量子卡诺制冷机制冷率与熵产率的协调优化性能

研究了内可逆谐振子量子卡诺制冷机的整体最优性能。得到了协调优化目标函数Ｅ最大时量子制冷机的制冷系数以及最佳制冷率和熵产率。     

Packaging production and consumption in the world and in some industrialized countries

This paper reports on statistics concerning production and consumption of packaging (as a whole or per capita) in Europe, in the USA, in Japan and in the world. Data have been provided by National Trade Associations and by consultants specialized in packaging and in economics. It is estimated that in 1986 the global consumption of packaging reached 150 millions of tonnes valued at 1200 billions of French francs. Consumption could reach 247 million tonnes by the year 2000. Paper and board have the highest consumption rate, but plastics have the highest rate of growth. Nevertheless, consumption per capita in the industrialized countries will be more than 10 times the consumption in underdeveloped countries. The packaging industries take fourth place in the USA, sixth in Western Germany and twelfth in France. In Europe, as in the world, paper and board is the material most used (40%), with glass (a high density material) taking second place and plastics third, i.e. if we consider the quantity of materials and not their value. Some differences appear between the various countries, but the figures for USA and Japan lead to similar conclusions. The survey shows clearly that the USA as compared with Europe has twice the consumption of packaging materials per capita and this difference is even greater compared with the rest of the world.     

双光子Jaynes－Cummings模型的亚泊松光子统计特性研究

本文利用量子电动力学理论和缀饰原于方法，对双光子Ｊａｍｅｓ－Ｃｕｍｍｉｎｇｓ模型中单模激光场的稳态亚泊松光子统计性质进行了系统研究。结果表明：激光上能级相对泵浦参量Ｘａ具有一个确定的阈值Ｘａｔ；当Ｘａ＞Ｘａｔ时，光场呈现亚泊松光子统计；而当Ｘａ＞＞Ｘａｔ时，光场将呈现出深度且完全恒定的亚泊松光子统计。     

一种基于高阶统计信息的信噪比估计改进算法

针对多进制正交幅度调制(Multiple quadrature amplitude modulation,MQAM)信号在低信噪比条件下估计精度不高的问题,提出了一种基于综合利用高阶统计信息的信噪比估计改进算法。根据所选高阶统计量最高阶数的不同,建立了3种信噪比与多种高阶统计量运算式之间的线性关系,利用全回归线性分析方法将3种线性关系转化为3种全回归模型,并求解模型系数。该算法充分利用了多种高阶统计量的有用信息,提高了信噪比估计精度。MQAM的仿真结果表明:在低信噪比条件下,该算法减小了信噪比估计误差,其估计性能明显优于传统的其他算法,且3种模型估计性能依次增加,可依据不同的信噪比要求对3种模型进行选取。     

针对语音变换的语音篡改检测

针对使用语音变换技术的语音篡改,提出一种自动检测方法。在分析语音变换基本模型和变换语音失真的基础上,提取语音信号的声道参数以及相关的信号统计量,并通过支持向量机递归特征消除法,选择出对语音变换比较敏感的特征作为分类特征,使用支持向量机进行语音变换检测和变换语音的说话人性别判别。对于一种语音变换软件的实验结果表明,该方法具有较高的检测准确率,其中语音变换检测的平均准确率为94.90%,变换语音的说话人性别判别平均准确率为92.09%。     

统计中的查找计数方法

本文以选票统计问题为例,讨论了3种查找计数方法(顺序法、二分法、插值法)在统计中的应用,提出了一种新颖的查找计数方法——一次到位法,给出了用FOXPLUS数据库语言编写的算法子程序,并比较了它们各自的特点和适用范围。     

基于模糊数学的高维稀疏数据聚类统计方法设计

传统的数据聚类统计方法仅适用于低维数据聚类问题,为此,本研究设计了基于模糊数据的高维稀疏数据聚类统计方法,以期提升高维稀疏数据的聚类统计效果。以模糊C均值聚类算法为基础,通过优化初始聚类中心解决局部最优问题,缩短聚类统计时间;然后引入权重机制,令该方法适用于高维稀疏数据聚类统计。基于此,以余弦距离替换原有的欧几里德距离,提高高维稀疏数据聚类统计效果。实验证明：在数据维度不同时,该方法均有较优的聚类统计效果。当数据维度较低时,分块比例为10%时聚类统计效果最优;当数据维度较高时,分块比例为40%时聚类统计效果最优。在不同稀疏度等级时,该方法的命中率和聚类统计效率均较高。     

Influences of mullite fibers on mechanical and thermal properties of silica-based ceramic cores

Mullite fibers composite silica-based ceramic cores were successfully prepared by injection molding. The effects of mullite fibers on the mechanical and thermal properties of ceramic cores were investigated. The results indicated that the linear shrinkage was significantly decreased and the porosity was gradually increased with the increase of mullite fibers. In addition, the flexural strength for the room temperature and the simulated casting temperature of 1500°C was increased to a maximum value when the content of mullite fibers was about 1 wt.%, and then decreased with the increase of mullite fibers. The mullite fibers of 1 wt.% presented excellent mechanical properties with a linear shrinkage of .65%, a porosity of 6.96%, and a flexural strength of 17 MPa at room temperature and 34.83 MPa at the simulated casting temperature of 1500°C. Besides, the change in microstructure and properties in various contents of mullite fibers were analyzed.     

Varnish layer hardness of oriental beech (fagus orientalist L.) wood as affected by impregnation and bleaching

The impacts of impregnation and bleaching on the varnish layer hardness of Oriental beech (Fagus orientalist L.) wood were investigated. A number of bleaching combinations {[NaOH−H₂O₂], [NaOH−Ca(OH)₂−H₂O₂], [NaOH−MgSO₄−H₂O₂] [NaHSO₃−H₂C₂O₄], [NaSiO₃−H₂O₂], [KMnO₄+NaHSO₃+H₂O₃]} were applied at 18% concentration for bleaching to both impregnated and unimpregnated specimens of Oriental beech wood. Subsequently, water-based (WB) varnish was coated over the samples and the varnish layer hardness values were determined in accordance with ASTM D 4366-95. All of the chemicals used for bleaching reduced the surface hardness. However, after varnish coating, the hardness of most samples was similar to that of the varnish-coated natural (control) samples.     

Autonomous tactile perception: A combined improved sensing and Bayesian nonparametric approach

In recent years, autonomous robots have increasingly been deployed in unknown environments and required to manipulate or categorize unknown objects. In order to cope with these unfamiliar situations, improvements must be made both in sensing technologies and in the capability to autonomously train perception models. In this paper, we explore this problem in the context of tactile surface identification and categorization. Using a highly-discriminant tactile probe based upon large bandwidth, triple axis accelerometer that is sensitive to surface texture and material properties, we demonstrate that unsupervised learning for surface identification with this tactile probe is feasible. To this end, we derived a Bayesian nonparametric approach based on Pitman–Yor processes to model power-law distributions, an extension of our previous work using Dirichlet processes Dallaire et al. (2011). When tested against a large collection of surfaces and without providing the actual number of surfaces, the tactile probe combined with our proposed approach demonstrated near-perfect recognition in many cases and achieved perfect recognition given the right conditions. We consider that our combined improvements demonstrate the feasibility of effective autonomous tactile perception systems.