基于FINS协议的Controller Link网监控系统设计

Controller Link（CLK）网是OMRON开发的一种应用广泛的工厂自动化（FA）网络,其节点为可编程序控制器（PLC）和计算机,FINS是OMRON FA网络的通信协议。CLK网可以实现节点间的数据链接及信息通信功能。在工程应用中,要求在计算机节点上监控网络中的各个PLC节点。该文利用Visual C++6.0设计了基于FINS协议的CLK网监控系统,并成功地用于城市污水处理系统的实时监控。     

基于萤火虫算法的无线传感器网络节点重部署策略

节点部署是无线传感器网络研究的重要问题之一.针对节点部署过程中的能量空洞问题,提出了一种基于萤火虫算法(FA)的节点重部署(NRBFA)策略.首先,在节点随机部署的传感器网络中,利用k-means算法进行分簇并引入冗余节点;然后,利用FA移动冗余节点,以分担簇头(CH)负载并均衡网络中节点的能耗;最后,再次利用FA寻找...     

Internet网络延迟分析与评测

Ｉｎｔｅｒｎｅｔ是当前使用最广泛的广域网,但它的网络延迟也在逐渐增加。本文对Ｉｎｔｎｅｒｔ的网络延迟进行了较为全面的分析,并介绍了几种减少网络时延的技术。     

两种因特网服务模型的比较研究

未来的计算机网络将是一种能够提供多种有同服务,以支持多种不同应用需求,有着集成服务（ｉｎｔｅｇｒａｔｅｄ ｓｅｒｖｉｃｅｓ）支持能力的网络．这种网络是通过在统一的分组交换网络上实现各种不同的服务性能保证机制来构造的．针对止目前广泛研究的两种不同因特网服务模型进行比较研究,分析它们各自组成部件的功能入作用,比较两者之间存在的内在联系,从而进一步提出了一种融合两者优点的组合扩展模型,并以此为基础提出了     

基于有色Petri网的入侵检测系统的研究

随着Internet的发展,各种网络入侵事件层出不穷,入侵检测系统作为一种主动的网络防护技术,正广泛运用于Internet中。Petri网作为一种工具正广泛应用于各种领域。本文首先分析了网络入侵的一般过程,然后提出了一种基于有色Petri网的入侵检测方法,该方法对建立一个有效的入侵检测系统有着一定的意义。     

贝叶斯网在态势评估中的应用

作为一种知识推理和进行概率推理的框架,贝叶斯网络在具有内在不确定性和决策问题中得到了广泛的应用。因果推理是态势评估中的一个重要环节,用贝叶斯网找出态势假设和事件之间的潜在关系,正是态势评估所需完成的功能。根据态势与实践之间不同的连接关系建立了态势评估的贝叶斯网络模型,并分别介绍了相应的信息传播算法,最后一个实例来说明该网络的计算过程。     

集散控制系统网络结构的研究

为了提高集散控制系统通信的可靠性、稳定性、抗干扰性和可扩展性,降低集散控制系统通信的故障率,提出了一种基于工业以太网的网络通信方式,并验证了该通信网络的可行性。该网络是一种采用分布式、冗余式、立体式的多层次网络结构。此结构使网络的负荷均匀分配,降低了网络的故障率,并使集散控制系统的网络向开放化、信息化的方向发展。     

HSRP技术在MDCN网中的应用

路由热备份技术(HSRP)是现如今使用最为广泛的网络设备冗余技术,它在移动数据通信网络(MDCN)之中有着广泛的应用。热备份能够将两台或是多台的设备进行模拟,并通过一个平台的网络服务开展日常的应用,如果备份设备出现了故障,还能够让网络技术进行及时更新。     

一种基于频谱的电子邮件智能处理分析方法

随着ＵＩＮＴＥＲＮＥＴ的迅猛发展,信息安全成为人们越来越关心的问题,本文从应用最广泛的电子邮件服务入手,提出了一种简单易行的基于频谱的电子邮件分类系统,可以在效的增强企业网络的信息安全。并给出了系统的基本框架和实施策略。     

物理隔离和网闸的技术原理浅析

物理隔离技术是一种越来越受到重视的安全技术,它在需求高安全性的部门得到越来越广泛的应用。本文从拓扑学的观点分析了物理隔离技术在OSI七层协议模型中所处的角色,阐述了网络隔离的几种形式以及物理隔离在网络隔离中的地位。在物理隔离技术中,数据的转发是隔离技术关键。在分析了传统数据转发模型的缺陷的基础上,建立了物理隔离中的数据安全转发模型,对物理隔离的数据转发的安全措施进行了理论研究,并建立了内网的安全策略。     

萤火虫算法的改进分析及应用

针对萤火虫算法(FA)在求解有约束全局优化问题时,存在初始种群不易产生、相对吸引力的大小与萤火虫的绝对亮度无关、惯性权重没有充分利用目标函数信息、不能更好地控制和约束萤火虫的移动距离等缺点,提出一种改进的萤火虫算法。首先,给出了一种基于遗传算法(GA)的初始种群产生方法,提高了初始种群的产生速度;其次,给出了一种基于目标函数的动态自适应惯性权重萤火虫算法,以提高萤火虫算法收敛速度;另外,给出了一种相对吸引力大小与萤火虫的绝对亮度有关的吸引力的计算方法;最后,为了控制和约束萤火虫位置的移动距离,将压缩因子引入到萤火虫算法的位置更新公式中,从而提高了算法收敛速度。4个测试函数的计算结果表明,与标准FA和基于惯性权重的萤火虫算法相比,改进的萤火虫算法运算速度明显提高,迭代次数明显减少,从而验证了改进萤火虫算法的有效性。     

Language acceptability of finite automata based on theory of semi‐tensor product of matrices

Using the theories of many‐valued logic and semi‐tensor product of matrices (STP), this paper investigates how to mathematically determine whether or not a regular language is recognized by finite automata (FA). To this end, the dynamic behaviour of FA is first formulated as bilinear dynamic equations, which provides a uniform model for deterministic and non‐deterministic FA. Based on the bilinear model, the recognition power of FA understanding of regular languages is investigated and several algebraic criteria are obtained. With the algebraic criteria, to judge whether a regular sentence is accepted by a FA or not, one only needs to calculate an STP of some vectors, rather than making the sentence run over the machine as traditional manners. Further, the inverse problem of recognition is considered, an algorithm is developed that can mathematically construct all the accepted sentences for a given FA. The algebraic approach of this paper may be a new angle and means to understand and analyse the dynamics of FA.     

Development of firefly algorithm via chaotic sequence and population diversity to enhance the image contrast

Nature-inspired algorithms have been applied in the optimization field including digital image processing like image enhancement or segmentation. Firefly algorithm (FA) is one of the most powerful of them. In this paper two different implementation of FA has been taken into consideration. One of them is FA via lévy flight where step length of lévy flight has been taken from chaotic sequence. Chaotic sequence shows ergodicity property which helps in better searching. But in the second implementation chaotic sequence replaces lévy flight to enhance the capability of FA. Population of individuals has been created in every generation using the information of population diversity. As an affect FA does not converges prematurely. These two modified FA algorithms have been applied to optimize parameters of parameterized contrast stretching function. Entropy, contrast and energy of the image have been used as objective criterion for measuring goodness of image enhancement. Fitness criterion has been maximized in order to get enhanced image with better contrast. From the experimental results it has been shown that FA with chaotic sequence and population diversity information outperforms the Particle swarm optimization and FA via lévy flight.     

User evaluation: Synthetic talking faces for interactive services

facial animation (FA) will be. We have undertaken experiments on 190 subjects in order to explore the benefits of FA. Part of the experiment was aimed at exploring the objective benefits, i.e., to see if FA can help users to perform certain tasks better. The other part of the experiment was aimed at subjective benefits. At the same time comparison of different FA techniques was undertaken. We present the experiment design and the results. The results show that FA aids users in understanding spoken text in noisy conditions; that it can effectively make waiting times more acceptable to the user; and that it makes services more attractive to the users, particularly when they compare directly the same service with or without the FA.     

分层Mobile IP中的FA容错方案

介绍了Mobile IP和分层Mobilc IP的原理，分析了分层Mobile IP中的FA容错问题。在介绍已有的几种容错方案的基础上，提出了一种有效的FA容错方案，它利用同一级的FA相互作备份，能够迅速将发生故障的FA旁路掉，减少数据包的丢失。     

Extraction,selection and ranking of Field Association (FA) Terms from domain-specific corpora for building a comprehensive FA terms dictionary

Field Association (FA) Terms—words or phrases that serve to identify document fields are effective in document classification, similar file retrieval and passage retrieval. But the problem lies in the lack of an effective method to extract and select relevant FA Terms to build a comprehensive dictionary of FA Terms. This paper presents a new method to extract, select and rank FA Terms from domain-specific corpora using part-of-speech (POS) pattern rules, corpora comparison and modified tf-idf weighting. Experimental evaluation on 21 fields using 306 MB of domain-specific corpora obtained from English Wikipedia dumps selected up to 2,517 FA Terms (single and compound) per field at precision and recall of 74–97 and 65–98. This is better than the traditional methods. The FA Terms dictionary constructed using this method achieved an average accuracy of 97.6% in identifying the fields of 10,077 test documents collected from Wikipedia, Reuters RCV1 corpus and 20 Newsgroup data set.     

Front address structure for high luminous efficacy and low address voltage in ACPDPs

Abstract— 8‐in. AC plasma display panels with front address (FA) structures were developed. Deep barrier ribs, high‐Xe‐content gas, and long sustain gaps were applied to FA structures to achieve high luminous efficacy. The FA structures have several advantages over conventional structures. Because address electrodes are closer to sustain electrodes, FA PDPs can be driven at lower address voltages, under the condition of deep barrier ribs or high‐Xe‐content gas, than conventional PDPs. A disadvantage of FA PDPs is relatively high capacitance between the sustain electrodes and address electrodes compared to that of conventional PDPs.     

基于因素分析的复合神经网络及其在软测量中的应用

针对工业生产中,众多因素对生产影响程度不同的特点,提出了一种基于因素分析的复合神经网络(FA-MNN)模型.介绍了FA-MNN模型的结构,改进了神经网络的学习算法,并将其应用于氧化铝高压溶 出过程中苛性比值及溶出率的软测量,利用现场实际运行数据进行仿真,结果表明FA-MNN模型能有效实现苛性比值及溶出率的在线检测.     

Thermal buckling optimisation of composite plates using firefly algorithm

Abstract

Composite plates play a very important role in engineering applications, especially in aerospace industry. Thermal buckling of such components is of great importance and must be known to achieve an appropriate design. This paper deals with stacking sequence optimisation of laminated composite plates for maximising the critical buckling temperature using a powerful meta-heuristic algorithm called firefly algorithm (FA) which is based on the flashing behaviour of fireflies. The main objective of present work was to show the ability of FA in optimisation of composite structures. The performance of FA is compared with the results reported in the previous published works using other algorithms which shows the efficiency of FA in stacking sequence optimisation of laminated composite structures.     

Improving K-means clustering with enhanced Firefly Algorithms

In this research, we propose two variants of the Firefly Algorithm (FA), namely inward intensified exploration FA (IIEFA) and compound intensified exploration FA (CIEFA), for undertaking the obstinate problems of initialization sensitivity and local optima traps of the K-means clustering model. To enhance the capability of both exploitation and exploration, matrix-based search parameters and dispersing mechanisms are incorporated into the two proposed FA models. We first replace the attractiveness coefficient with a randomized control matrix in the IIEFA model to release the FA from the constraints of biological law, as the exploitation capability in the neighbourhood is elevated from a one-dimensional to multi-dimensional search mechanism with enhanced diversity in search scopes, scales, and directions. Besides that, we employ a dispersing mechanism in the second CIEFA model to dispatch fireflies with high similarities to new positions out of the close neighbourhood to perform global exploration. This dispersing mechanism ensures sufficient variance between fireflies in comparison to increase search efficiency. The ALL-IDB2 database, a skin lesion data set, and a total of 15 UCI data sets are employed to evaluate efficiency of the proposed FA models on clustering tasks. The minimum Redundancy Maximum Relevance (mRMR)-based feature selection method is also adopted to reduce feature dimensionality. The empirical results indicate that the proposed FA models demonstrate statistically significant superiority in both distance and performance measures for clustering tasks in comparison with conventional K-means clustering, five classical search methods, and five advanced FA variants.