High-accuracy quadrature methods for solving boundary integral equations of steady-state anisotropic heat conduction problems with Dirichlet conditions

This paper presents the mechanical quadrature methods (MQMs) for solving the boundary integral equations of steady-state anisotropic heat conduction equation on the smooth domains and polygons, respectively. The costless and high-accurate Sidi–Israeli quadrature formula are applied to deal with the integrals in which the kernels have a logarithmic singularity. Especially, the Sidi transformation is used for the polygon cases in order to obtain a rapid convergence by degrading the singularity at the corners on the boundary. The convergence and stability of the MQMs solution are proved based on Anselone's collective compact theory. In addition, asymptotic error expansion of the MQMs shows that the approximation order is of O(h³), where h is the partition size of the boundary. Finally, numerical examples are tested and results verify the theoretical analysis.     

A probabilistic integrated object recognition and tracking framework

This paper describes a probabilistic integrated object recognition and tracking framework called PIORT, together with two specific methods derived from it, which are evaluated experimentally in several test video sequences. The first step in the proposed framework is a static recognition module that provides class probabilities for each pixel of the image from a set of local features. These probabilities are updated dynamically and supplied to a tracking decision module capable of handling full and partial occlusions. The two specific methods presented use RGB color features and differ in the classifier implemented: one is a Bayesian method based on maximum likelihood and the other one is based on a neural network. The experimental results obtained have shown that, on one hand, the neural net based approach performs similarly and sometimes better than the Bayesian approach when they are integrated within the tracking framework. And on the other hand, our PIORT methods have achieved better results when compared to other published tracking methods in video sequences taken with a moving camera and including full and partial occlusions of the tracked object.     

三唑类化合物分子结构与防治小麦锈病活性关系的研究

本文用多元线性回归分析、逐步线性回归分析、主成分回归分析和偏最小二乘分析方法研究了三唑类化合物结构与防治小麦锈病活性的关系，并建立了构效关系式。对该系列化合物结构的变化对其生物性的影响作了一定的探讨。提出了设计高活性化合物的可能结构要求，并将研究结果用于实际化合物的设计中，取得了初步结果。     

利用网络日志去探索影响网站访问的先决因素

如何优化网站结构、提高访问量呢?在本文中,我们将提出一些客观方法来探讨网站的访问与一些先决因素之间关系,这些先决因素在早期利用web日志的研究中都曾经验证过。我们从万达公司网站(www.wondersgroup.com)上采集了日志数据,并建立了一个研究模型来解释这个关系。     

High Order Finite Difference Approximations of Electromagnetic Wave Propagation Close to Material Discontinuities

Electromagnetic wave propagation close to a material discontinuity is simulated by using summation by part operators of second, fourth and sixth order accuracy. The interface conditions at the discontinuity are imposed by the simultaneous approximation term procedure. Stability is shown and the order of accuracy is verified numerically.     

电力系统同调机群的识别方法

在对电力系统中同调机群的识别方法进行研究的同时，并对以往的各种同调机群的识别方法也进行了归纳总结，针对这些方法所存在的问题，给出了一种新的较为实用的同调机群识别方法。     

国际工程项目承包中招标方法研究

根据概率和数理统计分析，提出工程项目招标方法中的模拟技术，给出不同招标方法的比较研究结果。     

采样算子调整的径向基网络增量映射学习算法

为了提高增量映射学习(IPL)算法的效率,调整了径向基神经网络基函数的中心及方差,以达到调整采样算子的目的,同时,通过神经元函数相关性的计算,确定添加新神经元时,相关函数的阈值,为系统结构调整提供相应依据.新方法步骤相对简单,所以算法速度较快;仿真结果表明,由于系统参数得到调整,对于同一问题,改进IPL算法得到的径向基神经网络结构较一般算法得到的网络结构简单,输出结果也较为精确.     

A framework for determining design correctness

Quality is one of the main concerns in today's systems and software development and use. One important instrument in verification is the use of formal methods, which means that requirements and designs are analyzed formally to determine their relationships. Furthermore, since professional software design is to an increasing extent a distributed process, the issue of integrating different systems to an entity is of great importance in modern system development and design. Various candidates for formalizing system development and integration have prevailed, but very often, particularly for dynamic conflict detection, these introduce non-standard objects and formalisms, leading to severe confusion, both regarding the semantics and the computability. In contrast to such, we introduce a framework for defining requirement fulfillment by designs, detecting conflicts of various kinds as well as integration of heterogeneous schemata. The framework introduced transcends ordinary logical consequence, as it takes into account static and dynamic aspects of design consistency and, in particular, the specific features of the state space of a specification. Another feature of the approach is that it provides a unifying framework for design conflict analysis and schema integration.     

Optimal Ordered Problem Solver

We introduce a general and in a certain sense time-optimal way of solving one problem after another, efficiently searching the space of programs that compute solution candidates, including those programs that organize and manage and adapt and reuse earlier acquired knowledge. The Optimal Ordered Problem Solver (OOPS) draws inspiration from Levin's Universal Search designed for single problems and universal Turing machines. It spends part of the total search time for a new problem on testing programs that exploit previous solution-computing programs in computable ways. If the new problem can be solved faster by copy-editing/invoking previous code than by solving the new problem from scratch, then OOPS will find this out. If not, then at least the previous solutions will not cause much harm. We introduce an efficient, recursive, backtracking-based way of implementing OOPS on realistic computers with limited storage. Experiments illustrate how OOPS can greatly profit from metalearning or metasearching, that is, searching for faster search procedures.