Medial axis and singularities

We correct one erroneous statement made in our recent paper "Medial axis and singularities".Comment: Some minor misprints are corrected and one final remark is adde

Residue currents associated with weakly holomorphic functions

We construct Coleff-Herrera products and Bochner-Martinelli type residue currents associated with a tuple $f$ of weakly holomorphic functions, and show that these currents satisfy basic properties from the (strongly) holomorphic case, as the transformation law, the Poincar\'e-Lelong formula and the equivalence of the Coleff-Herrera product and the Bochner-Martinelli type residue current associated with $f$ when $f$ defines a complete intersection.Comment: 28 pages. Updated with some corrections from the revision process. In particular, corrected and clarified some things in Section 5 and 6 regarding products of weakly holomorphic functions and currents, and the definition of the Bochner-Martinelli type current

Positive solutions for nonlinear singular elliptic equations of p-Laplacian type with dependence on the gradient

In this paper, we study a nonlinear Dirichlet problem of p-Laplacian type with combined effects of nonlinear singular and convection terms. An existence theorem for positive solutions is established as well as the compactness of solution set. Our approach is based on Leray-Schauder alternative principle, method of sub-supersolution, nonlinear regularity, truncation techniques, and set-valued analysis

The relative effects of progressive relaxation and EMG biofeedback training on the disruptive behavior, academic achievement, and locus of control of hyperactive children

This study investigated the effects of relaxation training on the academic achievement, locus of control, and disruptive behavior scores of hyperactive children. Its purpose was to determine whether group-administered progressive relaxation training would improve those scores as effectively as individually- conducted EMG biofeedback training. The sample consisted of U3 hyperactive suburban elementary school students, 23 males and 20 females. Treatment was provided in eight 25 minute sessions, scheduled at weekly intervals. Progressive relaxation training (PR) was administered through a series of eight cassette tapes designed to teach relaxation techniques. EMG training (BF) integrated the eight tapes with frontalis biofeedback. The control group listened to taped narrations of children's stories. Post-treatment data on academic achievement, locus of control, and disruptive behavior were collected one week following treatment. Initially, multivariate analysis of variance (MANOVA) results indicated no significant differences between the PR, BF, and control groups. However, a univariate _F test and discriminant analysis disclosed that locus of control scores for the PR group were significantly more internal than either the BF or control groups. Also, differences between the experimental and control groups on measures of academic achievement and disruptive behavior, while not statistically significant, were all in the expected direction. Thus, while this study did not produce conclusive evidence that group relaxation training is an effective method for treating the hyperactive student, the findings appear sufficiently positive to warrant further research.Education, College o

Registration and fuzzy segmentation modules for SemiVis framework

This paper presents the cross-platform framework for image processing with a focus on medical imaging. It allows a fast addition and testing of new algorithms using a modular structure. New modules can be created by using a platform-independent The C++ class library can be easily integrated with a whole system by a plug-in mechanisms. Together with the system core in the framework medical image processing modules are included. The plug-in mechanism allows to create a processing pipelines of this modules to achieve sophisticated processing functions such as registration or segmentation

Segmentation and visualisation MR images of the human brain

Segmentation and visualisation of anatomical regions of the brain are fundamental problems in medical image analysis. In this paper, we present a fuzzy-logic segmentation system that is capable of segmenting magnetic resonance (MR) images of a human brain. The presented method consists of two main stages: histogram thresholding and pixel classification using a rule-based fuzzy logic inference. After the segmentation is complete, attributes of different tissue classes may be determined (e.g., volumes), or the classes may be visualised as spatial objects. The implemented system provides many advanced 3D imaging tools

Method for Filling and Sharpening False Colour Layers of Dual Energy X-ray Images

An X-ray scanning and image processing have a vast range of applications in the security. An image of a content of some package being passed for example to an airplane or to the court house may help to figure out if there are any dangerous objects inside that package and to avoid possible threatening situation. As the raw X-ray images are not always easy to analyze and interpret, some image processing methods like an object detection, a frequency resolution increase or a pseudocolouring are being used. In this paper, we propose a pseudocoloring improvement over material based approach. By addition of the edge detection methods we fill and sharpen colour layers over the image, making it easier to interpret. We demonstrate the effectiveness of the methods using real data, acquired from a professional dual energy X-ray scanner