Infrared thermography and NDT : 2050 horizon

Society is changing fast, new technologies and materials have been developed which require new inspection approaches. Infrared thermography (IRT) has emerged in the recent years as an attractive and reliable technique to address complex non-destructive testing (NDT) problems. Companies are now providing turn-key IRT-NDT systems, but the question we ask now is ‘What is next?’. Even though the future is elusive, we can consider the possible future developments in IR NDT. Our analysis shows that new developments will take place in various areas such as: acquisition, stimulation, processing and obviously an always enlarging range of applications with new materials which will have particular inspection requirements. This paper presents the various developments in the field of IRT which have evolved to lead to the current situation, and then examines the potential future trend in IRT-NDT

Chapter Coherent Resonant Properties of Cardiac Cells

Materials / States of matte

Coherent Resonant Properties of Cardiac Cells

Materials / States of matte

Muscle synergies in neuroscience and robotics: from input-space to task-space perspectives

In this paper we review the works related to muscle synergies that have been carried-out in neuroscience and control engineering. In particular, we refer to the hypothesis that the central nervous system (CNS) generates desired muscle contractions by combining a small number of predefined modules, called muscle synergies. We provide an overview of the methods that have been employed to test the validity of this scheme, and we show how the concept of muscle synergy has been generalized for the control of artificial agents. The comparison between these two lines of research, in particular their different goals and approaches, is instrumental to explain the computational implications of the hypothesized modular organization. Moreover, it clarifies the importance of assessing the functional role of muscle synergies: although these basic modules are defined at the level of muscle activations (input-space), they should result in the effective accomplishment of the desired task. This requirement is not always explicitly considered in experimental neuroscience, as muscle synergies are often estimated solely by analyzing recorded muscle activities. We suggest that synergy extraction methods should explicitly take into account task execution variables, thus moving from a perspective purely based on input-space to one grounded on task-space as well

Quantitative Performance Assessment of LiDAR-based Vehicle Contour Estimation Algorithms for Integrated Vehicle Safety Applications

Many nations and organizations are committing to achieving the goal of `Vision Zero\u27 and eliminate road traffic related deaths around the world. Industry continues to develop integrated safety systems to make vehicles safer, smarter and more capable in safety critical scenarios. Passive safety systems are now focusing on pre-crash deployment of restraint systems to better protect vehicle passengers. Current commonly used bounding box methods for shape estimation of crash partners lack the fidelity required for edge case collision detection and advanced crash modeling. This research presents a novel algorithm for robust and accurate contour estimation of opposing vehicles. The presented method is evaluated via a developed framework for key performance metrics and compared to alternative algorithms found in literature