ECG-based biometrics: A real time classification approach

Behavioral biometrics is one of the areas with growing interest within the biosignal research community. A recent trend in the field is ECG-based biometrics, where electrocardiographic (ECG) signals are used as input to the biometric system. Previous work has shown this to be a promising trait, with the potential to serve as a good complement to other existing, and already more established modalities, due to its intrinsic characteristics. In this paper, we propose a system for ECG biometrics centered on signals acquired at the subject's hand. Our work is based on a previously developed custom, non-intrusive sensing apparatus for data acquisition at the hands, and involved the pre-processing of the ECG signals, and evaluation of two classification approaches targeted at real-time or near real-time applications. Preliminary results show that this system leads to competitive results both for authentication and identification, and further validate the potential of ECG signals as a complementary modality in the toolbox of the biometric system designer.

Hyperspectral unmixing based on mixtures of Dirichlet components

This paper introduces a new unsupervised hyperspectral unmixing method conceived to linear but highly mixed hyperspectral data sets, in which the simplex of minimum volume, usually estimated by the purely geometrically based algorithms, is far way from the true simplex associated with the endmembers. The proposed method, an extension of our previous studies, resorts to the statistical framework. The abundance fraction prior is a mixture of Dirichlet densities, thus automatically enforcing the constraints on the abundance fractions imposed by the acquisition process, namely, nonnegativity and sum-to-one. A cyclic minimization algorithm is developed where the following are observed: 1) The number of Dirichlet modes is inferred based on the minimum description length principle; 2) a generalized expectation maximization algorithm is derived to infer the model parameters; and 3) a sequence of augmented Lagrangian-based optimizations is used to compute the signatures of the endmembers. Experiments on simulated and real data are presented to show the effectiveness of the proposed algorithm in unmixing problems beyond the reach of the geometrically based state-of-the-art competitors.

Peers' evaluation of a reconfigurable IEEE1451.0-compliant and FPGA-based weblab

It is already more than 10 years that weblabs are seen as important resources to provide the experimental work required in engineering education. Several weblabs have been applied in engineering courses, but there are still unsolved problems related to the development of their infrastructures. For solving some of those problems, it was implemented a weblab with a reconfigurable infrastructure compliant with the IEEE1451.0 Std. and supported by Field Programmable Gate Array (FPGA) technology. This paper presents the referred weblab, and provides and analyses a set of researchers' opinions about the implemented infrastructure, and the adopted methodology for the conduction of real experiments.

Reconfigurable IEEE1451-FPGA based weblab infrastructure

Weblabs are spreading their influence in Science and Engineering (S&E) courses providing a way to remotely conduct real experiments. Typically, they are implemented by different architectures and infrastructures supported by Instruments and Modules (I&Ms) able to be remotely controlled and observed. Besides the inexistence of a standard solution for implementing weblabs, their reconfiguration is limited to a setup procedure that enables interconnecting a set of preselected I&Ms into an Experiment Under Test (EUT). Moreover, those I&Ms are not able to be replicated or shared by different weblab infrastructures, since they are usually based on hardware platforms. Thus, to overcome these limitations, this paper proposes a standard solution that uses I&Ms embedded into Field-Programmable Gate Array (FPGAs) devices. It is presented an architecture based on the IEEE1451.0 Std. supported by a FPGA-based weblab infrastructure able to be remotely reconfigured with I&Ms, described through standard Hardware Description Language (HDL) files, using a Reconfiguration Tool (RecTool).

FPGA-based weblab infrastructures guidelines and a prototype implementation example

Recent trends show an increasing number of weblabs, implemented at universities and schools, supporting practical training in technical courses and providing the ability to remotely conduct experiments. However, their implementation is typically based on individual architectures, unable of being reconfigured with different instruments/modules usually required by every experiment. In this paper, we discuss practical guidelines for implementing reconfigurable weblabs that support both local and remote control interfaces. The underlying infrastructure is based on reconfigurable, low-cost, FPGA-based boards supporting several peripherals that are used for the local interface. The remote interface is powered by a module capable of communicating with an Ethernet based network and that can either correspond to an internal core of the FPGA or an external device. These two approaches are discussed in the paper, followed by a practical implementation example.

Embedding instruments & modules into an IEEE1451-FPGA-Based Weblab infrastructure

Adopting standard-based weblab infrastructures can be an added value for spreading their influence and acceptance in education. This paper suggests a solution based on the IEEE1451.0 Std. and FPGA technology for creating reconfigurable weblab infrastructures using Instruments and Modules (I&Ms) described through standard Hardware Description Language (HDL) files. It describes a methodology for creating and binding I&Ms into an IEEE1451-module embedded in a FPGA-based board able to be remotely controlled/accessed using IEEE1451-HTTP commands. At the end, an example of a step-motor controller module bond to that IEEE1451-module is described.

Coalition based approach for shop floor agility – a multiagent approach

Dissertation submitted for a PhD degree in Electrical Engineering, speciality of Robotics and Integrated Manufacturing from the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

A qualitative assessment of modularity in CaesarJ components based on implementations of design patterns

Tese de Mestrado em Engenharia Informática

Development of an interface for ontology‐based transformation between features of different types

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

A random key based genetic algorithm for the resource constrained project scheduling problem

This paper presents a genetic algorithm for the Resource Constrained Project Scheduling Problem (RCPSP). The chromosome representation of the problem is based on random keys. The schedule is constructed using a heuristic priority rule in which the priorities of the activities are defined by the genetic algorithm. The heuristic generates parameterized active schedules. The approach was tested on a set of standard problems taken from the literature and compared with other approaches. The computational results validate the effectiveness of the proposed algorithm.

Designing market-based instruments for biodiversity conservation: learning with the Australian experience and evaluating Portugal's potential

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia do Ambiente, perfil Gestão de Sistemas Ambientais

Location-Based services - A crescente importância da localização

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Linux based mobile: operating systems

Trabalho de Projeto para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Numerical 3D modeling of heat transfer in human tissues for microwave radiometry monitoring of Brown fat metabolismo

Background: Brown adipose tissue (BAT) plays an important role in whole body metabolism and could potentially mediate weight gain and insulin sensitivity. Although some imaging techniques allow BAT detection, there are currently no viable methods for continuous acquisition of BAT energy expenditure. We present a non-invasive technique for long term monitoring of BAT metabolism using microwave radiometry. Methods: A multilayer 3D computational model was created in HFSS™ with 1.5 mm skin, 3-10 mm subcutaneous fat, 200 mm muscle and a BAT region (2-6 cm3) located between fat and muscle. Based on this model, a log-spiral antenna was designed and optimized to maximize reception of thermal emissions from the target (BAT). The power absorption patterns calculated in HFSS™ were combined with simulated thermal distributions computed in COMSOL® to predict radiometric signal measured from an ultra-low-noise microwave radiometer. The power received by the antenna was characterized as a function of different levels of BAT metabolism under cold and noradrenergic stimulation. Results: The optimized frequency band was 1.5-2.2 GHz, with averaged antenna efficiency of 19%. The simulated power received by the radiometric antenna increased 2-9 mdBm (noradrenergic stimulus) and 4-15 mdBm (cold stimulus) corresponding to increased 15-fold BAT metabolism. Conclusions: Results demonstrated the ability to detect thermal radiation from small volumes (2-6 cm3) of BAT located up to 12 mm deep and to monitor small changes (0.5°C) in BAT metabolism. As such, the developed miniature radiometric antenna sensor appears suitable for non-invasive long term monitoring of BAT metabolism.

High-performance flexible hybrid field-effect transistors based on cellulose fiber paper

IEEE Electron Device Letters, VOL. 29, NO. 9,