On the representation of an inclined Gaussian beam

In most contemporary optics courses, Gaussian beams are demonstrated in the form of propagation along one coordinate axis. This is referred to as the conventional representation and is in fact a special form. In this paper, we derive the general representation of a Gaussian beam propagating obliquely to the coordinate axis, by performing a coordinate rotation transformation on the conventional representation. When doing so on the beam parameters, a restrictive condition has to be taken into account. Without this condition, the expressions for the beam parameters after the rotation are not consistent with the conventional ones.

Fast Haar Transform Based Feature Extraction for Face Representation and Recognition

Subspace learning is the process of finding a proper feature subspace and then projecting high-dimensional data onto the learned low-dimensional subspace. The projection operation requires many floating-point multiplications and additions, which makes the projection process computationally expensive. To tackle this problem, this paper proposes two simple-but-effective fast subspace learning and image projection methods, fast Haar transform (FHT) based principal component analysis and FHT based spectral regression discriminant analysis. The advantages of these two methods result from employing both the FHT for subspace learning and the integral vector for feature extraction. Experimental results on three face databases demonstrated their effectiveness and efficiency.

Graphical representation and the similarity of DNA primary sequences

In this article, graphical representations of DNA primary sequences were generated. Topological indices and molecular connectivity indices were calculated and used for the comparison of similarities among eight different DNA segments. The satisfactory results were achieved by this analysis.

Theoretical representation of shear and pressure influence on the phase separation behavior of PVME/PS mixture

In the framework of lattice fluid model, the Gibbs energy and equation of state are derived by introducing the energy (E-s) stored during flow for polymer blends under shear. From the calculation of the spinodal of poly(vinyl methyl ether) (PVME) and polystyrene (PS) mixtures, we have found the influence of E., an equation of state in pure component is inappreciable, but it is appreciable in the mixture. However, the effect of E, on phase separation behavior is extremely striking. In the calculation of spinodal for the PVME/PS system, a thin, long and banana miscibility gap generated by shear is seen beside the miscibility gap with lower critical solution temperature. Meanwhile, a binodal coalescence of upper and lower miscibility gaps is occurred. The three points of the three-phase equilibrium are forecasted. The shear rate dependence of cloud point temperature at a certain composition is discussed. The calculated results are acceptable compared with the experiment values obtained by Higgins et at. However, the maximum positive shift and the minimum negative shift of cloud point temperature guessed by Higgins are not obtained, Furthermore, the combining effects of pressure and shear on spinodal shift are predicted.

Representation of microscale ocean wavenumber spectrum correct to the second order

In this paper, the analytical representations of four wave source functions in high-frequency spectrum range are given on the basis of ocean wave theory and dimensional analysis, and the perturbation method is used to solve the governing equations of ocean wave high-frequency spectrum on the basis of the temporally stationary and locally homogeneous scale relations of microscale wave. The microscale ocean wavenumber spectrum correct to the second order has an explicit structure, its first order part represents the equilibrium between different source functions, and its second order part represents the contribution of microscale wave propagation.

学习不良少年的自我意识情绪研究

Self-conscious emotions (guilt, shame, embarrassment, pride, etc) are social emotions, and involve complex appraisals of how one’s behavior has been evaluated by the self and other people according to some value standards. Self-conscious emotions play an important role in human life by arousing and regulating human action tendencies, feeling and thoughts, which can promote people to work hard in achievement and task fields, maintain good interpersonal relationship according with social morality and expectation. The present study aimed to examine complex self-conscious emotional understanding capabilities in junior middle school students with and without learning disabilities, how the self-conscious emotions generate, and relationship between self-conscious emotions and self-representation in academic and interpersonal fields. Situational experimental methods were used in this research, and the results would give further supports for learning disabilities intervention. The main results of present research are as follows. 1. The study included 4 parts and 6 experiments. The aim of study 1 was to explore whether juveniles with learning disabilities understood complex self-conscious emotions differently from juveniles without learning disabilities. We surveyed the self-conscious emotions understanding of 37 learning disabilities and 45 non-learning disabilities with the emotional situation stories. The results indicated that the self-conscious emotional recognition in others for learning disabilities was lower than that of non-learning disabilities in different emotional recognition tasks. Moreover, children with learning disabilities were more inclined to recognize emotions in themselves as elemental emotions, however, children without learning disabilities were more inclined to recognize emotions in themselves as self-conscious emotions. 2. The aim of study 2 was to explore the generative mechanism of self-conscious emotions in academic and interpersonal fields with the method of situational experiments, namely to examine whether the self-discrepancy could cause self-conscious emotions for learning disabilities. 84 learning disabilities (in experiment 1) and 80 learning disabilities (in experiment 2) participated in the research, and the results were as follows. (1) Self discrepancy caused participants’ self-conscious emotions effectively in academic and interpersonal fields. One’s own and parents’ perspercive on the actual-ideal self-discrepancy both produced dejection-related emotions (shame、embarrassment) and agitation-related emotions (guilt). （2）In academic fields, children with learning disabilities caused higher level negative self-conscious emotions (embarrassment, shame, and guilt) and lower level positive self-conscious emotion (pride). However, there were no differences of self-conscious emotions for children with and without learning disabilities in non-academic fields. 3. The aim of study 3 was to explore what influence had self-conscious emotions on self-representation for learning disabilities with the method of situational experiments. 57 learning disabilities (in experiment 1) and 67 learning disabilities (in experiment 2) participated in the research, and the results were as follows. （1）The negative self-conscious for learning disabilities could influence their positive or negative academic and positive interpersonal self-representation stability, the ways in which self-evaluation of ability mediate these effects. However, there was no significant effect for the negative self-conscious and self-evaluation of ability predicting negative interpersonal self-representation stability. （2）The stability level of positive academic and interpersonal self-representation for learning disabilities was lower than that of non-learning disabilities. There was no significant difference of the negative interpersonal self-representation stability for children with and without learning disabilities in the positive self-conscious valence condition. However, the stability level of negative interpersonal self-representation for learning disabilities was lower than that of non-learning disabilities in the negative self-conscious valence condition. 4. The aim of study 4 was to explore the intervention effects for self-conscious emotions training course on emotional comprehension cability. 65 learning disabilities (34 in experimental group, and 31 in control group) participated in the research. The results showed that self-conscious emotions course boosted the self-conscious emotions apprehensive level for children with learning disabilities.

Taxonomic Syntax for First-Order Inference

Most knowledge representation languages are based on classes and taxonomic relationships between classes. Taxonomic hierarchies without defaults or exceptions are semantically equivalent to a collection of formulas in first order predicate calculus. Although designers of knowledge representation languages often express an intuitive feeling that there must be some advantage to representing facts as taxonomic relationships rather than first order formulas, there are few, if any, technical results supporting this intuition. We attempt to remedy this situation by presenting a taxonomic syntax for first order predicate calculus and a series of theorems that support the claim that taxonomic syntax is superior to classical syntax.

A Self-Organizing Multiple-View Representation of 3D Objects

We explore representation of 3D objects in which several distinct 2D views are stored for each object. We demonstrate the ability of a two-layer network of thresholded summation units to support such representations. Using unsupervised Hebbian relaxation, we trained the network to recognise ten objects from different viewpoints. The training process led to the emergence of compact representations of the specific input views. When tested on novel views of the same objects, the network exhibited a substantial generalisation capability. In simulated psychophysical experiments, the network's behavior was qualitatively similar to that of human subjects.

Analytical Representation of Contours

The interpretation and recognition of noisy contours, such as silhouettes, have proven to be difficult. One obstacle to the solution of these problems has been the lack of a robust representation for contours. The contour is represented by a set of pairwise tangent circular arcs. The advantage of such an approach is that mathematical properties such as orientation and curvature are explicityly represented. We introduce a smoothing criterion for the contour tht optimizes the tradeoff between the complexity of the contour and proximity of the data points. The complexity measure is the number of extrema of curvature present in the contour. The smoothing criterion leads us to a true scale-space for contours. We describe the computation of the contour representation as well as the computation of relevant properties of the contour. We consider the potential application of the representation, the smoothing paradigm, and the scale-space to contour interpretation and recognition.

Learning with Deictic Representation

Most reinforcement learning methods operate on propositional representations of the world state. Such representations are often intractably large and generalize poorly. Using a deictic representation is believed to be a viable alternative: they promise generalization while allowing the use of existing reinforcement-learning methods. Yet, there are few experiments on learning with deictic representations reported in the literature. In this paper we explore the effectiveness of two forms of deictic representation and a naive propositional representation in a simple blocks-world domain. We find, empirically, that the deictic representations actually worsen performance. We conclude with a discussion of possible causes of these results and strategies for more effective learning in domains with objects.

Tense, Aspect and the Cognitive Representation of Time

This paper explores the relationships between a computation theory of temporal representation (as developed by James Allen) and a formal linguistic theory of tense (as developed by Norbert Hornstein) and aspect. It aims to provide explicit answers to four fundamental questions: (1) what is the computational justification for the primitive of a linguistic theory; (2) what is the computational explanation of the formal grammatical constraints; (3) what are the processing constraints imposed on the learnability and markedness of these theoretical constructs; and (4) what are the constraints that a linguistic theory imposes on representations. We show that one can effectively exploit the interface between the language faculty and the cognitive faculties by using linguistic constraints to determine restrictions on the cognitive representation and vice versa. Three main results are obtained: (1) We derive an explanation of an observed grammatical constraint on tense?? Linear Order Constraint??m the information monotonicity property of the constraint propagation algorithm of Allen's temporal system: (2) We formulate a principle of markedness for the basic tense structures based on the computational efficiency of the temporal representations; and (3) We show Allen's interval-based temporal system is not arbitrary, but it can be used to explain independently motivated linguistic constraints on tense and aspect interpretations. We also claim that the methodology of research developed in this study??oss-level" investigation of independently motivated formal grammatical theory and computational models??a powerful paradigm with which to attack representational problems in basic cognitive domains, e.g., space, time, causality, etc.

Toward a Theory of Representation Design

This research is concerned with designing representations for analytical reasoning problems (of the sort found on the GRE and LSAT). These problems test the ability to draw logical conclusions. A computer program was developed that takes as input a straightforward predicate calculus translation of a problem, requests additional information if necessary, decides what to represent and how, designs representations capturing the constraints of the problem, and creates and executes a LISP program that uses those representations to produce a solution. Even though these problems are typically difficult for theorem provers to solve, the LISP program that uses the designed representations is very efficient.

The Role of Knowledge in Visual Shape Representation

This report shows how knowledge about the visual world can be built into a shape representation in the form of a descriptive vocabulary making explicit the important geometrical relationships comprising objects' shapes. Two computational tools are offered: (1) Shapestokens are placed on a Scale-Space Blackboard, (2) Dimensionality-reduction captures deformation classes in configurations of tokens. Knowledge lies in the token types and deformation classes tailored to the constraints and regularities ofparticular shape worlds. A hierarchical shape vocabulary has been implemented supporting several later visual tasks in the two-dimensional shape domain of the dorsal fins of fishes.