Storage Support for Multidimensional Discrete Data in Multimedia Databases

Multidimensional discrete data (MDD) is enormously important for multimedia applications since diverse types of such data are used simultaneously by any multimedia application. However, multidimensional discrete data is not adequately supported by most existing database systems. In this paper we discuss the major management requirements imposed by such data on multimedia database management systems both at the conceptual level and at the internal level. At the internal level, the spatial structure of the data must also be preserved and special emphasis must be given to the efficient spatial access to subrectangles of very large data of arbitrary dimensionality. Our major contribution is the presentation of a Storage Manager for this kind of data which preserves the spatial nature of the data at the internal level of the database management system and provides efficient spatial access. This Storage Manager is based on an innovative combination of the subdivision of data in multidimensional tiles and of a spatial index to access those tiles. Furthermore, it supports advanced registration data. The lower level modules of the Storage Manager are responsible for the access to the data stored in secondary storage. The implementation of these modules can rely on any secondary storage access system to access data on disk. The Storage Manager was implemented using the functionality of a relational database system. The implementation of this relational Storage Manager is presented.     

Strong controllability and extendibility of discrete multidimensional behaviors

In this paper we propose definitions of strong controllability and extendibility for discrete multidimensional behaviors. After characterizing extendibility in algebraic terms, we show that strong controllability is equivalent to simultaneous controllability and extendibility, thus obtaining an algebraic characterization for that property.     

统一多维数据模型的后关系数据库体系结构

随着面向对象编程技术的推广和Web技术的广泛应用,迫切需要在数据库领域提供对这些新技术的高效支持,而传统的关系数据库由于其本身的局限性在这些方面表现不佳。针对这一问题,并结合对象数据库及XML数据库的发展现状,提出了一种基于应用驱动的多接口混合型后关系数据库体系结构的概念模型,并在理论上加以验证。     

多媒介数据库系统的分析及设计

本文论述了多媒介数据库系统的一些基本问题，并介绍了一个新型的多媒介数据库管理系统ＣＤＢ／Ｍ的设计．     

分布式超媒体数据库系统的系统结构和组成

叙述了一种分布式超媒体数据库系统（ＨＤＢ）的系统结构、节点和链模型以及系统的组成。ＨＤＢ具有分布式宏文献结构，采用超媒体形式的节点和链来管理多媒体信息，可以实现过滤浏览、基于内容检索、多级导航等功能。ＨＤＢ由超媒体数据库创建、表现与查询、宏文献服务器、媒体服务器、脚本语言等模块组成。     

Effects on learning of multimedia animation combined with multidimensional concept maps

This study investigates whether teaching materials combining multimedia animation and multidimensional concept maps (MAMCMs) improve learning achievement, retention, and satisfaction more than multidimensional concept maps (MCMs), as suggested by Huang et al. (2012) in Computers & Education. Learning retention, learning achievement, and learning satisfaction associated with two sets of course materials were compared in this quasi-experimental study. In total, 114 students from two classes at one private university in Taiwan participated in this 6-week teaching experiment. Analytical results indicate that learning achievement, learning satisfaction, and learning retention of the MAMCM group were better than those of the MCM group. Pedagogical implications and suggestions are given.     

Effects of multidimensional concept maps on fourth graders’ learning in web-based computer course

This study explores the effect of multidimensional concept mapping instruction on students’ learning performance in a web-based computer course. The subjects consisted of 103 fourth graders from an elementary school in central Taiwan. They were divided into three groups: multidimensional concept map (MCM) instruction group, Novak concept map (NCM) instruction group, and traditional textbook (TT) instruction group. Four weeks of experimental instructions were given to the three groups, respectively. Students’ progresses were examined by pre-test and post-test measurements. The experimental results suggested that subjects in the MCM group performed significantly better than those in the NCM group which in turn performed significantly better than those in the TT group. Pedagogical implications were addressed, and conclusion and some suggestions were given.     

Investigation of multidimensional data using the interactive pattern analysis system ispahan

In 1972, Kanal has enumerated some reasons for the desirability of interactive pattern analysis and classification systems (IPACS). One such system, ISPAHAN, was developed at the Department of Medical Informatics of the Free University in Amsterdam. Although this system is still expanding, it is now in operation. In order to obtain some experience with its properties three data sets, varying in complexity were analysed. Especially the possibility of applying various pattern recognition techniques in succession is shown to lead to an unsupervised classification scheme which may yield essentially the same results as the maximum likelihood decision rule applied to the labelled data set. The results of unsupervised methods are generally influenced by user chosen initial conditions. An objective criterion should therefore be used to compare different configurations. The use of one such criterion, measuring the compactness of the resulting clusters, is demonstrated in this paper.     

一种全新的R树节点选择算法

在 R树插入算法中采用全新的节点选择算法 ,一改传统的从根节点开始自上而下的节点选择方案 ,而是从叶节点层开始 ,先自下而上再自上而下地选择叶节点 ,较好地解决了同层节点重叠所导致的查询效率低下的问题。实验证明 ,提出的 R树空间索引方法 ,不仅在查询效率上明显优于 R*树,而且 R树生成的时间开销也减少了 50%左右 ,综合性能超过了 R*树 ,便于扩展到三维甚至多维空间中 ,以实现对空间数据和时空数据的高效查询功能。     

海量多维数据的存储与查询研究

基于数据仓库的OLAP系统是当前海量多维数据分析的主要工具。随着信息技术的发展,海量多维数据的规模急剧增长,结构日益复杂,OLAP系统的性能严重下降,已经无法满足人们的数据分析需求。基于分布式计算系统Hadoop给出了新的海量多维数据的存储方法和查询方法。设计了HDFS上的列存储文件格式HCFile,基于HCFile给出了海量多维数据存储方案,该方案能够提高聚集计算效率,并有很好的可扩展性。同时,利用多维数据的层次性语义特征,设计了维层次索引,并给出了利用维层次索引和MapReduce进行聚集计算的方法。通过和Hive的对比实验,表明了数据存储方案和查询方法能够有效提高海量多维数据分析的性能。     

Scalable multi-feature index structure for music databases

The management of large collections of music data in a multimedia database has received much attention in the past few years. In the majority of current work, researchers extract the features, such as melodies, rhythms, and chords, from the music data and develop indices that will help to retrieve the relevant music quickly. Several reports have pointed out that these music features can be transformed and represented in forms of music feature strings or numeric values so that indices can be created for music retrieval. However, there are only a small number of existing approaches which introduce multi-feature index structures for music queries while most of the others are for developing single feature indices. The existing music multi-feature index structures are memory consuming and have lack of scalability. In this paper, we will propose a two-tier music index structure which is an efficient and scalable approach for multi-feature music indexing. Our experimental results show that this new approach outperforms existing multi-feature index schemes.     

空间数据挖掘技术的研究现状与发展趋势*

简要介绍了空间数据挖掘技术的产生背景和发展现状,对空间数据挖掘的体系结构和系统原型进行了概述,总结了空间数据挖掘近年来的研究方法及面临的主要问题,并对下一步的发展方向进行了展望。     

基于关系数据库系统的空间数据处理方法

目前,大量的数据都是通过数据库管理系统(DBMS)进行存储和管理,关系数据库是解决数据处理问题的最成熟和最有效的工具在地理信息系统(GIs)的应用中,是利用所谓的空间数据库来管理、分析和观察空间数据因为空间数据包含许多不同的数据格式和结构,这些复杂数据导致了对空间数据的操作和处理是非常复杂和困难的一项工作提出了一种利用关系数据库的成熟技术来解决空间数据处理的方法,思路是引入RSDD(regularly spatialdiscrete domains)概念,并定义基于RSDD的基本对象RPO(sDD_Based primary object)和对象RO(RSDD-Basedobject)概念,这些概念能够解决空间对象实数表示的无限精确性和计算机处理的有限精度之间的矛盾.     

Semantic processing of multimedia data for e-government applications

Knowledge management has become a challenge for almost all e-government applications where the efficient processing of large amounts of data is still a critical issue. In the last years, semantic techniques have been introduced to improve the full automatic digitalization process of documents, in order to facilitate the access to the information embedded in very large document repositories. In this paper, we present a novel model for multimedia digital documents aiming at improve effectiveness of digitalization activities within an information system supporting e-government organizations. At the best of our knowledge, the proposed model is one of the first attempts to give a single and unified characterization of multimedia documents managed by e-government applications, whereas semantic procedures and multimedia facilities are used for the transformation of unstructured documents into structured information. Furthermore, we define an architecture for the management of multimedia documents “life cycle”, which provides advanced functionalities for information extraction, semantic retrieval, indexing, storage, presentation, together with long-term preservation. Preliminary experiments concerning an e-health scenario are finally presented and discussed.     

关系数据库中多维数据分析及展现的研究

在对关系数据库业务模型分析的基础上通过建立多维模型定义使数据具有多维的概念,并在此基础上提供了一种B/S模式的多维数据查询和展现的方法,该方法充分利用了多种数据存储结构来优化数据的查询和显示.通过建立维度间的层次关系可实现多维数据的钻取、旋转、切片等操作,结合JFreeChart的图形功能提供了一种多维图形展现和分析的方法.     

Audio support for an object-oriented database-management system

We describe the development of the data type audio in an object-oriented database management system (DBMS). The interface of the data type includes operations to store, retrieve, and manipulate audio data. Additionally, a transport protocol supports continuous recording and presentation at the users' workstations in a client-server environment. Design considerations are outlined and lead us to use no compression algorithms and to handle parametrized sample rates and sizes transparently for the user. Specific manipulation operations, such as low-pass filtering and dynamic compression, are described in detail. The implementation of an interactive audio tool shows that the data type audio can be used in the same way as conventional data types. We give an outlook on further built-in support of time-dependent media that a comprehensive multimedia DBMS should offer.     

机器学习化数据库系统研究综述

数据库系统经过近50年的发展,虽然已经普遍商用,但随着大数据时代的到来,数据库系统在2个方面面临挑战.首先数据量持续增大期望单个查询任务具有更快的处理速度;其次查询负载的快速变化及其多样性使得基于DBA经验的数据库配置和查询优化偏好不能实时地调整为最佳运行时状态.而数据库系统的性能优化进入瓶颈期,优化空间收窄,进一步优化只能依托新的硬件加速器来实现,传统的数据库系统不能够有效利用现代的硬件加速器;数据库系统具有成百个可调参数,面对工作负载频繁变化,大量繁琐的参数配置已经超出DBA的能力,这使得数据库系统面对快速而又多样性的变化缺乏实时响应能力.当下机器学习技术恰好同时符合这2个条件：应用现代加速器以及从众多参数调节经验中学习.机器学习化数据库系统将机器学习技术引入到数据库系统设计中.一方面将顺序扫描转化为计算模型,从而能够利用现代硬件加速平台;另一方面将DBA的经验转化为预测模型,从而使得数据库系统更加智能地动态适应工作负载的快速多样性变化.将对机器学习化数据库系统当前的研究工作进行总结与归纳,主要包括存储管理、查询优化的机器学习化研究以及自动化的数据库管理系统.在对已有技术分析的基础上,指出了机器学习化数据库系统的未来研究方向及可能面临的问题与挑战.     

空间信息共享平台中数据索引服务的研究*

为消除空间信息孤岛,研究开放网格服务架构,建立空间信息共享平台。用户通过平台中的网格服务透明访问虚拟组织中的数据。为提升数据索引服务的性能,提出一种改进的R树算法,在节点分裂时考虑其他节点是否有剩余空间,从而避免了频繁的分裂导致产生大量的节点。实验结果表明,与经典R-树节点分裂算法相比,改进后的节点分裂算法的空间查询性能得到提升,该研究可为空间信息全面共享提供实用可行的实施方案。     

Towards the architecture of an instructional multimedia database

Abstract  The applicability of multimedia databases in education may be extended if they can serve multiple target groups, leading to affordable costs per unit for the user. In this contribution, an approach is described to build generic multimedia databases to serve that purpose. This approach is elaborated within the ODB Project ('Instructional Design of an Optical DataBase'); the term optical refers to the use of optical storage media to hold the audiovisual components. The project aims at developing a database in which a hypermedia encyclopedia is combined with instructional multimedia applications for different target groups at different educational levels. The architecture of the Optical Database will allow for switching between application types while working (for instance from tutorial instruction via the encyclopedia to a simulation and back). For instruction, the content of the database is thereby organized around so-called standard instruction routes: one route per target group. In the project, the teacher is regarded as the manager of instruction.
From that perspective, the database is primarily organized as a teaching facility. Central to the research is the condition that the architecture of the Optical Database has to enable teachers to select and tailor instruction routes to their needs in a way that is perceived as logical and easy to use.     

Systolic arrays for multidimensional discrete transforms

An active area of research in supercomputing is concerned with mapping certain finite sums, such as discrete Fourier transforms, onto arrays of processors. This paper presents systolic mapping techniques that exploit the parallelism inherent in discrete Fourier transforms. It is established that, for anM-dimensional signal, parallel executions of such transforms are closely related to mappings of an (M + 1)-dimensional finite vector space into itself. Three examples of such parallel schemes are then described for the discrete Fourier transform of a two-dimensional finite extent sequence of sizeN ₁ ×N ₂. The first is a linear array ofN ₁ +N ₂ – 1 processors and takesO(N ₁ N ₂) steps. The second is anN ₁ ×N ₂ rectangular array of processors and takesO(N ₁ +N ₂) steps, and the third is a hexagonal array which usesN ₁ N ₂ + (N ₂ – 1)(N ₁ +N ₂ – 1) processors andO(N ₁ +N ₂) steps. All three mappings are optimal in that they achieve asymptotically the highest speedup possible over the sequential execution of the same transform, and can easily be generalized to higher dimensions.