采用信息增益率的混合入侵检测模型设计

针对现有混合入侵检测模型仅定性选取特征而导致检测精度较低的问题，同时为了充分结合误用检测模型和异常检测模型的优势，提出一种采用信息增益率的混合入侵检测模型.首先，利用信息增益率定量地选择特征子集，最大程度地保留样本信息；其次，采用余弦时变粒子群算法确定支持向量机参数构建误用检测模型，使其更好地平衡粒子在全局和局部的搜索能力，然后，选取灰狼算法确定单类支持向量机参数构建异常检测模型，以此来提高对最优参数的搜索效率和精细程度，综合提高混合入侵检测模型对攻击的检测效果；最后，通过两种数据集进行仿真实验，验证了所提混合入侵检测模型具有较好的检测性能.     

An orthogonal basis for the hyperbolic hybrid polynomial space

Motivated by the wide usage of the Tchebyshev basis and Legendre basis in the algebra polynomial space, we construct an orthogonal basis with the properties of the H-Bézier basis in the hyperbolic hybrid polynomial space, which is similar to the Legendre basis and holds remarkable properties. Moreover, we derive the transformation matrices that map the H-Bézier basis and the orthogonal basis forms into each other. An example for approximating the degree reduction of the H- Bézier curves is sketched to illustrate the utility of the orthogonal basis.     

Boundary knot method for 2D and 3D Helmholtz and convection–diffusion problems under complicated geometry

The boundary knot method (BKM) of very recent origin is an inherently meshless, integration‐free, boundary‐type, radial basis function collocation technique for the numerical discretization of general partial differential equation systems. Unlike the method of fundamental solutions, the use of non‐singular general solution in the BKM avoids the unnecessary requirement of constructing a controversial artificial boundary outside the physical domain. The purpose of this paper is to extend the BKM to solve 2D Helmholtz and convection–diffusion problems under rather complicated irregular geometry. The method is also first applied to 3D problems. Numerical experiments validate that the BKM can produce highly accurate solutions using a relatively small number of knots. For inhomogeneous cases, some inner knots are found necessary to guarantee accuracy and stability. The stability and convergence of the BKM are numerically illustrated and the completeness issue is also discussed. Copyright © 2003 John Wiley & Sons, Ltd.     

网络分解法的误差分析

网络分解法是求解电大尺寸复杂结构电磁问题的重要方法之一,关于网络分解法误差分析的研究有着重要的理论意义和实用价值.本文给出了网络分解法的误差估计,并对于脉冲基函数转换成三角基函数的情况给出了三角基函数个数的最优公式,数值结果表明了分析的正确性.     

关于Imamura猜想1的一个结果

本文证明了GF(q)的特征为2且n为奇数时GF(q~n)在GF(q)上有自对偶正规基。     

AN EXTENDED MODELING OF TIDE-WAVE MOTION

1 .　ＩＮＴＲＯＤＵＣＴＩＯＮＴｏｓｔｕｄｙｔｈｅｍｏｔｉｏｎｏｆｔｈｅｔｉｄｅ ｗａｖｅｓ,ｔｈｅｓｈａｌｌｏｗｗａｔｅｒｅｑｕａｔｉｏｎｓ ,ｉ.ｅ .ｔｈｅｖｅｒｔｉｃａｌｉｎｔｅｒｇｒａ ｔｉｏｎｏｆｔｈｅｃｏｎｔｉｎｕｉｔｙｅｑｕａｔｉｏｎａｎｄｍｏｍｅｎｔｕｍｅｑｕａ ｔｉｏｎ ,ｉｓｃｏｎｓｉｄｅｒｅｄａｓｔｈｅｇｏｖｅｒｎｉｎｇｅｑｕａｔｉｏｎｓ.Ｂｙａｂｏｖｅｅｑｕａｔｉｏｎｓｔｗｏｅｑｕａｔｉｏｎｓｒｅｌａｔｅｄｔｏｔｈｅｈｏｒｉｚｏｎ ｔａｌｆｌｕｘｏｆｔｈｅｔｉｄｅ ｃｕｒｒｅｎｔｓａ…     

An implementation for a fast public-key cryptosystem

In this paper we examine the development of a high-speed implementation of a system to perform exponentiation in fields of the form GF(2 ⁿ ). For sufficiently large n, this device has applications in public-key cryptography. The selection of representation and observations on the structure of multiplication have led to the development of an architecture which is of low complexity and high speed. A VLSI implementation has being fabricated with measured throughput for exponentiation for cryptographic purposes of approximately 300 kilobits per second.     

Anthony D. Wagner: Award for Distinguished Scientific Early Career Contributions to Psychology.

Presents the citation for Anthony D. Wagner, who received the Award for Distinguished Scientific Early Career Contributions to Psychology (cognition and human learning) "for outstanding and innovative research on the neural basis of memory and executive control." A brief profile and a selected bibliography accompany the citation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

一种新型桩基动测激振设备的研制

论述桩基承载力检测的新激振设备的设计，制作和安装，根据试验和对实际工程中桩基础的应用结果，表明该激振设备工作性能良好，使用方便，测试结果可靠。     

Arithmetic operations inGF(2 m )

This article is concerned with various arithmetic operations inGF(2 ^m ). In particular we discuss techniques for computing multiplicative inverses and doing exponentiation. The method used for exponentiation is highly suited to parallel computation. All methods achieve much of their efficiency from exploiting a normal basis representation in the field.