Deformation transition of intact coal induced by gas injection

Gas migration in coal bed is a multiple-physical process, of which not only includes gas desorption/diffusion through coal matrix and gas Darcy flow through the cleat system, but also results in deform...     

对Al-Cu合金中α-Al及Al2Cu生长行为的探讨

研究了Al-Cu合金中α-Al和Al2Cu的生长行为,分析了初生α-Al及初生Al2Cu作为共晶核心形核的能力.结果发现,在过共晶组织中,初生相Al2Cu形貌大部分有明显的拐角,观察其平面有的呈矩形,呈现小面生长特性.而α-Al与Al2Cu共晶生长时,Al2Cu择优生长特征削弱,与α-Al耦合生长呈现非小面-非小面生长,表明Al2Cu在不同的生长阶段表现出的生长行为不同.在亚共晶组织中,初生相α-Al周围形成离异共晶的Al2Cu,而过共晶组织中初生相Al2Cu周围没有离异共晶的α-Al,表明初生相Al2Cu作为共晶层片核心的能力比初生相α-Al作为共晶层片核心的能力强.     

用计算机图形处理软件定量分析SEM图像

用图形处理软件PHOTOSHOP对SEM图像进行图像定量分析，对高温合金K23σ析出相的体积分数和M8钢样的夹杂物颗粒尺寸进行了定量测定。结果表明，该方法操作方便，有一定的可行性。     

椭圆弧数控代码的自动生成方法

提出了一种基于计算机辅助制造的数控加工代码自动生成的方法，着重阐述了该方法针对椭圆弧的数控代码自动生成过程。该方法通过分析加工图形的dxf文件，提取图形的坐标信息，再经过数据拟和，自动生成该图形的数控代码。该方法由VC＋＋6．0实现相应的功能，经实际运行表明，能满足加工精度要求。该方法摆脱了传统数控机床从加工图形到形成数控加工代码时间长且精度不高的缺点，极大她提高了工作效率。     

基于云存储的离线下载系统

数据获取是现代网络应用中的重要组成部分,是几乎所有网络操作的前提。下载工具能够帮助用户更加便捷地获取网络资源。该文提出一个基于云存储的离线下载系统,系统保持离线下载原有特色与优点,并引入云存储解决系统存储空间不足和"秒杀"下载率不高的的问题,利用基于文件存储价值的存储更新策略提高云存储系统的存储效率。双机热备技术的引入,有效提高系统整体可靠性。     

Speech authentication by semi-fragile speech watermarking utilizing analysis by synthesis and spectral distortion optimization

This paper proposes an improved semi-fragile speech watermarking scheme by quantization of linear prediction (LP) parameters, i.e., the inverse sine (IS) parameters. The spectral distortion due to watermark embedding is controlled to meet the ‘transparency’ criterion in speech coding. A modified bit allocation algorithm combined with watermarking is developed to determine the quantization step so that the ‘transparency’ requirement is satisfied. Due to the statistical nature, the LP coefficients estimated from the watermarked speech signal are different from the watermarked LP coefficients even in the absence of attacks. This effect is the cause of increase in decoding error and minimum authentication length. To tackle this problem, an Analysis by Synthesis (AbS) scheme is developed to reduce the difference between the estimated LP coefficients and the watermarked ones. The watermark detection threshold and minimum authentication length are then derived according to the probability of error and the signal to noise ratio (SNR) requirements. Experimental results show that the proposed AbS based method can effectively reduce the difference between the watermarked IS parameter and the extracted IS parameter when there is no attacks. In addition, the modified bit allocation algorithm can automatically find the appropriate quantization step used in the odd-even modulation so that the transparency requirement is satisfied.     

任务多变情况下技术团队隐性知识管理策略

很多以技术性活动为主的团队所执行的任务环境多变,无论是地形、气候或者是人员、设备的变化非常规问题地多发,会对其知识管理尤其是隐性知识管理带来一定影响。本文提出将承载着隐性知识的非结构化文档以数列集合的方式表达,能够便于管理和决策。     

Locally linear discriminant embedding: An efficient method for face recognition

In this paper an efficient feature extraction method named as locally linear discriminant embedding (LLDE) is proposed for face recognition. It is well known that a point can be linearly reconstructed by its neighbors and the reconstruction weights are under the sum-to-one constraint in the classical locally linear embedding (LLE). So the constrained weights obey an important symmetry: for any particular data point, they are invariant to rotations, rescalings and translations. The latter two are introduced to the proposed method to strengthen the classification ability of the original LLE. The data with different class labels are translated by the corresponding vectors and those belonging to the same class are translated by the same vector. In order to cluster the data with the same label closer, they are also rescaled to some extent. So after translation and rescaling, the discriminability of the data will be improved significantly. The proposed method is compared with some related feature extraction methods such as maximum margin criterion (MMC), as well as other supervised manifold learning-based approaches, for example ensemble unified LLE and linear discriminant analysis (En-ULLELDA), locally linear discriminant analysis (LLDA). Experimental results on Yale and CMU PIE face databases convince us that the proposed method provides a better representation of the class information and obtains much higher recognition accuracies.