Evolving cellular automata schemes for protein folding modeling using the Rosetta atomic representation

Genetic Programming and Evolvable Machines - Protein folding is the dynamic process by which a protein folds into its final native structure. This is different to the traditional problem of the...     

Spatio-temporal organization of a cellular automaton model for computer network

It was unveiled by Ren et al. [Comput. Phys. Comm. (2001)] that congestion transition emerges in cellular automaton models for computer network and this NaSch network model with Q=1 has similar behaviours as the NaSch traffic model with maximum velocity v_max=1. For these two NaSch models, the main difference lies in a node cell contained in the NaSch network model. In this paper, we will focus on our further investigation on spatio-temporal organization of the NaSch network model. More interesting phenomena of phase transition are discovered. Firstly, fundamental diagram illustrates that when Q>1 for the NaSch network model it is significantly different from its counterpart, i.e. the NaSch traffic model in a road traffic system. The addition of a node cell, which is allowed to have more than one packets, will lead to generating a new phase. Secondly, in order to characterize phase transition occurred in the NaSch network model, an order parameter is presented with the use of the time average density of nearest-neighbor pairs m. The computational results obtained show that criticality will disappear in a strict sense if noise exists. Finally, two other numerical features, i.e. spatial correlation functions G(r) and relaxation times τ, are analyzed so as to deeply describe behaviours near critical points.     

Offset control of traffic signal using cellular automaton traffic model

This paper deals with an offset control of traffic signals using a cellular automaton traffic model. A stochastic optimal control method for distributed traffic signals is modified to achieve coordinated traffic signal control with the proposed offset control method. In the proposed coordinated traffic signal control method, splits of each cycle and common cycle length are calculated using a modified stochastic optimal control method, and then the offset is calculated using an estimation method based on a modified CA traffic model at intervals. Also, simulations are carried out at multiple intersections using a micro traffic simulator. The effectiveness of the proposed coordinated control method is proved by comparing with other traffic signal control methods such as pre-timed signal control, two types of the traditional coordinated control and distributed control.     

A simplified combat model based on a cellular automaton

The work is devoted to constructing a cellular automaton based model of motion and combat activity of systems of hierarchically organized agents with allowance for terrain ruggedness, communication channels between the agents, and the necessity of choosing behavior adequate to the current situation.     

Analysis of a cellular automaton model for car traffic with a slow-to-stop rule

We propose a modification of the widely known Benjamin–Johnson–Hui (BJH) cellular automaton model for single-lane traffic simulation. In particular, our model includes a ‘slow-to-stop’ rule that exhibits more realistic microscopic driver behaviour than the BJH model. We present some statistics related to fuel economy and pollution generation and show that our model differs greatly in these measures. We give concise results based on extensive simulations using our system.     

Halting the hallmarks: a cellular automaton model of early cancer growth inhibition

Cancer treatment is a fragmented and varied process, as “cancer” is really hundreds of different diseases. The “hallmarks of cancer” proposed by Hanahan and Weinberg (Cell 100(1):57–70, 2000) are a framework for viewing cancer within a common set of underlying principles—ten properties that are common to almost all cancers, allowing them to grow uncontrollably and ravage the body. We used a cellular automaton model of tumour growth paired with lattice Boltzmann methods modelling oxygen flow to simulate combination drugs targeted at knocking out pairs of hallmarks. We found that knocking out some pairs of cancer-enabling hallmarks did not prevent tumour formation, while other pairs significantly prevent tumour growth (\(p=0.0004\) using Wilcoxon signed-rank adjusted with the Bonferroni correction for multiple comparisons). This is not what would be expected from models of knocking out the hallmarks individually, as many pairs did not have an additive effect but had either no statistically significant effect or a multiplicative one. We propose that targeting certain pairs of cancer hallmarks, specifically cancers ability to induce blood vessel development paired with another cancer hallmark, could prove an effective cancer treatment option.     

Prediction of traveling front behavior in a lattice-gas cellular automaton model for tumor invasion

Cancer invasion is the process of cells detaching from a primary tumor and infiltrating the healthy tissue. Cancer invasion has been recognized as a complex system, since a tumor’s invasive behavior emerges from the combined effect of tumor cell proliferation, tumor cell migration and cell–microenvironment interactions. Cellular automata (CA) provide simple models of self-organizing complex systems in which collective behavior can emerge out of an ensemble of many interacting “simple” components. Here, we introduce a lattice-gas cellular automaton (LGCA) model of tumor cell proliferation, necrosis and tumor cell migration. The impact of the tumor environment on tumor cells has been investigated in a previous study. Our analysis aims at predicting the velocity of the traveling invasion front, which depends upon fluctuations that arise from the motion of the discrete cells at the front. We find an excellent agreement between the velocities measured in simulations of the LGCA and an analytical estimate derived in the cut-off mean-field approximation via the discrete Lattice Boltzmann equation and its linearization. In particular, we predict the front velocity to scale with the square root of the product of probabilities for mitosis and the migration coefficient. Finally, we calculate the width of the traveling front which is found to be proportional to the front velocity.     

CURIE: a cellular automaton for concept drift detection

Data Mining and Knowledge Discovery - Data stream mining extracts information from large quantities of data flowing fast and continuously (data streams). They are usually affected by changes in the...     

Designing self-timed devices using the finite automaton model

The authors suggest a procedure for designing a self-timed device defined by the finite automaton model. This procedure proves useful when designing these devices using the available synchronous behavior specifications. They illustrate the effectiveness of their procedure by applying it to the design of a stack memory and constant acknowledgement delay counter     

On the hierarchy of conservation laws in a cellular automaton

Conservation laws in cellular automata (CA) are studied as an abstraction of the conservation laws observed in nature. In addition to the usual real-valued conservation laws we also consider more general group-valued and semigroup-valued conservation laws. The (algebraic) conservation laws in a CA form a hierarchy, based on the range of the interactions they take into account. The conservation laws with smaller interaction ranges are the homomorphic images of those with larger interaction ranges, and for each specific range there is a most general law that incorporates all those with that range. For one-dimensional CA, such a most general conservation law has—even in the semigroup-valued case—an effectively constructible finite presentation, while for higher-dimensional CA such effective construction exists only in the group-valued case. It is even undecidable whether a given two-dimensional CA conserves a given semigroup-valued energy assignment. Although the local properties of this hierarchy are tractable in the one-dimensional case, its global properties turn out to be undecidable. In particular, we prove that it is undecidable whether this hierarchy is trivial or unbounded. We point out some interconnections between the structure of this hierarchy and the dynamical properties of the CA. In particular, we show that positively expansive CA do not have non-trivial real-valued conservation laws.     

On a three-parameter quantum battle of the sexes cellular automaton

The dynamics of a spatial quantum 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 effect of spatial structure is assessed when allowing the players to adopt quantum strategies that are no restricted to any particular subset of the possible strategies.     

An FPGA implemented cellular automaton crowd evacuation model inspired by the electrostatic-induced potential fields

This paper studies the on-chip realisation of a dynamic model proposed to simulate crowd behaviour, originated from electrostatic-induced potential fields. It is based on cellular automata (CA), thus taking advantage of their inherent ability to represent sufficiently phenomena of arbitrary complexity and, additionally, to be simulated precisely by digital computers. The model combines electrostatic-induced potential fields to incorporate flexibility in the movement of pedestrians. It primarily calculates distances in an obstacle filled space based on the Euclidean metric. Furthermore, it adopts a computationally fast and efficient method to overcome trouble-inducing obstacles by shifting the moving mechanism to a potential field method based on Manhattan-distance. The hardware implementation of the model is based on FPGA logic. Initialisation of the dedicated processor takes place in collaboration with a detecting and tracking algorithm supported by cameras. The instant response of the processor provides the location of pedestrians around exits. Hardware implementation exploits the prominent feature of parallelism that CA structures inherently possess in contrast to the serial computers, thus accelerating the response of the model. Furthermore, FPGA implementation of the model is advantageous in terms of low-cost, high-speed, compactness and portability features. Finally, the processor could be used as a part of an embedded, real-time, decision support system, aiming at the efficient guidance of crowd in cases of mass egress.     

Utilizing a cellular automaton model to explore the influence of coastal flood adaptation strategies on Helsinki's urbanization patterns

A cellular automaton model (SLEUTH-3r) is utilized to explore the impacts of coastal flood risk management strategies on the urbanization parameters of Helsinki's metropolitan area, at a 50-m spatial resolution by 2040. The current urbanization trend is characterized by the consolidation of existing built-up land and loss of interspersed green spaces, whereas the most intense growth is forecast inside the coastal flood risk areas. This baseline is compared to strategies that test various responses of the planning system to real estate market forces and the spatial distribution of flood risks. A set of scenarios translates property price effects of flood risk information into various attraction-repulsion areas in and adjacent to the floodplain, while a second set explores varying degrees of restricting new growth in the flood risk zones without reference to the housing market.The simulations indicate that growth under all scenarios is distributed in a more fragmented manner relative to the baseline, which can be interpreted favorably regarding house prices and increased access to ecosystem services, although the indirect effects should also be considered. Demand for coastal flood-safe properties does not appear to automatically translate to refocusing of development toward those areas, unless planning interventions encourage this redistribution. The character of the planning system with respect to market drivers and the spatial distribution of risks and amenities is thus important. A mixture of market-based measures and moderate zoning interventions may be preferable for flood risk management and provide the necessary precision for adaptation strategies.     

A new hardware module for automated visual inspection based on a cellular automaton architecture

This paper presents the design and VLSI implementation of a new automated visual inspection system based on a cellular automaton architecture, suitable for circular object inspection. Cellular Automata (CA) transform the area of the object of interest into a number of evolution steps in the CA space. The proposed technique does not require the extraction of image features, such as boundary length and total area, which are computationally expensive in other methods. The die size dimensions of the chip, for a 16×16 pixel image, are 3.73 mm×3.09 mm=11.52 mm² and its maximum frequency of operation is 25 MHz. Experimental results using computer-generated images, as well as real images obtained and processed through a commercial vision system, showing the suitability of the proposed hardware module for detecting circular objects, are also presented. Targeted applications include inspection tasks (accept/reject operations) of circular objects, such as tablets in the pharmaceutical industry, and detection of uncoated areas, foreign objects and level of bake in the confectionery and food industry.     

A cellular automaton simulation tool for modelling seismicity in the region of Xanthi

Seismicity is an extended geophysical characteristic of the Greek dominion. There are certain areas of high seismic activity, as well as, regions of low seismicity where strong earthquakes are rather rare events. Consequently, it is of great interest to present a methodology concerning the earthquake process in Greece even for areas considered to be of low seismicity. In this paper, a study of the earthquake activity of an area in Northeastern Greece, centred at Xanthi, Thrace, extending over a region of radius R = 80 km, during a certain time period is presented. A two-dimensional cellular automaton (CA) dynamic system consisting of cells representing charges is used for the simulation of the earthquake process. The model has been tested as well as calibrated using the recorded events of the above-mentioned region as initial conditions. The simulation results are found in good quantitative and qualitative agreement with the Gutenberg–Richter (GR) scaling relations. Finally, the CA model has a user-friendly interface and enables the user to change several of its parameters, in order to study various hypotheses concerning the seismicity of the region under consideration.     

Octree-based, GPU implementation of a continuous cellular automaton for the simulation of complex, evolving surfaces

Presently, dynamic surface-based models are required to contain increasingly larger numbers of points and to propagate them over longer time periods. For large numbers of surface points, the octree data structure can be used as a balance between low memory occupation and relatively rapid access to the stored data. For evolution rules that depend on neighborhood states, extended simulation periods can be obtained by using simplified atomistic propagation models, such as the Cellular Automata (CA). This method, however, has an intrinsic parallel updating nature and the corresponding simulations are highly inefficient when performed on classical Central Processing Units (CPUs), which are designed for the sequential execution of tasks. In this paper, a series of guidelines is presented for the efficient adaptation of octree-based, CA simulations of complex, evolving surfaces into massively parallel computing hardware. A Graphics Processing Unit (GPU) is used as a cost-efficient example of the parallel architectures. For the actual simulations, we consider the surface propagation during anisotropic wet chemical etching of silicon as a computationally challenging process with a wide-spread use in microengineering applications. A continuous CA model that is intrinsically parallel in nature is used for the time evolution. Our study strongly indicates that parallel computations of dynamically evolving surfaces simulated using CA methods are significantly benefited by the incorporation of octrees as support data structures, substantially decreasing the overall computational time and memory usage.     

Assessing cellular automata model behaviour using a sensitivity analysis approach

Rapid advances in computer and geospatial technology have made it increasingly possible to design and develop urban models to efficiently simulate spatial growth patterns. An approach commonly used in geography and urban growth modelling is based on cellular automata theory and the GIS framework. However, the behaviour of cellular automaton (CA) models is affected by uncertainties arising from the interaction between model elements, structures, and the quality of data sources used as model input. The uncertainty of CA models has not been sufficiently addressed in the research literature. The objective of this study is to analyze the behaviour of a GIS-based CA urban growth model using sensitivity analysis (SA). The proposed SA approach has both qualitative and quantitative components. These components were operationalized using the cross-tabulation map, KAPPA index with coincidence matrices, and spatial metrics. The research focus was on the impacts of CA neighbourhood size and type on the model outcomes. A total of 432 simulations were generated and the results suggest that CA neighbourhood size and type configurations have a significant influence on the CA model output. This study provides insights about the limitations of CA model behaviour and contributes to enhancing existing spatial urban growth modelling procedures.     

Differential evolution-based nonlinear system modeling using a bilinear series model

This paper presents a new modeling method for nonlinear dynamic systems based on using bilinear series model. Basically, bilinear model is an extension of infinite impulse response (IIR) filter and belongs to the recursive nonlinear system model, i.e., its past output signals will heavily affect the present output. This kind of model can efficiently approximate a large class of nonlinear systems with fewer parameters than other non-recursive models. To adjust the model kernels, we here adopt an evolutionary computation called the differential evolution (DE) algorithm. This algorithm is based on real-valued manipulations and has a good convergence property for finding the global solution or the near global solution of optimized problem. Design steps of DE-based nonlinear system modeling are clearly given in this study. Finally, two kinds of digital systems are illustrated to demonstrate the efficiency of the proposed method.     

Real-time landscape model interaction using a tangible geospatial modeling environment

Emerging technologies that combine the flexibility of digital landscape representation with easy-to-interpret 3D physical models open new possibilities for user interaction with geospatial data. A prototype tangible geospatial modeling environment lets users interact with landscape analysis and simulations using a tangible physical model. We introduce a concept that builds upon previous independent tangible user interface (TUI) and terrain analysis research and aims at more intuitive collaborative interaction with digital landscape data.     

一种利用工作流模型的分层任务网络规划领域建模方法

为了有效地获取和利用领域知识,提高规划效率,分析了工作流模型和分层任务网络(HTN)规划领域模型的相似性,提出了一种采用工作流模型进行规划领域建模,对领域知识进行获取和表达的方法.工作流模型中的行动和工作流模式,转换为HTN规划中的行动和任务分解;另外,引入了循环(Loop)工作流模式,转换为HTN规划中的递归调用,扩展了工作流模式对规划领域知识的表达能力.在典型的几个规划领域中,引入领域知识后大大提高了规划器的求解效率,从而验证了应用工作流模型进行规划领域建模的有效性.