利用朋友机制生成一类无标度网络

针对网络模型的演化问题,提出了一种新的无标度网络演化模型。该模型可以帮助人们从"朋友机制"捕捉网络形成的动态特性、了解该机制对网络最终结构的影响,对研究网络功能及网络上的动力学行为有一定的参考价值。通过理论分析与数据仿真证明,该演化模型具有无标度特征和小世界特征,比BA模型更接近于真实网络。     

钙离子信号及细胞调控信号网络动力学

钙离子(Ca²⁺)是细胞内广泛存在的一种重要的第二信使,参与并控制着几乎所有的生命活动过程.细胞信号分子网络对细胞正常和病理生理活动过程进行着精密调控,确保细胞各项生理功能有序地进行.本文综述了近些年本课题组关于细胞内钙信号及细胞信号网络动力学模型方面的研究进展,包括集团化钙离子通道释放局域钙信号、细胞全局钙波信号、内质网和线粒体钙微域调控钙信号和钙信号调控细胞凋亡信号网络动力学,以及细胞信号调控网络动力学等.这些理论工作为研究钙信号和蛋白质信号网络调控细胞复杂生命过程的动力学机制提供了方向和思路.     

Trail geometry gives polarity to ant foraging networks

Pheromone trails are used by many ants to guide foragers between nest and food. But how does a forager that has become displaced from a trail know which way to go on rejoining the trail? A laden forager, for example, should walk towards the nest. Polarized trails would enable ants to choose the appropriate direction, thereby saving time and reducing predation risk. However, previous research has found no evidence that ants can detect polarity from the pheromone trail alone. Pharaoh's ants (Monomorium pharaonis) produce elaborate trail networks throughout their foraging environment. Here we show that by using information from the geometry of trail bifurcations within this network, foragers joining a trail can adaptively reorientate themselves if they initially walk in the wrong direction. The frequency of correct reorientations is maximized when the trail bifurcation angle is approximately 60 degrees, as found in natural networks. These are the first data to demonstrate how ant trails can themselves provide polarity information. They also demonstrate previously unsuspected sophistication in the organization and information content of networks in insect societies.     

论回归差求和通用定理及某些系定理

本文在建立了非平面网络的不定阻抗矩阵的基础上,证明了在任意网络(即包含有源和耦合元件的平面及非平面网络)中,对应网络所有元素的回归差倒数之和等于该网络的秩(rank)元素阻抗及其传输导纳乘积之和等于读网络的零度,并讨论了有关激励点导纳求和的某些系定理。     

计算机网络的安全隐患与对策

随着计算机网络的迅速发展,安全问题受到人们越来越多的关注.计算机网络的脆弱及其潜在的威胁,使计算机用户深受其害,因此采取强有力的安全策略,保障网络主机安全是非常必要的.在网络日益复杂化、多样化的今天,如何保护网络和应用及及信息的安全,已成了各级网络管理人员最重视的事.     

具有热鲁棒性的适应性基因调控网络

通过对三节点基因调控网络的枚举、参数空间的随机采样以及动力学模拟, 找到具有热鲁棒性(即温度补偿)的适应性基因转录调控网络, 对其进行结构分析表明, 存在3种最基本的结构可以实现具有热鲁棒性的适应性动力学功能, 复杂的适应性网络都以此3种网络为核心骨架。为了考察三节点适应性网络的适应性对网络动力学中各参数改变的敏感度, 计算了各参数相应的控制系数。对控制系数的聚类分析表明, 三节点功能网络实现热鲁棒的机制为温度隔离, 即尽管网络中所有的速率参数都依赖于温度, 但仅输出节点的生成和降解速率明显偏离0且具有相反的符号, 大多数热鲁棒适应性都通过输出节点的拮抗平衡调节来实现。     

Self-similarity of complex networks

Complex networks have been studied extensively owing to their relevance to many real systems such as the world-wide web, the Internet, energy landscapes and biological and social networks. A large number of real networks are referred to as 'scale-free' because they show a power-law distribution of the number of links per node. However, it is widely believed that complex networks are not invariant or self-similar under a length-scale transformation. This conclusion originates from the 'small-world' property of these networks, which implies that the number of nodes increases exponentially with the 'diameter' of the network, rather than the power-law relation expected for a self-similar structure. Here we analyse a variety of real complex networks and find that, on the contrary, they consist of self-repeating patterns on all length scales. This result is achieved by the application of a renormalization procedure that coarse-grains the system into boxes containing nodes within a given 'size'. We identify a power-law relation between the number of boxes needed to cover the network and the size of the box, defining a finite self-similar exponent. These fundamental properties help to explain the scale-free nature of complex networks and suggest a common self-organization dynamics.     

基于迟滞噪声混沌神经网络的TDMA广播调度

分组无线网络的时分多址(Time Division Multiple Access,TDMA)广播调度问题是一个经典的NP-hard组合优化问题,可用神经网络求解.混沌动力学、随机游动和迟滞动力学均能够有效地提高神经网络的优化性能.为了提高迟滞动力学在噪声混沌神经网络中的优化能力,又不增加噪声混沌神经网络的参数,将噪声混沌神经网络的噪声幅值作为Sigmoid函数的中心参数,并通过神经元的输入变化来控制噪声幅值形成迟滞环,提出了一种新型的迟滞噪声混沌神经网络.对神经元状态演化行为的研究表明,该网络能够同时演化出混沌倒分岔、随机游动和迟滞等动力学行为.对分组无线网络的TDMA广播调度问题的仿真表明,提出的迟滞噪声混沌神经网络具有更好的优化性能.     

果蝇体极性基因网络的稳定性分析

果蝇的全基因组的序列测定早已完成,但是,对于基因之间是如何相互调控以实现复杂的生物功能,还需要深入的研究.认识并解析复杂的基因调控网络的构成和动力学机制,已成为现代生命科学中的前沿课题之一.在本文中,我们重点研究了果蝇的胚胎发育过程中图式形成的体极性基因网络调控.这一调控是通过相邻细胞中的基因网络的相互影响而达成的.本文主要考察这种基因网络调控对于初始条件的稳定性,以此说明生物胚胎发育对于初始条件的相对稳定性.我们发现该调控系统对于特定位置的干扰有极好的稳定性,对于整个系统的小干扰有良好的稳定性.     

Delay-distance correlation study for IP geolocation

Although many classical IP geolocation algorithms are suitable to rich-connected networks, their performances are seriously affected in poor-connected networks with weak delay-distance correlation. This paper tries to improve the performances of classical IP geolocation algorithms by finding rich-connected sub-networks inside poor-connected networks. First, a new delay-distance correlation model (RTD-Corr model) is proposed. It builds the relationship between delay-distance correlation and actual network factors such as the tortuosity of the network path and the ratio of propagation delay. Second, based on the RTD-Corr model and actual network characteristics, this paper discusses about how to find rich-connected networks inside China Internet which is a typical actual poor-connected network. Then we find rich-connected sub-networks of China Internet through a large-scale network measurement which covers three major ISPs and thirty provinces. At last, based on the founded rich-connected sub-networks, we modify two classical IP geolocation algorithms and the experiments in China Internet show that their accuracy is significantly increased.     

时变特性的人脑超网络构建方法及其分类

脑网络已在神经成像领域内得到广泛的应用。近年来,高阶功能连接网络和超网络在脑疾病诊断方面取得了较大的进步。然而,两种网络均存在相应的问题:高阶功能连接网络虽然考虑了网络的时变特性,但并不能处理网络中的空间多元交互问题;而超网络虽然可以表征多个大脑区域之间的相互关系,但并未考虑网络的动态特性。为了解决以上问题,融合了高阶功能连接网络和超网络的特性,提出一种具有时变特性的脑功能超网络的构建方法。该方法在考虑到脑网络时间动态性的基础上,基于最小绝对值收敛和选择算子(least absolute shrinkage and selection operator, LASSO)方法进行脑功能超网络构建,并将该网络应用至脑疾病诊断中。该网络消除了上述两个网络的弊端,结果表明,该方法的分类准确率达到86.36%,显著高于之前所提出的方法,能有效提高抑郁症的分类表现,具有重要的理论意义和临床价值。     

Evaluation on Stability of Stope Structure Based on Nonlinear Dynamics of Coupling Artificial Neural Network

The nonlinear dynamical behaviors of artificial neural network (ANN) and their application to science and engineering were summarized. The mechanism of two kinds of dynamical processes, i.e. weight dynamics and activation dynamics in neural networks, and the stability of computing in structural analysis and design were stated briefly. It was successfully applied to nonlinear neural network to evaluate the stability of underground stope structure in a gold mine. With the application of BP network, it is proven that the neuro-com-puting is a practical and advanced tool for solving large-scale underground rock engineering problems.     

基于复杂网络的城市交通系统复杂性概述

主要同顾了复杂网络在城市交通网络中的相关研究概况,包括城市交通网络拓扑结构复杂性、道路交通流与复杂网络及网络交通流与复杂网络之间相结合的研究,并就交通系统特有的属性提出了综合应用复杂网络、系统科学、非线性动力学、城市交通等理论来研究城市交通复杂性的重要意义。最后对进一步需要讨论和分析的问题进行了展望。     

空天海地一体化观测网络的任务管理探讨与展望

观测网络的网络拓扑动态性、资源异构性及其系统复杂性给空天海地一体化观测网络的任务管理带来了巨大的挑战。本文首先研究探讨面向一体化观测网络及其任务管理的主要内容、关键技术及其面临的挑战。为了应对观测网络面临的问题,本文将基于ACP的平行智能方法引入到观测网络任务管理领域,提出平行观测网络的概念与架构。平行观测网络首先通过人工观测网络系统来模拟实际观测网络系统;然后进行大量不同观测场景及事件的计算实验进行训练与评估;最后,通过平行执行来滚动在线优化人工和实际观测网络系统,从而实现对复杂观测网络的描述智能、预测智能和引导智能。因此,可以实现根据观测环境及任务需求快速灵活地组网,提高网络的灵活性及任务管理效率。平行观测网络将为国家网络数据安全、能源与资源开发、环境监测、灾害预报预警等研究提供有效支撑。     

Experimental Analysis of Link Estimation Methods in Low Power Wireless Networks

Wireless sensor networks are envisioned to be an integral part of cyber-physical systems,yet wireless networks are inherently dynamic and come with various uncertainties.One such uncertainty is wireless communication itself which assumes complex spatial and temporal dynamics.For dependable and predictable performance,therefore,link estimation has become a basic element of wireless network routing.Several approaches using broadcast beacons and/or unicast MAC feedback have been proposed in the past years,but ...     

Evidence for dynamically organized modularity in the yeast protein-protein interaction network

In apparently scale-free protein-protein interaction networks, or 'interactome' networks, most proteins interact with few partners, whereas a small but significant proportion of proteins, the 'hubs', interact with many partners. Both biological and non-biological scale-free networks are particularly resistant to random node removal but are extremely sensitive to the targeted removal of hubs. A link between the potential scale-free topology of interactome networks and genetic robustness seems to exist, because knockouts of yeast genes encoding hubs are approximately threefold more likely to confer lethality than those of non-hubs. Here we investigate how hubs might contribute to robustness and other cellular properties for protein-protein interactions dynamically regulated both in time and in space. We uncovered two types of hub: 'party' hubs, which interact with most of their partners simultaneously, and 'date' hubs, which bind their different partners at different times or locations. Both in silico studies of network connectivity and genetic interactions described in vivo support a model of organized modularity in which date hubs organize the proteome, connecting biological processes--or modules--to each other, whereas party hubs function inside modules.     

Levenberg-Marquardt神经网络在煤矿作业人员人因可靠性评价中应用研究

依据人因可靠性原理、事故致因理论,结合煤矿生产系统的特点,提出了观测可靠度的概念,确立了一系列便于统计和赋值的人因可靠性评价指标.针对人因失误事件过程的动态性、复杂性以及数据的不完整性,利用BP神经网络对非线性动态系统的自学习性和自适应性的特点,建立了基于BP神经网络的煤矿作业人员人因可靠性评价模型.运用Levenberg-Marquardt算法改进的BP神经网络,克服了收敛速度慢,容易陷入局部极小点的缺点,提高了预测精度和稳定性.对于岗位工龄短或有效记录不足的煤矿作业人员,采用BP神经网络模型进行了人因可靠性评价.评价结果表明,基于BP神经网络的煤矿作业人员人因可靠性评价方法具有较好的适用性和可行性.     

基于分布式流的复杂网络上边级联失效

考虑现实网络中流的分布式传输方式和边的负载-容量关系,提出了一个带有可调权重参数的边级联失效模型.依据新的度量网络鲁棒性指标,探讨了两种典型复杂网络由蓄意边攻击而引发的级联失效行为.仿真结果表明,存在最优参数值使得网络达到最强抵制边级联失效的鲁棒性,能够显著降低灾害动力学发生的可能性.而且,网络的拓扑结构和平均度均对网络鲁棒性产生了影响。     

局部信息流通均衡网络的动态随机生成——模型与算法实现

考察信息流通网络在局部流通的前提下并且信息流通过程中没有损耗的情形,研究均衡网络的结构特性尤其是动态生成均衡网络的规律。本文的主要结果一是建立并实现了局部信息流通网络的动态随机生成进程;二是针对两类典型的具有核心-边缘结构的局部信息流通网络给出了其均衡网络结构特性的定理。