强磁场对硅锰铸钢于A_1点附近等温珠光体相变的影响

通过开展12 T强磁下硅锰铸钢(50Si_2Mn_3)于A_1点温度附近不同等温时间的热处理试验,并对比强磁场与无磁场条件下等温珠光体相变试验结果,研究了磁场对珠光体转变量及组织形貌的影响。研究表明,对于50Si_2Mn_3在A1点以下较高温度范围内,强磁场可缩短珠光体相变的孕育期,促进硅锰铸钢珠光体转变,使其转变量明显增加;强磁场能够提高珠光体转变临界点,使50Si_2Mn_3在A1点以上等温过程中能够发生珠光体相变。     

Action categorization with modified hidden conditional random field

In this paper, we present a method for action categorization with a modified hidden conditional random field (HCRF). Specifically, effective silhouette-based action features are extracted using motion moments and spectrum of chain code. We formulate a modified HCRF (mHCRF) to have a guaranteed global optimum in the modelling of the temporal action dependencies after the HMM pathing stage. Experimental results on action categorization using this model are compared favorably against several existing model-based methods including GMM, SVM, Logistic Regression, HMM, CRF and HCRF.     

Gröbner basis of the alternating galoisian ideal

This article proposes an efficient and simple algebraic method of computation of a Gröbner basis generating the alternating galoisian ideal of a univariate separable polynomial. We named this method “the descent of the Vandermonde determinants”.     

Identification and quantification of different vapours using a single polymer chemoresistor and the novel dual transient temperature modulation technique

This paper presents a novel signal processing technique for a square wave temperature modulated carbon black/polymer composite sensor. The technique consists of only two mathematical operations: summing the off- and on-transients of the conductance signals, and subtracting the steady-state conductance signal. The technique has been verified through its application to a carbon black/polyvinylpyrrolidone composite chemoresistor. Identification of water, methanol and ethanol vapours was successfully demonstrated using the peak time of the resultant curves. Furthermore, quantification of those vapours was found to be possible using the height of the peak heights, which was linearly proportional to concentration. The technique does not require zero-gas calibration and thus is superior to previously reported techniques.     

Frequency domain regularization of d-dimensional structure tensor-based directional fields

The present work is intended to address two of the major difficulties that can be found when tackling the estimation of the local orientation of the data in a scene, a task which is usually accomplished by means of the computation of the structure tensor-based directional field. On one hand, the orientation information only exists in the non-homogeneous regions of the dataset, while it is zero in the areas where the gradient (i.e. the first-order intensity variation) remains constant. Due to this lack of information, there are many cases in which the overall shape of the represented objects cannot be precisely inferred from the directional field. On the other hand, the orientation estimation is highly dependent on the particular choice of the averaging window used for its computation (since a collection of neighboring gradient vectors is needed to obtain a dominant orientation), typically resulting in vector fields which vary from very irregular (thus yielding a noisy estimation) to very uniform (but at the expense of a loss of angular resolution). The proposed solution to both drawbacks is the regularization of the directional field; this process extends smoothly the previously computed vectors to the whole dataset while preserving the angular information of relevant structures. With this purpose, the paper introduces a suitable mathematical framework and deals with the d-dimensional variational formulation which is derived from it. The proposed formulation is finally translated into the frequency domain in order to obtain an increase of insight on the regularization problem, which can be understood as a low-pass filtering of the directional field. The frequency domain point of view also allows for an efficient implementation of the resulting iterative algorithm. Simulation experiments involving datasets of different dimensionality prove the validity of the theoretical approach.     

The use of genetic algorithms for assessment of high voltage fields

There are several numerical methods for calculation of electric fields but they need some sort of experience and trial and error to get the correct solution. A genetic algorithm (GA) based approach is used to eliminate the need for the experience and to save time and effort spent in the trial and error. Two enhancement techniques, namely, Refreshment Method and No-Twins Method, are used with the GA operators to improve the performance of the GA in assessment of high voltage fields. The performance of these two enhancement techniques has been studied for computing the electrostatic field in high voltage applications.     

Comparison of image reconstruction by using near‐field and far‐field data for an imperfect conductor

Image reconstruction by using near‐field and far‐field data for an imperfectly conducting cylinder is investigated. A conducting cylinder of unknown shape and conductivity scatters the incident wave in free space and the scattered near and far fields are measured. By using measured fields, the imaging problem is reformulated into an optimization problem and solved by the genetic algorithm. Numerical results show that the convergence speed and final reconstructed results by using near‐field data are better than those obtained by using far‐field data. This work provides both comparative and quantitative information. © 2001 John Wiley & Sons, Inc. Int J RF and Microwave CAE 11: 69–73, 2001.     

基于F2上遍历矩阵的Shamir三次传递协议的实现

给出了Shamir三次传递协议的一种新的实现方案.与已有的基于离散对数问题的实现方案不同,它是基于在特定的非交换壹半群(m,·)中,由A和B＝x·A·y求解x和y的难度;为此我们选取有限域F2上的n×n矩阵在F2矩阵乘法下所构成的非交换壹半群作为研究的对象,利用F2上"遍历矩阵"的密码学特性,提出了一个基于F2上遍历矩阵的Shamir三次传递协议的实现方案,并对可能的攻击手段进行了分析.为了增加通讯的安全性,提出了"强壮矩阵"的概念,并对于给定的两个遍历矩阵Q1和Q2,给出了关于Q1,Q2的强壮矩阵的判别标准和寻找算法;利用<Q1>,<Q2>以及关于Q1,Q2的强壮矩阵m,可以构造一个单向(陷门)函数,基于该单向函数,可具体实现Shamir三次传递协议、Diffie-Hellman密钥交换协议以及常规的公钥密码.