246 resultados para automata


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Pós-graduação em Geociências e Meio Ambiente - IGCE

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Brazil is a major world producer and exporter of agricultural products like soybeans, sugar, coffee, orange and tobacoo. However, the action of phytopathogenic fungi has been one of the largest challenges encountered in the field as they are responsible for approximately 25 to 50 per cent of losses in crops of fruits and vegetables. The presence of these pathogens is always a problem, because the damage on the tissues and organs promote lesions which decreses growth vegetation and often leads the individual (host) to death. Therefore, it is crucial to understand the process of spreading of these pathogens in the field to develop strategies which prevent the epidemics caused by them. In this study, the dispersal of fungi phytopathogenic in the field was modeled using the automata cellular formalism. The growth rate of infected plants population was measured by the radius of gyration and the influence of host different susceptibility degrees into the disease spread was assessed. The spatial anisotropy related to the plant-to-plant space and the system’s response to distinct seasonal patterns were also evaluated. The results obtained by a mean field model (spatially implicit models) emphasized the importance of the spatial structure on the spreading process, and dispersal patterns obtained by simulation (using a cellular automata) were in agreement with thse observed in data. All computational implementation was held in language Cl

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In this paper, a computational analysis, using a cellular automata model, has been developed to analyze post-feeding dispersal behavior of blow y larvae. This model aimed to: simulate the exponential decline of pupal number in relation to the feed source and spatial oscillation due to larval interaction during dispersal; study whether the prior pupal presence in uences distribution patterns of larval frequency; and compare obtained unidirectional dispersal patterns to the cross-dimensional ones. The cellular automata (CA) model was able to successfully reproduce the essential features of the larval dispersal process and, thus, show the importance of local interaction in the studied dispersal process dynamics. Oscillations could be explained by the interaction among dispersing larvae and intrinsic pupation time. The box size and the initial larval density were important factors for the experiment because they in uenced the results. Results showed that the unidirectional dispersal could be used to simulate the larval dispersion that occurs in the natural environment, because both models had a similar result. These results are important to understand how di erent factors can in uence the dynamics of blow y larval dispersal, bringing important results for behavioral ecology and forensic entomology

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In this work, some aspects of the erythrocyte cycle of the malaria parasite was incorporated into a cellular automata model to simulated the major factors leading to disruption of the erythrocyte cycle and consequent appearance of gametocytes, which infected the mosquitoes. Furthermore, the time seies of parasitaemia of infected patients was analyzed and compared to simulated data. The results suggested that differences in the temporal patterns of the asexual parasitaemia are associated with different effectiveness of the immune system in controlling the infection

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The market of digital games have grown in the last years, becoming popular between many ages, the number of smartphones and tablets users have also showed a recent increase, including the ones using Android as operational system. The main objective of a digital game is the ludic activity but also it can be used as a tool to education, learning and even simulation. This work proposes the development of a game for smartphones or tablet running on Android operational system, this game will simulate living beings in an environment, each one with different behaviors, based in the concepts of artificial live, cellular automata and emergence. This way simulating the behavior of a living being community with a computational base in artificial live and following concepts of game design. The game can represent visually some characteristics of living beings, as well behaviors and interactions between them, in a very simple way. The game can be upgraded in the future to represent better living beings using more details to the simulation of these

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This undergraduate thesis aims formally define aspects of Quantum Turing Machine using as a basis quantum finite automata. We introduce the basic concepts of quantum mechanics and quantum computing through principles such as superposition, entanglement of quantum states, quantum bits and algorithms. We demonstrate the Bell's teleportation theorem, enunciated in the form of Deutsch-Jozsa definition for quantum algorithms. The way as the overall text were written omits formal aspects of quantum mechanics, encouraging computer scientists to understand the framework of quantum computation. We conclude our thesis by listing the Quantum Turing Machine's main limitations regarding the well-known Classical Turing Machines

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This undergraduate thesis aims formally define aspects of Quantum Turing Machine using as a basis quantum finite automata. We introduce the basic concepts of quantum mechanics and quantum computing through principles such as superposition, entanglement of quantum states, quantum bits and algorithms. We demonstrate the Bell's teleportation theorem, enunciated in the form of Deutsch-Jozsa definition for quantum algorithms. The way as the overall text were written omits formal aspects of quantum mechanics, encouraging computer scientists to understand the framework of quantum computation. We conclude our thesis by listing the Quantum Turing Machine's main limitations regarding the well-known Classical Turing Machines

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In epidemiology, the basic reproduction number R-0 is usually defined as the average number of new infections caused by a single infective individual introduced into a completely susceptible population. According to this definition. R-0 is related to the initial stage of the spreading of a contagious disease. However, from epidemiological models based on ordinary differential equations (ODE), R-0 is commonly derived from a linear stability analysis and interpreted as a bifurcation parameter: typically, when R-0 >1, the contagious disease tends to persist in the population because the endemic stationary solution is asymptotically stable: when R-0 <1, the corresponding pathogen tends to naturally disappear because the disease-free stationary solution is asymptotically stable. Here we intend to answer the following question: Do these two different approaches for calculating R-0 give the same numerical values? In other words, is the number of secondary infections caused by a unique sick individual equal to the threshold obtained from stability analysis of steady states of ODE? For finding the answer, we use a susceptibleinfective-recovered (SIR) model described in terms of ODE and also in terms of a probabilistic cellular automaton (PCA), where each individual (corresponding to a cell of the PCA lattice) is connected to others by a random network favoring local contacts. The values of R-0 obtained from both approaches are compared, showing good agreement. (C) 2012 Elsevier B.V. All rights reserved.

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We study the firing rate properties of a cellular automaton model for a neuronal network with chemical synapses. We propose a simple mechanism in which the nonlocal connections are included, through electrical and chemical synapses. In the latter case, we introduce a time delay which produces self-sustained activity. Nonlocal connections, or shortcuts, are randomly introduced according to a specified connection probability. There is a range of connection probabilities for which neuron firing occurs, as well as a critical probability for which the firing ceases in the absence of time delay. The critical probability for nonlocal shortcuts depends on the network size according to a power-law. We also compute the firing rate amplification factor by varying both the connection probability and the time delay for different network sizes. (C) 2011 Elsevier B.V. All rights reserved.

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In this work we present an agent-based model for the spread of tuberculosis where the individuals can be infected with either drug-susceptible or drug-resistant strains and can also receive a treatment. The dynamics of the model and the role of each one of the parameters are explained. The whole set of parameters is explored to check their importance in the numerical simulation results. The model captures the beneficial impact of the adequate treatment on the prevalence of tuberculosis. Nevertheless, depending on the treatment parameters range, it also captures the emergence of drug resistance. Drug resistance emergence is particularly likely to occur for parameter values corresponding to less efficacious treatment, as usually found in developing countries.

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We investigate the nonequilibrium roughening transition of a one-dimensional restricted solid-on-solid model by directly sampling the stationary probability density of a suitable order parameter as the surface adsorption rate varies. The shapes of the probability density histograms suggest a typical Ginzburg-Landau scenario for the phase transition of the model, and estimates of the "magnetic" exponent seem to confirm its mean-field critical behavior. We also found that the flipping times between the metastable phases of the model scale exponentially with the system size, signaling the breaking of ergodicity in the thermodynamic limit. Incidentally, we discovered that a closely related model not considered before also displays a phase transition with the same critical behavior as the original model. Our results support the usefulness of off-critical histogram techniques in the investigation of nonequilibrium phase transitions. We also briefly discuss in the appendix a good and simple pseudo-random number generator used in our simulations.

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Os princípios e as diretrizes do Sistema Único de Saúde (SUS) impõem uma estrutura de assistência baseada em redes de políticas públicas que, combinada ao modelo de financiamento adotado, conduz a falhas de mercado. Isso impõe barreiras à gestão do sistema público de saúde e à concretização dos objetivos do SUS. As características institucionais e a heterogeneidade dos atores, aliadas à existência de diferentes redes de atenção à saúde, geram complexidade analítica no estudo da dinâmica global da rede do SUS. Há limitações ao emprego de métodos quantitativos baseados em análise estática com dados retrospectivos do sistema público de saúde. Assim, propõe-se a abordagem do SUS como sistema complexo, a partir da utilização de metodologia quantitativa inovadora baseada em simulação computacional. O presente artigo buscou analisar desafios e potencialidades na utilização de modelagem com autômatos celulares combinada com modelagem baseada em agentes para simulação da evolução da rede de serviços do SUS. Tal abordagem deve permitir melhor compreensão da organização, heterogeneidade e dinâmica estrutural da rede de serviços do SUS e possibilitar minimização dos efeitos das falhas de mercado no sistema de saúde brasileiro.