无参数局部保持投影及人脸识别

局部保持投影(LPP)通过构造近邻图来保持样本的局部结构,在构图过程中,LPP面临复杂的参数选择问题.为解决此问题,提出无参数局部保持投影(PLPP)算法.首先设计一种无参数的构图方法,能够动态地获取样本的近邻点并配置相应的边权.其次,利用该构图方法,PLPP通过寻求最佳投影矩阵,用于保持样本在低维空间的局部结构.由于PLPP在构图过程中并未设置任何参数且采用余弦距离设置边权,因此PLPP计算更加方便快捷且对离群样本更具鲁棒性.另外,为进一步提升PLPP的识别性能,在PLPP的基础上通过加入样本的类别信息,提出监督的无参数局部保持投影算法(SPLPP).最后,在ORL、FERET及AR人脸库上的实验验证了PLPP与SPLPP的有效性.     

样本列信息与自适应邻域图的局部保持投影

针对局部保持投影(locality preserving projection,LPP)算法在传统k近邻构图过程中出现的参数k选择困难问题和样本的一维向量容易忽略样本的原始结构特征问题,引入样本的列信息思想,提出了一种基于样本对应列信息的自适应邻域构图的局部保持投影算法(adaptive neighbor and corresponding columns based graph construction on LPP,ANCCG-LPP)。该算法根据样本间的列信息自适应地得出所有样本列的列近邻,然后根据样本间成对的列近邻个数自适应地确定样本的邻域;最后通过重新定义权值矩阵来优化目标函数进行最优投影向量集的求解。在ANCCG-LPP算法的基础上,通过加入样本的类别信息,提出了有监督的ANCCGLPP算法。在ORL、Yale Extended B人脸库上的仿真实验验证了该算法的有效性。     

应用于人脸识别的改进局部保持投影算法

局部保持投影算法（locality preserving projections,LPP）作为降维算法,在机器学习和模式识别中有着广泛应用。在识别分类中,为了更好的利用类别信息,在保持样本点的局部特征外,有效地从高维数据中提取出低维的人脸图像信息并提高人脸图像的识别率和识别速度,使分类达到一定优化,基于LPP算法结合流形学习思想,通过构造一种吸引向量的方法提出一种改进的局部保持投影算法（reformation locality preserve projections ,RLPP）。将数据集利用极端学习机分类器进行分类后,在标准人脸数据库上的进行试验,实验结果证明,改进后算法的识别率优于LPP算法、局部保持平均邻域边际最大化算法和鲁棒线性降维算法,具有较强的泛化能力和较高的识别率。     

有监督的无参数核局部保持投影及人脸识别

针对发掘人脸图像中的高维非线性结构,将加核及构造无参数近邻图两种思想同时引入到局部保持投影算法中,在有监督的模式下,提出了一种新的有监督的无参数核局部保持投影(Parameter-less Supervised Kernel Locality Preserving Projection,PSKLPP)算法并给出了其推导过程。该算法通过将欧氏距离改为对离群数据更为鲁棒的余弦距离,构造无参数近邻图,利用核方法提取人脸图像中的非线性信息,并将其投影在一个高维非线性空间,运用局部保持投影算法得到一线性映射,有效避免了在计算相似矩阵过程中面临的复杂参数选择问题。在ORL和Yale人脸库上的仿真实验验证了所提算法的有效性。     

完备的无参数近邻保持及最大化非近邻算法

无参数保持投影算法无需参数设置且识别性能稳定,但算法不能有效地保持样本的局部结构,且忽略了非局部样本所起的作用,而且存在着小样本(SSS)问题,为此提出了一种完备的无参数近邻保持及最大化非近邻算法。算法以样本间余弦距离0.5为分界点将样本分成近邻及非近邻样本,为了充分利用近邻样本及非近邻样本,分别构造了近邻散度矩阵及非近邻散度矩阵,因此算法的目标函数就是求取能够最小化近邻散度矩阵的同时,最大化非近邻散度矩阵的投影矩阵。对于目标函数的求解,可先将高维样本通过主成分分析(PCA)算法降至一个低维的子空间,并通过两个定理证明了这种处理方法没有损失任何有效的判别信息;然后将目标函数转换为差形式,从而有效地解决了小样本问题。在人脸库及掌纹库上的实验结果表明,与无参数局部保持投影算法相比,所提算法平均识别率更高,验证了算法的有效性。     

基于排斥图和吸引图的局部保持投影

局部保持投影(LPP)算法未利用样本类别信息进行人脸识别,提取的特征不适合分类。为解决该问题,提出一种基于排斥图和吸引图的LPP算法。在K近邻图的基础上建立排斥图和吸引图,使排斥图反映2个邻近但不同类样本之间的关系,吸引图反映2个同类但不近邻样本之间的关系,结合两者进行特征提取,定义样本相似性度量,以去除原始特征提取噪声和特征值变异的影响。在Feret和Yale人脸数据库上的实验结果表明,该算法的识别率高于主成分分析算法和传统LPP算法。     

基于有监督直接局部保持投影的人脸识别

提出一种用于图像识别的有监督直接局部保持投影算法,该算法结合样本类别信息,通过同时对角化的方法求解局部保持投影问题,避免矩阵的奇异性。在ORL人脸库上的测试结果表明,该算法的识别率高于PCA, PCA+LPP等方法。     

基于中心域的LPP算法研究

针对LPP算法中最近相邻图不能很好地表示流形的局部结构问题,提出一种基于中心域的保局投影算法。该算法采用LBP获取图像的高阶全局统计信息,并将其投影到LPP的流形空间。流形空间的获取是以各图像间的中心域的欧式距离为标准构建最近相邻图,使其可以简单地、较好地表示流形局部结构,并得到数量较少的特征维数。在ORL人脸库上的实验结果表明,该方法可有效地降低特征维数,并取得较好的识别率。     

基于无参数二维判别局部保持投影算法的人脸识别

通过向二维局部保持投影（2D-LPP）算法中引入类间约束和类标识信息,得到二维判别局部保持投影（2D-DLPP）算法,使它拥有更多的判别信息。但它却面临复杂的参数选择问题,这使得它在解决识别问题时受到限制。为解决此问题,构造无参数的相似矩阵,提出无参数的二维判别局部投影（无参数2D-DLPP）算法。在Yale和ORL人脸库上的仿真实验结果表明,该算法与二维判别局部保持投影（2D-DLPP）、二维局部保持投影法（2D-LPP）和二维线性判别分析法（2D-LDA）相比能够取得更高的识别率。     

全局加权稀疏局部保留投影

针对稀疏保留投影(SPP)算法运行时间较长并且忽略了样本的类间差异信息的问题,在稀疏保留投影算法的基础上,提出了全局加权稀疏局部保留投影(GWSLPP)算法。该算法在保持样本的稀疏重构关系的同时,使样本具有很好的鉴别能力,算法通过对样本进行稀疏重构处理;然后对样本进行投影并且最大化样本的类间散度;最后利用得到的投影将样本分类。该算法分别在FERET人脸库和YALE人脸库上进行实验。实验结果表明,全局加权稀疏保留算法在执行时间和识别率综合性能上,优于局部保留投影(LPP)、SPP和FisherFace算法,执行时间只有25s,识别率能达到95%以上,实验数据验证了算法的有效性。     

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。     

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.     

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.     

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.