p-型层状氧化锌的热电性质研究

采用第一性原理和玻尔兹曼输运理论,我们系统的研究了p-型二层氧化锌的热电性质.基于对单层氧化锌的晶格优化,计算得到其无虚频的声子谱,证明了它的热力学稳定性.由此构建了热力学性质稳定的二层氧化锌.采用实空间有限差分法生成了二层氧化锌的二阶和三阶力常数,然后得到了其声子散射和晶格热导率,使用两种计算方法得到了其晶格热导率在室温下分别为κ_ι~(BTE)=2.65 W/m·K和κ_ι~(RTA)=2.38 W/m·K.并且得到了p-型二层氧化锌在300 K至900 K等差温度下的热电优值为0.052～0.601,证明通过调节温度可以获得较高的热电优值.     

基于状态驻留时间下由转移弧产生输出的HMM模型中的参数估计

本讨论了用状态驻留时间来模型化传统的HMM模型。HMM的一个基本假设是它认为语音信号是准平稳的。然而由状态输出yt的HMM模型，并不能很好地表征语音信号中平稳段或平稳段之间的具体特征；由转移弧产生输出的自左向右HMM系统,则对语音特征作更为细致的描述。本主要讨论在[2]的基础上,对新建模型进行参数估计。     

Mixing between the 23S1 and 13D1Ds

Mixing between the 23S1 and 13D1Ds is studied within the 3P0 model. If mixing between these two 1 states exists, Ds1* （2700） ± and DsJ*（2860）± could be interpreted as the two orthogonal mixed states with mixing angle θ≈-80 °in the case of a special β for each meson. However, in the case of a universal β for all mesons, D_s1^*（2700） ± could be interpreted as the mixed state of 23S1 and 13D1 with mixing angle 12° < θ < 21° but D_sJ^*（2860）± seems difficult to interpret as the orthogonal partner of D_s1^*（2700）±.     

星对星激光雷达反射层析成像技术探讨

以星对星激光雷达成像为应用背景,提出了一种基于啁啾脉冲信号的反射层析成像处理方法,该方法通过激光雷达多角度回波非相干累积实现高分辨率的图像重构;分析了星对星反射层析成像的实现条件,包括成像分辨率、工作模式及成像时间.研究结果表明,采用本文所提出的成像方法,通过同轨道面的伴星探测方式可以满足激光雷达反射层析成像多角度探测的要求,在观测角度范围大于60°时能够得到0.1 m目标分辨率,角度范围越大,分辨率越高,且成像时间与卫星轨道半径和两星距离有关.实验验证了该方法的有效性和星对星反射层析成像的可行性.     

基于新型电荷生成层的P-i-N结构白色有机叠层电致发光器件

采用2,9-Dimethyl-4,7-diphenyl-1,10-phenanthroline(BCP): 5 wt.% cesium carbonate(Cs₂CO₃)和N, N'-Bis(naphthalen-1-yl)-N,N'-bis(phenyl)-benzidine(NPB): 20 wt.% molybdenum oxide(MoO₃)分别作为器件的电子注入层和空穴注入层,研究了N型和P-i-N结构有机电致发光器件的载流子传输特性.载流子传输层中BCP: Cs₂CO₃和NPB:MoO₃的引入有效增强了载流子注入能力,从而降低了器件的驱动电压.基于新型电荷生成层BCP: 5 wt.% Cs₂CO₃/ NPB: 20 wt.% MoO₃制备了色稳定、高效率P-i-N结构有机叠层器件.与单元器件相比,引入新电荷生成层有机叠层器件的最大电流效率增大了2.5倍,表明该电荷生成层可以有效地将电子和空穴分别注入到相邻发光单元中.采用该电荷生成层制备了P-i-N结构白色有机叠层器件,器件的上下发光单元分别为橙光和蓝光发射.当发光亮度从500增加到5 000 cd/m²时,器件的色坐标稳定在(0.33, 0.29)附近,接近白光等能点.利用单色发光单元堆叠制备白色有机叠层器件的方法为实现色稳定、高效率的白色有机电致发光器件提供了一种有效的途径.     

紫色土土壤全氮和全磷含量的高光谱遥感预测

高光谱遥感技术是土壤养分预测的有效手段之一。以三峡库区王家沟小流域为研究区,在对土壤样本的理化性质和实验室反射光谱数据分析和测量的基础上,用偏最小二乘回归方法建立了紫色土土壤全氮和全磷含量的预测模型,并用33个水稻土土壤样本对紫色土土壤养分预测模型进行了验证。结果显示,紫色土土壤全氮预测模型得到的土壤样本预测值和实测值之间的总相关系数达到了0.672,而紫色土土壤全磷预测模型得到的相关系数只有0.498; 用紫色土土壤养分预测模型对水稻土土壤养分进行预测得到的相关系数分别为0.550和0.124。因此,用高光谱来预测紫色土土壤全氮含量具有一定的可行性,但高光谱对于紫色土全磷含量的预测效果相对较差;土壤养分预测模型在不同类型土壤之间并不具有很好的通用性。     

Dynamical fluctuations in fragmentation reactions in a Boltzmann–Langevin approach

Based on the isospin-dependent Boltzmann–Langevin model, the dynamical fluctuations in the fragmentation reaction of ¹¹²Sn+¹¹²Sn are investigated. The quadrupole moment and octupole moment with zero magnetic quantum number have large fluctuations in the early time of the collisions. The dynamical fluctuations in momentum space show a strong dependence on the incident energy. The effects of using different fluctuations on the fragment cross sections are also studied in the fragmentation reactions. The results by using Q₂₀ + Q₃₀ fluctuation have a better agreement with the experimental data. Calculations using Q₂₀ + Q₃₀ fluctuation produce more proton-rich and neutron-rich nuclei than those using Q₂₀ fluctuation only. Besides, the difference between the production cross sections of fragments calculated by using Q₂₀ and Q₂₀ + Q₃₀ fluctuations is larger in the vicinity of the projectile. These results present that the dynamical fluctuations may affect the whole dynamical process of fragmentation reactions including the production of fragments, due to the nonlinear nature of the Boltzmann–Langevin equation.     

Image Encryption Scheme with Compressed Sensing Based on a New Six-Dimensional Non-Degenerate Discrete Hyperchaotic System and Plaintext-Related Scrambling

Digital images can be large in size and contain sensitive information that needs protection. Compression using compressed sensing performs well, but the measurement matrix directly affects the signal compression and reconstruction performance. The good cryptographic characteristics of chaotic systems mean that using one to construct the measurement matrix has obvious advantages. However, existing low-dimensional chaotic systems have low complexity and generate sequences with poor randomness. Hence, a new six-dimensional non-degenerate discrete hyperchaotic system with six positive Lyapunov exponents is proposed in this paper. Using this chaotic system to design the measurement matrix can improve the performance of image compression and reconstruction. Because image encryption using compressed sensing cannot resist known- and chosen-plaintext attacks, the chaotic system proposed in this paper is introduced into the compressed sensing encryption framework. A scrambling algorithm and two-way diffusion algorithm for the plaintext are used to encrypt the measured value matrix. The security of the encryption system is further improved by generating the SHA-256 value of the original image to calculate the initial conditions of the chaotic map. A simulation and performance analysis shows that the proposed image compression-encryption scheme has high compression and reconstruction performance and the ability to resist known- and chosen-plaintext attacks.     

Significance Support Vector Regression for Image Denoising

As an extension of the support vector machine, support vector regression (SVR) plays a significant role in image denoising. However, due to ignoring the spatial distribution information of noisy pixels, the conventional SVR denoising model faces the bottleneck of overfitting in the case of serious noise interference, which leads to a degradation of the denoising effect. For this problem, this paper proposes a significance measurement framework for evaluating the sample significance with sample spatial density information. Based on the analysis of the penalty factor in SVR, significance SVR (SSVR) is presented by assigning the sample significance factor to each sample. The refined penalty factor enables SSVR to be less susceptible to outliers in the solution process. This overcomes the drawback that the SVR imposes the same penalty factor for all samples, which leads to the objective function paying too much attention to outliers, resulting in poorer regression results. As an example of the proposed framework applied in image denoising, a cutoff distance-based significance factor is instantiated to estimate the samples’ importance in SSVR. Experiments conducted on three image datasets showed that SSVR demonstrates excellent performance compared to the best-in-class image denoising techniques in terms of a commonly used denoising evaluation index and observed visual.     

水中目标回波亮点统计特征研究

礁石和海洋动物引起的混响是主动声纳最严重的干扰, 如何区分礁石、鱼群和水中目标一直是制约主动声纳识别技术的难点问题. 针对礁石与目标回波难以区分的问题, 从特征识别的应用角度, 研究水中复杂目标全方位回波亮点特征的有效表征和应用方式, 基于目标回波亮点模型, 提出拷贝相关器输出的目标散射函数估计方法, 给出对目标回波亮点相对关系进行定量分析的目标回波特征统计表征方式, 并基于湖上实验提取了物理机理明确的目标回波亮点统计特征, 使得目标时间-角度谱中所蕴含的目标特征信息能够很直接地转化为主动声纳易于应用的目标特征. 关键词： 水中目标 回波亮点 统计特征