Synthesis of cryptographic interleaved sequences by means of linear cellular automata

This work shows that a class of pseudorandom binary sequences, the so-called interleaved sequences, can be generated by means of linear multiplicative polynomial cellular automata. In fact, these linear automata generate all the solutions of a type of linear difference equations with binary coefficients. Interleaved sequences are just particular solutions of such equations. In this way, popular nonlinear sequence generators with cryptographic application can be linearized in terms of simple cellular automata.     

A cellular automaton model for collective neural dynamics

A stochastic epidemic model for the collective behaviour of a large set of Boolean automata placed upon the sites of a complete graph is revisited. In this paper we study the generalisation of the model to take into account inhibitory neurons. The resulting stochastic cellular automata are completely defined by five parameters: the number of excitatory neurons, N, the number of inhibitory neurons, M, the probabilities of excitation, α, and inhibition, γ, among neurons and the spontaneous transition rate from the firing to the quiescent state, β.We propose that the background of the electroencephalographic signals could be mimicked by the fluctuations in the total number of firing neurons in the excitatory subnetwork. These fluctuations are Gaussian and the mean-square displacement from an initial state displays a strongly subdiffusive behaviour approximately given by , where NA=β/(β+Mγ), τ=2(Nα−β). Comparison with real EEG records exhibits good agreement with these predictions.     

Hybrid Dynamics of Stochastic π-Calculus

In this paper we describe a method to map stochastic π-calculus processes in chemical ground form into hybrid automata. Hybrid automata are tools widely employed to model systems characterized by both discrete and continuous evolution and their use in the context of Systems Biology allows us to address rather fundamental issues. Specifically, the key ingredient we use in this work is the possibility granted by hybrid automata to implement a separation of control and molecular terms in biochemical systems. The computational counterpart of our analysis turns out to be related to the determination of conservation properties of the system.      

Investigation of phase diagrams for cylindrical Ising nanotube using cellular automata

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.     

通道中行人-机动车相互作用机理的建模和模拟

本文研究了通道中行人与车辆同向或反向运动时的人车相互作用.车辆运动的描述采用细化的确定性元胞自动机模型,而行人流则采用考虑背景场的格子气模型.车辆及其影响区被视为一种可移动的障碍物,形成动态变化的背景场,可以更好地反映人车之间的相互作用.通过数值模拟得到典型参数下的行人流基本图以及平均车速随行人密度的变化曲线.人车反向时行人流基本图中存在两个临界密度,其间的行人流量-密度曲线呈线性分布,曲线斜率k主要依赖于车辆宽度和行人预判时间,而平均车速近似为k,即反向车辆形成的移动瓶颈和行人拥堵向上游传播的速度是一致的.文中进一步考察了行人预判时间、车辆宽度及限速对人车混合交通流的影响.人车同向时,这三个参数的影响都不明显.人车反向时,当车辆宽度较小,即使在很高密度下,车辆仍可以前行,而更大的行人预判时间也有助于车辆的运动.     

多路段元胞自动机交通流模型

在经典单路段元胞自动机交通流模型的基础上,将多个路段视为一个道路系统,提出并研究了多路段条件下的交通流问题.针对多路段道路的特点,通过引入车辆流入规则、路口随机慢化规则和路口车辆流入规则,控制车辆从上一路段流入下一路段.首先提出了"汽车池"的概念,来控制每一路口车辆的流入;然后通过路口随机慢化,来模拟路口对交通的影响;最后,当车辆离开时,依直行率进入下一路段,实现车流的继续流动.同时,通过数值模拟,仿真了不同条件下的交通情况,对重要参数进行了研究.结果表明,出现了混合流这一新的现象,拥堵地段与非拥堵地段间存在明显的界限.拥堵往往最先从路口开始,然后蔓延到整个路段.多路段道路还存在临界突变的特性.随着车辆流入概率的增大,路口对平均速度和车流密度的影响愈加明显.当流入概率超过一定阈值时,车辆缓慢地增加也会引起整体道路通行能力的迅速下降.     

Pedestrian choice behavior analysis and simulation of vertical walking facilities in transfer station

Considering the interlayer height, luggage, the difference between queuing pedestrians, and walking speed, the pedestrian choice model of vertical walking facilities is established based on a support vector machine. This model is verified with the pedestrian flow data of Changchun light-rail transfer station and Beijing Xizhimen transfer station. Adding the pedestrian choice model of vertical walking facilities into the pedestrian simulation model which is based on cellular automata, the pedestrian choice behavior is simulated. In the simulation, the effects of the dynamic influence factors are analyzed. To reduce the conflicts between pedestrians in opposite directions, the layout of vertical walking facilities is improved. The simulations indicate that the improved layout of vertical walking facilities can improve the efficiency of pedestrians passing.     

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

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.     

Study on bi-directional pedestrian movement using ant algorithms

A cellular automata model is proposed to simulate bi-directional pedestrian flow. Pedestrian movement is investigated by using ant algorithms. Ants communicate with each other by dropping a chemical, called a pheromone, on the substrate while crawling forward. Similarly, it is considered that oppositely moving pedestrians drop ‘visual pheromones' on their way and the visual pheromones might cause attractive or repulsive interactions. This pheromenon is introduced into modelling the pedestrians' walking preference. In this way, the decision-making process of pedestrians will be based on ‘the instinct of following'. At some densities, the relationships of velocity–density and flux–density are analyzed for different evaporation rates of visual pheromones. Lane formation and phase transition are observed for certain evaporation rates of visual pheromones.     

Statistical distributions of avalanche size and waiting times in an inter-sandpile cascade model

Sandpile-based models have successfully shed light on key features of nonlinear relaxational processes in nature, particularly the occurrence of fat-tailed magnitude distributions and exponential return times, from simple local stress redistributions. In this work, we extend the existing sandpile paradigm into an inter-sandpile cascade, wherein the avalanches emanating from a uniformly-driven sandpile (first layer) is used to trigger the next (second layer), and so on, in a successive fashion. Statistical characterizations reveal that avalanche size distributions evolve from a power-law p(S)≈S^−1.3 for the first layer to gamma distributions p(S)≈S^αexp(−S/S₀) for layers far away from the uniformly driven sandpile. The resulting avalanche size statistics is found to be associated with the corresponding waiting time distribution, as explained in an accompanying analytic formulation. Interestingly, both the numerical and analytic models show good agreement with actual inventories of non-uniformly driven events in nature.