基于图像对比度数量映射的矢量场可视化算法

矢量场可视化是科学计算可视化中的一个研究热点,基于纹理图像的流线积分算法可以清楚地描述矢量场的细节。科学计算的数据通常是多维的变量,为了能在图像上同时显示超过2维的变量,采取了如对图像的颜色、明暗等属性进行数量映射的各种方法。本文提出了一种对图像的对比度进行数量映射的方法,动态改变图像局部的对比度,达到较好的可视化效果。

空间量化的心理表征

空间量化(spacial quantification)是空间知觉的基础,是对特定空间性质的表达。离散量(discrete magnitude)与连续量(continuous quantity)分别反映了空间分立和连续的性质,二者有着相似的行为效应,在神经表达上也有部分重叠,这些证据暗示了二者可能有共同的表征机制——模拟表征(analog magnitude representation)。数量空间映射(number–space mappings)提供了数量与空间关系的直接证据。但空间量化的研究中还有许多未解之谜,如:空间量化的动态表征、量化机制的普遍性、参照点问题、复杂和多维空间的量化等。在具身认知(embodied cognition)的框架下,空间量化的心理表征研究将对空间的性质做出更深刻的回答。

Database-oriented storage based on LMDB and linear octree for massive block model

Data organization requires high efficiency for large amount of data applied in the digital mine system. A new method of storing massive data of block model is proposed to meet the characteristics of the database, including ACID-compliant, concurrency support, data sharing, and efficient access. Each block model is organized by linear octree, stored in LMDB（lightning memory-mapped database）. Geological attribute can be queried at any point of 3D space by comparison algorithm of location code and conversion algorithm from address code of geometry space to location code of storage. The performance and robustness of querying geological attribute at 3D spatial region are enhanced greatly by the transformation from 3D to 2D and the method of 2D grid scanning to screen the inner and outer points. Experimental results showed that this method can access the massive data of block model, meeting the database characteristics. The method with LMDB is at least 3 times faster than that with etree, especially when it is used to read. In addition, the larger the amount of data is processed, the more efficient the method would be.

Mapping of quantitative trait loci using the skew-normal distribution

In standard interval mapping (IM) of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. When this assumption of normality is violated, the most commonly adopted strategy is to use the previous model after data transformation. However, an appropriate transformation may not exist or may be difficult to find. Also this approach can raise interpretation issues. An interesting alternative is to consider a skew-normal mixture model in standard IM, and the resulting method is here denoted as skew-normal IM. This flexible model that includes the usual symmetric normal distribution as a special case is important, allowing continuous variation from normality to non-normality. In this paper we briefly introduce the main peculiarities of the skew-normal distribution. The maximum likelihood estimates of parameters of the skew-normal distribution are obtained by the expectation-maximization (EM) algorithm. The proposed model is illustrated with real data from an intercross experiment that shows a significant departure from the normality assumption. The performance of the skew-normal IM is assessed via stochastic simulation. The results indicate that the skew-normal IM has higher power for QTL detection and better precision of QTL location as compared to standard IM and nonparametric IM.

Mapping methods for output-based objective speech quality assessment using data mining

Objective speech quality is difficult to be measured without the input reference speech.Mapping methods using data mining are investigated and designed to improve the output-based speech quality assessment algorithm.The degraded speech is firstly separated into three classes(unvoiced,voiced and silence),and then the consistency measurement between the degraded speech signal and the pre-trained reference model for each class is calculated and mapped to an objective speech quality score using data mining.Fuzzy Gaussian mixture model(GMM)is used to generate the artificial reference model trained on perceptual linear predictive(PLP)features.The mean opinion score(MOS)mapping methods including multivariate non-linear regression(MNLR),fuzzy neural network(FNN)and support vector regression(SVR)are designed and compared with the standard ITU-T P.563 method.Experimental results show that the assessment methods with data mining perform better than ITU-T P.563.Moreover,FNN and SVR are more efficient than MNLR,and FNN performs best with 14.50% increase in the correlation coefficient and 32.76% decrease in the root-mean-square MOS error.

Periodic Semifolded Solitary Waves for (2+1)-Dimensional Variable Coefficient Broer-Kaup System

Applying the extended mapping method via Riccati equation, many exact variable separation solutions for the （2＆1 ）-dimensional variable coefficient Broer-Kaup equation are obtained. Introducing multiple valued function and Jacobi elliptic function in the seed solution, special types of periodic semifolded solitary waves are derived. In the long wave limit these periodic semifolded solitary wave excitations may degenerate into single semifolded localized soliton structures. The interactions of the periodic semifolded solitary waves and their degenerated single semifolded soliton structures are investigated graphically and found to be completely elastic.

Formal Difference Analysis and Unification on p-Norm Distribution Density Functions

The cause of the formal difference of p-norm distribution density functions is analyzed, two problems in the deduction of p-norm formulating are improved, and it is proved that two different forms of p-norm distribution density functions are equivalent. This work is useful for popularization and application of the p-norm theory to surveying and mapping.

Variable-Coefficient Mapping Method Based on Elliptical Equation and Exact Solutions to Nonlinear SchrSdinger Equations with Variable Coefficient

In this paper, by means of the variable-coefficient mapping method based on elliptical equation, we obtain explicit solutions of nonlinear Schrodinger equation with variable-coefficient. These solutions include Jacobian elliptic function solutions, solitary wave solutions, soliton-like solutions, and trigonometric function solutions, among which some are found for the first time. Six figures are given to illustrate some features of these solutions. The method can be applied to other nonlinear evolution equations in mathematical physics.

Fuzzy Metrics Characterized by Molecules and Sets

Erceg in [1] extended the Hausdorff distance function betwen subsets of a set X to fuzzy settheory, and introduced a fuzzy pseudo-quasi-metric(p. q. metric) p: L^x xL^x -[0,∞] where L is acompletely distributive lattice, and the associated family of neighborhood mappings {Dr |r>O}. Thefuzzy metric space in Erceg's sense is denoted by (L^x, p, Dr) since there exists a one to one correspondence between fuzzy p. q. metrics and associatcd families of neighborhood mapping, a family{Dr|r>0}satisfying certain conditions is also callcd a (standard) fuzzy p. q metric. In [2] Liang defimed apointwise fuzzy p. q. metric d: P(L^x)×P(L^x)-[0, ∞) and applicd it to the construction of theproduct fuzzy metric. In this paper, we give axiomatic definitions of molcculewise and

A Note on Functor( )~0

We construct a counter-example about functor（ )0, and prove an isomor-phism theorem front convolution algebra to dual algebra of tensor coalgebra，

Discrete-Time Chaotic Systems Synchronization Based on Vector Norms Approach

Suitable stabilization conditions obtained for continuous chaotic systems are generalized to discrete-time chaotic systems. The proposed approach, leading to these conditions for complete synchronization is based on the use of state feedback and aggregation techniques for stability studies associated with the arrow form matrix for system description. The results are successfully applied for two identical discrete-time hyper chaotic Henon maps with different orders and also for non-identical discrete-time chaotic systems with same order namely the Lozi and the Ushio maps.

Parametric curve with an implicit domain

In this paper we present a new representation of curve, named parametric curve with an implicit domain(PCID), which is a curve that exists in parametric form defined on an implicit domain. PCID provides a bridge between parametric curve and implicit curve because the conversion of parametric form or implicit form to PCID is very convenient and efficient. We propose a framework model for mapping given points to the implicit curve in a homeomorphic manner. The resulting map is continuous and does not overlap. This framework can be used for many applications such as compatible triangulation, image deformation and fisheye views. We also present some examples and experimental results to demonstrate the effectiveness of the framework of our proposed model.