XML的关系化存储及与关系数据库的数据转换

随着不断增长的基于XML应用的出现,如何在数据库中可靠、有效地存储XML文档以及XML和数据库间的数据转换技术变得越来越重要。讨论了基于模式驱动的XML与关系数据库的数据映射,给出了其基本原理和实例,并且分析了采用该技术实现的一个与数据库平台无关的、支持多模式和多种转换方式的应用系统,给出了该系统的设计和实现方案。其原型的测试结果表明,该系统的原理和设计是可行的和有效的。     

Application of the ICL DAP for two-dimensional image processing

An optimisation of the fast Fourier transform for two-dimensional transforms is described, followed by a discussion of a number of numeric-intensive techniques in image processing using this method.     

Several digital realizations of two-dimensional E-filters applied to image processing

This paper presents several digital implementations for two-dimensional E-filters. The E-filter is based on a non-linear transformation into the spatial domain. Its response is essentially independent of the frequency of the incoming signal under certain conditions, but depends largely on the digital amplitude. Several digital realizations and attendant problems are presented for E-filters applied to biomedical images obtained from an Anger scintillation camera. The associated sensitivity of the digital E-filter to changes of its parameters is examined. A two-dimensional linear filter is realized by the use of a bi-cubic spline interpolation scheme. The boundary detection of unprocessed and filtered images is also investigated using the hexagonal Golay transform. Several examples of abnormal heart and brain-scans are presented including the filtered images and bounded areas of infarcted and abnormal tissue.     

Application of two-dimensional canonical correlation analysis for face image processing and recognition

Paper presents the method of two-dimensional canonical correlation analysis (2DCCA) applied to image processing and biometrics. Method is based on representing the image as the sets of its rows (r) and columns (c) and implementation of CCA using these sets (for this reason we named the method as CCArc). CCArc features simple implementation and lower complexity than other known approaches. In applications to biometrics CCArc is suitable to solving the problems when dimension of images (dimension of feature space) is greater than number of images, i.e. when Small Sample Size (SSS) problem exists.     

基于嵌入式图像采集处理系统的二维码识别

对基于FPGA和DSP结构的嵌入式二维码图像识别系统的硬件架构设计方案作了讨论,主要介绍了包括CMOS图像传感器,FPGA,DSP,SDRAM,FLASH,RS-232等硬件在内的各个工作模块的功能实现,并在此平台上实现了二维码图片的识读,验证了平台设计的正确性、可靠性.该系统具有通用性强,编程灵活,很适合模块化应用的特点.     

Pattern storage and processing in attractor networks with short-time synaptic dynamics

Neurophysiological experiments show that the strength of synaptic connections can undergo substantial changes on a short time scale. These changes depend on the history of the presynaptic input. Using mean-field techniques, we study how short-time dynamics of synaptic connections influence the performance of attractor neural networks in terms of their memory capacity and capability to process external signals. For binary discrete-time as well as for firing rate continuous-time neural networks, the fixed points of the network dynamics are shown to be unaffected by synaptic dynamics. However, the stability of patterns changes considerably. Synaptic depression turns out to reduce the storage capacity. On the other hand, synaptic depression is shown to be advantageous for processing of pattern sequences. The analytical results on stability, size of the basins of attraction and on the switching between patterns are complemented by numerical simulations.     

Data storage practices and query processing in XML databases: A survey

With the rapid emergence of XML as a data exchange standard over the Web, storing and querying XML data have become critical issues. The two main approaches to storing XML data are (1) to employ traditional storage such as relational database, object-oriented database and so on, and (2) to create an XML-specific native storage. The storage representation affects the efficiency of query processing. In this paper, firstly, we review the two approaches for storing XML data. Secondly, we review various query optimization techniques such as indexing, labeling and join algorithms to enhance query processing in both approaches. Next, we suggest an indexing classification scheme and discuss some of the current trends in indexing methods, which indicate a clear shift towards hybrid indexing.     

传感器网络中图像小波处理的低存储硬件实现

为了适应当前传感器网络中越来越多的图像压缩处理,提出了一种片上低存储离散小波变换(DWT)的超大规模集成电路(VLSI)结构.现今人们周围遍布各种图像采集设备,包括监视器、电脑、手机视频摄像头等,并且人们对图像精度的需求越来越高,使得传统软件处理图像压缩的速度逐渐无法满足人们的需求,这就需要考虑使用硬件处理来进行加速.小波变换常被用于图像的压缩,而采用5/3提升小波技术来进行硬件实现相对比较方便.为减少硬件的片上存储,通过特殊的调度运算方式进行行列并行运算有效降低片上存储需求.该设计进行RTL级仿真并使用SMIC的0.18μm工艺进行综合,结果表明:该调度方法可以大大节省缓存单元,并且在100 MHz时钟下就可以保证对高清图像的快速处理,可以满足当前传感器网络中图像压缩解码的需求.     

Towards a framework for large-scale multimedia data storage and processing on Hadoop platform

Cloud computing techniques take the form of distributed computing by utilizing multiple computers to execute computing simultaneously on the service side. To process the increasing quantity of multimedia data, numerous large-scale multimedia data storage computing techniques in the cloud computing have been developed. Of all the techniques, Hadoop plays a key role in the cloud computing. Hadoop, a computing cluster formed by low-priced hardware, can conduct the parallel computing of petabytes of multimedia data. Hadoop features high-reliability, high-efficiency, and high-scalability. The numerous large-scale multimedia data computing techniques include not only the key core techniques, Hadoop and MapReduce, but also the data collection techniques, such as File Transfer Protocol and Flume. In addition, distributed system configuration allocation, automatic installation, and monitoring platform building and management techniques are all included. As a result, only with the integration of all the techniques, a reliable large-scale multimedia data platform can be offered. In this paper, we introduce how cloud computing can make a breakthrough by proposing a multimedia social network dataset on Hadoop platform and implementing a prototype version. Detailed specifications and design issues are discussed as well. An important finding of this article is that we can save more time if we conduct the multimedia social networking analysis using Cloud Hadoop Platform rather than using a single computer. The advantages of cloud computing over the traditional data processing practices are fully demonstrated in this article. The applicable framework designs and the tools available for the large-scale data processing are also proposed. We show the experimental multimedia data including data sizes and processing time.     

Organizational Blogs and the Human Voice: Relational Strategies and Relational Outcomes

This study develops and tests operational definitions of relational maintenance strategies appropriate to online public relations. An experiment was designed to test the new measures and to test hypotheses evaluating potential advantages of organizational blogs over traditional Web sites. Participants assigned to the blog condition perceived an organization's "conversational human voice" to be greater than participants who were assigned to read traditional Web pages. Moreover, perceived relational strategies (conversational human voice, communicated relational commitment) were found to correlate significantly with relational outcomes (trust, satisfaction, control mutuality, commitment).     

Synthesis of state machine diagrams from communication diagrams using Petri nets

Service-oriented architecture is an architecture style to build up a large-scale networked system composed of a set of components or functions, each of which is called a service. A problem to construct behavioral models of services from given global interaction specifications, called choreography, is known as the choreography realization problem. The constructed model is still an intermediate model in the process of system developments; the model will be corrected, modified, and enhanced further by designers. Therefore, we also have to consider readability of the constructed model. In this paper, we proposed a method to construct state machine models from choreographies described by a set of communication diagrams using Petri nets. The proposed method will try to use the composite states and the orthogonal regions of UML state machines for the readability.     

基于DSP+FPGA的高速数据处理与存储系统设计

针对信号处理数据量大、实时性要求高的特点,从实际应用出发,设计了以双DSP+FPGA为核心的并行信号处理模块。为了满足不同的信号处理任务需求,FPGA可以灵活地选择与不同的DSP组成不同的信号处理结构,同时为满足大数据存储要求设计了可方便网络控制的数据存储模块。模块之间可以通过自定义LVDS接口实现互联,组成一个系统。     

基于关系代数的模糊综合评判算法的研究和实现

模糊综合评判有着广泛的实际应用背景。关系代数是数据库技术的一个非常重要的理论基础,SQL语言是关系代数在数据库技术中的表现形式。把关系代数与模糊综合评判结合起来,有着重要的实践意义。基于关系代数的RFCE就是关系代数与模糊综合评判结合的结晶。     

Unifying Concurrent and Relational Refinement

Refinement in a concurrent context, as typified by a process algebra, takes a number of different forms depending on what is considered observable, where observations record, for example, which events a system is prepared to accept or refuse. Examples of concurrent refinement relations include trace refinement, failures-divergences refinement and bisimulation.Refinement in a state-based language such as Z, on the other hand, is defined using a relational model in terms of input/output behaviour of abstract programs. These refinements are verified by using two simulation rules which help make the verification tractable.The purpose of this paper is to unify these two standpoints, and we do so by generalising the standard relational model to include additional observable aspects. The central result of the paper is then to develop simulation rules to verify relations such as failures-divergences refinement in a relational setting, and show how these might be applied in a specification language such as Z.     

关系型数据库与NoSQL数据库

通过对传统关系型数据库以及他目前存在的问题的说明,进而引出了NoSQL数据库,并指出NoSQL数据库的特点以及目前应用状况,最后总结出传统关系型数据库和NoSQL数据库在某种场景下结合使用,并给出具体实例加以说明。     

Referent Systems and Relational Grammar

Relational Grammar (RG) was introduced in the 1970s as a theory of grammatical relations and relation change, for example, passivization, dative shift, and raising. Furthermore, the idea behind RG was that transformations as originally designed in generative grammar were unable to capture the common kernel of, e.g., passivization across languages. The researchconducted within RG has uncovered a wealth of phenomena for which it could produce a satisfactory analysis. Although the theory of Government and Binding has answered some of the complaints, still it left many phenomena unaccounted for. Referent Systems (RSs) have been introduced by Vermeulen (1995) to overcome certain weaknesses of Dynamic Semantics. Their usefulness has not yet been realized in semantical theory. We shall show here that their significance cannot be overestimated. Namely, we will show in this paper that there exists a fundamental affinity to RG. Both handle the relation between an argument and a functor by means of a shared relational sign, which is unique for each argument. This assignment can be changed. What is interesting is that the notion of a chômeur, which is central to RG, finds a natural treatment in RSs. This coincidence is in our view not accidental but reveals some fundamental properties of the human language faculty.     

Formal modeling and validation of Stateflow diagrams

Stateflow is an industrial tool for modeling and simulating control systems in model-based development. In this paper, we present our latest work on automatic verification of Stateflow using model-checking techniques. We propose an approach to systematically translate Stateflow diagrams to a formal modeling language called CSP# by precisely following Stateflow’s execution semantics, which is described by examples. A translator is developed inside the Process Analysis Toolkit (PAT) model checker to automate this process with the support of various Stateflow advanced modeling features. Formal analysis can be conducted on the transformed CSP# with PAT’s simulation and model-checking power. Using our approach, we can not only detect bugs in Stateflow diagrams, but also discover subtle semantics flaws in Stateflow user’s guide and demo cases.     

Combined new nonnegative matrix factorization algorithms with two-dimensional nonnegative matrix factorization for image processing

In recent years, nonnegative matrix factorization (NMF) has attracted significant amount of attentions in image processing, text mining, speech processing and related fields. Although NMF has been applied in several application successfully, its simple application on image processing has a few caveats. For example, NMF costs considerable computational resources when performing on large databases. In this paper, we propose two enhanced NMF algorithms for image processing to save the computational costs. One is modified rank-one residue iteration (MRRI) algorithm , the other is element-wisely residue iteration (ERI) algorithm. Here we combine CAPG (a NMF algorithm proposed by Lin), MRRI and ERI with two-dimensional nonnegative matrix factorization (2DNMF) for image processing. The main difference between NMF and 2DNMF is that the former first aligns images into one-dimensional (1D) vectors and then represents them with a set of 1D bases, while the latter regards images as 2D matrices and represents them with a set of 2D bases. The three combined algorithms are named CAPG-2DNMF, MRRI-2DNMF and ERI-2DNMF. The computational complexity and convergence analyses of proposed algorithms are also presented in this paper. Three public databases are used to test the three NMF algorithms and the three combinations, the results of which show the enhancement performance of our proposed algorithms (MRRI and ERI algorithms) over the CAPG algorithm. MRRI and ERI have similar performance. The three combined algorithms have better image reconstruction quality and less running time than their corresponding 1DNMF algorithms under the same compression ratio. We also do some experiments on a real-captured image database and get similar conclusions.     

A semantics of sequence diagrams

We develop a formal semantics of sequence diagrams. The semantics is given in terms of our new temporal logic, named HDTL, which is designed to specify dynamically evolving systems. This approach allows to facilitate the generic feature of sequence diagrams as well as an automatic analysis, the identification of the instances of a sequence diagram over a trace.     

A link-based storage scheme for efficient aggregate query processing on clustered road networks

The need to have efficient storage schemes for spatial networks is apparent when the volume of query processing in some road networks (e.g., the navigation systems) is considered. Specifically, under the assumption that the road network is stored in a central server, the adjacent data elements in the network must be clustered on the disk in such a way that the number of disk page accesses is kept minimal during the processing of network queries. In this work, we introduce the link-based storage scheme for clustered road networks and compare it with the previously proposed junction-based storage scheme. In order to investigate the performance of aggregate network queries in clustered road networks, we extend our recently proposed clustering hypergraph model from junction-based storage to link-based storage. We propose techniques for additional storage savings in bidirectional networks that make the link-based storage scheme even more preferable in terms of the storage efficiency. We evaluate the performance of our link-based storage scheme against the junction-based storage scheme both theoretically and empirically. The results of the experiments conducted on a wide range of road network datasets show that the link-based storage scheme is preferable in terms of both storage and query processing efficiency.