Contributo para a validação de uma escala pediátrica, Peabody Developmental Motor Scale-2 (versão portuguesa)

Mestrado em Fisioterapia

A power line communication stack for metering, SCADA and large-scale domotic applications

This paper describes the communication stack of the REMPLI system: a structure using power-lines and IPbased networks for communication, for data acquisition and control of energy distribution and consumption. It is furthermore prepared to use alternative communication media like GSM or analog modem connections. The REMPLI system provides communication service for existing applications, namely automated meter reading, energy billing and domotic applications. The communication stack, consisting of physical, network, transport, and application layer is described as well as the communication services provided by the system. We show how the peculiarities of the power-line communication influence the design of the communication stack, by introducing requirements to efficiently use the limited bandwidth, optimize traffic and implement fair use of the communication medium for the extensive communication partners.

Biodegradação enzimática de aminas aromáticas tóxicas

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Química e Biológica

Application of continuous wavelet transform to the analysis of the modulus of the fractional Fourier transform bands for resolving two component mixture

In this paper, the fractional Fourier transform (FrFT) is applied to the spectral bands of two component mixture containing oxfendazole and oxyclozanide to provide the multicomponent quantitative prediction of the related substances. With this aim in mind, the modulus of FrFT spectral bands are processed by the continuous Mexican Hat family of wavelets, being denoted by MEXH-CWT-MOFrFT. Four modulus sets are obtained for the parameter a of the FrFT going from 0.6 up to 0.9 in order to compare their effects upon the spectral and quantitative resolutions. Four linear regression plots for each substance were obtained by measuring the MEXH-CWT-MOFrFT amplitudes in the application of the MEXH family to the modulus of the FrFT. This new combined powerful tool is validated by analyzing the artificial samples of the related drugs, and it is applied to the quality control of the commercial veterinary samples.

Analysis of financial indices by means of the windowed Fourier transform

The goal of this study is to analyze the dynamical properties of financial data series from nineteen worldwide stock market indices (SMI) during the period 1995–2009. SMI reveal a complex behavior that can be explored since it is available a considerable volume of data. In this paper is applied the window Fourier transform and methods of fractional calculus. The results reveal classification patterns typical of fractional order systems.

Dynamical behaviour of multi-particle large-scale systems

Collective behaviours can be observed in both natural and man-made systems composed of a large number of elemental subsystems. Typically, each elemental subsystem has its own dynamics but, whenever interaction between individuals occurs, the individual behaviours tend to be relaxed, and collective behaviours emerge. In this paper, the collective behaviour of a large-scale system composed of several coupled elemental particles is analysed. The dynamics of the particles are governed by the same type of equations but having different parameter values and initial conditions. Coupling between particles is based on statistical feedback, which means that each particle is affected by the average behaviour of its neighbours. It is shown that the global system may unveil several types of collective behaviours, corresponding to partial synchronisation, characterised by the existence of several clusters of synchronised subsystems, and global synchronisation between particles, where all the elemental particles synchronise completely.

EMMON: a system architecture for large- scale, dense and real-time WSNs

In spite of the significant amount of scientific work in Wireless Sensor Networks (WSNs), there is a clear lack of effective, feasible and usable WSN system architectures that address both functional and non-functional requirements in an integrated fashion. This poster abstract outlines the EMMON system architecture for large-scale, dense, real-time embedded monitoring. EMMON relies on a hierarchical network architecture together with integrated middleware and command&control mechanisms. It has been designed to use standard commercially– available technologies, while maintaining as much flexibility as possible to meet specific applications’ requirements. The EMMON WSN architecture has been validated through extensive simulation and experimental evaluation, including through a 300+ node test-bed, the largest WSN test-bed in Europe to date

Poster: EMMON: a WSN system architecture and toolset for large-scale and dense real-time embedded monitoring

Wireless sensor networks (WSNs) have attracted growing interest in the last decade as an infrastructure to support a diversity of ubiquitous computing and cyber-physical systems. However, most research work has focused on protocols or on specific applications. As a result, there remains a clear lack of effective and usable WSN system architectures that address both functional and non-functional requirements in an integrated fashion. This poster outlines the EMMON system architecture for large-scale, dense, real-time embedded monitoring. It provides a hierarchical communication architecture together with integrated middleware and command and control software. It has been designed to maintain as much as flexibility as possible while meeting specific applications requirements. EMMON has been validated through extensive analytical, simulation and experimental evaluations, including through a 300+ nodes test-bed the largest single-site WSN test-bed in Europe.

The dark side of DEMMON: what is behind the scene in engineering large-scale wireless sensor networks

Most research work on WSNs has focused on protocols or on specific applications. There is a clear lack of easy/ready-to-use WSN technologies and tools for planning, implementing, testing and commissioning WSN systems in an integrated fashion. While there exists a plethora of papers about network planning and deployment methodologies, to the best of our knowledge none of them helps the designer to match coverage requirements with network performance evaluation. In this paper we aim at filling this gap by presenting an unified toolset, i.e., a framework able to provide a global picture of the system, from the network deployment planning to system test and validation. This toolset has been designed to back up the EMMON WSN system architecture for large-scale, dense, real-time embedded monitoring. It includes network deployment planning, worst-case analysis and dimensioning, protocol simulation and automatic remote programming and hardware testing tools. This toolset has been paramount to validate the system architecture through DEMMON1, the first EMMON demonstrator, i.e., a 300+ node test-bed, which is, to the best of our knowledge, the largest single-site WSN test-bed in Europe to date.

EMMON: a WSN system architecture for large scale and dense real-time embedded monitoring

Wireless sensor networks (WSNs) have attracted growing interest in the last decade as an infrastructure to support a diversity of ubiquitous computing and cyber-physical systems. However, most research work has focused on protocols or on specific applications. As a result, there remains a clear lack of effective, feasible and usable system architectures that address both functional and non-functional requirements in an integrated fashion. In this paper, we outline the EMMON system architecture for large-scale, dense, real-time embedded monitoring. EMMON provides a hierarchical communication architecture together with integrated middleware and command and control software. It has been designed to use standard commercially-available technologies, while maintaining as much flexibility as possible to meet specific applications requirements. The EMMON architecture has been validated through extensive simulation and experimental evaluation, including a 300+ node test-bed, which is, to the best of our knowledge, the largest single-site WSN test-bed in Europe to date.

Efficient aggregate computations in large-scale dense WSN

We focus on large-scale and dense deeply embedded systems where, due to the large amount of information generated by all nodes, even simple aggregate computations such as the minimum value (MIN) of the sensor readings become notoriously expensive to obtain. Recent research has exploited a dominance-based medium access control(MAC) protocol, the CAN bus, for computing aggregated quantities in wired systems. For example, MIN can be computed efficiently and an interpolation function which approximates sensor data in an area can be obtained efficiently as well. Dominance-based MAC protocols have recently been proposed for wireless channels and these protocols can be expected to be used for achieving highly scalable aggregate computations in wireless systems. But no experimental demonstration is currently available in the research literature. In this paper, we demonstrate that highly scalable aggregate computations in wireless networks are possible. We do so by (i) building a new wireless hardware platform with appropriate characteristics for making dominance-based MAC protocols efficient, (ii) implementing dominance-based MAC protocols on this platform, (iii) implementing distributed algorithms for aggregate computations (MIN, MAX, Interpolation) using the new implementation of the dominance-based MAC protocol and (iv) performing experiments to prove that such highly scalable aggregate computations in wireless networks are possible.

Capital social no ELSA-Brasil: confiabilidade teste-reteste do Resource Generator scale

OBJETIVO: Estimar a confiabilidade teste-reteste dos itens do Resource Generator scale para avaliação de capital social no Estudo Longitudinal de Saúde do Adulto (ELSA-Brasil).MÉTODOS: A escala de capital social foi aplicada em subamostra de 281 participantes dos seis Centros de Investigação do ELSA, em duas oportunidades, com intervalo de sete a 14 dias. O instrumento é constituído por 31 itens que representam situações concretas para avaliar o acesso a diferentes tipos de recursos, além de avaliar a fonte dos recursos disponíveis (familiares, amigos ou conhecidos). A análise estatística foi realizada por meio de estatísticas kappa (k) e kappa ajustado pela prevalência (ka).RESULTADOS: Os recursos sociais investigados foram encontrados com grande frequência (acima de 50%). Em relação à presença ou ausência dos recursos, as estimativas de confiabilidade ajustadas pela prevalência (ka) variaram de 0,54 a 0,97. No que se refere à fonte de recurso, essas estimativas variaram de ka = 0,45 (alguém que tenha bons contatos com a mídia) a ka = 0,86 (alguém que se formou no Ensino Médio).CONCLUSÕES: A escala apresentou níveis adequados de confiabilidade, que variaram de acordo com o tipo de recurso.

Localizing objects in large-scale cyber- physical systems

We use the term Cyber-Physical Systems to refer to large-scale distributed sensor systems. Locating the geographic coordinates of objects of interest is an important problemin such systems. We present a new distributed approach to localize objects and events of interest in time complexity independent of number of nodes.

Brazilian version of the Quality of Care Scale: the perspective of people with disabilities

OBJECTIVE To analyze evidence of the validity and reliability of a Brazilian Portuguese version of the Quality of Care Scale from the perspective of people with physical and intellectual disabilities.METHODS There were 162 people with physical disabilities and 156 with intellectual disabilities from Porto Alegre and metropolitan region, who participated in the study in 2008. Classical psychometrics was used to independently analyze the two samples. Hypotheses for evidence of criterion validity (concurrent type) were tested with the Mann-Whitney test for non-normal distributions. Principal components analysis was used to explore factorial models. Evidence of reliability was calculated with Cronbach alpha for the scales and subscales. Test-retest reliability was analyzed for individuals with intellectual disabilities through intra-class correlation coefficient and the Willcoxon test.RESULTS The principal components in the group with physical disabilities replicated the original model presented as a solution to the international project data. Evidence of discriminant validity and test-retest reliability was found.CONCLUSIONS The transcultural factor model found within the international sample project seems appropriate for the samples investigated in this study, especially the physical disabilities group. Depression, pain, satisfaction with life and disability may play a mediating role in the evaluation of quality of care. Additional research is needed to add to evidence of the validity of the instruments.

Enhancing Multimodal Silent Speech Interfaces With Feature Selection

In research on Silent Speech Interfaces (SSI), different sources of information (modalities) have been combined, aiming at obtaining better performance than the individual modalities. However, when combining these modalities, the dimensionality of the feature space rapidly increases, yielding the well-known "curse of dimensionality". As a consequence, in order to extract useful information from this data, one has to resort to feature selection (FS) techniques to lower the dimensionality of the learning space. In this paper, we assess the impact of FS techniques for silent speech data, in a dataset with 4 non-invasive and promising modalities, namely: video, depth, ultrasonic Doppler sensing, and surface electromyography. We consider two supervised (mutual information and Fisher's ratio) and two unsupervised (meanmedian and arithmetic mean geometric mean) FS filters. The evaluation was made by assessing the classification accuracy (word recognition error) of three well-known classifiers (knearest neighbors, support vector machines, and dynamic time warping). The key results of this study show that both unsupervised and supervised FS techniques improve on the classification accuracy on both individual and combined modalities. For instance, on the video component, we attain relative performance gains of 36.2% in error rates. FS is also useful as pre-processing for feature fusion. Copyright © 2014 ISCA.