煤与瓦斯突出信号挖掘方法研究

针对传统关联聚类算法因难以捕捉异常信号非线性随机变化而造成采煤作业中特征信号检测不准确的问题,提出一种基于特征关联挖掘算法的煤与瓦斯突出信号挖掘方法。该方法利用小波变换提取煤矿井下作业区状态信号特征,为煤与瓦斯突出信号挖掘提供依据;计算煤矿井下作业区状态信号特征之间的关联度,实现煤与瓦斯突出特征信号挖掘。实验结果表明,该方法可提高煤与瓦斯突出信号挖掘的准确性。     

电子通信突变非线性多频干扰检测方法

电子通信中同频段窄带信号通常含有多种不同频谱的非线性信号,对通信造成突发性干扰。此类非线性信号干扰的多频段表现性强且特征种类多,检测难度较大。为此提出一种考虑动态特征的突变非线性多频干扰检测方法。构建电子通信模型,采集信号样本,根据时域逐步增加的关系完成信号的扩频。计算扩频前和扩频后的幅度差值,根据信号跟随时间变化的递推关系推导出每个源点区域的实时状态特征。采用DFT多级模型按照特征大小顺序逐一检测,若信号超过门限值,则输入到下一级检测层中;若信号低于门限值,直接输出非线性多频干扰检测结果。实验证明：研究方法能够高精度检测电子通信突变非线性多频干扰的时域和频域幅值,说明上述方法的应用性能更好,研究价值较高。     

基于深度学习的复杂观测条件下工频磁异常探测

复杂观测条件下使用工频磁场探测人员、车辆、飞行目标等多类型目标造成的磁场扰动时,受到复杂环境下电磁噪声、供电设备及外来物体扰动等影响,工频磁场扰动信号具有噪声多、干扰强等特征,为有效削弱噪声及干扰对工频磁场扰动信号的影响,实现工频磁场扰动探测,该文利用实验数据对复杂观测条件下的磁场扰动信号进行特征分析,提出了一种基于深度学习的工频磁场异常探测方法,通过提取正常状态与有扰动状态的信号序列,将该信号输入神经网络训练,得到准确检测工频磁场异常信号的网络模型。实验结果表明,该方法的识别准确率在80%以上。     

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.     

基于知识本体提纯的无人机故障数据采集仿真

无人机在飞行的过程中,采集的故障信号数据会随着飞行环境的随机性变化而改变,造成异常信号数据关联性降低.利用传统算法进行异常信号数据挖掘的过程中,建立的关联规则过于复杂,加入过多约束条件分析环境特征,导致挖掘过程耗时较长.为解决上述问题,提出基于知识本体提纯的无人机采集实时数据挖掘方法.针对无人机异常信号数据知识本体表示方法进行了详细阐述.利用贝叶斯概率方法计算当前状态信号属于某类别异常信号的最大概率,从而为异常信号的提纯提供了准确依据.针对相似度较高的两个异常信号进行提纯处理,在提纯过程中充分考虑到信号采集时间间隔和时延,从而保证了实时性要求.实验结果表明,利用改进算法进行无人机异常信号挖掘,能够提高异常信号挖掘的及时性和准确性.     

大型炼钢炉炉温异常检测方法研究

在炼钢炉内高温高压环境下,异常温度信号往往瞬间形成,在炉内气浪、异常压力鼓动等外部干扰下,温度异常信号会迅速发生非正常衰减,甚至与其它异常信号发生混淆,造成温度测量不准.传统的炉内温度异常检测方法在信号发生不可控衰减或混淆的情况下,信号分离和识别的过程存在较大困难,在外部干扰下,对温度信号的单独识别、提取效果不佳,温度检测存在较大弊端.提出一种采用约束模糊聚类算法的大型炼钢炉炉温异常信号检测方法.根据傅里叶变换方法对信号采集设备采集到的信号进行隔离处理,克服由于信号混淆带来的困难.根据约束模糊聚类算法,对隔离后的信号进行聚类,使其成为有效的识别特征,完成了异常温度的检测.实验结果表明,利用改进算法进行大型炼钢炉炉温异常检测,能够极大提高异常温度信号检测的准确率.     

航空发动机气路传感网络的故障节点挖掘仿真

航空发动机的气路传感网络故障检测,是通过与发动机气路传感网络产生的基准线进行比较,产生的偏差作为阀值,作为检测故障的基础.由于航空发动机气路传感网络的高度非线性、噪声、测量不足等因素的影响,检测的基准线也呈现波动状态,传统的故障挖掘方法,需要通过做一些必要的假设,设置各种可能故障和性能恶化的范围,规定故障挖掘空间以降低波动干扰,但是上述假设降低了检测的精度.提出一种航空发动机气路传感网络的故障节点挖掘方法.计算故障传感节点的特征,为故障传感节点的挖掘提供数据基础.利用神经网络建立故障传感节点挖掘模型,完成故障传感节点的挖掘.实验结果表明,利用改进算法进行航空发动机气路传感网络的故障节点挖掘,能够有效提高检测的准确性和挖掘效率.     

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.     

自动驾驶车辆道路跟驰与状态一致性控制

针对含有未知输入和外部干扰的非线性自动驾驶车辆时变跟驰队列系统,研究系统部分状态可测情况下的车辆道路跟驰和状态一致性控制问题.基于车辆跟驰和二自由度动力学模型,得到含有外部干扰和未知输入的离散化状态方程,利用前导跟驰特性,得到自动驾驶车辆跟驰队列系统;利用比例积分状态观测器解决系统部分状态不可测问题,提出一种基于观测器实现含有未知输入和外部干扰的自动驾驶车辆状态一致性控制协议;将观测器估计效果和一致性控制问题转化为误差系统的稳定性问题,由此构造Lyapunov-Krasovkii函数,利用离散系统稳定性理论推导出一个充分条件;通过求解线性矩阵不等式(linear matrix inequality, LMI)得到跟驰系统的增益矩阵和参数矩阵,利用H_∞性能指标分析系统鲁棒性.仿真结果表明:所设计观测器能够估计未知输入、外部干扰和系统状态,并且基于观测器设计能够使自动驾驶车辆道路跟驰和状态达到一致.     

基于Rossle混沌平均互信息特征挖掘的网络攻击检测算法

传统网络攻击检测方法中,通常使用混沌系统结合高斯混合模型实现同步控制检测,当待检测的攻击信号具有高斯线性特征时,这种方法的检测效果理想。随着网络攻击信号向着非线性随机序列方向发展,传统检测模型无法实现有效的攻击检测。提出一种基于Rossle混沌模型的平均互信息特征潜质挖掘算法,并根据挖掘的互信息这种非线性特征解,实现对具有非线性随机特性的网络攻击信号有效检测。根据Rossle混沌系统基础模型,采用最小均方误差准则,设计一个能去除多个已知干扰频率成分的自适应级联陷波器,实现对攻击信号的滤波预处理,提取待检测网络数据流的Rossle混沌非线性互信息特征,实现对网络攻击信号的特征挖掘和检测。仿真实验表明,采用该算法进行网络攻击检测,检测性能明显提高,检测概率达到97.8%,展示了算法优越的检测性能和网络安全防御价值。     

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。     

基于QTE的蒙古文显示机制研究与实现

蒙古语言是中国蒙古族使用的通用语言,由于蒙古文区别于其他文字的书写方式和其自身变形机制等特点,在很多通用的文字处理引擎中都不被支持。在嵌入式产品开发与应用领域中Linux加QTE已经成为流行方式。该文给出了一种在QTE环境上实现基于标准Unicode的蒙古文点阵显示和变形算法, 并自定义了支持蒙古文的QTE组件,扩展了QTE功能,为在Linux加QTE方式的嵌入式体系结构中处理蒙古文提供了一种解决方法。