内存数据库优于查询的存储结构的研究与设计

以内存数据库数据存储结构研究重点,以提高数据查询效率为目的,提出在内存数据库现有的N-Array存储结构中利用离散存储结构思想对其改进的方案,并给出具体的设计及实现方式。随后以属性选择查询为主要评估点,对N-Array存储结构和改进的存储结构的查询效率进行全方位分析和对比,最后得出结论:改进的存储结构在属性的选择查询上能更好的利用到系统的缓存优势,在内存数据库的查询效率上它是有意义的。     

基于关系数据库的时态XML存取研究

时间是自然界无所不在的客观属性,更是信息的重要属性。能够根据时序进行访问的XML文档称之为时态XML。针对时态XML文档这种特殊的文档,应用一种数据模型进行时态的扩展并在此数据模型的基础上研究基于关系数据库时态XML数据的存储和查询方法。该方法使时态XML的查询变成可以在关系数据库里使用SQL语句的一般查询。     

分布式本体库存储模型的设计与优化

针对如何高效地构建用于语义交互的分布式本体库展开了研究。首先,分析了基于本体的语义交互平台的通用体系结构,进而明确分布式本体库在平台中的作用,提出了一种分布式本体库存储模型。围绕该模型,详细讨论了网络本体库与本地本体库的映射方法,语义数据的编码方法,然后详细分析了该模型中指令分发和数据演化组件的工作机制,最后通过实验验证了:在集群存储模式下,对于大数据量查询,网络数据传输对查询时间开销的影响远远小于查询本身,从而为分布式本体库存储效率的优化奠定了基础,即在本体库中采用分布式集群存储可以达到优化检索效率的目的。该存储模型已经在STASIS平台中得到应用。     

大规模时空图数据存储和分析的优化方法

时空图数据在数据量和数据更新速率两方面具有独特的特征,可以用来优化存储和查询分析。然而,现有的成熟的大数据存储和分析系统提供统一化的支持,没有考虑结合数据特征和查询特征做针对性的优化,因而无法很好地应对大规模数据的挑战,存储和分析能力都有待加强。本文利用时空图数据的数据特征,提出了针对不同类型的顶点和边的差异化存储方案;利用时空图数据的查询特征,提出了差异化的存储布局和基于此的查询执行优化方案。实验结果表明,和现有方案相比,本研究提出的优化方法能减少1.7～5.4倍的存储空间,查询性能可以提高1～4个数量级。     

基于多通道采样数据的高速存储系统设计

建立了一个四层文件系统,将来自多个通道的采样数据按存储任务编号、通道号、采样起始时间分层存储,并对每层数据提供相应的索引文件,提供了按通道号及时间段的快速查询服务。测试表明,在IBM服务器上达到了150MB／s的存储速度,可以满足同时300个通道的实时采样数据存储任务。     

基于简单路径的XML数据存储技术研究

随着XML在数据表示、交换以及索引等方面发挥作用日益增强,如何保证XML数据的有效存储以及查询速度显得尤为重要。现有的XML数据存储系统虽然在一定程度上满足了当前需求,但是在数据查询时性能上会有很大的废弃率。本文结合XML数据存储的特点,提出了一种新型的基于简单路径的XML数据存储技术,很大程度上降低了XML数据查询时的废弃率。     

基于云存储的医院PACS系统存储研究

做为医院数字化建设的重要系统PACS(医学影像存储与传输系统)目前在许多大医院都完成初步建设,对于PACS系统来说,存储的图像数据信息量大,现有的存储技术都不能很好的解决这一需求,需要一种新的信息系统存储架构,完成数据的集中存储、备份,并保证数据安全性和共享,提出云存储的概念,分析云存储的优越性,为PACS系统存储提供新的存储系统架构模型。     

大型建筑结构健康监测的海量数据处理与数据库开发研究

在大型建筑的结构健康监测中,要对大量不同类型的传感器采集到的数据信号进行处理。基于Oracle数据库开发平台,根据各传感器的分类、采集的时间,建立相应的数据库系统。该系统能有效地对采集到的海量数据进行存储、管理、查询及异常数据的预警处理。将着重介绍该数据库系统的功能、特点、结构以及系统的框架组成,并以振弦式应变传感器采集到的数据信号的实例描述该系统处理海量数据的特点。     

日研究人员研制出新型大容量数据存储系统

日研究人员研制出新型大容量数据存储系统据英国《新科学家》杂志报道，日本电子工业界巨人松下公司将一种新的存储方式和新的存储媒体相结合，研制出了两种大容量数据存储系统。一种是称为ＰＤ（Ｐａｎｄｉｓｃ）的可重写式光盘，其数据读取速度是传统ＣＤ－ＲＯＭ的４倍...     

无线传感器网络中数据存储与查询分析

无线传感器网络是通讯技术高度发展的结果 ,通过建立无线传感器网络能够更好的进行数据的比对查询和存储分析,使人们的信息交流更加便捷快速。文章通过分析传感器的结构与作用,对数据的存储类型和查询方式进行深入探讨,为进一步推广无线传感器网络奠定基础。     

Encoding Random Hot Spots of a Volume Gold Nanorod Assembly for Ultralow Energy Memory

Data storage with ultrahigh density, ultralow energy, high security, and long lifetime is highly desirable in the 21st century and optical data storage is considered as the most promising way to meet the challenge of storing big data. Plasmonic coupling in regularly arranged metallic nanoparticles has demonstrated its superior properties in various applications due to the generation of hot spots. Here, the discovery of the polarization and spectrum sensitivity of random hot spots generated in a volume gold nanorod assembly is reported. It is demonstrated that the two‐photon‐induced absorption and two‐photon‐induced luminescence of the gold nanorods adjacent to such hot spots are enhanced significantly because of plasmonic coupling. The polarization, wavelength, and spatial multiplexing of the hot spots can be realized by using an ultralow energy of only a few picojoule per pulse, which is two orders of magnitude lower than the value in the state‐of‐the‐art technology that utilizes isolated gold nanorods. The ultralow recording energy reduces the cross‐talk between different recording channels and makes it possible to realize rewriting function, improving significantly both the quality and capacity of optical data storage. It is anticipated that the demonstrated technology can facilitate the development of multidimensional optical data storage for a greener future.     

径向基函数神经网络在多维力传感器标定中的应用

维间耦合是制约多维力传感器测量精度的主要因素,为了克服传统线性标定方法的局限性,利用径向基函数（RBF）神经网络强非线性逼近能力进行了多维腕力传感器的静态标定,并将其与最小二乘法和BP神经网络标定法作了比较。以研制的六维腕力传感器为对象进行了实验,结果表明,采用RBF神经网络对多维腕力传感器标定比用最小二乘线性标定有更高的标定精度,网络训练速度则大大快于BP神经网络。这种新方法具有一定的实用价值。     

An experimental model of Chinese textual database

Abstract

A textual database deals with retrieval and manipulation of documents. It allows a user to search on‐line complete documents or parts of documents rather than attributes of documents. Resembling a formatted database which uses a data model as its underlying structure, a textual database has to base its development upon a document model. In this paper, a document model, called the ECHO model, is proposed. The ECHO model provides a document representation, called the ECHO structure, for expressing documents and operations on the representation that serve to express queries and manipulations on documents. It has the ability to provide multiple document structures for a document, a flexible search unit for retrieving textual information, and a subrange search on a textual database. In addition, the ECHO structure is relatively easy to maintain. An architecture of a textual database based on the ECHO model is also proposed. In order to improve the query performance, a refined character inversion method, called ARCIM, is proposed as the text‐access method of the Chinese textual database. The ARCIM can retrieve texts faster than a simple inversion method and requires less space overhead.     

Multidimensional Scaling to Explore Complex Aspects in Dissimilarity Judgment

This paper proposes a model to analyze the structure and context effects involved in dissimilarity judgment. With some restrictions incorporated, the model is also interpreted as a kind of the distance-density model and further interpreted as a mixed distance and content model. Algorithms for multidimensional scaling based on the proposed model are implemented using nonlinear optimization methods. The algorithms are evaluated through a Monte Carlo study, and applications are demonstrated with real data. Problems regarding the model, the algorithms and possible applications are discussed.

     

飞机垂尾抖振极限载荷预测方法

为满足先进战斗机高速、大机动飞行性能的要求,在飞机设计的强度估算与校核中必须考虑抖振载荷的影响,以保证飞机结构在全包线飞行状态中具有足够的强度。按照飞机飞行状态进行抖振飞行子状态划分建立起抖振载荷数据库的数据存储关系,提出根据有限测点处测试的抖振响应重构飞机垂尾结构抖振载荷的方法,并基于所选抖振飞行子状态载荷概率分布模型预测出抖振极限载荷。最后以某飞机垂尾上某节点的抖振极限载荷预测为例,演示用本文方法预测飞机垂尾抖振极限载荷流程。     

Heuristic algorithms for a storage location assignment problem in a chaotic warehouse

The extensive application of emerging technologies is revolutionizing warehouse management. These technologies facilitate working with complex and powerful warehouse management models in which products do not have assigned fixed locations (random storage). Random storage allows the utilization of the available space to be optimized. In this context, and motivated by a real problem, this article presents a model that looks for the optimal allocation of goods in order to maximize the storage space availability within the restrictions of the warehouse. For the proposed model a construction method, a local search algorithm and different metaheuristics have been developed. The introduced algorithms can also be used for other purposes such as to assess when and how it is convenient to perform relocation of stored items to improve the current level of storage space availability. Computational tests performed on a set of randomly generated and real warehouse instances show the effectiveness of the proposed methods.     

冰浆在蓄冰池中的贮存与融化研究进展

总结分析现有的蓄冰池中冰浆贮存及融化在机理、数学模型、实验方面的研究成果,在此基础上,实验研究了入口冰浆流量、冰浆固相含量、初始液面高度和进水管布置等参数对贮存和融化特性的影响。实验发现使用高浓度的二元溶液、高含量冰浆固相以及增大进口流量都可以使冰浆贮存更均匀;增大融冰溶液的流量、增加扰动以及均匀喷撒溶液是避免"沟道"效应从而实现快速、均匀融冰有效手段。     

An adaptive regularization algorithm for recovering the rate constant distribution from biosensor data

We present here the theoretical results and numerical analysis of a regularization method for the inverse problem of determining the rate constant distribution from biosensor data. The rate constant distribution method is a modern technique to study binding equilibrium and kinetics for chemical reactions. Finding a rate constant distribution from biosensor data can be described as a multidimensional Fredholm integral equation of the first kind, which is a typical ill-posed problem in the sense of J. Hadamard. By combining regularization theory and the goal-oriented adaptive discretization technique, we develop an Adaptive Interaction Distribution Algorithm (AIDA) for the reconstruction of rate constant distributions. The mesh refinement criteria are proposed based on the a posteriori error estimation of the finite element approximation. The stability of the obtained approximate solution with respect to data noise is proven. Finally, numerical tests for both synthetic and real data are given to show the robustness of the AIDA.     

Determination of the representativity between two multidimensional data sets by a comparison of their structure

An approach for the investigation and comparison of the data structure in the multidimensional space is proposed. It is based on three properties, namely, the direction of the data sets, the variance–covariance of the data points, and the location of the data sets' centroids. A number of tests have been studied and are presented. It is shown that the combined use of these parameters allows a satisfactory estimation of the representativity between two data sets. Simulated data, as well as real case studies are presented.     

Usage and risk of hydrocarbon refrigerants in motor cars for Australia and the United States

Commercial replacement of fluorocarbons in mobile air conditioning systems (MACS) with typically HC-290/600a[60/40] and minimal precautions began in Idaho in 1993. R290/600a has low environmental impact but mixed with air is flammable and frequencies for fire, injury and cabin overpressure were predicted. No such accidents are known from 1993 to mid-2003. R290/600a suppliers consumption, representative MACS charges and charge termination frequency were used to predict yearly total MACS numbers. Mid-2002 in Australia there were 0.33×10⁶ and at end 2002 in the USA 4.7×10⁶ R290/600a MACS. Integrating over time gave usage for Australia to the end 2002 as 1.09×10⁶ car-years and to mid-2003 for the USA 21.7×10⁶ car-years. The measured US fire, injury and cabin overpressure frequencies are less than 3.2×10⁻⁷ per car year with high probability. This fire frequency is a hundred times lower than predicted because most R290/600a leaks in MACS use are effectively non flammable.