A Probabilistic Method for Point Matching in the Presence of Noise and Degeneracy

The Bayesian method is widely used in image processing and computer vision to solve ill-posed problems. This is commonly achieved by introducing a prior which, together with the data constraints, determines a unique and hopefully stable solution. Choosing a “correct” prior is however a well-known obstacle. This paper demonstrates that in a certain class of motion estimation problems, the Bayesian technique of integrating out the “nuisance parameters” yields stable solutions even if a flat prior on the motion parameters is used. The advantage of the suggested method is more noticeable when the domain points approach a degenerate configuration, and/or when the noise is relatively large with respect to the size of the point configuration.     

Prognosis of ω-Languages for the Diagnosis of *-Languages: A Topological Perspective

This article offers a novel perspective on the diagnosis of *-languages via a topological characterization of ω-languages. This allows for the different concepts that currently exist in diagnosis of discrete-event systems to be related to one another in a uniform setting and to study their complexity. For this purpose, we introduce the notion of prognosability of an ω-language, which in the classical setting corresponds to testing if a language is diagnosable and prediagnosable. We show that we can build a prognoser for some ω-language if this language is open and saturated, where openness is usually implied in the finitary setting. For both of these problems we present PSPACE algorithms, and establish that prognosability (i.e., whether or not a prognoser exists) for an ω-language is a PSPACE-complete problem. Our new characterization offers a novel point of view in the classical setting of diagnosis.     

On Convergence of the Arrow–Hurwicz Method for Saddle Point Problems

Journal of Mathematical Imaging and Vision - The Arrow–Hurwicz method is an inexact version of the Uzawa method; it has been widely applied to solve various saddle point problems in different...     

Algorithms for the Determination of Cutsets in a Hypergraph

Given a hypergraph,this paper provides three algorithms for finding all its minimal cutsets,minimal link cutsets and the least cutsets.The result not only set up a new studying field on cutsets of hypergraph,but also lay a foundation of analyzing the performance of multibus systems.The algorithm for determining all the least cutsets in a hypergaph is polynomial complex and more efficient than that in [2].     

A new algorithm for the extraction of the surface waves for the Green''''s function in layered dielectrics

There exist the complicated waveguide modes as well as the surface waves in the electromagnetic field induced by a horizontal electric dipole in layered lossless dielectrics between two ground planes. In spectral domain, all these modes can be characterized by the rational parts with the real poles of the vector and scalar potentials. The accurate extraction of these modes plays an important role in the evaluation of the Green's function in spatial domain. In this paper, a new algorithm based on rational approximation is presented, which can accurately extract all the real poles and the residues of each pole simultaneously. Thus, we can get all the surface wave modes and waveguide modes, which is of great help to the calculation of the spatial domain Green's function. The numerical results demonstrated the accuracy and efficiency of the proposed method.     

Using a Three-Impulse Maneuvering Scheme for Returning from the Lunar Orbit to the Reentry Point of the Earth’s Atmosphere

Journal of Computer and Systems Sciences International - A practically useful algorithm for constructing the trajectory of returning from a Lunar orbit to the Earth using one-impulse and...     

A new algorithm for the extraction of the surface waves for the Green’s function in layered dielectrics

There exist the complicated waveguide modes as well as the surface waves in the electromagnetic field induced by a horizontal electric dipole in layered lossless dielectrics between two ground planes. In spectral domain, all these modes can be characterized by the rational parts with the real poles of the vector and scalar potentials. The accurate extraction of these modes plays an important role in the evaluation of the Green’s function in spatial domain. In this paper, a new algorithm based on rational approximation is presented, which can accurately extract all the real poles and the residues of each pole simultaneously. Thus, we can get all the surface wave modes and waveguide modes, which is of great help to the calculation of the spatial domain Green’s function. The numerical results demonstrated the accuracy and efficiency of the proposed method.     

Super-Convergence in Maximum Norm of the Gradient for the Shortley–Weller Method

We prove in this paper the second-order super-convergence in \(L^{\infty }\)-norm of the gradient for the Shortley–Weller method. Indeed, this method is known to be second-order accurate for the solution itself and for the discrete gradient, although its consistency error near the boundary is only first-order. We present a proof in the finite-difference spirit, using a discrete maximum principle to obtain estimates on the coefficients of the inverse matrix. The proof is based on a discrete Poisson equation for the discrete gradient, with second-order accurate Dirichlet boundary conditions. The advantage of this finite-difference approach is that it can provide pointwise convergence results depending on the local consistency error and the location on the computational domain.     

Application of ‘vision in the loop’ for inspection of lace fabric

Within the textile manufacturing environment, inspection is an important process which is employed in order to ensure high quality of the final products. Traditionally, this process is achieved manually which is very tedious, time consuming and labour intensive. A central problem in automatic visual inspection and computer vision is to determine the extent to which one shape differs from another. This is the key element of any inspection algorithm. Pattern recognition operations such as correlation, template matching and model based vision methods can all be viewed as techniques for determining the difference between shapes. In this paper the problem of visual inspection of deformable materials in general, and lace in particular, is considered. This is particularly difficult to achieve due to inherent and inevitable variations between a ‘model’ and the material being inspected. A mechatronic approach based on correlation along with morphological filters and ‘active vision in the loop’ using a line-scan CCD camera is presented. The utilized algorithm and its advantages and disadvantages are also discussed.     

Characterization of static bifurcations for n-dimensional flows in the frequency domain

In this paper n-dimensional flows （described by continuous-time system） with static bifurcations are considered with the aim of classification of different elementary bifurcations using the frequency domain formalism. Based on frequency domain approach, we prove some criterions for the saddle-node bifurcation, transcritical bifurcation and pitchfork bifurcation, and give an example to illustrate the efficiency of the result obtained.     

Evaluation of the Kinect™ sensor for 3-D kinematic measurement in the workplace

Recording posture and movement is important for determining risk of musculoskeletal injury in the workplace, but existing motion capture systems are not suited for field work. Estimates of the 3-D relative positions of four 0.10 m cubes from the Kinect were compared to estimates from a Vicon motion capture system to determine whether the hardware sensing components were sensitive enough to be used as a portable 3-D motion capture system for workplace ergonomic assessments. The root-mean-squared errors (SD) were 0.0065 m (0.0048 m), 0.0109 m (0.0059 m), 0.0057 m (0.0042 m) in the x, y and z directions (with x axis to the right, y axis away from the sensor and z axis upwards). These data were collected over a range of 1.0-3.0m from the device covering a field of view of 54.0 degrees horizontally and 39.1 degrees vertically. Requirements for software, hardware and subject preparation were also considered to determine the usability of the Kinect in the field.     

Experimental application and enhancement of the XFEM–GA algorithm for the detection of flaws in structures

The extended finite element formulation (XFEM) combined with genetic algorithms (GAs) have previously been shown to be very effective in the detection of flaws in structures. By this approach, the XFEM is used to model the forward problem and a GA is used as the optimization scheme, converging to the true flaw. The convergence is obtained by minimizing the error between sensor measurements and data obtained by solving the forward problem.The current study proposes several advances of this XFEM–GA algorithm, more specifically: (i) a novel genetic algorithm that accelerates the convergence of the scheme and alleviates entrapment in local optima, (ii) a generic XFEM formulation of an elliptical hole which is utilized to detect any type of flaw (cracks or holes) of any shape, and (iii) experimental verification of the approach for an arbitrary crack in a 2D plate.Convergence studies on various benchmark problems including the experimental verification clearly show the potential of this approach to detection of arbitrary flaws.     

Dynamics of quantum correlation for a qubit–qutrit system in the presence of the dephasing environments

We analytically study the dynamic behaviors of quantum correlation measured by three kinds of measures including quantum discord (QD), geometric quantum discord (GQD) and one-norm GQD for a qubit–qutrit system under the influence of dephasing environments with Ohmic-like spectral densities at nonzero temperature. It is shown that the similar evolution behaviors may be obtained for sub-Ohmic and Ohmic reservoirs. By properly choosing the system’s initial states and reservoir temperature, quantum correlation can take on some interesting results, such as the frozen and double sudden transition as well as the “revival” phenomenon, etc. Meanwhile, the remarkable similarities and differences among these correlation measures are also analyzed in detail and some significant results are presented. Our results provide some important information for the application of quantum correlation in hybrid qubit–qutrit systems in quantum information.     

A hybrid rule – neural approach for the automation of legal reasoning in the discretionary domain of family law in Australia

Few automated legal reasoning systems have been developed in domains of law in which a judicial decision maker has extensive discretion in the exercise of his or her powers. Discretionary domains challenge existing artificial intelligence paradigms because models of judicial reasoning are difficult, if not impossible to specify. We argue that judicial discretion adds to the characterisation of law as open textured in a way which has not been addressed by artificial intelligence and law researchers in depth. We demonstrate that systems for reasoning with this form of open texture can be built by integrating rule sets with neural networks trained with data collected from standard past cases. The obstacles to this approach include difficulties in generating explanations once conclusions have been inferred, difficulties associated with the collection of sufficient data from past cases and difficulties associated with integrating two vastly different paradigms. A knowledge representation scheme based on the structure of arguments proposed by Toulmin has been used to overcome these obstacles. The system, known as Split Up, predicts judicial decisions in property proceedings within family law in Australia. Predictions from the system have been compared to those from a group of lawyers with favourable results.     

2-D EAG Method for the Recognition of Hand-Printed Chinese Characters

A method, called Two-Dimensional Extended Attribute Grammars (2-DEAGs). for the recognition ofhand-printed Chinese characters is presented. This method uses directly two dimensional information, and pro-vides a scheme for dealing with various kinds of specific cases in a uniform way. In this method, componentsare drawn in guided and redundant way and reductions are made level by level just in accordance with the com-ponent combination relations of Chinese characters. The method provides also polysemous grammars,coexisting grammars and structure inferrings which constrain redundant recognition by comparison among similarcharacters or components and greatly increase the tolerance ability to distortion.     

Using the Fredholm resolvent for computing the ℋ2-norm of linear periodic systems

This article presents a method for the ?₂-norm computation of single-loop finite-dimensional linear continuous periodic systems, which is based on the parametric transfer function concept and the calculus of Fredholm integral equations of the second kind. General formulae for the computation of the mean output variance are provided as relations of two integral functions of an auxiliary parameter. On the basis of the general solution, an approximate computation method is derived, and the deviation of the approximate solution is estimated. In principle, this approach allows one to perform the computation with any desired accuracy.     

2-D EAG Method for the Recognition of Hand-Printed Chinese Characters

A method,called Two-Dimensional Extended Attribute Grammars(2-D EAGs) for the recognition of hand-printed Chinese characters is presented.This method uses directly two dimensional information,and provides a scheme for dealing with various kinds of specific cases in a uniform way.In this method,components are drawn in guided and redundant way and reductions are made level by leve just in accordance with the component combination relations of Chinese characters.The method provids also polysemous grammars,coexisting grammars and structure inferrings whih constrain redundant recognition by comparison among similar characters of components and greatly increase the tolerance ability to distortion.     

Parallel Implementation of the BiCGStab（2） Method in GPU Using CUDA and Matlab for Solution of Linear Systems

This paper presents a parallel implementation of the hybrid BiCGStab（2） （bi-conjugate gradient stabilized） iterative method in a GPU （graphics processing unit） for solution of large and sparse linear systems. This implementation uses the CUDA-Matlab integration, in which the method operations are performed in a GPU core using Matlab built-in functions. The goal is to show that the exploitation of parallelism by using this new technology can provide a significant computational performance. For the validation of the work, we compared the proposed implementation with a BiCGStab（2） sequential and parallelized implementation in the C and CUDA-C languages. The results showed that the proposed implementation is more efficient and can be viable for simulations being carried out with quality and in a timely manner. The gains in computational efficiency were 76x and 6x compared to the implementation in C and CUDA-C, respectively.     

A Geometric Approach for Regularization of the Data Term in Stereo-Vision

Every stereovision application must cope with the correspondence problem. The space of the matching variables, often consisting of spatial coordinates, intensity and disparity, is commonly referred as the data term (space). Since the data is often noisy a-priori, preference is required to result a smooth disparity (or piecewise smooth). To this end, each local method (e.g. window correlation techniques) performs a regularization of the data space. In this paper we propose a geometric framework for anisotropic regularization of the data space seeking to preserve the discontinuities in this space when filtering out the noise. On the other hand, the global methods consider a non-regularized data term with a smoothing constraint imposed directly on the disparity. This paper also proposes a new idea where the data space is regularized in a global method prior to the disparity evaluation. The idea is implemented on the state of the art variational method. Experimental results on the Middlebury real images demonstrate the advantages of the proposed approach.