Lessius Mechelen

About: Lessius Mechelen is a based out in . It is known for research contribution in the topics: Bearing (mechanical) & Object detection. The organization has 27 authors who have published 26 publications receiving 816 citations.

The critical distance theory for fatigue analysis of notched aluminium specimens subjected to repeated bending

Abstract: This paper provides new insights in the use of the critical distance method for fatigue analysis of notched aluminium components subjected to constant amplitude bending loading. A straightforward test setup was developed to load test samples with different stress concentrations in repeated bending at high test frequency. The mean values of the local endurable stress amplitudes are determined with the staircase method and the Dixon and Mood theory using a minimum amount of test samples. The critical distance is determined using these fatigue limits and the corresponding stress gradients determined by means of finite element analysis. The results indicate a unique critical distance of 0.22 mm for fatigue crack initiation. Consequently, the critical distance theory can be successfully applied for fatigue analysis of notched specimens or engineering components of aluminium EN AW 7075 T7351 with geometrical features of various size and shape subjected to fluctuating loading in bending.

Incluso: Social software for the social inclusion of marginalized youth

Abstract: INCLUSO: Social software for the social inclusion of marginalized youth Can ICT, and more specifically social software, support welfare organizations in their work with marginalized young people? This was the main research question addressed in INCLUSO, a research project funded by the European Commission’s 7th Framework Programme. In this paper, the authors start by introducing the concepts of social exclusion, e-inclusion and the digital divide. They discuss the concept of social software, its use by youngsters and the potential of social software to contribute to social inclusion. The authors then report on the organizational challenges met as they guided four social welfare organizations from Austria, Belgium, Poland and the UK in their implementation of social software tools to support their interaction with marginalized young people. They identify these challenges and present tools to assist social work organizations in defining successful strategies for adopting ICT and social software within their organizations. INCLUSO: Sociale software ten behoeve van sociale inclusie van gemarginaliseerde jongeren In hoeverre kan ICT, en in het bijzonder het gebruik van sociale software, een bijdrage leveren aan de sociale inclusie van kansarme jongeren? Wat is de rol van welzijnsorganisaties in dit proces en wat zijn de voornaamste belemmeringen voor het gebruik van sociale software als middel om sociale inclusie te stimuleren? Deze vragen stonden centraal in het INCLUSOproject, een onderzoeksproject dat werd gefinancierd door de European Commission’s 7th Framework Programme . Dit artikel start met een toelichting op concepten als sociale uitsluiting, digitale inclusie en digital divide . Ook wordt ingegaan op het gebruik van social software door jongeren en de potentie ervan voor sociale inclusie. De auteurs doen vervolgens verslag van de organisatorische uitdagingen die ontstonden bij de begeleiding van vier welzijnsorganisaties, bij de implementatie van social software ten behoeve van sociale inclusie. Zij identificeren deze uitdagingen en presenteren hulpmiddelen die welzijnsorganisaties behulpzaam kunnen zijn bij het zoeken naar succesvolle strategieen om ICT en sociale software in hun organisatie toe te passen.

Is the game worth the candle? Evaluation of OpenCL for object detection algorithm optimization

Abstract: In this paper we present out experiences with the implementation of an object detector using OpenCL. With this implementation we fullfil the need for fast and robust object detection, necessary in many applications in multiple domains (surveillance, traffic, image retrieval, ...). The algorithm lends itself to be implemented in a parallel way. We exploit this opportunity by implementing it on a GPU. For this implementation, we have choosen to use the OpenCL programming language, since this allows for scalability to more performant and different types of hardware, with minimal changes to the implementation. We will discuss how the parallelization is done, and discuss the challenges we met. We will also discuss the experimental timing results we achieved and evaluate the ease-of-use of OpenCL.

Faster and more intelligent object detection by combining OpenCL and KR

Abstract: In this paper we present a fast implementation of a robust object detector by using OpenCL. The use of fast object detection is of great use for a broad range of applications in multiple domains. OpenCL allows for scalability to more performant and different types of hardware, with minimal changes to the implementation. By using a GPU as execution device, we exploit the data parallelism opportunities of the algorithm. We also discuss the use of knowledge representation as a means to integrate expert knowledge into applications. This can be used both for faster processing by limiting the searching space, and for applications to work more autonomous by exploiting a higher level of intelligence.

Fungal plant pathogen detection in plant and soil samples using DNA macroarrays.

Abstract: PCR-based DNA array technology is one of the most suitable techniques to detect and identify multiple pathogens in a single assay. Out of the different array platforms that currently exist, membrane-based DNA macroarrays are the most convenient for plant disease diagnosis because of low costs, great sensitivity, and modest equipment requirements. Here we describe a protocol for routine detection of plant pathogens using DNA macroarrays, i.e., from sampling to analysis of hybridization results. Diagnosis can be completed within 36 h after sample collection.