O Balanced Scorecard como instrumento de gestão estratégica: sua implementação numa empresa de engenharia e construção

Mestrado em Contabilidade e Gestão das Instituições Financeiras

Host-symbiont interactions in the deep-sea vent mussel Bathymodiolus azoricus : a molecular approach

Tese de Doutoramento, Ciências do Mar, especialidade de Biologia Marinha, 19 de Dezembro de 2015, Universidade dos Açores.

Reconstruir as fronteiras do mercado através de uma estratégia híbrida sustentável

Mestrado em Gestão e Empreendedorismo

Gestão de projectos no âmbito da construção sustentável

A indústria da construção, nomeadamente no sector da edificação, baseia-se essencialmente em métodos de construção tradicional. Esta indústria é caracterizada pelo consumo excessivo de matérias-primas, de recursos energéticos não renováveis e pela elevada produção de resíduos. Esta realidade é de todo incompatível com os desígnios do desenvolvimento sustentável, nos quais se procura a conveniência harmoniosa entre as dimensões ambiental, social e económica. O desafio da sustentabilidade, colocado à actividade da construção, tem motivado abordagens distintas, não só por parte das várias especialidades da engenharia, como também da arquitectura. É nesta perspectiva, que o presente modelo pretende ser um contributo para uma abordagem inovadora, introduzindo linhas de intervenção e de orientação, para apoiar e estimular o desenvolvimento de soluções sustentáveis em edifícios habitacionais, em qualquer fase do ciclo de evolução de um projecto e das várias especialidades do mesmo. Assim, no sentido de optimizar os recursos envolvidos no projecto são expostas estratégias de intervenção, com os seguintes objectivos: optimização do potencial do local, preservação da identidade regional e cultural, minimização do consumo de energia, utilização de materiais e produtos de baixo impacto ambiental, redução do consumo de água, redução da produção de emissões, resíduos e outros poluentes, adequada qualidade do ambiente interior e optimização das fases de operação e manutenção. A ferramenta apresentada surge como um instrumento facilitador para a equipa de projectistas, e que se esta adaptada para o desenvolvimento de projectos de edifícios de habitação, dada a génese dos métodos utilizados. As soluções de sustentabilidade apresentadas neste manual emanam dos sistemas de certificação LíderA, LEED, BREEAM e SBToolpt. O modelo encontra-se estruturado, no que às fases de projecto diz respeito, de acordo com os requisitos expressos na Portaria 701-H/2008 de 29 de Julho, tendo sido igualmente seguido o descrito para os respectivos intervenientes.

Fuzzy Monte Carlo model for transmission power systems reliability based decision making

This thesis presents the Fuzzy Monte Carlo Model for Transmission Power Systems Reliability based studies (FMC-TRel) methodology, which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states. This is followed by a remedial action algorithm, based on Optimal Power Flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. For the system states that cause load curtailment, an optimization approach is applied to reduce the probability of occurrence of these states while minimizing the costs to achieve that reduction. This methodology is of most importance for supporting the transmission system operator decision making, namely in the identification of critical components and in the planning of future investments in the transmission power system. A case study based on Reliability Test System (RTS) 1996 IEEE 24 Bus is presented to illustrate with detail the application of the proposed methodology.

Capillary bridging and long-range attractive forces in a mean-field approach

When a mixture is confined, one of the phases can condense out. This condensate, which is otherwise metastable in the bulk, is stabilized by the presence of surfaces. In a sphere-plane geometry, routinely used in atomic force microscope and surface force apparatus, it, can form a bridge connecting the surfaces. The pressure drop in the bridge gives rise to additional long-range attractive forces between them. By minimizing the free energy of a binary mixture we obtain the force-distance curves as well as the structural phase diagram of the configuration with the bridge. Numerical results predict a discontinuous transition between the states with and without the bridge and linear force-distance curves with hysteresis. We also show that similar phenomenon can be observed in a number of different systems, e.g., liquid crystals and polymer mixtures. (C). 2004 American Institute of Physics.

Simulation and theory of hybrid aligned liquid crystal films

We present a study of the effects of nanoconfinement on a system of hard Gaussian overlap particles interacting with planar substrates through the hard-needle-wall potential, extending earlier work by two of us [D. J. Cleaver and P. I. C. Teixeira, Chem. Phys. Lett. 338, 1 (2001)]. Here, we consider the case of hybrid films, where one of the substrates induces strongly homeotropic anchoring, while the other favors either weakly homeotropic or planar anchoring. These systems are investigated using both Monte Carlo simulation and density-functional theory, the latter implemented at the level of Onsager's second-virial approximation with Parsons-Lee rescaling. The orientational structure is found to change either continuously or discontinuously depending on substrate separation, in agreement with earlier predictions by others. The theory is seen to perform well in spite of its simplicity, predicting the positional and orientational structure seen in simulations even for small particle elongations.

Neural-network approach to modeling liquid crystals in complex confinement

Finding the structure of a confined liquid crystal is a difficult task since both the density and order parameter profiles are nonuniform. Starting from a microscopic model and density-functional theory, one has to either (i) solve a nonlinear, integral Euler-Lagrange equation, or (ii) perform a direct multidimensional free energy minimization. The traditional implementations of both approaches are computationally expensive and plagued with convergence problems. Here, as an alternative, we introduce an unsupervised variant of the multilayer perceptron (MLP) artificial neural network for minimizing the free energy of a fluid of hard nonspherical particles confined between planar substrates of variable penetrability. We then test our algorithm by comparing its results for the structure (density-orientation profiles) and equilibrium free energy with those obtained by standard iterative solution of the Euler-Lagrange equations and with Monte Carlo simulation results. Very good agreement is found and the MLP method proves competitively fast, flexible, and refinable. Furthermore, it can be readily generalized to the richer experimental patterned-substrate geometries that are now experimentally realizable but very problematic to conventional theoretical treatments.

A sustainable approach to the reuse of student - centered learning scenarios

Proceedings of EULEARN09 - Intenational Conference and New Learning Technologies, Barcelona, Spain, 6-8 July

Dominant set approach to ECG biometrics

Electrocardiographic (ECG) signals are emerging as a recent trend in the field of biometrics. In this paper, we propose a novel ECG biometric system that combines clustering and classification methodologies. Our approach is based on dominant-set clustering, and provides a framework for outlier removal and template selection. It enhances the typical workflows, by making them better suited to new ECG acquisition paradigms that use fingers or hand palms, which lead to signals with lower signal to noise ratio, and more prone to noise artifacts. Preliminary results show the potential of the approach, helping to further validate the highly usable setups and ECG signals as a complementary biometric modality.

A waste management school approach towards sustainability

Education towards sustainability in Chemical Engineering (CEng) gave birth to awaste management program (WMP) at Instituto Superior de Engenharia do Porto, in Portugal. It involves students, teachers, and laboratory technicians. It aims to enhance the conscientiousness of the decision-maker next generation for saving resources, managing wastes, and at same time to develop applied chemistry understanding. This program was implemented in 1999 and is responsible for management and fate of all inorganic wastewater providing from training experimental activities of the CEng degree. An immediate reduction of wastes at their source was first defined. Wastes were collected separately and were reused, recycled or chemically treated, and after analytically controlled as legally imposed. Solids formed after this program were recycled, purified or followed suitable elimination. Global results point out environmental, pedagogical, and social benefits. Active participants are aware, in agreement, and publicly committed to the WMP.

Feature selection for clustering categorical data with an embedded modelling approach

Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

Categorical data clustering using a minimum message length criterion

Research on cluster analysis for categorical data continues to develop, new clustering algorithms being proposed. However, in this context, the determination of the number of clusters is rarely addressed. We propose a new approach in which clustering and the estimation of the number of clusters is done simultaneously for categorical data. We assume that the data originate from a finite mixture of multinomial distributions and use a minimum message length criterion (MML) to select the number of clusters (Wallace and Bolton, 1986). For this purpose, we implement an EM-type algorithm (Silvestre et al., 2008) based on the (Figueiredo and Jain, 2002) approach. The novelty of the approach rests on the integration of the model estimation and selection of the number of clusters in a single algorithm, rather than selecting this number based on a set of pre-estimated candidate models. The performance of our approach is compared with the use of Bayesian Information Criterion (BIC) (Schwarz, 1978) and Integrated Completed Likelihood (ICL) (Biernacki et al., 2000) using synthetic data. The obtained results illustrate the capacity of the proposed algorithm to attain the true number of cluster while outperforming BIC and ICL since it is faster, which is especially relevant when dealing with large data sets.

A new MILP based approach for unit commitment in power production planning

This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances, including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.

CYCLOTech - an innovative approach for the reliable production of 99mTc - technetium

CYCLOTech is a high-tech Project, related with an innovative method for direct production of a radioactive pharmaceutical, used in excess of 85% of 35 Million Nuclear Medicine procedures done yearly, worldwide, representing globally more than 3 Billion Euros. The CYCLOTech team has developed an innovative proprietary methodology based on the use of Cyclotron Centers, formally identified as the Clients (actually, there are around 450 of this Centers in function worldwide), to directly produce and deliver the radiopharmaceutical to the final users, at the Hospitals and other Health Institutions (estimating at around 25.000, worldwide). The investment still need to finish Research and Technological Development (RTD), Industrial, Regulatory and Intellectual Property Rights (IPR) issues and allow the introduction in the Market is 4,35 M€, with a Payback of 3 years, with an Investment Return Rate (IRR) of 81,7% and a Net Present Value (NPV) of 60.620.525€ (in 2020).