多平台海上协同搜索与路径优化策略研究

针对传统海上搜索研究中搜索平台与行为单一、缺乏协同的问题,建立多平台海上协同搜索路径优化模型,研究协同搜索与路径优化对策.在协同搜索策略方面,给出同构协同与异构协同搜索策略的定义,并设计不同规模的协同仿真场景;在路径优化策略方面,根据海上搜索平台的搜索特点,设计基于行为和基于智能算法的路径优化策略.在此基础上,对比研究不同规模的海上协同搜索策略与路径优化策略效果.结果表明:基于混合智能算法的路径优化效果普遍优于基于行为的搜索策略与单一算法,异构协同搜索策略能够充分发挥各平台优势、取长补短,取得了优于单平台和同构协同搜索的收益效果.     

基于记忆化搜索的分层网络最大流算法

当前,路由选择算法、计算机视觉图像切割以及机器学习领域的许多问题都可以归结为求解网络最大流.为了提高基于分层网络最大流算法的效率,提出了一种基于记忆化搜索策略的最大流算法,针对传统EdmondsKarp算法和Dinic算法重复搜索无效路径所导致的额外开销问题,设计了一种能够记录搜索状态的记忆化搜索策略,来避免重复搜索流网络中的无效部分.实例分析表明了记忆化搜索策略的高效性与可行性.最终实验结果表明,基于记忆化搜索的最大流算法执行效率优于传统的Dinic算法.     

异质信息网络的复杂条件社区搜索

社区是信息网络的重要属性, 社区搜索旨在寻找满足用户给定条件的节点集合, 是信息网络分析的重要研究内容. 异质信息网络由于包含更加全面、丰富的结构和语义信息, 所以异质信息网络的社区搜索近年来受到人们的广泛关注. 针对现有异质信息网络的社区搜索方法难以满足复杂条件社区搜索要求的不足, 定义了复杂条件社区搜索问题, 提出了考虑非对称元路径、受限元路径和禁止节点约束的搜索算法. 3种算法分别通过元路径补全策略、调整带标签的批量搜索策略和拆分复杂搜索条件的方式搜索社区, 同时针对禁止节点约束的搜索算法设计了基于剪枝策略和近似策略的优化算法以提高搜索效率. 在真实数据集上进行了大量实验, 实验结果证明了所提算法的有效性和高效性.     

多运动目标的多无人机协同搜索追踪策略

针对多无人机协同搜索追踪区域内多运动目标问题,考虑无人机的传感器与避撞等约束和目标随机运动等特征,提出了以垂线搜索为基础的多无人机协同搜索追踪策略.策略包含任务分配和航迹规划两部分.在任务分配部分,设计了航道均分垂线搜索算法,将搜索资源在区域内均匀分配,提高协同搜索效能.在航迹规划部分,设计了改进的人工势场算法,避免发生机间碰撞,保障飞行安全.在典型场景下,仿真验证了策略的有效性,相比传统垂线搜索方法,本策略能在保证安全的前提下,引导无人机群捕获更多的目标,有效提升了多无人机协同搜索追踪的效果.     

基于多超级节点的PMDN资源搜索策略

针对目前P2P分发网中本地数据命中率低和中心目录服务器(Directory Server)压力过大的问题,提出了基于多超级节点的PMDN(P2P-MediaDistribution Network)搜索策略MSS(Multi-Super-Peer Search),与传统的资源搜索策略相比,其不需频繁地查询中心服务器,且能充分考虑临近资源,因而系统服务质量得以大大提高.实验结果表明MSS策略与传统资源搜索策略相比,提高了本地命中率,缩短了用户的平均响应时间,也大大减轻了中心目录服务器的压力.     

基于MPEG-4的运动估计算法及硬件实现设计

提出的运动估计算法在块运动向量搜索中采用菱形搜索替代传统全搜索策略,在保证编码精度的条件下,减少了50%的搜索像素点,加快了编码速度.设计的运动估计硬件加速器方案正是采用这种搜索算法.仿真实验采用在标准的MPEG-4验证软件中植入硬件加速器模块的方法.其结果显示改进的4MV搜索策略在图像的PSNR和每帧图像的平均比特数方面与全搜索策略相当.这种新型的运动估计算法对设计运动估计硬件加速器有着重要的指导意义.     

一种基于边界搜索策略的匹配算法

基于灰度相关的图像匹配法,因匹配概率高而广泛应用于各个领域,但传统灰度相关算法的搜索策略是遍历性的,匹配速度较慢.为提高图像匹配速度,本文提出了一种基于边界搜索策略和矢量关系的匹配算法.该算法从矢量关系的角度,分析图像间差异.采用高维空间矢量表征图像所含信息,通过计算矢量之间的角度衡量待匹配区与模板的相关性.实验验证了采用的矢量角度作为图像间关系的测度的合理性和准确性,表明了该算法的图像匹配具有快速性和较高的准确性.     

基于进化稳定策略的遗传算法

为了解决传统遗传算法易陷入局部最优解的问题,在借鉴生物学中"进化稳定策略"的基础上,对传统的遗传算法进行了改进,提出了基于进化稳定策略的遗传算法.该算法的核心在于,稳定参数控制下的突变算子的构造,通过稳定参数的设定来稳定种群中最优个体的数目,并有目标地对最优个体进行突变操作,以达到快速扩大搜索空间、稳定群体中个体多样性的目的.仿真结果表明,该算法有效地避免了传统遗传算法中因选择压力过大造成早熟现象的发生,显著地提高了GA对全局最优解的搜索能力和收敛速度.这将使GA在众多实际的优化问题上具有更广泛的应用前景.     

语义搜索研究综述

语义搜索将语义Web技术引入搜索引擎,改善当前搜索引擎的搜索效果,近年来得到广泛关注.文章介绍了语义搜索领域的研究基础,包括研究现状和常用的研究方法,对语义搜索进行了分类研究和深入分析,语义搜索主要可分为基于传统搜索的增强型语义搜索和基于本体推理的知识型语义搜索;文章指出了语义搜索研究中存在的问题,并对未来开展语义搜索研究进行了总结和展望.     

基于本地插件的个性化搜索研究

个性化搜索是一种通过采集、预测用户的兴趣爱好,根据用户的兴趣模型优化搜索结果的新型搜索形武.但传统的个性化搜索采用的兴趣模型不够准确,所提出的动态调整策略不够完备,不能够准确反映用户的兴趣变化.针对这些问题,提出了以二维兴趣多边形作为兴趣模型,基于本地插件的个性化搜索方案.详细介绍了二维兴趣多边形的建模、动态调整策略产生的动机和算法、网页领域模型的建立及适用于兴趣多边形的相似度匹配算法,最后通过实验验证了该个性化搜索方案能够提高搜索质量.     

高技术与文化混搭：有趣的力量

Xrange即十一各务所的灵魂人物是洪裕钧和张淑征夫妻档,一位专攻工业设计,另一位则是建筑师,活跃于台湾的设计界。张淑征是马来西亚华侨,纽约哥伦比亚大学建筑学成后,年纪轻轻就进入世界知名的建筑师事务所Bernard Tschumi和OMA工作。     

单片机混合编程的实现

介绍了单片机的发展,当前应用较多的主流单片机,并对单片机的混合编程实现进行分析与讲解。     

Mixed language programming

Subroutines for numerical computation have in the past been written mainly in Fortran and in Algol 60, whereas most programming in the future is expected to be in more advanced languages, for example in Ada. It seems to be a great waste if it will become necessary to convert all existing numerical software into the new languages. What is needed is a facility to include subroutines written in the old languages into programs being written in the newer languages. In this paper an automatic procedure to facilitate the use of mixed languages is suggested, the purpose of the paper is to indicate the desirability for providing the required facilities, and to encourage discussion and further research in the area of mixed language programming.     

Mixed reality storytelling environments

The focus of this paper is the collaborative storytelling environments created as part of a three-year multi-disciplinary research project, KidStory. The project team, from the UK, Sweden and the USA, developed a series of story creation and telling tools and virtual environments for children aged 5–7 years. This paper concerns work with a Nottingham primary school to design and develop collaborative storytelling tools, including tangible interfaces devices and reactive spaces, with the aim of integrating these within the school context. The final set-up allowed children to dynamically produce story content, to create basic narrative structures and to retell their stories in a collaborative and adaptable physical space. Acknowledgements.This work has been conducted as part of the EU Esprit 29310 KidStory project. The authors acknowledge support from all partners (SICS/Maryland/KTH). Thanks also to the teachers and children at the primary school in Nottingham for their collaboration in this work. To download KidPad see http://www.kidpad.org.     

一种混合多变量签名方案

RGB（Red-Green-Blue）方案是一个可以抵抗已知代数攻击的混合多变量签名方案,但是同其他多变量公钥方案一样,它也具有公钥量大的缺点.针对RGB方案这一不足,本文采用循环公钥的思想对RGB方案进行优化,提出了一个新的方案——CyclicRGB混合多变量签名方案.与RGB方案相比较,CyclicRGB方案在降低公钥大小的同时,还具有更快的签名验证.通过本文方案和RGB方案的实验比较,结果表明本文方案的公钥大小约为RGB方案公钥大小的40%,CyclicRGB方案签名验证所需时间为RGB方案签名验证所需时间的60%.     

Mixed size tournament selection

 In genetic algorithms, tournament schemes are often applied as selection operators. The advantage is simplicity and efficiency. On the other hand, major deficiencies related to tournament selection are the coarse scaling of the selection pressure and the poor sampling accuracy. We introduce a new variant of tournament selection which provides an adjustable probability distribution, a fine-tuning facility for the selection pressure and an improved sampling accuracy at the cost of a minimal increase of the complexity and with almost no loss of efficiency.     

Mixed intelligent-multivariate missing imputation

In real applications, important rates of missing data are often found and have to be preprocessed before the analysis. The literature for missing imputation is abundant. However, the most precise imputation methods require long time, and sometimes specific software; this implies a significant delay to get final results. The Mixed Intelligent-Multivariate Missing Imputation (MIMMI) method is proposed as a hybrid missing imputation methodology based on clustering. The MIMMI is a non-parametric method that combines the prior expert knowledge with multivariate analysis without requiring assumptions on the probabilistic models of the variables (normality, exponentiality, etc.). The proposed imputation values implicitly take into account the joint distribution of all variables and can be determined in a relatively short time. The MIMMI uses the conditional mean according to the self-underlying structure of the data set. It provides a good trade-off between accuracy and both simplicity and required time to data preparation. The mechanics of the method is illustrated with some case-studies, both synthetic and real applications related with human behaviour. In both cases, acceptable quality results were obtained in short time.     

MiRA—Mixed Reality Agents

In recent years, an increasing number of Mixed Reality (MR) applications have been developed using agent technology — both for the underlying software and as an interface metaphor. However, no unifying field or theory currently exists that can act as a common frame of reference for these varied works. As a result, much duplication of research is evidenced in the literature. This paper seeks to fill this important gap by outlining “for the first time” a formal field of research that has hitherto gone unacknowledged, namely the field of Mixed Reality Agents (MiRAs), which are defined as agents embodied in a Mixed Reality environment.Based on this definition, a taxonomy is offered that classifies MiRAs along three axes: agency, based on the weak and strong notions outlined by Wooldridge and Jennings (1995); corporeal presence, which describes the degree of virtual or physical representation (body) of a MiRA; and interactive capacity, which characterises its ability to sense and act on the virtual and physical environment.Furthermore, this paper offers the first comprehensive survey of the state-of-the-art of MiRA research and places each project within the proposed taxonomy. Finally, common trends and future directions for MiRA research are discussed.By defining Mixed Reality Agents as a formal field, establishing a common taxonomy, and retrospectively placing existing MiRA projects within it, future researchers can effectively position their research within this landscape, thereby avoiding duplication and fostering reuse and interoperability.     

Interpolatory and Mixed Loop Schemes

This paper presents a new interpolatory Loop scheme and an unified and mixed interpolatory and approximation subdivision scheme for triangular meshes. The former which is C¹ continuous as same as the modified Butterfly scheme has better effect in some complex models. The latter can be used to solve the “popping effect” problem when switching between meshes at different levels of resolution. The scheme generates surfaces coincident with the Loop subdivision scheme in the limit condition having the coefficient k equal 0. When k equal 1, it will be changed into a new interpolatory subdivision scheme. Eigen‐structure analysis demonstrates that subdivision surfaces generated using the new scheme are C¹ continuous. All these are achieved only by changing the value of a parameter k. The method is a completely simple one without constructing and solving equations. It can achieve local interpolation and solve the “popping effect” problem which are the method's advantages over the modified Butterfly scheme.