A contribution of the multiquadric method: Interpolation of potential inside the earth

The multiquadric (MQ) method, when converted into a proper integral equation, is a potential function. As a numerical method, it is capable of interpolation without the usual reciprocal distance singularities. An unusual result of a more detailed study is that the Newtonian attraction generated by each volume element inside a material body is a constant, proportional to the product of G and the density. Consequently, potential at the boundary is identical, whether computed internally with a proper integral for material space, or externally by the approach of unit masses from infinity in free space to the boundary points of a sphere. The capability of the proper integral form, and the corresponding MQ numerical approximation provides a basis for interpolation of potential and its functionals inside and on the boundary of the Earth.     

Improved multiquadric method for elliptic partial differential equations via PDE collocation on the boundary

The multiquadric radial basis function (MQ) method is a recent meshless collocation method with global basis functions. It was introduced for discretizing partial differential equations (PDEs) by Kansa in the early 1990s. The MQ method was originally used for interpolation of scattered data, and it was shown to have exponential convergence for interpolation problems.In [1], we have extended the Kansa-MQ method to numerical solution and detection of bifurcations in 1D and 2D parameterized nonlinear elliptic PDEs. We have found there that the modest size nonlinear systems resulting from the MQ discretization can be efficiently continued by a standard continuation software, such as auto. We have observed high accuracy with a small number of unknowns, as compared with most known results from the literature.In this paper, we formulate an improved Kansa-MQ method with PDE collocation on the boundary (MQ PDECB): we add an additional set of nodes (which can lie inside or outside of the domain) adjacent to the boundary and, correspondingly, add an additional set of collocation equations obtained via collocation of the PDE on the boundary. Numerical results are given that show a considerable improvement in accuracy of the MQ PDECB method over the Kansa-MQ method, with both methods having exponential convergence with essentially the same rates.     

数学进化中的知识发现方法

从数学历史发展过程中去发现数学的进化规律,从创造数学符号和包容对立的概念中获得了最早的数学知识.将数学符号组合而成的表达式和方程,使问题变换成了形式化表示,当表达式和方程通过推演和求证,判断其正确性时,就形成了公式和定理,它们是数学中的基础理论.推演和求证过程是采用了等价变换.数学进化中更重要的知识发现方法是利用进化变换(对变量、函数、方程、方法等的变换)来拓展数学的新概念和解决不能求解的问题(可拓变换),从而建立了数学的理论体系.创造、包容、形式化变换、等价变换和进化变换都是数学进化中的知识发现方法.     

Topic discovery and evolution in scientific literature based on content and citations

Researchers across the globe have been increasingly interested in the manner in which important research topics evolve over time within the corpus of scientific literature. In a dataset of scientific articles, each document can be considered to comprise both the words of the document itself and its citations of other documents. In this paper, we propose a citation- content-latent Dirichlet allocation (LDA) topic discovery method that accounts for both document citation relations and the con-tent of the document itself via a probabilistic generative model. The citation-content-LDA topic model exploits a two-level topic model that includes the citation information for ‘father’ topics and text information for sub-topics. The model parameters are estimated by a collapsed Gibbs sampling algorithm. We also propose a topic evolution algorithm that runs in two steps: topic segmentation and topic dependency relation calculation. We have tested the proposed citation-content-LDA model and topic evolution algorithm on two online datasets, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) and IEEE Computer Society (CS), to demonstrate that our algorithm effectively discovers important topics and reflects the topic evolution of important research themes. According to our evaluation metrics, citation-content-LDA outperforms both content-LDA and citation-LDA.     

符合动态演变特性的网格资源发现机制研究

近年来人们对如何提高网格资源发现效率做了大量的研究,但却忽略了适应网格资源动态演变特性的重要性.针对这一问题,结合小世界理论的网络特征,提出了一种新的基于P2P分布式结构化的网格资源发现机制.通过计算资源节点间属性相似度的方法,将网格资源分类组织在不同的虚拟组织中,结合P2P技术构建出两层覆盖式资源发现模型,并设计出相应的资源查找算法DSRD (distributed structure grid resource discovery).仿真实验结果表明,DSRD算法既能够适应资源的动态特性,同时又可有效地提高资源发现效率.     

A framework for knowledge discovery and evolution in databases

A concept for knowledge discovery and evolution in databases is described. The key issues include: using a database query to discover new rules; using not only positive examples (answer to a query), but also negative examples to discover new rules; and harmonizing existing rules with the new rules. A tool for characterizing the exceptions in databases and evolving knowledge as a database evolves is developed     

Miscellaneous error bounds for multiquadric and related interpolators

We establish several types of a a priori error bounds for multiquadric and related interpolators. The results are stated and proven in the general multivariate case. These estimates show, for example, that in many cases such interpolators converge very quickly and can be used in the recovery of band limited functions from discrete data. We also include numerical experiments which illustrate the theoretical results.     

基于资源区域的网格资源发现方法

资源发现是整个网格系统的热点研究问题。结合P2P技术提出了一种基于资源区域的网格资源发现的新方法,按照资源的类型将网格资源划分为多个区域,具有相同类型资源的网格信息节点组织在同一区域中,各区域由一个域中心节点进行管理,各域中心节点形成P2P层。把网格中的资源分为域间－域内两类,从而大大提高了查询效率和通信效率,减少了网络流量。     

一种基于新词发现的Web文本表示方法

Web文本表示是Web文本特征提取和分类的前提,最常用的文本表示是向量空间模型（VSM）,其中向量一般是基于词的特征项。由于向量空间模型本身没有考虑文本上下文间的潜在概念结构（如词汇间的共现关系）,而Web文本是一种半结构化文本,同时经常有新词出现,因此在VSM基础上提出了一种基于新词发现的Web文本表示方法：首先进行预处理将网页转化为文本;然后进行文本分词;接着通过二元互信息进行新词发现,同时把新词加入字典重新分词;最后用词和新词共同来表示Web文本。实验结果表明,该方法可以帮助识别未登录词并扩充现有字典,能够增强Web文本表示能力,改善Web文本的特征项质量,提高Web文本分类效果。     

一种分布式Web服务发现方法

Web服务发现系统由一个或多个服务注册器连接组成一定的系统拓扑来存储和维护服务信息,服务注册器的连接拓扑直接关系到Web服务发现系统的可扩展性。采用层次模型在数据层定义统一的动态元组模型来解决各种数据源和数据模型的异构性,在抽象层定制统一的发布和查询API实现统一的访问方式,在网络层构造一种全新的双层结构保证整个系统的可扩展性、灵活性和鲁棒性,设计实现了一种分布式Web服务发现方法。给出了适应双层拓扑结构的两阶段查找算法,并对算法的时间、空间和消息复杂性进行了分析。实验结果表明,该Web服务发现方法具有明显的自组织特性和良好的可扩展性,适应Web服务自主,动态变化和强分布特点,同时两阶段查找算法具有较好的服务查找能力。     

一种基于扩展ONS的链式发现服务方法

总结了目前最新的EPC网络发现服务方法,在此基础上,提出了一种基于扩展ONS的链式发现服务方法。该方法通过扩展ONS静态信息,解决了EPC物品的当前位置的存储问题,并通过在企业EPCIS中维护指针数据库,从而实现了链式发现服务。详细介绍了链式发现服务的工作过程,对其可靠性和安全性等关键点做了细致讨论,并提出了相应的应对策略。最后,从多个方面出发,将该方法与其他方法进行比较,论证了该方法的优越性。     

基于轨迹点聚类的航路发现方法

为了加强对局部空域航路的掌握和管理,提出一种基于轨迹点聚类的航路发现方法.首先,针对根据真实数据的分布特点生成的仿真数据,采用预处理模块对轨迹数据的噪声进行削弱和剔除;其次,提出一种包括孤立点剔除、轨迹重采样、轨迹点聚类、聚类中心修正和连接聚类中心五个部分的航路发现方法,对航路进行提取;最后,对航路提取结果进行了可视化...     

基于SSDP和DNS-SD协议的双栈主机发现方法及其安全分析

随着全球互联网IPv4地址分配耗尽,IPv6开始加速推广和部署。双栈技术允许设备同时启用IPv4和IPv6 栈,这意味着用户暴露了双倍的安全风险。尽管现有的工作可实现对部分双栈服务器的识别和测量,但仍存在以下问题。首先,双栈主机识别需要对主机服务进行深层协议识别,然而这种方式会消耗过高的扫描资源。其次,实际的网络服务提供商有可能在分布式主机上提供一致的服务,使得通过服务指纹进行双栈主机判别的准确性难以保证。针对此问题,利用局域网服务发现协议将主机服务与 IP 地址绑定的协议特性,提出了基于SSDP和DNS-SD协议的双栈主机发现方法：在IPv4网络环境下,通过SSDP诱导目标主机主动向构建的IPv6服务器发送请求,然后从服务器日志中提取IPv6地址;或通过DNS-SD协议枚举目标主机的服务列表及其对应的AAAA记录,获取目标主机IPv6地址,实现双栈地址对的发现。该方法直接从IPv4主机获取其IPv6 地址,确保了发现的双栈主机的准确性,同时,在发现过程中只需要针对特定协议构造请求数据包,极大地节约了扫描资源。基于该方法,对全球IPv4网络意外暴露的SSDP主机和DNS-SD主机进行了测量,共收集到158 000个不重复的IPv6地址,其中55 000个为拥有全球可达IPv6地址的双栈主机地址对。与现有工作将测量目标聚焦于双栈服务器不同,该方法主要针对终端用户和客户端设备,构建了迄今为止尚未探索过的活跃IPv6设备独特集合及双栈主机地址对集合。通过对获取的IPv6地址编址类型的分析,随机生成已成为当前IPv6地址分配的主要方式,这一方式大大降低了IPv6主机被扫描发现的可能性。特别地,通过对双栈主机的开放端口和服务测量,发现双栈主机在不同协议栈上的安全策略差异：IPv6 栈上暴露了更多高风险服务,扩大了主机的攻击面。研究结果表明,IPv6 地址空间遍历扫描的不可行性缓解了 IPv6 的安全风险,但错误的网络配置大幅增加了这些高风险的IPv6主机被发现的可能性,用户应该重新审视双栈主机上的IPv6安全策略。     

基于语义的Web服务发现方法的研究

传统的服务发现技术是建立在语法描述的基础上,主要采用的服务发现机制是WSDL和UDDI规范相结合的解决方案,这些发现方法查准率极其低下,已经不能很好的满足用户需要.在研究本体与语义web服务的基础上,提出了一种基于语义的web服务发现框架与服务发现算法,从而提高查准率.     

联系发现在证券客户划分中的应用研究

证券客户划分可以帮助证券公司掌握更多的客户特征,但是传统的证券客户划分方法都是基于客户自身属性进行分析并划分的,缺少对证券客户之间联系信息的分析,使得划分结果具有一定的局限性和偏差性。针对这种问题,首先分析了证券客户的属性,提取客户之间行为的联系信息,在此基础上利用联系发现的方法对证券客户进行划分,通过联系假设、联系产生、联系确定等三个阶段得到划分结果。对比实验表明,新方法减少了计算量,提高了划分效率,具有较好的客户划分准确率。     

Multizone decomposition for simulation of time-dependent problems using the multiquadric scheme

This paper discusses the application of the multizone decomposition technique with multiquadric scheme for the numerical solutions of a time-dependent problem. The construction of the multizone algorithm is based on a domain decomposition technique to subdivide the global region into a number of finite subdomains. The reduction of ill-conditioning and the improvement of the computational efficiency can be achieved with a smaller resulting matrix on each subdomain. The proposed scheme is applied to a hypothetical linear two-dimensional hydrodynamic model as well as a real-life nonlinear two-dimensional hydrodynamic model in the Tolo Harbour of Hong Kong to simulate the water flow circulation patterns. To illustrate the computational efficiency and accuracy of the technique, the numerical results are compared with those solutions obtained from the same problem using a single domain multiquadric scheme. The computational efficiency of the multizone technique is improved substantially with faster convergence without significant degradation in accuracy.     

Comments on "A computer-aided root-locus method"

This note generalizes the result given by C. T. Pan and K. S. Chao in the above paper to the case where the gain is negative, and emphasizes the use of Newton-Raphson for correcting starting points originated from complex multiple poles. Finally, it proposes the use of mixed scales in plotting RL's with this methodology.     

Identification of non-linear processes using reciprocal multiquadric functions

In this paper radial basis function (RBF) networks are used to model general non-linear discrete-time systems. In particular, reciprocal multiquadric functions are used as activation functions for the RBF networks. A stepwise regression algorithm based on orthogonalization and a series of statistical tests is employed for designing and training of the network. The identification method yields non-linear models, which are stable and linear in the model parameters. The advantages of the proposed method compared to other radial basis function methods and backpropagation neural networks are described. Finally, the effectiveness of the identification method is demonstrated by the identification of two non-linear chemical processes, a simulated continuous stirred tank reactor and an experimental pH neutralization process.     

基于不确定性知识发现的入侵报警关联方法

针对入侵检测系统报警信息量大、琐碎和分散的问题,提出了一种基于不确定性知识发现的入侵报警关联方法。该方法的知识发现部分采用提出的不确定性序列模式发现算法—CWINEPI对报警数据进行序列模式发现,并将经过筛选后获得的入侵报警序列模式转化成入侵报警精简规则;再对入侵报警序列模式进行关联以获取攻击模式,并转化为入侵场景重建规则。入侵报警关联部分利用获取的入侵报警精简规则和入侵场景重建规则,以模式匹配方法构造报警关联引擎,对多个入侵检测系统上报的入侵报警进行关联。美国国防部高级研究计划局2000年入侵评测数据（DARPA2000）的报警数据验证了知识发现部分的良好性能;测试环境中的入侵报警的关联结果表明了该方法是高效、可行的。