Microstructure,mechanical, tribological,and oxidizing properties of AlCrSiN/AlCrVN/AlCrNbN multilayer coatings with different modulated thicknesses

Multilayer structure design is one of the most promising methods for improving the comprehensive performance of AlCrN-based hard coatings applied to cutting tools. In this study, four types of AlCrSiN/AlCrVN/AlCrNbN multilayer coatings, with different modulated thicknesses, were deposited to investigate their microstructure, mechanical, tribological, and oxidizing properties. All multilayer coatings exhibited grain growth along the crystallographic plane of (200) with a NaCl-type face-centered cubic (FCC) structure. The results show that, as the modulation thickness decreases from ～35 nm to ～10 nm, (1) the grain refinement effect is increasingly evident; (2) all multilayer coatings show a hardness of >30 GPa and an elastic modulus of >300 GPa. Both the ability to resist elastic strain to failure and the plastic deformation of multilayer coatings increase. In addition, their resistance to cracking reduces; (3) the wear rates of these multilayer coatings reduce successively from 1.78 × 10^?16 m³ N^?1 m^?1 to 7.7 × 10^?17 m³ N^?1 m^?1. This is attributed to an increase in self-lubricating VO_x and a decrease in adhesives from the counterparts; (4) the best high-temperature oxidation resistance was obtained for the multilayer coating with a modulated thickness of ～15 nm.     

Negative effects of sufficiently small initial weights on back-propagation neural networks

In the training of feedforward neural networks,it is usually suggested that the initial weights should be small in magnitude in order to prevent premature saturation.The aim of this paper is to point out the other side of the story:In some cases,the gradient of the error functions is zero not only for infinitely large weights but also for zero weights.Slow convergence in the beginning of the training procedure is often the result of sufficiently small initial weights.Therefore,we suggest that,in these cases,the initial values of the weights should be neither too large,nor too small.For instance,a typical range of choices of the initial weights might be something like(0.4,0.1) ∪(0.1,0.4),rather than(0.1,0.1) as suggested by the usual strategy.Our theory that medium size weights should be used has also been extended to a few commonly used transfer functions and error functions.Numerical experiments are carried out to support our theoretical findings.     

橡胶硫化促进剂NS的合成研究

本研究采用促进剂M、叔丁胺为原料,以过氧化氢为氧化剂,用水做溶剂在酸性条件下合成橡胶硫化促进剂NS。并通过实验得到优化工艺条件:n(叔丁胺)/n(促进剂M)为2.0、n(过氧化氢)/n(促进剂M)为1.5、反应温度为60℃和反应时间为90min,在此工艺条件下合成橡胶硫化促进剂NS的收率可达90.0%。     

轻量级PRESENT加密算法功耗攻击研究

PRESENT密码算法是2007年提出来的一种轻量级分组密码算法, 适合于物联网环境下的安全加密。对PRESENT加密算法结构进行了深入研究, 提出了其适合功耗攻击的两个最佳攻击点, 详细介绍了针对PRESENT加密系统进行功耗分析攻击的设计与实现过程, 实验结果表明未加防护措施的PRESENT加密系统不能抵御一阶差分功耗分析攻击, 从而给PRESENT加密算法的安全改进提供一定的设计参考。     

叙事教学法视域下大学生叙事能力的培养

叙事能力即话语能力,培养学生的叙事能力是大学英语教学重要目标之一。叙事教学法以叙事为中心,强调学生叙事能力发展,注重叙事对学生的认知作用及其个性化学习。针对叙事教学法的特点和大学英语教学的要求,探寻大学生叙事能力的培养的途径,以期提高教学实际质量。     

一种轻量级TWINE密码硬件优化实现研究

随着物联网的广泛应用,如何有效实现轻量级密码算法成为近年的研究热点。对2011年提出的TWINE加密算法进行了硬件优化实现,相同的轮运算只实现一次,采用重复调用方式完成。TWINE算法总共有36轮运算,其中前35轮运算结构相同,可以重复调用实现,而第36轮相比前35轮在结构上少了块混淆,因此原始算法最多只能进行35轮重复调用。直接进行36轮循环调用运算,同时在36轮循环运算完成后构造一个块混淆逆运算,运算一次块混淆逆运算即可使输出密文正确。这样使TWINE最后的第36轮不必重新实现,而是直接复用前面可重复轮函数模块,只需增加一个比原始算法最后一轮运算相对简单的块混淆逆运算。下载到FPGA上的实验结果表明,优化后的TWINE密码算法在面积上减少了2204个Slices,系统速率提高了5倍。     

Adaptive mode decision for multiview video coding based on macroblock position constraint model

Multiview video coding (MVC) exploits mode decision, motion estimation and disparity estimation to achieve high compression ratio, which results in an extensive computational complexity. This paper presents an efficient mode decision approach for MVC using a macroblock (MB) position constraint model (MPCM). The proposed approach reduces the number of candidate modes by utilizing the mode correlation and rate distortion cost (RD cost) in the previously encoded frames/views. Specifically, the mode correlations both in the temporal-spatial domain and the inter-view are modeled with MPCM. Then, MPCM is exploited to select the optimal prediction direction for the current encoding MB. Finally, the inter mode is early determined in the optimal prediction direction. Experimental results show that the proposed method can save 86.03 % of encoding time compared with the exhaustive mode decision used in the reference software of joint multiview video coding, with only 0.077 dB loss in Bjontegaard delta peak signal-to-noise ratio (BDPSNR) and 2.29 % increment of the total Bjontegaard delta bit rate (BDBR), which is superior to the performances of state-of-the-art approaches.     

谈如何用Java语言实现Huffman编码

Huffman编码作为一种高效的不等长编码技术正日益广泛地在文本、图像、视频压缩及通信、密码等领域得到应用。Java语言是一种目前比较流行的、面向对象的程序设计语言,文章就如何利用Java的优先队列结构建立Huffman编码树进行了探讨,并给出了编码与反编码程序。