NoC contention analysis using a branch-and-prune algorithm

“Many-core” systems based on a Network-on-Chip (NoC) architecture offer various opportunities in terms of performance and computing capabilities, but at the same time they pose many challenges for the deployment of real-time systems, which must fulfill specific timing requirements at runtime. It is therefore essential to identify, at design time, the parameters that have an impact on the execution time of the tasks deployed on these systems and the upper bounds on the other key parameters. The focus of this work is to determine an upper bound on the traversal time of a packet when it is transmitted over the NoC infrastructure. Towards this aim, we first identify and explore some limitations in the existing recursive-calculus-based approaches to compute the Worst-Case Traversal Time (WCTT) of a packet. Then, we extend the existing model by integrating the characteristics of the tasks that generate the packets. For this extended model, we propose an algorithm called “Branch and Prune” (BP). Our proposed method provides tighter and safe estimates than the existing recursive-calculus-based approaches. Finally, we introduce a more general approach, namely “Branch, Prune and Collapse” (BPC) which offers a configurable parameter that provides a flexible trade-off between the computational complexity and the tightness of the computed estimate. The recursive-calculus methods and BP present two special cases of BPC when a trade-off parameter is 1 or ∞, respectively. Through simulations, we analyze this trade-off, reason about the implications of certain choices, and also provide some case studies to observe the impact of task parameters on the WCTT estimates.

GLODS: Global and Local Optimization using Direct Search

Locating and identifying points as global minimizers is, in general, a hard and time-consuming task. Difficulties increase in the impossibility of using the derivatives of the functions defining the problem. In this work, we propose a new class of methods suited for global derivative-free constrained optimization. Using direct search of directional type, the algorithm alternates between a search step, where potentially good regions are located, and a poll step where the previously located promising regions are explored. This exploitation is made through the launching of several instances of directional direct searches, one in each of the regions of interest. Differently from a simple multistart strategy, direct searches will merge when sufficiently close. The goal is to end with as many direct searches as the number of local minimizers, which would easily allow locating the global extreme value. We describe the algorithmic structure considered, present the corresponding convergence analysis and report numerical results, showing that the proposed method is competitive with currently commonly used global derivative-free optimization solvers.

Analysis of Forest Fires by means of Pseudo Phase Plane and Multidimensional Scaling Methods

Forest fires dynamics is often characterized by the absence of a characteristic length-scale, long range correlations in space and time, and long memory, which are features also associated with fractional order systems. In this paper a public domain forest fires catalogue, containing information of events for Portugal, covering the period from 1980 up to 2012, is tackled. The events are modelled as time series of Dirac impulses with amplitude proportional to the burnt area. The time series are viewed as the system output and are interpreted as a manifestation of the system dynamics. In the first phase we use the pseudo phase plane (PPP) technique to describe forest fires dynamics. In the second phase we use multidimensional scaling (MDS) visualization tools. The PPP allows the representation of forest fires dynamics in two-dimensional space, by taking time series representative of the phenomena. The MDS approach generates maps where objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to better understand forest fires behaviour.

Unmixing hyperspectral data: independent and dependent component analysis

The development of high spatial resolution airborne and spaceborne sensors has improved the capability of ground-based data collection in the fields of agriculture, geography, geology, mineral identification, detection [2, 3], and classification [4–8]. The signal read by the sensor from a given spatial element of resolution and at a given spectral band is a mixing of components originated by the constituent substances, termed endmembers, located at that element of resolution. This chapter addresses hyperspectral unmixing, which is the decomposition of the pixel spectra into a collection of constituent spectra, or spectral signatures, and their corresponding fractional abundances indicating the proportion of each endmember present in the pixel [9, 10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. The linear mixing model holds when the mixing scale is macroscopic [13]. The nonlinear model holds when the mixing scale is microscopic (i.e., intimate mixtures) [14, 15]. The linear model assumes negligible interaction among distinct endmembers [16, 17]. The nonlinear model assumes that incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [18]. Under the linear mixing model and assuming that the number of endmembers and their spectral signatures are known, hyperspectral unmixing is a linear problem, which can be addressed, for example, under the maximum likelihood setup [19], the constrained least-squares approach [20], the spectral signature matching [21], the spectral angle mapper [22], and the subspace projection methods [20, 23, 24]. Orthogonal subspace projection [23] reduces the data dimensionality, suppresses undesired spectral signatures, and detects the presence of a spectral signature of interest. The basic concept is to project each pixel onto a subspace that is orthogonal to the undesired signatures. As shown in Settle [19], the orthogonal subspace projection technique is equivalent to the maximum likelihood estimator. This projection technique was extended by three unconstrained least-squares approaches [24] (signature space orthogonal projection, oblique subspace projection, target signature space orthogonal projection). Other works using maximum a posteriori probability (MAP) framework [25] and projection pursuit [26, 27] have also been applied to hyperspectral data. In most cases the number of endmembers and their signatures are not known. Independent component analysis (ICA) is an unsupervised source separation process that has been applied with success to blind source separation, to feature extraction, and to unsupervised recognition [28, 29]. ICA consists in finding a linear decomposition of observed data yielding statistically independent components. Given that hyperspectral data are, in given circumstances, linear mixtures, ICA comes to mind as a possible tool to unmix this class of data. In fact, the application of ICA to hyperspectral data has been proposed in reference 30, where endmember signatures are treated as sources and the mixing matrix is composed by the abundance fractions, and in references 9, 25, and 31–38, where sources are the abundance fractions of each endmember. In the first approach, we face two problems: (1) The number of samples are limited to the number of channels and (2) the process of pixel selection, playing the role of mixed sources, is not straightforward. In the second approach, ICA is based on the assumption of mutually independent sources, which is not the case of hyperspectral data, since the sum of the abundance fractions is constant, implying dependence among abundances. This dependence compromises ICA applicability to hyperspectral images. In addition, hyperspectral data are immersed in noise, which degrades the ICA performance. IFA [39] was introduced as a method for recovering independent hidden sources from their observed noisy mixtures. IFA implements two steps. First, source densities and noise covariance are estimated from the observed data by maximum likelihood. Second, sources are reconstructed by an optimal nonlinear estimator. Although IFA is a well-suited technique to unmix independent sources under noisy observations, the dependence among abundance fractions in hyperspectral imagery compromises, as in the ICA case, the IFA performance. Considering the linear mixing model, hyperspectral observations are in a simplex whose vertices correspond to the endmembers. Several approaches [40–43] have exploited this geometric feature of hyperspectral mixtures [42]. Minimum volume transform (MVT) algorithm [43] determines the simplex of minimum volume containing the data. The MVT-type approaches are complex from the computational point of view. Usually, these algorithms first find the convex hull defined by the observed data and then fit a minimum volume simplex to it. Aiming at a lower computational complexity, some algorithms such as the vertex component analysis (VCA) [44], the pixel purity index (PPI) [42], and the N-FINDR [45] still find the minimum volume simplex containing the data cloud, but they assume the presence in the data of at least one pure pixel of each endmember. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. Hyperspectral sensors collects spatial images over many narrow contiguous bands, yielding large amounts of data. For this reason, very often, the processing of hyperspectral data, included unmixing, is preceded by a dimensionality reduction step to reduce computational complexity and to improve the signal-to-noise ratio (SNR). Principal component analysis (PCA) [46], maximum noise fraction (MNF) [47], and singular value decomposition (SVD) [48] are three well-known projection techniques widely used in remote sensing in general and in unmixing in particular. The newly introduced method [49] exploits the structure of hyperspectral mixtures, namely the fact that spectral vectors are nonnegative. The computational complexity associated with these techniques is an obstacle to real-time implementations. To overcome this problem, band selection [50] and non-statistical [51] algorithms have been introduced. This chapter addresses hyperspectral data source dependence and its impact on ICA and IFA performances. The study consider simulated and real data and is based on mutual information minimization. Hyperspectral observations are described by a generative model. This model takes into account the degradation mechanisms normally found in hyperspectral applications—namely, signature variability [52–54], abundance constraints, topography modulation, and system noise. The computation of mutual information is based on fitting mixtures of Gaussians (MOG) to data. The MOG parameters (number of components, means, covariances, and weights) are inferred using the minimum description length (MDL) based algorithm [55]. We study the behavior of the mutual information as a function of the unmixing matrix. The conclusion is that the unmixing matrix minimizing the mutual information might be very far from the true one. Nevertheless, some abundance fractions might be well separated, mainly in the presence of strong signature variability, a large number of endmembers, and high SNR. We end this chapter by sketching a new methodology to blindly unmix hyperspectral data, where abundance fractions are modeled as a mixture of Dirichlet sources. This model enforces positivity and constant sum sources (full additivity) constraints. The mixing matrix is inferred by an expectation-maximization (EM)-type algorithm. This approach is in the vein of references 39 and 56, replacing independent sources represented by MOG with mixture of Dirichlet sources. Compared with the geometric-based approaches, the advantage of this model is that there is no need to have pure pixels in the observations. The chapter is organized as follows. Section 6.2 presents a spectral radiance model and formulates the spectral unmixing as a linear problem accounting for abundance constraints, signature variability, topography modulation, and system noise. Section 6.3 presents a brief resume of ICA and IFA algorithms. Section 6.4 illustrates the performance of IFA and of some well-known ICA algorithms with experimental data. Section 6.5 studies the ICA and IFA limitations in unmixing hyperspectral data. Section 6.6 presents results of ICA based on real data. Section 6.7 describes the new blind unmixing scheme and some illustrative examples. Section 6.8 concludes with some remarks.

The impact of an online mathematics education project (MATACTIVA) on higher education students

The Online Mathematics Education Project (MatActiva) is an exciting new initiative which aims to support and enhance mathematics education. The project is led by the Institute of Accounting and Administration of Porto (ISCAP), part of the Polytechnic Institute of Porto (IPP). It provides innovative resources and carefully constructed materials around themes such as Elementary Mathematics, Calculus, Algebra, Statistics and Financial Mathematics to help support and inspire students and teachers of mathematics. The goal is to increase mathematical understanding, confidence and enjoyment, enrich the mathematical experience of each person, and promote creative and imaginative approaches to mathematics. Furthermore the project can be used to deliver engaging and effective mathematics instruction through the flipped classroom model. This paper also presents the findings of a large survey, whose propose was to study the student’s reaction to the project.

Matemática 100 stress: um projeto aberto no IPP

A Era Tecnológica em que nos vemos inseridos, cujos avanços acontecem a uma velocidade vertiginosa exige, por parte das Instituições de Ensino Superior (IES) uma atitude proactiva no sentido de utilização dos muitos recursos disponíveis. Por outro lado, os elementos próprios da sociedade da informação – flexibilidade, formação ao longo da vida, acessibilidade à informação, mobilidade, entre muito outros – atuam como fortes impulsionadores externos para que as IES procurem e analisem novas modalidades formativas. Perante a mobilidade crescente, que se tem revelado massiva, a aprendizagem tende a ser cada vez mais individualizada, visual e prática. A conjugação de várias formas/tipologias de transmissão de conhecimento, de métodos didáticos e mesmo de ambientes e situações de aprendizagem induzem uma melhor adaptação do estudante, que poderá procurar aqueles que melhor vão ao encontro das suas expetativas, isto é, favorecem um processo de ensino-aprendizagem eficiente na perspetiva da forma de aprender de cada um. A definição de políticas estratégicas relacionadas com novas modalidades de ensino/formação tem sido uma preocupação constante na nossa instituição, nomeadamente no domínio do ensino à distância, seja ele e-Learning, b-Learning ou, mais recentemente, “open-Learning”, onde se inserem os MOOC – Massive Open Online Courses (não esquecendo a vertente m-Learning), de acordo com as várias tendências europeias (OECD, 2007) (Comissão Europeia, 2014) e com os objetivos da “Europa 2020”. Neste sentido surge o Projeto Matemática 100 STRESS, integrado no projeto e-IPP | Unidade de e-Learning do Politécnico do Porto que criou a sua plataforma MOOC, abrindo em junho de 2014 o seu primeiro curso – Probabilidades e Combinatória. Pretendemos dar a conhecer este Projeto, e em particular este curso, que envolveu vários docentes de diferentes unidades orgânicas do IPP.

The Persistence of Memory

This paper analyzes several natural and man-made complex phenomena in the perspective of dynamical systems. Such phenomena are often characterized by the absence of a characteristic length-scale, long range correlations and persistent memory, which are features also associated to fractional order systems. For each system, the output, interpreted as a manifestation of the system dynamics, is analyzed by means of the Fourier transform. The amplitude spectrum is approximated by a power law function and the parameters are interpreted as an underlying signature of the system dynamics. The complex systems under analysis are then compared in a global perspective in order to unveil and visualize hidden relationships among them.

Entropy Analysis of Industrial Accident Data Series

Complex industrial plants exhibit multiple interactions among smaller parts and with human operators. Failure in one part can propagate across subsystem boundaries causing a serious disaster. This paper analyzes the industrial accident data series in the perspective of dynamical systems. First, we process real world data and show that the statistics of the number of fatalities reveal features that are well described by power law (PL) distributions. For early years, the data reveal double PL behavior, while, for more recent time periods, a single PL fits better into the experimental data. Second, we analyze the entropy of the data series statistics over time. Third, we use the Kullback–Leibler divergence to compare the empirical data and multidimensional scaling (MDS) techniques for data analysis and visualization. Entropy-based analysis is adopted to assess complexity, having the advantage of yielding a single parameter to express relationships between the data. The classical and the generalized (fractional) entropy and Kullback–Leibler divergence are used. The generalized measures allow a clear identification of patterns embedded in the data.

Influência do ciclo menstrual na fracção exalada de óxido nítrico

RESUMO:A determinação da fracção exalada de óxido nítrico (FENO) é amplamente utilizada como um biomarcador da inflamação eosinofílica das vias aéreas. Alguns estudos sugerem que a produção de óxido nítrico (NO) é influenciada pelas variações cíclicas hormonais na mulher,porém os dados não são consensuais. Deste modo, o objectivo do nosso estudo foi avaliar como varia a FENO ao longo do ciclo menstrual. Com esta finalidade, avaliamos um grupo de 20 voluntárias, em idade fértil, com ciclo menstrual regular, não fumadoras, que não utilizavam contraceptivos hormonais, nem suplementos alimentares e/ou medicamentosos e que não se encontravam grávidas, nem a amamentar. Todas referiram não ter conhecimento de qualquer patologia que afecte a FENO. A existência de atopia foi controlada através de testes cutâneos por prick, tendo-se excluído as participantes que apresentaram testes positivos. Realizamos quatro visitas de estudo, com base na periodicidade do ciclo de cada participante, nas quais, efectuamos a determinação da FENO, a quantificação dos níveis plasmáticos de óxido nítrico e nitratos (NO/NO3 -) e o doseamento hormonal de 17 -estradiol e progesterona. As avaliações realizaram-se no período da manhã, em jejum absoluto, tendo respeitado uma dieta pobre em nitratos no dia anterior e abstido da prática de exercício vigoroso uma hora antes da avaliação. Com este trabalho, verificamos um aumento significativo da FENO na fase secretora (17.97 ppb ± 5.8) comparativamente com a fase menstrual e proliferativa (16.48 ppb ± 3.6 e 15.95 ppb ±2.8, respectivamente). Não observamos variações significativas dos níveis plasmáticos de NO/NO3 - ao longo do ciclo. Constatamos uma correlação positiva entre a FENO e os níveis plasmáticos de NO/NO3 - durante a ovulação e verificamos que, para a nossa amostra, os níveis hormonais de estradiol e progesterona não são preditores do valor da FENO, nem dos níveis plasmáticos de NO/NO3-. Os resultados deste trabalho mostram uma variação da FENO ao longo do ciclo, ainda assim, mantendo-se os seus valores dentro do intervalo de referência, reforçando a fiabilidade deste biomarcador.--ABSTRACT:The determination of fractional exhaled nitric oxide (FENO) is widely used as a biomarker of eosinophilic airway inflammation. Some studies suggest that nitric oxide (NO) is influenced by cyclical hormonal changes in women, but those are not consensual. The aim of our study was to assess how FENO varies throughout the menstrual cycle. With this purpose, we studied a group of 20 volunteers within childbearing age, with regular menstrual cycle, non-smokers, who were not taking any medications including hormonal contraception and food supplements and who were not pregnant or breast-feeding. All participants reported not being aware of any condition that could affect the FENO. The presence of atopy was controlled by a skin prick test, having been excluded participants with positive test. We conducted four study visits, based on the periodicity of the cycle of each participant. In each visit, we made the determination of the FENO, the quantification of plasmatic levels of nitric oxide and nitrates (NO/NO3 -) and the blood levels of hormone estradiol-17 and progesterone. The evaluations occurred at morning, after overnight fasting. The participants were request to follow a low-nitrate diet in the previous day and refrained from vigorous exercise, for at least one hour before the visit We found a significant increase of FENO on secretory phase (17.97 ppb ± 5.8) compared with the menstrual and proliferative phase (16.48 ppb ± 3.6 and 15.95 ppb ± 2.8, espectively). No significant variations were found throughout the menstrual cycle in plasmatic levels of NO/NO3 -. We found a positive correlation between FENO and plasmatic levels of NO/NO3 - during ovulation. Finally, in our sample, the levels of oestradiol and progesterone are not predictors of FENO value nor of plasmatic levels of NO/NO3-. This study shows a variation of FENO over the menstrual cycle, nevertheless, the values remain within the reference range, reinforcing the reliability of this biomarker.

Utilidade do Doppler Tecidular na Predição de Eventos Arrítmicos em Adultos com Tetralogia de Fallot Corrigida

INTRODUCTION: Adults with repaired tetralogy of Fallot (TOF) may be at risk for progressive right ventricular (RV) dilatation and dysfunction, which is commonly associated with arrhythmic events. In frequently volume-overloaded patients with congenital heart disease, tissue Doppler imaging (TDI) is particularly useful for assessing RV function. However, it is not known whether RV TDI can predict outcome in this population. OBJECTIVE: To evaluate whether RV TDI parameters are associated with supraventricular arrhythmic events in adults with repaired TOF. METHODS: We studied 40 consecutive patients with repaired TOF (mean age 35 +/- 11 years, 62% male) referred for routine echocardiographic exam between 2007 and 2008. The following echocardiographic measurements were obtained: left ventricular (LV) ejection fraction, LV end-systolic volume, LV end-diastolic volume, RV fractional area change, RV end-systolic area, RV end-diastolic area, left and right atrial volumes, mitral E and A velocities, RV myocardial performance index (Tei index), tricuspid annular plane systolic excursion (TAPSE), myocardial isovolumic acceleration (IVA), pulmonary regurgitation color flow area, TDI basal lateral, septal and RV lateral peak diastolic and systolic annular velocities (E' 1, A' 1, S' 1, E' s, A' s, S' s, E' rv, A' rv, S' rv), strain, strain rate and tissue tracking of the same segments. QRS duration on resting ECG, total duration of Bruce treadmill exercise stress test and presence of exercise-induced arrhythmias were also analyzed. The patients were subsequently divided into two groups: Group 1--12 patients with previous documented supraventricular arrhythmias (atrial tachycardia, fibrillation or flutter) and Group 2 (control group)--28 patients with no previous arrhythmic events. Univariate and multivariate analysis was used to assess the statistical association between the studied parameters and arrhythmic events. RESULTS: Patients with previous events were older (41 +/- 14 vs. 31 +/- 6 years, p = 0.005), had wider QRS (173 +/- 20 vs. 140 +/- 32 ms, p = 0.01) and lower maximum heart rate on treadmill stress testing (69 +/- 35 vs. 92 +/- 9%, p = 0.03). All patients were in NYHA class I or II. Clinical characteristics including age at corrective surgery, previous palliative surgery and residual defects did not differ significantly between the two groups. Left and right cardiac chamber dimensions and ventricular and valvular function as evaluated by conventional Doppler parameters were also not significantly different. Right ventricular strain and strain rate were similar between the groups. However, right ventricular myocardial TDI systolic (Sa: 5.4+2 vs. 8.5 +/- 3, p = 0.004) and diastolic indices and velocities (Ea, Aa, septal E/Ea, and RV free wall tissue tracking) were significantly reduced in patients with arrhythmias compared to the control group. Multivariate linear regression analysis identified RV early diastolic velocity as the sole variable independently associated with arrhythmic history (RV Ea: 4.5 +/- 1 vs. 6.7 +/- 2 cm/s, p = 0.01). A cut-off for RV Ea of < 6.1 cm/s identified patients in the arrhythmic group with 86% sensitivity and 59% specificity (AUC = 0.8). CONCLUSIONS: Our results suggest that TDI may detect RV dysfunction in patients with apparently normal function as assessed by conventional echocardiographic parameters. Reduction in RV early diastolic velocity appears to be an early abnormality and is associated with occurrence of arrhythmic events. TDI may be useful in risk stratification of patients with repaired tetralogy of Fallot.

New Concepts Towards the Synthesis of Digital Circuits Through Genetic Algorithms

This paper analyses the performance of a Genetic Algorithm using two new concepts, namely a static fitness function including a discontinuity measure and a fractional-order dynamic fitness function, for the synthesis of combinational logic circuits. In both cases, experiments reveal superior results in terms of speed and convergence to achieve a solution.

Simple Kinematic Design for Evading the Forced Oscillation of a Car-Wheel Suspension System

An adaptive control damping the forced vibration of a car while passing along a bumpy road is investigated. It is based on a simple kinematic description of the desired behavior of the damped system. A modified PID controller containing an approximation of Caputo’s fractional derivative suppresses the high-frequency components related to the bumps and dips, while the low frequency part of passing hills/valleys are strictly traced. Neither a complete dynamic model of the car nor ’a priori’ information on the surface of the road is needed. The adaptive control realizes this kinematic design in spite of the existence of dynamically coupled, excitable internal degrees of freedom. The method is investigated via Scicos-based simulation in the case of a paradigm. It was found that both adaptivity and fractional order derivatives are essential parts of the control that can keep the vibration of the load at bay without directly controlling its motion.

Analysis of Two Arms Working in Cooperation

This paper analyzes the performance of two cooperative robot manipulators. In order to capture the working performancewe formulated several performance indices that measure the manipulability, the effort reduction and the equilibrium between the two robots. In this perspective the proposed indices we determined the optimal values for the system parameters. Furthermore, it is studied the implementation of fractional-order algorithms in the position/force control of two cooperative robotic manipulators holding an object.

Challenges in the creation and development of a mathematics MOOC

The fast development of distance learning tools such as Open Educational Resources (OER) and Massive Open Online Courses (MOOC or MOOCs) are indicators of a shift in the way in which digital teaching and learning are understood. MOOC are a new style of online classes that allow any person with web access, anywhere, usually free of charge, to participate through video lectures, computer graded tests and discussion forums. They have been capturing the attention of many higher education institutions around the world. This paper will give us an overview of the “Introduction to Differential Calculus” a MOOC Project, created by an engaged volunteer team of Mathematics lecturers from four schools of the Polytechnic Institute of Oporto (IPP). The MOOC theories and their popularity are presented and complemented by a discussion of some MOOC definitions and their inherent advantages and disadvantages. It will also explore what MOOC mean for Mathematics education. The Project development is revealed by focusing on used MOOC structure, as well as the quite a lot of types of course materials produced. It ends with a presentation of a short discussion about problems and challenges met throughout the development of the project. It is also our goal to contribute for a change in the way teaching and learning Mathematics is seen and practiced nowadays, trying to make education more accessible to as many people as possible and increase our institution (IPP) recognition.

New Features to Look at Natural Phenomena

Proceeding of the 3rd International Conference on Fractional Systems and Signals, at Ghent, Belgium