Top-hat by reconstruction operators based multi-scale multi-structuring element method for multiple linear feature detection with simple post-processing

To efficiently extract all the possible linear features in image, a multi-scale multi-structuring element top-hat by reconstruction operator based algorithm with simple post-processing is proposed in this paper. Multi-scale top-hat by reconstruction operator using multi-scale structuring elements is discussed, firstly. Also, through importing multi-structuring elements with linear shapes at different directions, multi-scale multi-structuring element top-hat by reconstruction operator for linear feature extraction is shown. By using the multi-scales of multi-structuring elements, the method of extracting all the possible linear feature regions in an image is proposed. After extracting the linear feature regions, the final detected linear features, which are expressed as lines with different shapes and lengths, are obtained through image binarisation and refinement. Experimental results on different types of images show that, the proposed algorithm is efficient for linear feature detection and could be widely used in different applications related to multiple linear feature detection.     

Image enhancement through contrast enlargement using the image regions extracted by multiscale top-hat by reconstruction

An image enhancement algorithm based on multiscale top-hat by reconstruction is proposed in this paper. Firstly, multiscale top-hat by reconstruction using multiscale structuring elements is discussed. Then, multiscale bright and black image regions are extracted. Thirdly, useful image regions for image enhancement are obtained from the extracted multiscale bright and black image regions. Finally, after a base image is calculated from the results of the opening and closing by reconstruction operations, the original image is enhanced through combing the useful image regions into the base image. Experimental results on different types of images show that the proposed algorithm is efficient.     

An improved building boundary extraction algorithm based on fusion of optical imagery and LIDAR data

This article presents a new method of automatic boundary extraction using LIDAR-optical fusion suited to handle diverse building shapes. This method makes full use of the complementary advantages of LIDAR data and optical imagery. Different building features are extracted from the two data sources and fused to form the final complete building boundaries. First, the points of each roof patch are detected from LIDAR point cloud. This process consists of four steps: filtering, building detection, wall point removal and roof patch detection. Second, initial building edges are extracted from optical imagery using an improved Canny detector constrained by edge location information derived from the LIDAR point cloud as edge buffer areas. Finally, the roof patch and initial edges are integrated by mathematical morphology to form the final complete building boundaries. All processes have no constraints or rules on building shapes. This method is fully data-driven and suitable for any building shape. LIDAR data and aerial images of complex geographical environments are used to test the method. These experimental results demonstrate that our method can automatically extract accurate boundaries for buildings with complex shapes, and also is highly robust in complex environments.     

A conformal approach for the analysis of the non-linear stability of radiation cosmologies

The conformal Einstein equations for a trace-free (radiation) perfect fluid are derived in terms of the Levi-Civita connection of a conformally rescaled metric. These equations are used to provide a non-linear stability result for de Sitter-like trace-free (radiation) perfect fluid Friedman–Lemaître–Robertson–Walker cosmological models. The solutions thus obtained exist globally towards the future and are future geodesically complete.     

A macroscopic kinetic model for DNA polymerase elongation and high-fidelity nucleotide selection

The enzymatically catalyzed template-directed extension of ssDNA/primer complex is an important reaction of extraordinary complexity. The DNA polymerase does not merely facilitate the insertion of dNMP, but it also performs rapid screening of substrates to ensure a high degree of fidelity. Several kinetic studies have determined rate constants and equilibrium constants for the elementary steps that make up the overall pathway. The information is used to develop a macroscopic kinetic model, using an approach described by Ninio [Ninio J., 1987. Alternative to the steady-state method: derivation of reaction rates from first-passage times and pathway probabilities. Proc. Natl. Acad. Sci. U.S.A. 84, 663-667]. The principle idea of the Ninio approach is to track a single template/primer complex over time and to identify the expected behavior. The average time to insert a single nucleotide is a weighted sum of several terms, including the actual time to insert a nucleotide plus delays due to polymerase detachment from either the ternary (template-primer-polymerase) or quaternary (+nucleotide) complexes and time delays associated with the identification and ultimate rejection of an incorrect nucleotide from the binding site. The passage times of all events and their probability of occurrence are expressed in terms of the rate constants of the elementary steps of the reaction pathway. The model accounts for variations in the average insertion time with different nucleotides as well as the influence of G + C content of the sequence in the vicinity of the insertion site. Furthermore the model provides estimates of error frequencies. If nucleotide extension is recognized as a competition between successful insertions and time delaying events, it can be described as a binomial process with a probability distribution. The distribution gives the probability to extend a primer/template complex with a certain number of base pairs and in general it maps annealed complexes into extension products.     

Optimizing Area and Perimeter of Convex Sets for Fixed Circumradius and Inradius

 In this paper two problems posed by Santaló are solved: we determine the planar convex sets which have maximum and minimum area or perimeter when the circumradius and the inradius are given, obtaining complete systems of inequalities for the cases (A, R, r) and (p, R, r). This work is supported in part by Dirección General de Investigación (MCYT) BFM2001-2871, and by OTKA grants No 31984 and 30012 Received October 15, 2001; revised January 29, 2002     

On the linearization of some singular, nonlinear elliptic problems and applications

This paper deals with the spectrum of a linear, weighted eigenvalue problem associated with a singular, second order, elliptic operator in a bounded domain, with Dirichlet boundary data. In particular, we analyze the existence and uniqueness of principal eigenvalues. As an application, we extend the usual concepts of linearization and Frechet derivability, and the method of sub and supersolutions to some semilinear, singular elliptic problems.     

On optimum design of structures and materials

A survey of problems of optimum design of structures and materials is presented with the main emphasis on fundamental aspects and on current methods and capabilities for topology and shape optimization.The methods are selected from conditions of versatility and suitability for integration into an engineering design optimization system which realizes the design process as an iterative solution procedure of a multicriterion optimization problem based on the concept of integration of finite element analysis, sensitivity analysis, and optimization by mathematical programming.A picture of current possibilities and the present status of the field is given through a number of examples.General invited lecture presented at the 12th Italian Congress on Theoretical and Applied Mechanics AIMETA '95, Naples, 3–6 October 1995.     

Long-Step Primal Path-Following Algorithm for Monotone Variational Inequality Problems

In this paper, we present a long-step primal path-following algorithm and prove its global convergence under usual assumptions. It is seen that the short-step algorithm is a special case of the long-step algorithm for a specific selection of the parameters and the initial solution. Our theoretical result indicates that the long-step algorithm is more flexible. Numerical results indicate that the long-step algorithm converges faster than the short-step algorithm.