Modelling the Mechanical Behavior of Polymer-Based Nanocomposites

Molecular dynamics simulations were employed to analyze the mechanical properties of polymer-based nanocomposites with varying nanofiber network parameters. The study was focused on nanofiber aspect ratio, concentration and initial orientation. The reinforcing phase affects the behavior of the polymeric nanocomposite. Simulations have shown that the fiber concentration has a significant effect on the properties, with higher loadings resulting in higher stress levels and higher stiffness, matching the general behavior from experimental knowledge in this field. The results also indicate that, within the studied range, the observed effect of the aspect ratio and initial orientation is smaller than that of the concentration, and that these two parameters are interrelated.

GUIsurfer: A Reverse Engineering Framework for User Interface Software

GUIsurfer: A Reverse Engineering Framework for User Interface Software

The role of coordination analysis in software integration projects

What sort of component coordination strategies emerge in a software integration process? How can such strategies be discovered and further analysed? How close are they to the coordination component of the envisaged architectural model which was supposed to guide the integration process? This paper introduces a framework in which such questions can be discussed and illustrates its use by describing part of a real case-study. The approach is based on a methodology which enables semi-automatic discovery of coordination patterns from source code, combining generalized slicing techniques and graph manipulation

Criminal Liability of Organizations, Corporations, Legal Persons, and Similar Entities on Law of Portuguese Cybercrime: A Brief Discussion on the Issue of Crimes of “False Information,” the “Damage on Other Programs or Computer Data,” the “Computer-Software Sabotage,” the “Illegitimate Access,” the “Unlawful Interception,” and “Illegitimate Reproduction of the Protected Program”

Abstract: in Portugal, and in much of the legal systems of Europe, «legal persons» are likely to be criminally responsibilities also for cybercrimes. Like for example the following crimes: «false information»; «damage on other programs or computer data»; «computer-software sabotage»; «illegitimate access»; «unlawful interception» and «illegitimate reproduction of protected program». However, in Portugal, have many exceptions. Exceptions to the «question of criminal liability» of «legal persons». Some «legal persons» can not be blamed for cybercrime. The legislature did not leave! These «legal persons» are v.g. the following («public entities»): legal persons under public law, which include the public business entities; entities utilities, regardless of ownership; or other legal persons exercising public powers. In other words, and again as an example, a Portuguese public university or a private concessionaire of a public service in Portugal, can not commit (in Portugal) any one of cybercrime pointed. Fair? Unfair. All laws should provide that all legal persons can commit cybercrimes. PS: resumo do artigo em inglês.

Artificial neural networks for automatic modelling of the pectus excavatum corrective prosthesis

Pectus excavatum is the most common deformity of the thorax and usually comprises Computed Tomography (CT) examination for pre-operative diagnosis. Aiming at the elimination of the high amounts of CT radiation exposure, this work presents a new methodology for the replacement of CT by a laser scanner (radiation-free) in the treatment of pectus excavatum using personally modeled prosthesis. The complete elimination of CT involves the determination of ribs external outline, at the maximum sternum depression point for prosthesis placement, based on chest wall skin surface information, acquired by a laser scanner. The developed solution resorts to artificial neural networks trained with data vectors from 165 patients. Scaled Conjugate Gradient, Levenberg-Marquardt, Resilient Back propagation and One Step Secant gradient learning algorithms were used. The training procedure was performed using the soft tissue thicknesses, determined using image processing techniques that automatically segment the skin and rib cage. The developed solution was then used to determine the ribs outline in data from 20 patient scanners. Tests revealed that ribs position can be estimated with an average error of about 6.82±5.7 mm for the left and right side of the patient. Such an error range is well below current prosthesis manual modeling (11.7±4.01 mm) even without CT imagiology, indicating a considerable step forward towards CT replacement by a 3D scanner for prosthesis personalization.