中国古代文学中“九尾狐”形象的嬗变

基于中国古代文学作品中经常出现的动物形象狐,探讨了九尾狐在中国文代文学作品中形象的嬗变。狐有九尾,生物发展史上并未出现过,乃是前人的想象。九尾狐由最初的臆想之物到瑞兽,再由天狐到狐妖,其文学形象的改变反映了人们观念的转换,文化的变迁。     

基于Chebyshev多项式的身份认证方案的研究

基于有限域的Chebyshev多项式由于其良好的单向性和半群特性,被广泛应用到公钥密码算法、密钥协商及身份认证方案中。在安全性方面对已有的基于Chebyshev多项式的身份认证方案进行了分析,并提出了一个新的身份认证方案。通过对其性能的研究,新的方案是安全有效的。     

基于信息论安全的防窃听网络编码方案

为提高组播通信网络中信息传输的安全性,提出一种基于信息论安全的网络编码方案。利用大素数及其本原根产生不同的噪声符号,并将噪声符号与原始信息进行混合,达到隐藏信息的目的。分析结果表明,该方案通过舍弃少量带宽,使网络编码以很高的概率达到信息论安全的要求,当信源与信宿之间有一条专用的安全信道时,可在不增加通信开销的前提下使网络的信息论安全概率为1。     

Object representation and recognition in shape spaces

In this paper, we describe a shape space based approach for invariant object representation and recognition. In this approach, an object and all its similarity transformed versions are identified with a single point in a high-dimensional manifold called the shape space. Object recognition is achieved by measuring the geodesic distance between an observed object and a model in the shape space. This approach produced promising results in 2D object recognition experiments: it is invariant to similarity transformations and is relatively insensitive to noise and occlusion. Potentially, it can also be used for 3D object recognition.     

Reusing Primitive and Acquired Motion Knowledge for Gait Generation of a Six-legged Robot Using Genetic Programming

There has been growing interest in motion planning problems for mobile robots. In this field, the main research is to generate a motion for a specific robot and task without previously acquired motions. However it is too wasteful not to use hard-earned acquired motions for other tasks. Here, we focus on a mechanism of reusing acquired motion knowledge and study a motion planning system able to generate and reuse motion knowledge. In this paper, we adopt a tree-based representation for expressing knowledge of motion, and propose a hierarchical knowledge for realizing a reuse mechanism. We construct a motion planning system using hierarchical knowledge as motion knowledge and using genetic programming as a learning method. We apply a proposed method for the gait generation task of a six-legged locomotion robot and show its availability with computer simulation.     

劳动者具有人身自由是劳动力成为商品的前提条件

本文在分析了马克思关于劳动力成为商品条件的基础上，论述了劳动者一无所有为劳动力成为商品的必要条件，仅与资本主义原始积累这一历史时期相适应，而在当今社会主义市场经济条件下．劳动者具有人身自由是劳动力成为商品的前提条件．     

论印欧语系原始词根的排列组合及语义特征

本文运用语言学理论对印欧语系的原始词根进行了全新的分析和综合，揭示了词根字母排列组合的内在规律、首位字母的宏观倾向性语义及词根语义的相互关系。这有助于加深对印欧语系原始母语的了解，促进对其所派生的现代相关语言的研究。     

Numerical inversion of multidimensional Laplace transforms by the Laguerre method

Numerical transform inversion can be useful to solve stochastic models arising in the performance evaluation of telecommunications and computer systems. We contribute to this technique in this paper by extending our recently developed variant of the Laguerre method for numerically inverting Laplace transforms to multidimensional Laplace transforms. An important application of multidimensional inversion is to calculate time-dependent performance measures of stochastic systems. Key features of our new algorithm are: (1) an efficient FFT-based extension of our previously developed variant of the Fourierseries method to calculate the coefficients of the multidimensional Laguerre generating function, and (2) systematic methods for scaling to accelerate convergence of infinite series, using Wynn's ε-algorithm and exploiting geometric decay rates of Laguerre coefficients. These features greatly speed up the algorithm while controlling errors. We illustrate the effectiveness of our algorithm through numerical examples. For many problems, hundreds of function evaluations can be computed in just a few seconds.     

Handwritten Chinese Character Recognition Based on Primitive and Fuzzy Features via the SEART Neural Net Model

A handwritten Chinese character recognition method based on primitive and compound fuzzy features using the SEART neural network model is proposed. The primitive features are extracted in local and global view. Since handwritten Chinese characters vary a great deal, the fuzzy concept is used to extract the compound features in structural view. We combine the two categories of features and use a fast classifier, called the Supervised Extended ART (SEART) neural network model, to recognize handwritten Chinese characters. The SEART classifier has excellent performance, is fast, and has good generalization and exception handling abilities in complex problems. Using the fuzzy set theory in feature extraction and the neural network model as a classifier is helpful for reducing distortions, noise and variations. In spite of the poor thinning, a 90.24% recognition rate on average for the 605 test character categories was obtained. The database used is CCL/HCCR3 (provided by CCL, ITRI, Taiwan). The experiment not only confirms the feasibility of the proposed system, but also suggests that applying the fuzzy set theory and neural networks to recognition of handwritten Chinese characters is an efficient and promising approach.     

On Pattern Frequency Occurrences in a Markovian Sequence

Consider a given pattern H and a random text T generated by a Markovian source. We study the frequency of pattern occurrences in a random text when overlapping copies of the pattern are counted separately. We present exact and asymptotic formulae for moments (including the variance), and probability of r pattern occurrences for three different regions of r , namely: (i) r=O(1) , (ii) central limit regime, and (iii) large deviations regime. In order to derive these results, we first construct certain language expressions that characterize pattern occurrences which are later translated into generating functions. We then use analytical methods to extract asymptotic behaviors of the pattern frequency from the generating functions. These findings are of particular interest to molecular biology problems (e.g., finding patterns with unexpectedly high or low frequencies, and gene recognition), information theory (e.g., second-order properties of the relative frequency), and pattern matching algorithms (e.g., q -gram algorithms).