N. D. Gonçalves

Design of calibrators for profile extrusion : optimizing multi-step systems

Abstract A computer code, that couples numerical modelling and optimization routines, is described and used to automatically optimize the performance of a multi-step calibration stage of a plastic profile extrusion line. The objective of the optimization process is to minimize two conflicting criteria: final plastic profile average temperature and corresponding distribution standard deviation, both computed at the end of the calibration/cooling stage. The optimization routine uses Multi-Objective Evolutionary Algorithms (MOEA). Having in mind the well-known difficulties in characterizing the interface heat transfer coefficient, the system optimization was performed using different constant values for this parameter.

Privacy preserving gate counting with collaborative bluetooth scanners

Due to its pervasiveness and communication capabilities, Bluetooth can be used as an infrastructure for several situated interaction and massive sensing scenarios. This paper shows how Bluetooth scanning can be used in gate counting scenarios, where the main goal is to provide an accurate count for the number of unique devices sighted. To this end, we present an analysis of several stochastic counting techniques that not only provide an accurate count for the number of unique devices, but offer privacy guarantees as well.

Using the GPU to design complex profile extrusion dies

Abstract In the present work the benefits of using graphics processing units (GPU) to aid the design of complex geometry profile extrusion dies, are studied. For that purpose, a 3D finite volume based code that employs unstructured meshes to solve and couple the continuity, momentum and energy conservation equations governing the fluid flow, together with a constitutive equation, was used. To evaluate the possibility of reducing the calculation time spent on the numerical calculations, the numerical code was parallelized in the GPU, using a simple programing approach without complex memory manipulations. For verification purposes, simulations were performed for three benchmark problems: Poiseuille flow, lid-driven cavity flow and flow around a cylinder. Subsequently, the code was used on the design of two real life extrusion dies for the production of a medical catheter and a wood plastic composite decking profile. To evaluate the benefits, the results obtained with the GPU parallelized code were compared, in terms of speedup, with a serial implementation of the same code, that traditionally runs on the central processing unit (CPU). The results obtained show that, even with the simple parallelization approach employed, it was possible to obtain a significant reduction of the computation times.

Collaborative and Privacy-Aware Sensing for Observing Urban Movement Patterns

The information infrastructure that pervades urban environments represents a major opportunity for collecting information about Human mobility. However, this huge potential has been undermined by the overwhelming privacy risks that are associated with such forms of large scale sensing. In this research, we are concerned with the problem of how to enable a set of autonomous sensing nodes, e.g. a Bluetooth scanner or a Wi-Fi hotspot, to collaborate in the observation of movement patterns of individuals without compromising their privacy. We describe a novel technique that generates Precedence Filters and allows probabilistic estimations of sequences of visits to monitored locations and we demonstrate how this technique can combine plausible deniability by an individual with valuable information about aggregate movement patterns.