金刚石与石墨局域态密度和能带结构的第一原理分析

计算与分析电子结构对类金刚石薄膜材料的研究尤为重要.本文用第一原理分子动力学模拟,以研究金刚石和石墨的局域态密度和能带结构.第一原理计算赝势平面波法和密度泛函理论(DFT)去计算,电子交换相关能采用广义梯度近似(GGA)去描述,这种方法可以正确无误的预测半导体带隙与尺寸的关系.金刚石的禁带很宽,为绝缘体,Sp3杂化轨道在费米能级附近提供部分能态密度.石墨是零带隙半金属的内部结构根源就在于离域π键,费米能级处的能态密度几乎全部来自p能级的贡献.研究结果预测,结构变化和Sp杂化轨道产生的函数关系,是很多物理性质不同的最根本原因,而物理性质的研究则可以最直观的体现这种函数关系,可以更深入地研究金刚石和石墨这两种物质.     

论吡咯与双卤分子间的卤键

运用量子化学微扰理论MP2方法,采用6-311++G(d,p)基组,对吡咯与双卤分子XY(XY=ClF,BrF,BrCl)形成的卤键复合物进行构型全优化,得到各分子的稳定几何构型和分子间相互作用能.利用电子密度拓扑分析方法分析卤键复合物的拓扑性质,探讨了该类分子间卤键的作用本质.证明吡咯与双卤分子间存在Y-X...N和Y-X...π2类相互作用,且后者比前者强.复合物中的卤键介于共价键与离子键之间,偏于静电作用成分为主.形成卤键后,2种类型卤键复合物中的电子受体X-Y键伸长,其振动频率发生红移.用电子密度拓扑分析程序GTA-2000,将π型卤键体系中π电子与σ电子分开处理,绘制出π电子密度等值线图和Laplacian量等值线图,更加形象地说明π型卤键的存在和作用本质.利用AIM程序计算了卤键复合物中各原子电子积分的性质,原子积分性质随着卤键形成发生了改变.     

The establishment of edge-based loop algebra theory of kinematic chains and its applications

Based on the edge-based array representation of loops in the topological graphs of kinematic chains, this paper first proposes three arithmetic operations of loops. Then the concept of the independent loop set as well as its determination rules is introduced, and a new structure decomposition algorithm of kinematic chains is presented. Based on the algorithm, an automatic and efficient method for rigid sub-chain detection and driving pair selection of kinematic chains is proposed. Finally, an index is proposed to assess computation complexity of kinematic analysis with respect to different driving pair selections.     

Resource service optimal-selection based on intuitionistic fuzzy set and non-functionality QoS in manufacturing grid system

In manufacturing grid (MGrid) system, according to functional requirements of a task, there exist a lot of resource services which have similar functional characteristics. Multiple resource services with similar functional characteristics raise the concern over resource service optimal-selection (RSOS). It is important to select the optimal resource service according to their non-functionality characteristics or quality of service (QoS). However, QoS attributes are not easy to measure due to their complexity and involvement of ill-structured information. In this study, user’s feeling is taken into account in RSOS in an MGrid system. The non-functionality QoS evaluation of resource services is based on users’ feeling and transaction experiences using intuitionistic fuzzy set (IFS). Furthermore, the dynamics of non-functionality QoS is considered, and a time-decay function is introduced into non-functionality QoS evaluation. A new method is proposed for RSOS based on IFS and non-functionality QoS, and the procedures are presented in detail. A practice case study is used to illustrate the proposed method and procedure. The performance and advantage of the proposed method are discussed.     

Text detection in images using sparse representation with discriminative dictionaries

Text detection is important in the retrieval of texts from digital pictures, video databases and webpages. However, it can be very challenging since the text is often embedded in a complex background. In this paper, we propose a classification-based algorithm for text detection using a sparse representation with discriminative dictionaries. First, the edges are detected by the wavelet transform and scanned into patches by a sliding window. Then, candidate text areas are obtained by applying a simple classification procedure using two learned discriminative dictionaries. Finally, the adaptive run-length smoothing algorithm and projection profile analysis are used to further refine the candidate text areas. The proposed method is evaluated on the Microsoft common test set, the ICDAR 2003 text locating set, and an image set collected from the web. Extensive experiments show that the proposed method can effectively detect texts of various sizes, fonts and colors from images and videos.     

Effective multiplicative updates for non-negative discriminative learning in multimodal dimensionality reduction

Fisher discriminant analysis gives the unsatisfactory results if points in the same class have within-class multimodality and fails to produce the non-negativity of projection vectors. In this paper, we focus on the newly formulated within and between-class scatters based supervised locality preserving dimensionality reduction problem and propose an effective dimensionality reduction algorithm, namely, Multiplicative Updates based non-negative Discriminative Learning (MUNDL), which optimally seeks to obtain two non-negative embedding transformations with high preservation and discrimination powers for two data sets in different classes such that nearby sample pairs in the original space compact in the learned embedding space, under which the projections of the original data in different classes can be appropriately separated from each other. We also show that MUNDL can be easily extended to nonlinear dimensionality reduction scenarios by employing the standard kernel trick. We verify the feasibility and effectiveness of MUNDL by conducting extensive data visualization and classification experiments. Numerical results on some benchmark UCI and real-world datasets show the MUNDL method tends to capture the intrinsic local and multimodal structure characteristics of the given data and outperforms some established dimensionality reduction methods, while being much more efficient.     

On the L∞ convergence of a difference scheme for coupled nonlinear Schrödinger equations

In this article, a finite difference scheme for coupled nonlinear Schrödinger equations is studied. The existence of the difference solution is proved by Brouwer fixed point theorem. With the aid of the fact that the difference solution satisfies two conservation laws, the finite difference solution is proved to be bounded in the discrete $L_{\infty }$ norm. Then, the difference solution is shown to be unique and second order convergent in the discrete $L_{\infty }$ norm. Finally, a convergent iterative algorithm is presented.     

Well-posedness, regularity and exact controllability of the SCOLE model

The SCOLE model is a coupled system consisting of a flexible beam (modelled as an Euler–Bernoulli equation) with one end clamped and the other end linked to a rigid body. Its inputs are the force and the torque acting on the rigid body. It is well-known that the SCOLE model is not exactly controllable with L ² input signals in the natural energy state space H ^c , because the control operator is bounded from the input space \mathbbC²{\mathbb{C}^2} to H ^c , and hence compact. We regard the velocity and the angular velocity of the rigid body as the output signals of this system. Using the theory of coupled linear systems (one infinite-dimensional and one finite-dimensional) developed by us recently in another paper, we show that the SCOLE model is well-posed, regular and exactly controllable in arbitrarily short time when using a certain smoother state space X ì H^c{\mathcal{X}\subset H^c}.     

Applications of projected circle centers in camera calibration

A novel camera calibration algorithm for solving the problems of both circles based and spheres based camera calibration is proposed. By treating the images of both a circle and a sphere as a revolving stick, the introduced algorithm gives the constraint of the imaged absolute conic (IAC) with the help of the projected circle centers. It is also introduced on how to compute the projected circle centers of different calibration objects. Once the projected circle centers are computed, the Euclidean structure then can be determined by the constraint of the IAC. Experiments with simulated and real data are carried out to show the validity of the proposed camera calibration algorithm.     

Quantifying Heuristics in the Ordinal Optimization Framework

Finding the optimal design for a discrete event dynamic system (DEDS) is in general difficult due to the large search space and the simulation-based performance evaluation. Various heuristics have been developed to find good designs. An important question is how to quantify the goodness of the heuristic designs. Inspired by the Ordinal Optimization, which has become an important tool for optimizing DEDS, we provide a method which can quantify the goodness of the design. By comparing with a set of designs that are uniformly sampled, we measure the ordinal performances of heuristic designs, i.e., we quantify the ranks of all (or some of) the heuristic designs among all the designs in the entire search space. The mathematical tool we use is the Hypothesis Testing, and the probability of making Type II error in the quantification is controlled to be under a very low level. The method can be used both when the performances of the designs can be accurately evaluated and when such performances are estimated by a crude but computationally easy model. The method can quantify both heuristics that output a single design and that output a set of designs. The method is demonstrated through numerical examples.