车辆碰撞信号准确挖掘过程的仿真分析

研究车祸中车辆碰撞信号的准确检测问题.针对车辆在完成碰撞的过程中,车辆碰撞部位随机性很大,碰撞过程较短,声音信号的采样周期和间隔很小,碰撞信号与外部的干扰声音信号经常形成交叉冲突,造成瞬时碰撞信号很难被准确采集.传统的检测算法很难在碰撞中对短促碰撞信号与外界声音信号进行区分,造成检测度不高,提出了一种粗糙集神经网络的车辆碰撞声音信号检测方法.采集车辆声音信号,对信号进行预处理,从而获取粗糙集神经网络参数.建立粗糙集神经网络模型,对车辆碰撞信号进行深度挖掘检测.实验结果表明,提出的算法能够有效提高车辆碰撞声音信号检测的准确性.     

小区域GPS短距离定位优化仿真

研究小区域内的GPS短距离准确定位问题.卫星发射的电磁波由于超强,达到建筑物或障碍物时会被漫反射到各个方向,反射随机性很强且很难控制,对正常的卫星通信信号形成干扰,造成卫星定位信号出现测距偏差.传统的GPS定位方法依靠得到的测距坐标完成区域定位,在受到卫星信号干扰的情况下,很难保证坐标测距的准确性,造成对小区域内的定位精度不高.为解决上述问题,提出了一种静态点位估计算法的小区域GPS短距离定位方法.对采集的CPS信号进行离散化处理,去除信号中的白色噪声.利用静态点位估计方法,获取目标的位置信息,从而实现小区域GPS短距离定位.仿真结果表明,提出的算法能够有效提高卫星信号干扰下的小区域GPS短距离定位的准确性.     

多车干扰下的车距信号采集方法仿真

在十字路口丁字路口等特殊区域,多车发生群聚,形成堆积.车辆间的车速与车距等信息不定.在多车距信息采集中,不同车辆的实时速度、车辆距离信号之间存在干扰,受到路口拐角车辆堆积遮挡等效应的影响,目标车距信号无法直接到达采集终端.传统的车辆信号采集在这种情况下,以多直线折射传递损失误差的方法,逼近曲线信号传递过程,一旦逼近计算过程增加,造成采集的车距误差增大.提出基于衰减补偿的车辆车距遮挡信号采集方法.计算车辆信号采集的基本波,针对初始车辆车距信号进行连续小波位移变换,完成了车辆车距多车下信号的抗干扰处理.计算车辆车距遮挡后信号衰减系数估计结果,针对估计结果进行衰减误差补偿,实现车辆车距信号的准确提取.实验结果表明,利用改进算法进行车辆车距信号采集,能够极大地提高车辆信号的准确性,优化效果明显.     

无线网络雷击信号快速采集方法研究与仿真

在雷击信号准确采集的研究中,无线网络受到雷击后,会导致信号突变,突变的周期很短.传统的信号采集方法采用提高采集频率的方法对这种瞬时信号进行采集,存在较大漏检风险.为提高采集精度,提出采用小波模糊网络算法的无线网络雷击信号快速采集方法.针对无线传感网络采集到的所有信号进行滤波处理,提取信号特征,并针对信号特征进行微分变换,能够得到滤波处理结果.将上述滤波处理结果输入到小波模糊网络模型中,获取雷击信号特征向量和对应的检测误差,针对检测误差进行补偿,实现无线网络信号更新,模型的输出结果是无线网络雷击信号.实验结果表明,利用改进算法进行无线网络雷击信号检测,能够对雷击信号频率进行准确的分析,提高采集的准确性.     

抗运动误差的车辆超载检测方法研究与仿真

车辆超载检测以静态检测为主.由于汽车超载运动检测过程中,车辆运动往往伴随着包括接触面分离和再附着、非定常涡脱落和高扰动、大比例尺的湍流结构以及弯曲剪切层等复杂现象,使得压力分布发生偏差,造成传统的车辆超载检测方法无法实现动态检测.为此,提出利用多频段信号竞争免疫算法的车辆超载检测方法.采集多频段车辆超载信号,并进行拉普拉斯能量和权重计算,对低频分解结果和高频分解结果进行融合.将竞争机制引入到免疫算法中,获取误差与真实结果的竞争关系,排除动态干扰.实验结果表明,利用改进算法进行抗运动误差的车辆超载检测,能够在汽车运动过程中进行准确的超载检测,提高检测的准确性和实用性.     

基于智能视觉的车辆事故预警监控系统设计

针对车辆行驶中驾驶员视觉盲区或注意力不集中而造成的交通事故问题,提出采用智能视觉技术对车辆行驶过程中四周的异常物体进行视频监控,对动态视频场景中的运动目标进行检测、识别与实时测距,通过车辆智能视频监控系统最大程度的为驾驶员提供更多预警信息,预防交通事故的发生;文中介绍了车辆智能视觉监控系统的硬件设计方法与软件工作流程,并研究了运动目标检测算法与单目视觉测距算法,通过仿真实验,验证了该智能视觉车辆监控系统对于运动目标进行检测、识别与智能测距判断的实验结果.     

调频连续波太赫兹雷达近程测距精度提高算法

太赫兹雷达的波长短且带宽大,与微波、毫米波相比,易于实现很高的测距精度.采用调频连续波雷达测距,在差频信号进行频谱分析过程中,频谱泄露和栅栏效应影响其测距精度.该算法通过调整采样参数实现整周期采样,减少频谱泄露,通过峰值谱线和相邻谱线构成的梯度法估计频谱峰值中心频率,减小离散频谱间隔造成的误差,通过两步的校正提高测距精度.实验结果表明:该算法的测量精度误差与传统频率估计法相比有所降低,与直接采用FFT的方法平均提高了58.5％.     

车辆气囊圆管填充蜂窝结构撞击检测方法研究

研究车辆气囊圆管填充蜂窝结构撞击准确检测的方法.在车辆气囊设计过程中,由于气囊圆管填充蜂窝结构的尺寸存在较大的差异,造成在撞击过程中发生形变.利用传统的模糊聚类算法进行车辆气囊圆管填充蜂窝结构撞击检测,无法对发生形变的蜂窝结构进行准确的检测.为了避免上述缺陷,提出了一种基于层次分析算法的车辆气囊圆管填充蜂窝结构撞击检测方法.采集车辆气囊圆管填充蜂窝结构承压信号,对信号特征进行有效的提取,从而为车辆气囊圆管填充蜂窝结构检测提供准确的数据基础.利用层次分析方法,对车辆气囊圆管填充蜂窝结构进行撞击检测.实验结果表明,利用本文算法进行车辆气囊圆管填充蜂窝结构撞击检测,可以极大地提高检测的准确性,满足车辆气囊安全性能的实际需求.     

基于卫星定位信号的车辆行驶里程计算方法

本文针对当前各种车联网应用服务中,基于车辆实时经纬度信息的里程计算与统计误差问题,提出一种低采样频率下的车辆行驶里程计算方法.首先对起点进行信任度验证,消除起点漂移带来的影响;然后采用连续大角度过滤、大距离过滤、大速度过滤、大加速度过滤相结合的方法进行噪点过滤;在此基础上,采用速度插值与角度插值相结合的方法对弯道进行里程补偿;另外,针对丢点数据,采用基于路径规划的电子地图调用方式进行里程补偿,进一步提高算法的准确性.经实验验证,在较低的位置信号采样频率下,该方法仍有较高的里程计算精确度和执行效率.     

基于图像的肇事逃逸车辆定位方法研究与仿真

研究肇事逃逸车辆快速准确定位问题.车辆在逃逸过程中,逃逸车辆图像所在场景变换较为快速,车辆行驶方向突变性较强,使得车辆定位特征衰退明显.传统的车辆定位算法建立的特征模型由于这种场景图像快速变换和方向突变的影响,无法准确的捕获运动车辆的关键特征,定位准确性较差.提出改进关联挖掘算法的肇事逃逸车辆图像快速定位方法,在变化场景对包含冗余车辆特征的信息进行二次校验过滤,进而减小定位图像错误分类的可能,运用关联特征准确完成定位.仿真结果证明,改进算法能够大幅提高肇事逃逸车辆图片的关键帧定位结果的准确性,为逃逸车辆准确定位提供了依据.     

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.