基于Hadoop的煤矿数据中心架构设计

根据煤矿安全生产业务需求及智慧矿山发展要求,新型的煤矿数据中心需满足对同一时空坐标体系下煤矿海量、多元数据的高效处理、缓存、计算、存储与发布。针对传统煤矿数据中心各类数据离散存储,数据集成、业务应用及数据分析难度大等问题,设计了一种基于Hadoop的煤矿数据中心架构。采用Storm实时数据流引擎进行数据实时计算,并应用MapReduce,Spark实现批处理计算和内存计算,解决高频时序数据存储与海量数据计算问题;采用Hadoop分布式文件系统(HDFS)实现文件的可靠存储,并采用HBase分布式存储数据库实现历史数据的持久化存储,利用其无模式稀疏设计满足同一时空坐标体系下的数据分析需求;采用Redis作为实时数据库存储数据快照进行最新数据检索。基于Hadoop的煤矿数据中心充分利用大数据技术的高速数据存取和压缩性能,通过统一的云计算数据中心,有效降低了煤炭企业数据应用的复杂度及数据中心日常运维难度,可为智慧矿山建设奠定数据基础。     

基于Hadoop的企业云存储技术探索

Hadoop平台作为一种新技术,近些年发展非常迅速,它的应用不仅能实现计算的"平民化",而且它可以忽略开发并行应用程序的细节,使程序员只需要专注于业务逻辑即可,从而大大提高了编程开发效率。在云计算相关技术日益发展的今天,Hadoop在企业云存储平台构建中的应用已成为当前企业信息化管理的重要发展趋势,本文在对基于Hadoop的企业云存储构建所依赖的云计算技术以及Hadoop平台作分析说明的基础上,就基于Hadoop的企业云存储的实现进行探究。     

大规模文本数据的分类系统的设计与实现

云计算模式解决了大规模数据存储和计算能力上存在的瓶颈,为大规模数据挖掘技术提供了理想的计算模式和技术手段。分析Hadoop云计算平台的数据存储和计算模型,在云计算模式的基础上．实现云计算平台上Web文本数据的贝叶斯分类模型。对于大规模数据挖掘中的数据存储和计算的问题和难点．提出一种高效、低成本的解决方案。     

基于Hadoop和双密钥的云计算数据安全存储策略设计

针对原有的Hadoop平台仅通过CRC-32循环冗余校验保证数据存储的安全性,设计了一种基于双密钥和混沌信号的云计算安全存储策略;首先,介绍了原有的Hadoop框架下的数据存储对应的文件读写过程,并基于加密机制设计了改进的Hadoop数据存储模型,然后根据云存储数据量大和响应要求及时的特点,设计了一种基于双密钥的改进对称密钥算法,在传统的私钥的基础上加入动态公钥,并作为敏感函数的输入获得最终的密钥,从而实现明文的加密和密文的解密,最终定义了具体的基于Hadoop和改进双密钥对称加密算法的云计算安全存储算法;通过搭建Hadoop仿真实验平台进行实验,结果表明文中方法能有效地实现云计算环境下的安全存储,存储时间与其它方法相比少15%以上,具有安全性高和存储效率高的优点,具有一定的优越性。     

基于云环境下的海量大数据存储系统设计

云计算是目前国际和国内新兴的一项热门技术,正在给人们的生产生活方式带来深刻的变革;在分布式文件系统中,为了实现数据的可用性和持久性,数据通常被分割成大小相同的文件块,通过多副本的形式分布存储在不同地理位置;大型的云计算服务提供商拥有自己的数据中心,这些数据中心往往分布在世界的不同角落,数据以副本的形式分布在不同的地理位置可以实现更好的容错机制,从而提供高可用的持久化的数据存储;文章主要研究了海量大数据存储系统设计,系统设计以Hadoop为平台,提出了一种新的基于云计算环境的海量大数据存储设计方法,主要给出了文件存储方案设计以及副本方案设计等,为云计算海量数据存储与管理提供了一种可行的关键技术方案。     

基于Hadoop的云存储技术在档案馆的应用研究

随着大数据和云计算的应用,传统档案馆的信息储存方式已无法适应大数据时代的新要求。笔者基于Hadoop平台介绍了HDFS分布式文件系统和Map-Reduce计算框架,探索了基于Hadoop的档案馆云存储构架,并结合其优势以及档案馆提供的不同类型服务,讨论了其在档案馆应用中的优势和未来的发展趋势。     

基于Hadoop平台的校本数据中心建设研究

本文通过搭建Hadoop平台搭建校本数据中心,并将数据集中存储在HBase数据库中.基于Hadoop的校本数据中心,提供了强大的数据统一存储和计算力,将校本数据进行了整合及标准化,形成数据中心的标准库和主题库,为广大师生提供数据查询、数据分析等各种数据服务.校本数据中心能够实现内信息化精益化运营分析,支持实时统计分析的...     

基于Hadoop的分布式数据库系统

云计算是当前研究的热点,包括分布式存储和分布式计算技术。Hadoop是一个能够让用户轻松架构和使用的分布式计算平台,用户可以轻松地在Hadoop上开发和运行处理海量数据的应用程序。基于对大量数据进行处理和分析的需求,本文分析了基于Hadoop的分布式计算平台,介绍基于Hadoop的分布式数据库系统。     

基于云计算平台的电力全业务数据中心建设研究

针对电力全业务数据中心建设过程中,传统数据中心普遍存在的成本高、不易扩展、数据存储和处理等方面缺陷,提出基于云计算平台的电力全业务数据中心建设,将云计算平台框架与电力全业务数据框架结合,充分利用云平台的数据存储、数据计算、以及数据分析处理优势,对电网公司的全类型业务数据通过接入、采集和过滤,构造出全业务数据模型,进行数据分析挖掘,从而优化公司各类业务、管理及决策,有效实现电网公司全业务数据中心的建设和治理。     

一种基于Hadoop的Scool云存储平台

针对海量数据的指数级增长,现有的文件存储系统很难满足现有系统需求,提出基于Hadoop的Scool云存储平台,系统通过采用Linux集群技术、分布式文件系统和云计算框架等技术,来实现海量数据存储和高速数据处理。通过比较云存储和传统存储模式的区别,分析了云存储技术优势和可行性,介绍了云存储架构模型,设计了基于Hadoop的Scool云存储文件管理系统,为今后深入研究云计算和云存储提供了一定的基础。     

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.     

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.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.     

Editorial: Special issue on recent advances in hybrid control theory and applications

正The demands of a rapidly advancing technology for faster and more accurate controllers have always had a strong influence on the progress of automatic control theory.In recent years control problems have been arising with increasing frequency in widely different areas,which cannot be addressed using conventional control techniques.The principal reason for this is the fact that a highly competitive economy is forcing systems to operate in regimes where     

Information for Authors

正Aim The Journals of Zhejiang University-SCIENCE(A/B/C)areedited by the international board of distinguished Chinese andforeign scientists,and are aimed to present the latest devel-opments and achievements in scientific research in China andoverseas to the world’s scientific circles,especially to stimulateand promote academic exchange between Chinese and for-eign scientists everywhere.     

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.