Autonomic workflow activities: the award framework

Workflows have been successfully applied to express the decomposition of complex scientific applications. This has motivated many initiatives that have been developing scientific workflow tools. However the existing tools still lack adequate support to important aspects namely, decoupling the enactment engine from workflow tasks specification, decentralizing the control of workflow activities, and allowing their tasks to run autonomous in distributed infrastructures, for instance on Clouds. Furthermore many workflow tools only support the execution of Direct Acyclic Graphs (DAG) without the concept of iterations, where activities are executed millions of iterations during long periods of time and supporting dynamic workflow reconfigurations after certain iteration. We present the AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic) model of computation, based on the Process Networks model, where the workflow activities (AWA) are autonomic processes with independent control that can run in parallel on distributed infrastructures, e. g. on Clouds. Each AWA executes a Task developed as a Java class that implements a generic interface allowing end-users to code their applications without concerns for low-level details. The data-driven coordination of AWA interactions is based on a shared tuple space that also enables support to dynamic workflow reconfiguration and monitoring of the execution of workflows. We describe how AWARD supports dynamic reconfiguration and discuss typical workflow reconfiguration scenarios. For evaluation we describe experimental results of AWARD workflow executions in several application scenarios, mapped to a small dedicated cluster and the Amazon (Elastic Computing EC2) Cloud.

ECG Biometrics: A Template Selection Approach

Electrocardiography (ECG) biometrics is emerging as a viable biometric trait. Recent developments at the sensor level have shown the feasibility of performing signal acquisition at the fingers and hand palms, using one-lead sensor technology and dry electrodes. These new locations lead to ECG signals with lower signal to noise ratio and more prone to noise artifacts; the heart rate variability is another of the major challenges of this biometric trait. In this paper we propose a novel approach to ECG biometrics, with the purpose of reducing the computational complexity and increasing the robustness of the recognition process enabling the fusion of information across sessions. Our approach is based on clustering, grouping individual heartbeats based on their morphology. We study several methods to perform automatic template selection and account for variations observed in a person's biometric data. This approach allows the identification of different template groupings, taking into account the heart rate variability, and the removal of outliers due to noise artifacts. Experimental evaluation on real world data demonstrates the advantages of our approach.

BITalino: a novel hardware framework for physiological computing

Physical computing has spun a true global revolution in the way in which the digital interfaces with the real world. From bicycle jackets with turn signal lights to twitter-controlled christmas trees, the Do-it-Yourself (DiY) hardware movement has been driving endless innovations and stimulating an age of creative engineering. This ongoing (r)evolution has been led by popular electronics platforms such as the Arduino, the Lilypad, or the Raspberry Pi, however, these are not designed taking into account the specific requirements of biosignal acquisition. To date, the physiological computing community has been severely lacking a parallel to that found in the DiY electronics realm, especially in what concerns suitable hardware frameworks. In this paper, we build on previous work developed within our group, focusing on an all-in-one, low-cost, and modular biosignal acquisition hardware platform, that makes it quicker and easier to build biomedical devices. We describe the main design considerations, experimental evaluation and circuit characterization results, together with the results from a usability study performed with volunteers from multiple target user groups, namely health sciences and electrical, biomedical, and computer engineering. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.

PV system modeling by five parameters and in Situ test

This paper focuses on a novel formalization for assessing the five parameter modeling of a photovoltaic cell. An optimization procedure is used as a feasibility problem to find the parameters tuned at the open circuit, maximum power, and short circuit points in order to assess the data needed for plotting the I-V curve. A comparison with experimental results is presented for two monocrystalline PV modules.

Autonomic Activities in the Execution of Scientific Workflows: Evaluation of the AWARD Framework

Workflows have been successfully applied to express the decomposition of complex scientific applications. However the existing tools still lack adequate support to important aspects namely, decoupling the enactment engine from tasks specification, decentralizing the control of workflow activities allowing their tasks to run in distributed infrastructures, and supporting dynamic workflow reconfigurations. We present the AWARD (Autonomic Workflow Activities Reconfigurable and Dynamic) model of computation, based on Process Networks, where the workflow activities (AWA) are autonomic processes with independent control that can run in parallel on distributed infrastructures. Each AWA executes a task developed as a Java class with a generic interface allowing end-users to code their applications without low-level details. The data-driven coordination of AWA interactions is based on a shared tuple space that also enables dynamic workflow reconfiguration. For evaluation we describe experimental results of AWARD workflow executions in several application scenarios, mapped to the Amazon (Elastic Computing EC2) Cloud.

Avaliação do gasto energético em amputados de membro inferior utilizando o Six-Minute Walk Test

A capacidade de deambulação apresenta um significado bastante importante para a população em geral, uma vez que contribui para a manutenção do estado de saúde e para a reabilitação e melhoria da condição física, de uma forma geral. A amputação de um membro inferior, com ou sem abordagem protésica, impõe, ao amputado, um aumento no gasto energético durante a deambulação. A medição do gasto energético durante a marcha em amputados serve, não só para quantificar o esforço requerido, mas também para comparar a eficácia de diferentes componentes protésicos. Objetivos do estudo - Determinação dos fatores que influenciam a capacidade funcional dos amputados do membro inferior. Perceção do impacto das características pessoais, quadro clínico, hábitos e fatores comportamentais, bem como componentes protésicos no consumo de oxigénio e capacidade de deambulação.

Characterisation and electrochemical behaviour of electrodeposited Cu-Fe foams applied as pseudocapacitor electrodes

Copper iron (Cu-Fe) 3D porous foams for supercapacitor electrodes were electrodeposited in the cathodic regime, on stainless steel current collectors, using hydrogen bubbling dynamic template. The foams were prepared at different current densities and deposition times. The foams were submitted to thermal conditioning at temperatures of 150 and 250 degrees C. The morphology, composition and structure of the formed films were studied by SEM, EDS and XRD, respectively. The electrochemical behaviour was studied by cyclic voltammetry, electrochemical impedance spectroscopy and chronopotentiometry. The morphology of the 3D Cu-Fe foams is sensitive to the electrodeposition current and time. The increase of the current density produces a denser, larger and more ramified dendritic structure. Thermal conditioning at high temperature induces a coarser grain structure and the formation of copper oxides, which affect the electrochemical behaviour. The electrochemical response reveals the presence of various redox peaks assigned to the oxidation and reduction of Cu and Fe oxides and hydroxides in the foams. The specific capacitance of the 3D Cu Fe foams was significantly enhanced by thermal conditioning at 150 degrees C. The highest specific capacitance values attained 297 Fg(-1) which are much above the ones typically observed for single Cu or Fe Oxides and hydroxides. These values highlight a synergistic behaviour resulting from the combination of Cu and Fe in the form of nanostructured metallic foams. Moreover, the capacitance retention observed in an 8000 charge/discharge cycling test was above 66%, stating the good performance of these materials and its enhanced electrochemical response as supercapacitor negative electrodes. (C) 2014 Elsevier B.V. All rights reserved.

An enzymatic route to a benzocarbazole framework using bacterial CotA laccase

The CotA laccase-catalysed oxidation of the meta, para-disubstituted arylamine 2,4-diaminophenyldiamine delivers, under mild reaction conditions, a benzocarbazole derivative (1) (74% yield), a key structural motif of a diverse range of applications. This work extends the scope of aromatic frameworks obtained using these enzymes and represents a new efficient and clean method to construct in one step C-C and C-N bonds.

Hyperspectral imagery framework for unmixing and dimensionality estimation

In hyperspectral imagery a pixel typically consists mixture of spectral signatures of reference substances, also called endmembers. Linear spectral mixture analysis, or linear unmixing, aims at estimating the number of endmembers, their spectral signatures, and their abundance fractions. This paper proposes a framework for hyperpsectral unmixing. A blind method (SISAL) is used for the estimation of the unknown endmember signature and their abundance fractions. This method solve a non-convex problem by a sequence of augmented Lagrangian optimizations, where the positivity constraints, forcing the spectral vectors to belong to the convex hull of the endmember signatures, are replaced by soft constraints. The proposed framework simultaneously estimates the number of endmembers present in the hyperspectral image by an algorithm based on the minimum description length (MDL) principle. Experimental results on both synthetic and real hyperspectral data demonstrate the effectiveness of the proposed algorithm.