I

2016-05-13

Cellular automata model identification is an important way of building simplified simulation models. In this study, we describe a generic architectural framework to ease the development process of new metaheuristic-based algorithms for cellular automata model identification in protein-folding trajectories. Our framework was developed by a methodology based on design patterns that allow an improved experience for new algorithms development. The usefulness of the proposed framework is demonstrated by the implementation of four algorithms, able to obtain extremely precise cellular automata models of the protein-folding process with a protein contact map representation. Dynamic rules obtained by the proposed approach are discussed, and future use for the new tool is outlined.

Molecular Magnetic Quantum Cellular Automata

DTIC Science & Technology

2004-06-01

Folting K, Gatteschi D, Christou G, Hendrickson D N 1993a, High-Spin Molecules - [Mn12O12(O2CR)16(H2O)4], J. Am. Chem. Soc. 115 1804 Sessoli R... Gatteschi D, Caneschi A and Novak M A 1993b, Magnetic bistability in a metal-ion cluster, Nature 365 141 Twamely J 2003, Quantum-cellular-automata

Cellular automaton formulation of passive scalar dynamics

NASA Technical Reports Server (NTRS)

Chen, Hudong; Matthaeus, William H.

1987-01-01

Cellular automata modeling of the advection of a passive scalar in a two-dimensional flow is examined in the context of discrete lattice kinetic theory. It is shown that if the passive scalar is represented by tagging or 'coloring' automation particles a passive advection-diffusion equation emerges without use of perturbation expansions. For the specific case of the hydrodynamic lattice gas model of Frisch et al. (1986), the diffusion coefficient is calculated by perturbation.

A stochastic cellular automata model of tautomer equilibria

NASA Astrophysics Data System (ADS)

Bowers, Gregory A.; Seybold, Paul G.

2018-03-01

Many chemical substances, including drugs and biomolecules, exist in solution not as a single species, but as a collection of tautomers and related species. Importantly, each of these species is an independent compoundwith its own specific biochemical and physicochemical properties. The species interconvert in a dynamic and often complicated manner, making modelling the overall species composition difficult. Agent-based cellular automata models are uniquely suited to meet this challenge, allowing the equilibria to be simulated using simple rulesand at the same time capturing the inherent stochasticity of the natural phenomenon. In the present example a stochastic cellular automata model is employed to simulate the tautomer equilibria of 9-anthrone and 9-anthrol in the presence of their common anion. The observed KE of the 9-anthrone ⇌ 9-anthrol tautomerisation along with the measured tautomer pKa values were used to model the equilibria at pH values 4, 7 and 10. At pH 4 and 7, the anthrone comprises >99% of the total species population, while at pH 10the anthrone and the anion each represent just under half of the total population. The advantages of the cellular automata approach over the customary coupled differential equation approach are discussed.

Scalable asynchronous execution of cellular automata

NASA Astrophysics Data System (ADS)

Folino, Gianluigi; Giordano, Andrea; Mastroianni, Carlo

2016-10-01

The performance and scalability of cellular automata, when executed on parallel/distributed machines, are limited by the necessity of synchronizing all the nodes at each time step, i.e., a node can execute only after the execution of the previous step at all the other nodes. However, these synchronization requirements can be relaxed: a node can execute one step after synchronizing only with the adjacent nodes. In this fashion, different nodes can execute different time steps. This can be a notable advantageous in many novel and increasingly popular applications of cellular automata, such as smart city applications, simulation of natural phenomena, etc., in which the execution times can be different and variable, due to the heterogeneity of machines and/or data and/or executed functions. Indeed, a longer execution time at a node does not slow down the execution at all the other nodes but only at the neighboring nodes. This is particularly advantageous when the nodes that act as bottlenecks vary during the application execution. The goal of the paper is to analyze the benefits that can be achieved with the described asynchronous implementation of cellular automata, when compared to the classical all-to-all synchronization pattern. The performance and scalability have been evaluated through a Petri net model, as this model is very useful to represent the synchronization barrier among nodes. We examined the usual case in which the territory is partitioned into a number of regions, and the computation associated with a region is assigned to a computing node. We considered both the cases of mono-dimensional and two-dimensional partitioning. The results show that the advantage obtained through the asynchronous execution, when compared to the all-to-all synchronous approach is notable, and it can be as large as 90% in terms of speedup.

Fuzzy cellular automata models in immunology

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahmed, E.

1996-10-01

The self-nonself character of antigens is considered to be fuzzy. The Chowdhury et al. cellular automata model is generalized accordingly. New steady states are found. The first corresponds to a below-normal help and suppression and is proposed to be related to autoimmune diseases. The second corresponds to a below-normal B-cell level.

Astrobiological complexity with probabilistic cellular automata.

PubMed

Vukotić, Branislav; Ćirković, Milan M

2012-08-01

The search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling the astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous space of the input parameters. We perform a simple clustering analysis of typical astrobiological histories with "Copernican" choice of input parameters and discuss the relevant boundary conditions of practical importance for planning and guiding empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.

Index Theory of One Dimensional Quantum Walks and Cellular Automata

NASA Astrophysics Data System (ADS)

Gross, D.; Nesme, V.; Vogts, H.; Werner, R. F.

2012-03-01

If a one-dimensional quantum lattice system is subject to one step of a reversible discrete-time dynamics, it is intuitive that as much "quantum information" as moves into any given block of cells from the left, has to exit that block to the right. For two types of such systems — namely quantum walks and cellular automata — we make this intuition precise by defining an index, a quantity that measures the "net flow of quantum information" through the system. The index supplies a complete characterization of two properties of the discrete dynamics. First, two systems S 1, S 2 can be "pieced together", in the sense that there is a system S which acts like S 1 in one region and like S 2 in some other region, if and only if S 1 and S 2 have the same index. Second, the index labels connected components of such systems: equality of the index is necessary and sufficient for the existence of a continuous deformation of S 1 into S 2. In the case of quantum walks, the index is integer-valued, whereas for cellular automata, it takes values in the group of positive rationals. In both cases, the map {S mapsto ind S} is a group homomorphism if composition of the discrete dynamics is taken as the group law of the quantum systems. Systems with trivial index are precisely those which can be realized by partitioned unitaries, and the prototypes of systems with non-trivial index are shifts.

Cellular automata and its applications in protein bioinformatics.

PubMed

Xiao, Xuan; Wang, Pu; Chou, Kuo-Chen

2011-09-01

With the explosion of protein sequences generated in the postgenomic era, it is highly desirable to develop high-throughput tools for rapidly and reliably identifying various attributes of uncharacterized proteins based on their sequence information alone. The knowledge thus obtained can help us timely utilize these newly found protein sequences for both basic research and drug discovery. Many bioinformatics tools have been developed by means of machine learning methods. This review is focused on the applications of a new kind of science (cellular automata) in protein bioinformatics. A cellular automaton (CA) is an open, flexible and discrete dynamic model that holds enormous potentials in modeling complex systems, in spite of the simplicity of the model itself. Researchers, scientists and practitioners from different fields have utilized cellular automata for visualizing protein sequences, investigating their evolution processes, and predicting their various attributes. Owing to its impressive power, intuitiveness and relative simplicity, the CA approach has great potential for use as a tool for bioinformatics.

Potential field cellular automata model for pedestrian flow

NASA Astrophysics Data System (ADS)

Zhang, Peng; Jian, Xiao-Xia; Wong, S. C.; Choi, Keechoo

2012-02-01

This paper proposes a cellular automata model of pedestrian flow that defines a cost potential field, which takes into account the costs of travel time and discomfort, for a pedestrian to move to an empty neighboring cell. The formulation is based on a reconstruction of the density distribution and the underlying physics, including the rule for resolving conflicts, which is comparable to that in the floor field cellular automaton model. However, we assume that each pedestrian is familiar with the surroundings, thereby minimizing his or her instantaneous cost. This, in turn, helps reduce the randomness in selecting a target cell, which improves the existing cellular automata modelings, together with the computational efficiency. In the presence of two pedestrian groups, which are distinguished by their destinations, the cost distribution for each group is magnified due to the strong interaction between the two groups. As a typical phenomenon, the formation of lanes in the counter flow is reproduced.

Cellular Automata Ideas in Digital Circuits and Switching Theory.

ERIC Educational Resources Information Center

Siwak, Pawel P.

1985-01-01

Presents two examples which illustrate the usefulness of ideas from cellular automata. First, Lee's algorithm is recalled and its cellular nature shown. Then a problem from digraphs, which has arisen from analyzing predecessing configurations in the famous Conway's "game of life," is considered. (Author/JN)

A novel image encryption algorithm using chaos and reversible cellular automata

NASA Astrophysics Data System (ADS)

Wang, Xingyuan; Luan, Dapeng

2013-11-01

In this paper, a novel image encryption scheme is proposed based on reversible cellular automata (RCA) combining chaos. In this algorithm, an intertwining logistic map with complex behavior and periodic boundary reversible cellular automata are used. We split each pixel of image into units of 4 bits, then adopt pseudorandom key stream generated by the intertwining logistic map to permute these units in confusion stage. And in diffusion stage, two-dimensional reversible cellular automata which are discrete dynamical systems are applied to iterate many rounds to achieve diffusion on bit-level, in which we only consider the higher 4 bits in a pixel because the higher 4 bits carry almost the information of an image. Theoretical analysis and experimental results demonstrate the proposed algorithm achieves a high security level and processes good performance against common attacks like differential attack and statistical attack. This algorithm belongs to the class of symmetric systems.

Structure and Reversibility of 2D von Neumann Cellular Automata Over Triangular Lattice

NASA Astrophysics Data System (ADS)

Uguz, Selman; Redjepov, Shovkat; Acar, Ecem; Akin, Hasan

2017-06-01

Even though the fundamental main structure of cellular automata (CA) is a discrete special model, the global behaviors at many iterative times and on big scales could be a close, nearly a continuous, model system. CA theory is a very rich and useful phenomena of dynamical model that focuses on the local information being relayed to the neighboring cells to produce CA global behaviors. The mathematical points of the basic model imply the computable values of the mathematical structure of CA. After modeling the CA structure, an important problem is to be able to move forwards and backwards on CA to understand their behaviors in more elegant ways. A possible case is when CA is to be a reversible one. In this paper, we investigate the structure and the reversibility of two-dimensional (2D) finite, linear, triangular von Neumann CA with null boundary case. It is considered on ternary field ℤ3 (i.e. 3-state). We obtain their transition rule matrices for each special case. For given special triangular information (transition) rule matrices, we prove which triangular linear 2D von Neumann CAs are reversible or not. It is known that the reversibility cases of 2D CA are generally a much challenged problem. In the present study, the reversibility problem of 2D triangular, linear von Neumann CA with null boundary is resolved completely over ternary field. As far as we know, there is no structure and reversibility study of von Neumann 2D linear CA on triangular lattice in the literature. Due to the main CA structures being sufficiently simple to investigate in mathematical ways, and also very complex to obtain in chaotic systems, it is believed that the present construction can be applied to many areas related to these CA using any other transition rules.

Quantum cellular automata and free quantum field theory

NASA Astrophysics Data System (ADS)

D'Ariano, Giacomo Mauro; Perinotti, Paolo

2017-02-01

In a series of recent papers [1-4] it has been shown how free quantum field theory can be derived without using mechanical primitives (including space-time, special relativity, quantization rules, etc.), but only considering the easiest quantum algorithm encompassing a countable set of quantum systems whose network of interactions satisfies the simple principles of unitarity, homogeneity, locality, and isotropy. This has opened the route to extending the axiomatic information-theoretic derivation of the quantum theory of abstract systems [5, 6] to include quantum field theory. The inherent discrete nature of the informational axiomatization leads to an extension of quantum field theory to a quantum cellular automata theory, where the usual field theory is recovered in a regime where the discrete structure of the automata cannot be probed. A simple heuristic argument sets the scale of discreteness to the Planck scale, and the customary physical regime where discreteness is not visible is the relativistic one of small wavevectors. In this paper we provide a thorough derivation from principles that in the most general case the graph of the quantum cellular automaton is the Cayley graph of a finitely presented group, and showing how for the case corresponding to Euclidean emergent space (where the group resorts to an Abelian one) the automata leads to Weyl, Dirac and Maxwell field dynamics in the relativistic limit. We conclude with some perspectives towards the more general scenario of non-linear automata for interacting quantum field theory.

Cellular automata with object-oriented features for parallel molecular network modeling.

PubMed

Zhu, Hao; Wu, Yinghui; Huang, Sui; Sun, Yan; Dhar, Pawan

2005-06-01

Cellular automata are an important modeling paradigm for studying the dynamics of large, parallel systems composed of multiple, interacting components. However, to model biological systems, cellular automata need to be extended beyond the large-scale parallelism and intensive communication in order to capture two fundamental properties characteristic of complex biological systems: hierarchy and heterogeneity. This paper proposes extensions to a cellular automata language, Cellang, to meet this purpose. The extended language, with object-oriented features, can be used to describe the structure and activity of parallel molecular networks within cells. Capabilities of this new programming language include object structure to define molecular programs within a cell, floating-point data type and mathematical functions to perform quantitative computation, message passing capability to describe molecular interactions, as well as new operators, statements, and built-in functions. We discuss relevant programming issues of these features, including the object-oriented description of molecular interactions with molecule encapsulation, message passing, and the description of heterogeneity and anisotropy at the cell and molecule levels. By enabling the integration of modeling at the molecular level with system behavior at cell, tissue, organ, or even organism levels, the program will help improve our understanding of how complex and dynamic biological activities are generated and controlled by parallel functioning of molecular networks. Index Terms-Cellular automata, modeling, molecular network, object-oriented.

Modeling cell adhesion and proliferation: a cellular-automata based approach.

PubMed

Vivas, J; Garzón-Alvarado, D; Cerrolaza, M

Cell adhesion is a process that involves the interaction between the cell membrane and another surface, either a cell or a substrate. Unlike experimental tests, computer models can simulate processes and study the result of experiments in a shorter time and lower costs. One of the tools used to simulate biological processes is the cellular automata, which is a dynamic system that is discrete both in space and time. This work describes a computer model based on cellular automata for the adhesion process and cell proliferation to predict the behavior of a cell population in suspension and adhered to a substrate. The values of the simulated system were obtained through experimental tests on fibroblast monolayer cultures. The results allow us to estimate the cells settling time in culture as well as the adhesion and proliferation time. The change in the cells morphology as the adhesion over the contact surface progress was also observed. The formation of the initial link between cell and the substrate of the adhesion was observed after 100 min where the cell on the substrate retains its spherical morphology during the simulation. The cellular automata model developed is, however, a simplified representation of the steps in the adhesion process and the subsequent proliferation. A combined framework of experimental and computational simulation based on cellular automata was proposed to represent the fibroblast adhesion on substrates and changes in a macro-scale observed in the cell during the adhesion process. The approach showed to be simple and efficient.

Quantum-dot cellular automata: Review and recent experiments (invited)

NASA Astrophysics Data System (ADS)

Snider, G. L.; Orlov, A. O.; Amlani, I.; Zuo, X.; Bernstein, G. H.; Lent, C. S.; Merz, J. L.; Porod, W.

1999-04-01

An introduction to the operation of quantum-dot cellular automata is presented, along with recent experimental results. Quantum-dot cellular automata (QCA) is a transistorless computation paradigm that addresses the issues of device density and interconnection. The basic building blocks of the QCA architecture, such as AND, OR, and NOT are presented. The experimental device is a four-dot QCA cell with two electrometers. The dots are metal islands, which are coupled by capacitors and tunnel junctions. An improved design of the cell is presented in which all four dots of the cell are coupled by tunnel junctions. The operation of this basic cell is confirmed by the externally controlled polarization change of the cell.

Design of Efficient Mirror Adder in Quantum- Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Mishra, Prashant Kumar; Chattopadhyay, Manju K.

2018-03-01

Lower power consumption is an essential demand for portable multimedia system using digital signal processing algorithms and architectures. Quantum dot cellular automata (QCA) is a rising nano technology for the development of high performance ultra-dense low power digital circuits. QCA based several efficient binary and decimal arithmetic circuits are implemented, however important improvements are still possible. This paper demonstrate Mirror Adder circuit design in QCA. We present comparative study of mirror adder cells designed using conventional CMOS technique and mirror adder cells designed using quantum-dot cellular automata. QCA based mirror adders are better in terms of area by order of three.

On the spatial dynamics and oscillatory behavior of a predator-prey model based on cellular automata and local particle swarm optimization.

PubMed

Molina, Mario Martínez; Moreno-Armendáriz, Marco A; Carlos Seck Tuoh Mora, Juan

2013-11-07

A two-dimensional lattice model based on Cellular Automata theory and swarm intelligence is used to study the spatial and population dynamics of a theoretical ecosystem. It is found that the social interactions among predators provoke the formation of clusters, and that by increasing the mobility of predators the model enters into an oscillatory behavior. © 2013 Elsevier Ltd. All rights reserved.

Color image encryption based on hybrid hyper-chaotic system and cellular automata

NASA Astrophysics Data System (ADS)

Yaghouti Niyat, Abolfazl; Moattar, Mohammad Hossein; Niazi Torshiz, Masood

2017-03-01

This paper proposes an image encryption scheme based on Cellular Automata (CA). CA is a self-organizing structure with a set of cells in which each cell is updated by certain rules that are dependent on a limited number of neighboring cells. The major disadvantages of cellular automata in cryptography include limited number of reversal rules and inability to produce long sequences of states by these rules. In this paper, a non-uniform cellular automata framework is proposed to solve this problem. This proposed scheme consists of confusion and diffusion steps. In confusion step, the positions of the original image pixels are replaced by chaos mapping. Key image is created using non-uniform cellular automata and then the hyper-chaotic mapping is used to select random numbers from the image key for encryption. The main contribution of the paper is the application of hyper chaotic functions and non-uniform CA for robust key image generation. Security analysis and experimental results show that the proposed method has a very large key space and is resistive against noise and attacks. The correlation between adjacent pixels in the encrypted image is reduced and the amount of entropy is equal to 7.9991 which is very close to 8 which is ideal.

Simulation of interdiffusion and voids growth based on cellular automata

NASA Astrophysics Data System (ADS)

Zhang, Fan; Zhang, Boyan; Zhang, Nan; Du, Haishun; Zhang, Xinhong

2017-02-01

In the interdiffusion of two solid-state materials, if the diffusion coefficients of the two materials are not the same, the interface of the two materials will shift to the material with the lower diffusion coefficient. This effect is known as the Kirkendall effect. The Kirkendall effect leads to Kirkendall porosity. The pores act as sinks for vacancies and become voids. In this paper, the movement of the Kirkendall plane at interdiffusion is simulated based on cellular automata. The number of vacancies, the critical radius of voids nucleation and the nucleation rate are analysed. The vacancies diffusion, vacancies aggregation and voids growth are also simulated based on cellular automata.

A 2D flood inundation model based on cellular automata approach

NASA Astrophysics Data System (ADS)

Dottori, Francesco; Todini, Ezio

2010-05-01

In the past years, the cellular automata approach has been successfully applied in two-dimensional modelling of flood events. When used in experimental applications, models based on such approach have provided good results, comparable to those obtained with more complex 2D models; moreover, CA models have proven significantly faster and easier to apply than most of existing models, and these features make them a valuable tool for flood analysis especially when dealing with large areas. However, to date the real degree of accuracy of such models has not been demonstrated, since they have been mainly used in experimental applications, while very few comparisons with theoretical solutions have been made. Also, the use of an explicit scheme of solution, which is inherent in cellular automata models, forces them to work only with small time steps, thus reducing model computation speed. The present work describes a cellular automata model based on the continuity and diffusive wave equations. Several model versions based on different solution schemes have been realized and tested in a number of numerical cases, both 1D and 2D, comparing the results with theoretical and numerical solutions. In all cases, the model performed well compared to the reference solutions, and proved to be both stable and accurate. Finally, the version providing the best results in terms of stability was tested in a real flood event and compared with different hydraulic models. Again, the cellular automata model provided very good results, both in term of computational speed and reproduction of the simulated event.

A comparative analysis of electronic and molecular quantum dot cellular automata

DOE Office of Scientific and Technical Information (OSTI.GOV)

Umamahesvari, H., E-mail: umamaheswarihema@gmail.com, E-mail: ajithavijay1@gmail.com; Ajitha, D., E-mail: umamaheswarihema@gmail.com, E-mail: ajithavijay1@gmail.com

This paper presents a comparative analysis of electronic quantum-dot cellular automata (EQCA) and Magnetic quantum dot Cellular Automata (MQCA). QCA is a computing paradigm that encodes and processes information by the position of individual electrons. To enhance the high dense and ultra-low power devices, various researches have been actively carried out to find an alternative way to continue and follow Moore’s law, so called “beyond CMOS technology”. There have been several proposals for physically implementing QCA, EQCA and MQCA are the two important QCAs reported so far. This paper provides a comparative study on these two QCAs.

Quantum cellular automata

NASA Astrophysics Data System (ADS)

Porod, Wolfgang; Lent, Craig S.; Bernstein, Gary H.

1994-06-01

The Notre Dame group has developed a new paradigm for ultra-dense and ultra-fast information processing in nanoelectronic systems. These Quantum Cellular Automata (QCA's) are the first concrete proposal for a technology based on arrays of coupled quantum dots. The basic building block of these cellular arrays is the Notre Dame Logic Cell, as it has been called in the literature. The phenomenon of Coulomb exclusion, which is a synergistic interplay of quantum confinement and Coulomb interaction, leads to a bistable behavior of each cell which makes possible their use in large-scale cellular arrays. The physical interaction between neighboring cells has been exploited to implement logic functions. New functionality may be achieved in this fashion, and the Notre Dame group invented a versatile majority logic gate. In a series of papers, the feasibility of QCA wires, wire crossing, inverters, and Boolean logic gates was demonstrated. A major finding is that all logic functions may be integrated in a hierarchial fashion which allows the design of complicated QCA structures. The most complicated system which was simulated to date is a one-bit full adder consisting of some 200 cells. In addition to exploring these new concepts, efforts are under way to physically realize such structures both in semiconductor and metal systems. Extensive modeling work of semiconductor quantum dot structures has helped identify optimum design parameters for QCA experimental implementations.

Universal map for cellular automata

NASA Astrophysics Data System (ADS)

García-Morales, V.

2012-08-01

A universal map is derived for all deterministic 1D cellular automata (CAs) containing no freely adjustable parameters and valid for any alphabet size and any neighborhood range (including non-symmetrical neighborhoods). The map can be extended to an arbitrary number of dimensions and topologies and to arbitrary order in time. Specific CA maps for the famous Conway's Game of Life and Wolfram's 256 elementary CAs are given. An induction method for CAs, based in the universal map, allows mathematical expressions for the orbits of a wide variety of elementary CAs to be systematically derived.

Boolean linear differential operators on elementary cellular automata

NASA Astrophysics Data System (ADS)

Martín Del Rey, Ángel

2014-12-01

In this paper, the notion of boolean linear differential operator (BLDO) on elementary cellular automata (ECA) is introduced and some of their more important properties are studied. Special attention is paid to those differential operators whose coefficients are the ECA with rule numbers 90 and 150.

Cellular automata in photonic cavity arrays.

PubMed

Li, Jing; Liew, T C H

2016-10-31

We propose theoretically a photonic Turing machine based on cellular automata in arrays of nonlinear cavities coupled with artificial gauge fields. The state of the system is recorded making use of the bistability of driven cavities, in which losses are fully compensated by an external continuous drive. The sequential update of the automaton layers is achieved automatically, by the local switching of bistable states, without requiring any additional synchronization or temporal control.

Conway's Game of Life is a near-critical metastable state in the multiverse of cellular automata.

PubMed

Reia, Sandro M; Kinouchi, Osame

2014-05-01

Conway's cellular automaton Game of Life has been conjectured to be a critical (or quasicritical) dynamical system. This criticality is generally seen as a continuous order-disorder transition in cellular automata (CA) rule space. Life's mean-field return map predicts an absorbing vacuum phase (ρ = 0) and an active phase density, with ρ = 0.37, which contrasts with Life's absorbing states in a square lattice, which have a stationary density of ρ(2D) ≈ 0.03. Here, we study and classify mean-field maps for 6144 outer-totalistic CA and compare them with the corresponding behavior found in the square lattice. We show that the single-site mean-field approach gives qualitative (and even quantitative) predictions for most of them. The transition region in rule space seems to correspond to a nonequilibrium discontinuous absorbing phase transition instead of a continuous order-disorder one. We claim that Life is a quasicritical nucleation process where vacuum phase domains invade the alive phase. Therefore, Life is not at the "border of chaos," but thrives on the "border of extinction."

Conway's game of life is a near-critical metastable state in the multiverse of cellular automata

NASA Astrophysics Data System (ADS)

Reia, Sandro M.; Kinouchi, Osame

2014-05-01

Conway's cellular automaton Game of Life has been conjectured to be a critical (or quasicritical) dynamical system. This criticality is generally seen as a continuous order-disorder transition in cellular automata (CA) rule space. Life's mean-field return map predicts an absorbing vacuum phase (ρ =0) and an active phase density, with ρ =0.37, which contrasts with Life's absorbing states in a square lattice, which have a stationary density of ρ2D≈0.03. Here, we study and classify mean-field maps for 6144 outer-totalistic CA and compare them with the corresponding behavior found in the square lattice. We show that the single-site mean-field approach gives qualitative (and even quantitative) predictions for most of them. The transition region in rule space seems to correspond to a nonequilibrium discontinuous absorbing phase transition instead of a continuous order-disorder one. We claim that Life is a quasicritical nucleation process where vacuum phase domains invade the alive phase. Therefore, Life is not at the "border of chaos," but thrives on the "border of extinction."

Robustness of a cellular automata model for the HIV infection

NASA Astrophysics Data System (ADS)

Figueirêdo, P. H.; Coutinho, S.; Zorzenon dos Santos, R. M.

2008-11-01

An investigation was conducted to study the robustness of the results obtained from the cellular automata model which describes the spread of the HIV infection within lymphoid tissues [R.M. Zorzenon dos Santos, S. Coutinho, Phys. Rev. Lett. 87 (2001) 168102]. The analysis focused on the dynamic behavior of the model when defined in lattices with different symmetries and dimensionalities. The results illustrated that the three-phase dynamics of the planar models suffered minor changes in relation to lattice symmetry variations and, while differences were observed regarding dimensionality changes, qualitative behavior was preserved. A further investigation was conducted into primary infection and sensitiveness of the latency period to variations of the model’s stochastic parameters over wide ranging values. The variables characterizing primary infection and the latency period exhibited power-law behavior when the stochastic parameters varied over a few orders of magnitude. The power-law exponents were approximately the same when lattice symmetry varied, but there was a significant variation when dimensionality changed from two to three. The dynamics of the three-dimensional model was also shown to be insensitive to variations of the deterministic parameters related to cell resistance to the infection, and the necessary time lag to mount the specific immune response to HIV variants. The robustness of the model demonstrated in this work reinforce that its basic hypothesis are consistent with the three-stage dynamic of the HIV infection observed in patients.

A Programmable Cellular-Automata Polarized Dirac Vacuum

NASA Astrophysics Data System (ADS)

Osoroma, Drahcir S.

2013-09-01

We explore properties of a `Least Cosmological Unit' (LCU) as an inherent spacetime raster tiling or tessellating the unique backcloth of Holographic Anthropic Multiverse (HAM) cosmology as an array of programmable cellular automata. The HAM vacuum is a scale-invariant HD extension of a covariant polarized Dirac vacuum with `bumps' and `holes' typically described by extended electromagnetic theory corresponding to an Einstein energy-dependent spacetime metric admitting a periodic photon mass. The new cosmology incorporates a unique form of M-Theoretic Calabi-Yau-Poincaré Dodecadedral-AdS5-DS5space (PDS) with mirror symmetry best described by an HD extension of Cramer's Transactional Interpretation when integrated also with an HD extension of the de Broglie-Bohm-Vigier causal interpretation of quantum theory. We incorporate a unique form of large-scale additional dimensionality (LSXD) bearing some similarity to that conceived by Randall and Sundrum; and extend the fundamental basis of our model to the Unified Field, UF. A Sagnac Effect rf-pulsed incursive resonance hierarchy is utilized to manipulate and ballistically program the geometric-topological properties of this putative LSXD space-spacetime network. The model is empirically testable; and it is proposed that a variety of new technologies will arise from ballistic programming of tessellated LCU vacuum cellular automata.

Magnetohydrodynamic cellular automata

NASA Technical Reports Server (NTRS)

Montgomery, David; Doolen, Gary D.

1987-01-01

A generalization of the hexagonal lattice gas model of Frisch, Hasslacher and Pomeau is shown to lead to two-dimensional magnetohydrodynamics. The method relies on the ideal point-wise conservation law for vector potential.

Simulation of the 1992 Tessina landslide by a cellular automata model and future hazard scenarios

NASA Astrophysics Data System (ADS)

Avolio, MV; Di Gregorio, Salvatore; Mantovani, Franco; Pasuto, Alessandro; Rongo, Rocco; Silvano, Sandro; Spataro, William

Cellular Automata are a powerful tool for modelling natural and artificial systems, which can be described in terms of local interactions of their constituent parts. Some types of landslides, such as debris/mud flows, match these requirements. The 1992 Tessina landslide has characteristics (slow mud flows) which make it appropriate for modelling by means of Cellular Automata, except for the initial phase of detachment, which is caused by a rotational movement that has no effect on the mud flow path. This paper presents the Cellular Automata approach for modelling slow mud/debris flows, the results of simulation of the 1992 Tessina landslide and future hazard scenarios based on the volumes of masses that could be mobilised in the future. They were obtained by adapting the Cellular Automata Model called SCIDDICA, which has been validated for very fast landslides. SCIDDICA was applied by modifying the general model to the peculiarities of the Tessina landslide. The simulations obtained by this initial model were satisfactory for forecasting the surface covered by mud. Calibration of the model, which was obtained from simulation of the 1992 event, was used for forecasting flow expansion during possible future reactivation. For this purpose two simulations concerning the collapse of about 1 million m 3 of material were tested. In one of these, the presence of a containment wall built in 1992 for the protection of the Tarcogna hamlet was inserted. The results obtained identified the conditions of high risk affecting the villages of Funes and Lamosano and show that this Cellular Automata approach can have a wide range of applications for different types of mud/debris flows.

Simulation of root forms using cellular automata model

NASA Astrophysics Data System (ADS)

Winarno, Nanang; Prima, Eka Cahya; Afifah, Ratih Mega Ayu

2016-02-01

This research aims to produce a simulation program for root forms using cellular automata model. Stephen Wolfram in his book entitled "A New Kind of Science" discusses the formation rules based on the statistical analysis. In accordance with Stephen Wolfram's investigation, the research will develop a basic idea of computer program using Delphi 7 programming language. To best of our knowledge, there is no previous research developing a simulation describing root forms using the cellular automata model compared to the natural root form with the presence of stone addition as the disturbance. The result shows that (1) the simulation used four rules comparing results of the program towards the natural photographs and each rule had shown different root forms; (2) the stone disturbances prevent the root growth and the multiplication of root forms had been successfully modeled. Therefore, this research had added some stones, which have size of 120 cells placed randomly in the soil. Like in nature, stones cannot be penetrated by plant roots. The result showed that it is very likely to further develop the program of simulating root forms by 50 variations.

Simulation of root forms using cellular automata model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Winarno, Nanang, E-mail: nanang-winarno@upi.edu; Prima, Eka Cahya; Afifah, Ratih Mega Ayu

This research aims to produce a simulation program for root forms using cellular automata model. Stephen Wolfram in his book entitled “A New Kind of Science” discusses the formation rules based on the statistical analysis. In accordance with Stephen Wolfram’s investigation, the research will develop a basic idea of computer program using Delphi 7 programming language. To best of our knowledge, there is no previous research developing a simulation describing root forms using the cellular automata model compared to the natural root form with the presence of stone addition as the disturbance. The result shows that (1) the simulation usedmore » four rules comparing results of the program towards the natural photographs and each rule had shown different root forms; (2) the stone disturbances prevent the root growth and the multiplication of root forms had been successfully modeled. Therefore, this research had added some stones, which have size of 120 cells placed randomly in the soil. Like in nature, stones cannot be penetrated by plant roots. The result showed that it is very likely to further develop the program of simulating root forms by 50 variations.« less

Growth and Decay in Life-Like Cellular Automata

NASA Astrophysics Data System (ADS)

Eppstein, David

Since the study of life began, many have asked: is it unique in the universe, or are there other interesting forms of life elsewhere? Before we can answer that question, we should ask others: What makes life special? If we happen across another system with life-like behavior, how would we be able to recognize it? We are speaking, of course, of the mathematical systems of cellular automata, of the fascinating patterns that have been discovered and engineered in Conway's Game of Life, and of the possible existence of other cellular automaton rules with equally complex behavior to that of Life.

Design of Improved Arithmetic Logic Unit in Quantum-Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Heikalabad, Saeed Rasouli; Gadim, Mahya Rahimpour

2018-06-01

The quantum-dot cellular automata (QCA) can be replaced to overcome the limitation of CMOS technology. An arithmetic logic unit (ALU) is a basic structure of any computer devices. In this paper, design of improved single-bit arithmetic logic unit in quantum dot cellular automata is presented. The proposed structure for ALU has AND, OR, XOR and ADD operations. A unique 2:1 multiplexer, an ultra-efficient two-input XOR and a low complexity full adder are used in the proposed structure. Also, an extended design of this structure is provided for two-bit ALU in this paper. The proposed structure of ALU is simulated by QCADesigner and simulation result is evaluated. Evaluation results show that the proposed design has best performance in terms of area, complexity and delay compared to the previous designs.

Design of Improved Arithmetic Logic Unit in Quantum-Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Heikalabad, Saeed Rasouli; Gadim, Mahya Rahimpour

2018-03-01

The quantum-dot cellular automata (QCA) can be replaced to overcome the limitation of CMOS technology. An arithmetic logic unit (ALU) is a basic structure of any computer devices. In this paper, design of improved single-bit arithmetic logic unit in quantum dot cellular automata is presented. The proposed structure for ALU has AND, OR, XOR and ADD operations. A unique 2:1 multiplexer, an ultra-efficient two-input XOR and a low complexity full adder are used in the proposed structure. Also, an extended design of this structure is provided for two-bit ALU in this paper. The proposed structure of ALU is simulated by QCADesigner and simulation result is evaluated. Evaluation results show that the proposed design has best performance in terms of area, complexity and delay compared to the previous designs.

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

On the derivation of approximations to cellular automata models and the assumption of independence.

PubMed

Davies, K J; Green, J E F; Bean, N G; Binder, B J; Ross, J V

2014-07-01

Cellular automata are discrete agent-based models, generally used in cell-based applications. There is much interest in obtaining continuum models that describe the mean behaviour of the agents in these models. Previously, continuum models have been derived for agents undergoing motility and proliferation processes, however, these models only hold under restricted conditions. In order to narrow down the reason for these restrictions, we explore three possible sources of error in deriving the model. These sources are the choice of limiting arguments, the use of a discrete-time model as opposed to a continuous-time model and the assumption of independence between the state of sites. We present a rigorous analysis in order to gain a greater understanding of the significance of these three issues. By finding a limiting regime that accurately approximates the conservation equation for the cellular automata, we are able to conclude that the inaccuracy between our approximation and the cellular automata is completely based on the assumption of independence. Copyright © 2014 Elsevier Inc. All rights reserved.

A class of cellular automata modeling winnerless competition

NASA Astrophysics Data System (ADS)

Afraimovich, V.; Ordaz, F. C.; Urías, J.

2002-06-01

Neural units introduced by Rabinovich et al. ("Sensory coding with dynamically competitive networks," UCSD and CIT, February 1999) motivate a class of cellular automata (CA) where spatio-temporal encoding is feasible. The spatio-temporal information capacity of a CA is estimated by the information capacity of the attractor set, which happens to be finitely specified. Two-dimensional CA are studied in detail. An example is given for which the attractor is not a subshift.

Self-organized perturbations enhance class IV behavior and 1/f power spectrum in elementary cellular automata.

PubMed

Nakajima, Kohei; Haruna, Taichi

2011-09-01

In this paper, we propose a new class of cellular automata based on the modification of its state space. It is introduced to model a computation which is exposed to an environment. We formalized the computation as extension and projection processes of its state space and resulting misidentifications of the state. This is motivated to embed the role of an environment into the system itself, which naturally induces self-organized internal perturbations rather than the usual external perturbations. Implementing this structure into the elementary cellular automata, we characterized its effect by means of input entropy and power spectral analysis. As a result, the cellular automata with this structure showed robust class IV behavior and a 1/f power spectrum in a wide range of rule space comparative to the notion of the edge of chaos. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Three-dimensional cellular automata as a model of a seismic fault

NASA Astrophysics Data System (ADS)

Gálvez, G.; Muñoz, A.

2017-01-01

The Earth's crust is broken into a series of plates, whose borders are the seismic fault lines and it is where most of the earthquakes occur. This plating system can in principle be described by a set of nonlinear coupled equations describing the motion of the plates, its stresses, strains and other characteristics. Such a system of equations is very difficult to solve, and nonlinear parts leads to a chaotic behavior, which is not predictable. In 1989, Bak and Tang presented an earthquake model based on the sand pile cellular automata. The model though simple, provides similar results to those observed in actual earthquakes. In this work the cellular automata in three dimensions is proposed as a best model to approximate a seismic fault. It is noted that the three-dimensional model reproduces similar properties to those observed in real seismicity, especially, the Gutenberg-Richter law.

Synchronization, TIGoRS, and Information Flow in Complex Systems: Dispositional Cellular Automata.

PubMed

Sulis, William H

2016-04-01

Synchronization has a long history in physics where it refers to the phase matching of two identical oscillators. This notion has been extensively studied in physics as well as in biology, where it has been applied to such widely varying phenomena as the flashing of fireflies and firing of neurons in the brain. Human behavior, however, may be recurrent but it is not oscillatory even though many physiological systems do exhibit oscillatory tendencies. Moreover, much of human behaviour is collaborative and cooperative, where the individual behaviours may be distinct yet contemporaneous (if not simultaneous) and taken collectively express some functionality. In the context of behaviour, the important aspect is the repeated co-occurrence in time of behaviours that facilitate the propagation of information or of functionality, regardless of whether or not these behaviours are similar or identical. An example of this weaker notion of synchronization is transient induced global response synchronization (TIGoRS). Previous work has shown that TIGoRS is a ubiquitous phenomenon among complex systems, enabling them to stably parse environmental transients into salient units to which they stably respond. This leads to the notion of Sulis machines, which emergently generate a primitive linguistic structure through their dynamics. This article reviews the notion of TIGoRS and its expression in several complex systems models including tempered neural networks, driven cellular automata and cocktail party automata. The emergent linguistics of Sulis machines are discussed. A new class of complex systems model, the dispositional cellular automaton is introduced. A new metric for TIGoRS, the excess synchronization, is introduced and applied to the study of TIGoRS in dispositional cellular automata. It is shown that these automata exhibit a nonlinear synchronization response to certain perturbing transients.

A Cellular Automata Model of Bone Formation

PubMed Central

Van Scoy, Gabrielle K.; George, Estee L.; Asantewaa, Flora Opoku; Kerns, Lucy; Saunders, Marnie M.; Prieto-Langarica, Alicia

2017-01-01

Bone remodeling is an elegantly orchestrated process by which osteocytes, osteoblasts and osteoclasts function as a syncytium to maintain or modify bone. On the microscopic level, bone consists of cells that create, destroy and monitor the bone matrix. These cells interact in a coordinated manner to maintain a tightly regulated homeostasis. It is this regulation that is responsible for the observed increase in bone gain in the dominant arm of a tennis player and the observed increase in bone loss associated with spaceflight and osteoporosis. The manner in which these cells interact to bring about a change in bone quality and quantity has yet to be fully elucidated. But efforts to understand the multicellular complexity can ultimately lead to eradication of metabolic bone diseases such as osteoporosis and improved implant longevity. Experimentally validated mathematical models that simulate functional activity and offer eventual predictive capabilities offer tremendous potential in understanding multicellular bone remodeling. Here we undertake the initial challenge to develop a mathematical model of bone formation validated with in vitro data obtained from osteoblastic bone cells induced to mineralize and quantified at 26 days of culture. A cellular automata model was constructed to simulate the in vitro characterization. Permutation tests were performed to compare the distribution of the mineralization in the cultures and the distribution of the mineralization in the mathematical models. The results of the permutation test show the distribution of mineralization from the characterization and mathematical model come from the same probability distribution, therefore validating the cellular automata model. PMID:28189632

A cellular automata model of bone formation.

PubMed

Van Scoy, Gabrielle K; George, Estee L; Opoku Asantewaa, Flora; Kerns, Lucy; Saunders, Marnie M; Prieto-Langarica, Alicia

2017-04-01

Bone remodeling is an elegantly orchestrated process by which osteocytes, osteoblasts and osteoclasts function as a syncytium to maintain or modify bone. On the microscopic level, bone consists of cells that create, destroy and monitor the bone matrix. These cells interact in a coordinated manner to maintain a tightly regulated homeostasis. It is this regulation that is responsible for the observed increase in bone gain in the dominant arm of a tennis player and the observed increase in bone loss associated with spaceflight and osteoporosis. The manner in which these cells interact to bring about a change in bone quality and quantity has yet to be fully elucidated. But efforts to understand the multicellular complexity can ultimately lead to eradication of metabolic bone diseases such as osteoporosis and improved implant longevity. Experimentally validated mathematical models that simulate functional activity and offer eventual predictive capabilities offer tremendous potential in understanding multicellular bone remodeling. Here we undertake the initial challenge to develop a mathematical model of bone formation validated with in vitro data obtained from osteoblastic bone cells induced to mineralize and quantified at 26 days of culture. A cellular automata model was constructed to simulate the in vitro characterization. Permutation tests were performed to compare the distribution of the mineralization in the cultures and the distribution of the mineralization in the mathematical models. The results of the permutation test show the distribution of mineralization from the characterization and mathematical model come from the same probability distribution, therefore validating the cellular automata model. Copyright © 2017 Elsevier Inc. All rights reserved.

Opinion evolution based on cellular automata rules in small world networks

NASA Astrophysics Data System (ADS)

Shi, Xiao-Ming; Shi, Lun; Zhang, Jie-Fang

2010-03-01

In this paper, we apply cellular automata rules, which can be given by a truth table, to human memory. We design each memory as a tracking survey mode that keeps the most recent three opinions. Each cellular automata rule, as a personal mechanism, gives the final ruling in one time period based on the data stored in one's memory. The key focus of the paper is to research the evolution of people's attitudes to the same question. Based on a great deal of empirical observations from computer simulations, all the rules can be classified into 20 groups. We highlight the fact that the phenomenon shown by some rules belonging to the same group will be altered within several steps by other rules in different groups. It is truly amazing that, compared with the last hundreds of presidential voting in America, the eras of important events in America's history coincide with the simulation results obtained by our model.

Parallel Implementation of Triangular Cellular Automata for Computing Two-Dimensional Elastodynamic Response on Arbitrary Domains

NASA Astrophysics Data System (ADS)

Leamy, Michael J.; Springer, Adam C.

In this research we report parallel implementation of a Cellular Automata-based simulation tool for computing elastodynamic response on complex, two-dimensional domains. Elastodynamic simulation using Cellular Automata (CA) has recently been presented as an alternative, inherently object-oriented technique for accurately and efficiently computing linear and nonlinear wave propagation in arbitrarily-shaped geometries. The local, autonomous nature of the method should lead to straight-forward and efficient parallelization. We address this notion on symmetric multiprocessor (SMP) hardware using a Java-based object-oriented CA code implementing triangular state machines (i.e., automata) and the MPI bindings written in Java (MPJ Express). We use MPJ Express to reconfigure our existing CA code to distribute a domain's automata to cores present on a dual quad-core shared-memory system (eight total processors). We note that this message passing parallelization strategy is directly applicable to computer clustered computing, which will be the focus of follow-on research. Results on the shared memory platform indicate nearly-ideal, linear speed-up. We conclude that the CA-based elastodynamic simulator is easily configured to run in parallel, and yields excellent speed-up on SMP hardware.

Evolution of Cellular Automata toward a LIFE-Like Rule Guided by 1/ƒ Noise

NASA Astrophysics Data System (ADS)

Ninagawa, Shigeru

There is evidence in favor of a relationship between the presence of 1/ƒ noise and computational universality in cellular automata. To confirm the relationship, we search for two-dimensional cellular automata with a 1/ƒ power spectrum by means of genetic algorithms. The power spectrum is calculated from the evolution of the state of the cell, starting from a random initial configuration. The fitness is estimated by the power spectrum with consideration of the spectral similarity to the 1/ƒ spectrum. The result shows that the rule with the highest fitness over the most runs exhibits a 1/ƒ type spectrum and its transition function and behavior are quite similar to those of the Game of Life, which is known to be a computationally universal cellular automaton. These results support the relationship between the presence of 1/ƒ noise and computational universality.

An authenticated image encryption scheme based on chaotic maps and memory cellular automata

NASA Astrophysics Data System (ADS)

Bakhshandeh, Atieh; Eslami, Ziba

2013-06-01

This paper introduces a new image encryption scheme based on chaotic maps, cellular automata and permutation-diffusion architecture. In the permutation phase, a piecewise linear chaotic map is utilized to confuse the plain-image and in the diffusion phase, we employ the Logistic map as well as a reversible memory cellular automata to obtain an efficient and secure cryptosystem. The proposed method admits advantages such as highly secure diffusion mechanism, computational efficiency and ease of implementation. A novel property of the proposed scheme is its authentication ability which can detect whether the image is tampered during the transmission or not. This is particularly important in applications where image data or part of it contains highly sensitive information. Results of various analyses manifest high security of this new method and its capability for practical image encryption.

Quantifying a cellular automata simulation of electric vehicles

NASA Astrophysics Data System (ADS)

Hill, Graeme; Bell, Margaret; Blythe, Phil

2014-12-01

Within this work the Nagel-Schreckenberg (NS) cellular automata is used to simulate a basic cyclic road network. Results from SwitchEV, a real world Electric Vehicle trial which has collected more than two years of detailed electric vehicle data, are used to quantify the results of the NS automata, demonstrating similar power consumption behavior to that observed in the experimental results. In particular the efficiency of the electric vehicles reduces as the vehicle density increases, due in part to the reduced efficiency of EVs at low speeds, but also due to the energy consumption inherent in changing speeds. Further work shows the results from introducing spatially restricted speed restriction. In general it can be seen that induced congestion from spatially transient events propagates back through the road network and alters the energy and efficiency profile of the simulated vehicles, both before and after the speed restriction. Vehicles upstream from the restriction show a reduced energy usage and an increased efficiency, and vehicles downstream show an initial large increase in energy usage as they accelerate away from the speed restriction.

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach

PubMed Central

2014-01-01

Background The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. Methods An epidemic is characterized trough an individual–based–model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. Results A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. Conclusions The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach.

PubMed

López, Leonardo; Burguerner, Germán; Giovanini, Leonardo

2014-04-12

The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. An epidemic is characterized trough an individual-based-model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the

A Study of Chaos in Cellular Automata

NASA Astrophysics Data System (ADS)

Kamilya, Supreeti; Das, Sukanta

This paper presents a study of chaos in one-dimensional cellular automata (CAs). The communication of information from one part of the system to another has been taken into consideration in this study. This communication is formalized as a binary relation over the set of cells. It is shown that this relation is an equivalence relation and all the cells form a single equivalence class when the cellular automaton (CA) is chaotic. However, the communication between two cells is sometimes blocked in some CAs by a subconfiguration which appears in between the cells during evolution. This blocking of communication by a subconfiguration has been analyzed in this paper with the help of de Bruijn graph. We identify two types of blocking — full and partial. Finally a parameter has been developed for the CAs. We show that the proposed parameter performs better than the existing parameters.

Cellular automata and epidemiological models with spatial dependence

NASA Astrophysics Data System (ADS)

Fuentes, M. A.; Kuperman, M. N.

We present a cellular automata model developed to study the evolution of an infectivity nucleus in several conditions and for two kinds of epidemiologically different diseases. We analyse the role of the model parameters, concerning the epidemiological and demographic aspects of the problem, and of the evolution rules in relation to the spread of such infectious diseases, the arising of periodic temporal modulations related to the infectivity and recovery fronts, and the evolution of travelling waves. Among the obtained results we find analogies to endemic situations and pandemics.

A cellular automata approach for modeling surface water runoff

NASA Astrophysics Data System (ADS)

Jozefik, Zoltan; Nanu Frechen, Tobias; Hinz, Christoph; Schmidt, Heiko

2015-04-01

This abstract reports the development and application of a two-dimensional cellular automata based model, which couples the dynamics of overland flow, infiltration processes and surface evolution through sediment transport. The natural hill slopes are represented by their topographic elevation and spatially varying soil properties infiltration rates and surface roughness coefficients. This model allows modeling of Hortonian overland flow and infiltration during complex rainfall events. An advantage of the cellular automata approach over the kinematic wave equations is that wet/dry interfaces that often appear with rainfall overland flows can be accurately captured and are not a source of numerical instabilities. An adaptive explicit time stepping scheme allows for rainfall events to be adequately resolved in time, while large time steps are taken during dry periods to provide for simulation run time efficiency. The time step is constrained by the CFL condition and mass conservation considerations. The spatial discretization is shown to be first-order accurate. For validation purposes, hydrographs for non-infiltrating and infiltrating plates are compared to the kinematic wave analytic solutions and data taken from literature [1,2]. Results show that our cellular automata model quantitatively accurately reproduces hydrograph patterns. However, recent works have showed that even through the hydrograph is satisfyingly reproduced, the flow field within the plot might be inaccurate [3]. For a more stringent validation, we compare steady state velocity, water flux, and water depth fields to rainfall simulation experiments conducted in Thies, Senegal [3]. Comparisons show that our model is able to accurately capture these flow properties. Currently, a sediment transport and deposition module is being implemented and tested. [1] M. Rousseau, O. Cerdan, O. Delestre, F. Dupros, F. James, S. Cordier. Overland flow modeling with the Shallow Water Equation using a well balanced

A cardiac electrical activity model based on a cellular automata system in comparison with neural network model.

PubMed

Khan, Muhammad Sadiq Ali; Yousuf, Sidrah

2016-03-01

Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each electrical activity during cardiac cycle should be monitor non-invasively for the assessment of "Action Potential" (regular) and "Arrhythmia" (irregular) rhythms. Many heart diseases can easily be examined through Automata model like Cellular Automata concepts. This paper deals with the different states of cardiac rhythms using cellular automata with the comparison of neural network also provides fast and highly effective stimulation for the contraction of cardiac muscles on the Atria in the result of genesis of electrical spark or wave. The specific formulated model named as "States of automaton Proposed Model for CEA (Cardiac Electrical Activity)" by using Cellular Automata Methodology is commonly shows the three states of cardiac tissues conduction phenomena (i) Resting (Relax and Excitable state), (ii) ARP (Excited but Absolutely refractory Phase i.e. Excited but not able to excite neighboring cells) (iii) RRP (Excited but Relatively Refractory Phase i.e. Excited and able to excite neighboring cells). The result indicates most efficient modeling with few burden of computation and it is Action Potential during the pumping of blood in cardiac cycle.

Stair evacuation simulation based on cellular automata considering evacuees’ walk preferences

NASA Astrophysics Data System (ADS)

Ding, Ning; Zhang, Hui; Chen, Tao; Peter, B. Luh

2015-06-01

As a physical model, the cellular automata (CA) model is widely used in many areas, such as stair evacuation. However, existing CA models do not consider evacuees’ walk preferences nor psychological status, and the structure of the basic model is unapplicable for the stair structure. This paper is to improve the stair evacuation simulation by addressing these issues, and a new cellular automata model is established. Several evacuees’ walk preference and how evacuee’s psychology influences their behaviors are introduced into this model. Evacuees’ speeds will be influenced by these features. To validate this simulation, two fire drills held in two high-rise buildings are video-recorded. It is found that the simulation results are similar to the fire drill results. The structure of this model is simple, and it is easy to further develop and utilize in different buildings with various kinds of occupants. Project supported by the National Basic Research Program of China (Grant No. 2012CB719705) and the National Natural Science Foundation of China (Grant Nos. 91224008, 91024032, and 71373139).

Computing aggregate properties of preimages for 2D cellular automata.

PubMed

Beer, Randall D

2017-11-01

Computing properties of the set of precursors of a given configuration is a common problem underlying many important questions about cellular automata. Unfortunately, such computations quickly become intractable in dimension greater than one. This paper presents an algorithm-incremental aggregation-that can compute aggregate properties of the set of precursors exponentially faster than naïve approaches. The incremental aggregation algorithm is demonstrated on two problems from the two-dimensional binary Game of Life cellular automaton: precursor count distributions and higher-order mean field theory coefficients. In both cases, incremental aggregation allows us to obtain new results that were previously beyond reach.

Computing aggregate properties of preimages for 2D cellular automata

NASA Astrophysics Data System (ADS)

Beer, Randall D.

2017-11-01

Computing properties of the set of precursors of a given configuration is a common problem underlying many important questions about cellular automata. Unfortunately, such computations quickly become intractable in dimension greater than one. This paper presents an algorithm—incremental aggregation—that can compute aggregate properties of the set of precursors exponentially faster than naïve approaches. The incremental aggregation algorithm is demonstrated on two problems from the two-dimensional binary Game of Life cellular automaton: precursor count distributions and higher-order mean field theory coefficients. In both cases, incremental aggregation allows us to obtain new results that were previously beyond reach.

Simulations of Living Cell Origins Using a Cellular Automata Model

NASA Astrophysics Data System (ADS)

Ishida, Takeshi

2014-04-01

Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

Simulations of living cell origins using a cellular automata model.

PubMed

Ishida, Takeshi

2014-04-01

Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

Stochastic cellular automata model of cell migration, proliferation and differentiation: validation with in vitro cultures of muscle satellite cells.

PubMed

Garijo, N; Manzano, R; Osta, R; Perez, M A

2012-12-07

Cell migration and proliferation has been modelled in the literature as a process similar to diffusion. However, using diffusion models to simulate the proliferation and migration of cells tends to create a homogeneous distribution in the cell density that does not correlate to empirical observations. In fact, the mechanism of cell dispersal is not diffusion. Cells disperse by crawling or proliferation, or are transported in a moving fluid. The use of cellular automata, particle models or cell-based models can overcome this limitation. This paper presents a stochastic cellular automata model to simulate the proliferation, migration and differentiation of cells. These processes are considered as completely stochastic as well as discrete. The model developed was applied to predict the behaviour of in vitro cell cultures performed with adult muscle satellite cells. Moreover, non homogeneous distribution of cells has been observed inside the culture well and, using the above mentioned stochastic cellular automata model, we have been able to predict this heterogeneous cell distribution and compute accurate quantitative results. Differentiation was also incorporated into the computational simulation. The results predicted the myotube formation that typically occurs with adult muscle satellite cells. In conclusion, we have shown how a stochastic cellular automata model can be implemented and is capable of reproducing the in vitro behaviour of adult muscle satellite cells. Copyright © 2012 Elsevier Ltd. All rights reserved.

Computer simulation of a cellular automata model for the immune response in a retrovirus system

NASA Astrophysics Data System (ADS)

Pandey, R. B.

1989-02-01

Immune response in a retrovirus system is modeled by a network of three binary cell elements to take into account some of the main functional features of T4 cells, T8 cells, and viruses. Two different intercell interactions are introduced, one of which leads to three fixed points while the other yields bistable fixed points oscillating between a healthy state and a sick state in a mean field treatment. Evolution of these cells is studied for quenched and annealed random interactions on a simple cubic lattice with a nearest neighbor interaction using inhomogenous cellular automata. Populations of T4 cells and viral cells oscillate together with damping (with constant amplitude) for annealed (quenched) interaction on increasing the value of mixing probability B from zero to a characteristic value B ca ( B cq). For higher B, the average number of T4 cells increases while that of the viral infected cells decreases monotonically on increasing B, suggesting a phase transition at B ca ( B cq).

From QCA (Quantum Cellular Automata) to Organocatalytic Reactions with Stabilized Carbenium Ions.

PubMed

Gualandi, Andrea; Mengozzi, Luca; Manoni, Elisabetta; Giorgio Cozzi, Pier

2016-06-01

What do quantum cellular automata (QCA), "on water" reactions, and SN 1-type organocatalytic transformations have in common? The link between these distant arguments is the practical access to useful intermediates and key products through the use of stabilized carbenium ions. Over 10 years, starting with a carbenium ion bearing a ferrocenyl group, to the 1,3-benzodithiolylium carbenium ion, our group has exploited the use of these intermediates in useful and practical synthetic transformations. In particular, we have applied the use of carbenium ions to stereoselective organocatalytic alkylation reactions, showing a possible solution for the "holy grail of organocatalysis". Examples of the use of these quite stabilized intermediates are now also considered in organometallic chemistry. On the other hand, the stable carbenium ions are also applied to tailored molecules adapted to quantum cellular automata, a new possible paradigm for computation. Carbenium ions are not a problem, they can be a/the solution! © 2016 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modeling of urban growth using cellular automata (CA) optimized by Particle Swarm Optimization (PSO)

NASA Astrophysics Data System (ADS)

Khalilnia, M. H.; Ghaemirad, T.; Abbaspour, R. A.

2013-09-01

In this paper, two satellite images of Tehran, the capital city of Iran, which were taken by TM and ETM+ for years 1988 and 2010 are used as the base information layers to study the changes in urban patterns of this metropolis. The patterns of urban growth for the city of Tehran are extracted in a period of twelve years using cellular automata setting the logistic regression functions as transition functions. Furthermore, the weighting coefficients of parameters affecting the urban growth, i.e. distance from urban centers, distance from rural centers, distance from agricultural centers, and neighborhood effects were selected using PSO. In order to evaluate the results of the prediction, the percent correct match index is calculated. According to the results, by combining optimization techniques with cellular automata model, the urban growth patterns can be predicted with accuracy up to 75 %.

A dynamically reconfigurable logic cell: from artificial neural networks to quantum-dot cellular automata

NASA Astrophysics Data System (ADS)

Naqvi, Syed Rameez; Akram, Tallha; Iqbal, Saba; Haider, Sajjad Ali; Kamran, Muhammad; Muhammad, Nazeer

2018-02-01

Considering the lack of optimization support for Quantum-dot Cellular Automata, we propose a dynamically reconfigurable logic cell capable of implementing various logic operations by means of artificial neural networks. The cell can be reconfigured to any 2-input combinational logic gate by altering the strength of connections, called weights and biases. We demonstrate how these cells may appositely be organized to perform multi-bit arithmetic and logic operations. The proposed work is important in that it gives a standard implementation of an 8-bit arithmetic and logic unit for quantum-dot cellular automata with minimal area and latency overhead. We also compare the proposed design with a few existing arithmetic and logic units, and show that it is more area efficient than any equivalent available in literature. Furthermore, the design is adaptable to 16, 32, and 64 bit architectures.

Simulation of elastic wave propagation using cellular automata and peridynamics, and comparison with experiments

DOE PAGES

Nishawala, Vinesh V.; Ostoja-Starzewski, Martin; Leamy, Michael J.; ...

2015-09-10

Peridynamics is a non-local continuum mechanics formulation that can handle spatial discontinuities as the governing equations are integro-differential equations which do not involve gradients such as strains and deformation rates. This paper employs bond-based peridynamics. Cellular Automata is a local computational method which, in its rectangular variant on interior domains, is mathematically equivalent to the central difference finite difference method. However, cellular automata does not require the derivation of the governing partial differential equations and provides for common boundary conditions based on physical reasoning. Both methodologies are used to solve a half-space subjected to a normal load, known as Lamb’smore » Problem. The results are compared with theoretical solution from classical elasticity and experimental results. Furthermore, this paper is used to validate our implementation of these methods.« less

Traffic jam dynamics in stochastic cellular automata

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nagel, K.; Schreckenberg, M.

1995-09-01

Simple models for particles hopping on a grid (cellular automata) are used to simulate (single lane) traffic flow. Despite their simplicity, these models are astonishingly realistic in reproducing start-stop-waves and realistic fundamental diagrams. One can use these models to investigate traffic phenomena near maximum flow. A so-called phase transition at average maximum flow is visible in the life-times of jams. The resulting dynamic picture is consistent with recent fluid-dynamical results by Kuehne/Kerner/Konhaeuser, and with Treiterer`s hysteresis description. This places CA models between car-following models and fluid-dynamical models for traffic flow. CA models are tested in projects in Los Alamos (USA)more » and in NRW (Germany) for large scale microsimulations of network traffic.« less

Multilane Traffic Flow Modeling Using Cellular Automata Theory

NASA Astrophysics Data System (ADS)

Chechina, Antonina; Churbanova, Natalia; Trapeznikova, Marina

2018-02-01

The paper deals with the mathematical modeling of traffic flows on urban road networks using microscopic approach. The model is based on the cellular automata theory and presents a generalization of the Nagel-Schreckenberg model to a multilane case. The created program package allows to simulate traffic on various types of road fragments (T or X type intersection, strait road elements, etc.) and on road networks that consist of these elements. Besides that, it allows to predict the consequences of various decisions regarding road infrastructure changes, such as: number of lanes increasing/decreasing, putting new traffic lights into operation, building new roads, entrances/exits, road junctions.

Reversible Flip-Flops in Quantum-Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Rad, Samaneh Kazemi; Heikalabad, Saeed Rasouli

2017-09-01

Quantum-dot cellular automata is a new technology to design the efficient combinational and sequential circuits at the nano-scale. This technology has many desirable advantages compared to the CMOS technology such as low power consumption, less occupation area and low latency. These features make it suitable for use in flip-flop design. In this paper, with knowing the characteristics of reversible logic, we design new structures for flip-flops. The operations of these structures are evaluated with QCADesigner Version 2.0.3 simulator. In addition, we calculate the power dissipation of these structures by QCAPro tool. The results illustrated that proposed structures are efficient compared to the previous ones.

Fire and Heat Spreading Model Based on Cellular Automata Theory

NASA Astrophysics Data System (ADS)

Samartsev, A. A.; Rezchikov, A. F.; Kushnikov, V. A.; Ivashchenko, V. A.; Bogomolov, A. S.; Filimonyuk, L. Yu; Dolinina, O. N.; Kushnikov, O. V.; Shulga, T. E.; Tverdokhlebov, V. A.; Fominykh, D. S.

2018-05-01

The distinctive feature of the proposed fire and heat spreading model in premises is the reduction of the computational complexity due to the use of the theory of cellular automata with probability rules of behavior. The possibilities and prospects of using this model in practice are noted. The proposed model has a simple mechanism of integration with agent-based evacuation models. The joint use of these models could improve floor plans and reduce the time of evacuation from premises during fires.

Energy dissipation dataset for reversible logic gates in quantum dot-cellular automata.

PubMed

Bahar, Ali Newaz; Rahman, Mohammad Maksudur; Nahid, Nur Mohammad; Hassan, Md Kamrul

2017-02-01

This paper presents an energy dissipation dataset of different reversible logic gates in quantum-dot cellular automata. The proposed circuits have been designed and verified using QCADesigner simulator. Besides, the energy dissipation has been calculated under three different tunneling energy level at temperature T =2 K. For estimating the energy dissipation of proposed gates; QCAPro tool has been employed.

Mosquito population dynamics from cellular automata-based simulation

NASA Astrophysics Data System (ADS)

Syafarina, Inna; Sadikin, Rifki; Nuraini, Nuning

2016-02-01

In this paper we present an innovative model for simulating mosquito-vector population dynamics. The simulation consist of two stages: demography and dispersal dynamics. For demography simulation, we follow the existing model for modeling a mosquito life cycles. Moreover, we use cellular automata-based model for simulating dispersal of the vector. In simulation, each individual vector is able to move to other grid based on a random walk. Our model is also capable to represent immunity factor for each grid. We simulate the model to evaluate its correctness. Based on the simulations, we can conclude that our model is correct. However, our model need to be improved to find a realistic parameters to match real data.

Computer simulation of a cellular automata model for the immune response in a retrovirus system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pandey, R.B.

1989-02-01

Immune response in a retrovirus system is modeled by a network of three binary cell elements to take into account some of the main functional features of T4 cells, T8 cells, and viruses. Two different intercell interactions are introduced, one of which leads to three fixed points while the other yields bistable fixed points oscillating between a healthy state and a sick state in a mean field treatment. Evolution of these cells is studied for quenched and annealed random interactions on a simple cubic lattice with a nearest neighbor interaction using inhomogenous cellular automata. Populations of T4 cells and viralmore » cells oscillate together with damping (with constant amplitude) for annealed (quenched) interaction on increasing the value of mixing probability B from zero to a characteristic value B/sub ca/ (B/sub cq/). For higher B, the average number of T4 cells increases while that of the viral infected cells decreases monotonically on increasing B, suggesting a phase transition at B/sub ca/ (B/sub cq/).« less

Evolution of cellular automata with memory: The Density Classification Task.

PubMed

Stone, Christopher; Bull, Larry

2009-08-01

The Density Classification Task is a well known test problem for two-state discrete dynamical systems. For many years researchers have used a variety of evolutionary computation approaches to evolve solutions to this problem. In this paper, we investigate the evolvability of solutions when the underlying Cellular Automaton is augmented with a type of memory based on the Least Mean Square algorithm. To obtain high performance solutions using a simple non-hybrid genetic algorithm, we design a novel representation based on the ternary representation used for Learning Classifier Systems. The new representation is found able to produce superior performance to the bit string traditionally used for representing Cellular automata. Moreover, memory is shown to improve evolvability of solutions and appropriate memory settings are able to be evolved as a component part of these solutions.

The Neurona at Home project: Simulating a large-scale cellular automata brain in a distributed computing environment

NASA Astrophysics Data System (ADS)

Acedo, L.; Villanueva-Oller, J.; Moraño, J. A.; Villanueva, R.-J.

2013-01-01

The Berkeley Open Infrastructure for Network Computing (BOINC) has become the standard open source solution for grid computing in the Internet. Volunteers use their computers to complete an small part of the task assigned by a dedicated server. We have developed a BOINC project called Neurona@Home whose objective is to simulate a cellular automata random network with, at least, one million neurons. We consider a cellular automata version of the integrate-and-fire model in which excitatory and inhibitory nodes can activate or deactivate neighbor nodes according to a set of probabilistic rules. Our aim is to determine the phase diagram of the model and its behaviour and to compare it with the electroencephalographic signals measured in real brains.

Cellular automata model for traffic flow at intersections in internet of vehicles

NASA Astrophysics Data System (ADS)

Zhao, Han-Tao; Liu, Xin-Ru; Chen, Xiao-Xu; Lu, Jian-Cheng

2018-03-01

Considering the effect of the front vehicle's speed, the influence of the brake light and the conflict of the traffic flow, we established a cellular automata model called CE-NS for traffic flow at the intersection in the non-vehicle networking environment. According to the information interaction of Internet of Vehicles (IoV), introducing parameters describing the congestion and the accurate speed of the front vehicle into the CE-NS model, we improved the rules of acceleration, deceleration and conflict, and finally established a cellular automata model for traffic flow at intersections of IoV. The relationship between traffic parameters such as vehicle speed, flow and average travel time is obtained by numerical simulation of two models. Based on this, we compared the traffic situation of the non-vehicle networking environment with conditions of IoV environment, and analyzed the influence of the different degree of IoV on the traffic flow. The results show that the traffic speed is increased, the travel time is reduced, the flux of intersections is increased and the traffic flow is more smoothly under IoV environment. After the vehicle which achieves IoV reaches a certain proportion, the operation effect of the traffic flow begins to improve obviously.

Simple and Flexible Self-Reproducing Structures in Asynchronous Cellular Automata and Their Dynamics

NASA Astrophysics Data System (ADS)

Huang, Xin; Lee, Jia; Yang, Rui-Long; Zhu, Qing-Sheng

2013-03-01

Self-reproduction on asynchronous cellular automata (ACAs) has attracted wide attention due to the evident artifacts induced by synchronous updating. Asynchronous updating, which allows cells to undergo transitions independently at random times, might be more compatible with the natural processes occurring at micro-scale, but the dark side of the coin is the increment in the complexity of an ACA in order to accomplish stable self-reproduction. This paper proposes a novel model of self-timed cellular automata (STCAs), a special type of ACAs, where unsheathed loops are able to duplicate themselves reliably in parallel. The removal of sheath cannot only allow various loops with more flexible and compact structures to replicate themselves, but also reduce the number of cell states of the STCA as compared to the previous model adopting sheathed loops [Y. Takada, T. Isokawa, F. Peper and N. Matsui, Physica D227, 26 (2007)]. The lack of sheath, on the other hand, often tends to cause much more complicated interactions among loops, when all of them struggle independently to stretch out their constructing arms at the same time. In particular, such intense collisions may even cause the emergence of a mess of twisted constructing arms in the cellular space. By using a simple and natural method, our self-reproducing loops (SRLs) are able to retract their arms successively, thereby disentangling from the mess successfully.

A Cellular Automata Model of Infection Control on Medical Implants

PubMed Central

Prieto-Langarica, Alicia; Kojouharov, Hristo; Chen-Charpentier, Benito; Tang, Liping

2011-01-01

S. epidermidis infections on medically implanted devices are a common problem in modern medicine due to the abundance of the bacteria. Once inside the body, S. epidermidis gather in communities called biofilms and can become extremely hard to eradicate, causing the patient serious complications. We simulate the complex S. epidermidis-Neutrophils interactions in order to determine the optimum conditions for the immune system to be able to contain the infection and avoid implant rejection. Our cellular automata model can also be used as a tool for determining the optimal amount of antibiotics for combating biofilm formation on medical implants. PMID:23543851

Collective dynamics in heterogeneous networks of neuronal cellular automata

NASA Astrophysics Data System (ADS)

Manchanda, Kaustubh; Bose, Amitabha; Ramaswamy, Ramakrishna

2017-12-01

We examine the collective dynamics of heterogeneous random networks of model neuronal cellular automata. Each automaton has b active states, a single silent state and r - b - 1 refractory states, and can show 'spiking' or 'bursting' behavior, depending on the values of b. We show that phase transitions that occur in the dynamical activity can be related to phase transitions in the structure of Erdõs-Rényi graphs as a function of edge probability. Different forms of heterogeneity allow distinct structural phase transitions to become relevant. We also show that the dynamics on the network can be described by a semi-annealed process and, as a result, can be related to the Boolean Lyapunov exponent.

Jahn-Teller effect in molecular electronics: quantum cellular automata

NASA Astrophysics Data System (ADS)

Tsukerblat, B.; Palii, A.; Clemente-Juan, J. M.; Coronado, E.

2017-05-01

The article summarizes the main results of application of the theory of the Jahn-Teller (JT) and pseudo JT effects to the description of molecular quantum dot cellular automata (QCA), a new paradigm of quantum computing. The following issues are discussed: 1) QCA as a new paradigm of quantum computing, principles and advantages; 2) molecular implementation of QCA; 3) role of the JT effect in charge trapping, encoding of binary information in the quantum cell and non-linear cell-cell response; 4) spin-switching in molecular QCA based on mixed-valence cell; 5) intervalence optical absorption in tetrameric molecular mixed-valence cell through the symmetry assisted approach to the multimode/multilevel JT and pseudo JT problems.

Cellular automata approach for the dynamics of HIV infection under antiretroviral therapies: The role of the virus diffusion

NASA Astrophysics Data System (ADS)

González, Ramón E. R.; de Figueirêdo, Pedro Hugo; Coutinho, Sérgio

2013-10-01

We study a cellular automata model to test the timing of antiretroviral therapy strategies for the dynamics of infection with human immunodeficiency virus (HIV). We focus on the role of virus diffusion when its population is included in previous cellular automata model that describes the dynamics of the lymphocytes cells population during infection. This inclusion allows us to consider the spread of infection by the virus-cell interaction, beyond that which occurs by cell-cell contagion. The results show an acceleration of the infectious process in the absence of treatment, but show better efficiency in reducing the risk of the onset of AIDS when combined antiretroviral therapies are used even with drugs of low effectiveness. Comparison of results with clinical data supports the conclusions of this study.

Cellular automata model for human articular chondrocytes migration, proliferation and cell death: An in vitro validation.

PubMed

Vaca-González, J J; Gutiérrez, M L; Guevara, J M; Garzón-Alvarado, D A

2017-01-01

Articular cartilage is characterized by low cell density of only one cell type, chondrocytes, and has limited self-healing properties. When articular cartilage is affected by traumatic injuries, a therapeutic strategy such as autologous chondrocyte implantation is usually proposed for its treatment. This approach requires in vitro chondrocyte expansion to yield high cell number for cell transplantation. To improve the efficiency of this procedure, it is necessary to assess cell dynamics such as migration, proliferation and cell death during culture. Computational models such as cellular automata can be used to simulate cell dynamics in order to enhance the result of cell culture procedures. This methodology has been implemented for several cell types; however, an experimental validation is required for each one. For this reason, in this research a cellular automata model, based on random-walk theory, was devised in order to predict articular chondrocyte behavior in monolayer culture during cell expansion. Results demonstrated that the cellular automata model corresponded to cell dynamics and computed-accurate quantitative results. Moreover, it was possible to observe that cell dynamics depend on weighted probabilities derived from experimental data and cell behavior varies according to the cell culture period. Thus, depending on whether cells were just seeded or proliferated exponentially, culture time probabilities differed in percentages in the CA model. Furthermore, in the experimental assessment a decreased chondrocyte proliferation was observed along with increased passage number. This approach is expected to having other uses as in enhancing articular cartilage therapies based on tissue engineering and regenerative medicine.

The Design of Fault Tolerant Quantum Dot Cellular Automata Based Logic

NASA Technical Reports Server (NTRS)

Armstrong, C. Duane; Humphreys, William M.; Fijany, Amir

2002-01-01

As transistor geometries are reduced, quantum effects begin to dominate device performance. At some point, transistors cease to have the properties that make them useful computational components. New computing elements must be developed in order to keep pace with Moore s Law. Quantum dot cellular automata (QCA) represent an alternative paradigm to transistor-based logic. QCA architectures that are robust to manufacturing tolerances and defects must be developed. We are developing software that allows the exploration of fault tolerant QCA gate architectures by automating the specification, simulation, analysis and documentation processes.

A cellular automata model of land cover change to integrate urban growth with open space conservation

EPA Science Inventory

The preservation of riparian zones and other environmentally sensitive areas has long been recognized as one of the most cost-effective methods of managing stormwater and providing a broad range of ecosystem services. In this research, a cellular automata (CA)—Markov chain model ...

Facilitating arrhythmia simulation: the method of quantitative cellular automata modeling and parallel running

PubMed Central

Zhu, Hao; Sun, Yan; Rajagopal, Gunaretnam; Mondry, Adrian; Dhar, Pawan

2004-01-01

Background Many arrhythmias are triggered by abnormal electrical activity at the ionic channel and cell level, and then evolve spatio-temporally within the heart. To understand arrhythmias better and to diagnose them more precisely by their ECG waveforms, a whole-heart model is required to explore the association between the massively parallel activities at the channel/cell level and the integrative electrophysiological phenomena at organ level. Methods We have developed a method to build large-scale electrophysiological models by using extended cellular automata, and to run such models on a cluster of shared memory machines. We describe here the method, including the extension of a language-based cellular automaton to implement quantitative computing, the building of a whole-heart model with Visible Human Project data, the parallelization of the model on a cluster of shared memory computers with OpenMP and MPI hybrid programming, and a simulation algorithm that links cellular activity with the ECG. Results We demonstrate that electrical activities at channel, cell, and organ levels can be traced and captured conveniently in our extended cellular automaton system. Examples of some ECG waveforms simulated with a 2-D slice are given to support the ECG simulation algorithm. A performance evaluation of the 3-D model on a four-node cluster is also given. Conclusions Quantitative multicellular modeling with extended cellular automata is a highly efficient and widely applicable method to weave experimental data at different levels into computational models. This process can be used to investigate complex and collective biological activities that can be described neither by their governing differentiation equations nor by discrete parallel computation. Transparent cluster computing is a convenient and effective method to make time-consuming simulation feasible. Arrhythmias, as a typical case, can be effectively simulated with the methods described. PMID:15339335

Gaussian Mean Field Lattice Gas

NASA Astrophysics Data System (ADS)

Scoppola, Benedetto; Troiani, Alessio

2018-03-01

We study rigorously a lattice gas version of the Sherrington-Kirckpatrick spin glass model. In discrete optimization literature this problem is known as unconstrained binary quadratic programming and it belongs to the class NP-hard. We prove that the fluctuations of the ground state energy tend to vanish in the thermodynamic limit, and we give a lower bound of such ground state energy. Then we present a heuristic algorithm, based on a probabilistic cellular automaton, which seems to be able to find configurations with energy very close to the minimum, even for quite large instances.

Simulations of Forest Fires by the Cellular Automata Model "ABBAMPAU"

NASA Astrophysics Data System (ADS)

di Gregorio, S.; Bendicenti, E.

2003-04-01

Forest fires represent a serious environmental problem, whose negative impact is becoming day by day more worrisome. Forest fires are very complex phenomena; that need an interdisciplinary approach. The adopted method to modelling involves the definition of local rules, from which the global behaviour of the system can emerge. The paradigm of Cellular Automata was applied and the model ABBAMPAU was projected to simulate the evolution of forest fires. Cellular Automata features (parallelism and a-centrism) seem to match the system "forest fire"; the parameters, describing globally a forest fire, i.e. propagation rate, flame length and direction, fireline intensity, fire duration time et c. are mainly depending on some local characteristics i.e. vegetation type (live and dead fuel), relative humidity, fuel moisture, heat, territory morphology (altitude, slope), et c.. The only global characteristic is given by wind velocity and direction, but wind velocity and direction is locally altered according to the morphology; therefore wind has also to be considered at local level. ABBAMPAU accounts for the following aspects of the phenomenon: effects of combustion in surface and crown fire inside the cell, crown fire triggering off; surface and crown fire spread, determination of the local wind rate and direction. A validation of ABBAMPAU was tested on a real case of forest fire, in the territory of Villaputzu, Sardinia island, August 22nd, 1998. First simulations account for the main characteristics of the phenomenon and agree with the observations. The results show that the model could be applied for the forest fire preventions, the productions of risk scenarios and the evaluation of the forest fire environmental impact.

An Asynchronous Cellular Automata-Based Adaptive Illumination Facility

NASA Astrophysics Data System (ADS)

Bandini, Stefania; Bonomi, Andrea; Vizzari, Giuseppe; Acconci, Vito

The term Ambient Intelligence refers to electronic environments that are sensitive and responsive to the presence of people; in the described scenario the environment itself is endowed with a set of sensors (to perceive humans or other physical entities such as dogs, bicycles, etc.), interacting with a set of actuators (lights) that choose their actions (i.e. state of illumination) in an attempt improve the overall experience of these users. The model for the interaction and action of sensors and actuators is an asynchronous Cellular Automata (CA) with memory, supporting a self-organization of the system as a response to the presence and movements of people inside it. The paper will introduce the model, as well as an ad hoc user interface for the specification of the relevant parameters of the CA transition rule that determines the overall system behaviour.

A new cellular automata model of traffic flow with negative exponential weighted look-ahead potential

NASA Astrophysics Data System (ADS)

Ma, Xiao; Zheng, Wei-Fan; Jiang, Bao-Shan; Zhang, Ji-Ye

2016-10-01

With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations. Project supported by the National Natural Science Foundation of China (Grant Nos. 11572264, 11172247, 11402214, and 61373009).

Free Quantum Field Theory from Quantum Cellular Automata

NASA Astrophysics Data System (ADS)

Bisio, Alessandro; D'Ariano, Giacomo Mauro; Perinotti, Paolo; Tosini, Alessandro

2015-10-01

After leading to a new axiomatic derivation of quantum theory (see D'Ariano et al. in Found Phys, 2015), the new informational paradigm is entering the domain of quantum field theory, suggesting a quantum automata framework that can be regarded as an extension of quantum field theory to including an hypothetical Planck scale, and with the usual quantum field theory recovered in the relativistic limit of small wave-vectors. Being derived from simple principles (linearity, unitarity, locality, homogeneity, isotropy, and minimality of dimension), the automata theory is quantum ab-initio, and does not assume Lorentz covariance and mechanical notions. Being discrete it can describe localized states and measurements (unmanageable by quantum field theory), solving all the issues plaguing field theory originated from the continuum. These features make the theory an ideal framework for quantum gravity, with relativistic covariance and space-time emergent solely from the interactions, and not assumed a priori. The paper presents a synthetic derivation of the automata theory, showing how the principles lead to a description in terms of a quantum automaton over a Cayley graph of a group. Restricting to Abelian groups we show how the automata recover the Weyl, Dirac and Maxwell dynamics in the relativistic limit. We conclude with some new routes about the more general scenario of non-Abelian Cayley graphs. The phenomenology arising from the automata theory in the ultra-relativistic domain and the analysis of corresponding distorted Lorentz covariance is reviewed in Bisio et al. (Found Phys 2015, in this same issue).

An energy and cost efficient majority-based RAM cell in quantum-dot cellular automata

NASA Astrophysics Data System (ADS)

Khosroshahy, Milad Bagherian; Moaiyeri, Mohammad Hossein; Navi, Keivan; Bagherzadeh, Nader

Nanotechnologies, notably quantum-dot cellular automata, have achieved major attentions for their prominent features as compared to the conventional CMOS circuitry. Quantum-dot cellular automata, particularly owning to its considerable reduction in size, high switching speed and ultra-low energy consumption, is considered as a potential alternative for the CMOS technology. As the memory unit is one of the most essential components in a digital system, designing a well-optimized QCA random access memory (RAM) cell is an important area of research. In this paper, a new five-input majority gate is presented which is suitable for implementing efficient single-layer QCA circuits. In addition, a new RAM cell with set and reset capabilities is designed based on the proposed majority gate, which has an efficient and low-energy structure. The functionality, performance and energy consumption of the proposed designs are evaluated based on the QCADesigner and QCAPro tools. According to the simulation results, the proposed RAM design leads to on average 38% lower total energy dissipation, 25% smaller area, 20% lower cell count, 28% lower delay and 60% lower QCA cost as compared to its previous counterparts.

Dynamic Simulation of 1D Cellular Automata in the Active aTAM.

PubMed

Jonoska, Nataša; Karpenko, Daria; Seki, Shinnosuke

2015-07-01

The Active aTAM is a tile based model for self-assembly where tiles are able to transfer signals and change identities according to the signals received. We extend Active aTAM to include deactivation signals and thereby allow detachment of tiles. We show that the model allows a dynamic simulation of cellular automata with assemblies that do not record the entire computational history but only the current updates of the states, and thus provide a way for (a) algorithmic dynamical structural changes in the assembly and (b) reusable space in self-assembly. The simulation is such that at a given location the sequence of tiles that attach and detach corresponds precisely to the sequence of states the synchronous cellular automaton generates at that location.

Dynamic Simulation of 1D Cellular Automata in the Active aTAM

PubMed Central

Jonoska, Nataša; Karpenko, Daria; Seki, Shinnosuke

2016-01-01

The Active aTAM is a tile based model for self-assembly where tiles are able to transfer signals and change identities according to the signals received. We extend Active aTAM to include deactivation signals and thereby allow detachment of tiles. We show that the model allows a dynamic simulation of cellular automata with assemblies that do not record the entire computational history but only the current updates of the states, and thus provide a way for (a) algorithmic dynamical structural changes in the assembly and (b) reusable space in self-assembly. The simulation is such that at a given location the sequence of tiles that attach and detach corresponds precisely to the sequence of states the synchronous cellular automaton generates at that location. PMID:27789918

Iterons, fractals and computations of automata

NASA Astrophysics Data System (ADS)

Siwak, Paweł

1999-03-01

Processing of strings by some automata, when viewed on space-time (ST) diagrams, reveals characteristic soliton-like coherent periodic objects. They are inherently associated with iterations of automata mappings thus we call them the iterons. In the paper we present two classes of one-dimensional iterons: particles and filtrons. The particles are typical for parallel (cellular) processing, while filtrons, introduced in (32) are specific for serial processing of strings. In general, the images of iterated automata mappings exhibit not only coherent entities but also the fractals, and quasi-periodic and chaotic dynamics. We show typical images of such computations: fractals, multiplication by a number, and addition of binary numbers defined by a Turing machine. Then, the particles are presented as iterons generated by cellular automata in three computations: B/U code conversion (13, 29), majority classification (9), and in discrete version of the FPU (Fermi-Pasta-Ulam) dynamics (7, 23). We disclose particles by a technique of combinational recoding of ST diagrams (as opposed to sequential recoding). Subsequently, we recall the recursive filters based on FCA (filter cellular automata) window operators, and considered by Park (26), Ablowitz (1), Fokas (11), Fuchssteiner (12), Bruschi (5) and Jiang (20). We present the automata equivalents to these filters (33). Some of them belong to the class of filter automata introduced in (30). We also define and illustrate some properties of filtrons. Contrary to particles, the filtrons interact nonlocally in the sense that distant symbols may influence one another. Thus their interactions are very unusual. Some examples have been given in (32). Here we show new examples of filtron phenomena: multifiltron solitonic collisions, attracting and repelling filtrons, trapped bouncing filtrons (which behave like a resonance cavity) and quasi filtrons.

Dynamics of HIV infection on 2D cellular automata

NASA Astrophysics Data System (ADS)

Benyoussef, A.; HafidAllah, N. El; ElKenz, A.; Ez-Zahraouy, H.; Loulidi, M.

2003-05-01

We use a cellular automata approach to describe the interactions of the immune system with the human immunodeficiency virus (HIV). We study the evolution of HIV infection, particularly in the clinical latency period. The results we have obtained show the existence of four different behaviours in the plane of death rate of virus-death rate of infected T cell. These regions meet at a critical point, where the virus density and the infected T cell density remain invariant during the evolution of disease. We have introduced two kinds of treatments, the protease inhibitors and the RT inhibitors, in order to study their effects on the evolution of HIV infection. These treatments are powerful in decreasing the density of the virus in the blood and the delay of the AIDS onset.

A new simulation system of traffic flow based on cellular automata principle

NASA Astrophysics Data System (ADS)

Shan, Junru

2017-05-01

Traffic flow is a complex system of multi-behavior so it is difficult to give a specific mathematical equation to express it. With the rapid development of computer technology, it is an important method to study the complex traffic behavior by simulating the interaction mechanism between vehicles and reproduce complex traffic behavior. Using the preset of multiple operating rules, cellular automata is a kind of power system which has discrete time and space. It can be a good simulation of the real traffic process and a good way to solve the traffic problems.

Cellular automata models for diffusion of information and highway traffic flow

NASA Astrophysics Data System (ADS)

Fuks, Henryk

In the first part of this work we study a family of deterministic models for highway traffic flow which generalize cellular automaton rule 184. This family is parameterized by the speed limit m and another parameter k that represents degree of 'anticipatory driving'. We compare two driving strategies with identical maximum throughput: 'conservative' driving with high speed limit and 'anticipatory' driving with low speed limit. Those two strategies are evaluated in terms of accident probability. We also discuss fundamental diagrams of generalized traffic rules and examine limitations of maximum achievable throughput. Possible modifications of the model are considered. For rule 184, we present exact calculations of the order parameter in a transition from the moving phase to the jammed phase using the method of preimage counting, and use this result to construct a solution to the density classification problem. In the second part we propose a probabilistic cellular automaton model for the spread of innovations, rumors, news, etc., in a social system. We start from simple deterministic models, for which exact expressions for the density of adopters are derived. For a more realistic model, based on probabilistic cellular automata, we study the influence of a range of interaction R on the shape of the adoption curve. When the probability of adoption is proportional to the local density of adopters, and individuals can drop the innovation with some probability p, the system exhibits a second order phase transition. Critical line separating regions of parameter space in which asymptotic density of adopters is positive from the region where it is equal to zero converges toward the mean-field line when the range of the interaction increases. In a region between R=1 critical line and the mean-field line asymptotic density of adopters depends on R, becoming zero if R is too small (smaller than some critical value). This result demonstrates the importance of connectivity in

Stochastic cellular automata model for stock market dynamics

NASA Astrophysics Data System (ADS)

Bartolozzi, M.; Thomas, A. W.

2004-04-01

In the present work we introduce a stochastic cellular automata model in order to simulate the dynamics of the stock market. A direct percolation method is used to create a hierarchy of clusters of active traders on a two-dimensional grid. Active traders are characterized by the decision to buy, σi (t)=+1 , or sell, σi (t)=-1 , a stock at a certain discrete time step. The remaining cells are inactive, σi (t)=0 . The trading dynamics is then determined by the stochastic interaction between traders belonging to the same cluster. Extreme, intermittent events, such as crashes or bubbles, are triggered by a phase transition in the state of the bigger clusters present on the grid, where almost all the active traders come to share the same spin orientation. Most of the stylized aspects of the financial market time series, including multifractal proprieties, are reproduced by the model. A direct comparison is made with the daily closures of the S&P500 index.

Object Synthesis in Conway's Game of Life and Other Cellular Automata

NASA Astrophysics Data System (ADS)

Niemiec, Mark D.

Of the very large number of cellular automata rules in existence, a relatively small number of rules may be considered interesting. Some of the features that make such rules interesting permit patterns to expand, contract, separate into multiple sub-patterns, or combine with other patterns. Such rules generally include still-lifes, oscillators, spaceships, spaceship guns, and puffer trains. Such structures can often be used to construct more complicated computational circuitry, and rules that contain them can often be shown to be computationally universal. Conway's Game of Life is one rule that has been well-studied for several decades, and has been shown to be very fruitful in this regard.

Quantum-Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Snider, Gregory

2000-03-01

Quantum-dot Cellular Automata (QCA) [1] is a promising architecture which employs quantum dots for digital computation. It is a revolutionary approach that holds the promise of high device density and low power dissipation. A basic QCA cell consists of four quantum dots coupled capacitively and by tunnel barriers. The cell is biased to contain two excess electrons within the four dots, which are forced to opposite "corners" of the four-dot cell by mutual Coulomb repulsion. These two possible polarization states of the cell will represent logic "0" and "1". Properly arranged, arrays of these basic cells can implement Boolean logic functions. Experimental results from functional QCA devices built of nanoscale metal dots defined by tunnel barriers will be presented. The experimental devices to be presented consist of Al islands, which we will call quantum dots, interconnected by tunnel junctions and lithographically defined capacitors. Aluminum/ aluminum-oxide/aluminum tunnel junctions were fabricated using a standard e-beam lithography and shadow evaporation technique. The experiments were performed in a dilution refrigerator at a temperature of 70 mK. The operation of a cell is evaluated by direct measurements of the charge state of dots within a cell as the input voltage is changed. The experimental demonstration of a functioning cell will be presented. A line of three cells demonstrates that there are no metastable switching states in a line of cells. A QCA majority gate will also be presented, which is a programmable AND/OR gate and represents the basic building block of QCA systems. The results of recent experiments will be presented. 1. C.S. Lent, P.D. Tougaw, W. Porod, and G.H. Bernstein, Nanotechnology, 4, 49 (1993).

Exact results of 1D traffic cellular automata: The low-density behavior of the Fukui-Ishibashi model

NASA Astrophysics Data System (ADS)

Salcido, Alejandro; Hernández-Zapata, Ernesto; Carreón-Sierra, Susana

2018-03-01

The maximum entropy states of the cellular automata models for traffic flow in a single-lane with no anticipation are presented and discussed. The exact analytical solutions for the low-density behavior of the stochastic Fukui-Ishibashi traffic model were obtained and compared with computer simulations of the model. An excellent agreement was found.

On the topological sensitivity of cellular automata

NASA Astrophysics Data System (ADS)

Baetens, Jan M.; De Baets, Bernard

2011-06-01

Ever since the conceptualization of cellular automata (CA), much attention has been paid to the dynamical properties of these discrete dynamical systems, and, more in particular, to their sensitivity to the initial condition from which they are evolved. Yet, the sensitivity of CA to the topology upon which they are based has received only minor attention, such that a clear insight in this dependence is still lacking and, furthermore, a quantification of this so-called topological sensitivity has not yet been proposed. The lack of attention for this issue is rather surprising since CA are spatially explicit, which means that their dynamics is directly affected by their topology. To overcome these shortcomings, we propose topological Lyapunov exponents that measure the divergence of two close trajectories in phase space originating from a topological perturbation, and we relate them to a measure grasping the sensitivity of CA to their topology that relies on the concept of topological derivatives, which is introduced in this paper. The validity of the proposed methodology is illustrated for the 256 elementary CA and for a family of two-state irregular totalistic CA.

Field validation of a free-agent cellular automata model of fire spread with fire–atmosphere coupling

Treesearch

Gary Achtemeier

2012-01-01

A cellular automata fire model represents ‘elements’ of fire by autonomous agents. A few simple algebraic expressions substituted for complex physical and meteorological processes and solved iteratively yield simulations for ‘super-diffusive’ fire spread and coupled surface-layer (2-m) fire–atmosphere processes. Pressure anomalies, which are integrals of the thermal...

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks.

PubMed

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-22

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

PubMed Central

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-01-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability. PMID:27874024

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

NASA Astrophysics Data System (ADS)

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

Quantitative Analysis of Intra Urban Growth Modeling using socio economic agents by combining cellular automata model with agent based model

NASA Astrophysics Data System (ADS)

Singh, V. K.; Jha, A. K.; Gupta, K.; Srivastav, S. K.

2017-12-01

Recent studies indicate that there is a significant improvement in the urban land use dynamics through modeling at finer spatial resolutions. Geo-computational models such as cellular automata and agent based model have given evident proof regarding the quantification of the urban growth pattern with urban boundary. In recent studies, socio- economic factors such as demography, education rate, household density, parcel price of the current year, distance to road, school, hospital, commercial centers and police station are considered to the major factors influencing the Land Use Land Cover (LULC) pattern of the city. These factors have unidirectional approach to land use pattern which makes it difficult to analyze the spatial aspects of model results both quantitatively and qualitatively. In this study, cellular automata model is combined with generic model known as Agent Based Model to evaluate the impact of socio economic factors on land use pattern. For this purpose, Dehradun an Indian city is selected as a case study. Socio economic factors were collected from field survey, Census of India, Directorate of economic census, Uttarakhand, India. A 3X3 simulating window is used to consider the impact on LULC. Cellular automata model results are examined for the identification of hot spot areas within the urban area and agent based model will be using logistic based regression approach where it will identify the correlation between each factor on LULC and classify the available area into low density, medium density, high density residential or commercial area. In the modeling phase, transition rule, neighborhood effect, cell change factors are used to improve the representation of built-up classes. Significant improvement is observed in the built-up classes from 84 % to 89 %. However after incorporating agent based model with cellular automata model the accuracy improved from 89 % to 94 % in 3 classes of urban i.e. low density, medium density and commercial classes

Analytical formulation of cellular automata rules using data models

NASA Astrophysics Data System (ADS)

Jaenisch, Holger M.; Handley, James W.

2009-05-01

We present a unique method for converting traditional cellular automata (CA) rules into analytical function form. CA rules have been successfully used for morphological image processing and volumetric shape recognition and classification. Further, the use of CA rules as analog models to the physical and biological sciences can be significantly extended if analytical (as opposed to discrete) models could be formulated. We show that such transformations are possible. We use as our example John Horton Conway's famous "Game of Life" rule set. We show that using Data Modeling, we are able to derive both polynomial and bi-spectrum models of the IF-THEN rules that yield equivalent results. Further, we demonstrate that the "Game of Life" rule set can be modeled using the multi-fluxion, yielding a closed form nth order derivative and integral. All of the demonstrated analytical forms of the CA rule are general and applicable to real-time use.

Electoral surveys’ influence on the voting processes: a cellular automata model

NASA Astrophysics Data System (ADS)

Alves, S. G.; Oliveira Neto, N. M.; Martins, M. L.

2002-12-01

Nowadays, in societies threatened by atomization, selfishness, short-term thinking, and alienation from political life, there is a renewed debate about classical questions concerning the quality of democratic decision making. In this work a cellular automata model for the dynamics of free elections, based on the social impact theory is proposed. By using computer simulations, power-law distributions for the size of electoral clusters and decision time have been obtained. The major role of broadcasted electoral surveys in guiding opinion formation and stabilizing the “status quo” was demonstrated. Furthermore, it was shown that in societies where these surveys are manipulated within the universally accepted statistical error bars, even a majoritary opposition could be hindered from reaching power through the electoral path.

Investigation of phase diagrams for cylindrical Ising nanotube using cellular automata

NASA Astrophysics Data System (ADS)

Astaraki, M.; Ghaemi, M.; Afzali, K.

2018-05-01

Recent developments in the field of applied nanoscience and nanotechnology have heightened the need for categorizing various characteristics of nanostructures. In this regard, this paper establishes a novel method to investigate magnetic properties (phase diagram and spontaneous magnetization) of a cylindrical Ising nanotube. Using a two-layer Ising model and the core-shell concept, the interactions within nanotube has been modelled. In the model, both ferromagnetic and antiferromagnetic cases have been considered. Furthermore, the effect of nanotube's length on the critical temperature is investigated. The model has been simulated using cellular automata approach and phase diagrams were constructed for different values of inter- and intra-layer couplings. For the antiferromagnetic case, the possibility of existence of compensation point is observed.

Cellular automata and integrodifferential equation models for cell renewal in mosaic tissues

PubMed Central

Bloomfield, J. M.; Sherratt, J. A.; Painter, K. J.; Landini, G.

2010-01-01

Mosaic tissues are composed of two or more genetically distinct cell types. They occur naturally, and are also a useful experimental method for exploring tissue growth and maintenance. By marking the different cell types, one can study the patterns formed by proliferation, renewal and migration. Here, we present mathematical modelling suggesting that small changes in the type of interaction that cells have with their local cellular environment can lead to very different outcomes for the composition of mosaics. In cell renewal, proliferation of each cell type may depend linearly or nonlinearly on the local proportion of cells of that type, and these two possibilities produce very different patterns. We study two variations of a cellular automaton model based on simple rules for renewal. We then propose an integrodifferential equation model, and again consider two different forms of cellular interaction. The results of the continuous and cellular automata models are qualitatively the same, and we observe that changes in local environment interaction affect the dynamics for both. Furthermore, we demonstrate that the models reproduce some of the patterns seen in actual mosaic tissues. In particular, our results suggest that the differing patterns seen in organ parenchymas may be driven purely by the process of cell replacement under different interaction scenarios. PMID:20375040

Computational Modeling of Proteins based on Cellular Automata: A Method of HP Folding Approximation.

PubMed

Madain, Alia; Abu Dalhoum, Abdel Latif; Sleit, Azzam

2018-06-01

The design of a protein folding approximation algorithm is not straightforward even when a simplified model is used. The folding problem is a combinatorial problem, where approximation and heuristic algorithms are usually used to find near optimal folds of proteins primary structures. Approximation algorithms provide guarantees on the distance to the optimal solution. The folding approximation approach proposed here depends on two-dimensional cellular automata to fold proteins presented in a well-studied simplified model called the hydrophobic-hydrophilic model. Cellular automata are discrete computational models that rely on local rules to produce some overall global behavior. One-third and one-fourth approximation algorithms choose a subset of the hydrophobic amino acids to form H-H contacts. Those algorithms start with finding a point to fold the protein sequence into two sides where one side ignores H's at even positions and the other side ignores H's at odd positions. In addition, blocks or groups of amino acids fold the same way according to a predefined normal form. We intend to improve approximation algorithms by considering all hydrophobic amino acids and folding based on the local neighborhood instead of using normal forms. The CA does not assume a fixed folding point. The proposed approach guarantees one half approximation minus the H-H endpoints. This lower bound guaranteed applies to short sequences only. This is proved as the core and the folds of the protein will have two identical sides for all short sequences.

Consequences of Landscape Fragmentation on Lyme Disease Risk: A Cellular Automata Approach

PubMed Central

Li, Sen; Hartemink, Nienke; Speybroeck, Niko; Vanwambeke, Sophie O.

2012-01-01

The abundance of infected Ixodid ticks is an important component of human risk of Lyme disease, and various empirical studies have shown that this is associated, at least in part, to landscape fragmentation. In this study, we aimed at exploring how varying woodland fragmentation patterns affect the risk of Lyme disease, through infected tick abundance. A cellular automata model was developed, incorporating a heterogeneous landscape with three interactive components: an age-structured tick population, a classical disease transmission function, and hosts. A set of simplifying assumptions were adopted with respect to the study objective and field data limitations. In the model, the landscape influences both tick survival and host movement. The validation of the model was performed with an empirical study. Scenarios of various landscape configurations (focusing on woodland fragmentation) were simulated and compared. Lyme disease risk indices (density and infection prevalence of nymphs) differed considerably between scenarios: (i) the risk could be higher in highly fragmented woodlands, which is supported by a number of recently published empirical studies, and (ii) grassland could reduce the risk in adjacent woodland, which suggests landscape fragmentation studies of zoonotic diseases should not focus on the patch-level woodland patterns only, but also on landscape-level adjacent land cover patterns. Further analysis of the simulation results indicated strong correlations between Lyme disease risk indices and the density, shape and aggregation level of woodland patches. These findings highlight the strong effect of the spatial patterns of local host population and movement on the spatial dynamics of Lyme disease risks, which can be shaped by woodland fragmentation. In conclusion, using a cellular automata approach is beneficial for modelling complex zoonotic transmission systems as it can be combined with either real world landscapes for exploring direct spatial

A study for bank effect on ship traffic in narrow water channels using cellular automata

NASA Astrophysics Data System (ADS)

Sun, Zhuo; Cong, Shuang; Pan, Junnan; Zheng, Jianfeng

2017-12-01

In narrow water channels, bank might affect nearby ships due to hydrodynamic forces (bank effect). To avoid accidents, different sailing rules (i.e., lane-changing, speed control) are required. In this paper, a two-lane cellular automata model is proposed to evaluate such phenomena. Numerical experiments show that ships will form a “slow-moving chunk” in the bank area, which will significantly block the flux. As further study demonstrated to alleviate bank effect, ship speed and bank length should be controlled.

Modelling of Microstructure Changes in Hot Deformed Materials Using Cellular Automata

NASA Astrophysics Data System (ADS)

Kuc, Dariusz; Gawąd, Jerzy

2011-01-01

The paper is focused on application of multi-scale 2D method. Model approach consists of Cellular Automata (CA) model of microstructure development and the finite element code to solve thermo-mechanical problem. Dynamic recrystallization phenomenon is taken into account in 2D CA model which takes advantage of explicit representation of microstructure, including individual grains and grain boundaries. Flow stress is the main material parameter in mechanical part of FE and is calculated on the basis of average dislocation density obtained from CA model. The results attained from the model were validated with the experimental data. In the present study, austenitic steel X3CrNi18-10 was investigated. The examination of microstructure for the initial and final microstructures was carried out, using light microscopy and transmission electron microscopy.

Experimental Studies of Quasi-Adiabatic Quantum-dot Cellular Automata

NASA Astrophysics Data System (ADS)

Orlov, Alexei; Amlani, Islamshah; Kummamuru, Ravi; Toth, Geza; Bernstein, Gary; Lent, Craig; Snider, Gregory

2000-03-01

The computational approach known as Quantum-dot Cellular Automata (QCA) uses interacting quantum dots to encode and process binary information. The first realization of a functioning QCA cell has already been reported. Recently, quasi-adiabatic switching of QCA in a metal dot system near the instantaneous ground state was proposed [1]. The advantage if this approach is that it allows both logic and addressable memory to be implemented within the QCA framework. We report on the fabrication and measurement of such a device in the Al-AlOx tunnel junction system. This basic building block consists of three metal islands connected in series by tunnel junctions, where an electron can be moved between islands by means of electrostatic perturbation on either control electrodes or adjacent cells. The cell can have three operational modes, i.e. active, locked and null, which provide a solution for ground state computing that is not susceptible to metastable states. [1] G. Toth and C. S. Lent, J. appl. Phys. 85 5, 2977-2984, 1999.

Critical Behavior in Cellular Automata Animal Disease Transmission Model

NASA Astrophysics Data System (ADS)

Morley, P. D.; Chang, Julius

Using cellular automata model, we simulate the British Government Policy (BGP) in the 2001 foot and mouth epidemic in Great Britain. When clinical symptoms of the disease appeared in a farm, there is mandatory slaughter (culling) of all livestock in an infected premise (IP). Those farms in the neighboring of an IP (contiguous premise, CP), are also culled, aka nearest neighbor interaction. Farms where the disease may be prevalent from animal, human, vehicle or airborne transmission (dangerous contact, DC), are additionally culled, aka next-to-nearest neighbor interactions and lightning factor. The resulting mathematical model possesses a phase transition, whereupon if the physical disease transmission kernel exceeds a critical value, catastrophic loss of animals ensues. The nonlocal disease transport probability can be as low as 0.01% per day and the disease can still be in the high mortality phase. We show that the fundamental equation for sustainable disease transport is the criticality equation for neutron fission cascade. Finally, we calculate that the percentage of culled animals that are actually healthy is ≈30%.

Ca-Pri a Cellular Automata Phenomenological Research Investigation: Simulation Results

NASA Astrophysics Data System (ADS)

Iannone, G.; Troisi, A.

2013-05-01

Following the introduction of a phenomenological cellular automata (CA) model capable to reproduce city growth and urban sprawl, we develop a toy model simulation considering a realistic framework. The main characteristic of our approach is an evolution algorithm based on inhabitants preferences. The control of grown cells is obtained by means of suitable functions which depend on the initial condition of the simulation. New born urban settlements are achieved by means of a logistic evolution of the urban pattern while urban sprawl is controlled by means of the population evolution function. In order to compare model results with a realistic urban framework we have considered, as the area of study, the island of Capri (Italy) in the Mediterranean Sea. Two different phases of the urban evolution on the island have been taken into account: a new born initial growth as induced by geographic suitability and the simulation of urban spread after 1943 induced by the population evolution after this date.

Accurate reliability analysis method for quantum-dot cellular automata circuits

NASA Astrophysics Data System (ADS)

Cui, Huanqing; Cai, Li; Wang, Sen; Liu, Xiaoqiang; Yang, Xiaokuo

2015-10-01

Probabilistic transfer matrix (PTM) is a widely used model in the reliability research of circuits. However, PTM model cannot reflect the impact of input signals on reliability, so it does not completely conform to the mechanism of the novel field-coupled nanoelectronic device which is called quantum-dot cellular automata (QCA). It is difficult to get accurate results when PTM model is used to analyze the reliability of QCA circuits. To solve this problem, we present the fault tree models of QCA fundamental devices according to different input signals. After that, the binary decision diagram (BDD) is used to quantitatively investigate the reliability of two QCA XOR gates depending on the presented models. By employing the fault tree models, the impact of input signals on reliability can be identified clearly and the crucial components of a circuit can be found out precisely based on the importance values (IVs) of components. So this method is contributive to the construction of reliable QCA circuits.

Cellular automata simulation of topological effects on the dynamics of feed-forward motifs

PubMed Central

Apte, Advait A; Cain, John W; Bonchev, Danail G; Fong, Stephen S

2008-01-01

Background Feed-forward motifs are important functional modules in biological and other complex networks. The functionality of feed-forward motifs and other network motifs is largely dictated by the connectivity of the individual network components. While studies on the dynamics of motifs and networks are usually devoted to the temporal or spatial description of processes, this study focuses on the relationship between the specific architecture and the overall rate of the processes of the feed-forward family of motifs, including double and triple feed-forward loops. The search for the most efficient network architecture could be of particular interest for regulatory or signaling pathways in biology, as well as in computational and communication systems. Results Feed-forward motif dynamics were studied using cellular automata and compared with differential equation modeling. The number of cellular automata iterations needed for a 100% conversion of a substrate into a target product was used as an inverse measure of the transformation rate. Several basic topological patterns were identified that order the specific feed-forward constructions according to the rate of dynamics they enable. At the same number of network nodes and constant other parameters, the bi-parallel and tri-parallel motifs provide higher network efficacy than single feed-forward motifs. Additionally, a topological property of isodynamicity was identified for feed-forward motifs where different network architectures resulted in the same overall rate of the target production. Conclusion It was shown for classes of structural motifs with feed-forward architecture that network topology affects the overall rate of a process in a quantitatively predictable manner. These fundamental results can be used as a basis for simulating larger networks as combinations of smaller network modules with implications on studying synthetic gene circuits, small regulatory systems, and eventually dynamic whole-cell models

Stochastic modeling for dynamics of HIV-1 infection using cellular automata: A review.

PubMed

Precharattana, Monamorn

2016-02-01

Recently, the description of immune response by discrete models has emerged to play an important role to study the problems in the area of human immunodeficiency virus type 1 (HIV-1) infection, leading to AIDS. As infection of target immune cells by HIV-1 mainly takes place in the lymphoid tissue, cellular automata (CA) models thus represent a significant step in understanding when the infected population is dispersed. Motivated by these, the studies of the dynamics of HIV-1 infection using CA in memory have been presented to recognize how CA have been developed for HIV-1 dynamics, which issues have been studied already and which issues still are objectives in future studies.

Integer lattice gas with Monte Carlo collision operator recovers the lattice Boltzmann method with Poisson-distributed fluctuations

NASA Astrophysics Data System (ADS)

Blommel, Thomas; Wagner, Alexander J.

2018-02-01

We examine a new kind of lattice gas that closely resembles modern lattice Boltzmann methods. This new kind of lattice gas, which we call a Monte Carlo lattice gas, has interesting properties that shed light on the origin of the multirelaxation time collision operator, and it derives the equilibrium distribution for an entropic lattice Boltzmann. Furthermore these lattice gas methods have Galilean invariant fluctuations given by a Poisson statistics, giving further insight into the properties that we should expect for fluctuating lattice Boltzmann methods.

The Development of Design Tools for Fault Tolerant Quantum Dot Cellular Automata Based Logic

NASA Technical Reports Server (NTRS)

Armstrong, Curtis D.; Humphreys, William M.

2003-01-01

We are developing software to explore the fault tolerance of quantum dot cellular automata gate architectures in the presence of manufacturing variations and device defects. The Topology Optimization Methodology using Applied Statistics (TOMAS) framework extends the capabilities of the A Quantum Interconnected Network Array Simulator (AQUINAS) by adding front-end and back-end software and creating an environment that integrates all of these components. The front-end tools establish all simulation parameters, configure the simulation system, automate the Monte Carlo generation of simulation files, and execute the simulation of these files. The back-end tools perform automated data parsing, statistical analysis and report generation.

Unstable vicinal crystal growth from cellular automata

NASA Astrophysics Data System (ADS)

Krasteva, A.; Popova, H.; KrzyŻewski, F.; Załuska-Kotur, M.; Tonchev, V.

2016-03-01

In order to study the unstable step motion on vicinal crystal surfaces we devise vicinal Cellular Automata. Each cell from the colony has value equal to its height in the vicinal, initially the steps are regularly distributed. Another array keeps the adatoms, initially distributed randomly over the surface. The growth rule defines that each adatom at right nearest neighbor position to a (multi-) step attaches to it. The update of whole colony is performed at once and then time increases. This execution of the growth rule is followed by compensation of the consumed particles and by diffusional update(s) of the adatom population. Two principal sources of instability are employed - biased diffusion and infinite inverse Ehrlich-Schwoebel barrier (iiSE). Since these factors are not opposed by step-step repulsion the formation of multi-steps is observed but in general the step bunches preserve a finite width. We monitor the developing surface patterns and quantify the observations by scaling laws with focus on the eventual transition from diffusion-limited to kinetics-limited phenomenon. The time-scaling exponent of the bunch size N is 1/2 for the case of biased diffusion and 1/3 for the case of iiSE. Additional distinction is possible based on the time-scaling exponents of the sizes of multi-step Nmulti, these are 0.36÷0.4 (for biased diffusion) and 1/4 (iiSE).

Lattice Boltzmann for Simulation of Gases Mixture in Fruit Storage Chambers

NASA Astrophysics Data System (ADS)

Fabero, J. C.; Barreiro, P.; Casasús, L.

2003-04-01

Fluid Dynamics can be modelled through the Navier-Stokes equations. This description corresponds to a macroscopic definition of the fluid motion phenomena. During the past 20 year new simulation procedures are emerging from Statistical Physics and Computer Science domains. One of them is the Lattice Gas Cellular Automata (LGCA) method. This approach, which is considered to be a microscopic description of the world, in spite of its intuitiveness and numerical efficiency, fails to simulate the real Navier-Stokes equations. Another classical simulation procedure for the fluid motion phenomena is the so called Lattice Boltzmann method [1]. This corresponds to a meso-scale description of the world [2]. Simulation of laminar and turbulent motions of fluids, specially when considering several gas species is still an ongoing research [3]. Nowadays, the use of Low Oxygen and Ultra Low Oxygen Controlled Atmospheres has been recognized as a reliable method to extend the storage life of fruits an vegetables. However, small spatial gradients in gas concentration during storage may generate internal disorders in the commodities. In this work, four different gases will be considered: oxygen, carbon dioxide, water vapor and ethylene. Physiological effects such as transpiration, which affects the level of water vapor, respiration, which modifies both oxygen and carbon dioxide concentrations, and ethylene emission, must be taken into account in the hole model. The numerical model, based on that proposed by Shan and Chen, is implemented, being able to consider the behavior of multiple mixable gas species. Forced air motion, needed to obtain a correct ventilation of the chamber, has also been modelled.

Bulk diffusion in a kinetically constrained lattice gas

NASA Astrophysics Data System (ADS)

Arita, Chikashi; Krapivsky, P. L.; Mallick, Kirone

2018-03-01

In the hydrodynamic regime, the evolution of a stochastic lattice gas with symmetric hopping rules is described by a diffusion equation with density-dependent diffusion coefficient encapsulating all microscopic details of the dynamics. This diffusion coefficient is, in principle, determined by a Green-Kubo formula. In practice, even when the equilibrium properties of a lattice gas are analytically known, the diffusion coefficient cannot be computed except when a lattice gas additionally satisfies the gradient condition. We develop a procedure to systematically obtain analytical approximations for the diffusion coefficient for non-gradient lattice gases with known equilibrium. The method relies on a variational formula found by Varadhan and Spohn which is a version of the Green-Kubo formula particularly suitable for diffusive lattice gases. Restricting the variational formula to finite-dimensional sub-spaces allows one to perform the minimization and gives upper bounds for the diffusion coefficient. We apply this approach to a kinetically constrained non-gradient lattice gas in two dimensions, viz. to the Kob-Andersen model on the square lattice.

Using Cellular Automata for Parking Recommendations in Smart Environments

PubMed Central

Horng, Gwo-Jiun

2014-01-01

In this work, we propose an innovative adaptive recommendation mechanism for smart parking. The cognitive RF module will transmit the vehicle location information and the parking space requirements to the parking congestion computing center (PCCC) when the driver must find a parking space. Moreover, for the parking spaces, we use a cellular automata (CA) model mechanism that can adjust to full and not full parking lot situations. Here, the PCCC can compute the nearest parking lot, the parking lot status and the current or opposite driving direction with the vehicle location information. By considering the driving direction, we can determine when the vehicles must turn around and thus reduce road congestion and speed up finding a parking space. The recommendation will be sent to the drivers through a wireless communication cognitive radio (CR) model after the computation and analysis by the PCCC. The current study evaluates the performance of this approach by conducting computer simulations. The simulation results show the strengths of the proposed smart parking mechanism in terms of avoiding increased congestion and decreasing the time to find a parking space. PMID:25153671

A scale-invariant cellular-automata model for distributed seismicity

NASA Technical Reports Server (NTRS)

Barriere, Benoit; Turcotte, Donald L.

1991-01-01

In the standard cellular-automata model for a fault an element of stress is randomly added to a grid of boxes until a box has four elements, these are then redistributed to the adjacent boxes on the grid. The redistribution can result in one or more of these boxes having four or more elements in which case further redistributions are required. On the average added elements are lost from the edges of the grid. The model is modified so that the boxes have a scale-invariant distribution of sizes. The objective is to model a scale-invariant distribution of fault sizes. When a redistribution from a box occurs it is equivalent to a characteristic earthquake on the fault. A redistribution from a small box (a foreshock) can trigger an instability in a large box (the main shock). A redistribution from a large box always triggers many instabilities in the smaller boxes (aftershocks). The frequency-size statistics for both main shocks and aftershocks satisfy the Gutenberg-Richter relation with b = 0.835 for main shocks and b = 0.635 for aftershocks. Model foreshocks occur 28 percent of the time.

Cellular automata rule characterization and classification using texture descriptors

NASA Astrophysics Data System (ADS)

Machicao, Jeaneth; Ribas, Lucas C.; Scabini, Leonardo F. S.; Bruno, Odermir M.

2018-05-01

The cellular automata (CA) spatio-temporal patterns have attracted the attention from many researchers since it can provide emergent behavior resulting from the dynamics of each individual cell. In this manuscript, we propose an approach of texture image analysis to characterize and classify CA rules. The proposed method converts the CA spatio-temporal patterns into a gray-scale image. The gray-scale is obtained by creating a binary number based on the 8-connected neighborhood of each dot of the CA spatio-temporal pattern. We demonstrate that this technique enhances the CA rule characterization and allow to use different texture image analysis algorithms. Thus, various texture descriptors were evaluated in a supervised training approach aiming to characterize the CA's global evolution. Our results show the efficiency of the proposed method for the classification of the elementary CA (ECAs), reaching a maximum of 99.57% of accuracy rate according to the Li-Packard scheme (6 classes) and 94.36% for the classification of the 88 rules scheme. Moreover, within the image analysis context, we found a better performance of the method by means of a transformation of the binary states to a gray-scale.

Lattice gas methods for computational aeroacoustics

NASA Technical Reports Server (NTRS)

Sparrow, Victor W.

1995-01-01

This paper presents the lattice gas solution to the category 1 problems of the ICASE/LaRC Workshop on Benchmark Problems in Computational Aeroacoustics. The first and second problems were solved for Delta t = Delta x = 1, and additionally the second problem was solved for Delta t = 1/4 and Delta x = 1/2. The results are striking: even for these large time and space grids the lattice gas numerical solutions are almost indistinguishable from the analytical solutions. A simple bug in the Mathematica code was found in the solutions submitted for comparison, and the comparison plots shown at the end of this volume show the bug. An Appendix to the present paper shows an example lattice gas solution with and without the bug.

Topometry optimization of sheet metal structures for crashworthiness design using hybrid cellular automata

NASA Astrophysics Data System (ADS)

Mozumder, Chandan K.

The objective in crashworthiness design is to generate plastically deformable energy absorbing structures which can satisfy the prescribed force-displacement (FD) response. The FD behavior determines the reaction force, displacement and the internal energy that the structure should withstand. However, attempts to include this requirement in structural optimization problems remain scarce. The existing commercial optimization tools utilize models under static loading conditions because of the complexities associated with dynamic/impact loading. Due to the complexity of a crash event and the consequent time required to numerically analyze the dynamic response of the structure, classical methods (i.e., gradient-based and direct) are not well developed to solve this undertaking. This work presents an approach under the framework of the hybrid cellular automaton (HCA) method to solve the above challenge. The HCA method has been successfully applied to nonlinear transient topology optimization for crashworthiness design. In this work, the HCA algorithm has been utilized to develop an efficient methodology for synthesizing shell-based sheet metal structures with optimal material thickness distribution under a dynamic loading event using topometry optimization. This method utilizes the cellular automata (CA) computing paradigm and nonlinear transient finite element analysis (FEA) via ls-dyna. In this method, a set field variables is driven to their target states by changing a convenient set of design variables (e.g., thickness). These rules operate locally in cells within a lattice that only know local conditions. The field variables associated with the cells are driven to a setpoint to obtain the desired structure. This methodology is used to design for structures with controlled energy absorption with specified buckling zones. The peak reaction force and the maximum displacement are also constrained to meet the desired safety level according to passenger safety

Cellular-automata-based learning network for pattern recognition

NASA Astrophysics Data System (ADS)

Tzionas, Panagiotis G.; Tsalides, Phillippos G.; Thanailakis, Adonios

1991-11-01

Most classification techniques either adopt an approach based directly on the statistical characteristics of the pattern classes involved, or they transform the patterns in a feature space and try to separate the point clusters in this space. An alternative approach based on memory networks has been presented, its novelty being that it can be implemented in parallel and it utilizes direct features of the patterns rather than statistical characteristics. This study presents a new approach for pattern classification using pseudo 2-D binary cellular automata (CA). This approach resembles the memory network classifier in the sense that it is based on an adaptive knowledge based formed during a training phase, and also in the fact that both methods utilize pattern features that are directly available. The main advantage of this approach is that the sensitivity of the pattern classifier can be controlled. The proposed pattern classifier has been designed using 1.5 micrometers design rules for an N-well CMOS process. Layout has been achieved using SOLO 1400. Binary pseudo 2-D hybrid additive CA (HACA) is described in the second section of this paper. The third section describes the operation of the pattern classifier and the fourth section presents some possible applications. The VLSI implementation of the pattern classifier is presented in the fifth section and, finally, the sixth section draws conclusions from the results obtained.

Coupling of Markov chains and cellular automata spatial models to predict land cover changes (case study: upper Ci Leungsi catchment area)

NASA Astrophysics Data System (ADS)

Marko, K.; Zulkarnain, F.; Kusratmoko, E.

2016-11-01

Land cover changes particular in urban catchment area has been rapidly occur. Land cover changes occur as a result of increasing demand for built-up area. Various kinds of environmental and hydrological problems e.g. floods and urban heat island can happen if the changes are uncontrolled. This study aims to predict land cover changes using coupling of Markov chains and cellular automata. One of the most rapid land cover changes is occurs at upper Ci Leungsi catchment area that located near Bekasi City and Jakarta Metropolitan Area. Markov chains has a good ability to predict the probability of change statistically while cellular automata believed as a powerful method in reading the spatial patterns of change. Temporal land cover data was obtained by remote sensing satellite imageries. In addition, this study also used multi-criteria analysis to determine which driving factor that could stimulate the changes such as proximity, elevation, and slope. Coupling of these two methods could give better prediction model rather than just using it separately. The prediction model was validated using existing 2015 land cover data and shown a satisfactory kappa coefficient. The most significant increasing land cover is built-up area from 24% to 53%.

Structural classification of proteins using texture descriptors extracted from the cellular automata image.

PubMed

Kavianpour, Hamidreza; Vasighi, Mahdi

2017-02-01

Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.

Preliminary cellular-automata forecast of permit activity from 1998 to 2010, Idaho and Western Montana

USGS Publications Warehouse

Raines, G.L.; Zientek, M.L.; Causey, J.D.; Boleneus, D.E.

2002-01-01

For public land management in Idaho and western Montana, the U.S. Forest Service (USFS) has requested that the U.S. Geological Survey (USGS) predict where mineral-related activity will occur in the next decade. Cellular automata provide an approach to simulation of this human activity. Cellular automata (CA) are defined by an array of cells, which evolve by a simple transition rule, the automaton. Based on exploration trends, we assume that future exploration will focus in areas of past exploration. Spatial-temporal information about mineral-related activity, that is permits issued by USFS and Bureau of Land Management (BLM) in the last decade, and spatial information about undiscovered resources, provide a basis to calibrate a CA. The CA implemented is a modified annealed voting rule that simulates mineral-related activity with spatial and temporal resolution of 1 mi2 and 1 year based on activity from 1989 to 1998. For this CA, the state of the economy and exploration technology is assumed constant for the next decade. The calibrated CA reproduces the 1989-1998-permit activity with an agreement of 94%, which increases to 98% within one year. Analysis of the confusion matrix and kappa correlation statistics indicates that the CA underestimates high activity and overestimates low activity. Spatially, the major differences between the actual and calculated activity are that the calculated activity occurs in a slightly larger number of small patches and is slightly more uneven than the actual activity. Using the calibrated CA in a Monte Carlo simulation projecting from 1998 to 2010, an estimate of the probability of mineral activity shows high levels of activity in Boise, Caribou, Elmore, Lincoln, and western Valley counties in Idaho and Beaverhead, Madison, and Stillwater counties in Montana, and generally low activity elsewhere. ?? 2002 International Association for Mathematical Geology.

In silico characterization of cell-cell interactions using a cellular automata model of cell culture.

PubMed

Kihara, Takanori; Kashitani, Kosuke; Miyake, Jun

2017-07-14

Cell proliferation is a key characteristic of eukaryotic cells. During cell proliferation, cells interact with each other. In this study, we developed a cellular automata model to estimate cell-cell interactions using experimentally obtained images of cultured cells. We used four types of cells; HeLa cells, human osteosarcoma (HOS) cells, rat mesenchymal stem cells (MSCs), and rat smooth muscle A7r5 cells. These cells were cultured and stained daily. The obtained cell images were binarized and clipped into squares containing about 10 4 cells. These cells showed characteristic cell proliferation patterns. The growth curves of these cells were generated from the cell proliferation images and we determined the doubling time of these cells from the growth curves. We developed a simple cellular automata system with an easily accessible graphical user interface. This system has five variable parameters, namely, initial cell number, doubling time, motility, cell-cell adhesion, and cell-cell contact inhibition (of proliferation). Within these parameters, we obtained initial cell numbers and doubling times experimentally. We set the motility at a constant value because the effect of the parameter for our simulation was restricted. Therefore, we simulated cell proliferation behavior with cell-cell adhesion and cell-cell contact inhibition as variables. By comparing growth curves and proliferation cell images, we succeeded in determining the cell-cell interaction properties of each cell. Simulated HeLa and HOS cells exhibited low cell-cell adhesion and weak cell-cell contact inhibition. Simulated MSCs exhibited high cell-cell adhesion and positive cell-cell contact inhibition. Simulated A7r5 cells exhibited low cell-cell adhesion and strong cell-cell contact inhibition. These simulated results correlated with the experimental growth curves and proliferation images. Our simulation approach is an easy method for evaluating the cell-cell interaction properties of cells.

A stochastic parameterization for deep convection using cellular automata

NASA Astrophysics Data System (ADS)

Bengtsson, L.; Steinheimer, M.; Bechtold, P.; Geleyn, J.

2012-12-01

Cumulus parameterizations used in most operational weather and climate models today are based on the mass-flux concept which took form in the early 1970's. In such schemes it is assumed that a unique relationship exists between the ensemble-average of the sub-grid convection, and the instantaneous state of the atmosphere in a vertical grid box column. However, such a relationship is unlikely to be described by a simple deterministic function (Palmer, 2011). Thus, because of the statistical nature of the parameterization challenge, it has been recognized by the community that it is important to introduce stochastic elements to the parameterizations (for instance: Plant and Craig, 2008, Khouider et al. 2010, Frenkel et al. 2011, Bentsson et al. 2011, but the list is far from exhaustive). There are undoubtedly many ways in which stochastisity can enter new developments. In this study we use a two-way interacting cellular automata (CA), as its intrinsic nature possesses many qualities interesting for deep convection parameterization. In the one-dimensional entraining plume approach, there is no parameterization of horizontal transport of heat, moisture or momentum due to cumulus convection. In reality, mass transport due to gravity waves that propagate in the horizontal can trigger new convection, important for the organization of deep convection (Huang, 1988). The self-organizational characteristics of the CA allows for lateral communication between adjacent NWP model grid-boxes, and temporal memory. Thus the CA scheme used in this study contain three interesting components for representation of cumulus convection, which are not present in the traditional one-dimensional bulk entraining plume method: horizontal communication, memory and stochastisity. The scheme is implemented in the high resolution regional NWP model ALARO, and simulations show enhanced organization of convective activity along squall-lines. Probabilistic evaluation demonstrate an enhanced spread in

Modeling the Land Use/Cover Change in an Arid Region Oasis City Constrained by Water Resource and Environmental Policy Change using Cellular Automata Model

NASA Astrophysics Data System (ADS)

Hu, X.; Li, X.; Lu, L.

2017-12-01

Land use/cover change (LUCC) is an important subject in the research of global environmental change and sustainable development, while spatial simulation on land use/cover change is one of the key content of LUCC and is also difficult due to the complexity of the system. The cellular automata (CA) model had an irreplaceable role in simulating of land use/cover change process due to the powerful spatial computing power. However, the majority of current CA land use/cover models were binary-state model that could not provide more general information about the overall spatial pattern of land use/cover change. Here, a multi-state logistic-regression-based Markov cellular automata (MLRMCA) model and a multi-state artificial-neural-network-based Markov cellular automata (MANNMCA) model were developed and were used to simulate complex land use/cover evolutionary process in an arid region oasis city constrained by water resource and environmental policy change, the Zhangye city during the period of 1990-2010. The results indicated that the MANNMCA model was superior to MLRMCA model in simulated accuracy. These indicated that by combining the artificial neural network with CA could more effectively capture the complex relationships between the land use/cover change and a set of spatial variables. Although the MLRMCA model were also some advantages, the MANNMCA model was more appropriate for simulating complex land use/cover dynamics. The two proposed models were effective and reliable, and could reflect the spatial evolution of regional land use/cover changes. These have also potential implications for the impact assessment of water resources, ecological restoration, and the sustainable urban development in arid areas.

Evaluating a Novel Cellular Automata-Based Distributed Power Management Approach for Mobile Wireless Sensor Networks

NASA Astrophysics Data System (ADS)

Adabi, Sepideh; Adabi, Sahar; Rezaee, Ali

According to the traditional definition of Wireless Sensor Networks (WSNs), static sensors have limited the feasibility of WSNs in some kind of approaches, so the mobility was introduced in WSN. Mobile nodes in a WSN come equipped with battery and from the point of deployment, this battery reserve becomes a valuable resource since it cannot be replenished. Hence, maximizing the network lifetime by minimizing the energy is an important challenge in Mobile WSN. Energy conservation can be accomplished by different approaches. In this paper, we presented an energy conservation solution based on Cellular Automata. The main objective of this solution is based on dynamically adjusting the transmission range and switching between operational states of the sensor nodes.

A novel FPGA-programmable switch matrix interconnection element in quantum-dot cellular automata

NASA Astrophysics Data System (ADS)

Hashemi, Sara; Rahimi Azghadi, Mostafa; Zakerolhosseini, Ali; Navi, Keivan

2015-04-01

The Quantum-dot cellular automata (QCA) is a novel nanotechnology, promising extra low-power, extremely dense and very high-speed structure for the construction of logical circuits at a nanoscale. In this paper, initially previous works on QCA-based FPGA's routing elements are investigated, and then an efficient, symmetric and reliable QCA programmable switch matrix (PSM) interconnection element is introduced. This element has a simple structure and offers a complete routing capability. It is implemented using a bottom-up design approach that starts from a dense and high-speed 2:1 multiplexer and utilise it to build the target PSM interconnection element. In this study, simulations of the proposed circuits are carried out using QCAdesigner, a layout and simulation tool for QCA circuits. The results demonstrate high efficiency of the proposed designs in QCA-based FPGA routing.

A solution to the biodiversity paradox by logical deterministic cellular automata.

PubMed

Kalmykov, Lev V; Kalmykov, Vyacheslav L

2015-06-01

The paradox of biological diversity is the key problem of theoretical ecology. The paradox consists in the contradiction between the competitive exclusion principle and the observed biodiversity. The principle is important as the basis for ecological theory. On a relatively simple model we show a mechanism of indefinite coexistence of complete competitors which violates the known formulations of the competitive exclusion principle. This mechanism is based on timely recovery of limiting resources and their spatio-temporal allocation between competitors. Because of limitations of the black-box modeling there was a problem to formulate the exclusion principle correctly. Our white-box multiscale model of two-species competition is based on logical deterministic individual-based cellular automata. This approach provides an automatic deductive inference on the basis of a system of axioms, and gives a direct insight into mechanisms of the studied system. It is one of the most promising methods of artificial intelligence. We reformulate and generalize the competitive exclusion principle and explain why this formulation provides a solution of the biodiversity paradox. In addition, we propose a principle of competitive coexistence.

Study on queueing behavior in pedestrian evacuation by extended cellular automata model

NASA Astrophysics Data System (ADS)

Hu, Jun; You, Lei; Zhang, Hong; Wei, Juan; Guo, Yangyong

2018-01-01

This paper proposes a pedestrian evacuation model for effective simulation of evacuation efficiency based on extended cellular automata. In the model, pedestrians' momentary transition probability to a target position is defined in terms of the floor field and queueing time, and the critical time is defined as the waiting time threshold in a queue. Queueing time and critical time are derived using Fractal Brownian Motion through analysis of pedestrian arrival characteristics. Simulations using the platform and actual evacuations were conducted to study the relationships among system evacuation time, average system velocity, pedestrian density, flow rate, and critical time. The results demonstrate that at low pedestrian density, evacuation efficiency can be improved through adoption of the shortest route strategy, and critical time has an inverse relationship with average system velocity. Conversely, at higher pedestrian densities, it is better to adopt the shortest queueing time strategy, and critical time is inversely related to flow rate.

Stochastic cellular automata model of neurosphere growth: Roles of proliferative potential, contact inhibition, cell death, and phagocytosis.

PubMed

Sipahi, Rifat; Zupanc, Günther K H

2018-05-14

Neural stem and progenitor cells isolated from the central nervous system form, under specific culture conditions, clonal cell clusters known as neurospheres. The neurosphere assay has proven to be a powerful in vitro system to study the behavior of such cells and the development of their progeny. However, the theory of neurosphere growth has remained poorly understood. To overcome this limitation, we have, in the present paper, developed a cellular automata model, with which we examined the effects of proliferative potential, contact inhibition, cell death, and clearance of dead cells on growth rate, final size, and composition of neurospheres. Simulations based on this model indicated that the proliferative potential of the founder cell and its progenitors has a major influence on neurosphere size. On the other hand, contact inhibition of proliferation limits the final size, and reduces the growth rate, of neurospheres. The effect of this inhibition is particularly dramatic when a stem cell becomes encapsulated by differentiated or other non-proliferating cells, thereby suppressing any further mitotic division - despite the existing proliferative potential of the stem cell. Conversely, clearance of dead cells through phagocytosis is predicted to accelerate growth by reducing contact inhibition. A surprising prediction derived from our model is that cell death, while resulting in a decrease in growth rate and final size of neurospheres, increases the degree of differentiation of neurosphere cells. It is likely that the cellular automata model developed as part of the present investigation is applicable to the study of tissue growth in a wide range of systems. Copyright © 2018 Elsevier Ltd. All rights reserved.

A novel chaotic based image encryption using a hybrid model of deoxyribonucleic acid and cellular automata

NASA Astrophysics Data System (ADS)

Enayatifar, Rasul; Sadaei, Hossein Javedani; Abdullah, Abdul Hanan; Lee, Malrey; Isnin, Ismail Fauzi

2015-08-01

Currently, there are many studies have conducted on developing security of the digital image in order to protect such data while they are sending on the internet. This work aims to propose a new approach based on a hybrid model of the Tinkerbell chaotic map, deoxyribonucleic acid (DNA) and cellular automata (CA). DNA rules, DNA sequence XOR operator and CA rules are used simultaneously to encrypt the plain-image pixels. To determine rule number in DNA sequence and also CA, a 2-dimension Tinkerbell chaotic map is employed. Experimental results and computer simulations, both confirm that the proposed scheme not only demonstrates outstanding encryption, but also resists various typical attacks.

Multisite Interactions in Lattice-Gas Models

NASA Astrophysics Data System (ADS)

Einstein, T. L.; Sathiyanarayanan, R.

For detailed applications of lattice-gas models to surface systems, multisite interactions often play at least as significant a role as interactions between pairs of adatoms that are separated by a few lattice spacings. We recall that trio (3-adatom, non-pairwise) interactions do not inevitably create phase boundary asymmetries about half coverage. We discuss a sophisticated application to an experimental system and describe refinements in extracting lattice-gas energies from calculations of total energies of several different ordered overlayers. We describe how lateral relaxations complicate matters when there is direct interaction between the adatoms, an issue that is important when examining the angular dependence of step line tensions. We discuss the connector model as an alternative viewpoint and close with a brief account of recent work on organic molecule overlayers.

Dirac Cellular Automaton from Split-step Quantum Walk

PubMed Central

Mallick, Arindam; Chandrashekar, C. M.

2016-01-01

Simulations of one quantum system by an other has an implication in realization of quantum machine that can imitate any quantum system and solve problems that are not accessible to classical computers. One of the approach to engineer quantum simulations is to discretize the space-time degree of freedom in quantum dynamics and define the quantum cellular automata (QCA), a local unitary update rule on a lattice. Different models of QCA are constructed using set of conditions which are not unique and are not always in implementable configuration on any other system. Dirac Cellular Automata (DCA) is one such model constructed for Dirac Hamiltonian (DH) in free quantum field theory. Here, starting from a split-step discrete-time quantum walk (QW) which is uniquely defined for experimental implementation, we recover the DCA along with all the fine oscillations in position space and bridge the missing connection between DH-DCA-QW. We will present the contribution of the parameters resulting in the fine oscillations on the Zitterbewegung frequency and entanglement. The tuneability of the evolution parameters demonstrated in experimental implementation of QW will establish it as an efficient tool to design quantum simulator and approach quantum field theory from principles of quantum information theory. PMID:27184159

Mammogram segmentation using maximal cell strength updation in cellular automata.

PubMed

Anitha, J; Peter, J Dinesh

2015-08-01

Breast cancer is the most frequently diagnosed type of cancer among women. Mammogram is one of the most effective tools for early detection of the breast cancer. Various computer-aided systems have been introduced to detect the breast cancer from mammogram images. In a computer-aided diagnosis system, detection and segmentation of breast masses from the background tissues is an important issue. In this paper, an automatic segmentation method is proposed to identify and segment the suspicious mass regions of mammogram using a modified transition rule named maximal cell strength updation in cellular automata (CA). In coarse-level segmentation, the proposed method performs an adaptive global thresholding based on the histogram peak analysis to obtain the rough region of interest. An automatic seed point selection is proposed using gray-level co-occurrence matrix-based sum average feature in the coarse segmented image. Finally, the method utilizes CA with the identified initial seed point and the modified transition rule to segment the mass region. The proposed approach is evaluated over the dataset of 70 mammograms with mass from mini-MIAS database. Experimental results show that the proposed approach yields promising results to segment the mass region in the mammograms with the sensitivity of 92.25% and accuracy of 93.48%.

Design of a fault-tolerant reversible control unit in molecular quantum-dot cellular automata

NASA Astrophysics Data System (ADS)

Bahadori, Golnaz; Houshmand, Monireh; Zomorodi-Moghadam, Mariam

Quantum-dot cellular automata (QCA) is a promising emerging nanotechnology that has been attracting considerable attention due to its small feature size, ultra-low power consuming, and high clock frequency. Therefore, there have been many efforts to design computational units based on this technology. Despite these advantages of the QCA-based nanotechnologies, their implementation is susceptible to a high error rate. On the other hand, using the reversible computing leads to zero bit erasures and no energy dissipation. As the reversible computation does not lose information, the fault detection happens with a high probability. In this paper, first we propose a fault-tolerant control unit using reversible gates which improves on the previous design. The proposed design is then synthesized to the QCA technology and is simulated by the QCADesigner tool. Evaluation results indicate the performance of the proposed approach.

Quasi-classical modeling of molecular quantum-dot cellular automata multidriver gates

NASA Astrophysics Data System (ADS)

Rahimi, Ehsan; Nejad, Shahram Mohammad

2012-05-01

Molecular quantum-dot cellular automata (mQCA) has received considerable attention in nanoscience. Unlike the current-based molecular switches, where the digital data is represented by the on/off states of the switches, in mQCA devices, binary information is encoded in charge configuration within molecular redox centers. The mQCA paradigm allows high device density and ultra-low power consumption. Digital mQCA gates are the building blocks of circuits in this paradigm. Design and analysis of these gates require quantum chemical calculations, which are demanding in computer time and memory. Therefore, developing simple models to probe mQCA gates is of paramount importance. We derive a semi-classical model to study the steady-state output polarization of mQCA multidriver gates, directly from the two-state approximation in electron transfer theory. The accuracy and validity of this model are analyzed using full quantum chemistry calculations. A complete set of logic gates, including inverters and minority voters, are implemented to provide an appropriate test bench in the two-dot mQCA regime. We also briefly discuss how the QCADesigner tool could find its application in simulation of mQCA devices.

Strategies for using cellular automata to locate constrained layer damping on vibrating structures

NASA Astrophysics Data System (ADS)

Chia, C. M.; Rongong, J. A.; Worden, K.

2009-01-01

It is often hard to optimise constrained layer damping (CLD) for structures more complicated than simple beams and plates as its performance depends on its location, the shape of the applied patch, the mode shapes of the structure and the material properties. This paper considers the use of cellular automata (CA) in conjunction with finite element analysis to obtain an efficient coverage of CLD on structures. The effectiveness of several different sets of local rules governing the CA are compared against each other for a structure with known optimum coverage—namely a plate. The algorithm which attempts to replicate most closely known optimal configurations is considered the most successful. This algorithm is then used to generate an efficient CLD treatment that targets several modes of a curved composite panel. To validate the modelling approaches used, results are also presented of a comparison between theoretical and experimentally obtained modal properties of the damped curved panel.

Cellular automata model for urban road traffic flow considering pedestrian crossing street

NASA Astrophysics Data System (ADS)

Zhao, Han-Tao; Yang, Shuo; Chen, Xiao-Xu

2016-11-01

In order to analyze the effect of pedestrians' crossing street on vehicle flows, we investigated traffic characteristics of vehicles and pedestrians. Based on that, rules of lane changing, acceleration, deceleration, randomization and update are modified. Then we established two urban two-lane cellular automata models of traffic flow, one of which is about sections with non-signalized crosswalk and the other is on uncontrolled sections with pedestrians crossing street at random. MATLAB is used for numerical simulation of the different traffic conditions; meanwhile space-time diagram and relational graphs of traffic flow parameters are generated and then comparatively analyzed. Simulation results indicate that when vehicle density is lower than around 25 vehs/(km lane), pedestrians have modest impact on traffic flow, whereas when vehicle density is higher than about 60 vehs/(km lane), traffic speed and volume will decrease significantly especially on sections with non-signal-controlled crosswalk. The results illustrate that the proposed models reconstruct the traffic flow's characteristic with the situation where there are pedestrians crossing and can provide some practical reference for urban traffic management.

Local Structure Theory for Cellular Automata.

NASA Astrophysics Data System (ADS)

Gutowitz, Howard Andrew

The local structure theory (LST) is a generalization of the mean field theory for cellular automata (CA). The mean field theory makes the assumption that iterative application of the rule does not introduce correlations between the states of cells in different positions. This assumption allows the derivation of a simple formula for the limit density of each possible state of a cell. The most striking feature of CA is that they may well generate correlations between the states of cells as they evolve. The LST takes the generation of correlation explicitly into account. It thus has the potential to describe statistical characteristics in detail. The basic assumption of the LST is that though correlation may be generated by CA evolution, this correlation decays with distance. This assumption allows the derivation of formulas for the estimation of the probability of large blocks of states in terms of smaller blocks of states. Given the probabilities of blocks of size n, probabilities may be assigned to blocks of arbitrary size such that these probability assignments satisfy the Kolmogorov consistency conditions and hence may be used to define a measure on the set of all possible (infinite) configurations. Measures defined in this way are called finite (or n-) block measures. A function called the scramble operator of order n maps a measure to an approximating n-block measure. The action of a CA on configurations induces an action on measures on the set of all configurations. The scramble operator is combined with the CA map on measure to form the local structure operator (LSO). The LSO of order n maps the set of n-block measures into itself. It is hypothesised that the LSO applied to n-block measures approximates the rule itself on general measures, and does so increasingly well as n increases. The fundamental advantage of the LSO is that its action is explicitly computable from a finite system of rational recursion equations. Empirical study of a number of CA rules

Usage Automata

NASA Astrophysics Data System (ADS)

Bartoletti, Massimo

Usage automata are an extension of finite stata automata, with some additional features (e.g. parameters and guards) that improve their expressivity. Usage automata are expressive enough to model security requirements of real-world applications; at the same time, they are simple enough to be statically amenable, e.g. they can be model-checked against abstractions of program usages. We study here some foundational aspects of usage automata. In particular, we discuss about their expressive power, and about their effective use in run-time mechanisms for enforcing usage policies.

Temperature Effects on Olive Fruit Fly Infestation in the FlySim Cellular Automata Model

NASA Astrophysics Data System (ADS)

Bruno, Vincenzo; Baldacchini, Valerio; di Gregorio, Salvatore

FlySim is a Cellular Automata model developed for simulating infestation of olive fruit flies (Bactrocera Oleae) on olive (Olea europaea) groves. The flies move into the groves looking for mature olives where eggs are spawn. This serious agricultural problem is mainly tackled by using chemical agents at the first signs of the infestation, but organic productions with no or few chemicals are strongly requested by the market. Oil made with infested olives is poor in quality, nor olives are suitable for selling in stores. The FlySim model simulates the diffusion of flies looking for mature olives and the growing of flies due to atmospheric conditions. Foreseeing an infestation is the best way to prevent it and to reduce the need of chemicals in agriculture. In this work we investigated the effects of temperature on olive fruit flies and resulting infestation during late spring and summer.

An Optimized Three-Level Design of Decoder Based on Nanoscale Quantum-Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Seyedi, Saeid; Navimipour, Nima Jafari

2018-03-01

Quantum-dot Cellular Automata (QCA) has been potentially considered as a supersede to Complementary Metal-Oxide-Semiconductor (CMOS) because of its inherent advantages. Many QCA-based logic circuits with smaller feature size, improved operating frequency, and lower power consumption than CMOS have been offered. This technology works based on electron relations inside quantum-dots. Due to the importance of designing an optimized decoder in any digital circuit, in this paper, we design, implement and simulate a new 2-to-4 decoder based on QCA with low delay, area, and complexity. The logic functionality of the 2-to-4 decoder is verified using the QCADesigner tool. The results have shown that the proposed QCA-based decoder has high performance in terms of a number of cells, covered area, and time delay. Due to the lower clock pulse frequency, the proposed 2-to-4 decoder is helpful for building QCA-based sequential digital circuits with high performance.

Molecular quantum cellular automata cell design trade-offs: latching vs. power dissipation.

PubMed

Rahimi, Ehsan; Reimers, Jeffrey R

2018-06-20

The use of molecules to enact quantum cellular automata (QCA) cells has been proposed as a new way for performing electronic logic operations at sub-nm dimensions. A key question that arises concerns whether chemical or physical processes are to be exploited. The use of chemical reactions allows the state of a switch element to be latched in molecular form, making the output of a cell independent of its inputs, but costs energy to do the reaction. Alternatively, if purely electronic polarization is manipulated then no internal latching occurs, but no power is dissipated provided the fields from the inputs change slowly compared to the molecular response times. How these scenarios pan out is discussed by considering calculated properties of the 1,4-diallylbutane cation, a species often used as a paradigm for molecular electronic switching. Utilized are results from different calculation approaches that depict the ion either as a charge-localized mixed-valence compound functioning as a bistable switch, or else as an extremely polarizable molecule with a delocalized electronic structure. Practical schemes for using molecular cells in QCA and other devices emerge.

A cellular automata based FPGA realization of a new metaheuristic bat-inspired algorithm

NASA Astrophysics Data System (ADS)

Progias, Pavlos; Amanatiadis, Angelos A.; Spataro, William; Trunfio, Giuseppe A.; Sirakoulis, Georgios Ch.

2016-10-01

Optimization algorithms are often inspired by processes occuring in nature, such as animal behavioral patterns. The main concern with implementing such algorithms in software is the large amounts of processing power they require. In contrast to software code, that can only perform calculations in a serial manner, an implementation in hardware, exploiting the inherent parallelism of single-purpose processors, can prove to be much more efficient both in speed and energy consumption. Furthermore, the use of Cellular Automata (CA) in such an implementation would be efficient both as a model for natural processes, as well as a computational paradigm implemented well on hardware. In this paper, we propose a VHDL implementation of a metaheuristic algorithm inspired by the echolocation behavior of bats. More specifically, the CA model is inspired by the metaheuristic algorithm proposed earlier in the literature, which could be considered at least as efficient than other existing optimization algorithms. The function of the FPGA implementation of our algorithm is explained in full detail and results of our simulations are also demonstrated.

QM Automata: A New Class of Restricted Quantum Membrane Automata.

PubMed

Giannakis, Konstantinos; Singh, Alexandros; Kastampolidou, Kalliopi; Papalitsas, Christos; Andronikos, Theodore

2017-01-01

The term "Unconventional Computing" describes the use of non-standard methods and models in computing. It is a recently established field, with many interesting and promising results. In this work we combine notions from quantum computing with aspects of membrane computing to define what we call QM automata. Specifically, we introduce a variant of quantum membrane automata that operate in accordance with the principles of quantum computing. We explore the functionality and capabilities of the QM automata through indicative examples. Finally we suggest future directions for research on QM automata.

Lattice gas simulations of dynamical geometry in one dimension.

PubMed

Love, Peter J; Boghosian, Bruce M; Meyer, David A

2004-08-15

We present numerical results obtained using a lattice gas model with dynamical geometry. The (irreversible) macroscopic behaviour of the geometry (size) of the lattice is discussed in terms of a simple scaling theory and obtained numerically. The emergence of irreversible behaviour from the reversible microscopic lattice gas rules is discussed in terms of the constraint that the macroscopic evolution be reproducible. The average size of the lattice exhibits power-law growth with exponent at late times. The deviation of the macroscopic behaviour from reproducibility for particular initial conditions ('rogue states') is investigated as a function of system size. The number of such 'rogue states' is observed to decrease with increasing system size. Two mean-field analyses of the macroscopic behaviour are also presented. Copyright 2004 The Royal Society

An attempt of modelling debris flows characterised by strong inertial effects through Cellular Automata

NASA Astrophysics Data System (ADS)

Iovine, G.; D'Ambrosio, D.

2003-04-01

Cellular Automata models do represent a valid method for the simulation of complex phenomena, when these latter can be described in "a-centric" terms - i.e. through local interactions within a discrete time-space. In particular, flow-type landslides (such as debris flows) can be viewed as a-centric dynamical system. SCIDDICA S4b, the last release of a family of two-dimensional hexagonal Cellular Automata models, has recently been developed for simulating debris flows characterised by strong inertial effects. It has been derived by progressively enriching an initial simplified CA model, originally derived for simulating very simple cases of slow-moving flow-type landslides. In S4b, by applying an empirical strategy, the inertial characters of the flowing mass have been translated into CA terms. In the transition function of the model, the distribution of landslide debris among the cells is computed by considering the momentum of the debris which move among the cells of the neighbourhood, and privileging the flow direction. By properly setting the value of one of the global parameters of the model (the "inertial factor"), the mechanism of distribution of the landslide debris among the cells can be influenced in order to emphasise the inertial effects, according to the energy of the flowing mass. Moreover, the high complexity of both the model and of the phenomena to be simulated (e.g. debris flows characterised by severe erosion along their path, and by strong inertial effects) suggested to employ an automated technique of evaluation, for the determination of the best set of global parameters. Accordingly, the calibration of the model has been performed through Genetic Algorithms, by considering several real cases of study: these latter have been selected among the population of landslides triggered in Campania (Southern Italy) in May 1998 and December 1999. Obtained results are satisfying: errors computed by comparing the simulations with the map of the real

Thermodynamics of a lattice gas with linear attractive potential

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pirjol, Dan; Schat, Carlos

We study the equilibrium thermodynamics of a one-dimensional lattice gas with interaction V(|i−j|)=−1/(μn) (ξ−1/n |i−j|) given by the superposition of a universal attractive interaction with strength −1/(μn) ξ<0, and a linear attractive potential 1/(μn{sup 2}) |i−j|. The interaction is rescaled with the lattice size n, such that the thermodynamical limit n → ∞ is well-behaved. The thermodynamical properties of the system can be found exactly, both for a finite size lattice and in the thermodynamical limit n → ∞. The lattice gas can be mapped to a system of non-interacting bosons which are placed on known energy levels. The exactmore » solution shows that the system has a liquid-gas phase transition for ξ > 0. In the large temperature limit T ≫ T{sub 0}(ρ) = ρ{sup 2}/(4μ) with ρ the density, the system becomes spatially homogeneous, and the equation of state is given to a good approximation by a lattice version of the van der Waals equation, with critical temperature T{sub c}{sup (vdW)}=1/(12μ) (3ξ−1)« less

Treatment Analysis in a Cancer Stem Cell Context Using a Tumor Growth Model Based on Cellular Automata.

PubMed

Monteagudo, Ángel; Santos, José

2015-01-01

Cancer can be viewed as an emergent behavior in terms of complex system theory and artificial life, Cellular Automata (CA) being the tool most used for studying and characterizing the emergent behavior. Different approaches with CA models were used to model cancer growth. The use of the abstract model of acquired cancer hallmarks permits the direct modeling at cellular level, where a cellular automaton defines the mitotic and apoptotic behavior of cells, and allows for an analysis of different dynamics of the cellular system depending on the presence of the different hallmarks. A CA model based on the presence of hallmarks in the cells, which includes a simulation of the behavior of Cancer Stem Cells (CSC) and their implications for the resultant growth behavior of the multicellular system, was employed. This modeling of cancer growth, in the avascular phase, was employed to analyze the effect of cancer treatments in a cancer stem cell context. The model clearly explains why, after treatment against non-stem cancer cells, the regrowth capability of CSCs generates a faster regrowth of tumor behavior, and also shows that a continuous low-intensity treatment does not favor CSC proliferation and differentiation, thereby allowing an unproblematic control of future tumor regrowth. The analysis performed indicates that, contrary to the current attempts at CSC control, trying to make CSC proliferation more difficult is an important point to consider, especially in the immediate period after a standard treatment for controlling non-stem cancer cell proliferation.

Mixed-valence molecular four-dot unit for quantum cellular automata: Vibronic self-trapping and cell-cell response.

PubMed

Tsukerblat, Boris; Palii, Andrew; Clemente-Juan, Juan Modesto; Coronado, Eugenio

2015-10-07

Our interest in this article is prompted by the vibronic problem of charge polarized states in the four-dot molecular quantum cellular automata (mQCA), a paradigm for nanoelectronics, in which binary information is encoded in charge configuration of the mQCA cell. Here, we report the evaluation of the electronic levels and adiabatic potentials of mixed-valence (MV) tetra-ruthenium (2Ru(ii) + 2Ru(iii)) derivatives (assembled as two coupled Creutz-Taube complexes) for which molecular implementations of quantum cellular automata (QCA) was proposed. The cell based on this molecule includes two holes shared among four spinless sites and correspondingly we employ the model which takes into account the two relevant electron transfer processes (through the side and through the diagonal of the square) as well as the difference in Coulomb energies for different instant positions of localization of the hole pair. The combined Jahn-Teller (JT) and pseudo JT vibronic coupling is treated within the conventional Piepho-Krauzs-Schatz model adapted to a bi-electronic MV species with the square-planar topology. The adiabatic potentials are evaluated for the low lying Coulomb levels in which the antipodal sites are occupied, the case just actual for utilization in mQCA. The conditions for the vibronic self-trapping in spin-singlet and spin-triplet states are revealed in terms of the two actual transfer pathways parameters and the strength of the vibronic coupling. Spin related effects in degrees of the localization which are found for spin-singlet and spin-triplet states are discussed. The polarization of the cell is evaluated and we demonstrate how the partial delocalization caused by the joint action of the vibronic coupling and electron transfer processes influences polarization of a four-dot cell. The results obtained within the adiabatic approach are compared with those based on the numerical solution of the dynamic vibronic problem. Finally, the Coulomb interaction between

A Compositional Translation of Timed Automata with Deadlines to Uppaal Timed Automata

NASA Astrophysics Data System (ADS)

Gómez, Rodolfo

Timed Automata with Deadlines (TAD) are a form of timed automata that admit a more natural representation of urgent actions, with the additional advantage of avoiding the most common form of timelocks. We offer a compositional translation of a practically useful subset of TAD to timed safety automata (the well-known variant of timed automata where time progress conditions are expressed by invariants). More precisely, we translate networks of TAD to the modeling language of Uppaal, a state-of-the-art verification tool for timed automata. We also describe an implementation of this translation, which allows Uppaal to aid the design and analysis of TAD models.

Exact diffusion constant in a lattice-gas wind-tree model on a Bethe lattice

NASA Astrophysics Data System (ADS)

Zhang, Guihua; Percus, J. K.

1992-02-01

Kong and Cohen [Phys. Rev. B 40, 4838 (1989)] obtained the diffusion constant of a lattice-gas wind-tree model in the Boltzmann approximation. The result is consistent with computer simulations for low tree concentration. In this Brief Report we find the exact diffusion constant of the model on a Bethe lattice, which turns out to be identical with the Kong-Cohen and Gunn-Ortuño results. Our interpretation is that the Boltzmann approximation is exact for this type of diffusion on a Bethe lattice in the same sense that the Bethe-Peierls approximation is exact for the Ising model on a Bethe lattice.

Modeling of the competition life cycle using the software complex of cellular automata PyCAlab

NASA Astrophysics Data System (ADS)

Berg, D. B.; Beklemishev, K. A.; Medvedev, A. N.; Medvedeva, M. A.

2015-11-01

The aim of the work is to develop a numerical model of the life cycle of competition on the basis of software complex cellular automata PyCAlab. The model is based on the general patterns of growth of various systems in resource-limited settings. At examples it is shown that the period of transition from an unlimited growth of the market agents to the stage of competitive growth takes quite a long time and may be characterized as monotonic. During this period two main strategies of competitive selection coexist: 1) capture of maximum market space with any reasonable costs; 2) saving by reducing costs. The obtained results allow concluding that the competitive strategies of companies must combine two mentioned types of behavior, and this issue needs to be given adequate attention in the academic literature on management. The created numerical model may be used for market research when developing of the strategies for promotion of new goods and services.

[A Cellular Automata Model for a Community Comprising Two Plant Species of Different Growth Forms].

PubMed

Frolov, P V; Zubkova, E V; Komarov, A S

2015-01-01

A cellular automata computer model for the interactions between two plant species of different growth forms--the lime hairgrass Deschampsia caespitosa (L.) P. Beauv., a sod cereal, and the moneywort Lysimachia nummularia L., a ground creeping perennial herb--is considered. Computer experiments on the self-maintenance of the populations of each species against the background of a gradual increase in the share of randomly eliminated individuals, coexistence of the populations of two species, and the effect of the phytogenous field have been conducted. As has been shown, all the studied factors determine the number of individuals and self-sustainability of the simulated populations by the degree of their impact. The limits of action have been determined for individual factors; within these limits, the specific features in plant reproduction and dispersal provide sustainable coexistence of the simulated populations. It has been demonstrated that the constructed model allows for studying the long-term developmental dynamics of the plants belonging to the selected growth forms.

Synthesis of a Neutral Mixed-Valence Diferrocenyl Carborane for Molecular Quantum-Dot Cellular Automata Applications.

PubMed

Christie, John A; Forrest, Ryan P; Corcelli, Steven A; Wasio, Natalie A; Quardokus, Rebecca C; Brown, Ryan; Kandel, S Alex; Lu, Yuhui; Lent, Craig S; Henderson, Kenneth W

2015-12-14

The preparation of 7-Fc(+) -8-Fc-7,8-nido-[C2 B9 H10 ](-) (Fc(+) FcC2 B9 (-) ) demonstrates the successful incorporation of a carborane cage as an internal counteranion bridging between ferrocene and ferrocenium units. This neutral mixed-valence Fe(II) /Fe(III) complex overcomes the proximal electronic bias imposed by external counterions, a practical limitation in the use of molecular switches. A combination of UV/Vis-NIR spectroscopic and TD-DFT computational studies indicate that electron transfer within Fc(+) FcC2 B9 (-) is achieved through a bridge-mediated mechanism. This electronic framework therefore provides the possibility of an all-neutral null state, a key requirement for the implementation of quantum-dot cellular automata (QCA) molecular computing. The adhesion, ordering, and characterization of Fc(+) FcC2 B9 (-) on Au(111) has been observed by scanning tunneling microscopy. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dynamics of the HIV infection under antiretroviral therapy: A cellular automata approach

NASA Astrophysics Data System (ADS)

González, Ramón E. R.; Coutinho, Sérgio; Zorzenon dos Santos, Rita Maria; de Figueirêdo, Pedro Hugo

2013-10-01

The dynamics of human immunodeficiency virus infection under antiretroviral therapy is investigated using a cellular automata model where the effectiveness of each drug is self-adjusted by the concentration of CD4+ T infected cells present at each time step. The effectiveness of the drugs and the infected cell concentration at the beginning of treatment are the control parameters of the cell population’s dynamics during therapy. The model allows describing processes of mono and combined therapies. The dynamics that emerges from this model when considering combined antiretroviral therapies reproduces with fair qualitative agreement the phases and different time scales of the process. As observed in clinical data, the results reproduce the significant decrease in the population of infected cells and a concomitant increase of the population of healthy cells in a short timescale (weeks) after the initiation of treatment. Over long time scales, early treatment with potent drugs may lead to undetectable levels of infection. For late treatment or treatments starting with a low density of CD4+ T healthy cells it was observed that the treatment may lead to a steady state in which the T cell counts are above the threshold associated with the onset of AIDS. The results obtained are validated through comparison to available clinical trial data.

Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion

NASA Astrophysics Data System (ADS)

Jokar Arsanjani, Jamal; Helbich, Marco; Kainz, Wolfgang; Darvishi Boloorani, Ali

2013-04-01

This research analyses the suburban expansion in the metropolitan area of Tehran, Iran. A hybrid model consisting of logistic regression model, Markov chain (MC), and cellular automata (CA) was designed to improve the performance of the standard logistic regression model. Environmental and socio-economic variables dealing with urban sprawl were operationalised to create a probability surface of spatiotemporal states of built-up land use for the years 2006, 2016, and 2026. For validation, the model was evaluated by means of relative operating characteristic values for different sets of variables. The approach was calibrated for 2006 by cross comparing of actual and simulated land use maps. The achieved outcomes represent a match of 89% between simulated and actual maps of 2006, which was satisfactory to approve the calibration process. Thereafter, the calibrated hybrid approach was implemented for forthcoming years. Finally, future land use maps for 2016 and 2026 were predicted by means of this hybrid approach. The simulated maps illustrate a new wave of suburban development in the vicinity of Tehran at the western border of the metropolis during the next decades.

Impact of time delay on the dynamics of SEIR epidemic model using cellular automata

NASA Astrophysics Data System (ADS)

Sharma, Natasha; Gupta, Arvind Kumar

2017-04-01

The delay of an infectious disease is significant when aiming to predict its strength and spreading patterns. In this paper the SEIR ​(susceptible-exposed-infected-recovered) epidemic spread with time delay is analyzed through a two-dimensional cellular automata model. The time delay corresponding to the infectious span, predominantly, includes death during the latency period in due course of infection. The advancement of whole system is described by SEIR transition function complemented with crucial factors like inhomogeneous population distribution, birth and disease independent mortality. Moreover, to reflect more realistic population dynamics some stochastic parameters like population movement and connections at local level are also considered. The existence and stability of disease free equilibrium is investigated. Two prime behavioral patterns of disease dynamics is found depending on delay. The critical value of delay, beyond which there are notable variations in spread patterns, is computed. The influence of important parameters affecting the disease dynamics on basic reproduction number is also examined. The results obtained show that delay plays an affirmative role to control disease progression in an infected host.

An extended cost potential field cellular automata model considering behavior variation of pedestrian flow

NASA Astrophysics Data System (ADS)

Guo, Fang; Li, Xingli; Kuang, Hua; Bai, Yang; Zhou, Huaguo

2016-11-01

The original cost potential field cellular automata describing normal pedestrian evacuation is extended to study more general evacuation scenarios. Based on the cost potential field function, through considering the psychological characteristics of crowd under emergencies, the quantitative formula of behavior variation is introduced to reflect behavioral changes caused by psychology tension. The numerical simulations are performed to investigate the effects of the magnitude of behavior variation, the different pedestrian proportions with different behavior variation and other factors on the evacuation efficiency and process in a room. The spatiotemporal dynamic characteristic during the evacuation process is also discussed. The results show that compared with the normal evacuation, the behavior variation under an emergency does not necessarily lead to the decrease of the evacuation efficiency. At low density, the increase of the behavior variation can improve the evacuation efficiency, while at high density, the evacuation efficiency drops significantly with the increasing amplitude of the behavior variation. In addition, the larger proportion of pedestrian affected by the behavior variation will prolong the evacuation time.

A cryptographic hash function based on chaotic network automata

NASA Astrophysics Data System (ADS)

Machicao, Jeaneth; Bruno, Odemir M.

2017-12-01

Chaos theory has been used to develop several cryptographic methods relying on the pseudo-random properties extracted from simple nonlinear systems such as cellular automata (CA). Cryptographic hash functions (CHF) are commonly used to check data integrity. CHF “compress” arbitrary long messages (input) into much smaller representations called hash values or message digest (output), designed to prevent the ability to reverse the hash values into the original message. This paper proposes a chaos-based CHF inspired on an encryption method based on chaotic CA rule B1357-S2468. Here, we propose an hybrid model that combines CA and networks, called network automata (CNA), whose chaotic spatio-temporal outputs are used to compute a hash value. Following the Merkle and Damgård model of construction, a portion of the message is entered as the initial condition of the network automata, so that the rest parts of messages are iteratively entered to perturb the system. The chaotic network automata shuffles the message using flexible control parameters, so that the generated hash value is highly sensitive to the message. As demonstrated in our experiments, the proposed model has excellent pseudo-randomness and sensitivity properties with acceptable performance when compared to conventional hash functions.

Social interactions of eating behaviour among high school students: a cellular automata approach

PubMed Central

2012-01-01

Background Overweight and obesity in children and adolescents is a global epidemic posing problems for both developed and developing nations. The prevalence is particularly alarming in developed nations, such as the United States, where approximately one in three school-aged adolescents (ages 12-19) are overweight or obese. Evidence suggests that weight gain in school-aged adolescents is related to energy imbalance exacerbated by the negative aspects of the school food environment, such as presence of unhealthy food choices. While a well-established connection exists between the food environment, presently there is a lack of studies investigating the impact of the social environment and associated interactions of school-age adolescents. This paper uses a mathematical modelling approach to explore how social interactions among high school adolescents can affect their eating behaviour and food choice. Methods In this paper we use a Cellular Automata (CA) modelling approach to explore how social interactions among school-age adolescents can affect eating behaviour, and food choice. Our CA model integrates social influences and transition rules to simulate the way individuals would interact in a social community (e.g., school cafeteria). To replicate these social interactions, we chose the Moore neighbourhood which allows all neighbours (eights cells in a two-dimensional square lattice) to influence the central cell. Our assumption is that individuals belong to any of four states; Bring Healthy, Bring Unhealthy, Purchase Healthy, and Purchase Unhealthy, and will influence each other according to parameter settings and transition rules. Simulations were run to explore how the different states interact under varying parameter settings. Results This study, through simulations, illustrates that students will change their eating behaviour from unhealthy to healthy as a result of positive social and environmental influences. In general, there is one common characteristic of

[Simulation of urban ecological security pattern based on cellular automata: a case of Dongguan City, Guangdong Province of South China].

PubMed

Yang, Qing-Sheng; Qiao, Ji-Gang; Ai, Bin

2013-09-01

Taking the Dongguan City with rapid urbanization as a case, and selecting landscape ecological security level as evaluation criterion, the urbanization cellular number of 1 km x 1 km ecological security cells was obtained, and imbedded into the transition rules of cellular automata (CA) as the restraint term to control urban development, establish ecological security urban CA, and simulate ecological security urban development pattern. The results showed the integrated landscape ecological security index of the City decreased from 0.497 in 1998 to 0.395 in 2005, indicating that the ecological security at landscape scale was decreased. The CA-simulated integrated ecological security index of the City in 2005 was increased from the measured 0.395 to 0.479, showing that the simulated urban landscape ecological pressure from human became lesser, ecological security became better, and integrated landscape ecological security became higher. CA could be used as an effective tool in researching urban ecological security.

Weighted Watson-Crick automata

NASA Astrophysics Data System (ADS)

Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku

2014-07-01

There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.

A living mesoscopic cellular automaton made of skin scales.

PubMed

Manukyan, Liana; Montandon, Sophie A; Fofonjka, Anamarija; Smirnov, Stanislav; Milinkovitch, Michel C

2017-04-12

In vertebrates, skin colour patterns emerge from nonlinear dynamical microscopic systems of cell interactions. Here we show that in ocellated lizards a quasi-hexagonal lattice of skin scales, rather than individual chromatophore cells, establishes a green and black labyrinthine pattern of skin colour. We analysed time series of lizard scale colour dynamics over four years of their development and demonstrate that this pattern is produced by a cellular automaton (a grid of elements whose states are iterated according to a set of rules based on the states of neighbouring elements) that dynamically computes the colour states of individual mesoscopic skin scales to produce the corresponding macroscopic colour pattern. Using numerical simulations and mathematical derivation, we identify how a discrete von Neumann cellular automaton emerges from a continuous Turing reaction-diffusion system. Skin thickness variation generated by three-dimensional morphogenesis of skin scales causes the underlying reaction-diffusion dynamics to separate into microscopic and mesoscopic spatial scales, the latter generating a cellular automaton. Our study indicates that cellular automata are not merely abstract computational systems, but can directly correspond to processes generated by biological evolution.

A living mesoscopic cellular automaton made of skin scales

NASA Astrophysics Data System (ADS)

Manukyan, Liana; Montandon, Sophie A.; Fofonjka, Anamarija; Smirnov, Stanislav; Milinkovitch, Michel C.

2017-04-01

In vertebrates, skin colour patterns emerge from nonlinear dynamical microscopic systems of cell interactions. Here we show that in ocellated lizards a quasi-hexagonal lattice of skin scales, rather than individual chromatophore cells, establishes a green and black labyrinthine pattern of skin colour. We analysed time series of lizard scale colour dynamics over four years of their development and demonstrate that this pattern is produced by a cellular automaton (a grid of elements whose states are iterated according to a set of rules based on the states of neighbouring elements) that dynamically computes the colour states of individual mesoscopic skin scales to produce the corresponding macroscopic colour pattern. Using numerical simulations and mathematical derivation, we identify how a discrete von Neumann cellular automaton emerges from a continuous Turing reaction-diffusion system. Skin thickness variation generated by three-dimensional morphogenesis of skin scales causes the underlying reaction-diffusion dynamics to separate into microscopic and mesoscopic spatial scales, the latter generating a cellular automaton. Our study indicates that cellular automata are not merely abstract computational systems, but can directly correspond to processes generated by biological evolution.

Efficient Algorithms for Handling Nondeterministic Automata

NASA Astrophysics Data System (ADS)

Vojnar, Tomáš

Finite (word, tree, or omega) automata play an important role in different areas of computer science, including, for instance, formal verification. Often, deterministic automata are used for which traditional algorithms for important operations such as minimisation and inclusion checking are available. However, the use of deterministic automata implies a need to determinise nondeterministic automata that often arise during various computations even when the computations start with deterministic automata. Unfortunately, determinisation is a very expensive step since deterministic automata may be exponentially bigger than the original nondeterministic automata. That is why, it appears advantageous to avoid determinisation and work directly with nondeterministic automata. This, however, brings a need to be able to implement operations traditionally done on deterministic automata on nondeterministic automata instead. In particular, this is the case of inclusion checking and minimisation (or rather reduction of the size of automata). In the talk, we review several recently proposed techniques for inclusion checking on nondeterministic finite word and tree automata as well as Büchi automata. These techniques are based on using the so called antichains, possibly combined with a use of suitable simulation relations (and, in the case of Büchi automata, the so called Ramsey-based or rank-based approaches). Further, we discuss techniques for reducing the size of nondeterministic word and tree automata using quotienting based on the recently proposed notion of mediated equivalences. The talk is based on several common works with Parosh Aziz Abdulla, Ahmed Bouajjani, Yu-Fang Chen, Peter Habermehl, Lisa Kaati, Richard Mayr, Tayssir Touili, Lorenzo Clemente, Lukáš Holík, and Chih-Duo Hong.

Lattice gas simulations of dynamical geometry in two dimensions.

PubMed

Klales, Anna; Cianci, Donato; Needell, Zachary; Meyer, David A; Love, Peter J

2010-10-01

We present a hydrodynamic lattice gas model for two-dimensional flows on curved surfaces with dynamical geometry. This model is an extension to two dimensions of the dynamical geometry lattice gas model previously studied in one dimension. We expand upon a variation of the two-dimensional flat space Frisch-Hasslacher-Pomeau (FHP) model created by Frisch [Phys. Rev. Lett. 56, 1505 (1986)] and independently by Wolfram, and modified by Boghosian [Philos. Trans. R. Soc. London, Ser. A 360, 333 (2002)]. We define a hydrodynamic lattice gas model on an arbitrary triangulation whose flat space limit is the FHP model. Rules that change the geometry are constructed using the Pachner moves, which alter the triangulation but not the topology. We present results on the growth of the number of triangles as a function of time. Simulations show that the number of triangles grows with time as t(1/3), in agreement with a mean-field prediction. We also present preliminary results on the distribution of curvature for a typical triangulation in these simulations.

High-performance multiprocessor architecture for a 3-D lattice gas model

NASA Technical Reports Server (NTRS)

Lee, F.; Flynn, M.; Morf, M.

1991-01-01

The lattice gas method has recently emerged as a promising discrete particle simulation method in areas such as fluid dynamics. We present a very high-performance scalable multiprocessor architecture, called ALGE, proposed for the simulation of a realistic 3-D lattice gas model, Henon's 24-bit FCHC isometric model. Each of these VLSI processors is as powerful as a CRAY-2 for this application. ALGE is scalable in the sense that it achieves linear speedup for both fixed and increasing problem sizes with more processors. The core computation of a lattice gas model consists of many repetitions of two alternating phases: particle collision and propagation. Functional decomposition by symmetry group and virtual move are the respective keys to efficient implementation of collision and propagation.

Optimal placement of fast cut back units based on the theory of cellular automata and agent

NASA Astrophysics Data System (ADS)

Yan, Jun; Yan, Feng

2017-06-01

The thermal power generation units with the function of fast cut back could serve power for auxiliary system and keep island operation after a major blackout, so they are excellent substitute for the traditional black-start power sources. Different placement schemes for FCB units have different influence on the subsequent restoration process. Considering the locality of the emergency dispatching rules, the unpredictability of specific dispatching instructions and unexpected situations like failure of transmission line energization, a novel deduction model for network reconfiguration based on the theory of cellular automata and agent is established. Several indexes are then defined for evaluating the placement schemes for FCB units. The attribute weights determination method based on subjective and objective integration and grey relational analysis are combinatorically used to determine the optimal placement scheme for FCB unit. The effectiveness of the proposed method is validated by the test results on the New England 10-unit 39-bus power system.

Prediction of lung cells oncogenic transformation for induced radon progeny alpha particles using sugarscape cellular automata.

PubMed

Baradaran, Samaneh; Maleknasr, Niaz; Setayeshi, Saeed; Akbari, Mohammad Esmaeil

2014-01-01

Alpha particle irradiation from radon progeny is one of the major natural sources of effective dose in the public population. Oncogenic transformation is a biological effectiveness of radon progeny alpha particle hits. The biological effects which has caused by exposure to radon, were the main result of a complex series of physical, chemical, biological and physiological interactions. The cellular and molecular mechanisms for radon-induced carcinogenesis have not been clear yet. Various biological models, including cultured cells and animals, have been found useful for studying the carcinogenesis effects of radon progeny alpha particles. In this paper, sugars cape cellular automata have been presented for computational study of complex biological effect of radon progeny alpha particles in lung bronchial airways. The model has included mechanism of DNA damage, which has been induced alpha particles hits, and then formation of transformation in the lung cells. Biomarkers were an objective measure or evaluation of normal or abnormal biological processes. In the model, the metabolism rate of infected cell has been induced alpha particles traversals, as a biomarker, has been followed to reach oncogenic transformation. The model results have successfully validated in comparison with "in vitro oncogenic transformation data" for C3H 10T1/2 cells. This model has provided an opportunity to study the cellular and molecular changes, at the various stages in radiation carcinogenesis, involving human cells. It has become well known that simulation could be used to investigate complex biomedical systems, in situations where traditional methodologies were difficult or too costly to employ.

Designing Nanoscale Counter Using Reversible Gate Based on Quantum-Dot Cellular Automata

NASA Astrophysics Data System (ADS)

Moharrami, Elham; Navimipour, Nima Jafari

2018-04-01

Some new technologies such as Quantum-dot Cellular Automata (QCA) is suggested to solve the physical limits of the Complementary Metal-Oxide Semiconductor (CMOS) technology. The QCA as one of the novel technologies at nanoscale has potential applications in future computers. This technology has some advantages such as minimal size, high speed, low latency, and low power consumption. As a result, it is used for creating all varieties of memory. Counter circuits as one of the important circuits in the digital systems are composed of some latches, which are connected to each other in series and actually they count input pulses in the circuit. On the other hand, the reversible computations are very important because of their ability in reducing energy in nanometer circuits. Improving the energy efficiency, increasing the speed of nanometer circuits, increasing the portability of system, making smaller components of the circuit in a nuclear size and reducing the power consumption are considered as the usage of reversible logic. Therefore, this paper aims to design a two-bit reversible counter that is optimized on the basis of QCA using an improved reversible gate. The proposed reversible structure of 2-bit counter can be increased to 3-bit, 4-bit and more. The advantages of the proposed design have been shown using QCADesigner in terms of the delay in comparison with previous circuits.

Canalization and Control in Automata Networks: Body Segmentation in Drosophila melanogaster

PubMed Central

Marques-Pita, Manuel; Rocha, Luis M.

2013-01-01

We present schema redescription as a methodology to characterize canalization in automata networks used to model biochemical regulation and signalling. In our formulation, canalization becomes synonymous with redundancy present in the logic of automata. This results in straightforward measures to quantify canalization in an automaton (micro-level), which is in turn integrated into a highly scalable framework to characterize the collective dynamics of large-scale automata networks (macro-level). This way, our approach provides a method to link micro- to macro-level dynamics – a crux of complexity. Several new results ensue from this methodology: uncovering of dynamical modularity (modules in the dynamics rather than in the structure of networks), identification of minimal conditions and critical nodes to control the convergence to attractors, simulation of dynamical behaviour from incomplete information about initial conditions, and measures of macro-level canalization and robustness to perturbations. We exemplify our methodology with a well-known model of the intra- and inter cellular genetic regulation of body segmentation in Drosophila melanogaster. We use this model to show that our analysis does not contradict any previous findings. But we also obtain new knowledge about its behaviour: a better understanding of the size of its wild-type attractor basin (larger than previously thought), the identification of novel minimal conditions and critical nodes that control wild-type behaviour, and the resilience of these to stochastic interventions. Our methodology is applicable to any complex network that can be modelled using automata, but we focus on biochemical regulation and signalling, towards a better understanding of the (decentralized) control that orchestrates cellular activity – with the ultimate goal of explaining how do cells and tissues ‘compute’. PMID:23520449

Canalization and control in automata networks: body segmentation in Drosophila melanogaster.

PubMed

Marques-Pita, Manuel; Rocha, Luis M

2013-01-01

We present schema redescription as a methodology to characterize canalization in automata networks used to model biochemical regulation and signalling. In our formulation, canalization becomes synonymous with redundancy present in the logic of automata. This results in straightforward measures to quantify canalization in an automaton (micro-level), which is in turn integrated into a highly scalable framework to characterize the collective dynamics of large-scale automata networks (macro-level). This way, our approach provides a method to link micro- to macro-level dynamics--a crux of complexity. Several new results ensue from this methodology: uncovering of dynamical modularity (modules in the dynamics rather than in the structure of networks), identification of minimal conditions and critical nodes to control the convergence to attractors, simulation of dynamical behaviour from incomplete information about initial conditions, and measures of macro-level canalization and robustness to perturbations. We exemplify our methodology with a well-known model of the intra- and inter cellular genetic regulation of body segmentation in Drosophila melanogaster. We use this model to show that our analysis does not contradict any previous findings. But we also obtain new knowledge about its behaviour: a better understanding of the size of its wild-type attractor basin (larger than previously thought), the identification of novel minimal conditions and critical nodes that control wild-type behaviour, and the resilience of these to stochastic interventions. Our methodology is applicable to any complex network that can be modelled using automata, but we focus on biochemical regulation and signalling, towards a better understanding of the (decentralized) control that orchestrates cellular activity--with the ultimate goal of explaining how do cells and tissues 'compute'.

On complexity and homogeneity measures in predicting biological aggressiveness of prostate cancer; Implication of the cellular automata model of tumor growth.

PubMed

Tanase, Mihai; Waliszewski, Przemyslaw

2015-12-01

We propose a novel approach for the quantitative evaluation of aggressiveness in prostate carcinomas. The spatial distribution of cancer cell nuclei was characterized by the global spatial fractal dimensions D0, D1, and D2. Two hundred eighteen prostate carcinomas were stratified into the classes of equivalence using results of ROC analysis. A simulation of the cellular automata mix defined a theoretical frame for a specific geometric representation of the cell nuclei distribution called a local structure correlation diagram (LSCD). The LSCD and dispersion Hd were computed for each carcinoma. Data mining generated some quantitative criteria describing tumor aggressiveness. Alterations in tumor architecture along progression were associated with some changes in both shape and the quantitative characteristics of the LSCD consistent with those in the automata mix model. Low-grade prostate carcinomas with low complexity and very low biological aggressiveness are defined by the condition D0 < 1.545 and Hd < 38. High-grade carcinomas with high complexity and very high biological aggressiveness are defined by the condition D0 > 1.764 and Hd < 38. The novel homogeneity measure Hd identifies carcinomas with very low aggressiveness within the class of complexity C1 or carcinomas with very high aggressiveness in the class C7. © 2015 Wiley Periodicals, Inc.

Mixed-valence molecular four-dot unit for quantum cellular automata: Vibronic self-trapping and cell-cell response

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsukerblat, Boris, E-mail: tsuker@bgu.ac.il, E-mail: andrew.palii@uv.es; Palii, Andrew, E-mail: tsuker@bgu.ac.il, E-mail: andrew.palii@uv.es; Clemente-Juan, Juan Modesto

2015-10-07

Our interest in this article is prompted by the vibronic problem of charge polarized states in the four-dot molecular quantum cellular automata (mQCA), a paradigm for nanoelectronics, in which binary information is encoded in charge configuration of the mQCA cell. Here, we report the evaluation of the electronic levels and adiabatic potentials of mixed-valence (MV) tetra-ruthenium (2Ru(II) + 2Ru(III)) derivatives (assembled as two coupled Creutz-Taube complexes) for which molecular implementations of quantum cellular automata (QCA) was proposed. The cell based on this molecule includes two holes shared among four spinless sites and correspondingly we employ the model which takes into accountmore » the two relevant electron transfer processes (through the side and through the diagonal of the square) as well as the difference in Coulomb energies for different instant positions of localization of the hole pair. The combined Jahn-Teller (JT) and pseudo JT vibronic coupling is treated within the conventional Piepho-Krauzs-Schatz model adapted to a bi-electronic MV species with the square-planar topology. The adiabatic potentials are evaluated for the low lying Coulomb levels in which the antipodal sites are occupied, the case just actual for utilization in mQCA. The conditions for the vibronic self-trapping in spin-singlet and spin-triplet states are revealed in terms of the two actual transfer pathways parameters and the strength of the vibronic coupling. Spin related effects in degrees of the localization which are found for spin-singlet and spin-triplet states are discussed. The polarization of the cell is evaluated and we demonstrate how the partial delocalization caused by the joint action of the vibronic coupling and electron transfer processes influences polarization of a four-dot cell. The results obtained within the adiabatic approach are compared with those based on the numerical solution of the dynamic vibronic problem. Finally, the Coulomb interaction

Definition and application of a five-parameter characterization of one-dimensional cellular automata rule space.

PubMed

Oliveira, G M; de Oliveira, P P; Omar, N

2001-01-01

Cellular automata (CA) are important as prototypical, spatially extended, discrete dynamical systems. Because the problem of forecasting dynamic behavior of CA is undecidable, various parameter-based approximations have been developed to address the problem. Out of the analysis of the most important parameters available to this end we proposed some guidelines that should be followed when defining a parameter of that kind. Based upon the guidelines, new parameters were proposed and a set of five parameters was selected; two of them were drawn from the literature and three are new ones, defined here. This article presents all of them and makes their qualities evident. Then, two results are described, related to the use of the parameter set in the Elementary Rule Space: a phase transition diagram, and some general heuristics for forecasting the dynamics of one-dimensional CA. Finally, as an example of the application of the selected parameters in high cardinality spaces, results are presented from experiments involving the evolution of radius-3 CA in the Density Classification Task, and radius-2 CA in the Synchronization Task.

Tuning of quantum entanglement in molecular quantum cellular automata based on mixed-valence tetrameric units.

PubMed

Palii, Andrew; Tsukerblat, Boris

2016-10-25

In this article we consider two coupled tetrameric mixed-valence (MV) units accommodating electron pairs, which play the role of cells in molecular quantum cellular automata. It is supposed that the Coulombic interaction between instantly localized electrons within the cell markedly inhibits the transfer processes between the redox centers. Under this condition, as well as due to the vibronic localization of the electron pair, the cell can encode binary information, which is controlled by neighboring cells. We show that under certain conditions the two low-lying vibronic spin levels of the cell (ground and first excited states) can be regarded as originating from an effective spin-spin interaction. This is shown to depend on the internal parameters of the cell as well as on the induced polarization. Within this simplified two-level picture we evaluate the quantum entanglement in the system represented by the two electrons in the cell and show how the entanglement within the cell and concurrence can be controlled via polarization of the neighboring cells and temperature.

Cellular automata model for drug release from binary matrix and reservoir polymeric devices.

PubMed

Johannes Laaksonen, Timo; Mikael Laaksonen, Hannu; Tapio Hirvonen, Jouni; Murtomäki, Lasse

2009-04-01

Kinetics of drug release from polymeric tablets, inserts and implants is an important and widely studied area. Here we present a new and widely applicable cellular automata model for diffusion and erosion processes occurring during drug release from polymeric drug release devices. The model divides a 2D representation of the release device into an array of cells. Each cell contains information about the material, drug, polymer or solvent that the domain contains. Cells are then allowed to rearrange according to statistical rules designed to match realistic drug release. Diffusion is modeled by a random walk of mobile cells and kinetics of chemical or physical processes by probabilities of conversion from one state to another. This is according to the basis of diffusion coefficients and kinetic rate constants, which are on fundamental level just probabilities for certain occurrences. The model is applied to three kinds of devices with different release mechanisms: erodable matrices, diffusion through channels or pores and membrane controlled release. The dissolution curves obtained are compared to analytical models from literature and the validity of the model is considered. The model is shown to be compatible with all three release devices, highlighting easy adaptability of the model to virtually any release system and geometry. Further extension and applications of the model are envisioned.

Land use change modeling through scenario-based cellular automata Markov: improving spatial forecasting.

PubMed

Jahanishakib, Fatemeh; Mirkarimi, Seyed Hamed; Salmanmahiny, Abdolrassoul; Poodat, Fatemeh

2018-05-08

Efficient land use management requires awareness of past changes, present actions, and plans for future developments. Part of these requirements is achieved using scenarios that describe a future situation and the course of changes. This research aims to link scenario results with spatially explicit and quantitative forecasting of land use development. To develop land use scenarios, SMIC PROB-EXPERT and MORPHOL methods were used. It revealed eight scenarios as the most probable. To apply the scenarios, we considered population growth rate and used a cellular automata-Markov chain (CA-MC) model to implement the quantified changes described by each scenario. For each scenario, a set of landscape metrics was used to assess the ecological integrity of land use classes in terms of fragmentation and structural connectivity. The approach enabled us to develop spatial scenarios of land use change and detect their differences for choosing the most integrated landscape pattern in terms of landscape metrics. Finally, the comparison between paired forecasted scenarios based on landscape metrics indicates that scenarios 1-1, 2-2, 3-2, and 4-1 have a more suitable integrity. The proposed methodology for developing spatial scenarios helps executive managers to create scenarios with many repetitions and customize spatial patterns in real world applications and policies.

Cellular automata-based modelling and simulation of biofilm structure on multi-core computers.

PubMed

Skoneczny, Szymon

2015-01-01

The article presents a mathematical model of biofilm growth for aerobic biodegradation of a toxic carbonaceous substrate. Modelling of biofilm growth has fundamental significance in numerous processes of biotechnology and mathematical modelling of bioreactors. The process following double-substrate kinetics with substrate inhibition proceeding in a biofilm has not been modelled so far by means of cellular automata. Each process in the model proposed, i.e. diffusion of substrates, uptake of substrates, growth and decay of microorganisms and biofilm detachment, is simulated in a discrete manner. It was shown that for flat biofilm of constant thickness, the results of the presented model agree with those of a continuous model. The primary outcome of the study was to propose a mathematical model of biofilm growth; however a considerable amount of focus was also placed on the development of efficient algorithms for its solution. Two parallel algorithms were created, differing in the way computations are distributed. Computer programs were created using OpenMP Application Programming Interface for C++ programming language. Simulations of biofilm growth were performed on three high-performance computers. Speed-up coefficients of computer programs were compared. Both algorithms enabled a significant reduction of computation time. It is important, inter alia, in modelling and simulation of bioreactor dynamics.

A cellular automata model for avascular solid tumor growth under the effect of therapy

NASA Astrophysics Data System (ADS)

Reis, E. A.; Santos, L. B. L.; Pinho, S. T. R.

2009-04-01

Tumor growth has long been a target of investigation within the context of mathematical and computer modeling. The objective of this study is to propose and analyze a two-dimensional stochastic cellular automata model to describe avascular solid tumor growth, taking into account both the competition between cancer cells and normal cells for nutrients and/or space and a time-dependent proliferation of cancer cells. Gompertzian growth, characteristic of some tumors, is described and some of the features of the time-spatial pattern of solid tumors, such as compact morphology with irregular borders, are captured. The parameter space is studied in order to analyze the occurrence of necrosis and the response to therapy. Our findings suggest that transitions exist between necrotic and non-necrotic phases (no-therapy cases), and between the states of cure and non-cure (therapy cases). To analyze cure, the control and order parameters are, respectively, the highest probability of cancer cell proliferation and the probability of the therapeutic effect on cancer cells. With respect to patterns, it is possible to observe the inner necrotic core and the effect of the therapy destroying the tumor from its outer borders inwards.

Safety impacts of red light cameras at signalized intersections based on cellular automata models.

PubMed

Chai, C; Wong, Y D; Lum, K M

2015-01-01

This study applies a simulation technique to evaluate the hypothesis that red light cameras (RLCs) exert important effects on accident risks. Conflict occurrences are generated by simulation and compared at intersections with and without RLCs to assess the impact of RLCs on several conflict types under various traffic conditions. Conflict occurrences are generated through simulating vehicular interactions based on an improved cellular automata (CA) model. The CA model is calibrated and validated against field observations at approaches with and without RLCs. Simulation experiments are conducted for RLC and non-RLC intersections with different geometric layouts and traffic demands to generate conflict occurrences that are analyzed to evaluate the hypothesis that RLCs exert important effects on road safety. The comparison of simulated conflict occurrences show favorable safety impacts of RLCs on crossing conflicts and unfavorable impacts for rear-end conflicts during red/amber phases. Corroborative results are found from broad analysis of accident occurrence. RLCs are found to have a mixed effect on accident risk at signalized intersections: crossing collisions are reduced, whereas rear-end collisions may increase. The specially developed CA model is found to be a feasible safety assessment tool.

Estimation of the spatiotemporal dynamics of snow covered area by using cellular automata models

NASA Astrophysics Data System (ADS)

Pardo-Igúzquiza, Eulogio; Collados-Lara, Antonio-Juan; Pulido-Velazquez, David

2017-07-01

Given the need to consider the cryosphere in water resources management for mountainous regions, the purpose of this paper is to model the daily spatially distributed dynamics of snow covered area (SCA) by using calibrated cellular automata models. For the operational use of the calibrated model, the only data requirements are the altitude of each cell of the spatial discretization of the area of interest and precipitation and temperature indexes for the area of interest. For the calibration step, experimental snow covered area data are needed. Potential uses of the model are to estimate the snow covered area when satellite data are absent, or when they provide a temporal resolution different from the operational resolution, or when the satellite images are useless because they are covered by clouds or because there has been a sensor failure. Another interesting application is the simulation of SCA dynamics for the snow covered area under future climatic scenarios. The model is applied to the Sierra Nevada mountain range, in southern Spain, which is home to significant biodiversity, contains important water resources in its snowpack, and contains the most meridional ski resort in Europe.

A Unified Theory of Non-Ideal Gas Lattice Boltzmann Models

NASA Technical Reports Server (NTRS)

Luo, Li-Shi

1998-01-01

A non-ideal gas lattice Boltzmann model is directly derived, in an a priori fashion, from the Enskog equation for dense gases. The model is rigorously obtained by a systematic procedure to discretize the Enskog equation (in the presence of an external force) in both phase space and time. The lattice Boltzmann model derived here is thermodynamically consistent and is free of the defects which exist in previous lattice Boltzmann models for non-ideal gases. The existing lattice Boltzmann models for non-ideal gases are analyzed and compared with the model derived here.

A probabilistic cellular automata model for the dynamics of a population driven by logistic growth and weak Allee effect

NASA Astrophysics Data System (ADS)

Mendonça, J. R. G.

2018-04-01

We propose and investigate a one-parameter probabilistic mixture of one-dimensional elementary cellular automata under the guise of a model for the dynamics of a single-species unstructured population with nonoverlapping generations in which individuals have smaller probability of reproducing and surviving in a crowded neighbourhood but also suffer from isolation and dispersal. Remarkably, the first-order mean field approximation to the dynamics of the model yields a cubic map containing terms representing both logistic and weak Allee effects. The model has a single absorbing state devoid of individuals, but depending on the reproduction and survival probabilities can achieve a stable population. We determine the critical probability separating these two phases and find that the phase transition between them is in the directed percolation universality class of critical behaviour.

Validating Cellular Automata Lava Flow Emplacement Algorithms with Standard Benchmarks

NASA Astrophysics Data System (ADS)

Richardson, J. A.; Connor, L.; Charbonnier, S. J.; Connor, C.; Gallant, E.

2015-12-01

A major existing need in assessing lava flow simulators is a common set of validation benchmark tests. We propose three levels of benchmarks which test model output against increasingly complex standards. First, imulated lava flows should be morphologically identical, given changes in parameter space that should be inconsequential, such as slope direction. Second, lava flows simulated in simple parameter spaces can be tested against analytical solutions or empirical relationships seen in Bingham fluids. For instance, a lava flow simulated on a flat surface should produce a circular outline. Third, lava flows simulated over real world topography can be compared to recent real world lava flows, such as those at Tolbachik, Russia, and Fogo, Cape Verde. Success or failure of emplacement algorithms in these validation benchmarks can be determined using a Bayesian approach, which directly tests the ability of an emplacement algorithm to correctly forecast lava inundation. Here we focus on two posterior metrics, P(A|B) and P(¬A|¬B), which describe the positive and negative predictive value of flow algorithms. This is an improvement on less direct statistics such as model sensitivity and the Jaccard fitness coefficient. We have performed these validation benchmarks on a new, modular lava flow emplacement simulator that we have developed. This simulator, which we call MOLASSES, follows a Cellular Automata (CA) method. The code is developed in several interchangeable modules, which enables quick modification of the distribution algorithm from cell locations to their neighbors. By assessing several different distribution schemes with the benchmark tests, we have improved the performance of MOLASSES to correctly match early stages of the 2012-3 Tolbachik Flow, Kamchakta Russia, to 80%. We also can evaluate model performance given uncertain input parameters using a Monte Carlo setup. This illuminates sensitivity to model uncertainty.

Coupling Cellular Automata Land Use Change with Distributed Hydrologic Models

NASA Astrophysics Data System (ADS)

Shu, L.; Duffy, C.

2017-12-01

There has been extensive research on LUC modeling with broad applications to simulating urban growth and changing demographic patterns across multiple scales. The importance of land conversion is a critical issue in watershed scale studies and is generally not treated in most watershed modeling approaches. In this study we apply spatially explicit hydrologic and landuse change models and the Conestoga Watershed in Lancaster County, Pennsylvania. The Penn State Integrated Hydrologic Model (PIHM) partitions the water balance in space and time over the urban catchment, the coupled Cellular Automata Land Use Change model (CALUC) dynamically simulates the evolution of land use classes based on physical measures associated with population change and land use demand factors. The CALUC model is based on iteratively applying discrete rules to each individual spatial cell. The essence the CA modeling involves calculation of the Transition Potential (TP) for conversion of a grid cell from one land use class to another. This potential includes five factors: random perturbation, suitability, accessibility, neighborhood effect, inertia effects and zonal factors. In spite of simplicity, this CALUC model has been shown to be very effective for simulating LUC leading to the emergence of complex spatial patterns. The components of TP are derived from present land use data for landuse reanalysis and for realistic future land use scenarios. For the CALUC we use early-settlement (circa 1790) initial land class values and final or present-day (2010) land classes to calibrate the model. CALUC- PIHM dynamically simulates the hydrologic response of conversion from pre-settlement to present landuse. The simulations highlight the capability and value of dynamic coupling of catchment hydrology with land use change over long time periods. Analysis of the simulation uses various metrics such as the distributed water balance, flow duration curves, etc. to show how deforestation, urbanization and

Reversible elementary cellular automaton with rule number 150 and periodic boundary conditions over 𝔽p

NASA Astrophysics Data System (ADS)

Martín Del Rey, A.; Rodríguez Sánchez, G.

2015-03-01

The study of the reversibility of elementary cellular automata with rule number 150 over the finite state set 𝔽p and endowed with periodic boundary conditions is done. The dynamic of such discrete dynamical systems is characterized by means of characteristic circulant matrices, and their analysis allows us to state that the reversibility depends on the number of cells of the cellular space and to explicitly compute the corresponding inverse cellular automata.

Modeling biological pathway dynamics with timed automata.

PubMed

Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

2014-05-01

Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

A hybrid gene selection approach for microarray data classification using cellular learning automata and ant colony optimization.

PubMed

Vafaee Sharbaf, Fatemeh; Mosafer, Sara; Moattar, Mohammad Hossein

2016-06-01

This paper proposes an approach for gene selection in microarray data. The proposed approach consists of a primary filter approach using Fisher criterion which reduces the initial genes and hence the search space and time complexity. Then, a wrapper approach which is based on cellular learning automata (CLA) optimized with ant colony method (ACO) is used to find the set of features which improve the classification accuracy. CLA is applied due to its capability to learn and model complicated relationships. The selected features from the last phase are evaluated using ROC curve and the most effective while smallest feature subset is determined. The classifiers which are evaluated in the proposed framework are K-nearest neighbor; support vector machine and naïve Bayes. The proposed approach is evaluated on 4 microarray datasets. The evaluations confirm that the proposed approach can find the smallest subset of genes while approaching the maximum accuracy. Copyright © 2016 Elsevier Inc. All rights reserved.

Algorithm for repairing the damaged images of grain structures obtained from the cellular automata and measurement of grain size

NASA Astrophysics Data System (ADS)

Ramírez-López, A.; Romero-Romo, M. A.; Muñoz-Negron, D.; López-Ramírez, S.; Escarela-Pérez, R.; Duran-Valencia, C.

2012-10-01

Computational models are developed to create grain structures using mathematical algorithms based on the chaos theory such as cellular automaton, geometrical models, fractals, and stochastic methods. Because of the chaotic nature of grain structures, some of the most popular routines are based on the Monte Carlo method, statistical distributions, and random walk methods, which can be easily programmed and included in nested loops. Nevertheless, grain structures are not well defined as the results of computational errors and numerical inconsistencies on mathematical methods. Due to the finite definition of numbers or the numerical restrictions during the simulation of solidification, damaged images appear on the screen. These images must be repaired to obtain a good measurement of grain geometrical properties. Some mathematical algorithms were developed to repair, measure, and characterize grain structures obtained from cellular automata in the present work. An appropriate measurement of grain size and the corrected identification of interfaces and length are very important topics in materials science because they are the representation and validation of mathematical models with real samples. As a result, the developed algorithms are tested and proved to be appropriate and efficient to eliminate the errors and characterize the grain structures.

Design and implementation of an efficient single layer five input majority voter gate in quantum-dot cellular automata.

PubMed

Bahar, Ali Newaz; Waheed, Sajjad

2016-01-01

The fundamental logical element of a quantum-dot cellular automata (QCA) circuit is majority voter gate (MV). The efficiency of a QCA circuit is depends on the efficiency of the MV. This paper presents an efficient single layer five-input majority voter gate (MV5). The structure of proposed MV5 is very simple and easy to implement in any logical circuit. This proposed MV5 reduce number of cells and use conventional QCA cells. However, using MV5 a multilayer 1-bit full-adder (FA) is designed. The functional accuracy of the proposed MV5 and FA are confirmed by QCADesigner a well-known QCA layout design and verification tools. Furthermore, the power dissipation of proposed circuits are estimated, which shows that those circuits dissipate extremely small amount of energy and suitable for reversible computing. The simulation outcomes demonstrate the superiority of the proposed circuit.

Phase change cellular automata modeling of GeTe, GaSb and SnSe stacked chalcogenide films

NASA Astrophysics Data System (ADS)

Mihai, C.; Velea, A.

2018-06-01

Data storage needs are increasing at a rapid pace across all economic sectors, so the need for new memory technologies with adequate capabilities is also high. Phase change memories (PCMs) are a leading contender in the emerging race for non-volatile memories due to their fast operation speed, high scalability, good reliability and low power consumption. However, in order to meet the present and future storage demands, PCM technologies must further increase the storage density. Here, we employ a probabilistic cellular automata approach to explore the multi-step threshold switching from the reset (off) to the set (on) state in chalcogenide stacked structures. Simulations have shown that in order to obtain multi-step switching with high contrast among different resistance states, the stacked structure needs to contain materials with a large difference among their crystallization temperatures and careful tuning of strata thicknesses. The crystallization dynamics can be controlled through the external energy pulses applied to the system, in such a way that a balance between nucleation and growth in phase change behavior can be achieved, optimized for PCMs.

Micro-simulation of vehicle conflicts involving right-turn vehicles at signalized intersections based on cellular automata.

PubMed

Chai, C; Wong, Y D

2014-02-01

At intersection, vehicles coming from different directions conflict with each other. Improper geometric design and signal settings at signalized intersection will increase occurrence of conflicts between road users and results in a reduction of the safety level. This study established a cellular automata (CA) model to simulate vehicular interactions involving right-turn vehicles (as similar to left-turn vehicles in US). Through various simulation scenarios for four case cross-intersections, the relationships between conflict occurrences involving right-turn vehicles with traffic volume and right-turn movement control strategies are analyzed. Impacts of traffic volume, permissive right-turn compared to red-amber-green (RAG) arrow, shared straight-through and right-turn lane as well as signal setting are estimated from simulation results. The simulation model is found to be able to provide reasonable assessment of conflicts through comparison of existed simulation approach and observed accidents. Through the proposed approach, prediction models for occurrences and severity of vehicle conflicts can be developed for various geometric layouts and traffic control strategies. Copyright © 2013 Elsevier Ltd. All rights reserved.

Evaluation of the dispersion effect in through movement bicycles at signalized intersection via cellular automata simulation

NASA Astrophysics Data System (ADS)

Jiang, Hang; Ma, Yongjian; Jiang, Lin; Chen, Guozhou; Wang, Dongwei

2018-05-01

At signalized intersection areas, bicycle traffic presents a dispersion feature which may influence the movements of vehicles during peak period. The primary objective of this study is to simulate the dispersion effect in through-movement bicycle traffic at intersection areas and evaluate its influence on through-movement traffic. A cellular automata (CA) model is developed and validated to simulate the operations of through-movement bicycle traffic departing from two types of intersection approaches. Simulation results show that bicycles benefit from the dispersion effect when they depart from the approach with an exclusive right-turn vehicle lane. But when bicycles travel from the approach with a shared right-turn and through vehicle lane, the dispersion effect will result in friction interference and block interference on through-movement vehicles. Bicycle interferences reduce the vehicle speed and increase the delay of through-movement vehicles. The policy implications in regard to the dispersion effect from two types of approaches are discussed to improve the performance of through-movement traffic operations at signalized intersections.

Analysis of Architectural Building Design Influences on Fire Spread in Densely Urban Settlement using Cellular Automata

NASA Astrophysics Data System (ADS)

Tambunan, L.; Salamah, H.; Asriana, N.

2017-03-01

This study aims to determine the influence of architectural design on the risk of fire spread in densely urban settlement area. Cellular Automata (CA) is used to analyse the fire spread pattern, speed, and the extent of damage. Four cells represent buildings, streets, and fields characteristic in the simulated area, as well as their flammability level and fire spread capabilities. Two fire scenarios are used to model the spread of fire: (1) fire origin in a building with concrete and wood material majority, and (2) fire origin in building with wood material majority. Building shape, building distance, road width, and total area of wall openings are considered constant, while wind is ignored. The result shows that fire spread faster in the building area with wood majority than with concrete majority. Significant amount of combustible building material, absence of distance between buildings, narrow streets and limited fields are factors which influence fire spread speed and pattern as well as extent of damage when fire occurs in the densely urban settlement area.

Bennett clocking of quantum-dot cellular automata and the limits to binary logic scaling.

PubMed

Lent, Craig S; Liu, Mo; Lu, Yuhui

2006-08-28

We examine power dissipation in different clocking schemes for molecular quantum-dot cellular automata (QCA) circuits. 'Landauer clocking' involves the adiabatic transition of a molecular cell from the null state to an active state carrying data. Cell layout creates devices which allow data in cells to interact and thereby perform useful computation. We perform direct solutions of the equation of motion for the system in contact with the thermal environment and see that Landauer's Principle applies: one must dissipate an energy of at least k(B)T per bit only when the information is erased. The ideas of Bennett can be applied to keep copies of the bit information by echoing inputs to outputs, thus embedding any logically irreversible circuit in a logically reversible circuit, at the cost of added circuit complexity. A promising alternative which we term 'Bennett clocking' requires only altering the timing of the clocking signals so that bit information is simply held in place by the clock until a computational block is complete, then erased in the reverse order of computation. This approach results in ultralow power dissipation without additional circuit complexity. These results offer a concrete example in which to consider recent claims regarding the fundamental limits of binary logic scaling.

Modelling land use/cover changes with markov-cellular automata in Komering Watershed, South Sumatera

NASA Astrophysics Data System (ADS)

Kusratmoko, E.; Albertus, S. D. Y.; Supriatna

2017-01-01

This research has a purpose to study and develop a model that can representing and simulating spatial distribution pattern of land use change in Komering watershed. The Komering watershed is one of nine sub Musi river basin and is located in the southern part of Sumatra island that has an area of 8060,62 km2. Land use change simulations, achieved through Markov-cellular automata (CA) methodologies. Slope, elevation, distance from road, distance from river, distance from capital sub-district, distance from settlement area area were driving factors that used in this research. Land use prediction result in 2030 also shows decrease of forest acreage up to -3.37%, agricultural land decreased up to -2.13%, and open land decreased up to -0.13%. On the other hand settlement area increased up to 0.07%, and plantation land increased up to 5.56%. Based on the predictive result, land use unconformity percentage to RTRW in Komering watershed is 18.62 % and land use conformity is 58.27%. Based on the results of the scenario, where forest in protected areas and agriculture land are maintained, shows increase the land use conformity amounted to 60.41 % and reduce unconformity that occur in Komering watershed to 17.23 %.

Bennett clocking of quantum-dot cellular automata and the limits to binary logic scaling

NASA Astrophysics Data System (ADS)

Lent, Craig S.; Liu, Mo; Lu, Yuhui

2006-08-01

We examine power dissipation in different clocking schemes for molecular quantum-dot cellular automata (QCA) circuits. 'Landauer clocking' involves the adiabatic transition of a molecular cell from the null state to an active state carrying data. Cell layout creates devices which allow data in cells to interact and thereby perform useful computation. We perform direct solutions of the equation of motion for the system in contact with the thermal environment and see that Landauer's Principle applies: one must dissipate an energy of at least kBT per bit only when the information is erased. The ideas of Bennett can be applied to keep copies of the bit information by echoing inputs to outputs, thus embedding any logically irreversible circuit in a logically reversible circuit, at the cost of added circuit complexity. A promising alternative which we term 'Bennett clocking' requires only altering the timing of the clocking signals so that bit information is simply held in place by the clock until a computational block is complete, then erased in the reverse order of computation. This approach results in ultralow power dissipation without additional circuit complexity. These results offer a concrete example in which to consider recent claims regarding the fundamental limits of binary logic scaling.

A novel power-efficient high-speed clock management unit using quantum-dot cellular automata

NASA Astrophysics Data System (ADS)

Abutaleb, M. M.

2017-04-01

Quantum-dot cellular automata (QCA) is one of the most attractive alternatives for complementary metal-oxide semiconductor technology. The QCA widely supports a new paradigm in the field of nanotechnology that has the potential for high density, low power, and high speed. The clock manager is an essential building block in the new microwave and radio frequency integrated circuits. This paper describes a novel QCA-based clock management unit (CMU) that provides innovative clocking capabilities. The proposed CMU is achieved by utilizing edge-triggered D-type flip-flops (D-FFs) in the design of frequency synthesizer and phase splitter. Edge-triggered D-FF structures proposed in this paper have the successful QCA implementation and simulation with the least complexity and power dissipation as compared to earlier structures. The frequency synthesizer is used to generate new clock frequencies from the reference clock frequency based on a combination of power-of-two frequency dividers. The phase splitter is integrated with the frequency synthesizer to generate four clock signals that are 90o out of phase with each other. This paper demonstrates that the proposed QCA CMU structure has a superior performance. Furthermore, the proposed CMU is straightforwardly scalable due to the use of modular component architecture.

Resolution of Infinite-Loop in Hyperincursive and Nonlocal Cellular Automata: Introduction to Slime Mold Computing

NASA Astrophysics Data System (ADS)

Aono, Masashi; Gunji, Yukio-Pegio

2004-08-01

How can non-algorithmic/non-deterministic computational syntax be computed? "The hyperincursive system" introduced by Dubois is an anticipatory system embracing the contradiction/uncertainty. Although it may provide a novel viewpoint for the understanding of complex systems, conventional digital computers cannot run faithfully as the hyperincursive computational syntax specifies, in a strict sense. Then is it an imaginary story? In this paper we try to argue that it is not. We show that a model of complex systems "Elementary Conflictable Cellular Automata (ECCA)" proposed by Aono and Gunji is embracing the hyperincursivity and the nonlocality. ECCA is based on locality-only type settings basically as well as other CA models, and/but at the same time, each cell is required to refer to globality-dominant regularity. Due to this contradictory locality-globality loop, the time evolution equation specifies that the system reaches the deadlock/infinite-loop. However, we show that there is a possibility of the resolution of these problems if the computing system has parallel and/but non-distributed property like an amoeboid organism. This paper is an introduction to "the slime mold computing" that is an attempt to cultivate an unconventional notion of computation.

New mathematics for old physics: The case of lattice fluids

NASA Astrophysics Data System (ADS)

Barberousse, Anouk; Imbert, Cyrille

2013-08-01

We analyze the effects of the introduction of new mathematical tools on an old branch of physics by focusing on lattice fluids, which are cellular automata (CA)-based hydrodynamical models. We examine the nature of these discrete models, the type of novelty they bring about within scientific practice and the role they play in the field of fluid dynamics. We critically analyze Rohrlich's, Fox Keller's and Hughes' claims about CA-based models. We distinguish between different senses of the predicates "phenomenological" and "theoretical" for scientific models and argue that it is erroneous to conclude, as they do, that CA-based models are necessarily phenomenological in any sense of the term. We conversely claim that CA-based models of fluids, though at first sight blatantly misrepresenting fluids, are in fact conservative as far as the basic laws of statistical physics are concerned and not less theoretical than more traditional models in the field. Based on our case-study, we propose a general discussion of the prospect of CA for modeling in physics. We finally emphasize that lattice fluids are not just exotic oddities but do bring about new advantages in the investigation of fluids' behavior.

Approximate probabilistic cellular automata for the dynamics of single-species populations under discrete logisticlike growth with and without weak Allee effects.

PubMed

Mendonça, J Ricardo G; Gevorgyan, Yeva

2017-05-01

We investigate one-dimensional elementary probabilistic cellular automata (PCA) whose dynamics in first-order mean-field approximation yields discrete logisticlike growth models for a single-species unstructured population with nonoverlapping generations. Beginning with a general six-parameter model, we find constraints on the transition probabilities of the PCA that guarantee that the ensuing approximations make sense in terms of population dynamics and classify the valid combinations thereof. Several possible models display a negative cubic term that can be interpreted as a weak Allee factor. We also investigate the conditions under which a one-parameter PCA derived from the more general six-parameter model can generate valid population growth dynamics. Numerical simulations illustrate the behavior of some of the PCA found.

Reliable Cellular Automata with Self-Organization

NASA Astrophysics Data System (ADS)

Gács, Peter

2001-04-01

In a probabilistic cellular automaton in which all local transitions have positive probability, the problem of keeping a bit of information indefinitely is nontrivial, even in an infinite automaton. Still, there is a solution in 2 dimensions, and this solution can be used to construct a simple 3-dimensional discrete-time universal fault-tolerant cellular automaton. This technique does not help much to solve the following problems: remembering a bit of information in 1 dimension; computing in dimensions lower than 3; computing in any dimension with non-synchronized transitions. Our more complex technique organizes the cells in blocks that perform a reliable simulation of a second (generalized) cellular automaton. The cells of the latter automaton are also organized in blocks, simulating even more reliably a third automaton, etc. Since all this (a possibly infinite hierarchy) is organized in "software," it must be under repair all the time from damage caused by errors. A large part of the problem is essentially self-stabilization recovering from a mess of arbitrary size and content. The present paper constructs an asynchronous one-dimensional fault-tolerant cellular automaton, with the further feature of "self-organization." The latter means that unless a large amount of input information must be given, the initial configuration can be chosen homogeneous.

Incorporating topography in a cellular automata model to simulate residents evacuation in a mountain area in China

NASA Astrophysics Data System (ADS)

Wang, Li; Liu, Mao; Meng, Bo

2013-02-01

In China, both the mountainous areas and the number of people who live in mountain areas occupy a significant proportion. When production accidents or natural disasters happen, the residents in mountain areas should be evacuated and the evacuation is of obvious importance to public safety. But it is a pity that there are few studies on safety evacuation in rough terrain. The particularity of the complex terrain in mountain areas, however, makes it difficult to study pedestrian evacuation. In this paper, a three-dimensional surface cellular automata model is proposed to numerically simulate the real time dynamic evacuation of residents. The model takes into account topographic characteristics (the slope gradient) of the environment and the biomechanics characteristics (weight and leg extensor power) of the residents to calculate the walking speed. This paper only focuses on the influence of topography and the physiological parameters are defined as constants according to a statistical report. Velocity varies with the topography. In order to simulate the behavior of a crowd with varying movement velocities, and a numerical algorithm is used to determine the time step of iteration. By doing so, a numerical simulation can be conducted in a 3D surface CA model. Moreover, considering residents evacuation around a gas well in a mountain area as a case, a visualization system for a three-dimensional simulation of pedestrian evacuation is developed. In the simulation process, population behaviors of congestion, queuing and collision avoidance can be observed. The simulation results are explained reasonably. Therefore, the model presented in this paper can realize a 3D dynamic simulation of pedestrian evacuation vividly in complex terrain and predict the evacuation procedure and evacuation time required, which can supply some valuable information for emergency management.

Quantum cloning by cellular automata

NASA Astrophysics Data System (ADS)

D'Ariano, G. M.; Macchiavello, C.; Rossi, M.

2013-03-01

We introduce a quantum cellular automaton that achieves approximate phase-covariant cloning of qubits. The automaton is optimized for 1→2N economical cloning. The use of the automaton for cloning allows us to exploit different foliations for improving the performance with given resources.

Simulation of Corrosion Process for Structure with the Cellular Automata Method

NASA Astrophysics Data System (ADS)

Chen, M. C.; Wen, Q. Q.

2017-06-01

In this paper, from the mesoscopic point of view, under the assumption of metal corrosion damage evolution being a diffusive process, the cellular automata (CA) method was proposed to simulate numerically the uniform corrosion damage evolution of outer steel tube of concrete filled steel tubular columns subjected to corrosive environment, and the effects of corrosive agent concentration, dissolution probability and elapsed etching time on the corrosion damage evolution were also investigated. It was shown that corrosion damage increases nonlinearly with increasing elapsed etching time, and the longer the etching time, the more serious the corrosion damage; different concentration of corrosive agents had different impacts on the corrosion damage degree of the outer steel tube, but the difference between the impacts was very small; the heavier the concentration, the more serious the influence. The greater the dissolution probability, the more serious the corrosion damage of the outer steel tube, but with the increase of dissolution probability, the difference between its impacts on the corrosion damage became smaller and smaller. To validate present method, corrosion damage measurements for concrete filled square steel tubular columns (CFSSTCs) sealed at both their ends and immersed fully in a simulating acid rain solution were conducted, and Faraday’s law was used to predict their theoretical values. Meanwhile, the proposed CA mode was applied for the simulation of corrosion damage evolution of the CFSSTCs. It was shown by the comparisons of results from the three methods aforementioned that they were in good agreement, implying that the proposed method used for the simulation of corrosion damage evolution of concrete filled steel tubular columns is feasible and effective. It will open a new approach to study and evaluate further the corrosion damage, loading capacity and lifetime prediction of concrete filled steel tubular structures.

The Cellular Automata for modelling of spreading of lava flow on the earth surface

NASA Astrophysics Data System (ADS)

Jarna, A.

2012-12-01

Volcanic risk assessment is a very important scientific, political and economic issue in densely populated areas close to active volcanoes. Development of effective tools for early prediction of a potential volcanic hazard and management of crises are paramount. However, to this date volcanic hazard maps represent the most appropriate way to illustrate the geographical area that can potentially be affected by a volcanic event. Volcanic hazard maps are usually produced by mapping out old volcanic deposits, however dynamic lava flow simulation gaining popularity and can give crucial information to corroborate other methodologies. The methodology which is used here for the generation of volcanic hazard maps is based on numerical simulation of eruptive processes by the principle of Cellular Automata (CA). The python script is integrated into ArcToolbox in ArcMap (ESRI) and the user can select several input and output parameters which influence surface morphology, size and shape of the flow, flow thickness, flow velocity and length of lava flows. Once the input parameters are selected, the software computes and generates hazard maps on the fly. The results can be exported to Google Maps (.klm format) to visualize the results of the computation. For validation of the simulation code are used data from a real lava flow. Comparison of the simulation results with real lava flows mapped out from satellite images will be presented.

Monitoring with Data Automata

NASA Technical Reports Server (NTRS)

Havelund, Klaus

2014-01-01

We present a form of automaton, referred to as data automata, suited for monitoring sequences of data-carrying events, for example emitted by an executing software system. This form of automata allows states to be parameterized with data, forming named records, which are stored in an efficiently indexed data structure, a form of database. This very explicit approach differs from other automaton-based monitoring approaches. Data automata are also characterized by allowing transition conditions to refer to other parameterized states, and by allowing transitions sequences. The presented automaton concept is inspired by rule-based systems, especially the Rete algorithm, which is one of the well-established algorithms for executing rule-based systems. We present an optimized external DSL for data automata, as well as a comparable unoptimized internal DSL (API) in the Scala programming language, in order to compare the two solutions. An evaluation compares these two solutions to several other monitoring systems.

Modeling and predicting urban growth pattern of the Tokyo metropolitan area based on cellular automata

NASA Astrophysics Data System (ADS)

Zhao, Yaolong; Zhao, Junsan; Murayama, Yuji

2008-10-01

The period of high economic growth in Japan which began in the latter half of the 1950s led to a massive migration of population from rural regions to the Tokyo metropolitan area. This phenomenon brought about rapid urban growth and urban structure changes in this area. Purpose of this study is to establish a constrained CA (Cellular Automata) model with GIS (Geographical Information Systems) to simulate urban growth pattern in the Tokyo metropolitan area towards predicting urban form and landscape for the near future. Urban land-use is classified into multi-categories for interpreting the effect of interaction among land-use categories in the spatial process of urban growth. Driving factors of urban growth pattern, such as land condition, railway network, land-use zoning, random perturbation, and neighborhood interaction and so forth, are explored and integrated into this model. These driving factors are calibrated based on exploratory spatial data analysis (ESDA), spatial statistics, logistic regression, and "trial and error" approach. The simulation is assessed at both macro and micro classification levels in three ways: visual approach; fractal dimension; and spatial metrics. Results indicate that this model provides an effective prototype to simulate and predict urban growth pattern of the Tokyo metropolitan area.

Modelling urban growth in the Indo-Gangetic plain using nighttime OLS data and cellular automata

NASA Astrophysics Data System (ADS)

Roy Chowdhury, P. K.; Maithani, Sandeep

2014-12-01

The present study demonstrates the applicability of the Operational Linescan System (OLS) sensor in modelling urban growth at regional level. The nighttime OLS data provides an easy, inexpensive way to map urban areas at a regional scale, requiring a very small volume of data. A cellular automata (CA) model was developed for simulating urban growth in the Indo-Gangetic plain; using OLS data derived maps as input. In the proposed CA model, urban growth was expressed in terms of causative factors like economy, topography, accessibility and urban infrastructure. The model was calibrated and validated based on OLS data of year 2003 and 2008 respectively using spatial metrics measures and subsequently the urban growth was predicted for the year 2020. The model predicted high urban growth in North Western part of the study area, in south eastern part growth would be concentrated around two cities, Kolkata and Howrah. While in the middle portion of the study area, i.e., Jharkhand, Bihar and Eastern Uttar Pradesh, urban growth has been predicted in form of clusters, mostly around the present big cities. These results will not only provide an input to urban planning but can also be utilized in hydrological and ecological modelling which require an estimate of future built up areas especially at regional level.

Gas Transfer in Cellularized Collagen-Membrane Gas Exchange Devices.

PubMed

Lo, Justin H; Bassett, Erik K; Penson, Elliot J N; Hoganson, David M; Vacanti, Joseph P

2015-08-01

Chronic lower respiratory disease is highly prevalent in the United States, and there remains a need for alternatives to lung transplant for patients who progress to end-stage lung disease. Portable or implantable gas oxygenators based on microfluidic technologies can address this need, provided they operate both efficiently and biocompatibly. Incorporating biomimetic materials into such devices can help replicate native gas exchange function and additionally support cellular components. In this work, we have developed microfluidic devices that enable blood gas exchange across ultra-thin collagen membranes (as thin as 2 μm). Endothelial, stromal, and parenchymal cells readily adhere to these membranes, and long-term culture with cellular components results in remodeling, reflected by reduced membrane thickness. Functionally, acellular collagen-membrane lung devices can mediate effective gas exchange up to ∼288 mL/min/m(2) of oxygen and ∼685 mL/min/m(2) of carbon dioxide, approaching the gas exchange efficiency noted in the native lung. Testing several configurations of lung devices to explore various physical parameters of the device design, we concluded that thinner membranes and longer gas exchange distances result in improved hemoglobin saturation and increases in pO2. However, in the design space tested, these effects are relatively small compared to the improvement in overall oxygen and carbon dioxide transfer by increasing the blood flow rate. Finally, devices cultured with endothelial and parenchymal cells achieved similar gas exchange rates compared with acellular devices. Biomimetic blood oxygenator design opens the possibility of creating portable or implantable microfluidic devices that achieve efficient gas transfer while also maintaining physiologic conditions.

Petit and grand ensemble Monte Carlo calculations of the thermodynamics of the lattice gas

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murch, G.E.; Thorn, R.J.

1978-11-01

A direct Monte Carlo method for estimating the chemical potential in the petit canonical ensemble was applied to the simple cubic Ising-like lattice gas. The method is based on a simple relationship between the chemical potential and the potential energy distribution in a lattice gas at equilibrium as derived independently by Widom, and Jackson and Klein. Results are presented here for the chemical potential at various compositions and temperatures above and below the zero field ferromagnetic and antiferromagnetic critical points. The same lattice gas model was reconstructed in the form of a restricted grand canonical ensemble and results at severalmore » temperatures were compared with those from the petit canonical ensemble. The agreement was excellent in these cases.« less

Effect of Fourier transform on the streaming in quantum lattice gas algorithms

NASA Astrophysics Data System (ADS)

Oganesov, Armen; Vahala, George; Vahala, Linda; Soe, Min

2018-04-01

All our previous quantum lattice gas algorithms for nonlinear physics have approximated the kinetic energy operator by streaming sequences to neighboring lattice sites. Here, the kinetic energy can be treated to all orders by Fourier transforming the kinetic energy operator with interlaced Dirac-based unitary collision operators. Benchmarking against exact solutions for the 1D nonlinear Schrodinger equation shows an extended range of parameters (soliton speeds and amplitudes) over the Dirac-based near-lattice-site streaming quantum algorithm.

An enhanced high-speed multi-digit BCD adder using quantum-dot cellular automata

NASA Astrophysics Data System (ADS)

Ajitha, D.; Ramanaiah, K. V.; Sumalatha, V.

2017-02-01

The advent of development of high-performance, low-power digital circuits is achieved by a suitable emerging nanodevice called quantum-dot cellular automata (QCA). Even though many efficient arithmetic circuits were designed using QCA, there is still a challenge to implement high-speed circuits in an optimized manner. Among these circuits, one of the essential structures is a parallel multi-digit decimal adder unit with significant speed which is very attractive for future environments. To achieve high speed, a new correction logic formulation method is proposed for single and multi-digit BCD adder. The proposed enhanced single-digit BCD adder (ESDBA) is 26% faster than the carry flow adder (CFA)-based BCD adder. The multi-digit operations are also performed using the proposed ESDBA, which is cascaded innovatively. The enhanced multi-digit BCD adder (EMDBA) performs two 4-digit and two 8-digit BCD addition 50% faster than the CFA-based BCD adder with the nominal overhead of the area. The EMDBA performs two 4-digit BCD addition 24% faster with 23% decrease in the area, similarly for 8-digit operation the EMDBA achieves 36% increase in speed with 21% less area compared to the existing carry look ahead (CLA)-based BCD adder design. The proposed multi-digit adder produces significantly less delay of (N –1) + 3.5 clock cycles compared to the N* One digit BCD adder delay required by the conventional BCD adder method. It is observed that as per our knowledge this is the first innovative proposal for multi-digit BCD addition using QCA.

Using economy of means to evolve transition rules within 2D cellular automata.

PubMed

Ripps, David L

2010-01-01

Running a cellular automaton (CA) on a rectangular lattice is a time-honored method for studying artificial life on a digital computer. Commonly, the researcher wishes to investigate some specific or general mode of behavior, say, the ability of a coherent pattern of points to glide within the lattice, or to generate copies of itself. This technique has a problem: how to design the transitions table-the set of distinct rules that specify the next content of a cell from its current content and that of its near neighbors. Often the table is painstakingly designed manually, rule by rule. The problem is exacerbated by the potentially vast number of individual rules that need be specified to cover all combinations of center and neighbors when there are several symbols in the alphabet of the CA. In this article a method is presented to have the set of rules evolve automatically while running the CA. The transition table is initially empty, with rules being added as the need arises. A novel principle drives the evolution: maximum economy of means-maximizing the reuse of rules introduced on previous cycles. This method may not be a panacea applicable to all CA studies. Nevertheless, it is sufficiently potent to evolve sets of rules and associated patterns of points that glide (periodically regenerate themselves at another location) and to generate gliding "children" that then "mate" by collision.

Multicomponent lattice Boltzmann model from continuum kinetic theory.

PubMed

Shan, Xiaowen

2010-04-01

We derive from the continuum kinetic theory a multicomponent lattice Boltzmann model with intermolecular interaction. The resulting model is found to be consistent with the model previously derived from a lattice-gas cellular automaton [X. Shan and H. Chen, Phys. Rev. E 47, 1815 (1993)] but applies in a much broader domain. A number of important insights are gained from the kinetic theory perspective. First, it is shown that even in the isothermal case, the energy equipartition principle dictates the form of the equilibrium distribution function. Second, thermal diffusion is shown to exist and the corresponding diffusivities are given in terms of macroscopic parameters. Third, the ordinary diffusion is shown to satisfy the Maxwell-Stefan equation at the ideal-gas limit.

Towards measuring the semantic capacity of a physical medium demonstrated with elementary cellular automata.

PubMed

Dittrich, Peter

2018-02-01

The organic code concept and its operationalization by molecular codes have been introduced to study the semiotic nature of living systems. This contribution develops further the idea that the semantic capacity of a physical medium can be measured by assessing its ability to implement a code as a contingent mapping. For demonstration and evaluation, the approach is applied to a formal medium: elementary cellular automata (ECA). The semantic capacity is measured by counting the number of ways codes can be implemented. Additionally, a link to information theory is established by taking multivariate mutual information for quantifying contingency. It is shown how ECAs differ in their semantic capacities, how this is related to various ECA classifications, and how this depends on how a meaning is defined. Interestingly, if the meaning should persist for a certain while, the highest semantic capacity is found in CAs with apparently simple behavior, i.e., the fixed-point and two-cycle class. Synergy as a predictor for a CA's ability to implement codes can only be used if context implementing codes are common. For large context spaces with sparse coding contexts synergy is a weak predictor. Concluding, the approach presented here can distinguish CA-like systems with respect to their ability to implement contingent mappings. Applying this to physical systems appears straight forward and might lead to a novel physical property indicating how suitable a physical medium is to implement a semiotic system. Copyright © 2017 Elsevier B.V. All rights reserved.

Simulating the conversion of rural settlements to town land based on multi-agent systems and cellular automata.

PubMed

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans.

An effective approach of lesion segmentation within the breast ultrasound image based on the cellular automata principle.

PubMed

Liu, Yan; Cheng, H D; Huang, Jianhua; Zhang, Yingtao; Tang, Xianglong

2012-10-01

In this paper, a novel lesion segmentation within breast ultrasound (BUS) image based on the cellular automata principle is proposed. Its energy transition function is formulated based on global image information difference and local image information difference using different energy transfer strategies. First, an energy decrease strategy is used for modeling the spatial relation information of pixels. For modeling global image information difference, a seed information comparison function is developed using an energy preserve strategy. Then, a texture information comparison function is proposed for considering local image difference in different regions, which is helpful for handling blurry boundaries. Moreover, two neighborhood systems (von Neumann and Moore neighborhood systems) are integrated as the evolution environment, and a similarity-based criterion is used for suppressing noise and reducing computation complexity. The proposed method was applied to 205 clinical BUS images for studying its characteristic and functionality, and several overlapping area error metrics and statistical evaluation methods are utilized for evaluating its performance. The experimental results demonstrate that the proposed method can handle BUS images with blurry boundaries and low contrast well and can segment breast lesions accurately and effectively.

Integrating GIS, cellular automata, and genetic algorithm in urban spatial optimization: a case study of Lanzhou

NASA Astrophysics Data System (ADS)

Xu, Xibao; Zhang, Jianming; Zhou, Xiaojian

2006-10-01

This paper presents a model integrating GIS, cellular automata (CA) and genetic algorithm (GA) in urban spatial optimization. The model involves three objectives of the maximization of land-use efficiency, the maximization of urban spatial harmony and appropriate proportion of each land-use type. CA submodel is designed with standard Moore neighbor and three transition rules to maximize the land-use efficiency and urban spatial harmony, according to the land-use suitability and spatial harmony index. GA submodel is designed with four constraints and seven steps for the maximization of urban spatial harmony and appropriate proportion of each land-use type, including encoding, initializing, calculating fitness, selection, crossover, mutation and elitism. GIS is used to prepare for the input data sets for the model and perform spatial analysis on the results, while CA and GA are integrated to optimize urban spatial structure, programmed with Matlab 7 and coupled with GIS loosely. Lanzhou, a typical valley-basin city with fast urban development, is chosen as the case study. At the end, a detail analysis and evaluation of the spatial optimization with the model are made, and it proves to be a powerful tool in optimizing urban spatial structure and make supplement for urban planning and policy-makers.

Design of cryptographically secure AES like S-Box using second-order reversible cellular automata for wireless body area network applications.

PubMed

Gangadari, Bhoopal Rao; Rafi Ahamed, Shaik

2016-09-01

In biomedical, data security is the most expensive resource for wireless body area network applications. Cryptographic algorithms are used in order to protect the information against unauthorised access. Advanced encryption standard (AES) cryptographic algorithm plays a vital role in telemedicine applications. The authors propose a novel approach for design of substitution bytes (S-Box) using second-order reversible one-dimensional cellular automata (RCA 2 ) as a replacement to the classical look-up-table (LUT) based S-Box used in AES algorithm. The performance of proposed RCA 2 based S-Box and conventional LUT based S-Box is evaluated in terms of security using the cryptographic properties such as the nonlinearity, correlation immunity bias, strict avalanche criteria and entropy. Moreover, it is also shown that RCA 2 based S-Boxes are dynamic in nature, invertible and provide high level of security. Further, it is also found that the RCA 2 based S-Box have comparatively better performance than that of conventional LUT based S-Box.

Design of cryptographically secure AES like S-Box using second-order reversible cellular automata for wireless body area network applications

PubMed Central

Rafi Ahamed, Shaik

2016-01-01

In biomedical, data security is the most expensive resource for wireless body area network applications. Cryptographic algorithms are used in order to protect the information against unauthorised access. Advanced encryption standard (AES) cryptographic algorithm plays a vital role in telemedicine applications. The authors propose a novel approach for design of substitution bytes (S-Box) using second-order reversible one-dimensional cellular automata (RCA2) as a replacement to the classical look-up-table (LUT) based S-Box used in AES algorithm. The performance of proposed RCA2 based S-Box and conventional LUT based S-Box is evaluated in terms of security using the cryptographic properties such as the nonlinearity, correlation immunity bias, strict avalanche criteria and entropy. Moreover, it is also shown that RCA2 based S-Boxes are dynamic in nature, invertible and provide high level of security. Further, it is also found that the RCA2 based S-Box have comparatively better performance than that of conventional LUT based S-Box. PMID:27733924

Gap Solitons of Superfluid Fermi Gas in FS Optical Lattices

NASA Astrophysics Data System (ADS)

Chen, Yan; Zhang, Ke-Zhi; He, Yong-Lin; Liu, Zhen-Lai; Zhu, Liao

2018-01-01

By employing the mean-field theory and hydrodynamic scheme, we study the gap solitons of superfluid Fermi gas in Fourier-Synthesized(FS) optical lattices. By means of numerical methods and variational approximation, the atomic interaction, the chemical potential, the potential depth of the lattice and relative phase of the Fermi system are derived along the Bose-Enstein condensation(BEC)side to the Bardeen-Cooper-Schrieffer (BCS)side. It means that the condition exciting gap solitons is obtained. Moreover, we analyze the fundamental gap soltions of the superfluid Fermi gas. It is found that the relative phase α impacts greatly on the properties of fundamental gap solitons for superfluid Fermi gas. Especially, the nonlinearity interaction term g decreases with α. Add, due to Fermi pressure, curvature changes of g in the BEC limit( γ = 1, here, γ is a function of an interaction parameter) is larger than that at unitary ( γ = 2/3). Spatial distribution of gap solitons exhibit very obvious different when the system transit from the BEC side to BCS side.

A cellular automaton for the signed particle formulation of quantum mechanics

NASA Astrophysics Data System (ADS)

Sellier, J. M.; Kapanova, K. G.; Dimov, I.

2017-02-01

Recently, a new formulation of quantum mechanics, based on the concept of signed particles, has been suggested. In this paper, we introduce a cellular automaton which mimics the dynamics of quantum objects in the phase-space in a time-dependent fashion. This is twofold: it provides a simplified and accessible language to non-physicists who wants to simulate quantum mechanical systems, at the same time it enables a different way to explore the laws of Physics. Moreover, it opens the way towards hybrid simulations of quantum systems by combining full quantum models with cellular automata when the former fail. In order to show the validity of the suggested cellular automaton and its combination with the signed particle formalism, several numerical experiments are performed, showing very promising results. Being this article a preliminary study on quantum simulations in phase-space by means of cellular automata, some conclusions are drawn about the encouraging results obtained so far and the possible future developments.

CAM: A high-performance cellular-automaton machine

NASA Astrophysics Data System (ADS)

Toffoli, Tommaso

1984-01-01

CAM is a high-performance machine dedicated to the simulation of cellular automata and other distributed dynamical systems. Its speed is about one-thousand times greater than that of a general-purpose computer programmed to do the same task; in practical terms, this means that CAM can show the evolution of cellular automata on a color monitor with an update rate, dynamic range, and spatial resolution comparable to those of a Super-8 movie, thus permitting intensive interactive experimentation. Machines of this kind can open up novel fields of research, and in this context it is important that results be easy to obtain, reproduce, and transmit. For these reasons, in designing CAM it was important to achieve functional simplicity, high flexibility, and moderate production cost. We expect that many research groups will be able to own their own copy of the machine to do research with.

Lattice-Gas Automata Fluids on Parallel Supercomputers

DTIC Science & Technology

1993-11-23

Kelvin-Helmholtz shear instabil- ity, and the Von Karman vortex shedding instability. Performance of the two machines in terms of both site update... PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Phillips Laboratory,Hanscom Field,MA,01731 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING...Helmholtz shear instability, and the Von Karman vortex shedding instability. Performance of the two machines in terms of both site update rate and

Understanding the complex dynamics of stock markets through cellular automata

NASA Astrophysics Data System (ADS)

Qiu, G.; Kandhai, D.; Sloot, P. M. A.

2007-04-01

We present a cellular automaton (CA) model for simulating the complex dynamics of stock markets. Within this model, a stock market is represented by a two-dimensional lattice, of which each vertex stands for a trader. According to typical trading behavior in real stock markets, agents of only two types are adopted: fundamentalists and imitators. Our CA model is based on local interactions, adopting simple rules for representing the behavior of traders and a simple rule for price updating. This model can reproduce, in a simple and robust manner, the main characteristics observed in empirical financial time series. Heavy-tailed return distributions due to large price variations can be generated through the imitating behavior of agents. In contrast to other microscopic simulation (MS) models, our results suggest that it is not necessary to assume a certain network topology in which agents group together, e.g., a random graph or a percolation network. That is, long-range interactions can emerge from local interactions. Volatility clustering, which also leads to heavy tails, seems to be related to the combined effect of a fast and a slow process: the evolution of the influence of news and the evolution of agents’ activity, respectively. In a general sense, these causes of heavy tails and volatility clustering appear to be common among some notable MS models that can confirm the main characteristics of financial markets.

Algebraic Systems and Pushdown Automata

NASA Astrophysics Data System (ADS)

Petre, Ion; Salomaa, Arto

We concentrate in this chapter on the core aspects of algebraic series, pushdown automata, and their relation to formal languages. We choose to follow here a presentation of their theory based on the concept of properness. We introduce in Sect. 2 some auxiliary notions and results needed throughout the chapter, in particular the notions of discrete convergence in semirings and C-cycle free infinite matrices. In Sect. 3 we introduce the algebraic power series in terms of algebraic systems of equations. We focus on interconnections with context-free grammars and on normal forms. We then conclude the section with a presentation of the theorems of Shamir and Chomsky-Schützenberger. We discuss in Sect. 4 the algebraic and the regulated rational transductions, as well as some representation results related to them. Section 5 is dedicated to pushdown automata and focuses on the interconnections with classical (non-weighted) pushdown automata and on the interconnections with algebraic systems. We then conclude the chapter with a brief discussion of some of the other topics related to algebraic systems and pushdown automata.

Implementation of Basic and Universal Gates In a single Circuit Based On Quantum-dot Cellular Automata Using Multi-Layer Crossbar Wire

NASA Astrophysics Data System (ADS)

Bhowmik, Dhrubajyoti; Saha, Apu Kr; Dutta, Paramartha; Nandi, Supratim

2017-08-01

Quantum-dot Cellular Automata (QCA) is one of the most substitutes developing nanotechnologies for electronic circuits, as a result of lower force utilization, higher speed and smaller size in correlation with CMOS innovation. The essential devices, a Quantum-dot cell can be utilized to logic gates and wires. As it is the key building block on nanotechnology circuits. By applying simple gates, the hardware requirements for a QCA circuit can be decreased and circuits can be less complex as far as level, delay and cell check. This article exhibits an unobtrusive methodology for actualizing novel upgraded simple and universal gates, which can be connected to outline numerous variations of complex QCA circuits. Proposed gates are straightforward in structure and capable as far as implementing any digital circuits. The main aim is to build all basic and universal gates in a simple circuit with and without crossbar-wire. Simulation results and physical relations affirm its handiness in actualizing each advanced circuit.

Cellular automata segmentation of the boundary between the compacta of vertebral bodies and surrounding structures

NASA Astrophysics Data System (ADS)

Egger, Jan; Nimsky, Christopher

2016-03-01

Due to the aging population, spinal diseases get more and more common nowadays; e.g., lifetime risk of osteoporotic fracture is 40% for white women and 13% for white men in the United States. Thus the numbers of surgical spinal procedures are also increasing with the aging population and precise diagnosis plays a vital role in reducing complication and recurrence of symptoms. Spinal imaging of vertebral column is a tedious process subjected to interpretation errors. In this contribution, we aim to reduce time and error for vertebral interpretation by applying and studying the GrowCut - algorithm for boundary segmentation between vertebral body compacta and surrounding structures. GrowCut is a competitive region growing algorithm using cellular automata. For our study, vertebral T2-weighted Magnetic Resonance Imaging (MRI) scans were first manually outlined by neurosurgeons. Then, the vertebral bodies were segmented in the medical images by a GrowCut-trained physician using the semi-automated GrowCut-algorithm. Afterwards, results of both segmentation processes were compared using the Dice Similarity Coefficient (DSC) and the Hausdorff Distance (HD) which yielded to a DSC of 82.99+/-5.03% and a HD of 18.91+/-7.2 voxel, respectively. In addition, the times have been measured during the manual and the GrowCut segmentations, showing that a GrowCutsegmentation - with an average time of less than six minutes (5.77+/-0.73) - is significantly shorter than a pure manual outlining.

Early warning of illegal development for protected areas by integrating cellular automata with neural networks.

PubMed

Li, Xia; Lao, Chunhua; Liu, Yilun; Liu, Xiaoping; Chen, Yimin; Li, Shaoying; Ai, Bing; He, Zijian

2013-11-30

Ecological security has become a major issue under fast urbanization in China. As the first two cities in this country, Shenzhen and Dongguan issued the ordinance of Eco-designated Line of Control (ELC) to "wire" ecologically important areas for strict protection in 2005 and 2009 respectively. Early warning systems (EWS) are a useful tool for assisting the implementation ELC. In this study, a multi-model approach is proposed for the early warning of illegal development by integrating cellular automata (CA) and artificial neural networks (ANN). The objective is to prevent the ecological risks or catastrophe caused by such development at an early stage. The integrated model is calibrated by using the empirical information from both remote sensing and handheld GPS (global positioning systems). The MAR indicator which is the ratio of missing alarms to all the warnings is proposed for better assessment of the model performance. It is found that the fast urban development has caused significant threats to natural-area protection in the study area. The integration of CA, ANN and GPS provides a powerful tool for describing and predicting illegal development which is in highly non-linear and fragmented forms. The comparison shows that this multi-model approach has much better performances than the single-model approach for the early warning. Compared with the single models of CA and ANN, this integrated multi-model can improve the value of MAR by 65.48% and 5.17% respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

Simulating the Conversion of Rural Settlements to Town Land Based on Multi-Agent Systems and Cellular Automata

PubMed Central

Liu, Yaolin; Kong, Xuesong; Liu, Yanfang; Chen, Yiyun

2013-01-01

Rapid urbanization in China has triggered the conversion of land from rural to urban use, particularly the conversion of rural settlements to town land. This conversion is the result of the joint effects of the geographic environment and agents involving the government, investors, and farmers. To understand the dynamic interaction dominated by agents and to predict the future landscape of town expansion, a small town land-planning model is proposed based on the integration of multi-agent systems (MAS) and cellular automata (CA). The MAS-CA model links the decision-making behaviors of agents with the neighbor effect of CA. The interaction rules are projected by analyzing the preference conflicts among agents. To better illustrate the effects of the geographic environment, neighborhood, and agent behavior, a comparative analysis between the CA and MAS-CA models in three different towns is presented, revealing interesting patterns in terms of quantity, spatial characteristics, and the coordinating process. The simulation of rural settlements conversion to town land through modeling agent decision and human-environment interaction is very useful for understanding the mechanisms of rural-urban land-use change in developing countries. This process can assist town planners in formulating appropriate development plans. PMID:24244472

Data Automata in Scala

NASA Technical Reports Server (NTRS)

Havelund, Klaus

2014-01-01

The field of runtime verification has during the last decade seen a multitude of systems for monitoring event sequences (traces) emitted by a running system. The objective is to ensure correctness of a system by checking its execution traces against formal specifications representing requirements. A special challenge is data parameterized events, where monitors have to keep track of the combination of control states as well as data constraints, relating events and the data they carry across time points. This poses a challenge wrt. efficiency of monitors, as well as expressiveness of logics. Data automata is a form of automata where states are parameterized with data, supporting monitoring of data parameterized events. We describe the full details of a very simple API in the Scala programming language, an internal DSL (Domain-Specific Language), implementing data automata. The small implementation suggests a design pattern. Data automata allow transition conditions to refer to other states than the source state, and allow target states of transitions to be inlined, offering a temporal logic flavored notation. An embedding of a logic in a high-level language like Scala in addition allows monitors to be programmed using all of Scala's language constructs, offering the full flexibility of a programming language. The framework is demonstrated on an XML processing scenario previously addressed in related work.

Simulating carbon sequestration using cellular automata and land use assessment for Karaj, Iran

NASA Astrophysics Data System (ADS)

Khatibi, Ali; Pourebrahim, Sharareh; Mokhtar, Mazlin Bin

2018-06-01

Carbon sequestration has been proposed as a means of slowing the atmospheric and marine accumulation of greenhouse gases. This study used observed and simulated land use/cover changes to investigate and predict carbon sequestration rates in the city of Karaj. Karaj, a metropolis of Iran, has undergone rapid population expansion and associated changes in recent years, and these changes make it suitable for use as a case study for rapidly expanding urban areas. In particular, high quality agricultural space, green space and gardens have rapidly transformed into industrial, residential and urban service areas. Five classes of land use/cover (residential, agricultural, rangeland, forest and barren areas) were considered in the study; vegetation and soil samples were taken from 20 randomly selected locations. The level of carbon sequestration was determined for the vegetation samples by calculating the amount of organic carbon present using the dry plant weight method, and for soil samples by using the method of Walkley and Black. For each area class, average values of carbon sequestration in vegetation and soil samples were calculated to give a carbon sequestration index. A cellular automata approach was used to simulate changes in the classes. Finally, the carbon sequestration indices were combined with simulation results to calculate changes in carbon sequestration for each class. It is predicted that, in the 15 year period from 2014 to 2029, much agricultural land will be transformed into residential land, resulting in a severe reduction in the level of carbon sequestration. Results from this study indicate that expansion of forest areas in urban counties would be an effective means of increasing the levels of carbon sequestration. Finally, future opportunities to include carbon sequestration into the simulation of land use/cover changes are outlined.

A 3-D model of tumor progression based on complex automata driven by particle dynamics.

PubMed

Wcisło, Rafał; Dzwinel, Witold; Yuen, David A; Dudek, Arkadiusz Z

2009-12-01

The dynamics of a growing tumor involving mechanical remodeling of healthy tissue and vasculature is neglected in most of the existing tumor models. This is due to the lack of efficient computational framework allowing for simulation of mechanical interactions. Meanwhile, just these interactions trigger critical changes in tumor growth dynamics and are responsible for its volumetric and directional progression. We describe here a novel 3-D model of tumor growth, which combines particle dynamics with cellular automata concept. The particles represent both tissue cells and fragments of the vascular network. They interact with their closest neighbors via semi-harmonic central forces simulating mechanical resistance of the cell walls. The particle dynamics is governed by both the Newtonian laws of motion and the cellular automata rules. These rules can represent cell life-cycle and other biological interactions involving smaller spatio-temporal scales. We show that our complex automata, particle based model can reproduce realistic 3-D dynamics of the entire system consisting of the tumor, normal tissue cells, blood vessels and blood flow. It can explain phenomena such as the inward cell motion in avascular tumor, stabilization of tumor growth by the external pressure, tumor vascularization due to the process of angiogenesis, trapping of healthy cells by invading tumor, and influence of external (boundary) conditions on the direction of tumor progression. We conclude that the particle model can serve as a general framework for designing advanced multiscale models of tumor dynamics and it is very competitive to the modeling approaches presented before.

Wolfram's class IV automata and a good life

NASA Astrophysics Data System (ADS)

McIntosh, Harold V.

1990-09-01

A comprehensive discussion of Wolfram's four classes of cellular automata is given, with the intention of relating them to Conway's criteria for a good game of Life. Although it is known that such classifications cannot be entirely rigorous, much information about the behavior of an automaton can be gleaned from the statistical properties of its transition table. Still more information can be deduced from the mean field approximation to its state densities, in particular, from the distribution of horizontal and diagonal tangents of the latter. In turn these characteristics can be related to the presence or absence of certain loops in the de Bruijn diagram of the automaton.

A Cellular Automata Model for the Study of Landslides

NASA Astrophysics Data System (ADS)

Liucci, Luisa; Suteanu, Cristian; Melelli, Laura

2016-04-01

Power-law scaling has been observed in the frequency distribution of landslide sizes in many regions of the world, for landslides triggered by different factors, and in both multi-temporal and post-event datasets, thus indicating the universal character of this property of landslides and suggesting that the same mechanisms drive the dynamics of mass wasting processes. The reasons for the scaling behavior of landslide sizes are widely debated, since their understanding would improve our knowledge of the spatial and temporal evolution of this phenomenon. Self-Organized Critical (SOC) dynamics and the key role of topography have been suggested as possible explanations. The scaling exponent of the landslide size-frequency distribution defines the probability of landslide magnitudes and it thus represents an important parameter for hazard assessment. Therefore, another - still unanswered - important question concerns the factors on which its value depends. This paper investigates these issues using a Cellular Automata (CA) model. The CA uses a real topographic surface acquired from a Digital Elevation Model to represent the initial state of the system, where the states of cells are defined in terms of altitude. The stability criterion is based on the slope gradient. The system is driven to instability through a temporal decrease of the stability condition of cells, which may be thought of as representing the temporal weakening of soil caused by factors like rainfall. A transition rule defines the way in which instabilities lead to discharge from unstable cells to the neighboring cells, deciding upon the landslide direction and the quantity of mass involved. Both the direction and the transferred mass depend on the local topographic features. The scaling properties of the area-frequency distributions of the resulting landslide series are investigated for several rates of weakening and for different time windows, in order to explore the response of the system to model

Automatic Management of Parallel and Distributed System Resources

NASA Technical Reports Server (NTRS)

Yan, Jerry; Ngai, Tin Fook; Lundstrom, Stephen F.

1990-01-01

Viewgraphs on automatic management of parallel and distributed system resources are presented. Topics covered include: parallel applications; intelligent management of multiprocessing systems; performance evaluation of parallel architecture; dynamic concurrent programs; compiler-directed system approach; lattice gaseous cellular automata; and sparse matrix Cholesky factorization.

Simulation of land use change and effect on potential deforestation using Markov Chain - Cellular Automata

NASA Astrophysics Data System (ADS)

Mujiono, Indra, T. L.; Harmantyo, D.; Rukmana, I. P.; Nadia, Z.

2017-07-01

The purpose of this study was to simulate land use change in 1996-2016 and its prediction in 2035 as well as its potential to deforestation. Both of these purposes were obtained through modeling analysis using Markov Chain Cellular Automata. This modeling method was considered important for understanding the causes and impacts. Based on the analysis, the land use change between 1996 to 2007 has caused forest loss (the region and non-region) covering an area of 62,012 ha. While in the period of 2007 to 2016, the change has lead to the east side of the slope grade of 0-15 percent and an altitude between 500-1000 meters above sea level. In this period, plantation area has increased by 50,822 ha, while the forest area has reduced from 80,038 ha. In a period of 20 years, North Bengkulu Regency has lost the forest area of 80,038 ha. The amount of intervention against forest suggested the potential for deforestation in this area. Simulation of land use change in 2035 did not indicate significant deforestation due to the limited land on physical factors such as slope and elevation. However, it should be noted that, in 2035, the area of conservation forest was reduced by 16,793 ha (29 %), while the areas of protected and production forest were reduced by 4,933 ha (19 %) and 2,114 ha (3 %), respectively. Land use change is a serious threat of deforestation, especially in forest areas in North Bengkulu Regency, where any decline in forest area means the addition of plantation area.

Toward Efficient Design of Reversible Logic Gates in Quantum-Dot Cellular Automata with Power Dissipation Analysis

NASA Astrophysics Data System (ADS)

Sasamal, Trailokya Nath; Singh, Ashutosh Kumar; Ghanekar, Umesh

2018-04-01

Nanotechnologies, remarkably Quantum-dot Cellular Automata (QCA), offer an attractive perspective for future computing technologies. In this paper, QCA is investigated as an implementation method for designing area and power efficient reversible logic gates. The proposed designs achieve superior performance by incorporating a compact 2-input XOR gate. The proposed design for Feynman, Toffoli, and Fredkin gates demonstrates 28.12, 24.4, and 7% reduction in cell count and utilizes 46, 24.4, and 7.6% less area, respectively over previous best designs. Regarding the cell count (area cover) that of the proposed Peres gate and Double Feynman gate are 44.32% (21.5%) and 12% (25%), respectively less than the most compact previous designs. Further, the delay of Fredkin and Toffoli gates is 0.75 clock cycles, which is equal to the delay of the previous best designs. While the Feynman and Double Feynman gates achieve a delay of 0.5 clock cycles, equal to the least delay previous one. Energy analysis confirms that the average energy dissipation of the developed Feynman, Toffoli, and Fredkin gates is 30.80, 18.08, and 4.3% (for 1.0 E k energy level), respectively less compared to best reported designs. This emphasizes the beneficial role of using proposed reversible gates to design complex and power efficient QCA circuits. The QCADesigner tool is used to validate the layout of the proposed designs, and the QCAPro tool is used to evaluate the energy dissipation.

Deriving urban dynamic evolution rules from self-adaptive cellular automata with multi-temporal remote sensing images

NASA Astrophysics Data System (ADS)

He, Yingqing; Ai, Bin; Yao, Yao; Zhong, Fajun

2015-06-01

Cellular automata (CA) have proven to be very effective for simulating and predicting the spatio-temporal evolution of complex geographical phenomena. Traditional methods generally pose problems in determining the structure and parameters of CA for a large, complex region or a long-term simulation. This study presents a self-adaptive CA model integrated with an artificial immune system to discover dynamic transition rules automatically. The model's parameters are allowed to be self-modified with the application of multi-temporal remote sensing images: that is, the CA can adapt itself to the changed and complex environment. Therefore, urban dynamic evolution rules over time can be efficiently retrieved by using this integrated model. The proposed AIS-based CA model was then used to simulate the rural-urban land conversion of Guangzhou city, located in the core of China's Pearl River Delta. The initial urban land was directly classified from TM satellite image in the year 1990. Urban land in the years 1995, 2000, 2005, 2009 and 2012 was correspondingly used as the observed data to calibrate the model's parameters. With the quantitative index figure of merit (FoM) and pattern similarity, the comparison was further performed between the AIS-based model and a Logistic CA model. The results indicate that the AIS-based CA model can perform better and with higher precision in simulating urban evolution, and the simulated spatial pattern is closer to the actual development situation.

The nature of turbulence in a triangular lattice gas automaton

NASA Astrophysics Data System (ADS)

Duong-Van, Minh; Feit, M. D.; Keller, P.; Pound, M.

1986-12-01

Power spectra calculated from the coarse-graining of a simple lattice gas automaton, and those of time averaging other stochastic times series that we have investigated, have exponents in the range -1.6 to -2, consistent with observation of fully developed turbulence. This power spectrum is a natural consequence of coarse-graining; the exponent -2 represents the continuum limit.

Observability of Automata Networks: Fixed and Switching Cases.

PubMed

Li, Rui; Hong, Yiguang; Wang, Xingyuan

2018-04-01

Automata networks are a class of fully discrete dynamical systems, which have received considerable interest in various different areas. This brief addresses the observability of automata networks and switched automata networks in a unified framework, and proposes simple necessary and sufficient conditions for observability. The results are achieved by employing methods from symbolic computation, and are suited for implementation using computer algebra systems. Several examples are presented to demonstrate the application of the results.

A SIMPLE CELLULAR AUTOMATON MODEL FOR HIGH-LEVEL VEGETATION DYNAMICS

EPA Science Inventory

We have produced a simple two-dimensional (ground-plan) cellular automata model of vegetation dynamics specifically to investigate high-level community processes. The model is probabilistic, with individual plant behavior determined by physiologically-based rules derived from a w...

Lattice model theory of the equation of state covering the gas, liquid, and solid phases

NASA Technical Reports Server (NTRS)

Bonavito, N. L.; Tanaka, T.; Chan, E. M.; Horiguchi, T.; Foreman, J. C.

1975-01-01

The three stable states of matter and the corresponding phase transitions were obtained with a single model. Patterned after Lennard-Jones and Devonshires's theory, a simple cubic lattice model containing two fcc sublattices (alpha and beta) is adopted. The interatomic potential is taken to be the Lennard-Jones (6-12) potential. Employing the cluster variation method, the Weiss and the pair approximations on the lattice gas failed to give the correct phase diagrams. Hybrid approximations were devised to describe the lattice term in the free energy. A lattice vibration term corresponding to a free volume correction is included semi-phenomenologically. The combinations of the lattice part and the free volume part yield the three states and the proper phase diagrams. To determine the coexistence regions, the equalities of the pressure and Gibbs free energy per molecule of the coexisting phases were utilized. The ordered branch of the free energy gives rise to the solid phase while the disordered branch yields the gas and liquid phases. It is observed that the triple point and the critical point quantities, the phase diagrams and the coexistence regions plotted are in good agreement with the experimental values and graphs for argon.

Using cellular automata to simulate forest fire propagation in Portugal

NASA Astrophysics Data System (ADS)

Freire, Joana; daCamara, Carlos

2017-04-01

Wildfires in the Mediterranean region have severe damaging effects mainly due to large fire events [1, 2]. When restricting to Portugal, wildfires have burned over 1:4 million ha in the last decade. Considering the increasing tendency in the extent and severity of wildfires [1, 2], the availability of modeling tools of fire episodes is of crucial importance. Two main types of mathematical models are generally available, namely deterministic and stochastic models. Deterministic models attempt a description of fires, fuel and atmosphere as multiphase continua prescribing mass, momentum and energy conservation, which typically leads to systems of coupled PDEs to be solved numerically on a grid. Simpler descriptions, such as FARSITE, neglect the interaction with atmosphere and propagate the fire front using wave techniques. One of the most important stochastic models are Cellular Automata (CA), in which space is discretized into cells, and physical quantities take on a finite set of values at each cell. The cells evolve in discrete time according to a set of transition rules, and the states of the neighboring cells. In the present work, we implement and then improve a simple and fast CA model designed to operationally simulate wildfires in Portugal. The reference CA model chosen [3] has the advantage of having been applied successfully in other Mediterranean ecosystems, namely to historical fires in Greece. The model is defined on a square grid with propagation to 8 nearest and next-nearest neighbors, where each cell is characterized by 4 possible discrete states, corresponding to burning, not-yet burned, fuel-free and completely burned cells, with 4 possible rules of evolution which take into account fuel properties, meteorological conditions, and topography. As a CA model, it offers the possibility to run a very high number of simulations in order to verify and apply the model, and is easily modified by implementing additional variables and different rules for the

A quantum Samaritan’s dilemma cellular automaton

PubMed Central

Situ, Haozhen

2017-01-01

The dynamics of a spatial quantum formulation of the iterated Samaritan’s dilemma game with variable entangling is studied in this work. The game is played in the cellular automata manner, i.e. with local and synchronous interaction. The game is assessed in fair and unfair contests, in noiseless scenarios and with disrupting quantum noise. PMID:28680654

A cellular automata model for population expansion of Spartina alterniflora at Jiuduansha Shoals, Shanghai, China

NASA Astrophysics Data System (ADS)

Huang, Hua-mei; Zhang, Li-quan; Guan, Yu-juan; Wang, Dong-hui

2008-03-01

Biological invasion has received considerable attention recently because of increasing impacts on local ecosystems. Expansion of Spartina alterniflora, a non-native species, on the intertidal mudflats of Jiuduansha Shoals at the Yangtze River Estuary is a prime example of a spatially-structured invasion in a relatively simple habitat, for which strategic control efforts can be modeled and applied. Here, we developed a Cellular Automata (CA) model, in conjunction with Remote Sensing and Geographical Information Systems, to simulate the expanding process of S. alterniflora for a period of 8 years after being introduced to the new shoals, and to study the interactions between spatial pattern and ecosystem processes for the saltmarsh vegetation. The results showed that the CA model could simulate the population dynamics of S. alterniflora and Phragmites australis on the Jiuduansha Shoals successfully. The results strongly support the hypothesis of space pre-emption as well as range expansion with simple advancing wave fronts for these two species. In the Yangtze River Estuary, the native species P. australis shares the same niche with the exotic species S. alterniflora. However, the range expansion rate of P. australis was much slower than that of S. alterniflora. With the accretion of the Jiuduansha Shoals due to the large quantity of sediments deposited by the Yangtze River, a rapid range expansion of S. alterniflora is predicted to last for a long period into future. This study indicated the potential for this approach to provide valuable insights into population and community ecology of invasive species, which could be very important for wetland biodiversity conservation and resource management in the Yangtze River Estuary and other such impacted areas.

Weakly coupled map lattice models for multicellular patterning and collective normalization of abnormal single-cell states

NASA Astrophysics Data System (ADS)

García-Morales, Vladimir; Manzanares, José A.; Mafe, Salvador

2017-04-01

We present a weakly coupled map lattice model for patterning that explores the effects exerted by weakening the local dynamic rules on model biological and artificial networks composed of two-state building blocks (cells). To this end, we use two cellular automata models based on (i) a smooth majority rule (model I) and (ii) a set of rules similar to those of Conway's Game of Life (model II). The normal and abnormal cell states evolve according to local rules that are modulated by a parameter κ . This parameter quantifies the effective weakening of the prescribed rules due to the limited coupling of each cell to its neighborhood and can be experimentally controlled by appropriate external agents. The emergent spatiotemporal maps of single-cell states should be of significance for positional information processes as well as for intercellular communication in tumorigenesis, where the collective normalization of abnormal single-cell states by a predominantly normal neighborhood may be crucial.

Weakly coupled map lattice models for multicellular patterning and collective normalization of abnormal single-cell states.

PubMed

García-Morales, Vladimir; Manzanares, José A; Mafe, Salvador

2017-04-01

We present a weakly coupled map lattice model for patterning that explores the effects exerted by weakening the local dynamic rules on model biological and artificial networks composed of two-state building blocks (cells). To this end, we use two cellular automata models based on (i) a smooth majority rule (model I) and (ii) a set of rules similar to those of Conway's Game of Life (model II). The normal and abnormal cell states evolve according to local rules that are modulated by a parameter κ. This parameter quantifies the effective weakening of the prescribed rules due to the limited coupling of each cell to its neighborhood and can be experimentally controlled by appropriate external agents. The emergent spatiotemporal maps of single-cell states should be of significance for positional information processes as well as for intercellular communication in tumorigenesis, where the collective normalization of abnormal single-cell states by a predominantly normal neighborhood may be crucial.

Semiautomated hybrid algorithm for estimation of three-dimensional liver surface in CT using dynamic cellular automata and level-sets

PubMed Central

Dakua, Sarada Prasad; Abinahed, Julien; Al-Ansari, Abdulla

2015-01-01

Abstract. Liver segmentation continues to remain a major challenge, largely due to its intense complexity with surrounding anatomical structures (stomach, kidney, and heart), high noise level and lack of contrast in pathological computed tomography (CT) data. We present an approach to reconstructing the liver surface in low contrast CT. The main contributions are: (1) a stochastic resonance-based methodology in discrete cosine transform domain is developed to enhance the contrast of pathological liver images, (2) a new formulation is proposed to prevent the object boundary, resulting from the cellular automata method, from leaking into the surrounding areas of similar intensity, and (3) a level-set method is suggested to generate intermediate segmentation contours from two segmented slices distantly located in a subject sequence. We have tested the algorithm on real datasets obtained from two sources, Hamad General Hospital and medical image computing and computer-assisted interventions grand challenge workshop. Various parameters in the algorithm, such as w, Δt, z, α, μ, α1, and α2, play imperative roles, thus their values are precisely selected. Both qualitative and quantitative evaluation performed on liver data show promising segmentation accuracy when compared with ground truth data reflecting the potential of the proposed method. PMID:26158101

Semiautomated hybrid algorithm for estimation of three-dimensional liver surface in CT using dynamic cellular automata and level-sets.

PubMed

Dakua, Sarada Prasad; Abinahed, Julien; Al-Ansari, Abdulla

2015-04-01

Liver segmentation continues to remain a major challenge, largely due to its intense complexity with surrounding anatomical structures (stomach, kidney, and heart), high noise level and lack of contrast in pathological computed tomography (CT) data. We present an approach to reconstructing the liver surface in low contrast CT. The main contributions are: (1) a stochastic resonance-based methodology in discrete cosine transform domain is developed to enhance the contrast of pathological liver images, (2) a new formulation is proposed to prevent the object boundary, resulting from the cellular automata method, from leaking into the surrounding areas of similar intensity, and (3) a level-set method is suggested to generate intermediate segmentation contours from two segmented slices distantly located in a subject sequence. We have tested the algorithm on real datasets obtained from two sources, Hamad General Hospital and medical image computing and computer-assisted interventions grand challenge workshop. Various parameters in the algorithm, such as [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text], play imperative roles, thus their values are precisely selected. Both qualitative and quantitative evaluation performed on liver data show promising segmentation accuracy when compared with ground truth data reflecting the potential of the proposed method.

A cellular automata model for traffic flow based on kinetics theory, vehicles capabilities and driver reactions

NASA Astrophysics Data System (ADS)

Guzmán, H. A.; Lárraga, M. E.; Alvarez-Icaza, L.; Carvajal, J.

2018-02-01

In this paper, a reliable cellular automata model oriented to faithfully reproduce deceleration and acceleration according to realistic reactions of drivers, when vehicles with different deceleration capabilities are considered is presented. The model focuses on describing complex traffic phenomena by coding in its rules the basic mechanisms of drivers behavior, vehicles capabilities and kinetics, while preserving simplicity. In particular, vehiclés kinetics is based on uniform accelerated motion, rather than in impulsive accelerated motion as in most existing CA models. Thus, the proposed model calculates in an analytic way three safe preserving distances to determine the best action a follower vehicle can take under a worst case scenario. Besides, the prediction analysis guarantees that under the proper assumptions, collision between vehicles may not happen at any future time. Simulations results indicate that all interactions of heterogeneous vehicles (i.e., car-truck, truck-car, car-car and truck-truck) are properly reproduced by the model. In addition, the model overcomes one of the major limitations of CA models for traffic modeling: the inability to perform smooth approach to slower or stopped vehicles. Moreover, the model is also capable of reproducing most empirical findings including the backward speed of the downstream front of the traffic jam, and different congested traffic patterns induced by a system with open boundary conditions with an on-ramp. Like most CA models, integer values are used to make the model run faster, which makes the proposed model suitable for real time traffic simulation of large networks.

Maximizing the Adjacent Possible in Automata Chemistries.

PubMed

Hickinbotham, Simon; Clark, Edward; Nellis, Adam; Stepney, Susan; Clarke, Tim; Young, Peter

2016-01-01

Automata chemistries are good vehicles for experimentation in open-ended evolution, but they are by necessity complex systems whose low-level properties require careful design. To aid the process of designing automata chemistries, we develop an abstract model that classifies the features of a chemistry from a physical (bottom up) perspective and from a biological (top down) perspective. There are two levels: things that can evolve, and things that cannot. We equate the evolving level with biology and the non-evolving level with physics. We design our initial organisms in the biology, so they can evolve. We design the physics to facilitate evolvable biologies. This architecture leads to a set of design principles that should be observed when creating an instantiation of the architecture. These principles are Everything Evolves, Everything's Soft, and Everything Dies. To evaluate these ideas, we present experiments in the recently developed Stringmol automata chemistry. We examine the properties of Stringmol with respect to the principles, and so demonstrate the usefulness of the principles in designing automata chemistries.

PAM: Particle automata model in simulation of Fusarium graminearum pathogen expansion.

PubMed

Wcisło, Rafał; Miller, S Shea; Dzwinel, Witold

2016-01-21

The multi-scale nature and inherent complexity of biological systems are a great challenge for computer modeling and classical modeling paradigms. We present a novel particle automata modeling metaphor in the context of developing a 3D model of Fusarium graminearum infection in wheat. The system consisting of the host plant and Fusarium pathogen cells can be represented by an ensemble of discrete particles defined by a set of attributes. The cells-particles can interact with each other mimicking mechanical resistance of the cell walls and cell coalescence. The particles can move, while some of their attributes can be changed according to prescribed rules. The rules can represent cellular scales of a complex system, while the integrated particle automata model (PAM) simulates its overall multi-scale behavior. We show that due to the ability of mimicking mechanical interactions of Fusarium tip cells with the host tissue, the model is able to simulate realistic penetration properties of the colonization process reproducing both vertical and lateral Fusarium invasion scenarios. The comparison of simulation results with micrographs from laboratory experiments shows encouraging qualitative agreement between the two. Copyright © 2015 Elsevier Ltd. All rights reserved.

Influence of Nutrient Availability and Quorum Sensing on the Formation of Metabolically Inactive Microcolonies Within Structurally Heterogeneous Bacterial Biofilms: An Individual-Based 3D Cellular Automata Model.

PubMed

Machineni, Lakshmi; Rajapantul, Anil; Nandamuri, Vandana; Pawar, Parag D

2017-03-01

The resistance of bacterial biofilms to antibiotic treatment has been attributed to the emergence of structurally heterogeneous microenvironments containing metabolically inactive cell populations. In this study, we use a three-dimensional individual-based cellular automata model to investigate the influence of nutrient availability and quorum sensing on microbial heterogeneity in growing biofilms. Mature biofilms exhibited at least three structurally distinct strata: a high-volume, homogeneous region sandwiched between two compact sections of high heterogeneity. Cell death occurred preferentially in layers in close proximity to the substratum, resulting in increased heterogeneity in this section of the biofilm; the thickness and heterogeneity of this lowermost layer increased with time, ultimately leading to sloughing. The model predicted the formation of metabolically dormant cellular microniches embedded within faster-growing cell clusters. Biofilms utilizing quorum sensing were more heterogeneous compared to their non-quorum sensing counterparts, and resisted sloughing, featuring a cell-devoid layer of EPS atop the substratum upon which the remainder of the biofilm developed. Overall, our study provides a computational framework to analyze metabolic diversity and heterogeneity of biofilm-associated microorganisms and may pave the way toward gaining further insights into the biophysical mechanisms of antibiotic resistance.

Fuzzy tree automata and syntactic pattern recognition.

PubMed

Lee, E T

1982-04-01

An approach of representing patterns by trees and processing these trees by fuzzy tree automata is described. Fuzzy tree automata are defined and investigated. The results include that the class of fuzzy root-to-frontier recognizable ¿-trees is closed under intersection, union, and complementation. Thus, the class of fuzzy root-to-frontier recognizable ¿-trees forms a Boolean algebra. Fuzzy tree automata are applied to processing fuzzy tree representation of patterns based on syntactic pattern recognition. The grade of acceptance is defined and investigated. Quantitative measures of ``approximate isosceles triangle,'' ``approximate elongated isosceles triangle,'' ``approximate rectangle,'' and ``approximate cross'' are defined and used in the illustrative examples of this approach. By using these quantitative measures, a house, a house with high roof, and a church are also presented as illustrative examples. In addition, three fuzzy tree automata are constructed which have the capability of processing the fuzzy tree representations of ``fuzzy houses,'' ``houses with high roofs,'' and ``fuzzy churches,'' respectively. The results may have useful applications in pattern recognition, image processing, artificial intelligence, pattern database design and processing, image science, and pictorial information systems.

Collective Behaviors in Spatially Extended Systems with Local Interactions and Synchronous Updating

NASA Astrophysics Data System (ADS)

ChatÉ, H.; Manneville, P.

1992-01-01

Assessing the extent to which dynamical systems with many degrees of freedom can be described within a thermodynamics formalism is a problem that currently attracts much attention. In this context, synchronously updated regular lattices of identical, chaotic elements with local interactions are promising models for which statistical mechanics may be hoped to provide some insights. This article presents a large class of cellular automata rules and coupled map lattices of the above type in space dimensions d = 2 to 6.Such simple models can be approached by a mean-field approximation which usually reduces the dynamics to that of a map governing the evolution of some extensive density. While this approximation is exact in the d = infty limit, where macroscopic variables must display the time-dependent behavior of the mean-field map, basic intuition from equilibrium statistical mechanics rules out any such behavior in a low-dimensional systems, since it would involve the collective motion of locally disordered elements.The models studied are chosen to be as close as possible to mean-field conditions, i.e., rather high space dimension, large connectivity, and equal-weight coupling between sites. While the mean-field evolution is never observed, a new type of non-trivial collective behavior is found, at odds with the predictions of equilibrium statistical mechanics. Both in the cellular automata models and in the coupled map lattices, macroscopic variables frequently display a non-transient, time-dependent, low-dimensional dynamics emerging out of local disorder. Striking examples are period 3 cycles in two-state cellular automata and a Hopf bifurcation for a d = 5 lattice of coupled logistic maps. An extensive account of the phenomenology is given, including a catalog of behaviors, classification tables for the celular automata rules, and bifurcation diagrams for the coupled map lattices.The observed underlying dynamics is accompanied by an intrinsic quasi-Gaussian noise

Crash energy management on the base of Movable cellular automata method

NASA Astrophysics Data System (ADS)

Psakhie, Serguei; Dmitriev, Andrei; Shilko, Evgueni; Tatarintsev, Evgueni; Korostelev, Serguei

2001-06-01

One of the main problems of materials science is increasing of structure's viability under dynamic loading. In general, a solution is the management of transformation of the energy of loading to the energy of destroying of the least important parts and details of the structure. It has to be noted that similar problem also exists in materials science, since a majority of modern materials are heterogeneous and have a complex internal structure. To optimize this structure for working under dynamic loading it is necessary to take into account the redistribution of elastic energy including phase transformation, generation and accumulation of micro-damages, etc. As far as real experiments on destroying the complex objects are sufficiently expensive and getting of detailed information is often associates with essential difficulties, the methods of computer modeling are used in solving the similar problems. As a rule, these are the methods of continuum mechanics. Although essential achievements have been obtained on the basis of these methods the continuum approach has several limitations, connected first of all with the possibility of description of generation of damages, formation and development of cracks and mass mixing effects. These problems may be solved on the basis of the Movable Cellular Automata (MCA) method, which has been successfully used for modeling fracture of the different material and structures In the paper behavior and peculiarities of failure of complex structures and materials under dynamic loading are studied on the basis of computer modeling. The results shown that sometimes even small changes of the internal structure leads to the significant increasing of the viability of the complex structures and materials. It is due to the elastic energy flux change over during the dynamical loading. This effect may be explained by the fact that elastic energy fluxes define the current stress concentration. Namely, because the area of inclusions are subjected

Low Power S-Box Architecture for AES Algorithm using Programmable Second Order Reversible Cellular Automata: An Application to WBAN.

PubMed

Gangadari, Bhoopal Rao; Ahamed, Shaik Rafi

2016-12-01

In this paper, we presented a novel approach of low energy consumption architecture of S-Box used in Advanced Encryption Standard (AES) algorithm using programmable second order reversible cellular automata (RCA 2 ). The architecture entails a low power implementation with minimal delay overhead and the performance of proposed RCA 2 based S-Box in terms of security is evaluated using the cryptographic properties such as nonlinearity, correlation immunity bias, strict avalanche criteria, entropy and also found that the proposed architecture is secure enough for cryptographic applications. Moreover, the proposed AES algorithm architecture simulation studies show that energy consumption of 68.726 nJ, power dissipation of 3.856 mW for 0.18- μm at 13.69 MHz and energy consumption of 29.408 nJ, power dissipation of 1.65 mW for 0.13- μm at 13.69 MHz. The proposed AES algorithm with RCA 2 based S-Box shows a reduction power consumption by 50 % and energy consumption by 5 % compared to best classical S-Box and composite field arithmetic based AES algorithm. Apart from that, it is also shown that RCA 2 based S-Boxes are dynamic in nature, invertible, low power dissipation compared to that of LUT based S-Box and hence suitable for Wireless Body Area Network (WBAN) applications.

Mitochondrial fusion through membrane automata.

PubMed

Giannakis, Konstantinos; Andronikos, Theodore

2015-01-01

Studies have shown that malfunctions in mitochondrial processes can be blamed for diseases. However, the mechanism behind these operations is yet not sufficiently clear. In this work we present a novel approach to describe a biomolecular model for mitochondrial fusion using notions from the membrane computing. We use a case study defined in BioAmbient calculus and we show how to translate it in terms of a P automata variant. We combine brane calculi with (mem)brane automata to produce a new scheme capable of describing simple, realistic models. We propose the further use of similar methods and the test of other biomolecular models with the same behaviour.

Effect of lattice-gas atoms on the adsorption behaviour of thioether molecules.

PubMed

Pan, Yi; Yang, Bing; Hulot, Catherine; Blechert, Siegfried; Nilius, Niklas; Freund, Hans-Joachim

2012-08-21

Using STM topographic imaging and spectroscopy, we have investigated the adsorption of two thioether molecules, 1,2-bis(phenylthio)benzene and (bis(3-phenylthio)-phenyl)sulfane, on noble and transition metal surfaces. The two substrates show nearly antipodal behaviour. Whereas complexes with one or two protruding centres are observed on Au(111), only flat and uniform ad-structures are found on NiAl(110). The difference is ascribed to the possibility of the thioethers to form metal-organic complexes by coordinating lattice-gas atoms on the Au(111), while only the pristine molecules adsorb on the alloy surface. The metal coordination in the first case is driven by the formation of strong Au-S bonds and enables the formation of characteristic monomer, dimer and chain-like structures of the thioethers, using the Au atoms as linkers. A similar mechanism is not available on the NiAl, because no lattice gas develops at this surface at room temperature. Our work demonstrates how surface properties, i.e. the availability of mobile ad-species, determine the interaction of organic molecules with metallic substrates.

Efficient Translation of LTL Formulae into Buchi Automata

NASA Technical Reports Server (NTRS)

Giannakopoulou, Dimitra; Lerda, Flavio

2001-01-01

Model checking is a fully automated technique for checking that a system satisfies a set of required properties. With explicit-state model checkers, properties are typically defined in linear-time temporal logic (LTL), and are translated into B chi automata in order to be checked. This report presents how we have combined and improved existing techniques to obtain an efficient LTL to B chi automata translator. In particular, we optimize the core of existing tableau-based approaches to generate significantly smaller automata. Our approach has been implemented and is being released as part of the Java PathFinder software (JPF), an explicit state model checker under development at the NASA Ames Research Center.

Automata-Based Verification of Temporal Properties on Running Programs

NASA Technical Reports Server (NTRS)

Giannakopoulou, Dimitra; Havelund, Klaus; Lan, Sonie (Technical Monitor)

2001-01-01

This paper presents an approach to checking a running program against its Linear Temporal Logic (LTL) specifications. LTL is a widely used logic for expressing properties of programs viewed as sets of executions. Our approach consists of translating LTL formulae to finite-state automata, which are used as observers of the program behavior. The translation algorithm we propose modifies standard LTL to Buchi automata conversion techniques to generate automata that check finite program traces. The algorithm has been implemented in a tool, which has been integrated with the generic JPaX framework for runtime analysis of Java programs.

Simulation of miniature endplate potentials in neuromuscular junctions by using a cellular automaton

NASA Astrophysics Data System (ADS)

Avella, Oscar Javier; Muñoz, José Daniel; Fayad, Ramón

2008-01-01

Miniature endplate potentials are recorded in the neuromuscular junction when the acetylcholine contents of one or a few synaptic vesicles are spontaneously released into the synaptic cleft. Since their discovery by Fatt and Katz in 1952, they have been among the paradigms in neuroscience. Those potentials are usually simulated by means of numerical approaches, such as Brownian dynamics, finite differences and finite element methods. Hereby we propose that diffusion cellular automata can be a useful alternative for investigating them. To illustrate this point, we simulate a miniature endplate potential by using experimental parameters. Our model reproduces the potential shape, amplitude and time course. Since our automaton is able to track the history and interactions of each single particle, it is very easy to introduce non-linear effects with little computational effort. This makes cellular automata excellent candidates for simulating biological reaction-diffusion processes, where no other external forces are involved.

Predicting the impact of lava flows at Mount Etna by an innovative method based on Cellular Automata: Applications regarding land-use and civil defence planning

NASA Astrophysics Data System (ADS)

Crisci, G. M.; Avolio, M. V.; D'Ambrosio, D.; di Gregorio, S.; Lupiano, G. V.; Rongo, R.; Spataro, W.; Benhcke, B.; Neri, M.

2009-04-01

Forecasting the time, character and impact of future eruptions is difficult at volcanoes with complex eruptive behaviour, such as Mount Etna, where eruptions occur from the summit and on the flanks, affecting areas distant from each other. Modern efforts for hazard evaluation and contingency planning in volcanic areas draw heavily on hazard maps and numerical simulations. The computational model here applied belongs to the SCIARA family of lava flow simulation models. In the specific case this is the SCIARA-fv release, which is considered to give the most accurate and efficient performance, given the extent (567 km2) of the study area and the great number of simulations to be carried out. The model is based on the Cellular Automata computational paradigm and, specifically, on the Macroscopic Cellular Automata approach for the modelling of spatially extended dynamic systems2. This work addresses the problem of compiling high-detailed susceptibility maps with an elaborate approach in the numerical simulation of Etnean lava flows, based on the results of 39,300 simulations of flows erupted from a grid of 393 hypothetical vents in the eastern sector of Etna. This sector was chosen because it is densely populated and frequently affected by flank eruptions. Besides the definition of general susceptibility maps, the availability of a large number of lava flows of different eruption types, magnitudes and locations simulated for this study allows the instantaneous extraction of various scenarios on demand. For instance, in a Civil Defence oriented application, it is possible to identify all source areas of lava flows capable of affecting a given area of interest, such as a town or a major infrastructure. Indeed, this application is rapidly accomplished by querying the simulation database, by selecting the lava flows that affect the area of interest and by circumscribing their sources. Eventually, a specific category of simulation is dedicated to the assessment of protective

Linear System Control Using Stochastic Learning Automata

NASA Technical Reports Server (NTRS)

Ziyad, Nigel; Cox, E. Lucien; Chouikha, Mohamed F.

1998-01-01

This paper explains the use of a Stochastic Learning Automata (SLA) to control switching between three systems to produce the desired output response. The SLA learns the optimal choice of the damping ratio for each system to achieve a desired result. We show that the SLA can learn these states for the control of an unknown system with the proper choice of the error criteria. The results of using a single automaton are compared to using multiple automata.

Electrostatic modulation of periodic potentials in a two-dimensional electron gas: From antidot lattice to quantum dot lattice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goswami, Srijit; Aamir, Mohammed Ali; Shamim, Saquib

2013-12-04

We use a dual gated device structure to introduce a gate-tuneable periodic potential in a GaAs/AlGaAs two dimensional electron gas (2DEG). Using only a suitable choice of gate voltages we can controllably alter the potential landscape of the bare 2DEG, inducing either a periodic array of antidots or quantum dots. Antidots are artificial scattering centers, and therefore allow for a study of electron dynamics. In particular, we show that the thermovoltage of an antidot lattice is particularly sensitive to the relative positions of the Fermi level and the antidot potential. A quantum dot lattice, on the other hand, provides themore » opportunity to study correlated electron physics. We find that its current-voltage characteristics display a voltage threshold, as well as a power law scaling, indicative of collective Coulomb blockade in a disordered background.« less

Cellular Automata Modelling in Predicting the Development of Settlement Areas, A Case Study in The Eastern District of Pontianak Waterfront City

NASA Astrophysics Data System (ADS)

Nurhidayati, E.; Buchori, I.; Mussadun; Fariz, T. R.

2017-07-01

Pontianak waterfront city as water-based urban has the potential of water resources, socio-economic, cultural, tourism and riverine settlements. Settlements areas in the eastern district of Pontianak waterfront city is located in the triangle of Kapuas river and Landak river. This study uses quantitative-GIS methods that integrates binary logistic regression and Cellular Automata-Markov models. The data used in this study such as satellite imagery Quickbird 2003, Ikonos 2008 and elevation contour interval 1 meter. This study aims to discover the settlement land use changes in 2003-2014 and to predict the settlements areas in 2020. This study results the accuracy in predicting of changes in settlements areas shows overall accuracy (79.74%) and the highest kappa index (0.55). The prediction results show that settlement areas (481.98 Ha) in 2020 and the increasingly of settlement areas (6.80 Ha/year) in 2014-2020. The development of settlement areas in 2020 shows the highest land expansion in Parit Mayor Village. The results of regression coefficient value (0) of flooding variable, so flooding did not influence to the development of settlement areas in the eastern district of Pontianak because the building’s adaptation of rumah panggung’s settlements was very good which have adjusted to the height of tidal flood.

Cellular automata-based forecasting of the impact of accidental fire and toxic dispersion in process industries.

PubMed

Sarkar, Chinmoy; Abbasi, S A

2006-09-01

The strategies to prevent accidents from occurring in a process industry, or to minimize the harm if an accident does take place, always revolve around forecasting the likely accidents and their impacts. Based on the likely frequency and severity of the accidents, resources are committed towards preventing the accidents. Nearly all techniques of ranking hazardous units, be it the hazard and operability studies, fault tree analysis, hazard indice, etc.--qualitative as well as quantitative--depend essentially on the assessment of the likely frequency and the likely harm accidents in different units may cause. This fact makes it exceedingly important that the forecasting the accidents and their likely impact is done as accurately as possible. In the present study we introduce a new approach to accident forecasting based on the discrete modeling paradigm of cellular automata. In this treatment an accident is modeled as a self-evolving phenomena, the impact of which is strongly influenced by the size, nature, and position of the environmental components which lie in the vicinity of the accident site. The outward propagation of the mass, energy and momentum from the accident epicenter is modeled as a fast diffusion process occurring in discrete space-time coordinates. The quantum of energy and material that would flow into each discrete space element (cell) due to the accidental release is evaluated and the degree of vulnerability posed to the receptors if present in the cell is measured at the end of each time element. This approach is able to effectively take into account the modifications in the flux of energy and material which occur as a result of the heterogeneous environment prevailing between the accident epicenter and the receptor. Consequently, more realistic accident scenarios are generated than possible with the prevailing techniques. The efficacy of the approach has been illustrated with case studies.

Viewing hybrid systems as products of control systems and automata

NASA Technical Reports Server (NTRS)

Grossman, R. L.; Larson, R. G.

1992-01-01

The purpose of this note is to show how hybrid systems may be modeled as products of nonlinear control systems and finite state automata. By a hybrid system, we mean a network of consisting of continuous, nonlinear control system connected to discrete, finite state automata. Our point of view is that the automata switches between the control systems, and that this switching is a function of the discrete input symbols or letters that it receives. We show how a nonlinear control system may be viewed as a pair consisting of a bialgebra of operators coding the dynamics, and an algebra of observations coding the state space. We also show that a finite automata has a similar representation. A hybrid system is then modeled by taking suitable products of the bialgebras coding the dynamics and the observation algebras coding the state spaces.

Using Mobile TLA as a Logic for Dynamic I/O Automata

NASA Astrophysics Data System (ADS)

Kapus, Tatjana

Input/Output (I/O) automata and the Temporal Logic of Actions (TLA) are two well-known techniques for the specification and verification of concurrent systems. Over the past few years, they have been extended to the so-called dynamic I/O automata and, respectively, Mobile TLA (MTLA) in order to be more appropriate for mobile agent systems. Dynamic I/O automata is just a mathematical model, whereas MTLA is a logic with a formally defined language. In this paper, therefore, we investigate how MTLA could be used as a formal language for the specification of dynamic I/O automata. We do this by writing an MTLA specification of a travel agent system which has been specified semi-formally in the literature on that model. In this specification, we deal with always existing agents as well as with an initially unknown number of dynamically created agents, with mobile and non-mobile agents, with I/O-automata-style communication, and with the changing communication capabilities of mobile agents. We have previously written a TLA specification of this system. This paper shows that an MTLA specification of such a system can be more elegant and faithful to the dynamic I/O automata definition because the agent existence and location can be expressed directly by using agent and location names instead of special variables as in TLA. It also shows how the reuse of names for dynamically created and destroyed agents within the dynamic I/O automata framework can be specified in MTLA.

Decentralized indirect methods for learning automata games.

PubMed

Tilak, Omkar; Martin, Ryan; Mukhopadhyay, Snehasis

2011-10-01

We discuss the application of indirect learning methods in zero-sum and identical payoff learning automata games. We propose a novel decentralized version of the well-known pursuit learning algorithm. Such a decentralized algorithm has significant computational advantages over its centralized counterpart. The theoretical study of such a decentralized algorithm requires the analysis to be carried out in a nonstationary environment. We use a novel bootstrapping argument to prove the convergence of the algorithm. To our knowledge, this is the first time that such analysis has been carried out for zero-sum and identical payoff games. Extensive simulation studies are reported, which demonstrate the proposed algorithm's fast and accurate convergence in a variety of game scenarios. We also introduce the framework of partial communication in the context of identical payoff games of learning automata. In such games, the automata may not communicate with each other or may communicate selectively. This comprehensive framework has the capability to model both centralized and decentralized games discussed in this paper.

van der Waals Interactions in Hadron Resonance Gas: From Nuclear Matter to Lattice QCD.

PubMed

Vovchenko, Volodymyr; Gorenstein, Mark I; Stoecker, Horst

2017-05-05

An extension of the ideal hadron resonance gas (HRG) model is constructed which includes the attractive and repulsive van der Waals (VDW) interactions between baryons. This VDW-HRG model yields the nuclear liquid-gas transition at low temperatures and high baryon densities. The VDW parameters a and b are fixed by the ground state properties of nuclear matter, and the temperature dependence of various thermodynamic observables at zero chemical potential are calculated within the VDW-HRG model. Compared to the ideal HRG model, the inclusion of VDW interactions between baryons leads to a qualitatively different behavior of second and higher moments of fluctuations of conserved charges, in particular in the so-called crossover region T∼140-190  MeV. For many observables this behavior resembles closely the results obtained from lattice QCD simulations. This hadronic model also predicts nontrivial behavior of net-baryon fluctuations in the region of phase diagram probed by heavy-ion collision experiments. These results imply that VDW interactions play a crucial role in the thermodynamics of hadron gas. Thus, the commonly performed comparisons of the ideal HRG model with the lattice and heavy-ion data may lead to misconceptions and misleading conclusions.

Plate-impact loading of cellular structures formed by selective laser melting

NASA Astrophysics Data System (ADS)

Winter, R. E.; Cotton, M.; Harris, E. J.; Maw, J. R.; Chapman, D. J.; Eakins, D. E.; McShane, G.

2014-03-01

Porous materials are of great interest because of improved energy absorption over their solid counterparts. Their properties, however, have been difficult to optimize. Additive manufacturing has emerged as a potential technique to closely define the structure and properties of porous components, i.e. density, strut width and pore size; however, the behaviour of these materials at very high impact energies remains largely unexplored. We describe an initial study of the dynamic compression response of lattice materials fabricated through additive manufacturing. Lattices consisting of an array of intersecting stainless steel rods were fabricated into discs using selective laser melting. The resulting discs were impacted against solid stainless steel targets at velocities ranging from 300 to 700 m s-1 using a gas gun. Continuum CTH simulations were performed to identify key features in the measured wave profiles, while 3D simulations, in which the individual cells were modelled, revealed details of microscale deformation during collapse of the lattice structure. The validated computer models have been used to provide an understanding of the deformation processes in the cellular samples. The study supports the optimization of cellular structures for application as energy absorbers.

Estimation of daily Snow Cover Area combining MODIS and LANDSAT information by using cellular automata

NASA Astrophysics Data System (ADS)

Pardo-Iguzquiza, Eulogio; Juan Collados Lara, Antonio; Pulido-Velazquez, David

2016-04-01

The snow availability in Alpine catchments is essential for the economy of these areas. It plays an important role in tourist development but also in the management of the Water Resources Snow is an important water resource in many river basins with mountains in the catchment area. The determination of the snow water equivalent requires the estimation of the evolution of the snow pack (cover area, thickness and snow density) along the time. Although there are complex physical models of the dynamics of the snow pack, sometimes the data available are scarce and a stochastic model like the cellular automata (CA) can be of great practical interest. CA can be used to model the dynamics of growth and wane of the snow pack. The CA is calibrated with historical data. This requires the determination of transition rules that are capable of modeling the evolution of the spatial pattern of snow cover area. Furthermore, CA requires the definition of states and neighborhoods. We have included topographical variables and climatological variables in order to define the state of each pixel. The evolution of snow cover in a pixel depends on its state, the state of the neighboring pixels and the transition rules. The calibration of the CA is done using daily MODIS data, available for the period 24/02/2002 to present with a spatial resolution of 500 m, and the LANDSAT information available with a sixteen-day periodicity from 1984 to the present and with spatial resolution of 30 m. The methodology has been applied to estimation of the snow cover area of Sierra Nevada mountain range in the Southern of Spain to obtain snow cover area daily information with 500 m spatial resolution for the period 1980-2014. Acknowledgments: This research has been partially supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank NASA DAAC and LANDSAT project for the data provided for this study.

Safety evaluation of driver cognitive failures and driving errors on right-turn filtering movement at signalized road intersections based on Fuzzy Cellular Automata (FCA) model.

PubMed

Chai, Chen; Wong, Yiik Diew; Wang, Xuesong

2017-07-01

This paper proposes a simulation-based approach to estimate safety impact of driver cognitive failures and driving errors. Fuzzy Logic, which involves linguistic terms and uncertainty, is incorporated with Cellular Automata model to simulate decision-making process of right-turn filtering movement at signalized intersections. Simulation experiments are conducted to estimate the relationships between cognitive failures and driving errors with safety performance. Simulation results show Different types of cognitive failures are found to have varied relationship with driving errors and safety performance. For right-turn filtering movement, cognitive failures are more likely to result in driving errors with denser conflicting traffic stream. Moreover, different driving errors are found to have different safety impacts. The study serves to provide a novel approach to linguistically assess cognitions and replicate decision-making procedures of the individual driver. Compare to crash analysis, the proposed FCA model allows quantitative estimation of particular cognitive failures, and the impact of cognitions on driving errors and safety performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Lattice Three-Species Models of the Spatial Spread of Rabies among FOXES

NASA Astrophysics Data System (ADS)

Benyoussef, A.; Boccara, N.; Chakib, H.; Ez-Zahraouy, H.

Lattice models describing the spatial spread of rabies among foxes are studied. In these models, the fox population is divided into three-species: susceptible (S), infected or incubating (I), and infectious or rabid (R). They are based on the fact that susceptible and incubating foxes are territorial while rabid foxes have lost their sense of direction and move erratically. Two different models are investigated: a one-dimensional coupled-map lattice model, and a two-dimensional automata network model. Both models take into account the short-range character of the infection process and the diffusive motion of rabid foxes. Numerical simulations show how the spatial distribution of rabies, and the speed of propagation of the epizootic front depend upon the carrying capacity of the environment and diffusion of rabid foxes out of their territory.

Solving multiconstraint assignment problems using learning automata.

PubMed

Horn, Geir; Oommen, B John

2010-02-01

This paper considers the NP-hard problem of object assignment with respect to multiple constraints: assigning a set of elements (or objects) into mutually exclusive classes (or groups), where the elements which are "similar" to each other are hopefully located in the same class. The literature reports solutions in which the similarity constraint consists of a single index that is inappropriate for the type of multiconstraint problems considered here and where the constraints could simultaneously be contradictory. This feature, where we permit possibly contradictory constraints, distinguishes this paper from the state of the art. Indeed, we are aware of no learning automata (or other heuristic) solutions which solve this problem in its most general setting. Such a scenario is illustrated with the static mapping problem, which consists of distributing the processes of a parallel application onto a set of computing nodes. This is a classical and yet very important problem within the areas of parallel computing, grid computing, and cloud computing. We have developed four learning-automata (LA)-based algorithms to solve this problem: First, a fixed-structure stochastic automata algorithm is presented, where the processes try to form pairs to go onto the same node. This algorithm solves the problem, although it requires some centralized coordination. As it is desirable to avoid centralized control, we subsequently present three different variable-structure stochastic automata (VSSA) algorithms, which have superior partitioning properties in certain settings, although they forfeit some of the scalability features of the fixed-structure algorithm. All three VSSA algorithms model the processes as automata having first the hosting nodes as possible actions; second, the processes as possible actions; and, third, attempting to estimate the process communication digraph prior to probabilistically mapping the processes. This paper, which, we believe, comprehensively reports the

Theory of gas hydrates: effect of the approximation of rigid water lattice.

PubMed

Pimpalgaonkar, Hrushikesh; Veesam, Shivanand K; Punnathanam, Sudeep N

2011-08-25

One of the assumptions of the van der Waals and Platteeuw theory for gas hydrates is that the host water lattice is rigid and not distorted by the presence of guest molecules. In this work, we study the effect of this approximation on the triple-point lines of the gas hydrates. We calculate the triple-point lines of methane and ethane hydrates via Monte Carlo molecular simulations and compare the simulation results with the predictions of van der Waals and Platteeuw theory. Our study shows that even if the exact intermolecular potential between the guest molecules and water is known, the dissociation temperatures predicted by the theory are significantly higher. This has serious implications to the modeling of gas hydrate thermodynamics, and in spite of the several impressive efforts made toward obtaining an accurate description of intermolecular interactions in gas hydrates, the theory will suffer from the problem of robustness if the issue of movement of water molecules is not adequately addressed. © 2011 American Chemical Society

Soliton cellular automaton associated with Dn(1)-crystal B2,s

NASA Astrophysics Data System (ADS)

Misra, Kailash C.; Wilson, Evan A.

2013-04-01

A solvable vertex model in ferromagnetic regime gives rise to a soliton cellular automaton which is a discrete dynamical system in which site variables take on values in a finite set. We study the scattering of a class of soliton cellular automata associated with the U_q(D_n^{(1)})-perfect crystal B2, s. We calculate the combinatorial R matrix for all elements of B2, s ⊗ B2, 1. In particular, we show that the scattering rule for our soliton cellular automaton can be identified with the combinatorial R matrix for U_q(A_1^{(1)}) oplus U_q(D_{n-2}^{(1)})-crystals.

Current quantization and fractal hierarchy in a driven repulsive lattice gas.

PubMed

Rotondo, Pietro; Sellerio, Alessandro Luigi; Glorioso, Pietro; Caracciolo, Sergio; Cosentino Lagomarsino, Marco; Gherardi, Marco

2017-11-01

Driven lattice gases are widely regarded as the paradigm of collective phenomena out of equilibrium. While such models are usually studied with nearest-neighbor interactions, many empirical driven systems are dominated by slowly decaying interactions such as dipole-dipole and Van der Waals forces. Motivated by this gap, we study the nonequilibrium stationary state of a driven lattice gas with slow-decayed repulsive interactions at zero temperature. By numerical and analytical calculations of the particle current as a function of the density and of the driving field, we identify (i) an abrupt breakdown transition between insulating and conducting states, (ii) current quantization into discrete phases where a finite current flows with infinite differential resistivity, and (iii) a fractal hierarchy of excitations, related to the Farey sequences of number theory. We argue that the origin of these effects is the competition between scales, which also causes the counterintuitive phenomenon that crystalline states can melt by increasing the density.

Current quantization and fractal hierarchy in a driven repulsive lattice gas

NASA Astrophysics Data System (ADS)

Rotondo, Pietro; Sellerio, Alessandro Luigi; Glorioso, Pietro; Caracciolo, Sergio; Cosentino Lagomarsino, Marco; Gherardi, Marco

2017-11-01

Driven lattice gases are widely regarded as the paradigm of collective phenomena out of equilibrium. While such models are usually studied with nearest-neighbor interactions, many empirical driven systems are dominated by slowly decaying interactions such as dipole-dipole and Van der Waals forces. Motivated by this gap, we study the nonequilibrium stationary state of a driven lattice gas with slow-decayed repulsive interactions at zero temperature. By numerical and analytical calculations of the particle current as a function of the density and of the driving field, we identify (i) an abrupt breakdown transition between insulating and conducting states, (ii) current quantization into discrete phases where a finite current flows with infinite differential resistivity, and (iii) a fractal hierarchy of excitations, related to the Farey sequences of number theory. We argue that the origin of these effects is the competition between scales, which also causes the counterintuitive phenomenon that crystalline states can melt by increasing the density.

Modelling and analyzing the watershed dynamics using Cellular Automata (CA)-Markov model - A geo-information based approach

NASA Astrophysics Data System (ADS)

Behera, Mukunda D.; Borate, Santosh N.; Panda, Sudhindra N.; Behera, Priti R.; Roy, Partha S.

2012-08-01

Improper practices of land use and land cover (LULC) including deforestation, expansion of agriculture and infrastructure development are deteriorating watershed conditions. Here, we have utilized remote sensing and GIS tools to study LULC dynamics using Cellular Automata (CA)-Markov model and predicted the future LULC scenario, in terms of magnitude and direction, based on past trend in a hydrological unit, Choudwar watershed, India. By analyzing the LULC pattern during 1972, 1990, 1999 and 2005 using satellite-derived maps, we observed that the biophysical and socio-economic drivers including residential/industrial development, road-rail and settlement proximity have influenced the spatial pattern of the watershed LULC, leading to an accretive linear growth of agricultural and settlement areas. The annual rate of increase from 1972 to 2004 in agriculture land, settlement was observed to be 181.96, 9.89 ha/year, respectively, while decrease in forest, wetland and marshy land were 91.22, 27.56 and 39.52 ha/year, respectively. Transition probability and transition area matrix derived using inputs of (i) residential/industrial development and (ii) proximity to transportation network as the major causes. The predicted LULC scenario for the year 2014, with reasonably good accuracy would provide useful inputs to the LULC planners for effective management of the watershed. The study is a maiden attempt that revealed agricultural expansion is the main driving force for loss of forest, wetland and marshy land in the Choudwar watershed and has the potential to continue in future. The forest in lower slopes has been converted to agricultural land and may soon take a call on forests occurring on higher slopes. Our study utilizes three time period changes to better account for the trend and the modelling exercise; thereby advocates for better agricultural practices with additional energy subsidy to arrest further forest loss and LULC alternations.

Identifying Flow Networks in a Karstified Aquifer by Application of the Cellular Automata-Based Deterministic Inversion Method (Lez Aquifer, France)

NASA Astrophysics Data System (ADS)

Fischer, P.; Jardani, A.; Wang, X.; Jourde, H.; Lecoq, N.

2017-12-01

The distributed modeling of flow paths within karstic and fractured fields remains a complex task because of the high dependence of the hydraulic responses to the relative locations between observational boreholes and interconnected fractures and karstic conduits that control the main flow of the hydrosystem. The inverse problem in a distributed model is one alternative approach to interpret the hydraulic test data by mapping the karstic networks and fractured areas. In this work, we developed a Bayesian inversion approach, the Cellular Automata-based Deterministic Inversion (CADI) algorithm to infer the spatial distribution of hydraulic properties in a structurally constrained model. This method distributes hydraulic properties along linear structures (i.e., flow conduits) and iteratively modifies the structural geometry of this conduit network to progressively match the observed hydraulic data to the modeled ones. As a result, this method produces a conductivity model that is composed of a discrete conduit network embedded in the background matrix, capable of producing the same flow behavior as the investigated hydrologic system. The method is applied to invert a set of multiborehole hydraulic tests collected from a hydraulic tomography experiment conducted at the Terrieu field site in the Lez aquifer, Southern France. The emergent model shows a high consistency to field observation of hydraulic connections between boreholes. Furthermore, it provides a geologically realistic pattern of flow conduits. This method is therefore of considerable value toward an enhanced distributed modeling of the fractured and karstified aquifers.

The role of the tunneling matrix element and nuclear reorganization in the design of quantum-dot cellular automata molecules

NASA Astrophysics Data System (ADS)

Henry, Jackson; Blair, Enrique P.

2018-02-01

Mixed-valence molecules provide an implementation for a high-speed, energy-efficient paradigm for classical computing known as quantum-dot cellular automata (QCA). The primitive device in QCA is a cell, a structure with multiple quantum dots and a few mobile charges. A single mixed-valence molecule can function as a cell, with redox centers providing quantum dots. The charge configuration of a molecule encodes binary information, and device switching occurs via intramolecular electron transfer between dots. Arrays of molecular cells adsorbed onto a substrate form QCA logic. Individual cells in the array are coupled locally via the electrostatic electric field. This device networking enables general-purpose computing. Here, a quantum model of a two-dot molecule is built in which the two-state electronic system is coupled to the dominant nuclear vibrational mode via a reorganization energy. This model is used to explore the effects of the electronic inter-dot tunneling (coupling) matrix element and the reorganization energy on device switching. A semi-classical reduction of the model also is made to investigate the competition between field-driven device switching and the electron-vibrational self-trapping. A strong electron-vibrational coupling (high reorganization energy) gives rise to self-trapping, which inhibits the molecule's ability to switch. Nonetheless, there remains an expansive area in the tunneling-reorganization phase space where molecules can support adequate tunneling. Thus, the relationship between the tunneling matrix element and the reorganization energy affords significant leeway in the design of molecules viable for QCA applications.

Simulation of gas flow in micro-porous media with the regularized lattice Boltzmann method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Junjian; Kang, Qinjun; Wang, Yuzhu

One primary challenge for prediction of gas flow in the unconventional gas reservoir at the pore-scale such as shale and tight gas reservoirs is the geometric complexity of the micro-porous media. In this paper, a regularized multiple-relaxation-time (MRT) lattice Boltzmann (LB) model is applied to analyze gas flow in 2-dimensional micro-porous medium reconstructed by quartet structure generation set (QSGS) on pore-scale. In this paper, the velocity distribution inside the porous structure is presented and analyzed, and the effects of the porosity and specific surface area on the rarefied gas flow and apparent permeability are examined and investigated. The simulation resultsmore » indicate that the gas exhibits different flow behaviours at various pressure conditions and the gas permeability is strongly related to the pressure. Finally, the increased porosity or the decreased specific surface area leads to the increase of the gas apparent permeability, and the gas flow is more sensitive to the pore morphological properties at low-pressure conditions.« less

Simulation of gas flow in micro-porous media with the regularized lattice Boltzmann method

DOE PAGES

Wang, Junjian; Kang, Qinjun; Wang, Yuzhu; ...

2017-06-01

One primary challenge for prediction of gas flow in the unconventional gas reservoir at the pore-scale such as shale and tight gas reservoirs is the geometric complexity of the micro-porous media. In this paper, a regularized multiple-relaxation-time (MRT) lattice Boltzmann (LB) model is applied to analyze gas flow in 2-dimensional micro-porous medium reconstructed by quartet structure generation set (QSGS) on pore-scale. In this paper, the velocity distribution inside the porous structure is presented and analyzed, and the effects of the porosity and specific surface area on the rarefied gas flow and apparent permeability are examined and investigated. The simulation resultsmore » indicate that the gas exhibits different flow behaviours at various pressure conditions and the gas permeability is strongly related to the pressure. Finally, the increased porosity or the decreased specific surface area leads to the increase of the gas apparent permeability, and the gas flow is more sensitive to the pore morphological properties at low-pressure conditions.« less

A cellular automata model of Ebola virus dynamics

NASA Astrophysics Data System (ADS)

Burkhead, Emily; Hawkins, Jane

2015-11-01

We construct a stochastic cellular automaton (SCA) model for the spread of the Ebola virus (EBOV). We make substantial modifications to an existing SCA model used for HIV, introduced by others and studied by the authors. We give a rigorous analysis of the similarities between models due to the spread of virus and the typical immune response to it, and the differences which reflect the drastically different timing of the course of EBOV. We demonstrate output from the model and compare it with clinical data.

Structure and anomalous solubility for hard spheres in an associating lattice gas model.

PubMed

Szortyka, Marcia M; Girardi, Mauricio; Henriques, Vera B; Barbosa, Marcia C

2012-08-14

In this paper we investigate the solubility of a hard-sphere gas in a solvent modeled as an associating lattice gas. The solution phase diagram for solute at 5% is compared with the phase diagram of the original solute free model. Model properties are investigated both through Monte Carlo simulations and a cluster approximation. The model solubility is computed via simulations and is shown to exhibit a minimum as a function of temperature. The line of minimum solubility (TmS) coincides with the line of maximum density (TMD) for different solvent chemical potentials, in accordance with the literature on continuous realistic models and on the "cavity" picture.

On the effect of memory in a quantum prisoner's dilemma cellular automaton

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón; Revuelta, Fabio

2018-03-01

The disrupting effect of quantum memory on the dynamics of a spatial quantum formulation of the iterated prisoner's dilemma game with variable entangling is studied. The game is played within a cellular automata framework, i.e., with local and synchronous interactions. The main findings of this work refer to the shrinking effect of memory on the disruption induced by noise.

Simulation of changes in heavy metal contamination in farmland soils of a typical manufacturing center through logistic-based cellular automata modeling.

PubMed

Qiu, Menglong; Wang, Qi; Li, Fangbai; Chen, Junjian; Yang, Guoyi; Liu, Liming

2016-01-01

A customized logistic-based cellular automata (CA) model was developed to simulate changes in heavy metal contamination (HMC) in farmland soils of Dongguan, a manufacturing center in Southern China, and to discover the relationship between HMC and related explanatory variables (continuous and categorical). The model was calibrated through the simulation and validation of HMC in 2012. Thereafter, the model was implemented for the scenario simulation of development alternatives for HMC in 2022. The HMC in 2002 and 2012 was determined through soil tests and cokriging. Continuous variables were divided into two groups by odds ratios. Positive variables (odds ratios >1) included the Nemerow synthetic pollution index in 2002, linear drainage density, distance from the city center, distance from the railway, slope, and secondary industrial output per unit of land. Negative variables (odds ratios <1) included elevation, distance from the road, distance from the key polluting enterprises, distance from the town center, soil pH, and distance from bodies of water. Categorical variables, including soil type, parent material type, organic content grade, and land use type, also significantly influenced HMC according to Wald statistics. The relative operating characteristic and kappa coefficients were 0.91 and 0.64, respectively, which proved the validity and accuracy of the model. The scenario simulation shows that the government should not only implement stricter environmental regulation but also strengthen the remediation of the current polluted area to effectively mitigate HMC.

A Decomposition Theorem for Finite Automata.

ERIC Educational Resources Information Center

Santa Coloma, Teresa L.; Tucci, Ralph P.

1990-01-01

Described is automata theory which is a branch of theoretical computer science. A decomposition theorem is presented that is easier than the Krohn-Rhodes theorem. Included are the definitions, the theorem, and a proof. (KR)

Threshold effect with stochastic fluctuation in bacteria-colony-like proliferation dynamics as analyzed through a comparative study of reaction-diffusion equations and cellular automata

NASA Astrophysics Data System (ADS)

Odagiri, Kenta; Takatsuka, Kazuo

2009-02-01

We report a comparative study on pattern formation between the methods of cellular automata (CA) and reaction-diffusion equations (RD) applying to a morphology of bacterial colony formation. To do so, we began the study with setting an extremely simple model, which was designed to realize autocatalytic proliferation of bacteria (denoted as X ) fed with nutrition (N) and their inactive state (prespore state) P1 due to starvation: X+N→2X and X→P1 , respectively. It was found numerically that while the CA could successfully generate rich patterns ranging from the circular fat structure to the viscous-finger-like complicated one, the naive RD reproduced only the circular pattern but failed to give a finger structure. Augmenting the RD equations by adding two physical factors, (i) a threshold effect in the dynamics of X+N→2X (breaking the continuity limit of RD) and (ii) internal noise with onset threshold (breaking the inherent symmetry of RD), we have found that the viscous-finger-like realistic patterns are indeed recovered by thus modified RD. This highlights the important difference between CA and RD, and at the same time, clarifies the necessary factors for the complicated patterns to emerge in such a surprisingly simple model system.

Towards a voxel-based geographic automata for the simulation of geospatial processes

NASA Astrophysics Data System (ADS)

Jjumba, Anthony; Dragićević, Suzana

2016-07-01

Many geographic processes evolve in a three dimensional space and time continuum. However, when they are represented with the aid of geographic information systems (GIS) or geosimulation models they are modelled in a framework of two-dimensional space with an added temporal component. The objective of this study is to propose the design and implementation of voxel-based automata as a methodological approach for representing spatial processes evolving in the four-dimensional (4D) space-time domain. Similar to geographic automata models which are developed to capture and forecast geospatial processes that change in a two-dimensional spatial framework using cells (raster geospatial data), voxel automata rely on the automata theory and use three-dimensional volumetric units (voxels). Transition rules have been developed to represent various spatial processes which range from the movement of an object in 3D to the diffusion of airborne particles and landslide simulation. In addition, the proposed 4D models demonstrate that complex processes can be readily reproduced from simple transition functions without complex methodological approaches. The voxel-based automata approach provides a unique basis to model geospatial processes in 4D for the purpose of improving representation, analysis and understanding their spatiotemporal dynamics. This study contributes to the advancement of the concepts and framework of 4D GIS.

Density profiles of a self-gravitating lattice gas in one, two, and three dimensions

NASA Astrophysics Data System (ADS)

Bakhti, Benaoumeur; Boukari, Divana; Karbach, Michael; Maass, Philipp; Müller, Gerhard

2018-04-01

We consider a lattice gas in spaces of dimensionality D =1 ,2 ,3 . The particles are subject to a hardcore exclusion interaction and an attractive pair interaction that satisfies Gauss' law as do Newtonian gravity in D =3 , a logarithmic potential in D =2 , and a distance-independent force in D =1 . Under mild additional assumptions regarding symmetry and fluctuations we investigate equilibrium states of self-gravitating material clusters, in particular radial density profiles for closed and open systems. We present exact analytic results in several instances and high-precision numerical data in others. The density profile of a cluster with finite mass is found to exhibit exponential decay in D =1 and power-law decay in D =2 with temperature-dependent exponents in both cases. In D =2 the gas evaporates in a continuous transition at a nonzero critical temperature. We describe clusters of infinite mass in D =3 with a density profile consisting of three layers (core, shell, halo) and an algebraic large-distance asymptotic decay. In D =3 a cluster of finite mass can be stabilized at T >0 via confinement to a sphere of finite radius. In some parameter regime, the gas thus enclosed undergoes a discontinuous transition between distinct density profiles. For the free energy needed to identify the equilibrium state we introduce a construction of gravitational self-energy that works in all D for the lattice gas. The decay rate of the density profile of an open cluster is shown to transform via a stretched exponential for 1

A cellular automaton implementation of a quantum battle of the sexes game with imperfect information

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón

2015-10-01

The dynamics of a spatial quantum formulation of the iterated battle of the sexes game with imperfect information is studied in this work. The game is played with variable entangling in a cellular automata manner, i.e. with local and synchronous interaction. The effect of spatial structure is assessed in fair and unfair scenarios.

A quantum relativistic battle of the sexes cellular automaton

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón; Situ, Haozhen

2017-02-01

The effect of variable entangling on the dynamics of a spatial quantum relativistic formulation of the iterated battle of the sexes game is studied in this work. The game is played in the cellular automata manner, i.e., with local and synchronous interaction. The game is assessed in fair and unfair contests. Despite the full range of quantum parameters initially accessible, they promptly converge into fairly stable configurations, that often show rich spatial structures in simulations with no negligible entanglement.

Authorship attribution based on Life-Like Network Automata

PubMed Central

Machicao, Jeaneth; Corrêa, Edilson A.; Miranda, Gisele H. B.; Amancio, Diego R.

2018-01-01

The authorship attribution is a problem of considerable practical and technical interest. Several methods have been designed to infer the authorship of disputed documents in multiple contexts. While traditional statistical methods based solely on word counts and related measurements have provided a simple, yet effective solution in particular cases; they are prone to manipulation. Recently, texts have been successfully modeled as networks, where words are represented by nodes linked according to textual similarity measurements. Such models are useful to identify informative topological patterns for the authorship recognition task. However, there is no consensus on which measurements should be used. Thus, we proposed a novel method to characterize text networks, by considering both topological and dynamical aspects of networks. Using concepts and methods from cellular automata theory, we devised a strategy to grasp informative spatio-temporal patterns from this model. Our experiments revealed an outperformance over structural analysis relying only on topological measurements, such as clustering coefficient, betweenness and shortest paths. The optimized results obtained here pave the way for a better characterization of textual networks. PMID:29566100

Authorship attribution based on Life-Like Network Automata.

PubMed

Machicao, Jeaneth; Corrêa, Edilson A; Miranda, Gisele H B; Amancio, Diego R; Bruno, Odemir M

2018-01-01

The authorship attribution is a problem of considerable practical and technical interest. Several methods have been designed to infer the authorship of disputed documents in multiple contexts. While traditional statistical methods based solely on word counts and related measurements have provided a simple, yet effective solution in particular cases; they are prone to manipulation. Recently, texts have been successfully modeled as networks, where words are represented by nodes linked according to textual similarity measurements. Such models are useful to identify informative topological patterns for the authorship recognition task. However, there is no consensus on which measurements should be used. Thus, we proposed a novel method to characterize text networks, by considering both topological and dynamical aspects of networks. Using concepts and methods from cellular automata theory, we devised a strategy to grasp informative spatio-temporal patterns from this model. Our experiments revealed an outperformance over structural analysis relying only on topological measurements, such as clustering coefficient, betweenness and shortest paths. The optimized results obtained here pave the way for a better characterization of textual networks.

Unary probabilistic and quantum automata on promise problems

NASA Astrophysics Data System (ADS)

Gainutdinova, Aida; Yakaryılmaz, Abuzer

2018-02-01

We continue the systematic investigation of probabilistic and quantum finite automata (PFAs and QFAs) on promise problems by focusing on unary languages. We show that bounded-error unary QFAs are more powerful than bounded-error unary PFAs, and, contrary to the binary language case, the computational power of Las-Vegas QFAs and bounded-error PFAs is equivalent to the computational power of deterministic finite automata (DFAs). Then, we present a new family of unary promise problems defined with two parameters such that when fixing one parameter QFAs can be exponentially more succinct than PFAs and when fixing the other parameter PFAs can be exponentially more succinct than DFAs.

Cellular automata modeling depicts degradation of cellulosic material by a cellulase system with single-molecule resolution.

PubMed

Eibinger, Manuel; Zahel, Thomas; Ganner, Thomas; Plank, Harald; Nidetzky, Bernd

2016-01-01

Enzymatic hydrolysis of cellulose involves the spatiotemporally correlated action of distinct polysaccharide chain cleaving activities confined to the surface of an insoluble substrate. Because cellulases differ in preference for attacking crystalline compared to amorphous cellulose, the spatial distribution of structural order across the cellulose surface imposes additional constraints on the dynamic interplay between the enzymes. Reconstruction of total system behavior from single-molecule activity parameters is a longstanding key goal in the field. We have developed a stochastic, cellular automata-based modeling approach to describe degradation of cellulosic material by a cellulase system at single-molecule resolution. Substrate morphology was modeled to represent the amorphous and crystalline phases as well as the different spatial orientations of the polysaccharide chains. The enzyme system model consisted of an internally chain-cleaving endoglucanase (EG) as well as two processively acting, reducing and non-reducing chain end-cleaving cellobiohydrolases (CBHs). Substrate preference (amorphous: EG, CBH II; crystalline: CBH I) and characteristic frequencies for chain cleavage, processive movement, and dissociation were assigned from biochemical data. Once adsorbed, enzymes were allowed to reach surface-exposed substrate sites through "random-walk" lateral diffusion or processive motion. Simulations revealed that slow dissociation of processive enzymes at obstacles obstructing further movement resulted in local jamming of the cellulases, with consequent delay in the degradation of the surface area affected. Exploiting validation against evidence from atomic force microscopy imaging as a unique opportunity opened up by the modeling approach, we show that spatiotemporal characteristics of cellulose surface degradation by the system of synergizing cellulases were reproduced quantitatively at the nanometer resolution of the experimental data. This in turn gave

Changes in mangrove species assemblages and future prediction of the Bangladesh Sundarbans using Markov chain model and cellular automata.

PubMed

Mukhopadhyay, Anirban; Mondal, Parimal; Barik, Jyotiskona; Chowdhury, S M; Ghosh, Tuhin; Hazra, Sugata

2015-06-01

The composition and assemblage of mangroves in the Bangladesh Sundarbans are changing systematically in response to several environmental factors. In order to understand the impact of the changing environmental conditions on the mangrove forest, species composition maps for the years 1985, 1995 and 2005 were studied. In the present study, 1985 and 1995 species zonation maps were considered as base data and the cellular automata-Markov chain model was run to predict the species zonation for the year 2005. The model output was validated against the actual dataset for 2005 and calibrated. Finally, using the model, mangrove species zonation maps for the years 2025, 2055 and 2105 have been prepared. The model was run with the assumption that the continuation of the current tempo and mode of drivers of environmental factors (temperature, rainfall, salinity change) of the last two decades will remain the same in the next few decades. Present findings show that the area distribution of the following species assemblages like Goran (Ceriops), Sundari (Heritiera), Passur (Xylocarpus), and Baen (Avicennia) would decrease in the descending order, whereas the area distribution of Gewa (Excoecaria), Keora (Sonneratia) and Kankra (Bruguiera) dominated assemblages would increase. The spatial distribution of projected mangrove species assemblages shows that more salt tolerant species will dominate in the future; which may be used as a proxy to predict the increase of salinity and its spatial variation in Sundarbans. Considering the present rate of loss of forest land, 17% of the total mangrove cover is predicted to be lost by the year 2105 with a significant loss of fresh water loving mangroves and related ecosystem services. This paper describes a unique approach to assess future changes in species composition and future forest zonation in mangroves under the 'business as usual' scenario of climate change.

Comparison of proposed countermeasures for dilemma zone at signalized intersections based on cellular automata simulations.

PubMed

Wu, Yina; Abdel-Aty, Mohamed; Ding, Yaoxian; Jia, Bin; Shi, Qi; Yan, Xuedong

2018-07-01

The Type II dilemma zone describes the road segment to a signalized intersection where drivers have difficulties to decide either stop or go at the onset of yellow signal. Such phenomenon can result in an increased crash risk at signalized intersections. Different types of warning systems have been proposed to help drivers make decisions. Although the warning systems help to improve drivers' behavior, they also have several disadvantages such as increasing rear-end crashes or red-light running (RLR) violations. In this study, a new warning system called pavement marking with auxiliary countermeasure (PMAIC) is proposed to reduce the dilemma zone and enhance the traffic safety at signalized intersections. The proposed warning system integrates the pavement marking and flashing yellow system which can provide drivers with better suggestions about stop/go decisions based on their arriving time and speed. In order to evaluate the performance of the proposed warning system, this paper presents a cellular automata (CA) simulation study. The CA simulations are conducted for four different scenarios in total, including the typical intersection without warning system, the intersection with flashing green countermeasure, the intersection with pavement marking, and the intersection with the PMAIC warning system. Before the specific CA simulation analysis, a logistic regression model is calibrated based on field video data to predict drivers' general stop/go decisions. Also, the rules of vehicle movements in the CA models under the influence by different warning systems are proposed. The proxy indicators of rear-end crash and potential RLR violations were estimated and used to evaluate safety levels for the different scenarios. The simulation results showed that the PMAIC countermeasure consistently offered best performance to reduce rear-end crash and RLR violation. Meanwhile, the results indicate that the flashing-green countermeasure could not effectively reduce either rear

Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm.

PubMed

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-12-14

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits.

Urban Growth Modeling Using Cellular Automata with Multi-Temporal Remote Sensing Images Calibrated by the Artificial Bee Colony Optimization Algorithm

PubMed Central

Naghibi, Fereydoun; Delavar, Mahmoud Reza; Pijanowski, Bryan

2016-01-01

Cellular Automata (CA) is one of the most common techniques used to simulate the urbanization process. CA-based urban models use transition rules to deliver spatial patterns of urban growth and urban dynamics over time. Determining the optimum transition rules of the CA is a critical step because of the heterogeneity and nonlinearities existing among urban growth driving forces. Recently, new CA models integrated with optimization methods based on swarm intelligence algorithms were proposed to overcome this drawback. The Artificial Bee Colony (ABC) algorithm is an advanced meta-heuristic swarm intelligence-based algorithm. Here, we propose a novel CA-based urban change model that uses the ABC algorithm to extract optimum transition rules. We applied the proposed ABC-CA model to simulate future urban growth in Urmia (Iran) with multi-temporal Landsat images from 1997, 2006 and 2015. Validation of the simulation results was made through statistical methods such as overall accuracy, the figure of merit and total operating characteristics (TOC). Additionally, we calibrated the CA model by ant colony optimization (ACO) to assess the performance of our proposed model versus similar swarm intelligence algorithm methods. We showed that the overall accuracy and the figure of merit of the ABC-CA model are 90.1% and 51.7%, which are 2.9% and 8.8% higher than those of the ACO-CA model, respectively. Moreover, the allocation disagreement of the simulation results for the ABC-CA model is 9.9%, which is 2.9% less than that of the ACO-CA model. Finally, the ABC-CA model also outperforms the ACO-CA model with fewer quantity and allocation errors and slightly more hits. PMID:27983633

Solutions for correlations along the coexistence curve and at the critical point of a kagomé lattice gas with three-particle interactions

NASA Astrophysics Data System (ADS)

Barry, J. H.; Muttalib, K. A.; Tanaka, T.

2008-01-01

We consider a two-dimensional (d=2) kagomé lattice gas model with attractive three-particle interactions around each triangular face of the kagomé lattice. Exact solutions are obtained for multiparticle correlations along the liquid and vapor branches of the coexistence curve and at criticality. The correlation solutions are also determined along the continuation of the curvilinear diameter of the coexistence region into the disordered fluid region. The method generates a linear algebraic system of correlation identities with coefficients dependent only upon the interaction parameter. Using a priori knowledge of pertinent solutions for the density and elementary triplet correlation, one finds a closed and linearly independent set of correlation identities defined upon a spatially compact nine-site cluster of the kagomé lattice. Resulting exact solution curves of the correlations are plotted and discussed as functions of the temperature and are compared with corresponding results in a traditional kagomé lattice gas having nearest-neighbor pair interactions. An example of application for the multiparticle correlations is demonstrated in cavitation theory.

Myxobacteria Fruiting Body Formation

NASA Astrophysics Data System (ADS)

Jiang, Yi

2006-03-01

Myxobacteria are social bacteria that swarm and glide on surfaces, and feed cooperatively. When starved, tens of thousands of cells change their movement pattern from outward spreading to inward concentration; they form aggregates that become fruiting bodies, inside which cells differentiate into nonmotile, environmentally resistant spores. Traditionally, cell aggregation has been considered to imply chemotaxis, a long-range cell interaction mediated by diffusing chemicals. However, myxobacteria aggregation is the consequence of direct cell-contact interactions. I will review our recent efforts in modeling the fruiting body formation of Myxobacteria, using lattice gas cellular automata models that are based on local cell-cell contact signaling. These models have reproduced the individual phases in Myxobacteria development such as the rippling, streaming, early aggregation and the final sporulation; the models can be unified to simulate the whole developmental process of Myxobacteria.

Towards a Quantum Game of Life

NASA Astrophysics Data System (ADS)

Flitney, Adrian P.; Abbott, Derek

Cellular automata provide a means of obtaining complex behaviour from a simple array of cells and a deterministic transition function. They supply a method of computation that dispenses with the need for manipulation of individual cells and they are computationally universal. Classical cellular automata have proved of great interest to computer scientists but the construction of quantum cellular automata pose particular difficulties. We present a version of John Conway's famous two-dimensional classical cellular automata Life that has some quantum-like features, including interference effects. Some basic structures in the new automata are given and comparisons are made with Conway's game.

Comparison between different adsorption-desorption kinetics schemes in two dimensional lattice gas

NASA Astrophysics Data System (ADS)

Huespe, V. J.; Belardinelli, R. E.; Pereyra, V. D.; Manzi, S. J.

2017-12-01

Monte Carlo simulation is used to study the adsorption-desorption kinetics in the framework of the kinetic lattice-gas model. Three schemes of the so-called hard dynamics and five schemes of the so called soft dynamics were used for this purpose. It is observed that for the hard dynamic schemes, the equilibrium and non-equilibrium observable, such as adsorption isotherms, sticking coefficients, and thermal desorption spectra, have a normal or physical sustainable behavior. While for the soft dynamics schemes, with the exception of the transition state theory, the equilibrium and non-equilibrium observables have several problems.

Modeling the Gross-Pitaevskii Equation Using the Quantum Lattice Gas Method

NASA Astrophysics Data System (ADS)

Oganesov, Armen

We present an improved Quantum Lattice Gas (QLG) algorithm as a mesoscopic unitary perturbative representation of the mean field Gross Pitaevskii (GP) equation for Bose-Einstein Condensates (BECs). The method employs an interleaved sequence of unitary collide and stream operators. QLG is applicable to many different scalar potentials in the weak interaction regime and has been used to model the Korteweg-de Vries (KdV), Burgers and GP equations. It can be implemented on both quantum and classical computers and is extremely scalable. We present results for 1D soliton solutions with positive and negative internal interactions, as well as vector solitons with inelastic scattering. In higher dimensions we look at the behavior of vortex ring reconnection. A further improvement is considered with a proper operator splitting technique via a Fourier transformation. This is great for quantum computers since the quantum FFT is exponentially faster than its classical counterpart which involves non-local data on the entire lattice (Quantum FFT is the backbone of the Shor algorithm for quantum factorization). We also present an imaginary time method in which we transform the Schrodinger equation into a diffusion equation for recovering ground state initial conditions of a quantum system suitable for the QLG algorithm.

Highly Parallel Computing Architectures by using Arrays of Quantum-dot Cellular Automata (QCA): Opportunities, Challenges, and Recent Results

NASA Technical Reports Server (NTRS)

Fijany, Amir; Toomarian, Benny N.

2000-01-01

There has been significant improvement in the performance of VLSI devices, in terms of size, power consumption, and speed, in recent years and this trend may also continue for some near future. However, it is a well known fact that there are major obstacles, i.e., physical limitation of feature size reduction and ever increasing cost of foundry, that would prevent the long term continuation of this trend. This has motivated the exploration of some fundamentally new technologies that are not dependent on the conventional feature size approach. Such technologies are expected to enable scaling to continue to the ultimate level, i.e., molecular and atomistic size. Quantum computing, quantum dot-based computing, DNA based computing, biologically inspired computing, etc., are examples of such new technologies. In particular, quantum-dots based computing by using Quantum-dot Cellular Automata (QCA) has recently been intensely investigated as a promising new technology capable of offering significant improvement over conventional VLSI in terms of reduction of feature size (and hence increase in integration level), reduction of power consumption, and increase of switching speed. Quantum dot-based computing and memory in general and QCA specifically, are intriguing to NASA due to their high packing density (10(exp 11) - 10(exp 12) per square cm ) and low power consumption (no transfer of current) and potentially higher radiation tolerant. Under Revolutionary Computing Technology (RTC) Program at the NASA/JPL Center for Integrated Space Microelectronics (CISM), we have been investigating the potential applications of QCA for the space program. To this end, exploiting the intrinsic features of QCA, we have designed novel QCA-based circuits for co-planner (i.e., single layer) and compact implementation of a class of data permutation matrices, a class of interconnection networks, and a bit-serial processor. Building upon these circuits, we have developed novel algorithms and QCA

Lattice Boltzmann Simulation of Shale Gas Transport in Organic Nano-Pores

PubMed Central

Zhang, Xiaoling; Xiao, Lizhi; Shan, Xiaowen; Guo, Long

2014-01-01

Permeability is a key parameter for investigating the flow ability of sedimentary rocks. The conventional model for calculating permeability is derived from Darcy's law, which is valid only for continuum flow in porous rocks. We discussed the feasibility of simulating methane transport characteristics in the organic nano-pores of shale through the Lattice Boltzmann method (LBM). As a first attempt, the effects of high Knudsen number and the associated slip flow are considered, whereas the effect of adsorption in the capillary tube is left for future work. Simulation results show that at small Knudsen number, LBM results agree well with Poiseuille's law, and flow rate (flow capacity) is proportional to the square of the pore scale. At higher Knudsen numbers, the relaxation time needs to be corrected. In addition, velocity increases as the slip effect causes non negligible velocities on the pore wall, thereby enhancing the flow rate inside the pore, i.e., the permeability. Therefore, the LBM simulation of gas flow characteristics in organic nano-pores provides an effective way of evaluating the permeability of gas-bearing shale. PMID:24784022

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach-A Case Study for the City of Wuhan in China.

PubMed

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-06-15

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study-simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan.

Urban Ecological Security Simulation and Prediction Using an Improved Cellular Automata (CA) Approach—A Case Study for the City of Wuhan in China

PubMed Central

Gao, Yuan; Zhang, Chuanrong; He, Qingsong; Liu, Yaolin

2017-01-01

Ecological security is an important research topic, especially urban ecological security. As highly populated eco-systems, cities always have more fragile ecological environments. However, most of the research on urban ecological security in literature has focused on evaluating current or past status of the ecological environment. Very little literature has carried out simulation or prediction of future ecological security. In addition, there is even less literature exploring the urban ecological environment at a fine scale. To fill-in the literature gap, in this study we simulated and predicted urban ecological security at a fine scale (district level) using an improved Cellular Automata (CA) approach. First we used the pressure-state-response (PSR) method based on grid-scale data to evaluate urban ecological security. Then, based on the evaluation results, we imported the geographically weighted regression (GWR) concept into the CA model to simulate and predict urban ecological security. We applied the improved CA approach in a case study—simulating and predicting urban ecological security for the city of Wuhan in Central China. By comparing the simulated ecological security values from 2010 using the improved CA model to the actual ecological security values of 2010, we got a relatively high value of the kappa coefficient, which indicates that this CA model can simulate or predict well future development of ecological security in Wuhan. Based on the prediction results for 2020, we made some policy recommendations for each district in Wuhan. PMID:28617348

Large-scale parallel lattice Boltzmann-cellular automaton model of two-dimensional dendritic growth

NASA Astrophysics Data System (ADS)

Jelinek, Bohumir; Eshraghi, Mohsen; Felicelli, Sergio; Peters, John F.

2014-03-01

An extremely scalable lattice Boltzmann (LB)-cellular automaton (CA) model for simulations of two-dimensional (2D) dendritic solidification under forced convection is presented. The model incorporates effects of phase change, solute diffusion, melt convection, and heat transport. The LB model represents the diffusion, convection, and heat transfer phenomena. The dendrite growth is driven by a difference between actual and equilibrium liquid composition at the solid-liquid interface. The CA technique is deployed to track the new interface cells. The computer program was parallelized using the Message Passing Interface (MPI) technique. Parallel scaling of the algorithm was studied and major scalability bottlenecks were identified. Efficiency loss attributable to the high memory bandwidth requirement of the algorithm was observed when using multiple cores per processor. Parallel writing of the output variables of interest was implemented in the binary Hierarchical Data Format 5 (HDF5) to improve the output performance, and to simplify visualization. Calculations were carried out in single precision arithmetic without significant loss in accuracy, resulting in 50% reduction of memory and computational time requirements. The presented solidification model shows a very good scalability up to centimeter size domains, including more than ten million of dendrites. Catalogue identifier: AEQZ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEQZ_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, UK Licensing provisions: Standard CPC license, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 29,767 No. of bytes in distributed program, including test data, etc.: 3131,367 Distribution format: tar.gz Programming language: Fortran 90. Computer: Linux PC and clusters. Operating system: Linux. Has the code been vectorized or parallelized?: Yes. Program is parallelized using MPI

Flat (0 0 1) surfaces of II-VI semiconductors: a lattice gas model

NASA Astrophysics Data System (ADS)

Ahr, Martin; Biehl, Michael

2002-05-01

We present a two-dimensional lattice gas with anisotropic interactions which model the known properties of the surface reconstructions of CdTe and ZnSe. In contrast to an earlier publication [M. Biehl, M. Ahr, W. Kinzel, M. Sokolowski, T. Volkmann, Europhys. Lett. 53 (2001) 169] the formation of anion dimers is considered. This alters the behaviour of the model considerably. We determine the phase diagram of this model by means of transfer matrix calculations and Monte Carlo simulations. We find qualitative agreement with the results of various experimental investigations.

Noise, chaos, and (ɛ, τ)-entropy per unit time

NASA Astrophysics Data System (ADS)

Gaspard, Pierre; Wang, Xiao-Jing

1993-12-01

The degree of dynamical randomness of different time processes is characterized in terms of the (ε, τ)-entropy per unit time. The (ε, τ)-entropy is the amount of information generated per unit time, at different scales τ of time and ε of the observables. This quantity generalizes the Kolmogorov-Sinai entropy per unit time from deterministic chaotic processes, to stochastic processes such as fluctuations in mesoscopic physico-chemical phenomena or strong turbulence in macroscopic spacetime dynamics. The random processes that are characterized include chaotic systems, Bernoulli and Markov chains, Poisson and birth-and-death processes, Ornstein-Uhlenbeck and Yaglom noises, fractional Brownian motions, different regimes of hydrodynamical turbulence, and the Lorentz-Boltzmann process of nonequilibrium statistical mechanics. We also extend the (ε, τ)-entropy to spacetime processes like cellular automata, Conway's game of life, lattice gas automata, coupled maps, spacetime chaos in partial differential equations, as well as the ideal, the Lorentz, and the hard sphere gases. Through these examples it is demonstrated that the (ε, τ)-entropy provides a unified quantitative measure of dynamical randomness to both chaos and noises, and a method to detect transitions between dynamical states of different degrees of randomness as a parameter of the system is varied.

Manufacturing and Characterization of 18Ni Marage 300 Lattice Components by Selective Laser Melting.

PubMed

Contuzzi, Nicola; Campanelli, Sabina L; Casavola, Caterina; Lamberti, Luciano

2013-08-13

The spreading use of cellular structures brings the need to speed up manufacturing processes without deteriorating mechanical properties. By using Selective Laser Melting (SLM) to produce cellular structures, the designer has total freedom in defining part geometry and manufacturing is simplified. The paper investigates the suitability of Selective Laser Melting for manufacturing steel cellular lattice structures with characteristic dimensions in the micrometer range. Alternative lattice topologies including reinforcing bars in the vertical direction also are considered. The selected lattice structure topology is shown to be superior over other lattice structure designs considered in literature. Compression tests are carried out in order to evaluate mechanical strength of lattice strut specimens made via SLM. Compressive behavior of samples also is simulated by finite element analysis and numerical results are compared with experimental data in order to assess the constitutive behavior of the lattice structure designs considered in this study. Experimental data show that it is possible to build samples of relative density in the 0.2456-0.4367 range. Compressive strength changes almost linearly with respect to relative density, which in turns depends linearly on the number of vertical reinforces. Specific strength increases with cell and strut edge size. Numerical simulations confirm the plastic nature of the instability phenomena that leads the cellular structures to collapse under compression loading.

Manufacturing and Characterization of 18Ni Marage 300 Lattice Components by Selective Laser Melting

PubMed Central

Contuzzi, Nicola; Campanelli, Sabina L.; Casavola, Caterina; Lamberti, Luciano

2013-01-01

The spreading use of cellular structures brings the need to speed up manufacturing processes without deteriorating mechanical properties. By using Selective Laser Melting (SLM) to produce cellular structures, the designer has total freedom in defining part geometry and manufacturing is simplified. The paper investigates the suitability of Selective Laser Melting for manufacturing steel cellular lattice structures with characteristic dimensions in the micrometer range. Alternative lattice topologies including reinforcing bars in the vertical direction also are considered. The selected lattice structure topology is shown to be superior over other lattice structure designs considered in literature. Compression tests are carried out in order to evaluate mechanical strength of lattice strut specimens made via SLM. Compressive behavior of samples also is simulated by finite element analysis and numerical results are compared with experimental data in order to assess the constitutive behavior of the lattice structure designs considered in this study. Experimental data show that it is possible to build samples of relative density in the 0.2456–0.4367 range. Compressive strength changes almost linearly with respect to relative density, which in turns depends linearly on the number of vertical reinforces. Specific strength increases with cell and strut edge size. Numerical simulations confirm the plastic nature of the instability phenomena that leads the cellular structures to collapse under compression loading. PMID:28811445

Symbolic Computation Using Cellular Automata-Based Hyperdimensional Computing.

PubMed

Yilmaz, Ozgur

2015-12-01

This letter introduces a novel framework of reservoir computing that is capable of both connectionist machine intelligence and symbolic computation. A cellular automaton is used as the reservoir of dynamical systems. Input is randomly projected onto the initial conditions of automaton cells, and nonlinear computation is performed on the input via application of a rule in the automaton for a period of time. The evolution of the automaton creates a space-time volume of the automaton state space, and it is used as the reservoir. The proposed framework is shown to be capable of long-term memory, and it requires orders of magnitude less computation compared to echo state networks. As the focus of the letter, we suggest that binary reservoir feature vectors can be combined using Boolean operations as in hyperdimensional computing, paving a direct way for concept building and symbolic processing. To demonstrate the capability of the proposed system, we make analogies directly on image data by asking, What is the automobile of air?

Simulating Space Radiation-Induced Breast Tumor Incidence Using Automata.

PubMed

Heuskin, A C; Osseiran, A I; Tang, J; Costes, S V

2016-07-01

Estimating cancer risk from space radiation has been an ongoing challenge for decades primarily because most of the reported epidemiological data on radiation-induced risks are derived from studies of atomic bomb survivors who were exposed to an acute dose of gamma rays instead of chronic high-LET cosmic radiation. In this study, we introduce a formalism using cellular automata to model the long-term effects of ionizing radiation in human breast for different radiation qualities. We first validated and tuned parameters for an automata-based two-stage clonal expansion model simulating the age dependence of spontaneous breast cancer incidence in an unexposed U.S. We then tested the impact of radiation perturbation in the model by modifying parameters to reflect both targeted and nontargeted radiation effects. Targeted effects (TE) reflect the immediate impact of radiation on a cell's DNA with classic end points being gene mutations and cell death. They are well known and are directly derived from experimental data. In contrast, nontargeted effects (NTE) are persistent and affect both damaged and undamaged cells, are nonlinear with dose and are not well characterized in the literature. In this study, we introduced TE in our model and compared predictions against epidemiologic data of the atomic bomb survivor cohort. TE alone are not sufficient for inducing enough cancer. NTE independent of dose and lasting ∼100 days postirradiation need to be added to accurately predict dose dependence of breast cancer induced by gamma rays. Finally, by integrating experimental relative biological effectiveness (RBE) for TE and keeping NTE (i.e., radiation-induced genomic instability) constant with dose and LET, the model predicts that RBE for breast cancer induced by cosmic radiation would be maximum at 220 keV/μm. This approach lays the groundwork for further investigation into the impact of chronic low-dose exposure, inter-individual variation and more complex space radiation

Transition of a small-bipolaron gas to a Fröhlich polaron in a deformable lattice

NASA Astrophysics Data System (ADS)

Hettiarachchi, Gayan Prasad; Muhid, Mohd Nazlan Mohd; Hamdan, Halimaton

2018-04-01

The electronic properties of guest Cs atoms in a deformable lattice are investigated at various densities n . Low values of n show optical absorptions of small bipolarons. At intermediate n values, new bands appear in the midinfrared (MIR) and high-frequency regions, which coexist with the small bipolaron bands. With a further increase in n , the small bipolaron bands become less discernible and subsequently disappear, resulting in the appearance of a Drude component superimposed on a MIR sideband suggesting a phase transition to a polaronic metal. In this itinerant phase, an approximately twofold mass enhancement is observed. This continuous transition of a gas of small bipolarons to a polaronic metal characterized by a Fröhlich polaron reveals an important part of the complex phase diagram of the metal-insulator transition in a deformable lattice.

Mixed-Valence Molecular Unit for Quantum Cellular Automata: Beyond the Born-Oppenheimer Paradigm through the Symmetry-Assisted Vibronic Approach.

PubMed

Clemente-Juan, Juan Modesto; Palii, Andrew; Coronado, Eugenio; Tsukerblat, Boris

2016-08-09

In this article, we focus on the electron-vibrational problem of the tetrameric mixed-valence (MV) complexes proposed for implementation as four-dot molecular quantum cellular automata (mQCA).1 Although the adiabatic approximation explored in ref 2 is an appropriate tool for the qualitative analysis of the basic characteristics of mQCA, like vibronic trapping of the electrons encoding binary information and cell-cell response, it loses its accuracy providing moderate vibronic coupling and fails in the description of the discrete pattern of the vibronic levels. Therefore, a precise solution of the quantum-mechanical vibronic problem is of primary importance for the evaluation of the shapes of the electron transfer optical absorption bands and quantitative analysis of the main parameters of tetrameric quantum cells. Here, we go beyond the Born-Oppenheimer paradigm and present a solution of the quantum-mechanical pseudo Jahn-Teller (JT) vibronic problem in bielectronic MV species (exemplified by the tetra-ruthenium complexes) based on the recently developed symmetry-assisted approach.3,4 The mathematical approach to the vibronic eigenproblem takes into consideration the point symmetry basis, and therefore, the total matrix of the JT Hamiltonian is blocked to the maximum extent. The submatrices correspond to the irreducible representations (irreps) of the point group. With this tool, we also extend the theory of the mQCA cell beyond the limit of prevailing Coulomb repulsion in the electronic pair (adopted in ref 2), and therefore, the general pseudo-JT problems for spin-singlet ((1)B1g, 2(1)A1g, (1)B2g, (1)Eu) ⊗ (b1g + eu) and spin-triplet states ((3)A2g, (3)B1g, 2(3)Eu) ⊗ (b1g + eu) in a square-planar bielectronic system are solved. The obtained symmetry-adapted electron-vibrational functions are employed for the calculation of the profiles (shape functions) of the charge transfer absorption bands in the tetrameric MV complexes and for the discussion of the

Dynamic behaviors of liquid droplets on a gas diffusion layer surface: Hybrid lattice Boltzmann investigation

NASA Astrophysics Data System (ADS)

Wu, Jie; Huang, Jun-Jie

2015-07-01

Water management is one of the key issues in proton exchange membrane fuel cells. Fundamentally, it is related to dynamic behaviors of droplets on a gas diffusion layer (GDL) surface, and consequently they are investigated in this work. A two-dimensional hybrid method is employed to implement numerical simulations, in which the flow field is solved by using the lattice Boltzmann method and the interface between droplet and gas is captured by solving the Cahn-Hilliard equation directly. One or two liquid droplets are initially placed on the GDL surface of a gas channel, which is driven by the fully developed Poiseuille flow. At a fixed channel size, the effects of viscosity ratio of droplet to gas ( μ ∗ ), Capillary number (Ca, ratio of gas viscosity to surface tension), and droplet interaction on the dynamic behaviors of droplets are systematically studied. By decreasing viscosity ratio or increasing Capillary number, the single droplet can detach from the GDL surface easily. On the other hand, when two identical droplets stay close to each other or a larger droplet is placed in front of a smaller droplet, the removal of two droplets is promoted.

Diffusion reordering kinetics in lattice-gas systems: Time evolution of configurational entropy and internal energy

NASA Astrophysics Data System (ADS)

Weinketz, Sieghard

1998-07-01

The reordering kinetics of a diffusion lattice-gas system of adsorbates with nearest- and next-nearest-neighbor interactions on a square lattice is studied within a dynamic Monte Carlo simulation, as it evolves towards the equilibrium from a given initial configuration, at a constant temperature. The diffusion kinetics proceeds through adsorbate hoppings to empty nearest-neighboring sites (Kawasaki dynamics). The Monte Carlo procedure allows a ``real'' time definition from the local transition rates, and the configurational entropy and internal energy can be obtained from the lattice configuration at any instant t by counting the local clusters and using the C2 approximation of the cluster variation method. These state functions are then used in their nonequilibrium form as a direct measure of reordering along the time. Different reordering processes are analyzed within this approach, presenting a rich variety of behaviors. It can also be shown that the time derivative of entropy (times temperature) is always equal to or lower than the time derivative of energy, and that the reordering path is always strongly dependent on the initial order, presenting in some cases an ``invariance'' of the entropy function to the magnitude of the interactions as far as the final order is unaltered.

Perceptions of teaching and learning automata theory in a college-level computer science course

NASA Astrophysics Data System (ADS)

Weidmann, Phoebe Kay

This dissertation identifies and describes student and instructor perceptions that contribute to effective teaching and learning of Automata Theory in a competitive college-level Computer Science program. Effective teaching is the ability to create an appropriate learning environment in order to provide effective learning. We define effective learning as the ability of a student to meet instructor set learning objectives, demonstrating this by passing the course, while reporting a good learning experience. We conducted our investigation through a detailed qualitative case study of two sections (118 students) of Automata Theory (CS 341) at The University of Texas at Austin taught by Dr. Lily Quilt. Because Automata Theory has a fixed curriculum in the sense that many curricula and textbooks agree on what Automata Theory contains, differences being depth and amount of material to cover in a single course, a case study would allow for generalizable findings. Automata Theory is especially problematic in a Computer Science curriculum since students are not experienced in abstract thinking before taking this course, fail to understand the relevance of the theory, and prefer classes with more concrete activities such as programming. This creates a special challenge for any instructor of Automata Theory as motivation becomes critical for student learning. Through the use of student surveys, instructor interviews, classroom observation, material and course grade analysis we sought to understand what students perceived, what instructors expected of students, and how those perceptions played out in the classroom in terms of structure and instruction. Our goal was to create suggestions that would lead to a better designed course and thus a higher student success rate in Automata Theory. We created a unique theoretical basis, pedagogical positivism, on which to study college-level courses. Pedagogical positivism states that through examining instructor and student perceptions

Study of Gas Flow Characteristics in Tight Porous Media with a Microscale Lattice Boltzmann Model

PubMed Central

Zhao, Jianlin; Yao, Jun; Zhang, Min; Zhang, Lei; Yang, Yongfei; Sun, Hai; An, Senyou; Li, Aifen

2016-01-01

To investigate the gas flow characteristics in tight porous media, a microscale lattice Boltzmann (LB) model with the regularization procedure is firstly adopted to simulate gas flow in three-dimensional (3D) digital rocks. A shale digital rock and a sandstone digital rock are reconstructed to study the effects of pressure, temperature and pore size on microscale gas flow. The simulation results show that because of the microscale effect in tight porous media, the apparent permeability is always higher than the intrinsic permeability, and with the decrease of pressure or pore size, or with the increase of temperature, the difference between apparent permeability and intrinsic permeability increases. In addition, the Knudsen numbers under different conditions are calculated and the results show that gas flow characteristics in the digital rocks under different Knudsen numbers are quite different. With the increase of Knudsen number, gas flow in the digital rocks becomes more uniform and the effect of heterogeneity of the porous media on gas flow decreases. Finally, two commonly used apparent permeability calculation models are evaluated by the simulation results and the Klinkenberg model shows better accuracy. In addition, a better proportionality factor in Klinkenberg model is proposed according to the simulation results. PMID:27587293

Discovering Motifs in Biological Sequences Using the Micron Automata Processor.

PubMed

Roy, Indranil; Aluru, Srinivas

2016-01-01

Finding approximately conserved sequences, called motifs, across multiple DNA or protein sequences is an important problem in computational biology. In this paper, we consider the (l, d) motif search problem of identifying one or more motifs of length l present in at least q of the n given sequences, with each occurrence differing from the motif in at most d substitutions. The problem is known to be NP-complete, and the largest solved instance reported to date is (26,11). We propose a novel algorithm for the (l,d) motif search problem using streaming execution over a large set of non-deterministic finite automata (NFA). This solution is designed to take advantage of the micron automata processor, a new technology close to deployment that can simultaneously execute multiple NFA in parallel. We demonstrate the capability for solving much larger instances of the (l, d) motif search problem using the resources available within a single automata processor board, by estimating run-times for problem instances (39,18) and (40,17). The paper serves as a useful guide to solving problems using this new accelerator technology.

Efficient Deterministic Finite Automata Minimization Based on Backward Depth Information.

PubMed

Liu, Desheng; Huang, Zhiping; Zhang, Yimeng; Guo, Xiaojun; Su, Shaojing

2016-01-01

Obtaining a minimal automaton is a fundamental issue in the theory and practical implementation of deterministic finite automatons (DFAs). A minimization algorithm is presented in this paper that consists of two main phases. In the first phase, the backward depth information is built, and the state set of the DFA is partitioned into many blocks. In the second phase, the state set is refined using a hash table. The minimization algorithm has a lower time complexity O(n) than a naive comparison of transitions O(n2). Few states need to be refined by the hash table, because most states have been partitioned by the backward depth information in the coarse partition. This method achieves greater generality than previous methods because building the backward depth information is independent of the topological complexity of the DFA. The proposed algorithm can be applied not only to the minimization of acyclic automata or simple cyclic automata, but also to automata with high topological complexity. Overall, the proposal has three advantages: lower time complexity, greater generality, and scalability. A comparison to Hopcroft's algorithm demonstrates experimentally that the algorithm runs faster than traditional algorithms.

Efficient Deterministic Finite Automata Minimization Based on Backward Depth Information

PubMed Central

Liu, Desheng; Huang, Zhiping; Zhang, Yimeng; Guo, Xiaojun; Su, Shaojing

2016-01-01

Obtaining a minimal automaton is a fundamental issue in the theory and practical implementation of deterministic finite automatons (DFAs). A minimization algorithm is presented in this paper that consists of two main phases. In the first phase, the backward depth information is built, and the state set of the DFA is partitioned into many blocks. In the second phase, the state set is refined using a hash table. The minimization algorithm has a lower time complexity O(n) than a naive comparison of transitions O(n2). Few states need to be refined by the hash table, because most states have been partitioned by the backward depth information in the coarse partition. This method achieves greater generality than previous methods because building the backward depth information is independent of the topological complexity of the DFA. The proposed algorithm can be applied not only to the minimization of acyclic automata or simple cyclic automata, but also to automata with high topological complexity. Overall, the proposal has three advantages: lower time complexity, greater generality, and scalability. A comparison to Hopcroft’s algorithm demonstrates experimentally that the algorithm runs faster than traditional algorithms. PMID:27806102

Accuracy of the lattice Boltzmann method for describing the behavior of a gas in the continuum limit.

PubMed

Kataoka, Takeshi; Tsutahara, Michihisa

2010-11-01

The accuracy of the lattice Boltzmann method (LBM) for describing the behavior of a gas in the continuum limit is systematically investigated. The asymptotic analysis for small Knudsen numbers is carried out to derive the corresponding fluid-dynamics-type equations, and the errors of the LBM are estimated by comparing them with the correct fluid-dynamics-type equations. We discuss the following three important cases: (I) the Mach number of the flow is much smaller than the Knudsen number, (II) the Mach number is of the same order as the Knudsen number, and (III) the Mach number is finite. From the von Karman relation, the above three cases correspond to the flows of (I) small Reynolds number, (II) finite Reynolds number, and (III) large Reynolds number, respectively. The analysis is made with the information only of the fundamental properties of the lattice Boltzmann models without stepping into their detailed form. The results are therefore applicable to various lattice Boltzmann models that satisfy the fundamental properties used in the analysis.

Quantum simulation in strongly correlated optical lattices

NASA Astrophysics Data System (ADS)

Mckay, David C.

My work on the 87Rb apparatus focuses on three main topics: simulating the Bose-Hubbard (BH) model out of equilibrium, developing thermometry probes, and developing impurity probes using a 3D spin-dependent lattice. Theoretical techniques (e.g., QMC) are adept at describing the equilibrium properties of the BH model, but the dynamics are unknown --- simulation is able to bridge this gap. We perform two experiments to simulate the BH model out of equilibrium. In the first experiment, published in Ref. [1], we measure the decay rate of the center-of-mass velocity for a Bose-Einstein condensate trapped in a cubic lattice. We explore this dissipation for different Bose-Hubbard parameters (corresponding to different lattice depths) and temperatures. We observe a decay rate that asymptotes to a finite value at zero temperature, which we interpret as evidence of intrinsic decay due to quantum tunneling of phase slips. The decay rate exponentially increases with temperature, which is consistent with a cross-over from quantum tunneling to thermal activation. While phase slips are a well-known dissipation mechanism in superconductors, numerous effects prevent unambiguous detection of quantum phase slips. Therefore, our measurement is among the strongest evidence for quantum tunneling of phase slips. In a second experiment, published in Ref. [2] with theory collaborators at Cornell University, we investigate condensate fraction evolution during fast (i.e., millisecond) ramps of the lattice potential depth. These ramps simulate the BH model with time-dependent parameters. We determine that interactions lead to significant condensate fraction redistribution during these ramps, in agreement with mean-field calculations. This result clarifies adiabatic timescales for the lattice gas and strongly constrains bandmapping as an equilibrium probe. Another part of this thesis work involves developing thermometry techniques for the lattice gas. These techniques are important because the

Simulation of debris flow events in Sicily by cellular automata model SCIDDICA_SS3

NASA Astrophysics Data System (ADS)

Cancelliere, A.; Lupiano, V.; Peres, D. J.; Stancanelli, L.; Avolio, M.; Foti, E.; Di Gregorio, S.

2013-12-01

Debris flow models are widely used for hazard mapping or for evaluating the effectiveness of risk mitigation measures. Several models analyze the dynamics of debris flow runout solving Partial Differential Equations. In use of such models, difficulties arise in estimating kinematic geotechnical soil parameters for real phenomena. In order to overcome such difficulties, alternative semi-empirical approaches can be employed, such as macroscopic Cellular Automata (CA). In particular, for CA simulation purposes, the runout of debris flows emerges from local interactions in a dynamical system, subdivided into elementary parts, whose state evolves within a spatial and temporal discretum. The attributes of each cell (substates) describe physical characteristics. For computational reasons, the natural phenomenon is splitted into a number of elementary processes, whose proper composition makes up the CA transition function. By simultaneously applying this function to all the cells, the evolution of the phenomenon can be simulated in terms of modifications of the substates. In this study, we present an application of the macroscopic CA semi-empirical model SCIDDICA_SS3 to the Peloritani Mountains area in Sicily island, Italy. The model was applied using detailed data from the 1 October 2009 debris flow event, which was triggered by a rainfall event of about 250 mm falling in 9 hours, that caused the death of 37 persons. This region is characterized by river valleys with large hillslope angles (30°-60°), catchment basins of small extensions (0.5-12 km2) and soil composed by metamorphic material, which is easy to be eroded. CA usage implies a calibration phase, that identifies an optimal set of parameters capable of adequately play back the considered case, and a validation phase, that tests the model on a sufficient (and different) number of cases similar in terms of physical and geomorphological properties. The performance of the model can be measured in terms of a fitness

Distribution functions of probabilistic automata

NASA Technical Reports Server (NTRS)

Vatan, F.

2001-01-01

Each probabilistic automaton M over an alphabet A defines a probability measure Prob sub(M) on the set of all finite and infinite words over A. We can identify a k letter alphabet A with the set {0, 1,..., k-1}, and, hence, we can consider every finite or infinite word w over A as a radix k expansion of a real number X(w) in the interval [0, 1]. This makes X(w) a random variable and the distribution function of M is defined as usual: F(x) := Prob sub(M) { w: X(w) < x }. Utilizing the fixed-point semantics (denotational semantics), extended to probabilistic computations, we investigate the distribution functions of probabilistic automata in detail. Automata with continuous distribution functions are characterized. By a new, and much more easier method, it is shown that the distribution function F(x) is an analytic function if it is a polynomial. Finally, answering a question posed by D. Knuth and A. Yao, we show that a polynomial distribution function F(x) on [0, 1] can be generated by a prob abilistic automaton iff all the roots of F'(x) = 0 in this interval, if any, are rational numbers. For this, we define two dynamical systems on the set of polynomial distributions and study attracting fixed points of random composition of these two systems.

Microgravity and Charge Transfer in the Neuronal Membrane: Implications for Computational Neurobiology

NASA Technical Reports Server (NTRS)

Wallace, Ron

1995-01-01

Evidence from natural and artificial membranes indicates that the neural membrane is a liquid crystal. A liquid-to-gel phase transition caused by the application of superposed electromagnetic fields to the outer membrane surface releases spin-correlated electron pairs which propagate through a charge transfer complex. The propagation generates Rydberg atoms in the lipid bilayer lattice. In the present model, charge density configurations in promoted orbitals interact as cellular automata and perform computations in Hilbert space. Due to the small binding energies of promoted orbitals, their automata are highly sensitive to microgravitational perturbations. It is proposed that spacetime is classical on the Rydberg scale, but formed of contiguous moving segments, each of which displays topological equivalence. This stochasticity is reflected in randomized Riemannian tensor values. Spacetime segments interact with charge automata as components of a computational process. At the termination of the algorithm, an orbital of high probability density is embedded in a more stabilized microscopic spacetime. This state permits the opening of an ion channel and the conversion of a quantum algorithm into a macroscopic frequency code.

Mechanisms of shrub encroachment into Northern Chihuahuan Desert grasslands and impacts of climate change investigated using a cellular automata model

NASA Astrophysics Data System (ADS)

Caracciolo, Domenico; Istanbulluoglu, Erkan; Noto, Leonardo Valerio; Collins, Scott L.

2016-05-01

Arid and semiarid grasslands of southwestern North America have changed dramatically over the last 150 years as a result of woody plant encroachment. Overgrazing, reduced fire frequency, and climate change are known drivers of woody plant encroachment into grasslands. In this study, relatively simple algorithms for encroachment factors (i.e., grazing, grassland fires, and seed dispersal by grazers) are proposed and implemented in the ecohydrological Cellular-Automata Tree Grass Shrub Simulator (CATGraSS). CATGraSS is used in a 7.3 km2 rectangular domain located in central New Mexico along a zone of grassland to shrubland transition, where shrub encroachment is currently active. CATGraSS is calibrated and used to investigate the relative contributions of grazing, fire frequency, seed dispersal by herbivores and climate change on shrub abundance over a 150-year period of historical shrub encroachment. The impact of future climate change is examined using a model output that realistically represents current vegetation cover as initial condition, in a series of stochastic CATGraSS future climate simulations. Model simulations are found to be highly sensitive to the initial distribution of shrub cover. Encroachment factors more actively lead to shrub propagation within the domain when the model starts with randomly distributed individual shrubs. However, when shrubs are naturally evolved into clusters, the model response to encroachment factors is muted unless the effect of seed dispersal by herbivores is amplified. The relative contribution of different drivers on modeled shrub encroachment varied based on the initial shrub cover condition used in the model. When historical weather data is used, CATGraSS predicted loss of shrub and grass cover during the 1950 s drought. While future climate change is found to amplify shrub encroachment (∼13% more shrub cover by 2100), grazing remains the dominant factor promoting shrub encroachment. When we modeled future climate

Layer Anti-Ferromagnetism on Bilayer Honeycomb Lattice

PubMed Central

Tao, Hong-Shuai; Chen, Yao-Hua; Lin, Heng-Fu; Liu, Hai-Di; Liu, Wu-Ming

2014-01-01

Bilayer honeycomb lattice, with inter-layer tunneling energy, has a parabolic dispersion relation, and the inter-layer hopping can cause the charge imbalance between two sublattices. Here, we investigate the metal-insulator and magnetic phase transitions on the strongly correlated bilayer honeycomb lattice by cellular dynamical mean-field theory combined with continuous time quantum Monte Carlo method. The procedures of magnetic spontaneous symmetry breaking on dimer and non-dimer sites are different, causing a novel phase transition between normal anti-ferromagnet and layer anti-ferromagnet. The whole phase diagrams about the magnetism, temperature, interaction and inter-layer hopping are obtained. Finally, we propose an experimental protocol to observe these phenomena in future optical lattice experiments. PMID:24947369

Lattice Boltzmann accelerated direct simulation Monte Carlo for dilute gas flow simulations.

PubMed

Di Staso, G; Clercx, H J H; Succi, S; Toschi, F

2016-11-13

Hybrid particle-continuum computational frameworks permit the simulation of gas flows by locally adjusting the resolution to the degree of non-equilibrium displayed by the flow in different regions of space and time. In this work, we present a new scheme that couples the direct simulation Monte Carlo (DSMC) with the lattice Boltzmann (LB) method in the limit of isothermal flows. The former handles strong non-equilibrium effects, as they typically occur in the vicinity of solid boundaries, whereas the latter is in charge of the bulk flow, where non-equilibrium can be dealt with perturbatively, i.e. according to Navier-Stokes hydrodynamics. The proposed concurrent multiscale method is applied to the dilute gas Couette flow, showing major computational gains when compared with the full DSMC scenarios. In addition, it is shown that the coupling with LB in the bulk flow can speed up the DSMC treatment of the Knudsen layer with respect to the full DSMC case. In other words, LB acts as a DSMC accelerator.This article is part of the themed issue 'Multiscale modelling at the physics-chemistry-biology interface'. © 2016 The Author(s).

Creating Clinical Fuzzy Automata with Fuzzy Arden Syntax.

PubMed

de Bruin, Jeroen S; Steltzer, Heinz; Rappelsberger, Andrea; Adlassnig, Klaus-Peter

2017-01-01

Formal constructs for fuzzy sets and fuzzy logic are incorporated into Arden Syntax version 2.9 (Fuzzy Arden Syntax). With fuzzy sets, the relationships between measured or observed data and linguistic terms are expressed as degrees of compatibility that model the unsharpness of the boundaries of linguistic terms. Propositional uncertainty due to incomplete knowledge of relationships between clinical linguistic concepts is modeled with fuzzy logic. Fuzzy Arden Syntax also supports the construction of fuzzy state monitors. The latter are defined as monitors that employ fuzzy automata to observe gradual transitions between different stages of disease. As a use case, we re-implemented FuzzyARDS, a previously published clinical monitoring system for patients suffering from acute respiratory distress syndrome (ARDS). Using the re-implementation as an example, we show how key concepts of fuzzy automata, i.e., fuzzy states and parallel fuzzy state transitions, can be implemented in Fuzzy Arden Syntax. The results showed that fuzzy state monitors can be implemented in a straightforward manner.

Solution on the Bethe lattice of a hard core athermal gas with two kinds of particles.

PubMed

Oliveira, Tiago J; Stilck, Jürgen F

2011-11-14

Athermal lattice gases of particles with first neighbor exclusion have been studied for a long time as simple models exhibiting a fluid-solid transition. At low concentration the particles occupy randomly both sublattices, but as the concentration is increased one of the sublattices is occupied preferentially. Here, we study a mixed lattice gas with excluded volume interactions only in the grand-canonical formalism with two kinds of particles: small ones, which occupy a single lattice site and large ones, which, when placed on a site, do not allow other particles to occupy its first neighbors also. We solve the model on a Bethe lattice of arbitrary coordination number q. In the parameter space defined by the activities of both particles, at low values of the activity of small particles (z(1)) we find a continuous transition from the fluid to the solid phase as the activity of large particles (z(2)) is increased. At higher values of z(1) the transition becomes discontinuous, both regimes are separated by a tricritical point. The critical line has a negative slope at z(1) = 0 and displays a minimum before reaching the tricritical point, so that a re-entrant behavior is observed for constant values of z(2) in the region of low density of small particles. The isobaric curves of the total density of particles as a function of the density or the activity of small particles show a minimum in the fluid phase. © 2011 American Institute of Physics

Game of Life on the Equal Degree Random Lattice

NASA Astrophysics Data System (ADS)

Shao, Zhi-Gang; Chen, Tao

2010-12-01

An effective matrix method is performed to build the equal degree random (EDR) lattice, and then a cellular automaton game of life on the EDR lattice is studied by Monte Carlo (MC) simulation. The standard mean field approximation (MFA) is applied, and then the density of live cells is given ρ=0.37017 by MFA, which is consistent with the result ρ=0.37±0.003 by MC simulation.

Effect of lattice defects on Hele-Shaw flow over an etched lattice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Decker, E.L.; Ignes-Mullol, J.; Baratt, A.

We examine the patterns formed by injecting nitrogen gas into the center of a horizontal, radial Hele-Shaw cell filled with paraffin oil. We use smooth plates and etched plates with lattices having different amounts of defects (0{endash}10&hthinsp;{percent}). In all cases, a quantitative measure of the pattern ramification shows a regular trend with injection rate and cell gap, such that the dimensionless perimeter scales with the dimensionless time. By adding defects to the lattice, we observe increased branching in the pattern morphologies. However, even in this case, the scaling behavior persists. Only the prefactor of the scaling function shows a dependencemore » on the defect density. For different lattice defect densities, we examine the nature of the different morphology phases. {copyright} {ital 1999} {ital The American Physical Society}« less

Towards implementation of cellular automata in Microbial Fuel Cells.

PubMed

Tsompanas, Michail-Antisthenis I; Adamatzky, Andrew; Sirakoulis, Georgios Ch; Greenman, John; Ieropoulos, Ioannis

2017-01-01

The Microbial Fuel Cell (MFC) is a bio-electrochemical transducer converting waste products into electricity using microbial communities. Cellular Automaton (CA) is a uniform array of finite-state machines that update their states in discrete time depending on states of their closest neighbors by the same rule. Arrays of MFCs could, in principle, act as massive-parallel computing devices with local connectivity between elementary processors. We provide a theoretical design of such a parallel processor by implementing CA in MFCs. We have chosen Conway's Game of Life as the 'benchmark' CA because this is the most popular CA which also exhibits an enormously rich spectrum of patterns. Each cell of the Game of Life CA is realized using two MFCs. The MFCs are linked electrically and hydraulically. The model is verified via simulation of an electrical circuit demonstrating equivalent behaviours. The design is a first step towards future implementations of fully autonomous biological computing devices with massive parallelism. The energy independence of such devices counteracts their somewhat slow transitions-compared to silicon circuitry-between the different states during computation.

Towards implementation of cellular automata in Microbial Fuel Cells

PubMed Central

Adamatzky, Andrew; Sirakoulis, Georgios Ch.; Greenman, John; Ieropoulos, Ioannis

2017-01-01

The Microbial Fuel Cell (MFC) is a bio-electrochemical transducer converting waste products into electricity using microbial communities. Cellular Automaton (CA) is a uniform array of finite-state machines that update their states in discrete time depending on states of their closest neighbors by the same rule. Arrays of MFCs could, in principle, act as massive-parallel computing devices with local connectivity between elementary processors. We provide a theoretical design of such a parallel processor by implementing CA in MFCs. We have chosen Conway’s Game of Life as the ‘benchmark’ CA because this is the most popular CA which also exhibits an enormously rich spectrum of patterns. Each cell of the Game of Life CA is realized using two MFCs. The MFCs are linked electrically and hydraulically. The model is verified via simulation of an electrical circuit demonstrating equivalent behaviours. The design is a first step towards future implementations of fully autonomous biological computing devices with massive parallelism. The energy independence of such devices counteracts their somewhat slow transitions—compared to silicon circuitry—between the different states during computation. PMID:28498871

Classifying elementary cellular automata using compressibility, diversity and sensitivity measures

NASA Astrophysics Data System (ADS)

Ninagawa, Shigeru; Adamatzky, Andrew

2014-10-01

An elementary cellular automaton (ECA) is a one-dimensional, synchronous, binary automaton, where each cell update depends on its own state and states of its two closest neighbors. We attempt to uncover correlations between the following measures of ECA behavior: compressibility, sensitivity and diversity. The compressibility of ECA configurations is calculated using the Lempel-Ziv (LZ) compression algorithm LZ78. The sensitivity of ECA rules to initial conditions and perturbations is evaluated using Derrida coefficients. The generative morphological diversity shows how many different neighborhood states are produced from a single nonquiescent cell. We found no significant correlation between sensitivity and compressibility. There is a substantial correlation between generative diversity and compressibility. Using sensitivity, compressibility and diversity, we uncover and characterize novel groupings of rules.

Applying genetic algorithms for calibrating a hexagonal cellular automata model for the simulation of debris flows characterised by strong inertial effects

NASA Astrophysics Data System (ADS)

Iovine, G.; D'Ambrosio, D.; Di Gregorio, S.

2005-03-01

In modelling complex a-centric phenomena which evolve through local interactions within a discrete time-space, cellular automata (CA) represent a valid alternative to standard solution methods based on differential equations. Flow-type phenomena (such as lava flows, pyroclastic flows, earth flows, and debris flows) can be viewed as a-centric dynamical systems, and they can therefore be properly investigated in CA terms. SCIDDICA S 4a is the last release of a two-dimensional hexagonal CA model for simulating debris flows characterised by strong inertial effects. S 4a has been obtained by progressively enriching an initial simplified model, originally derived for simulating very simple cases of slow-moving flow-type landslides. Using an empirical strategy, in S 4a, the inertial character of the flowing mass is translated into CA terms by means of local rules. In particular, in the transition function of the model, the distribution of landslide debris among the cells is obtained through a double cycle of computation. In the first phase, the inertial character of the landslide debris is taken into account by considering indicators of momentum. In the second phase, any remaining debris in the central cell is distributed among the adjacent cells, according to the principle of maximum possible equilibrium. The complexities of the model and of the phenomena to be simulated suggested the need for an automated technique of evaluation for the determination of the best set of global parameters. Accordingly, the model is calibrated using a genetic algorithm and by considering the May 1998 Curti-Sarno (Southern Italy) debris flow. The boundaries of the area affected by the debris flow are simulated well with the model. Errors computed by comparing the simulations with the mapped areal extent of the actual landslide are smaller than those previously obtained without genetic algorithms. As the experiments have been realised in a sequential computing environment, they could be

Automata network models of galaxy evolution

NASA Technical Reports Server (NTRS)

Chappell, David; Scalo, John

1993-01-01

Two ideas appear frequently in theories of star formation and galaxy evolution: (1) star formation is nonlocally excitatory, stimulating star formation in neighboring regions by propagation of a dense fragmenting shell or the compression of preexisting clouds; and (2) star formation is nonlocally inhibitory, making H2 regions and explosions which can create low-density and/or high temperature regions and increase the macroscopic velocity dispersion of the cloudy gas. Since it is not possible, given the present state of hydrodynamic modeling, to estimate whether one of these effects greatly dominates the other, it is of interest to investigate the predicted spatial pattern of star formation and its temporal behavior in simple models which incorporate both effects in a controlled manner. The present work presents preliminary results of such a study which is based on lattice galaxy models with various types of nonlocal inhibitory and excitatory couplings of the local SFR to the gas density, temperature, and velocity field meant to model a number of theoretical suggestions.

Ultrasonic Characteristics and Cellular Properties of Anabaena Gas Vesicles.

PubMed

Yang, Yaoheng; Qiu, Zhihai; Hou, Xuandi; Sun, Lei

2017-12-01

Ultrasound imaging is a common modality in clinical examination and biomedical research, but has not played a significant role in molecular imaging for lack of an appropriate contrast agent. Recently, biogenic gas vesicles (GVs), naturally formed by cyanobacteria and haloarchaea, have exhibited great potential as an ultrasound molecular imaging probe with a much smaller size (∼100 nm) and improved imaging contrast. However, the basic acoustic and biological properties of GVs remain unclear, which hinders future application. Here, we studied the fundamental acoustic properties of a rod-shaped gas vesicle from Anabaena, a kind of cyanobacterium, including attenuation, oscillation resonance, and scattering, as well as biological behaviors (cellular internalization and cytotoxicity). We found that GVs have two resonance peaks (85 and 120 MHz). We also observed a significant non-linear effect and its pressure dependence as well. Ultrasound B-mode imaging reveals sufficient echogenicity of GVs for ultrasound imaging enhancement at high frequencies. Biological characterization also reveals endocytosis and non-toxicity. Copyright © 2017 World Federation for Ultrasound in Medicine and Biology. Published by Elsevier Inc. All rights reserved.

A Semi-quantum Version of the Game of Life

NASA Astrophysics Data System (ADS)

Flitney, Adrian P.; Abbott, Derek

The following sections are included: * Background and Motivation * Classical cellular automata * Conway's game of life * Quantum cellular automata * Semi-quantum Life * The idea * A first model * A semi-quantum model * Discussion * Summary * References

Generic Transport Mechanisms for Molecular Traffic in Cellular Protrusions

NASA Astrophysics Data System (ADS)

Graf, Isabella R.; Frey, Erwin

2017-03-01

Transport of molecular motors along protein filaments in a half-closed geometry is a common feature of biologically relevant processes in cellular protrusions. Using a lattice-gas model we study how the interplay between active and diffusive transport and mass conservation leads to localized domain walls and tip localization of the motors. We identify a mechanism for task sharing between the active motors (maintaining a gradient) and the diffusive motion (transport to the tip), which ensures that energy consumption is low and motor exchange mostly happens at the tip. These features are attributed to strong nearest-neighbor correlations that lead to a strong reduction of active currents, which we calculate analytically using an exact moment identity, and might prove useful for the understanding of correlations and active transport also in more elaborate systems.

Numerical modeling of carrier gas flow in atomic layer deposition vacuum reactor: A comparative study of lattice Boltzmann models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pan, Dongqing; Chien Jen, Tien; Li, Tao

2014-01-15

This paper characterizes the carrier gas flow in the atomic layer deposition (ALD) vacuum reactor by introducing Lattice Boltzmann Method (LBM) to the ALD simulation through a comparative study of two LBM models. Numerical models of gas flow are constructed and implemented in two-dimensional geometry based on lattice Bhatnagar–Gross–Krook (LBGK)-D2Q9 model and two-relaxation-time (TRT) model. Both incompressible and compressible scenarios are simulated and the two models are compared in the aspects of flow features, stability, and efficiency. Our simulation outcome reveals that, for our specific ALD vacuum reactor, TRT model generates better steady laminar flow features all over the domainmore » with better stability and reliability than LBGK-D2Q9 model especially when considering the compressible effects of the gas flow. The LBM-TRT is verified indirectly by comparing the numerical result with conventional continuum-based computational fluid dynamics solvers, and it shows very good agreement with these conventional methods. The velocity field of carrier gas flow through ALD vacuum reactor was characterized by LBM-TRT model finally. The flow in ALD is in a laminar steady state with velocity concentrated at the corners and around the wafer. The effects of flow fields on precursor distributions, surface absorptions, and surface reactions are discussed in detail. Steady and evenly distributed velocity field contribute to higher precursor concentration near the wafer and relatively lower particle velocities help to achieve better surface adsorption and deposition. The ALD reactor geometry needs to be considered carefully if a steady and laminar flow field around the wafer and better surface deposition are desired.« less

Slow quench dynamics of a one-dimensional Bose gas confined to an optical lattice.

PubMed

Bernier, Jean-Sébastien; Roux, Guillaume; Kollath, Corinna

2011-05-20

We analyze the effect of a linear time variation of the interaction strength on a trapped one-dimensional Bose gas confined to an optical lattice. The evolution of different observables such as the experimentally accessible on site particle distribution are studied as a function of the ramp time by using time-dependent numerical techniques. We find that the dynamics of a trapped system typically displays two regimes: For long ramp times, the dynamics is governed by density redistribution, while at short ramp times, local dynamics dominates as the evolution is identical to that of an homogeneous system. In the homogeneous limit, we also discuss the nontrivial scaling of the energy absorbed with the ramp time.

Crackling sound generation during the formation of liquid bridges: A lattice gas model

NASA Astrophysics Data System (ADS)

Almeida, Alexandre B.; Buldyrev, Sergey V.; Alencar, Adriano M.

2013-08-01

Due to abnormal mechanical instabilities, liquid bridges may form in the small airways blocking airflow. Liquid bridge ruptures during inhalation are the major cause of the crackling adventitious lung sound, which can be heard using a simple stethoscope. Recently, Vyshedskiy and colleagues (2009) [1] described and characterized a crackle sound originated during expiration. However, the mechanism and origin of the expiratory crackle are still controversial. Thus, in this paper, we propose a mechanism for expiratory crackles. We hypothesize that the expiratory crackle sound is a result of the energy released in the form of acoustic waves during the formation of the liquid bridge. The magnitude of the energy released is proportional to the difference in free energy prior and after the bridge formation. We use a lattice gas model to describe the liquid bridge formation between two parallel planes. Specifically, we determine the surface free energy and the conditions of the liquid bridge formation between two parallel planes separated by a distance 2h by a liquid droplet of volume Ω and contact angle Θ, using both Monte Carlo simulation of a lattice gas model and variational calculus based on minimization of the surface area with the volume and the contact angle constrained. We numerically and analytically determine the phase diagram of the system as a function of the dimensionless parameter hΩ and Θ. We can distinguish two different phases: one droplet and one liquid bridge. We observe a hysteresis curve for the energy changes between these two states, and a finite size effect in the bridge formation. We compute the release of free energy during the formation of the liquid bridge and discuss the results in terms of system size. We also calculate the force exerted from liquid bridge on the planes by studying the dependence of the free energy on the separation between the planes 2h. The simulation results are in agreement with the analytical solution.

Ballistic magnetotransport in a suspended two-dimensional electron gas with periodic antidot lattices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhdanov, E. Yu., E-mail: zhdanov@isp.nsc.ru; Pogosov, A. G.; Budantsev, M. V.

2017-01-15

The magnetoresistance of suspended semiconductor nanostructures with a two-dimensional electron gas structured by periodic square antidot lattices is studied. It is shown that the ballistic regime of electron transport is retained after detaching the sample from the substrate. Direct comparative analysis of commensurability oscillations of magnetoresistance and their temperature dependences in samples before and after suspension is performed. It is found that the temperature dependences are almost identical for non-suspended and suspended samples, whereas significant differences are observed in the nonlinear regime, caused by direct current passage. Commensurability oscillations in the suspended samples are more stable with respect to exposuremore » to direct current, which can be presumably explained by electron–electron interaction enhancement after detaching nanostructures from the high-permittivity substrate.« less

Simulating Flaring Events via an Intelligent Cellular Automata Mechanism

NASA Astrophysics Data System (ADS)

Dimitropoulou, M.; Vlahos, L.; Isliker, H.; Georgoulis, M.

2010-07-01

We simulate flaring events through a Cellular Automaton (CA) model, in which, for the first time, we use observed vector magnetograms as initial conditions. After non-linear force free extrapolation of the magnetic field from the vector magnetograms, we identify magnetic discontinuities, using two alternative criteria: (1) the average magnetic field gradient, or (2) the normalized magnetic field curl (i.e. the current). Magnetic discontinuities are identified at the grid-sites where the magnetic field gradient or curl exceeds a specified threshold. We then relax the magnetic discontinuities according to the rules of Lu and Hamilton (1991) or Lu et al. (1993), i.e. we redistribute the magnetic field locally so that the discontinuities disappear. In order to simulate the flaring events, we consider several alternative scenarios with regard to: (1) The threshold above which magnetic discontinuities are identified (applying low, high, and height-dependent threshold values); (2) The driving process that occasionally causes new discontinuities (at randomly chosen grid sites, magnetic field increments are added that are perpendicular (or may-be also parallel) to the existing magnetic field). We address the question whether the coronal active region magnetic fields can indeed be considered to be in the state of self-organized criticality (SOC).

Cellular Automata for Spatiotemporal Pattern Formation from Reaction-Diffusion Partial Differential Equations

NASA Astrophysics Data System (ADS)

Ohmori, Shousuke; Yamazaki, Yoshihiro

2016-01-01

Ultradiscrete equations are derived from a set of reaction-diffusion partial differential equations, and cellular automaton rules are obtained on the basis of the ultradiscrete equations. Some rules reproduce the dynamical properties of the original reaction-diffusion equations, namely, bistability and pulse annihilation. Furthermore, other rules bring about soliton-like preservation and periodic pulse generation with a pacemaker, which are not obtained from the original reaction-diffusion equations.

Probabilistic arithmetic automata and their applications.

PubMed

Marschall, Tobias; Herms, Inke; Kaltenbach, Hans-Michael; Rahmann, Sven

2012-01-01

We present a comprehensive review on probabilistic arithmetic automata (PAAs), a general model to describe chains of operations whose operands depend on chance, along with two algorithms to numerically compute the distribution of the results of such probabilistic calculations. PAAs provide a unifying framework to approach many problems arising in computational biology and elsewhere. We present five different applications, namely 1) pattern matching statistics on random texts, including the computation of the distribution of occurrence counts, waiting times, and clump sizes under hidden Markov background models; 2) exact analysis of window-based pattern matching algorithms; 3) sensitivity of filtration seeds used to detect candidate sequence alignments; 4) length and mass statistics of peptide fragments resulting from enzymatic cleavage reactions; and 5) read length statistics of 454 and IonTorrent sequencing reads. The diversity of these applications indicates the flexibility and unifying character of the presented framework. While the construction of a PAA depends on the particular application, we single out a frequently applicable construction method: We introduce deterministic arithmetic automata (DAAs) to model deterministic calculations on sequences, and demonstrate how to construct a PAA from a given DAA and a finite-memory random text model. This procedure is used for all five discussed applications and greatly simplifies the construction of PAAs. Implementations are available as part of the MoSDi package. Its application programming interface facilitates the rapid development of new applications based on the PAA framework.

Cellular neural network-based hybrid approach toward automatic image registration

NASA Astrophysics Data System (ADS)

Arun, Pattathal VijayaKumar; Katiyar, Sunil Kumar

2013-01-01

Image registration is a key component of various image processing operations that involve the analysis of different image data sets. Automatic image registration domains have witnessed the application of many intelligent methodologies over the past decade; however, inability to properly model object shape as well as contextual information has limited the attainable accuracy. A framework for accurate feature shape modeling and adaptive resampling using advanced techniques such as vector machines, cellular neural network (CNN), scale invariant feature transform (SIFT), coreset, and cellular automata is proposed. CNN has been found to be effective in improving feature matching as well as resampling stages of registration and complexity of the approach has been considerably reduced using coreset optimization. The salient features of this work are cellular neural network approach-based SIFT feature point optimization, adaptive resampling, and intelligent object modelling. Developed methodology has been compared with contemporary methods using different statistical measures. Investigations over various satellite images revealed that considerable success was achieved with the approach. This system has dynamically used spectral and spatial information for representing contextual knowledge using CNN-prolog approach. This methodology is also illustrated to be effective in providing intelligent interpretation and adaptive resampling.

Regulation Effects by Programmed Molecules for Transcription-Based Diagnostic Automata towards Therapeutic Use

NASA Astrophysics Data System (ADS)

Hirabayashi, Miki; Ohashi, Hirotada; Kubo, Tai

We have presented experimental analysis on the controllability of our transcription-based diagnostic biomolecular automata by programmed molecules. Focusing on the noninvasive transcriptome diagnosis by salivary mRNAs, we already proposed the novel concept of diagnostic device using DNA computation. This system consists of the main computational element which has a stem shaped promoter region and a pseudo-loop shaped read-only memory region for transcription regulation through the conformation change caused by the recognition of disease-related biomarkers. We utilize the transcription of malachite green aptamer sequence triggered by the target recognition for observation of detection. This algorithm makes it possible to release RNA-aptamer drugs multiply, different from the digestion-based systems by the restriction enzyme which was proposed previously, for the in-vivo use, however, the controllability of aptamer release is not enough at the previous stage. In this paper, we verified the regulation effect on aptamer transcription by programmed molecules in basic conditions towards the developm! ent of therapeutic automata. These results would bring us one step closer to the realization of new intelligent diagnostic and therapeutic automata based on molecular circuits.

Sampling from complex networks using distributed learning automata

NASA Astrophysics Data System (ADS)

Rezvanian, Alireza; Rahmati, Mohammad; Meybodi, Mohammad Reza

2014-02-01

A complex network provides a framework for modeling many real-world phenomena in the form of a network. In general, a complex network is considered as a graph of real world phenomena such as biological networks, ecological networks, technological networks, information networks and particularly social networks. Recently, major studies are reported for the characterization of social networks due to a growing trend in analysis of online social networks as dynamic complex large-scale graphs. Due to the large scale and limited access of real networks, the network model is characterized using an appropriate part of a network by sampling approaches. In this paper, a new sampling algorithm based on distributed learning automata has been proposed for sampling from complex networks. In the proposed algorithm, a set of distributed learning automata cooperate with each other in order to take appropriate samples from the given network. To investigate the performance of the proposed algorithm, several simulation experiments are conducted on well-known complex networks. Experimental results are compared with several sampling methods in terms of different measures. The experimental results demonstrate the superiority of the proposed algorithm over the others.

On the effect of quantum noise in a quantum prisoner's dilemma cellular automaton

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón

2017-06-01

The disrupting effect of quantum noise on the dynamics of a spatial quantum formulation of the iterated prisoner's dilemma game with variable entangling is studied in this work. The game is played in the cellular automata manner, i.e., with local and synchronous interaction. It is concluded in this article that quantum noise induces in fair games the need for higher entanglement in order to make possible the emergence of the strategy pair ( Q, Q), which produces the same payoff of mutual cooperation. In unfair quantum versus classic player games, quantum noise delays the prevalence of the quantum player.

Stochastic computing with biomolecular automata

PubMed Central

Adar, Rivka; Benenson, Yaakov; Linshiz, Gregory; Rosner, Amit; Tishby, Naftali; Shapiro, Ehud

2004-01-01

Stochastic computing has a broad range of applications, yet electronic computers realize its basic step, stochastic choice between alternative computation paths, in a cumbersome way. Biomolecular computers use a different computational paradigm and hence afford novel designs. We constructed a stochastic molecular automaton in which stochastic choice is realized by means of competition between alternative biochemical pathways, and choice probabilities are programmed by the relative molar concentrations of the software molecules coding for the alternatives. Programmable and autonomous stochastic molecular automata have been shown to perform direct analysis of disease-related molecular indicators in vitro and may have the potential to provide in situ medical diagnosis and cure. PMID:15215499

Fluctuating ideal-gas lattice Boltzmann method with fluctuation dissipation theorem for nonvanishing velocities.

PubMed

Kaehler, G; Wagner, A J

2013-06-01

Current implementations of fluctuating ideal-gas descriptions with the lattice Boltzmann methods are based on a fluctuation dissipation theorem, which, while greatly simplifying the implementation, strictly holds only for zero mean velocity and small fluctuations. We show how to derive the fluctuation dissipation theorem for all k, which was done only for k=0 in previous derivations. The consistent derivation requires, in principle, locally velocity-dependent multirelaxation time transforms. Such an implementation is computationally prohibitively expensive but, with a small computational trick, it is feasible to reproduce the correct FDT without overhead in computation time. It is then shown that the previous standard implementations perform poorly for non vanishing mean velocity as indicated by violations of Galilean invariance of measured structure factors. Results obtained with the method introduced here show a significant reduction of the Galilean invariance violations.

Evaporative cooling in a compensated optical lattice

NASA Astrophysics Data System (ADS)

Duarte, P. M.; Hart, R.; Yang, T. L.; Liu, X.; Hulet, R. G.

2014-03-01

We present experimental results of evaporative cooling in a three-dimensional, red-detuned optical lattice. The lattice is compensated by the addition of three blue-detuned gaussian beams which overlap each of the lattice laser beams, but are not retro-reflected. The intensity of the compensating beams can be used to control the difference between the chemical potential in the lattice and the threshold for evaporation. We start with a two spin component degenerate Fermi gas of 6Li atoms at a temperature < 0 . 05TF in a dimple potential, which is obtained by rotating the polarization of the lattice retro beams to prevent the formation of standing waves. The temperature of the cloud is measured by releasing it from the dimple and fitting the momentum distribution to a Thomas-Fermi profile. We perform round-trip measurements into, and out of the lattice to study the adiabaticity of the loading as well as the effect of the compensating beams. Using the compensated lattice potential, we have reached temperatures low enough to produce antiferromagnetic spin correlations, which we detect via Bragg scattering of light. Supported by NSF, ONR, DARPA/ARO, and the Welch Foundation.

Phase separation and the formation of cellular bodies

NASA Astrophysics Data System (ADS)

Xu, Bin; Broedersz, Chase P.; Meir, Yigal; Wingreen, Ned S.

Cellular bodies in eukaryotic cells spontaneously assemble to form cellular compartments. Among other functions, these bodies carry out essential biochemical reactions. Cellular bodies form micron-sized structures, which, unlike canonical cell organelles, are not surrounded by membranes. A recent in vitro experiment has shown that phase separation of polymers in solution can explain the formation of cellular bodies. We constructed a lattice-polymer model to capture the essential mechanism leading to this phase separation. We used both analytical and numerical tools to predict the phase diagram of a system of two interacting polymers, including the concentration of each polymer type in the condensed and dilute phase.

Transfer-matrix study of a hard-square lattice gas with two kinds of particles and density anomaly

NASA Astrophysics Data System (ADS)

Oliveira, Tiago J.; Stilck, Jürgen F.

2015-09-01

Using transfer matrix and finite-size scaling methods, we study the thermodynamic behavior of a lattice gas with two kinds of particles on the square lattice. Only excluded volume interactions are considered, so that the model is athermal. Large particles exclude the site they occupy and its four first neighbors, while small particles exclude only their site. Two thermodynamic phases are found: a disordered phase where large particles occupy both sublattices with the same probability and an ordered phase where one of the two sublattices is preferentially occupied by them. The transition between these phases is continuous at small concentrations of the small particles and discontinuous at larger concentrations, both transitions are separated by a tricritical point. Estimates of the central charge suggest that the critical line is in the Ising universality class, while the tricritical point has tricritical Ising (Blume-Emery-Griffiths) exponents. The isobaric curves of the total density as functions of the fugacity of small or large particles display a minimum in the disordered phase.

Effects of lateral diffusion on morphology and dynamics of a microscopic lattice-gas model of pulsed electrodeposition.

PubMed

Frank, Stefan; Roberts, Daniel E; Rikvold, Per Arne

2005-02-08

The influence of nearest-neighbor diffusion on the decay of a metastable low-coverage phase (monolayer adsorption) in a square lattice-gas model of electrochemical metal deposition is investigated by kinetic Monte Carlo simulations. The phase-transformation dynamics are compared to the well-established Kolmogorov-Johnson-Mehl-Avrami theory. The phase transformation is accelerated by diffusion, but remains in accord with the theory for continuous nucleation up to moderate diffusion rates. At very high diffusion rates the phase-transformation kinetic shows a crossover to instantaneous nucleation. Then, the probability of medium-sized clusters is reduced in favor of large clusters. Upon reversal of the supersaturation, the adsorbate desorbs, but large clusters still tend to grow during the initial stages of desorption. Calculation of the free energy of subcritical clusters by enumeration of lattice animals yields a quasiequilibrium distribution which is in reasonable agreement with the simulation results. This is an improvement relative to classical droplet theory, which fails to describe the distributions, since the macroscopic surface tension is a bad approximation for small clusters.

Reconstruction of DNA sequences using genetic algorithms and cellular automata: towards mutation prediction?

PubMed

Mizas, Ch; Sirakoulis, G Ch; Mardiris, V; Karafyllidis, I; Glykos, N; Sandaltzopoulos, R

2008-04-01

Change of DNA sequence that fuels evolution is, to a certain extent, a deterministic process because mutagenesis does not occur in an absolutely random manner. So far, it has not been possible to decipher the rules that govern DNA sequence evolution due to the extreme complexity of the entire process. In our attempt to approach this issue we focus solely on the mechanisms of mutagenesis and deliberately disregard the role of natural selection. Hence, in this analysis, evolution refers to the accumulation of genetic alterations that originate from mutations and are transmitted through generations without being subjected to natural selection. We have developed a software tool that allows modelling of a DNA sequence as a one-dimensional cellular automaton (CA) with four states per cell which correspond to the four DNA bases, i.e. A, C, T and G. The four states are represented by numbers of the quaternary number system. Moreover, we have developed genetic algorithms (GAs) in order to determine the rules of CA evolution that simulate the DNA evolution process. Linear evolution rules were considered and square matrices were used to represent them. If DNA sequences of different evolution steps are available, our approach allows the determination of the underlying evolution rule(s). Conversely, once the evolution rules are deciphered, our tool may reconstruct the DNA sequence in any previous evolution step for which the exact sequence information was unknown. The developed tool may be used to test various parameters that could influence evolution. We describe a paradigm relying on the assumption that mutagenesis is governed by a near-neighbour-dependent mechanism. Based on the satisfactory performance of our system in the deliberately simplified example, we propose that our approach could offer a starting point for future attempts to understand the mechanisms that govern evolution. The developed software is open-source and has a user-friendly graphical input interface.

Query Monitoring and Analysis for Database Privacy - A Security Automata Model Approach.

PubMed

Kumar, Anand; Ligatti, Jay; Tu, Yi-Cheng

2015-11-01

Privacy and usage restriction issues are important when valuable data are exchanged or acquired by different organizations. Standard access control mechanisms either restrict or completely grant access to valuable data. On the other hand, data obfuscation limits the overall usability and may result in loss of total value. There are no standard policy enforcement mechanisms for data acquired through mutual and copyright agreements. In practice, many different types of policies can be enforced in protecting data privacy. Hence there is the need for an unified framework that encapsulates multiple suites of policies to protect the data. We present our vision of an architecture named security automata model (SAM) to enforce privacy-preserving policies and usage restrictions. SAM analyzes the input queries and their outputs to enforce various policies, liberating data owners from the burden of monitoring data access. SAM allows administrators to specify various policies and enforces them to monitor queries and control the data access. Our goal is to address the problems of data usage control and protection through privacy policies that can be defined, enforced, and integrated with the existing access control mechanisms using SAM. In this paper, we lay out the theoretical foundation of SAM, which is based on an automata named Mandatory Result Automata. We also discuss the major challenges of implementing SAM in a real-world database environment as well as ideas to meet such challenges.

An improved cellular automata model for train operation simulation with dynamic acceleration

NASA Astrophysics Data System (ADS)

Li, Wen-Jun; Nie, Lei

2018-03-01

Urban rail transit plays an important role in the urban public traffic because of its advantages of fast speed, large transport capacity, high safety, reliability and low pollution. This study proposes an improved cellular automaton (CA) model by considering the dynamic characteristic of the train acceleration to analyze the energy consumption and train running time. Constructing an effective model for calculating energy consumption to aid train operation improvement is the basis for studying and analyzing energy-saving measures for urban rail transit system operation.

Cluster properties of the one-dimensional lattice gas: the microscopic meaning of grand potential.

PubMed

Fronczak, Agata

2013-02-01

Using a concrete example, we demonstrate how the combinatorial approach to a general system of particles, which was introduced in detail in an earlier paper [Fronczak, Phys. Rev. E 86, 041139 (2012)], works and where this approach provides a genuine extension of results obtained through more traditional methods of statistical mechanics. We study the cluster properties of a one-dimensional lattice gas with nearest-neighbor interactions. Three cases (the infinite temperature limit, the range of finite temperatures, and the zero temperature limit) are discussed separately, yielding interesting results and providing alternative proof of known results. In particular, the closed-form expression for the grand partition function in the zero temperature limit is obtained, which results in the nonanalytic behavior of the grand potential, in accordance with the Yang-Lee theory.

IGF-II and IGFBP-6 regulate cellular contractility and proliferation in Dupuytren's disease.

PubMed

Raykha, Christina; Crawford, Justin; Gan, Bing Siang; Fu, Ping; Bach, Leon A; O'Gorman, David B

2013-10-01

Dupuytren's disease (DD) is a common and heritable fibrosis of the palmar fascia that typically manifests as permanent finger contractures. The molecular interactions that induce the development of hyper-contractile fibroblasts, or myofibroblasts, in DD are poorly understood. We have identified IGF2 and IGFBP6, encoding insulin-like growth factor (IGF)-II and IGF binding protein (IGFBP)-6 respectively, as reciprocally dysregulated genes and proteins in primary cells derived from contracture tissues (DD cells). Recombinant IGFBP-6 inhibited the proliferation of DD cells, patient-matched control (PF) cells and normal palmar fascia (CT) cells. Co-treatments with IGF-II, a high affinity IGFBP-6 ligand, were unable to rescue these effects. A non-IGF-II binding analog of IGFBP-6 also inhibited cellular proliferation, implicating IGF-II-independent roles for IGFBP-6 in this process. IGF-II enhanced the proliferation of CT cells, but not DD or PF cells, and significantly enhanced DD and PF cell contractility in stressed collagen lattices. While IGFBP-6 treatment did not affect cellular contractility, it abrogated the IGF-II-induced contractility of DD and PF cells in stressed collagen lattices. IGF-II also significantly increased the contraction of DD cells in relaxed lattices, however this effect was not evident in relaxed collagen lattices containing PF cells. The disparate effects of IGF-II on DD and PF cells in relaxed and stressed contraction models suggest that IGF-II can enhance lattice contractility through more than one mechanism. This is the first report to implicate IGFBP-6 as a suppressor of cellular proliferation and IGF-II as an inducer of cellular contractility in this connective tissue disease. Copyright © 2013 The Authors. Published by Elsevier B.V. All rights reserved.

Lattice distortion in hcp rare gas solids

NASA Astrophysics Data System (ADS)

Grechnev, A.; Tretyak, S. M.; Freiman, Yu. A.

2010-04-01

The lattice distortion parameter δ ≡c/a-√8/3 has been calculated as a function of molar volume for the hcp phases of He, Ar, Kr, and Xe. Results from both semi-empirical potentials and density functional theory are presented. Our study shows that δ is negative for helium in the entire pressure range. For Ar, Kr, and Xe δ changes sign from negative to positive as the pressure increases, growing rapidly in magnitude at higher pressures.

A High-Performance Cellular Automaton Model of Tumor Growth with Dynamically Growing Domains

PubMed Central

Poleszczuk, Jan; Enderling, Heiko

2014-01-01

Tumor growth from a single transformed cancer cell up to a clinically apparent mass spans many spatial and temporal orders of magnitude. Implementation of cellular automata simulations of such tumor growth can be straightforward but computing performance often counterbalances simplicity. Computationally convenient simulation times can be achieved by choosing appropriate data structures, memory and cell handling as well as domain setup. We propose a cellular automaton model of tumor growth with a domain that expands dynamically as the tumor population increases. We discuss memory access, data structures and implementation techniques that yield high-performance multi-scale Monte Carlo simulations of tumor growth. We discuss tumor properties that favor the proposed high-performance design and present simulation results of the tumor growth model. We estimate to which parameters the model is the most sensitive, and show that tumor volume depends on a number of parameters in a non-monotonic manner. PMID:25346862

Designing Composite Resins in the 21st Century: Ending the End Group Fallacy

DTIC Science & Technology

2015-09-30

unlimited. Network Automata • In correspondence with cellular automata , a system of differential equations describes the evolution of structures...LLNL). 11Distribution A: Approved for public release; distribution is unlimited. “State of the Art” Network Automata Example • Cure kinetics

Particle acceleration in a complex solar active region modelled by a Cellular automata model

NASA Astrophysics Data System (ADS)

Dauphin, C.; Vilmer, N.; Anastasiadis, A.

2004-12-01

The models of cellular automat allowed to reproduce successfully several statistical properties of the solar flares. We use a cellular automat model based on the concept of self-organised critical system to model the evolution of the magnetic energy released in an eruptive active area. Each burst of magnetic energy released is assimilated to a process of magnetic reconnection. We will thus generate several current layers (RCS) where the particles are accelerated by a direct electric field. We calculate the energy gain of the particles (ions and electrons) for various types of magnetic configuration. We calculate the distribution function of the kinetic energy of the particles after their interactions with a given number of RCS for each type of configurations. We show that the relative efficiency of the acceleration of the electrons and the ions depends on the selected configuration.

Topology Optimization - Engineering Contribution to Architectural Design

NASA Astrophysics Data System (ADS)

Tajs-Zielińska, Katarzyna; Bochenek, Bogdan

2017-10-01

The idea of the topology optimization is to find within a considered design domain the distribution of material that is optimal in some sense. Material, during optimization process, is redistributed and parts that are not necessary from objective point of view are removed. The result is a solid/void structure, for which an objective function is minimized. This paper presents an application of topology optimization to multi-material structures. The design domain defined by shape of a structure is divided into sub-regions, for which different materials are assigned. During design process material is relocated, but only within selected region. The proposed idea has been inspired by architectural designs like multi-material facades of buildings. The effectiveness of topology optimization is determined by proper choice of numerical optimization algorithm. This paper utilises very efficient heuristic method called Cellular Automata. Cellular Automata are mathematical, discrete idealization of a physical systems. Engineering implementation of Cellular Automata requires decomposition of the design domain into a uniform lattice of cells. It is assumed, that the interaction between cells takes place only within the neighbouring cells. The interaction is governed by simple, local update rules, which are based on heuristics or physical laws. The numerical studies show, that this method can be attractive alternative to traditional gradient-based algorithms. The proposed approach is evaluated by selected numerical examples of multi-material bridge structures, for which various material configurations are examined. The numerical studies demonstrated a significant influence the material sub-regions location on the final topologies. The influence of assumed volume fraction on final topologies for multi-material structures is also observed and discussed. The results of numerical calculations show, that this approach produces different results as compared with classical one

Lattice model for water-solute mixtures.

PubMed

Furlan, A P; Almarza, N G; Barbosa, M C

2016-10-14

A lattice model for the study of mixtures of associating liquids is proposed. Solvent and solute are modeled by adapting the associating lattice gas (ALG) model. The nature of interaction of solute/solvent is controlled by tuning the energy interactions between the patches of ALG model. We have studied three set of parameters, resulting in, hydrophilic, inert, and hydrophobic interactions. Extensive Monte Carlo simulations were carried out, and the behavior of pure components and the excess properties of the mixtures have been studied. The pure components, water (solvent) and solute, have quite similar phase diagrams, presenting gas, low density liquid, and high density liquid phases. In the case of solute, the regions of coexistence are substantially reduced when compared with both the water and the standard ALG models. A numerical procedure has been developed in order to attain series of results at constant pressure from simulations of the lattice gas model in the grand canonical ensemble. The excess properties of the mixtures, volume and enthalpy as the function of the solute fraction, have been studied for different interaction parameters of the model. Our model is able to reproduce qualitatively well the excess volume and enthalpy for different aqueous solutions. For the hydrophilic case, we show that the model is able to reproduce the excess volume and enthalpy of mixtures of small alcohols and amines. The inert case reproduces the behavior of large alcohols such as propanol, butanol, and pentanol. For the last case (hydrophobic), the excess properties reproduce the behavior of ionic liquids in aqueous solution.

Finding and defining the natural automata acting in living plants: Toward the synthetic biology for robotics and informatics in vivo.

PubMed

Kawano, Tomonori; Bouteau, François; Mancuso, Stefano

2012-11-01

The automata theory is the mathematical study of abstract machines commonly studied in the theoretical computer science and highly interdisciplinary fields that combine the natural sciences and the theoretical computer science. In the present review article, as the chemical and biological basis for natural computing or informatics, some plants, plant cells or plant-derived molecules involved in signaling are listed and classified as natural sequential machines (namely, the Mealy machines or Moore machines) or finite state automata. By defining the actions (states and transition functions) of these natural automata, the similarity between the computational data processing and plant decision-making processes became obvious. Finally, their putative roles as the parts for plant-based computing or robotic systems are discussed.

Query Monitoring and Analysis for Database Privacy - A Security Automata Model Approach

PubMed Central

Kumar, Anand; Ligatti, Jay; Tu, Yi-Cheng

2015-01-01

Privacy and usage restriction issues are important when valuable data are exchanged or acquired by different organizations. Standard access control mechanisms either restrict or completely grant access to valuable data. On the other hand, data obfuscation limits the overall usability and may result in loss of total value. There are no standard policy enforcement mechanisms for data acquired through mutual and copyright agreements. In practice, many different types of policies can be enforced in protecting data privacy. Hence there is the need for an unified framework that encapsulates multiple suites of policies to protect the data. We present our vision of an architecture named security automata model (SAM) to enforce privacy-preserving policies and usage restrictions. SAM analyzes the input queries and their outputs to enforce various policies, liberating data owners from the burden of monitoring data access. SAM allows administrators to specify various policies and enforces them to monitor queries and control the data access. Our goal is to address the problems of data usage control and protection through privacy policies that can be defined, enforced, and integrated with the existing access control mechanisms using SAM. In this paper, we lay out the theoretical foundation of SAM, which is based on an automata named Mandatory Result Automata. We also discuss the major challenges of implementing SAM in a real-world database environment as well as ideas to meet such challenges. PMID:26997936

Time-dependent perpendicular fluctuations in the driven lattice Lorentz gas

NASA Astrophysics Data System (ADS)

Leitmann, Sebastian; Schwab, Thomas; Franosch, Thomas

2018-02-01

We present results for the fluctuations of the displacement of a tracer particle on a planar lattice pulled by a step force in the presence of impenetrable, immobile obstacles. The fluctuations perpendicular to the applied force are evaluated exactly in first order of the obstacle density for arbitrarily strong pulling and all times. The complex time-dependent behavior is analyzed in terms of the diffusion coefficient, local exponent, and the non-Skellam parameter, which quantifies deviations from the dynamics on the lattice in the absence of obstacles. The non-Skellam parameter along the force is analyzed in terms of an asymptotic model and reveals a power-law growth for intermediate times.

Equivalence of interest rate models and lattice gases.

PubMed

Pirjol, Dan

2012-04-01

We consider the class of short rate interest rate models for which the short rate is proportional to the exponential of a Gaussian Markov process x(t) in the terminal measure r(t)=a(t)exp[x(t)]. These models include the Black-Derman-Toy and Black-Karasinski models in the terminal measure. We show that such interest rate models are equivalent to lattice gases with attractive two-body interaction, V(t(1),t(2))=-Cov[x(t(1)),x(t(2))]. We consider in some detail the Black-Karasinski model with x(t) as an Ornstein-Uhlenbeck process, and show that it is similar to a lattice gas model considered by Kac and Helfand, with attractive long-range two-body interactions, V(x,y)=-α(e(-γ|x-y|)-e(-γ(x+y))). An explicit solution for the model is given as a sum over the states of the lattice gas, which is used to show that the model has a phase transition similar to that found previously in the Black-Derman-Toy model in the terminal measure.

Equivalence of interest rate models and lattice gases

NASA Astrophysics Data System (ADS)

Pirjol, Dan

2012-04-01

We consider the class of short rate interest rate models for which the short rate is proportional to the exponential of a Gaussian Markov process x(t) in the terminal measure r(t)=a(t)exp[x(t)]. These models include the Black-Derman-Toy and Black-Karasinski models in the terminal measure. We show that such interest rate models are equivalent to lattice gases with attractive two-body interaction, V(t1,t2)=-Cov[x(t1),x(t2)]. We consider in some detail the Black-Karasinski model with x(t) as an Ornstein-Uhlenbeck process, and show that it is similar to a lattice gas model considered by Kac and Helfand, with attractive long-range two-body interactions, V(x,y)=-α(e-γ|x-y|-e-γ(x+y)). An explicit solution for the model is given as a sum over the states of the lattice gas, which is used to show that the model has a phase transition similar to that found previously in the Black-Derman-Toy model in the terminal measure.

Distributed learning automata-based algorithm for community detection in complex networks

NASA Astrophysics Data System (ADS)

Khomami, Mohammad Mehdi Daliri; Rezvanian, Alireza; Meybodi, Mohammad Reza

2016-03-01

Community structure is an important and universal topological property of many complex networks such as social and information networks. The detection of communities of a network is a significant technique for understanding the structure and function of networks. In this paper, we propose an algorithm based on distributed learning automata for community detection (DLACD) in complex networks. In the proposed algorithm, each vertex of network is equipped with a learning automation. According to the cooperation among network of learning automata and updating action probabilities of each automaton, the algorithm interactively tries to identify high-density local communities. The performance of the proposed algorithm is investigated through a number of simulations on popular synthetic and real networks. Experimental results in comparison with popular community detection algorithms such as walk trap, Danon greedy optimization, Fuzzy community detection, Multi-resolution community detection and label propagation demonstrated the superiority of DLACD in terms of modularity, NMI, performance, min-max-cut and coverage.

Supervisory control of (max,+) automata: extensions towards applications

NASA Astrophysics Data System (ADS)

Lahaye, Sébastien; Komenda, Jan; Boimond, Jean-Louis

2015-12-01

In this paper, supervisory control of (max,+) automata is studied. The synthesis of maximally permissive and just-in-time supervisor, as well as the synthesis of minimally permissive and just-after-time supervisor, are proposed. Results are also specialised to non-decreasing solutions, because only such supervisors can be realised in practice. The inherent issue of rationality raised recently is discussed. An illustration of concepts and results is presented through an example of a flexible manufacturing system.

Stimulus-Response Theory of Finite Automata, Technical Report No. 133.

ERIC Educational Resources Information Center

Suppes, Patrick

The central aim of this paper and its projected successors is to prove in detail that stimulus-response theory, or at least a mathematically precise version, can give an account of the learning of many phrase-structure grammars. Section 2 is concerned with standard notions of finite and probabilistic automata. An automaton is defined as a device…

Finding and defining the natural automata acting in living plants: Toward the synthetic biology for robotics and informatics in vivo

PubMed Central

Kawano, Tomonori; Bouteau, François; Mancuso, Stefano

2012-01-01

The automata theory is the mathematical study of abstract machines commonly studied in the theoretical computer science and highly interdisciplinary fields that combine the natural sciences and the theoretical computer science. In the present review article, as the chemical and biological basis for natural computing or informatics, some plants, plant cells or plant-derived molecules involved in signaling are listed and classified as natural sequential machines (namely, the Mealy machines or Moore machines) or finite state automata. By defining the actions (states and transition functions) of these natural automata, the similarity between the computational data processing and plant decision-making processes became obvious. Finally, their putative roles as the parts for plant-based computing or robotic systems are discussed. PMID:23336016

Detecting the BCS pairing amplitude via a sudden lattice ramp in a honeycomb lattice

NASA Astrophysics Data System (ADS)

Tiesinga, Eite; Nuske, Marlon; Mathey, Ludwig

2016-05-01

We determine the exact time evolution of an initial Bardeen-Cooper-Schrieffer (BCS) state of ultra-cold atoms in a hexagonal optical lattice. The dynamical evolution is triggered by ramping the lattice potential up, such that the interaction strength Uf is much larger than the hopping amplitude Jf. The quench initiates collective oscillations with frequency | Uf | /(2 π) in the momentum occupation numbers and imprints an oscillating phase with the same frequency on the order parameter Δ. The latter is not reproduced by treating the time evolution in mean-field theory. The momentum density-density or noise correlation functions oscillate at frequency | Uf | /(2 π) as well as its second harmonic. For a very deep lattice, with negligible tunneling energy, the oscillations of momentum occupation numbers are undamped. Non-zero tunneling after the quench leads to dephasing of the different momentum modes and a subsequent damping of the oscillations. This occurs even for a finite-temperature initial BCS state, but not for a non-interacting Fermi gas. We therefore propose to use this dephasing to detect a BCS state. Finally, we predict that the noise correlation functions in a honeycomb lattice will develop strong anti-correlations near the Dirac point. We acknowledge funding from the National Science Foundation.

Cellular automatons applied to gas dynamic problems

NASA Technical Reports Server (NTRS)

Long, Lyle N.; Coopersmith, Robert M.; Mclachlan, B. G.

1987-01-01

This paper compares the results of a relatively new computational fluid dynamics method, cellular automatons, with experimental data and analytical results. This technique has been shown to qualitatively predict fluidlike behavior; however, there have been few published comparisons with experiment or other theories. Comparisons are made for a one-dimensional supersonic piston problem, Stokes first problem, and the flow past a normal flat plate. These comparisons are used to assess the ability of the method to accurately model fluid dynamic behavior and to point out its limitations. Reasonable results were obtained for all three test cases, but the fundamental limitations of cellular automatons are numerous. It may be misleading, at this time, to say that cellular automatons are a computationally efficient technique. Other methods, based on continuum or kinetic theory, would also be very efficient if as little of the physics were included.

Last-position elimination-based learning automata.

PubMed

Zhang, Junqi; Wang, Cheng; Zhou, MengChu

2014-12-01

An update scheme of the state probability vector of actions is critical for learning automata (LA). The most popular is the pursuit scheme that pursues the estimated optimal action and penalizes others. This paper proposes a reverse philosophy that leads to last-position elimination-based learning automata (LELA). The action graded last in terms of the estimated performance is penalized by decreasing its state probability and is eliminated when its state probability becomes zero. All active actions, that is, actions with nonzero state probability, equally share the penalized state probability from the last-position action at each iteration. The proposed LELA is characterized by the relaxed convergence condition for the optimal action, the accelerated step size of the state probability update scheme for the estimated optimal action, and the enriched sampling for the estimated nonoptimal actions. The proof of the ϵ-optimal property for the proposed algorithm is presented. Last-position elimination is a widespread philosophy in the real world and has proved to be also helpful for the update scheme of the learning automaton via the simulations of well-known benchmark environments. In the simulations, two versions of the LELA, using different selection strategies of the last action, are compared with the classical pursuit algorithms Discretized Pursuit Reward-Inaction (DP(RI)) and Discretized Generalized Pursuit Algorithm (DGPA). Simulation results show that the proposed schemes achieve significantly faster convergence and higher accuracy than the classical ones. Specifically, the proposed schemes reduce the interval to find the best parameter for a specific environment in the classical pursuit algorithms. Thus, they can have their parameter tuning easier to perform and can save much more time when applied to a practical case. Furthermore, the convergence curves and the corresponding variance coefficient curves of the contenders are illustrated to characterize their

Quantum magnetic phase transition in square-octagon lattice.

PubMed

Bao, An; Tao, Hong-Shuai; Liu, Hai-Di; Zhang, XiaoZhong; Liu, Wu-Ming

2014-11-05

Quantum magnetic phase transition in square-octagon lattice was investigated by cellular dynamical mean field theory combining with continuous time quantum Monte Carlo algorithm. Based on the systematic calculation on the density of states, the double occupancy and the Fermi surface evolution of square-octagon lattice, we presented the phase diagrams of this splendid many particle system. The competition between the temperature and the on-site repulsive interaction in the isotropic square-octagon lattice has shown that both antiferromagnetic and paramagnetic order can be found not only in the metal phase, but also in the insulating phase. Antiferromagnetic metal phase disappeared in the phase diagram that consists of the anisotropic parameter λ and the on-site repulsive interaction U while the other phases still can be detected at T = 0.17. The results found in this work may contribute to understand well the properties of some consuming systems that have square-octagon structure, quasi square-octagon structure, such as ZnO.

Modelling robot's behaviour using finite automata

NASA Astrophysics Data System (ADS)

Janošek, Michal; Žáček, Jaroslav

2017-07-01

This paper proposes a model of a robot's behaviour described by finite automata. We split robot's knowledge into several knowledge bases which are used by the inference mechanism of the robot's expert system to make a logic deduction. Each knowledgebase is dedicated to the particular behaviour domain and the finite automaton helps us switching among these knowledge bases with the respect of actual situation. Our goal is to simplify and reduce complexity of one big knowledgebase splitting it into several pieces. The advantage of this model is that we can easily add new behaviour by adding new knowledgebase and add this behaviour into the finite automaton and define necessary states and transitions.

Digital Material Assembly by Passive Means and Modular Isotropic Lattice Extruder System

NASA Technical Reports Server (NTRS)

Gershenfeld, Neil (Inventor); Carney, Matthew Eli (Inventor); Jenett, Benjamin (Inventor)

2017-01-01

A set of machines and related systems build structures by the additive assembly of discrete parts. These digital material assemblies constrain the constituent parts to a discrete set of possible positions and orientations. In doing so, the structures exhibit many of the properties inherent in digital communication such as error correction, fault tolerance and allow the assembly of precise structures with comparatively imprecise tools. Assembly of discrete cellular lattices by a Modular Isotropic Lattice Extruder System (MILES) is implemented by pulling strings of lattice elements through a forming die that enforces geometry constraints that lock the elements into a rigid structure that can then be pushed against and extruded out of the die as an assembled, loadbearing structure.

Comparative study of the discrete velocity and lattice Boltzmann methods for rarefied gas flows through irregular channels

NASA Astrophysics Data System (ADS)

Su, Wei; Lindsay, Scott; Liu, Haihu; Wu, Lei

2017-08-01

Rooted from the gas kinetics, the lattice Boltzmann method (LBM) is a powerful tool in modeling hydrodynamics. In the past decade, it has been extended to simulate rarefied gas flows beyond the Navier-Stokes level, either by using the high-order Gauss-Hermite quadrature, or by introducing the relaxation time that is a function of the gas-wall distance. While the former method, with a limited number of discrete velocities (e.g., D2Q36), is accurate up to the early transition flow regime, the latter method (especially the multiple relaxation time (MRT) LBM), with the same discrete velocities as those used in simulating hydrodynamics (i.e., D2Q9), is accurate up to the free-molecular flow regime in the planar Poiseuille flow. This is quite astonishing in the sense that less discrete velocities are more accurate. In this paper, by solving the Bhatnagar-Gross-Krook kinetic equation accurately via the discrete velocity method, we find that the high-order Gauss-Hermite quadrature cannot describe the large variation in the velocity distribution function when the rarefaction effect is strong, but the MRT-LBM can capture the flow velocity well because it is equivalent to solving the Navier-Stokes equations with an effective shear viscosity. Since the MRT-LBM has only been validated in simple channel flows, and for complex geometries it is difficult to find the effective viscosity, it is necessary to assess its performance for the simulation of rarefied gas flows. Our numerical simulations based on the accurate discrete velocity method suggest that the accuracy of the MRT-LBM is reduced significantly in the simulation of rarefied gas flows through the rough surface and porous media. Our simulation results could serve as benchmarking cases for future development of the LBM for modeling and simulation of rarefied gas flows in complex geometries.

Comparative study of the discrete velocity and lattice Boltzmann methods for rarefied gas flows through irregular channels.

PubMed

Su, Wei; Lindsay, Scott; Liu, Haihu; Wu, Lei

2017-08-01

Rooted from the gas kinetics, the lattice Boltzmann method (LBM) is a powerful tool in modeling hydrodynamics. In the past decade, it has been extended to simulate rarefied gas flows beyond the Navier-Stokes level, either by using the high-order Gauss-Hermite quadrature, or by introducing the relaxation time that is a function of the gas-wall distance. While the former method, with a limited number of discrete velocities (e.g., D2Q36), is accurate up to the early transition flow regime, the latter method (especially the multiple relaxation time (MRT) LBM), with the same discrete velocities as those used in simulating hydrodynamics (i.e., D2Q9), is accurate up to the free-molecular flow regime in the planar Poiseuille flow. This is quite astonishing in the sense that less discrete velocities are more accurate. In this paper, by solving the Bhatnagar-Gross-Krook kinetic equation accurately via the discrete velocity method, we find that the high-order Gauss-Hermite quadrature cannot describe the large variation in the velocity distribution function when the rarefaction effect is strong, but the MRT-LBM can capture the flow velocity well because it is equivalent to solving the Navier-Stokes equations with an effective shear viscosity. Since the MRT-LBM has only been validated in simple channel flows, and for complex geometries it is difficult to find the effective viscosity, it is necessary to assess its performance for the simulation of rarefied gas flows. Our numerical simulations based on the accurate discrete velocity method suggest that the accuracy of the MRT-LBM is reduced significantly in the simulation of rarefied gas flows through the rough surface and porous media. Our simulation results could serve as benchmarking cases for future development of the LBM for modeling and simulation of rarefied gas flows in complex geometries.

Lattice surgery on the Raussendorf lattice

NASA Astrophysics Data System (ADS)

Herr, Daniel; Paler, Alexandru; Devitt, Simon J.; Nori, Franco

2018-07-01

Lattice surgery is a method to perform quantum computation fault-tolerantly by using operations on boundary qubits between different patches of the planar code. This technique allows for universal planar code computation without eliminating the intrinsic two-dimensional nearest-neighbor properties of the surface code that eases physical hardware implementations. Lattice surgery approaches to algorithmic compilation and optimization have been demonstrated to be more resource efficient for resource-intensive components of a fault-tolerant algorithm, and consequently may be preferable over braid-based logic. Lattice surgery can be extended to the Raussendorf lattice, providing a measurement-based approach to the surface code. In this paper we describe how lattice surgery can be performed on the Raussendorf lattice and therefore give a viable alternative to computation using braiding in measurement-based implementations of topological codes.

On Matrices, Automata, and Double Counting

NASA Astrophysics Data System (ADS)

Beldiceanu, Nicolas; Carlsson, Mats; Flener, Pierre; Pearson, Justin

Matrix models are ubiquitous for constraint problems. Many such problems have a matrix of variables M, with the same constraint defined by a finite-state automaton A on each row of M and a global cardinality constraint gcc on each column of M. We give two methods for deriving, by double counting, necessary conditions on the cardinality variables of the gcc constraints from the automaton A. The first method yields linear necessary conditions and simple arithmetic constraints. The second method introduces the cardinality automaton, which abstracts the overall behaviour of all the row automata and can be encoded by a set of linear constraints. We evaluate the impact of our methods on a large set of nurse rostering problem instances.

Traffic dynamics around weaving section influenced by accident: Cellular automata approach

NASA Astrophysics Data System (ADS)

Kong, Lin-Peng; Li, Xin-Gang; Lam, William H. K.

2015-07-01

The weaving section, as a typical bottleneck, is one source of vehicle conflicts and an accident-prone area. Traffic accident will block lanes and the road capacity will be reduced. Several models have been established to study the dynamics around traffic bottlenecks. However, little attention has been paid to study the complex traffic dynamics influenced by the combined effects of bottleneck and accident. This paper presents a cellular automaton model to characterize accident-induced traffic behavior around the weaving section. Some effective control measures are proposed and verified for traffic management under accident condition. The total flux as a function of inflow rates, the phase diagrams, the spatial-temporal diagrams, and the density and velocity profiles are presented to analyze the impact of accident. It was shown that the proposed control measures for weaving traffic can improve the capacity of weaving section under both normal and accident conditions; the accidents occurring on median lane in the weaving section are more inclined to cause traffic jam and reduce road capacity; the capacity of weaving section will be greatly reduced when the accident happens downstream the weaving section.

Investigation on Selective Laser Melting AlSi10Mg Cellular Lattice Strut: Molten Pool Morphology, Surface Roughness and Dimensional Accuracy

PubMed Central

Han, Xuesong; Zhu, Haihong; Nie, Xiaojia; Wang, Guoqing; Zeng, Xiaoyan

2018-01-01

AlSi10Mg inclined struts with angle of 45° were fabricated by selective laser melting (SLM) using different scanning speed and hatch spacing to gain insight into the evolution of the molten pool morphology, surface roughness, and dimensional accuracy. The results show that the average width and depth of the molten pool, the lower surface roughness and dimensional deviation decrease with the increase of scanning speed and hatch spacing. The upper surface roughness is found to be almost constant under different processing parameters. The width and depth of the molten pool on powder-supported zone are larger than that of the molten pool on the solid-supported zone, while the width changes more significantly than that of depth. However, if the scanning speed is high enough, the width and depth of the molten pool and the lower surface roughness almost keep constant as the density is still high. Therefore, high dimensional accuracy and density as well as good surface quality can be achieved simultaneously by using high scanning speed during SLMed cellular lattice strut. PMID:29518900

Lattice Boltzmann model for simulation of magnetohydrodynamics

NASA Technical Reports Server (NTRS)

Chen, Shiyi; Chen, Hudong; Martinez, Daniel; Matthaeus, William

1991-01-01

A numerical method, based on a discrete Boltzmann equation, is presented for solving the equations of magnetohydrodynamics (MHD). The algorithm provides advantages similar to the cellular automaton method in that it is local and easily adapted to parallel computing environments. Because of much lower noise levels and less stringent requirements on lattice size, the method appears to be more competitive with traditional solution methods. Examples show that the model accurately reproduces both linear and nonlinear MHD phenomena.

On Traveling Waves in Lattices: The Case of Riccati Lattices

NASA Astrophysics Data System (ADS)

Dimitrova, Zlatinka

2012-09-01

The method of simplest equation is applied for analysis of a class of lattices described by differential-difference equations that admit traveling-wave solutions constructed on the basis of the solution of the Riccati equation. We denote such lattices as Riccati lattices. We search for Riccati lattices within two classes of lattices: generalized Lotka-Volterra lattices and generalized Holling lattices. We show that from the class of generalized Lotka-Volterra lattices only the Wadati lattice belongs to the class of Riccati lattices. Opposite to this many lattices from the Holling class are Riccati lattices. We construct exact traveling wave solutions on the basis of the solution of Riccati equation for three members of the class of generalized Holling lattices.

Pathway towards Programmable Wave Anisotropy in Cellular Metamaterials

NASA Astrophysics Data System (ADS)

Celli, Paolo; Zhang, Weiting; Gonella, Stefano

2018-01-01

In this work, we provide a proof-of-concept experimental demonstration of the wave-control capabilities of cellular metamaterials endowed with populations of tunable electromechanical resonators. Each independently tunable resonator comprises a piezoelectric patch and a resistor-inductor shunt, and its resonant frequency can be seamlessly reprogrammed without interfering with the cellular structure's default properties. We show that, by strategically placing the resonators in the lattice domain and by deliberately activating only selected subsets of them, chosen to conform to the directional features of the beamed wave response, it is possible to override the inherent wave anisotropy of the cellular medium. The outcome is the establishment of tunable spatial patterns of energy distillation resulting in a nonsymmetric correction of the wave fields.

Equilibrium polymerization on the equivalent-neighbor lattice

NASA Technical Reports Server (NTRS)

Kaufman, Miron

1989-01-01

The equilibrium polymerization problem is solved exactly on the equivalent-neighbor lattice. The Flory-Huggins (Flory, 1986) entropy of mixing is exact for this lattice. The discrete version of the n-vector model is verified when n approaches 0 is equivalent to the equal reactivity polymerization process in the whole parameter space, including the polymerized phase. The polymerization processes for polymers satisfying the Schulz (1939) distribution exhibit nonuniversal critical behavior. A close analogy is found between the polymerization problem of index the Schulz r and the Bose-Einstein ideal gas in d = -2r dimensions, with the critical polymerization corresponding to the Bose-Einstein condensation.

Characterizing emergent properties of immunological systems with multi-cellular rule-based computational modeling.

PubMed

Chavali, Arvind K; Gianchandani, Erwin P; Tung, Kenneth S; Lawrence, Michael B; Peirce, Shayn M; Papin, Jason A

2008-12-01

The immune system is comprised of numerous components that interact with one another to give rise to phenotypic behaviors that are sometimes unexpected. Agent-based modeling (ABM) and cellular automata (CA) belong to a class of discrete mathematical approaches in which autonomous entities detect local information and act over time according to logical rules. The power of this approach lies in the emergence of behavior that arises from interactions between agents, which would otherwise be impossible to know a priori. Recent work exploring the immune system with ABM and CA has revealed novel insights into immunological processes. Here, we summarize these applications to immunology and, particularly, how ABM can help formulate hypotheses that might drive further experimental investigations of disease mechanisms.

A verification strategy for web services composition using enhanced stacked automata model.

PubMed

Nagamouttou, Danapaquiame; Egambaram, Ilavarasan; Krishnan, Muthumanickam; Narasingam, Poonkuzhali

2015-01-01

Currently, Service-Oriented Architecture (SOA) is becoming the most popular software architecture of contemporary enterprise applications, and one crucial technique of its implementation is web services. Individual service offered by some service providers may symbolize limited business functionality; however, by composing individual services from different service providers, a composite service describing the intact business process of an enterprise can be made. Many new standards have been defined to decipher web service composition problem namely Business Process Execution Language (BPEL). BPEL provides an initial work for forming an Extended Markup Language (XML) specification language for defining and implementing business practice workflows for web services. The problems with most realistic approaches to service composition are the verification of composed web services. It has to depend on formal verification method to ensure the correctness of composed services. A few research works has been carried out in the literature survey for verification of web services for deterministic system. Moreover the existing models did not address the verification properties like dead transition, deadlock, reachability and safetyness. In this paper, a new model to verify the composed web services using Enhanced Stacked Automata Model (ESAM) has been proposed. The correctness properties of the non-deterministic system have been evaluated based on the properties like dead transition, deadlock, safetyness, liveness and reachability. Initially web services are composed using Business Process Execution Language for Web Service (BPEL4WS) and it is converted into ESAM (combination of Muller Automata (MA) and Push Down Automata (PDA)) and it is transformed into Promela language, an input language for Simple ProMeLa Interpreter (SPIN) tool. The model is verified using SPIN tool and the results revealed better recital in terms of finding dead transition and deadlock in contrast to the

All-DNA finite-state automata with finite memory

PubMed Central

Wang, Zhen-Gang; Elbaz, Johann; Remacle, F.; Levine, R. D.; Willner, Itamar

2010-01-01

Biomolecular logic devices can be applied for sensing and nano-medicine. We built three DNA tweezers that are activated by the inputs H+/OH-; ; nucleic acid linker/complementary antilinker to yield a 16-states finite-state automaton. The outputs of the automata are the configuration of the respective tweezers (opened or closed) determined by observing fluorescence from a fluorophore/quencher pair at the end of the arms of the tweezers. The system exhibits a memory because each current state and output depend not only on the source configuration but also on past states and inputs. PMID:21135212

A Mobile Robot for Locomotion Through a 3D Periodic Lattice Environment

NASA Technical Reports Server (NTRS)

Jenett, Benjamin; Cellucci, Daniel; Cheung, Kenneth

2017-01-01

This paper describes a novel class of robots specifically adapted to climb periodic lattices, which we call 'Relative Robots'. These robots use the regularity of the structure to simplify the path planning, align with minimal feedback, and reduce the number of degrees of freedom (DOF) required to locomote. They can perform vital inspection and repair tasks within the structure that larger truss construction robots could not perform without modifying the structure. We detail a specific type of relative robot designed to traverse a cuboctahedral (CubOct) cellular solids lattice, show how the symmetries of the lattice simplify the design, and test these design methodologies with a CubOct relative robot that traverses a 76.2 mm (3 in.) pitch lattice, MOJO (Multi-Objective JOurneying robot). We perform three locomotion tasks with MOJO: vertical climbing, horizontal climbing, and turning, and find that, due to changes in the orientation of the robot relative to the gravity vector, the success rate of vertical and horizontal climbing is significantly different.

Hierarchical random cellular neural networks for system-level brain-like signal processing.

PubMed

Kozma, Robert; Puljic, Marko

2013-09-01

Sensory information processing and cognition in brains are modeled using dynamic systems theory. The brain's dynamic state is described by a trajectory evolving in a high-dimensional state space. We introduce a hierarchy of random cellular automata as the mathematical tools to describe the spatio-temporal dynamics of the cortex. The corresponding brain model is called neuropercolation which has distinct advantages compared to traditional models using differential equations, especially in describing spatio-temporal discontinuities in the form of phase transitions. Phase transitions demarcate singularities in brain operations at critical conditions, which are viewed as hallmarks of higher cognition and awareness experience. The introduced Monte-Carlo simulations obtained by parallel computing point to the importance of computer implementations using very large-scale integration (VLSI) and analog platforms. Copyright © 2013 Elsevier Ltd. All rights reserved.

Thermal lattice BGK models for fluid dynamics

NASA Astrophysics Data System (ADS)

Huang, Jian

1998-11-01

As an alternative in modeling fluid dynamics, the Lattice Boltzmann method has attracted considerable attention. In this thesis, we shall present a general form of thermal Lattice BGK. This form can handle large differences in density, temperature, and high Mach number. This generalized method can easily model gases with different adiabatic index values. The numerical transport coefficients of this model are estimated both theoretically and numerically. Their dependency on the sizes of integration steps in time and space, and on the flow velocity and temperature, are studied and compared with other established CFD methods. This study shows that the numerical viscosity of the Lattice Boltzmann method depends linearly on the space interval, and on the flow velocity as well for supersonic flow. This indicates this method's limitation in modeling high Reynolds number compressible thermal flow. On the other hand, the Lattice Boltzmann method shows promise in modeling micro-flows, i.e., gas flows in micron-sized devices. A two-dimensional code has been developed based on the conventional thermal lattice BGK model, with some modifications and extensions for micro- flows and wall-fluid interactions. Pressure-driven micro- channel flow has been simulated. Results are compared with experiments and simulations using other methods, such as a spectral element code using slip boundary condition with Navier-Stokes equations and a Direct Simulation Monte Carlo (DSMC) method.

Lattice dynamics and thermoelectric properties of nanocrystalline silicon-germanium alloys: Lattice dynamics and thermoelectric properties of nc Si-Ge alloys

DOE Office of Scientific and Technical Information (OSTI.GOV)

Claudio, Tania; Stein, Niklas; Petermann, Nils

2015-10-26

The lattice dynamics and thermoelectric properties of sintered phosphorus-doped nanostructured silicon–germanium alloys obtained by gas-phase synthesis were studied. Measurements of the density of phonon states by inelastic neutron scattering were combined with measurements of the elastic constants and the low-temperature heat capacity. A strong influence of nanostructuring and alloying on the lattice dynamics was observed. The thermoelectric transport properties of samples with different doping as well as samples sintered at different temperature were characterized between room temperature and 1000°C. A peak figure of merit zT=0.88 at 900°C is observed and is comparatively insensitive to the aforementioned parameter variations.

Fuzzy automata and pattern matching

NASA Technical Reports Server (NTRS)

Setzer, C. B.; Warsi, N. A.

1986-01-01

A wide-ranging search for articles and books concerned with fuzzy automata and syntactic pattern recognition is presented. A number of survey articles on image processing and feature detection were included. Hough's algorithm is presented to illustrate the way in which knowledge about an image can be used to interpret the details of the image. It was found that in hand generated pictures, the algorithm worked well on following the straight lines, but had great difficulty turning corners. An algorithm was developed which produces a minimal finite automaton recognizing a given finite set of strings. One difficulty of the construction is that, in some cases, this minimal automaton is not unique for a given set of strings and a given maximum length. This algorithm compares favorably with other inference algorithms. More importantly, the algorithm produces an automaton with a rigorously described relationship to the original set of strings that does not depend on the algorithm itself.

Knot Invariants and Cellular Automata

DTIC Science & Technology

1993-05-04

behavior might be found in a naturally associated two dimensional statistical mechanics model. The Boltzmann weight TV’b := exp[-/3E(a,b, c ,d)] can be...the Yang-Baxter (star-triangle) equation [10,11]: +, b ) C I k( ) = ± )tI k I The relevance of this result to our problem is the following. The two com...J. Baxter and P. J. Forrester, "Eight-vertex SOS model and generalized Rogers- Ramanujan -type identities," J. Stat. Phys. 35 (1934) 193-266. [13] L. H

Nanostructured 2D cellular materials in silicon by sidewall transfer lithography NEMS

NASA Astrophysics Data System (ADS)

Syms, Richard R. A.; Liu, Dixi; Ahmad, Munir M.

2017-07-01

Sidewall transfer lithography (STL) is demonstrated as a method for parallel fabrication of 2D nanostructured cellular solids in single-crystal silicon. The linear mechanical properties of four lattices (perfect and defected diamond; singly and doubly periodic honeycomb) with low effective Young’s moduli and effective Poisson’s ratio ranging from positive to negative are modelled using analytic theory and the matrix stiffness method with an emphasis on boundary effects. The lattices are fabricated with a minimum feature size of 100 nm and an aspect ratio of 40:1 using single- and double-level STL and deep reactive ion etching of bonded silicon-on-insulator. Nanoelectromechanical systems (NEMS) containing cellular materials are used to demonstrate stretching, bending and brittle fracture. Predicted edge effects are observed, theoretical values of Poisson’s ratio are verified and failure patterns are described.

Growth and setting of gas bubbles in a viscoelastic matrix imaged by X-ray microtomography: the evolution of cellular structures in fermenting wheat flour dough.

PubMed

Turbin-Orger, A; Babin, P; Boller, E; Chaunier, L; Chiron, H; Della Valle, G; Dendievel, R; Réguerre, A L; Salvo, L

2015-05-07

X-ray tomography is a relevant technique for the dynamic follow-up of gas bubbles in an opaque viscoelastic matrix, especially using image analysis. It has been applied here to pieces of fermenting wheat flour dough of various compositions, at two different voxel sizes (15 and 5 μm). The resulting evolution of the main cellular features shows that the creation of cellular structures follows two regimes that are defined by a characteristic time of connectivity, tc [30 and 80 min]: first (t ≤ tc), bubbles grow freely and then (t ≥ tc) they become connected since the percolation of the gas phase is limited by liquid films. During the first regime, bubbles can be tracked and the local strain rate can be measured. Its values (10(-4)-5 × 10(-4) s(-1)) are in agreement with those computed from dough viscosity and internal gas pressure, both of which depend on the composition. For higher porosity, P = 0.64 in our case, and thus occurring in the second regime, different cellular structures are obtained and XRT images show deformed gas cells that display complex shapes. The comparison of these images with confocal laser scanning microscopy images suggests the presence of liquid films that separate these cells. The dough can therefore be seen as a three-phase medium: viscoelastic matrix/gas cell/liquid phase. The contributions of the different levels of matter organization can be integrated by defining a capillary number (C = 0.1-1) that makes it possible to predict the macroscopic dough behavior.

Constraining the hadronic spectrum through QCD thermodynamics on the lattice

NASA Astrophysics Data System (ADS)

Alba, Paolo; Bellwied, Rene; Borsányi, Szabolcs; Fodor, Zoltan; Günther, Jana; Katz, Sandor D.; Mantovani Sarti, Valentina; Noronha-Hostler, Jacquelyn; Parotto, Paolo; Pasztor, Attila; Vazquez, Israel Portillo; Ratti, Claudia

2017-08-01

Fluctuations of conserved charges allow us to study the chemical composition of hadronic matter. A comparison between lattice simulations and the hadron resonance gas (HRG) model suggested the existence of missing strange resonances. To clarify this issue we calculate the partial pressures of mesons and baryons with different strangeness quantum numbers using lattice simulations in the confined phase of QCD. In order to make this calculation feasible, we perform simulations at imaginary strangeness chemical potentials. We systematically study the effect of different hadronic spectra on thermodynamic observables in the HRG model and compare to lattice QCD results. We show that, for each hadronic sector, the well-established states are not enough in order to have agreement with the lattice results. Additional states, either listed in the Particle Data Group booklet (PDG) but not well established, or predicted by the quark model (QM), are necessary in order to reproduce the lattice data. For mesons, it appears that the PDG and the quark model do not list enough strange mesons, or that, in this sector, interactions beyond those included in the HRG model are needed to reproduce the lattice QCD results.

A Fermi-degenerate three-dimentional optical lattice clock

NASA Astrophysics Data System (ADS)

Goban, Akihisa; Campbell, Sara; Hutson, Ross; Marti, G. Edward; Sonderhouse, Lindsay; Robinson, John; Zhang, Wei; Ye, Jun

2017-04-01

The pursuit of better atomic clocks has advanced many research areas, providing better quantum state control, tighter limits on fundamental constant variation, and improved tests of relativity. Recent progress in optical lattice clock to the accuracy of 2E-18 has benefited from the understanding of atomic interactions. Also the precision of clock spectroscopy has been applied to explore many-body interactions including SU(N) symmetry. In our previous 1D optical lattice, atomic interactions cause suppression and broadening of the atomic resonance, limiting the clock stability. To overcome this limitation, we demonstrate a scalable solution that takes advantage of the high density of a degenerate Fermi gas in a three-dimensional optical lattice to protect against on-site interaction shifts. Using an ultrastable laser, we achieve an unprecedented level of atom-light coherence, reaching a spectroscopic quality factor 5.2E15. We investigate clock systematics unique to this design; on-site interactions are resolved so that their contribution to clock shifts is orders of magnitude suppressed compared to the 1D optical lattice experiments. Also, we measure the combined scalar and tensor magic wavelengths for state-independent trapping along all three lattice axes. We acknowledge support from NIST, DARPA and the NSF JILA Physics Frontier Center.

Mechanical behavior of regular open-cell porous biomaterials made of diamond lattice unit cells.

PubMed

Ahmadi, S M; Campoli, G; Amin Yavari, S; Sajadi, B; Wauthle, R; Schrooten, J; Weinans, H; Zadpoor, A A

2014-06-01

Cellular structures with highly controlled micro-architectures are promising materials for orthopedic applications that require bone-substituting biomaterials or implants. The availability of additive manufacturing techniques has enabled manufacturing of biomaterials made of one or multiple types of unit cells. The diamond lattice unit cell is one of the relatively new types of unit cells that are used in manufacturing of regular porous biomaterials. As opposed to many other types of unit cells, there is currently no analytical solution that could be used for prediction of the mechanical properties of cellular structures made of the diamond lattice unit cells. In this paper, we present new analytical solutions and closed-form relationships for predicting the elastic modulus, Poisson׳s ratio, critical buckling load, and yield (plateau) stress of cellular structures made of the diamond lattice unit cell. The mechanical properties predicted using the analytical solutions are compared with those obtained using finite element models. A number of solid and porous titanium (Ti6Al4V) specimens were manufactured using selective laser melting. A series of experiments were then performed to determine the mechanical properties of the matrix material and cellular structures. The experimentally measured mechanical properties were compared with those obtained using analytical solutions and finite element (FE) models. It has been shown that, for small apparent density values, the mechanical properties obtained using analytical and numerical solutions are in agreement with each other and with experimental observations. The properties estimated using an analytical solution based on the Euler-Bernoulli theory markedly deviated from experimental results for large apparent density values. The mechanical properties estimated using FE models and another analytical solution based on the Timoshenko beam theory better matched the experimental observations. Copyright © 2014 Elsevier Ltd

Calibrating cellular automaton models for pedestrians walking through corners

NASA Astrophysics Data System (ADS)

Dias, Charitha; Lovreglio, Ruggiero

2018-05-01

Cellular Automata (CA) based pedestrian simulation models have gained remarkable popularity as they are simpler and easier to implement compared to other microscopic modeling approaches. However, incorporating traditional floor field representations in CA models to simulate pedestrian corner navigation behavior could result in unrealistic behaviors. Even though several previous studies have attempted to enhance CA models to realistically simulate pedestrian maneuvers around bends, such modifications have not been calibrated or validated against empirical data. In this study, two static floor field (SFF) representations, namely 'discrete representation' and 'continuous representation', are calibrated for CA-models to represent pedestrians' walking behavior around 90° bends. Trajectory data collected through a controlled experiment are used to calibrate these model representations. Calibration results indicate that although both floor field representations can represent pedestrians' corner navigation behavior, the 'continuous' representation fits the data better. Output of this study could be beneficial for enhancing the reliability of existing CA-based models by representing pedestrians' corner navigation behaviors more realistically.

New cellular automaton model for magnetohydrodynamics

NASA Technical Reports Server (NTRS)

Chen, Hudong; Matthaeus, William H.

1987-01-01

A new type of two-dimensional cellular automation method is introduced for computation of magnetohydrodynamic fluid systems. Particle population is described by a 36-component tensor referred to a hexagonal lattice. By appropriate choice of the coefficients that control the modified streaming algorithm and the definition of the macroscopic fields, it is possible to compute both Lorentz-force and magnetic-induction effects. The method is local in the microscopic space and therefore suited to massively parallel computations.

Thermal effects in light scattering from ultracold bosons in an optical lattice

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lakomy, Kazimierz; Idziaszek, Zbigniew; Trippenbach, Marek

2009-10-15

We study the scattering of a weak and far-detuned light from a system of ultracold bosons in one-dimensional and three-dimensional optical lattices. We show the connection between angular distributions of the scattered light and statistical properties of a Bose gas in a periodic potential. The angular patterns are determined by the Fourier transform of the second-order correlation function, and thus they can be used to retrieve information on particle number fluctuations and correlations. We consider superfluid and Mott-insulator phases of the Bose gas in a lattice and we analyze in detail how the scattering depends on the system dimensionality, temperature,more » and atom-atom interactions.« less

Ocean acidification affects competition for space: projections of community structure using cellular automata.

PubMed

McCoy, Sophie J; Allesina, Stefano; Pfister, Catherine A

2016-03-16

Historical ecological datasets from a coastal marine community of crustose coralline algae (CCA) enabled the documentation of ecological changes in this community over 30 years in the Northeast Pacific. Data on competitive interactions obtained from field surveys showed concordance between the 1980s and 2013, yet also revealed a reduction in how strongly species interact. Here, we extend these empirical findings with a cellular automaton model to forecast ecological dynamics. Our model suggests the emergence of a new dominant competitor in a global change scenario, with a reduced role of herbivory pressure, or trophic control, in regulating competition among CCA. Ocean acidification, due to its energetic demands, may now instead play this role in mediating competitive interactions and thereby promote species diversity within this guild. © 2016 The Author(s).

Towards Time Automata and Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Hutzler, G.; Klaudel, H.; Wang, D. Y.

2004-01-01

The design of reactive systems must comply with logical correctness (the system does what it is supposed to do) and timeliness (the system has to satisfy a set of temporal constraints) criteria. In this paper, we propose a global approach for the design of adaptive reactive systems, i.e., systems that dynamically adapt their architecture depending on the context. We use the timed automata formalism for the design of the agents' behavior. This allows evaluating beforehand the properties of the system (regarding logical correctness and timeliness), thanks to model-checking and simulation techniques. This model is enhanced with tools that we developed for the automatic generation of code, allowing to produce very quickly a running multi-agent prototype satisfying the properties of the model.

Optical Lattice Simulations of Correlated Fermions

DTIC Science & Technology

2013-10-04

Zhang, Xiaopeng Li, W. Vincent Liu. Stripe , checkerboard, and liquid-crystal ordering from anisotropic p-orbital Fermi surfaces in optical lattices...Meeting "The Role of Interactions in Disorder Induced Damping of Dipole Oscillations of a Bose-Einstein Condensate", S. Pollack, APS March Meeting...Rev. A 85, 043603 (2012)], and also worked out the diffusive transport behavior of the polarized Fermi gas, including heat transport, spin Seebeck

Achieving microaggregation for secure statistical databases using fixed-structure partitioning-based learning automata.

PubMed

Fayyoumi, Ebaa; Oommen, B John

2009-10-01

We consider the microaggregation problem (MAP) that involves partitioning a set of individual records in a microdata file into a number of mutually exclusive and exhaustive groups. This problem, which seeks for the best partition of the microdata file, is known to be NP-hard and has been tackled using many heuristic solutions. In this paper, we present the first reported fixed-structure-stochastic-automata-based solution to this problem. The newly proposed method leads to a lower value of the information loss (IL), obtains a better tradeoff between the IL and the disclosure risk (DR) when compared with state-of-the-art methods, and leads to a superior value of the scoring index, which is a criterion involving a combination of the IL and the DR. The scheme has been implemented, tested, and evaluated for different real-life and simulated data sets. The results clearly demonstrate the applicability of learning automata to the MAP and its ability to yield a solution that obtains the best tradeoff between IL and DR when compared with the state of the art.

Bandgaps and directional properties of two-dimensional square beam-like zigzag lattices

NASA Astrophysics Data System (ADS)

Wang, Yan-Feng; Wang, Yue-Sheng; Zhang, Chuanzeng