TCP拥塞控制分析模型

介绍了研究传输控制协议 (TCP)拥塞控制问题的各种分析模型 ,指出了研究TCP拥塞控制的主要目标 .对当前国内外的研究动态给予了讨论 ,并对当前现有模型根据其流量范围和使用的分析工具进行了分类概括 .最后概要地阐述了在端到端和在网络中进行拥塞控制的相互关系     

The behavior of the homozygous and heterozygous sub-types of rats which are genetically-selected for diabetes insipidus: A comparison with Long Evans and Wistar stocks

Several aspects of spontaneous and conditioned behavior (food and water intake, locomotion and emotionality, passive and active avoidance acquisition and retention) of standard (albino and pigmented) rats, and rats heterozygous (HEDI) and homozygous (HODI) for diabetes insipidus, are reviewed. As would be expected, HODI rats have been repeatedly found to consume far more fluid than either HEDI or control rats. Pigmented rats appear to be more active than albinos. HODI rats exhibit less marked emotional responses than do control rats, among which the pigmented ones exhibit the highest emotionality. Light aversion is more evident in albino than in pigmented rats. No differences are found among HEDI, HODI and normal Long Evans rats. It is quite difficult to provide a clear-cut statement concerning inter-strain differences in passive avoidance behavior, possibly because of the variety of techniques employed. In any case, HODI rats do not perform worse than normal controls do. In one-way active avoidance paradigms, pigmented rats perform better than albinos, and the performance of HODI rats does not differ from that of controls. In two-way avoidance paradigms, albinos appear to outperform pigmented rats. Once again, there are no obvious differences between HODI and control animals.In addition to indicating that HODI rats may actually be less emotional than the other groups of rats reviewed here, the studies described once again fail to confirm the previously alleged functions of vasopressin in memory consolidation.     

机器人避障功能的设计

本文介绍了通过硬件的连接以及利用汇编语言编写简单程序使机器人实现避障功能.     

Using genetically-defined rodent strains for the identification of hippocampal traits relevant for two-way avoidance behavior: a non-invasive approach

Summary Genetically-defined rodent strains permit the identification of hippocampal traits which are of functional relevance for the performance of two-way avoidance behavior. This is exemplified here by analyzing the relationship between infrapyramidal mossy fibers (a tiny projection terminating upon the basal dendrites of hippocampal pyramidal neurons) and two-way avoidance learning in about 800 animals. The necessary steps include 1) identification of structural traits sensitive to selective breeding for extremes in two-way avoidance, 2) testing the robustness of the associations found by studying individual and genetical correlations between hippocampal traits and behavior, 3) establishing causal relationships by Mendelian crossing of strains with extreme structural traits and studying the behavioral consequences of such structural randomization, 4) confirming causal relationships by manipulating the structural variable in inbred (isogenic) strains, thereby eliminating the possibility of genetic linkage, and 5) ruling out the possibility of spurious associations by studying the correlations between the hippocampal trait and other behaviors known to depend on hippocampal functioning.In comparison with the classical lesion approach for identifying relationships between brain and behavior, the present procedure appears to be superior in two aspects: it is non-invasive, and it focuses automatically on those brain traits which are used by natural selection to shape behaviorally-defined animal populations, i.e., it reveals the natural regulators of behavior.     

无线多媒体传感器网络自适应拥塞控制算法

针对无线多媒体传感器网络(WMSN)中多对一通信时产生的网络拥塞问题,提出了一种自适应的WSMN网络拥塞控制算法ACCP。通过结合速率控制和资源调度,并采用分簇的网络结构,根据簇首及簇内的拥塞指标,来分别启动对应的拥塞控制机制:当簇首发生短时间拥塞时,就启动属于资源调度的网络内存储管理机制,来暂时减缓网络内过多数据包;但当簇中的存储节点也无法容纳过量的数据包时,速率控制就启动,让流量减缓下来,并且只调整数据实时性要求较低的数据流的速率,以达到控制流量、减缓甚至消除网络拥塞的目的。仿真结果显示:ACCP在传送速率不同下,可以比InS、HCCP更有效的控制网络拥塞的情况,而在比较缓存容量不同的情况下,虽然ACCP只比HCCP能够稍微改善网络拥塞的情况,但却能够大幅度改善InS的数据包丢失率。     

一种基于速度势场的局部在线避碰方法

本文以势场方法的思想为出发点，提出一种基于速度势场的自主移动机器人的局部避碰方法。该方法可以更好地利用相对速度的信息，在存在移动障碍物和环境中得到较好的局部在线避碰效果。     

微小型LTA飞行机器人主动避障控制研究

采用基于行为的研究方法，设计了一种基于电机神经元网络的微小型LTA飞行机器人主动避障控制方法。该方法通过电机神经元网络选取飞行机器人的飞行动作，采用增强式学习方法对飞行结果作出评判，利用评判结果在线修改网络权值，从而实现微小型LTA飞行机器人在未知、动态环境中的主动避障。飞行机器人的仿真运行分析，验证了该方法的有效性。     

多瓶颈节点ATM网络预测拥塞控制方法

应用广义预测控制(GPC)方法,对多瓶颈节点的网络设计了一种ABR反馈控制方法,保证了闭环控制的稳定性,降低了网络的拥塞程度和持续时间,最大化了网络资源的利用率,同时极小化了高优先级业务对系统性能的影响.     

基于数据仓库的城市交通拥堵疏导数据管理

从分析城市交通拥堵疏导管理决策中数据来源的多样性及异构性出发，为实现对各种数据和信息的汇总和综合，提出了城市交通拥堵疏导管理数据仓库的体系结构，探讨了该体系结构建立中的数据抽取与转换，元数据、中央数据库与数据集市，数据访问与分析等重要组成部分，并且，通过主题，维度，粒度及分割等概念的引入，着重研究了该数据仓库中的数据组织与数据模型的建立，从而为城市交通拥堵疏导管理决策提供一个统一、综合的数据环境。     

TCPS-jump:卫星信道拥塞控制新算法

由于卫星通信系统具有的长时延特性以及无线信道误码率高的特点 ,传统的应用于Internet的TCP拥塞控制机制在卫星通信链路上进行TCP数据包传输时不能充分利用网络的吞吐量 ,导致网络效率低下 .因此提出一种新的基于TCP拥塞控制窗口大小的改变新算法TCP Sjump ,旨在有效提高卫星通信链路上的网络利用率 ,并给出了在实际环境中和利用计算机进行仿真试验的研究模型