Social network analysis applied to knowledge creation and transfer in the portuguese agricultural R&D field: an exploratory study

Paper presented at the 9th European Conference on Knowledge Management, Southampton Solent University, Southampton, UK, 4-5 Sep. 2008. URL: http://academic-conferences.org/eckm/eckm2008/eckm08-home.htm

Acqusition and data analysis of the eco-efficiency for the establishment of indicators parameters for industrial environmental sustainability

The industrial activity is inevitably associated with a certain degradation of the environmental quality, because is not possible to guarantee that a manufacturing process can be totally innocuous. The eco-efficiency concept is globally accepted as a philosophy of entreprise management, that encourages the companies to become more competitive, innovative and environmentally responsible by promoting the link between its companies objectives for excellence and its objectives of environmental excellence issues. This link imposes the creation of an organizational methodology where the performance of the company is concordant with the sustainable development. The main propose of this project is to apply the concept of eco-efficiency to the particular case of the metallurgical and metal workshop industries through the development of the particular indicators needed and to produce a manual of procedures for implementation of the accurate solution.

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.

Multy-dimensional composition by objectives in aspect-oriented requirements analysis

Thesis submitted to Faculdade de Ciências e Tecnologia of Universidade Nova de Lisboa in partial fulfilment of the requirements for the degree of Master in Computer Science

CDIO and the European Project Semester: a match for capstone projects?

The CDIO Initiative is an open innovative educational framework for engineering graduation degrees set in the context of Conceiving – Designing – Implementing – Operating real-world systems and products, which is embraced by a network of worldwide universities, the CDIO collaborators. A CDIO compliant engineering degree programme typically includes a capstone module on the final semester. Its purpose is to expose students to problems of a greater dimension and complexity than those faced throughout the degree programme as well as to put them in contact with the so-called real world, in opposition to the academic world. However, even in the CDIO context, there are barriers that separate engineering capstone students from the real world context of an engineering professional: (i) limited interaction with experts from diverse scientific areas; (ii) reduced cultural and scientific diversity within the teams; and (iii) lack of a project supportive framework to foster the complementary technical and non-technical skills required in an engineering professional. To address these shortcomings, we propose the adoption of the European Project Semester (EPS) framework, a one semester student centred international capstone programme offered by a group of European engineering schools (the EPS Providers) as part of their student exchange programme portfolio. The EPS package is organised around a central module – the EPS project – and a set of complementary supportive modules. Project proposals refer to open multidisciplinary real world problems and supervision becomes coaching. The students are organised in teams, grouping individuals from diverse academic backgrounds and nationalities, and each team is fully responsible for conducting its project. EPS complies with the CDIO directives on Design-Implement experiences and provides an integrated framework for undertaking capstone projects, which is focussed on multicultural and multidisciplinary teamwork, problem-solving, communication, creativity, leadership, entrepreneurship, ethical reasoning and global contextual analysis. As a result, we recommend the adoption of the EPS within CDIO capstone modules for the benefit of engineering students.

Education through theater equal opportunity project being a girl being a boy

Dramatic narratives give emphasis to the process of storytelling of daily life. The script or story is constructed as a dialogue between actors. The words acquire a signification through a dynamic process of communication, where narratives are written not with a pencil but with the body, not written with the mind but with anima. In this paper we present a phenomenological analysis of an experience conducted in a middle grade school of Italy with the proposal to analyze how boys and girls see themselves and the opposite gender and how they perceive the equal opportunity between female and masculine roles.

Development of Biomimetic Robots in the EPS Engineering Programme Capstone Project

This paper proposes the development of biologically inspired robots as the capstone project of the European Project Semester (EPS) framework. EPS is a one semester student centred international programme offered by a group of European engineering schools (EPS Providers) as part of their student exchange programme portfolio. EPS is organized around a central module (the EPS project) and a set of complementary supportive modules. Project proposals refer to open multidisciplinary real world problems. Its purpose is to expose students to problems of a greater dimension and complexity than those faced throughout the degree programme as well as to put them in contact with the socalled real world, in opposition to the academic world. Students are organized in teams, grouping individuals from diverse academic backgrounds and nationalities, and each team is fully responsible for conducting its project. EPS provides an integrated framework for undertaking capstone projects, which is focused on multicultural and multidisciplinary teamwork, communication, problem-solving, creativity, leadership, entrepreneurship, ethical reasoning and global contextual analysis. The design and development of biologically inspired robots allows the students to fulfil the previously described requirements and objectives and, as a result, we recommend the adoption of these projects within the EPS project capstone module for the benefit of engineering students.

Methodologies for the WCET Analysis of Parallel Applications on Many-core Architectures

Euromicro Conference on Digital System Design (DSD 2015), Funchal, Portugal.

Territorial Strategic Planning as a support instrument for Regional and Local Development : a comparative analysis between Lisbon and Barcelona metropolitan areas - a first approach

Trabalho de Projecto apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Metropolização, Planeamento Estratégico e Sustentabilidade.

Learning networks and moodle use in online courses: a social network analysis study

Dissertação para obtenção do Grau de Doutor em Ciências da Educação Especialidade em Tecnologias, Redes e Multimédia na Educação e Formação

Studying the impact of co-authorship with external researchers:the case of research community in Portugal using social network analysis.

Project work presented as a partial requirement to obtain a Master Degree in Information Management

Principal component analysis of the yield curve

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Comparative analysis: Public and private school management systems

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics

Analysis of benefits of the process of certification on international standars: ISO 9001-2008 for Mapfre Assistencia Portugal

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

Economic rents, institutions and growth: International aid and natural resources: A comparative analysis

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Economics from the NOVA – School of Business and Economics