SCLC法测量非晶硅有效隙态密度

提出了用空间电荷限制电流（SCLC）法测量非晶硅材料的有效隙态密度的新方法，并且报告了用4061A型半导体综合测试仪测量有效隙态密度的结果。测量结果发现与用低频电容法所得结果相符。     

Estimation of elastic constant of rocks using an ANFIS approach

The engineering properties of the rocks have the most vital role in planning of rock excavation and construction for optimum utilization of earth resources with greater safety and least damage to surroundings. The design and construction of structure is influenced by physico-mechanical properties of rock mass. Young's modulus provides insight about the magnitude and characteristic of the rock mass deformation due to change in stress field. The determination of the Young's modulus in laboratory is very time consuming and costly. Therefore, basic rock properties like point load, density and water absorption have been used to predict the Young's modulus. Point load, density and water absorption can be easily determined in field as well as laboratory and are pertinent properties to characterize a rock mass. The artificial neural network (ANN), fuzzy inference system (FIS) and neuro fuzzy are promising techniques which have proven to be very reliable in recent years. In, present study, neuro fuzzy system is applied to predict the rock Young's modulus to overcome the limitation of ANN and fuzzy logic. Total 85 dataset were used for training the network and 10 dataset for testing and validation of network rules. The network performance indices correlation coefficient, mean absolute percentage error (MAPE), root mean square error (RMSE), and variance account for (VAF) are found to be 0.6643, 7.583, 6.799, and 91.95 respectively, which endow with high performance of predictive neuro-fuzzy system to make use for prediction of complex rock parameter.     

THE ISOTHERMAL COMPRESSIBILITY OF GAS-SATURATED HYDROCARBON LIQUIDS

Volumetric measurements were made on compressed solutions of carbon dioxide in n-decane and trans-decalin at 37.78°C at pressures up to 60 bar. The data were numerically analyzed to yield the isothermal compressibility function of the solutions at their saturation pressures.     

Studies on fluorinated polyurethanes by X-ray diffraction and density functional theory calculations with periodic boundary conditions

Thin-film wide-angle X-ray diffraction, small-angle X-ray scattering, and density functional theory calculations using B3LYP hybrid functional with the two-dimensional periodic boundary conditions (2D-PBC) have been applied to study the crystal structures of parent and fluorinated polyurethanes. The crystal structures from 2D-PBC-B3LYP calculation and experiments showed the hard-segment chains within crystallites adopted an extended-chain conformation for polyurethanes. Energetically, the parent polyurethane preferred an alternating hydrogen-bonded sheet structure while the fluorinated one adopted a progressive hydrogen-bonded sheet structure.     

基于自然最近邻的密度峰值聚类算法

针对密度峰值聚类算法(Density Peaks Clustering,DPC)需要人为指定截断距离d c,以及局部密度定义简单和一步分配策略导致算法在复杂数据集上表现不佳的问题,提出了一种基于自然最近邻的密度峰值聚类算法(Density Peaks Clustering based on Natural Nearest Neighbor,NNN-DPC)。该算法无需指定任何参数,是一种非参数的聚类方法。该算法首先根据自然最近邻的定义,给出新的局部密度计算方法来描述数据的分布,揭示内在的联系;然后设计了两步分配策略来进行样本点的划分。最后定义了簇间相似度并提出了新的簇合并规则进行簇的合并,从而得到最终聚类结果。实验结果表明,在无需参数的情况下,NNN-DPC算法在各类数据集上都有优秀的泛化能力,对于流形数据或簇间密度差异大的数据能更加准确地识别聚类数目和分配样本点。与DPC、FKNN-DPC(Fuzzy Weighted K-nearest Density Peak Clustering)以及其他3种经典聚类算法的性能指标相比,NNN-DPC算法更具优势。     

Information-theoretic Approaches Based on Sequential Monte Carlo to Collaborative Distributed Sensors for Mobile Robot Localization

We consider the Sequential Monte Carlo (SMC) method for Bayesian inference applied to the problem of information-theoretic distributed sensor collaboration in complex environments. The robot kinematics and sensor observation under consideration are described by nonlinear models. The exact solution to this problem is prohibitively complex due to the nonlinear nature of the system. The SMC method is, therefore, employed to track the probabilistic kinematics of the robot and to make the corresponding Bayesian estimates and predictions. To meet the specific requirements inherent in distributed sensors, such as low-communication consumption and collaborative information processing, we propose a novel SMC solution that makes use of the particle filter technique for data fusion, and the density tree representation of the a posterior distribution for information exchange between sensor nodes. Meanwhile, an efficient numerical method is proposed for approximating the information utility in sensor selection. A further experiment, obtained with a real robot in an indoor environment, illustrates that under the SMC framework, the optimal sensor selection and collaboration can be implemented naturally, and significant improvement in localization accuracy is achieved when compared to conventional methods using all sensors.     

Hole pockets in the doped 2D Hubbard model

The electronic momentum distribution n(k) of the two dimensional Hubbard model is studied for different values of the coupling U/t, electronic density n , and temperature, using quantum Monte Carlo techniques. A detailed analysis of the data on 8 × 8 clusters shows that features consistent with hole pockets at momenta k=(±/2,±/2,) appear as the system is doped away from half-filling. Our results are consistent with recent experimental data for the cuprates discussed by Aebi et al. (Phys. Rev. Lett.72, 2757 (1994)). In the range of couplings studied, the depth of the pockets is maximum at n approximately 0.9, and it increases with decreasing temperature. The apparent absence of hole pockets in previous numerical studies of this model is explained.     

基于核密度估计的活动轮廓模型

基于核密度估计的活动轮廓模型如果没有适当的扰动机制,往往不能在弧度突变的边缘上获得较好的收敛结果,且在大噪声环境下鲁棒性较差。针对该问题,提出一个新的代价函数。该函数通过融合边缘映射的曲率信息,改善原算法在突变边缘的收敛效果,降低算法对初始轮廓的依赖。     

A resonating rheometer using two polymer membranes for measuring liquid viscosity and mass density

A resonating sensor for mechanical liquid properties facilitating measurements at two different modes of operation is presented. One mode is more sensitive to liquid viscosity the other to mass density. A sample liquid is subjected to time-harmonic shear stress induced by two opposed vibrating polymer membranes. These membranes, placed in an external static magnetic field, carry two conductive paths each. The first path is used to actuate the membranes by means of Lorentz forces while the second acts as a pick-up coil providing an induced voltage representing the movement of the membrane. From the resulting frequency response the liquid's viscosity and mass density can be deduced. This double membrane based setup allows examining the test liquid at adjustable frequencies in the low kilohertz range from 500 Hz to 20 kHz by varying the gap between both membranes. The sensor is suitable, e.g., for low cost handheld devices with inline capabilities and disposable sensor elements for measuring Newtonian liquids such as, e.g., oils and aqueous solutions.