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.

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.

Analysis of financial data series using fractional Fourier transform and multidimensional scaling

The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indexes during the period 2000–2009. We analyze, under a regional criterium, ten main indexes at a daily time horizon. The methods and algorithms that have been explored for the description of dynamical phenomena become an effective background in the analysis of economical data. We start by applying the classical concepts of signal analysis, fractional Fourier transform, and methods of fractional calculus. In a second phase we adopt the multidimensional scaling approach. Stock market indexes are examples of complex interacting systems for which a huge amount of data exists. Therefore, these indexes, viewed from a different perspectives, lead to new classification patterns.

Robotic manipulators with vibrations: short time fourier transform of fractional spectra

This paper analyzes the signals captured during impacts and vibrations of a mechanical manipulator. In order to acquire and study the signals an experimental setup is implemented. The signals are treated through signal processing tools such as the fast Fourier transform and the short time Fourier transform. The results show that the Fourier spectrum of several signals presents a non integer behavior. The experimental study provides valuable results that can assist in the design of a control system to deal with the unwanted effects of vibrations.

Adaptação para a população Portuguesa da escala de avaliação Trunk Impairment Scale (TIS)

Para uma melhor avaliação e definição do plano de intervenção do indivíduo, é cada vez mais importante a existência instrumentos de avaliação válidos e fiáveis para a população portuguesa. Objetivo: Traduzir e adaptar para a população Portuguesa a escala Trunk Impairment Scale (TIS) em pacientes pós-AVE, e avaliar as propriedades psicométricas da mesma. Metodologia: A TIS foi traduzida para o Português e adaptada culturalmente para a população portuguesa. As propriedades psicométricas da mesma, incluindo validade, fiabilidade, concordância inter-observadores, consistência interna, sensibilidade, especificidade, poder de resposta, foram avaliadas numa população diagnosticada com AVE e num grupo de controlo de participantes saudáveis. Participaram neste estudo 80 indivíduos, divididos em dois grupos, nomeadamente indivíduos pós-AVE (40) e um grupo sem patologia (40). Os participantes foram submetidos à aplicação das escalas de Berg, Medida de Independência Funcional e Escala de Desempenho Físico Fugl Meyer e a TIS de modo a avaliar as propriedades psicométricas desta. As avaliações foram realizadas por duas fisioterapeutas experientes e o re-teste foi realizado após 48 horas. Os dados foram registados e trabalhados com o programa informático SPSS 21.0. Resultados: Relativamente aos valores obtidos, verificou-se que, quanto à consistência interna da TIS estes apresentam-se de forma moderada a elevada (alfa Cronbach = 0,909). Quanto à fiabilidade inter-observadores, os itens com menor valor são os itens 1 e 4 (0,759 e 0,527, respetivamente) e os itens com valor de Kappa mais alto são os itens 5 e 6 (0,830 e 0,893, respetivamente). Relativamente à validade de critério, verificou-se que não houve correlação entre a escala de Desempenho Físico Fugl-Meyer, a escala de Equilibrio de Berg e a Medida de Independência Funcional, ou seja, os valores obtidos r=0,166; r=0,017; r= -0,002, respetivamente. Quanto à validade de construção, constatou-se que o valor da mediana é mais elevado nos itens 1 a 5, logo sugere que haja diferenças entre o grupo de indivíduos pós-AVE e o grupo de indivíduos saudáveis (p<0,001). Entre os outros dois itens (6 e 7) não foram encontradas diferenças nas respostas nos dois grupos, sendo o valor de p > 0,001. Conclusão: Os resultados obtidos neste estudo sugerem que a versão portuguesa da TIS apresenta bons níveis de fiabilidade, consistência interna e também apresenta bons resultados no que refere à concordância inter-observadores.

Using data mining techniques to support breast cancer diagnosis

More than ever, there is an increase of the number of decision support methods and computer aided diagnostic systems applied to various areas of medicine. In breast cancer research, many works have been done in order to reduce false-positives when used as a double reading method. In this study, we aimed to present a set of data mining techniques that were applied to approach a decision support system in the area of breast cancer diagnosis. This method is geared to assist clinical practice in identifying mammographic findings such as microcalcifications, masses and even normal tissues, in order to avoid misdiagnosis. In this work a reliable database was used, with 410 images from about 115 patients, containing previous reviews performed by radiologists as microcalcifications, masses and also normal tissue findings. Throughout this work, two feature extraction techniques were used: the gray level co-occurrence matrix and the gray level run length matrix. For classification purposes, we considered various scenarios according to different distinct patterns of injuries and several classifiers in order to distinguish the best performance in each case described. The many classifiers used were Naïve Bayes, Support Vector Machines, k-nearest Neighbors and Decision Trees (J48 and Random Forests). The results in distinguishing mammographic findings revealed great percentages of PPV and very good accuracy values. Furthermore, it also presented other related results of classification of breast density and BI-RADS® scale. The best predictive method found for all tested groups was the Random Forest classifier, and the best performance has been achieved through the distinction of microcalcifications. The conclusions based on the several tested scenarios represent a new perspective in breast cancer diagnosis using data mining techniques.

Data Extraction Tool to Analyse, Transform and Store Real Data from Electricity Markets

The study of electricity markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring process produced. Currently, lots of information concerning electricity markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge to define realistic scenarios, which are essential for understanding and forecast electricity markets behavior. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of electricity markets and of the behaviour of the involved entities. In this paper an adaptable tool capable of downloading, parsing and storing data from market operators’ websites is presented, assuring constant updating and reliability of the stored data.

An automatic tool to Extract, Transform and Load data from real electricity markets

The study of Electricity Markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring produced. Currently, lots of information concerning Electricity Markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge, to define realistic scenarios, essential for understanding and forecast Electricity Markets behaviour. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of Electricity Markets and the behaviour of the involved entities. In this paper we present an adaptable tool capable of downloading, parsing and storing data from market operators’ websites, assuring actualization and reliability of stored data.

Constructing and validating a scale of employee satisfaction with HRM practices in the healthcare context

The concept of HRM perceptions is a growing interest in the literature, as one of the antecedents of HRM outcomes. Regardless, not only the cognitive aspect of perception is interesting in this field (what you think) but also the affective perspective is of interest (how you feel about it). In this study we propose a scale for assessing satisfaction with the perceptions of the HRM practices. A 24 item Likert-type scale was developed considering literature review, to assess subjects’ satisfaction with Human Resources Practices in a healthcare setting. Talked reflections were held and a survey encompassing all workers from a Hospital was conducted later, with a sample of 922 subjects. Exploratory and Confirmatory Factor Analysis were performed; reliability was tested using Cronbach’s alpha. The scale presents good psychometric properties with alpha values that range from .71 to .91. Exploratory and Confirmatory Factor Analysis demonstrated that the scale presents a very good fit with CFI= 0.94, AGFI= 0.88, and RMSEA= 0.07. The present study represents a first approach in the usage of this scale and despite having a large sample, respondents originate from a single institution. This study presents a pertinent scale towards measuring a seldom explored construct of the worker-organization relationship. The scale is parsimonious and results are promising. There seems to be very little research on how subjects feel about the HRM practices. This construct, very much in line with more recent studies concerning worker perceptions can be especially interesting in the context of the worker-organization relationship.

Cultural Intelligence Scale: Validation in a Multicultural Setting of Erasmus Mundus Students and Alumni

Purpose: This work aims at further developing and testing the psychometric properties of the Cultural Intelligence Scale (Ang & Van Dyne, 2006) in an Erasmus Mundus Students and Alumni Population, including reliability. Design Methodology: The study included 626 participants from 109 different countries that emcompasses 6 continents. Exploratory and Confirmatory Factor Analysis procedures were carried out in order to test the scale in a multicultural scale of Erasmus Mundus Students. Reliability was assessed using Cronbach Alpha. Results: The scale presents excellent psychometric properties with alpha values that range from .84 to .90. Exploratory and Confirmatory Factor Analyses demonstrated that the original model of the scale presents an exceptionally good fit. Limitations: The present study was conducted using a convenience sample and online questionnaires that limit its conclusions when we consider the globality of the Erasmus Mundus Students. Research/Practical Implications: This study presents evidence that Ang and Van Dyne’s scale is an adequate measure instrument to assess intercultural intelligence in a multicultural setting of students and alumni. Originality/Value: Multicultural samples and studies are becoming more and more present and relevant; the study of intercultural competences and habilities is becoming increasingly important, and in this task, solid psychometric instruments are of paramount importance. This study presents evidence that Ang and Van Dyne’s (2006) scale is a fairly recent and parsimonious instrument with excellent psychometric properties properties.

XDense: A Dense Grid Sensor Network for Distributed Feature Extraction

XXXIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC 2015). 15 to 19, May, 2015, III Workshop de Comunicação em Sistemas Embarcados Críticos. Vitória, Brasil.