Lossless compression and information hiding in images

This paper presents an image lossless compression and information-hiding schemes based on the same methodology. The methodology presented here is based on the known SCAN formal language for data accessing and processing. In particular, the compression part produces a lossless compression ratio of 1.88 for the standard Lenna, while the hiding part is able to embeds digital information at 12.5% of the size of the original image. Results from various images are also provided.     

图像加密技术新进展

本文综述了图像加密技术的最新进展,阐述了近几年发展起来的（1）基于矩阵变换/像素置换;（2）基于伪随机序列;（3）基于SCAN语言;（4）基于“密钥图像”;（5）基于四叉树编码及SCAN语言;（6）基于矢量量化压缩编码及商业密码等图像加密技术,比较了他们的优缺点和适用范围．文章尤其详细介绍了混沌加密技术,指出了应用混沌技术的好处和一些值得进一步研究的问题．     

并行SCAN算法及其可扩放性分析

SCAN算法是构成某些并行算法的一个简单而常用的基本模块。本文首先描述了SCAN操作及其串行和并行算法的设计；然后介绍了并行算法的可扩放性概念、度量及其分析方法；最后分析了不同互连结构上的并行SCAN算法的可扩放性，并用一组在Transputer阵列上的实验对分析所得的结论进行了验证。     

基于MapReduce的图结构聚类算法

图结构聚类（SCAN）是一种著名的基于密度的图聚类算法。该算法不仅能够找到图中的聚类结构,而且还能发现图中的Hub节点和离群节点。然而,随着图数据规模越来越大,传统的SCAN算法的复杂度为O（m^1.5）（m为图中边的条数）,因此很难处理大规模的图数据。为了解决SCAN算法的可扩展性问题,本文提出了一种新颖的基于MapReduce的海量图结构聚类算法MRSCAN。具体地,我们提出了一种计算核心节点,以及两种合并聚类的MapReduce算法。最后,在多个真实的大规模图数据集上进行实验测试,实验结果验证了算法的准确性、有效性,以及可扩展性。     

基于扫描模式和混沌序列的彩色图像加密算法的研究

提出了一种新的基于扫描模式和混沌序列的图像加密算法,该算法使用正规语言来产生扫描模式,并且通过对二维存储空间的不同访问方式来产生非常大的扫描路径曲线.通过对扫描模式的像素位置的改变和灰度值的替代相结合的方式,来共同完成图像的加密算法.该算法具有良好密码特性的非线性耦合结构,并且在每次迭代过程中使用了密钥的融合操作,进一步提高了该加密算法的安全性.实验以lena等24位标准彩色图像进行仿真,结果表明,该算法具有良好的加密安全性和效率.     

ParaC:面向GPU平台的图像处理领域的编程框架

GPGPU加速器是当前提高图像处理算法性能的主流加速平台,但是,在GPGPU平台上,同一个程序充分利用硬件体系结构特征和软件特征的优化版本与简单实现版本在性能上会有数量级的差异。GPGPU加速器具有多维多层的大量执行线程和层次化存储体系结构,后者的不同层次具有不同的容量、带宽、延迟和访问权限。同时,图像处理应用程序具有复杂的计算操作、边界处理规则和数据访问特性。因此,任务的并发执行模式、线程的组织方式和并发任务到设备的映射不仅影响到程序的并发度、调度、通信和同步等特性,而且也会影响到访存的带宽、延迟等。因此,GPGPU平台上的程序优化是一个困难、复杂且效率较低的过程。本文提出基于语言扩展的领域编程模型：ParaC。ParaC编程环境利用高层语言扩展描述的程序语义信息,自动分析获取应用程序的操作信息、并发任务间的数据重用信息和访存信息等程序特征,同时结合硬件平台特征,利用基于领域先验知识驱动的编译优化模型自动生成GPGPU平台上的优化代码,最后,利用源源变换编译器生成标准OpenCL程序。本文在测试用例上的实验结果表明,ParaC在GPGPU平台上自动生成的优化版本相对于手工优化版本的加速比最高达到3.22倍,但代码行数只是后者的1.2%到39.68%。     

基于马尔可夫链的Web访问序列挖掘算法

Web问序列的数据挖掘有助于提高Web的访问质量,但序列是数据挖掘中一个比较困难的问题,经典序列算法普遍存在时间和存储空间开销过大的缺陷。提出了一种基于马尔可夫链的Web访问序列挖掘算法,可以通过较少的计算量发现请求网页的相关性。并将其用于某培训中心网站的设计,取得了良好的效果。     

移动实时环境下一种改进的广播调度算法

在网络带宽不对称的移动实时环境中,数据广播是一种有效的数据访问方式。针对这种网络特性,分析了现今已经存在的某些广播调度算法。针对UFO算法,分别提出了SBS算法和CRS算法,它们从服务器、移动客户端两个方面进行了改进。两种算法可以根据给定的数据项访问概率分布,自动生成广播调度。通过理论分析和实验结果表明,该算法不会产生事务重启,并且可以有效减少数据的访问时间,使用户访问数据广播的平均等待时间最小。     

List Factoring and Relative Worst Order Analysis

Relative worst order analysis is a supplement or alternative to competitive analysis which has been shown to give results more in accordance with observed behavior of online algorithms for a range of different online problems. The contribution of this paper is twofold. As the first contribution, it adds the static list accessing problem to the collection of online problems where relative worst order analysis gives better results. List accessing is a classic data structuring problem of maintaining optimal ordering in a linked list. It is also one of the classic problems in online algorithms, in that it is used as a model problem, along with paging and a few other problems, when trying out new techniques and quality measures. As the second contribution, this paper adds the non-trivial supplementary proof technique of list factoring to the theoretical toolbox for relative worst order analysis. List factoring is perhaps the most successful technique for analyzing list accessing algorithms, reducing the complexity of the analysis of algorithms on full-length lists to lists of length two.     

TSCAN:利用并行策略改进的图结构聚类算法

近年来,图数据聚类在学术界引起了广泛的关注,许多优秀的聚类方法,如模块度优化算法、谱聚类,以及基于密度的聚类算法在图数据上取得了很好的效果。SCAN是一种著名的基于密度的图聚类算法,该算法不仅能够找出图中的聚类,而且还能够发现不同聚类间的Hub节点,以及图中的离群点。然而,该算法存在两方面的局限性：首先,在大规模图数据上,该算法需要耗费大量的时间用于计算图中每条边的结构相似性;另一方面,该算法存在两个参数[ε]和[μ],并且对这两个参数比较敏感。为了解决其局限性,提出了一种基于OpenMP的并行算法来求解节点相似性,并且提出了两种有效的负载均衡策略;其次,提出一种基于三角形的新型图结构聚类算法TSCAN。该模型能够有效降低算法对参数的敏感性,而且还能够发现重叠以及更稠密的社区。在多个大规模数据集上实验发现,基于多核的并行算法能够达到近乎线性的加速比,而且TSCAN算法对参数不敏感,能有效发现重叠社区。     

基于C#.NET的Access数据库创建与访问

C#是用于.NET开发的一种语言,并且是唯一为.NET Framework设计的语言,ADO是微软极力推荐使用的最新的数据库访问技术,Access数据库是用户通常选择的方便易用的数据库,具有广泛的应用基础。     

Object-oriented programming—what for?

Object-oriented programming can improve the structure of a program as well as its extensibility and re-usability. However, it can also cause problems: one has to master large class libraries; the control flow of a program is cluttered among many small operations; and accessing all data via procedures reduces efficiency. Therefore, objectoriented programming cannot always be recommended. It is well suited for interactive applications and for programs which maintain heterogeneous data structures where additional variants of the data may be added later. It should not be used for closed algorithms which work on simple data or for time-critical applications. This paper deals with the following questions: When should classes be used? What are the typical application areas of object-oriented programming? Examples are included which demonstrate problems that can be solved elegantly with classes. The language Object Oberon is introduced.     

PICQUERY: a high level query language for pictorial databasemanagement

A reasonably comprehensive set of data accessing and manipulation operations that should be supported by a generalized pictorial database management system (PDBMS) is proposed. A corresponding high-level query language, PICQUERY, is presented and illustrated through examples. PICQUERY has been designed with a flavor similar to QBE as the highly nonprocedural and conservational language for the pictorial database management system PICDMS. PICQUERY and a relational QBE-like language would form the language by which a user could access conventional relational databases and at the same time pictorial databases managed by PICDMS or other robust PDBMS. This language interface is part of an architecture aimed toward data heterogeneity transparency over pictorial and nonpictorial databases     

Image and video encryption using SCAN patterns

This paper presents a new method for image and video encryption and a first stage lossy video compression based on frames difference before the encryption. The encryption methods are based on the SCAN methodology which is a formal language-based two-dimensional spatial accessing methodology which can generate very large number of scanning paths or space filling curves. The image encryption is performed by SCAN-based permutation of pixels and a substitution rule which together form an iterated product cipher. The video encryption is performed by first lossy compressing adjacent frame differences and then encrypting the compressed frame differences. The main characteristics of the proposed methods are image encryption, first stage compression-based frames differences and encryption of video whose compression error can be bounded pixelwise by a user specified value, very large number of encryption keys, and ability to encrypt large blocks of any digital data. Results from the use of the methods proposed here are also provided.     

Parallel parsing of Tree Adjoining Grammars on the Connection Machine

This paper describes a parsing algorithm for Tree Adjoining Grammar (TAG) and its parallel implementation on the Connection Machine. TAG is a formalism for natural language that employs trees as the basic grammar structures. Parsing involves the application of two operations, called adjunction and substitution, to produce derived tree structures. Sequential parsing algorithms for TAGs run in time quadratic in the grammar size, which is impractical for the very large grammars currently being developed for natural language. This paper presents two parallel algorithms, one running in time nearly linear in the grammar size, and the other running in time logarithmic in the grammar size. Both parallel algorithms were implemented on a Connection Machine CM-2 and performance measurements were obtained for varying grammar sizes.This research was supported in part by NSF Grant BNS-9022010, by the ARO Center for Excellence in Artificial Intelligence, University of Pennsylvania, and by the Army High Performance Computing Research Center (AHPCRC), University of Minnesota.     

Expression templates for partial differential equations

The implementation of numerical algorithms for solving partial differential equations costs a lot of time and the optimization of such codes is difficult. These problems can be reduced by expression templates for partial differential equations. Using this concept, one can implement numerical algorithms for PDE’s in a language which is close to the mathematical language. Expression templates give the compiler global informations on an expression such that the optimization of the code can be left to the compiler. Numerical results for the Stokes operator on general domains in 3D are presented. Received: 18 July 2000 / Accepted: 27 October 2000     

基于相对密度的社团结构探测算法

社团结构发现方法已经成为复杂网络的一个研究热点。在分析目前一些典型的社团探测算法的基础上,该文提出基于相对密度的社团结构划分方法,该方法可以有效地解决SCAN算法中对参数值过于敏感、参数值难以设置以及高密度社团完全被相连的低密度所包含等问题。把该算法应用到已知社团结构的计算机生成网络中,并与SCAN算法的划分结果进行比较。实验结果表明,该算法是有效可行的。     

离散萤火虫优化算法求解概率旅行商问题

对随机组合优化问题中的概率旅行商问题(PTSP)的理论和方法进行了研究分析,采用现代进化算法中有代表性发展优势的萤火虫优化算法(FA),提出一种离散萤火虫优化算法(DFA)以求解.其中引入了新的学习机制使其相比原始的萤火虫优化算法,更容易搜索到全局最优解,有更好的收敛性能.实验中用TSPLIB中的经典实例进行测试来验证其可行性.考察了萤火虫数量和进化迭代次数对求解结果性能的影响,并将DFA与GA、PSO和ACO等其他著名的进化计算算法进行性能比较.实验结果证实了DFA无论对固定访问概率,还是访问概率为区间内随机数等不同情况,都具有良好的有效性和高效性,因此对求解随机组合优化系列问题的有效解决具有一定参考和借鉴价值.     

基于BasicExcel的读写Excel方法研究

分析在Visual Studio 2005下利用C＋＋语言读取Microsoft Office Excel文件内容的几种典型方法的优缺点。当读写不含公式、图表Excel文件中的大量数据时可以采用读写Excel非常快的BasicExcel方法,本文详细给出一种修改Ba-sicExcel类的加载函数、Sheet页操作函数、读写单元格函数、另存为函数的方法,使该类能够很好地支持中文平台。     

Efficient algorithms for answering queries with unsorted multilists

Three algorithms are given in this paper, each one increasing in complexity and efficiency, for parallel tracing of unsorted multilists. These algorithms avoid multiple record accessing for disjunctive queries, and they attempt to reduce the amount of seek action required to access all the records that satisfy a query. The algorithms are more efficient and no more complex than the general algorithm of Hsiao and Harary. The algorithms can enable, in some cases, the same querying efficiency obtainable with sorted multilists. Hence, efficiencies in on-line querying and updating are simultaneously accomplished.