无线认知传感器网络的研究

在无线传感器网络中引入认知无线电技术,构成无线认知传感器网络,可以减少ISM频段干扰,提高数据传输率。对无线认知传感器网络的研究目前已成为一个新的研究领域。介绍了无线认知传感器网络的概念,从无线认知传感器网络的节点、频谱感知、频谱决策、频谱共享、频谱迁移、网络层、传输层、应用层等方面综述了现有的研究成果,讨论了目前存在的问题和需要进一步研究的方向。     

认知无线电下的电磁频谱管理探讨

现有的静态电磁频谱管理模式已经无法适应无线技术和无线服务的飞速发展,而且导致了已分配频谱使用率不高,频谱管理模式亟待改革。而认知无线电技术可以感知周围无线频谱环境,并且改变操作参数以更好地使用感知到的可用频谱。这种思想给未来的频谱管理带来了希望,基于认知无线电技术的频谱管理模式成为频谱管理部门的研究热点。本文也提出了对基于认知无线电的频谱管理模式的一些研究和看法。     

基于遗传算法的全双工认知无线电网络信道分配策略研究

随着无线通信业务的不断增长和智能终端的日益多样化,无线频谱资源变得愈加紧缺,认知无线电作为一项能够有效解决频谱利用率过低的技术,近年来引起了学术界和工程界的广泛关注。在认知无线电网络中,次用户以合作频谱感知的方式智能判断主用户的工作状态,以便在授权频谱的空闲时段内接入并加以使用。将全双工通信技术引入到传统的认知无线电网络中,实现了频谱感知和数据传输的同步,既能确保数据传输的连续性,又能减少对主用户的干扰,对提升无线频谱利用率具有重要作用。对于多信道全双工认知无线电网络的信道分配,建立了次级网络吞吐量最大化模型,并通过惩罚函数法,将混合整数非线性规划问题转换成不带约束条件的非线性规划问题,提出了基于遗传算法的全双工认知无线电网络信道分配策略。仿真实验结果表明,该算法能在综合考虑算法复杂度和性能的情况下,完成信道分配并保证次级网络吞吐量的最大化。     

基于NOMA的认知无线电车联网安全能效最优波束成形设计

非正交多址接入[1](NOMA)作为5G无线接入技术的重要准则之一，伴随着5G的高速发展，受到学术界和工业界的广泛关注，NOMA技术的核心是实现每个正交的资源块为多个用户提供服务，从而整体提高系统吞吐量。认知无线电（CR）技术的核心是感知周围空闲频谱资源并对其进行有效利用，从而提升频谱资源的利用率。因此，近年来已有学者将CR和NOMA联合研究，即CR-NOMA。以5G的重要实用场景车联网为背景，研究了基于NOMA的认知无线电车联网安全能效最优波束成形设计问题，并通过仿真实验对所提安全能效最大化传输方案进行了验证。     

动态阈值的双门限协作感知方法

随着通信技术的提高和通信应用的增多,无线频谱资源越来越匮乏.许多分配到资源的主用户利用率很低,认知无线电技术希望没有分配到资源的次用户合理使用主用户频谱来提高频谱的利用率.频谱感知技术关系到认知无线电中次用户对空闲频谱的使用机会,是认知无线电的关键技术之一.就是在已有的感知技术的基础上,提出了新的感知手段.在认知无线电网络中,不同的次用户由于与主用户距离以及自身所处环境的噪声影响不同,它们的信噪比一般是不一样的.这里采用的动态阈值的双门限协作感知方法,是对传统双门限能量感知方法的改进,通过充分考虑次用户之间的差异性来提高感知的性能.首先,根据对检测和虚警概率的要求,过滤掉一部分检测能力不满足条件的次用户.同时,每个次用户的用于能量感知的双门限会根据它们各自信噪比的不同而动态变化.通过与单门限能量感知以及传统双门限能量感知方法进行比较,可以看出本文提出的感知方法一定程度上提高了系统整体感知的性能.     

基于机器学习的认知无线网络优化策略

5G的发展带来了终端设备爆炸式增长的现象,使得频谱资源紧缺的问题越加严峻,认知无线网(cognitive radio,CR)的提出,被认为是提高频谱利用率的有效途径。认知无线网,融合了当代无线电通信技术、计算机技术、微电子学技术、软件无线电技术和现代信号处理技术等多学科之长,通过感知周围的电磁环境、学习及理解等方式,自主为用户寻找到当前空闲的频谱,完成信息交互过程。针对频谱资源紧张的现状,为改善频谱分配,首先介绍了有关认知无线网络的概念及其特点,重点介绍了机器学习中遗传算法,强化学习和隐马尔可夫模型在认知无线网络中的应用,并展望了其在认知无线网络中的发展前景。机器学习算法的引入,实现了高效的频谱资源管理,有效地解决了无线频谱资源紧张的问题。     

认知无线电技术在ZigBee中的应用研究

目前多种无线通信技术共享2．4GHzISM频段,它们之间的相互干扰以及频谱重叠现象已成为人们非常关注的一个问题。文中将认知无线电技术应用到ZigBee网络通信中,针对2．4GHz频段,利用认知无线电的频谱感知功能,对信道状态进行检测,搜寻频谱空穴,并且对频谱进行长期感知和统计,使ZigBee用户选择最可能空闲的频段作为传输信道,同时提出了一个2．4GHz无线环境感知模型。该方法提高了ISM频段的频谱利用率,并且减少了同频段其他多种无线通信技术对ZigBee产生的干扰,保证了ZigBee信号的有效传输。     

瑞利信道下多门限频谱合作感知方法研究

随着通信方式由语音转向多媒体应用,人们对高速无线传送的需求与日俱增。然而由于有限的自然频谱,现行的静态频率分配机制不能满足快速激增的高速通信设备的要求。因此,需要能够提高频谱利用效率的创新技术,认知无线电的出现解决了这种频谱拥塞的问题,本文将研究在能量探测频谱感知过程中使用多门限判决方法,在认知无线电网络中,决策中心接收多个认知无线电的观测数值,做出决定判断是否存在主用户。研究表明在瑞利信道下进行能量探测的合作频谱感知,采用多门限的判决方法能使感知效果的到提升。     

基于流行病理论的无线认知传感网抗攻击模型

大量无线通信设备在ISM频段工作致使免许可频段频谱资源稀缺,促使认知无线电和无线传感器网络（WSN）融合,形成无线认知传感器网络（WCSN）。文章研究了无线认知传感器网络中的数据伪造攻击,即恶意次用户通过向其他次用户发送伪造的频谱感知数据,导致控制中心做出错误的频谱分配决策。基于流行病理论,文章对数据伪造攻击中的信息传播过程进行了建模和分析,找出了决定无线认知传感器网络中潜在流行病爆发的关键因素。最后,通过仿真实验,对模型进行了验证,并对系统动态特性进行了研究。     

认知无线电在频谱感知和资源分配方面的探讨

认知无线电是一种智能无线电技术,具有自主寻找和利用空闲频谱资源的能力,它是解决无线通信需求增长与频谱资源稀缺的有效途径。本文简述了认知无线电的基本原理,对其在频谱感知和资源分配方面的研究进行了总结,并探讨了该技术发展需要解决的几个关键问题。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

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。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

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.     

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.     

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。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.