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

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 incon- sistencies on mathematical methods. Due to the finite definition of numbers or the numerical restrictions during the simulation of solidifica- tion, 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 al- gorithms are tested and proved to be appropriate and efficient to eliminate the errors and characterize the grain structures.

Providing a Therapeutic Scheduling for HIV Infected Individuals with Genetic Algorithms Using a Cellular Automata Model of HIV Infection in the Peripheral Blood Stream

The aim of this study is to develop two-dimensional cellular automata model of HIV infection that depicts the dynamics involved in the interactions between acquired immune system and HIV infection in the peripheral blood stream. The appropriate biological rules of cellular automata model have been extracted from expert knowledge and the model has been simulated with determined initial conditions. Obtained results have been validated through comparing with the accepted AIDS reference curve. The new rules and states were added to the proposed model to show the effects of applying combined antiretroviral therapy. Our results showed that by applying RTI and PI drugs with maximum drug effectiveness, comparing with cases in which no treatment was applied, the steady state concentrations of healthy (infected) CD4+T cells were increased (decreased) 53% (41%). Also, the use of cART with maximum drug effectiveness led to a 69% reduction in the steady state level of viral load. At this time, obtained results have been validated through comparing with available clinical data. Our results showed good agreement with both reference curve and the clinical data. In the second phase of this study, by applying genetic algorithms, a therapeutic schedule has been provided that its use, while maintaining the quality of the treatment, leads to a 47% reduction in both drug dosage and the side effects of antiretroviral drugs.

Text Extraction and Enhancement of Binary Images Using Cellular Automata

Text characters embedded in images represent a rich source of information for content-based indexing and retrieval applications. However, these text characters are difficult to be detected and recognized due to their various sizes, grayscale values, and complex backgrounds. Existing methods cannot handle well those texts with different contrast or embedded in a complex image background. In this paper, a set of sequential algorithms for text extraction and enhancement of image using cellular automata are proposed. The image enhancement includes gray level, contrast manipulation, edge detection, and filtering. First, it applies edge detection and uses a threshold to filter out for low-contrast text and simplify complex background of high-contrast text from binary image. The proposed algorithm is simple and easy to use and requires only a sample texture binary image as an input. It generates textures with perceived quality, better than those proposed by earlier published techniques. The performance of our method is demonstrated by presenting experimental results for a set of text based binary images. The quality of thresholding is assessed using the precision and recall analysis of the resultant text in the binary image.

A cellular automata model for simulating grain structures with straight and hyperbolic interfaces

A description of a mathematical algorithm for simulating grain structures with straight and hyperbolic interfaces is shown. The presence of straight and hyperbolic interfaces in many grain structures of metallic materials is due to different solidification conditions, in- eluding different solidification speeds, growth directions, and delaying on the nucleation times of each nucleated node. Grain growth is a complex problem to be simulated; therefore, computational methods based on the chaos theory have been developed for this purpose. Straight and hyperbolic interfaces are between columnar and equiaxed grain structures or in transition zones. The algorithm developed in this work involves random distributions of temperature to assign preferential probabilities to each node of the simulated sample for nucleation according to previously defined boundary conditions. Moreover, more than one single nucleation process can be established in order to gen- erate hyperbolic interfaces between the grains. The appearance of new nucleated nodes is declared in sequences with a particular number of nucleated nodes and a number of steps for execution. This input information influences directly on the final grain structure （grain size and dislribution）. Preferential growth directions are also established to obtain equiaxed and columnar grains. The simulation is done using rou- tines for nucleation and growth nested inside the main function. Here, random numbers are generated to place the coordinates of each new nucleated node at each nucleation sequence according to a solidification probability. Nucleation and growth routines are executed as a func- tion of nodal availability in order to know if a node will be part of a grain. Finally, this information is saved in a two-dimensional computa- tional array and displayed on the computer screen placing color pixels on the corresponding position forming an image as is done in cellular automaton.

Novel Lossless Compression Method Based on the Fourier Transform to Approximate the Kolmogorov Complexity of Elementary Cellular Automata

We propose a novel, lossless compression algorithm, based on the 2D Discrete Fast Fourier Transform, to approximate the Algorithmic (Kolmogorov) Complexity of Elementary Cellular Automata. Fast Fourier transforms are widely used in image compression but their lossy nature exclude them as viable candidates for Kolmogorov Complexity approximations. For the first time, we present a way to adapt fourier transforms for lossless image compression. The proposed method has a very strong Pearsons correlation to existing complexity metrics and we further establish its consistency as a complexity metric by confirming its measurements never exceed the complexity of nothingness and randomness (representing the lower and upper limits of complexity). Surprisingly, many of the other methods tested fail this simple sanity check. A final symmetry-based test also demonstrates our method’s superiority over existing lossless compression metrics. All complexity metrics tested, as well as the code used to generate and augment the original dataset, can be found in our github repository: ECA complexity metrics1.

KAMAR: A Lightweight Feistel Block Cipher Using Cellular Automata

Wireless Multimedia Sensor Network (WMSN) is an advancement of Wireless Sensor Network (WSN) that encapsulates WSN with multimedia information like image and video. The primary factors considered in the design and deployment of WSN are low power consumption, high speed and memory requirements. Security is indeed a major concern, in any communication system. Consequently, design of compact and high speed WMSN with cryptography algorithm for security, without compromising on sensor node performance is a challenge and this paper proposes a new lightweight symmetric key encryption algorithm based on 1 D cellular automata theory. Simulations are performed using MatLab and synthesized using Xilinx ISE. The proposed approach supports both software and hardware implementation and provides better performance compared to other existing algorithms in terms of number of slices, throughput and other hardware utilization.

基于改进蛇优化算法的无人机路径规划研究

为提高无人机在复杂山区环境中飞行的可靠性和安全性,提出了一种改进蛇优化算法的无人机路径规划方法。首先,结合数字高程信息和复杂地形威胁构建了无人机环境模型和山峰威胁模型;其次,提出改进蛇优化算法,将传统蛇优化算法与元胞自动机进行融合用于无人机路径规划,并引入小生境技术和最优局部抖动,避免算法陷入局部最优,提高全局搜索能力;最后,在3种场景下进行仿真实验验证所提方法的有效性。实验结果表明,所提方法在3种复杂场景下平均路径长度分别为2.201、1.801和2.187 km,平均收敛时间为14.8、13.9和14.9 s,与其他路径规划算法相比具有良好的优越性,且所生成的路径对真实无人机运行具有良好的实际效果。

基于动态视觉算法的人员疏散预动作时间预测模型

在元胞自动机的基础上,提出一种考虑视觉遮挡的动态视觉算法,结合视觉算法建立了预动作时间模型。从跟随效应的角度出发,在作用机理的层面上解释预动作时间在不同布局场景内产生分布差异的原因。通过试验验证了模型的合理性并探究了场景中不同因素对人群预动作时间的影响,试验结果表明:(1)本模型能够体现不同类型疏散场景下人群预动作时间变化的趋势,且各场景的仿真试验结果与真实试验结果数值相近,本模型具备一定合理性;(2)在相同场景内,提高室内空间的视野通透性可以将人群的预动作时间均值缩短7.05%;(3)疏散过程中当引导员在人群中的占比从0达到20%时,人群的预动作时间均值缩短23.17 s;(4)在单房间场景中,人群密度从0.1人/m^(2)提升至0.9人/m^(2),人群预动作时间均值缩短9.66 s。提出的模型为疏散预动作时间的生成提供了一种新理论,为建筑疏散优化提供了一种新方法。

融合显著性检测的V型焊缝激光条纹提取

针对在背景亮度不均的情况下提取的V型焊缝坡口激光带准确度低的问题,提出一种基于视觉注意机制融合颜色特征和方向特征的方法。首先,使用FT(Frequency-Tuned)显著性检测算法获取焊缝图像中激光带的颜色显著图。然后,利用Gabor滤波器得到激光带的单方向特征图,对各方向图阈值分割消除噪声后等比例加权融合得到方向显著图。使用多层元胞自动机融合颜色显著图和细化后的方向显著图,得到最终的焊缝激光带条纹。实验结果表明该方法简单有效,效果较好,准确度高,为后续工作打下基础。

基于航道-船闸系统模型的内河多线船闸调度优化仿真

为了缓解船舶过闸需求和船闸服务能力之间的矛盾,以内河多线船闸为研究对象,利用元胞自动机原理建立了包括顺直段和弯曲段的航道船舶交通流模型,在考虑闸室分配规则、BL排样算法和多闸室并行调度规则的基础上建立了多线船闸调度优化仿真模型,并利用内河航运系统船舶交通组织方法,将船闸与航道两个子模型看成系统模型中的节点和通道,建立了船闸-航道一体的多线船闸系统调度优化模型。以长洲水利枢纽四线船闸为研究对象,根据建立的船舶交通流模型和多线船闸系统调度优化仿真模型对航道船舶交通流时空分布特性、船闸调度优化指标等进行了仿真分析。试验结果表明:船舶上下行平均延误较实际分别降低了10.3%、8.8%,上下行闸室利用率分别提高了7.4%、7.1%。

考虑视野范围模糊性的从众疏散模型

为了提高疏散模拟的真实性,针对行人视野范围模糊性的特点,应用膨胀-连通域算法建立一种视野范围动态变化模型,分析不同人员数量、熟悉环境人数占比下从众行为对疏散时间的影响。结果表明:从众行为对疏散时间的影响具有两面性。人数较少情况下,从众行为可减少行人随机移动,减少疏散时间;人数较多但熟悉环境行人占比较少时,盲目从众容易导致行人受群体错误方向影响偏离出口,增加疏散时间。视野范围动态变化模型较固定值模型的从众群体现象特征更明显。

初始化对交通元胞自动机模型稳定性的影响

针对现有交通元胞自动机模型运行初始不稳定,数据输出存在较长时间的初始波动问题,基于Fisher-Yates算法原理,设计出一种新的交通流初始化方法。该方法可以确保车辆从进入元胞空间到随后的演化更新,其位置及更新时机的随机性。通过对采用新交通流初始化方法的模型进行演化实验,结果表明:任意空间占有率条件下交通流的初始波动区间都在50步以内;当演化更新总步数达到3600步时,模型剔除初始波动区间的输出数据已充分收敛,这时模型运行已足够稳定。

考虑恐慌情绪感染的CA疏散模型算法研究

为探究恐慌状态对行人疏散效率的影响,基于情绪感染等相关理论,在探讨了情绪感染影响因素的基础上,利用元胞自动机模型、A*算法和SIS算法仿真了在有障碍物的情境下恐慌情绪对行人疏散的影响关系,使用MATLAB软件建模对情绪阈值、情绪衰减速率、行人密度等重要情绪因子进行仿真模拟。结果表明:在一定程度上恐慌情绪确实影响着正常的疏散行为,疏散时间随着情绪阈值的增加而逐渐缩短直至降低到某一值后基本不变;情绪衰减速率越大,感染者越能在短时间内降低恐慌值变为易感者,情绪衰减速率也是影响疏散的关键性因素;行人密度增大,则恐慌情绪在房间内反复传播进而不断加强,恐慌值增加会导致疏散时间更长。

基于元胞自动机的移动sink路径规划算法

为降低无线传感器网络中移动sink数据收集时延,提出一种基于元胞自动机的移动sink路径规划算法。首先,利用网格划分获得移动sink备选驻留点;然后,基于元胞自动机搜索获得移动sink驻留点集合,采用Von Neumann元胞邻居模型计算备选驻留点预估密度,根据备选驻留点预估密度与备选驻留点至移动sink间距离选择驻留点;最后,使用蚁群算法优化经过所有驻留点的移动sink路径。仿真结果表明:所提算法可以减少驻留点数目,缩短移动sink路径长度,从而降低数据收集时延。

基于涟漪扩散算法的元胞自动机人员疏散模型研究

为探究大型公共场所内应急疏散调控策略的合理性、有效性和安全性,开展了2类场所的应急疏散调控策略的仿真研究,记录疏散时间、疏散拥堵时间和路径拥堵程度作为衡量应急疏散调控措施的指标,建立以多对多涟漪扩散算法为核心的线性元胞自动机模型。结果显示,与原有的疏散路线相比,使用算法规划的应急疏散路径可以缩短疏散时间;与仅仅使用算法规划应急疏散路径相比,考虑单一的路径拥堵情况或路网结构而增加的调控措施可能与疏散初衷相悖;但在使用算法规划路径的基础上,综合考虑路径拥堵情况和路网结构而增设的调控措施,其疏散效果是最好的。研究结果可为应急疏散管理者提供紧急情况下的调控策略,避免疏散过程中出现的拥挤、踩踏等二次事故的发生,进而保障人群的疏散安全。

考虑诱导信息耦合作用的人群疏散模型

为探究多种诱导信息对疏散中人群的叠加作用,在元胞自动机离散环境的基础上提出动态扫描算法,快速获取行人的第一人称视角。基于第一人称视角定义人群运动信息和引导员指示信息耦合规则,结合元胞自动机建立考虑诱导信息耦合作用的人群疏散模型。模拟结果表明:跟随效应作用会导致出口使用不均衡;引导员信息强度的适量增加可以有效改善出口使用的均衡程度,但强度超过某定值时几乎所有行人按引导员指示运动,出口使用失衡;引导员位置分布对疏散过程产生明显影响,且引导员连线应尽可能与疏散路线垂直。该模型提供一种多种视觉诱导信息耦合作用的研究框架。

Genetic algorithms for determining the parameters of cellular automata in urban simulation

This paper demonstrates that cellular automata(CA) can be a useful tool for analyzing the process of many geographical phenomena.There are many studies on using CA to simulate the evolution of cites.Urban dynamics is determined by many spatial variables.The contribution of each spatial variable to the simulation is quantified by its parameter or weight.Calibration procedures are usually required for obtaining a suitable set of parameters so that the realistic urban forms can be simulated.Each pa-rameter has a unique role in controlling urban morphology in the simulation.In this paper,these pa-rameters for urban simulation are determined by using empirical data.Genetic algorithms are used to search for the optimal combination of these parameters.There are spatial variations for urban dynam-ics in a large region.Distinct sets of parameters can be used to represent the unique features of urban dynamics for various subregions.A further experiment is to evaluate each set of parameters based on the theories of compact cities.It is considered that the better set of parameters can be identified ac-cording to the utility function in terms of compact development.This set of parameters can be cloned to other regions to improve overall urban morphology.The original parameters can be also modified to produce more compact urban forms for planning purposes.This approach can provide a useful ex-ploratory tool for testing various planning scenarios for urban development.

一种针对QCA电路自动布局布线的混合策略研究

量子元胞自动机(Quantum Cellular Automata,QCA)电路的自动布局布线是在相关约束条件下自动放置电路单元、自动形成连线,实现门级或元胞级电路的设计过程,是QCA电路设计大型化、复杂化和系统化的必要工具.布局布线算法设计过程中最大的难题是如何解决“时钟同步”,随着二维时钟方案提出,该问题的解决方案变得更加策略化,但仍存在诸多缺陷,如成功率低,布局面积较大等.本文将二维时钟方案的布局布线问题抽象成组合优化模型,提出了一种基于遗传算法GA(Genetic Algorithm)和改进A^(*)算法的混合策略.两种算法相互配合搭建可能的电路布局,并通过精心设计的适应度函数,搜索满足时钟同步的个体,最终实现从硬件电路到二维时钟方案上的门级布局.实验结果表明,本算法在目前被广泛应用的二维时钟方案USE(Universal,Scalable and Efficient)上的布局成功率接近100%.相较当前世界上最先进的两个QCA布局布线工具fiction和Ropper,本算法可适用电路规模更大(逻辑门数量大于10),在成功率和生成布局面积上都有大幅度的优化.

基于无人机遥感影像的城乡居民点空间布局规划研究

采用传统规划方法对城乡居民点进行空间布局规划时,未对获取的图像进行预处理,导致方法存在去噪效果差、搬迁总距离大、聚集度总量低和规划效果差的问题。为此,提出基于无人机遥感影像的城乡居民点空间布局规划方法,结合基于K-奇异值分解算法和主成分分析方法,对无人机遥感影像进行去噪处理,消除遥感影像中存在的噪声,保留遥感影像的细节信息。根据获取的信息通过元胞自动机构建城乡居民点空间布局规划模型,完成城乡居民点空间布局规划。实验结果表明,所提方法的去噪效果好、搬迁总距离小、聚集度总量高、规划效果好。

利用元胞自动机算法的建筑形态生成设计

随着建筑学的发展和创新,建筑设计不再拘泥于传统的简单欧式几何,不规则、非线性的建筑形态也逐渐进入了大众的视野,用于表达某些建筑意向,增添建筑趣味,并拓展建筑多样性。分形迭代便是生成非线性形态的重要方法,元胞自动机作为一种重要的分形迭代算法,在城市设计中已经有较为广泛的运用,但在建筑设计中应用较少。研究通过构建参数化的迭代模型,引入城市空间、交通等因素作为目标控制和约束条件,按照一定的体块规则进行不断迭代,生成复杂多样的体量形态,改变迭代规则和迭代次数,可以对生形结果进行探究和优化,最终经过建筑化的处理,得到具体的建筑体量。运用元胞自动机进行建筑生形,是一种对非线性建筑形态设计的新的探索。