时钟同步的RMD聚集预留状态管理

区分服务网络资源管理方案RMD（Resource Management in Differentiated Services）基于分布式信令,简单、可扩展。分析了RMD中的聚集预留状态管理算法,指出其无法保证资源状态的准确性,从而对聚集流的服务质量产生不利影响。针对RMD存在的问题,提出基于时钟同步的聚集预留状态管理方案,该方案包括时钟同步机制和路由器内的实现方法。仿真实验证明该方案可以保证聚集预留状态的准确性。     

基于计算机视觉与 BIM 的裂缝可视化管理方法

对结构表面裂缝进行持续检监测与管理对保障结构安全具有重要意义。为实现结构裂缝自动识别与管理,提出了一种基于计算机视觉与建筑信息模型(BIM)的裂缝识别、矢量化处理与可视化管理方法。首先基于深度学习的图像识别方法,从相机拍摄的结构表面图像中提取出裂缝形态的栅格图像;其次,提出了一种裂缝形态栅格图像的自动矢量化方法,获取裂缝形态关键点坐标;最终,使用 Dynamo 程序实现裂缝 BIM模型的自动建模与可视化。该方法可以获取裂缝的拓扑形态信息,并显著降低裂缝信息的存储数据量与可视化难度。通过开展 BIM 构件的碰撞分析,还可准确识别裂缝属于结构中的哪个构件,将裂缝所属的构件编号信息与裂缝宽度信息作为裂缝图元参数写入 BIM 模型,实现裂缝矢量化与裂缝 BIM 模型自动化建模与管理,为大范围、大批量的裂缝自动化检监测与管理提供参考。     

图聚集技术的现状与挑战

图聚集技术旨在获取能够涵盖原图大部分信息的简洁超图,用于提炼概要信息、解决存储消耗和社交隐私保护等问题.对当前的图聚集技术进行研究,综述了现有图聚集技术中的分组方法并对其进行分类,将分组标准划分为基于属性一致性、基于邻接分组一致性、基于关联强度一致性、基于邻接顶点一致性和基于零重建误差这5类;在高层次上将各分组标准概括为基于属性、基于结构和同时基于属性和结构的图聚集.较为全面地总结和分析了当前图聚集技术的研究现状和进展,并探讨了未来研究的方向.     

云计算环境下动态数据聚集算法研究

云计算技术的普及带动了数据的增长,为了对云环境下动态数据进行管理,防止数据损坏甚至丢失,方便后续利用,需要对云计算环境下动态数据进行聚集。但目前大多数算法都是基于线性时间概率计数的数据聚集算法,通过数据聚集操作在中间节点预先对数据进行处理,去除数据冗余,减少数据传输,实现节能,对于云计算环境下数据聚集操作存在的重复计数问题,通过研究对副本不敏感的概要结构并优化某些特性,从而完成数据聚集,但这种方法存在占用的存储空间较大,且不能保证动态数据聚集的准确性的问题。为此,提出一种基于粒子群优化算法的云计算环境下动态数据聚集算法,该算法通过对云计算环境下动态数据聚集算法数学模型进行分析,在此基础上,提出基于粒子群优化算法的云计算环境下动态数据聚集算法。首先对云计算环境中的动态数据结构模型进行分析,完成对云计算环境下动态数据的离散样本频谱特征的计算,实现云计算环境下动态数据聚集样本的特征提取和信息模型构建。针对粒子群算法收敛速度慢的问题,本文通过混沌映射方法对其进行优化,通过生成混沌序列,解决粒子群算法存在的问题,利用粒子群优化算法进行特征聚集,从而完成云计算环境下动态数据聚集算法。实验结果表明,本文所提算法能够有效提高动态数据聚集的可靠性和稳定性,降低聚集时间,减少所占内存空间,具有较强的实践性,为该领域的发展创造了条件。     

一种分布式数据流相关性分析的有效方法

在分布式数据流中,数据流之间相关性分析可以揭示被监测对象之间存在的内在联系。提出了一个基于基窗口的相关系数的计算方法,该方法先将计算相关系数的公式变形为由适合基窗口聚集的因子组成,然后用基于基窗口的方法聚集每个因子。基于基窗口的聚集方法是将窗口中的数据项划分成一系列基窗口并分别对基窗口进行计算。当窗口随机滑动后,新窗口中数据项的聚集可以部分地利用上一次窗口聚集的结果。模拟实验表明,与每次对窗口中所有数据进行聚集相比,基于基窗口的方法可以有效地降低数据流相关系数的计算时间。     

基于形态学的图像预处理技术研究

研究了基于形态学的背景抑制方法.对单结构元素的形态滤波进行分析,针对其不足,提出基于双结构元素顺序形态滤波的预处理方法.实验结果表明,双结构元素顺序形态滤波对于高频背景的抑制效果比单一结构元素好,经过图像分割后,剩余少量噪声,有利于后续目标检测.     

汽车牌照识别技术研究

本文分析了汽车牌照的几何特征和成像特点,提出了一种基于边缘检测和Hough变换的汽车牌照定位方法和基于图像投影的车牌字符分割方法。通过分析车牌号码中的字符图像特点,提出了基于字符图像几何形态和笔画结构的字母和数字识别方法,以及基于汉字结构知识的汉字识别方法,从而实现了汽车牌照的自动识别。     

基于时空轨迹的移动对象汇聚模式挖掘算法

移动对象的聚集模式是时空轨迹模式挖掘中的重要课题,它研究移动对象群体在多个连续时刻中的空间聚集问题。现有的聚集模式基于共现模式进行定义,挖掘结果中夹杂大量非运动的聚集群体,严重影响模式挖掘的效果。为了解决此问题,本文提出了基于群体运动过程建模的汇聚模式。该模式定义从群体运动形态出发进行设计,准确识别向心运动的移动群体,有效排除非聚集类型运动群体的干扰。本文设计并实现了汇聚模式挖掘（Converging pattern mining,CPM）算法,该算法首先定位密度峰值点,确定候选的汇聚中心区域,然后依次识别每个时刻的汇聚群体,按照群体汇聚的持续性要求识别汇聚模式。基于真实轨迹数据进行实验,结果验证了本文提出的CPM算法在挖掘效果和算法效率的有效性。     

小世界网络模型下的MA特性分析

介绍了网络的小世界特性,分析了小世界特性下多代理体系结构和路由算法的特性,分别提出了自组织结构中的资源发现算法和基于聚集度的簇头选举算法并作了定性分析.     

聚集显露模式在入侵检测中的应用研究

分析了基于轴属性的关联规则方法的局限性,提出了基于聚集显露模式的入侵检测方法。通过采用聚集显露模式分类,克服了因领域知识不足而导致的大量不相关规则的问题。实验表明,基于聚集显露模式分类的入侵检测方法可以有效地提高基于主机的入侵检测的检测效率。     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

The Distributed Time-Triggered Simulation Scheme: Core Principles and Supporting Execution Engine

Distributed real-time simulation is a young technology field but its practice is under increasing demands. In recent years the author and his collaborators have been establishing a new approach called the distributed time-triggered simulation (DTS) scheme which is conceptually simple and easy to use but widely applicable. The concept was initiated in the course of developing a new-generation object-oriented real-time programming scheme called the time-triggered message-triggered object (TMO) programming scheme. Some fundamental issues inherent in distributed real-time simulation that were learned during recent experimental studies are discussed along with some approaches for resolving the issues. An execution engine developed to support both the TMOs engaged in control computation and the TMOs engaged in DTS is also discussed along with its possible extensions that will enable significantly larger-scale DTSs.     

Software-Konfigurationsmanagement in großen Softwareprojekten

Zusammenfassung Mit zunehmender Größe der Softwaresysteme verschärfen sich die für die Software-Herstellung typischen Probleme: Beherrschen großer Objektmengen, Erhalten der Systemkonsistenz, Kontrolle der ständigen Änderungseinflüsse und Gewährleisten einer langen Lebensdauer. Die Disziplin Konfigurationsmanagement bildet den methodischen Ansatz, diese Probleme besser zu beherrschen. Software-Konfigurationsmanagement faßt die Herstellung von Softwaresystemen als eine Abfolge von kontrollierten Änderungen an gesicherten Zwischen- und Endergebnissen auf. Dargestellt werden die Objekte und Funktionen des Software-Konfigurationsmanagements sowie die hierfür in großen Software-Projekten benötigten Methoden, Instanzen und Hilfsmittel.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。