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。     

一种数据本地化存储与处理系统

简述了当前大型数据中心普遍采用的计算节点集群与存储系统模块化设计的系统结构,说明了部署在各模块上的主要集群系统。分析了具有独立性的结构化数据本地化存储于计算节点的可能性,给出了系统基本框架,从总体拥有成本（TCO）的角度分析了其价值。结合高能物理研究的原始数据特点,认为数据本地化存储在节点上,有利于提高整体利用率,指出了关键部件——文件元数据管理系统的设计要点,分析了PBS作业批处理系统集成文件元数据管理系统的三种方案,给出第一种方案的详细设计,相应的用户提交作业方式的改变。在测试环境下,初步部署了文件元数据管理系统,测试了三种集成方案,给出了简要的分析比较。     

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.     

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.     

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.     

Hybrid storage architecture and efficient MapReduce processing for unstructured data

As we are now entering the era of data deluge, how to efficiently manage these massive data is becoming a great challenge, especially for the exponentially growing unstructured data, which is far more than structured and semi-structured data. However, unstructured data is more complex for its variety. That is to say, different types of unstructured data have different file size, type and usage, which need different storage and processing for high efficiency. In this paper, we propose a hybrid storage architecture to store the pervasive unstructured data. This hybrid architecture integrates various kinds of data stores within a unified framework, where each type of unstructured data can find its suitable placement policy and it is transparent to users. In addition, we present several partitioning strategies based on the unified framework, which are beneficial to the MapReduce-based batch processing for these unstructured data. The experiments demonstrate that it is possible to build an efficient and smart system through the hybrid architecture and the partitioning strategies.     

Rough关系数据库模型及其关系操作

1.引言 E.F.Codd于七十年代提出了著名的关系数据库模型,经过几十年发展,以它为基础的关系数据库系统得到了广泛的流行和认可,它有着层次模型和网状模型无可比拟的优点,如灵活性、逻辑和物理独立性、数据完整性等。然而,它也有自身的不足,就是对于不确定性的数据处理能力较差。随着应用面的扩大和数据量的急剧膨胀,出现了各种不确定信息、不完全信息、模糊信息,而关系数据库的处理能力主要是对确定信息的处理,因此,十分有必要对关系数据库模型进行扩充。到目前为止,可以说对于关系数据库的扩充有六种方法。第一种是扩展关系代数使之能处理“null”值,且提供“null”值的语义,这种方法假设数据值是确定的或是未知的,这对于大     

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.     

一种适用于GPU图像处理算法的合并存储结构

大多数图像处理算法都可利用GPU进行加速以达到更好的执行性能,但数据传输操作与核函数执行之间的调度策略问题仍是桎梏加速性能进一步提升的主要瓶颈。为了解决这个问题,通常采用GPU任务流将核函数执行与数据传输操作进行重叠,以隐藏部分数据传输与核函数执行耗时。但是,由于CUDA编程模型的特性以及GPU硬件资源的限制,在某些情况下,即使创建较多的任务流用于任务重叠,每个流上仍会存在串行执行的任务,导致加速效果无法进一步提升。因此,考虑利用CSS将待处理图像进行合并从而将单个流中的算子核函数及数据传输操作进行合并,以减少数据传输操作和核函数执行的固定代价及调用间隙。通过实验结果可知,提出的CSS结构不仅能在单流的情况下提高GPU图像处理算法执行性能,在多流的情况下其加速性能也得到了进一步提升,具有较好的实用性及可扩展性,适用于包含较多算子操作或较小尺寸图像批量处理的情况。此外,提出的方法对图像处理算法的GPU加速提供了新的研究思路。     

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.     

投入驱动的存储与计算一体化的事务处理效率优化方法

事务处理技术是报告信息一致性和可靠性的关键技术,决定了Web服务是否可以应用于电子商务。类型化的数据、信息和知识等资源繁杂冗余,导致资源存储和处理效率低下,长事务的处理过程往往会持续较长时间,使得锁定资源的策略不能一直适用,为了协调事务型资源存储和计算代价,提出了一种投入驱动的事务处理方法。从资源建模、资源处理、处理优化和资源管理等角度进行研究,基于对现有知识图谱概念的拓展提出了一种三层可自动抽象调整的解决架构。这个架构包括：数据图谱、信息图谱和知识图谱等三个层面,关键在于对搜索目标资源对象类型转移代价和在资源存储空间上的存储代价的计算,并根据用户投入协同调整搜索目标资源对象的搜索机制和存储方案,从而降低资源搜索的时间复杂度和资源存储的空间复杂度,优化事务处理的时空效率。     

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.     

Activities and ternary phase diagrams

A set of theoretical formulae for calculating activities along the liquid surface in ternary phase diagrams has been presented. These formulae are rigorous since no assumption is made in the derivation. The expressions are generalized and can be simplified to the forms presented by Pelton, Chou, Elliott and Gokcen under certain conditions. In practice, the activity of the components are desired at a fixed temperature instead of a variable temperature like that along a liquid surface. Under this situation, with reasonable assumptions the equations can be further simplified such that they do not contain any partial thermodynamic properties. Activities can then be readily calculated from phase diagrams. The method presented in this paper is for a ternary system and can be extended to multicomponent systems.     

Algorithms useful for calculating multi-component equilibria,phase diagrams and other kinds of diagrams

Phase diagrams are important in materials science. They consist of lines separating regions with different sets of stable phases and different kind of axes can be used. Many available phase diagrams are drawn directly from experimental information. However, they are closely related to the thermodynamic properties of the phases and can be calculated from thermodynamic models of the phases using the Calphad technique. This paper presents a set of algorithms to calculate equilibria and several kinds of diagrams using a very flexible set of conditions and axes. The algorithms can be applied to multi-component systems using model parameters in thermodynamic databases.