Otimização estocástica para a exploração de centrais de concentração solar considerando incerteza e risco

Dissertação para obtenção do grau de Mestre em Engenharia Eletrotécnica

Optimal generation scheduling of wind-CSP systems in day-ahead electricity markets

This paper presents a coordination approach to maximize the total profit of wind power systems coordinated with concentrated solar power systems, having molten-salt thermal energy storage. Both systems are effectively handled by mixed-integer linear programming in the approach, allowing enhancement on the operational during non-insolation periods. Transmission grid constraints and technical operating constraints on both systems are modeled to enable a true management support for the integration of renewable energy sources in day-ahead electricity markets. A representative case study based on real systems is considered to demonstrate the effectiveness of the proposed approach. © IFIP International Federation for Information Processing 2015.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. 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. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

A supervised versus home-based program effects on liver transplanted familial amyloidotic polyneuropathy patients: walking, fatigue and quality of life

Purpose: To evaluate the effects of a six months exercise training program on walking capacity, fatigue and health related quality of life (HRQL). Relevance: Familial amyloidotic polyneuropathy disease (FAP) is an autossomic neurodegenerative disease, related with systemic deposition of amyloidal fibre mainly on peripheral nervous system and mainly produced in the liver. FAP often results in severe functional limitations. Liver transplantation is used as the only therapy so far, that stop the progression of some aspects of this disease. Transplantation requires aggressive medication which impairs muscle metabolism and associated to surgery process and previous possible functional impairments, could lead to serious deconditioning. Reports of fatigue are common feature in transplanted patients. The effect of supervised or home-based exercise training programs in FAP patients after a liver transplant (FAPTX) is currently unknown.

Effects of an exercise training program in physical condition after liver transplantation in familial amyloidotic polyneuropathy: a case report

Introduction: Familial amyloidotic polyneuropathy (FAP) is a neurodegenerative disease that leads to sensory and motor polyneuropathies as well as functional limitations. So far, liver transplantation is the only treatment for FAP because the mutated protein causing the disease is mainly produced in the liver. With the increasing survival of transplant recipients, functional and cardiovascular problems as consequences of immunosuppressant side effects are increasing associated with sedentary lifestyles and/or retransplantation status. We sought to analyze the impact of exercise training programs on 1 FAP patient’s course long-term after liver transplantation. Methodology. A FAP patient (female; 49 years of age; body mass index 18.8 kg/m2) underwent a liver transplantation 133 months before assessment. She was assessed for body composition, isometric quadriceps muscle strength, functional capacity, fatigue, and levels of physical activity before and after a 6-month period of combined exercise training. Results: After the exercise training program, almost all variables were improved, namely, total body skeletal muscle mass, proximal femoral bone mineral density, quadriceps strength, maximal oxygen consumption on 6 minutes walk test (6mwt) or VO2peak, total ventilation on 6mwt, and fatigue. The improvement in distance on 6mwt (69.2 m) was clinically significant. Preintervention the levels of physical activity were below international recommendations for health; after the program they achieved the recommendations. Conclusion: The results showed an improvement in functional capacity with a decrease in future disability risk associated with a better lifestyle with respect to physical activity levels in 1 patient.

Intermittent claudication and physical exercise: effectiveness of a home-based program

Peripheral arterial disease (PAD) as a high incidence in general population and 12% to 20% of population with more than 60 years has already clinical symptoms, such as intermittent claudication (IC), pain, loss of strength and functional incapacity. There are already some studies who refer the possible positive effects of physical exercise in functional consequences of PAD.

A supervised versus home-based program effects on liver transplanted familial amyloidotic polyneuropathy patients: walking, fatigue and quality of life

Familial amyloidotic polyneuropathy is a systemic deposition of amyloidal fibre mainly on peripheral nervous system (but also in other systems like heart, gastrointestinal tract, kidneys, etc) and mainly produced in the liver. Purpose of this study: to evaluate the effects of a six months exercise training program(supervised or home-based) on walking capacity, fatigue and health related quality of life (HRQL) on Familial Amyloidotic Polyneuropathy patients submitted to a liver transplant.

Nonlinear optimization method for short-term hydro scheduling considering head-dependency

This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent reservoirs under competitive environment. We propose a new nonlinear optimization method to consider hydroelectric power generation as a function of water discharge and also of the head. Head-dependency is considered on short-term hydro scheduling in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems, providing a higher profit at a negligible additional computation time in comparison with a linear optimization method that ignores head-dependency.

Intermittent claudication and physical exercise: effectiveness of a home-based program

Peripheral arterial disease (PAD) as a high incidence in general population and 12% to 20% of population with more than 60 years has already clinical symptoms, such as intermittent claudication (IC), pain, loss of strength and functional incapacity. There are already some studies that refer the possible positive effects of physical exercise in functional consequences of PAD. The purpose of this study was to verify the results of a home-based (HB) weekly supervised physical exercise program in patients with IC in consequence of PAD in lower limbs, and observe the medium number of diary steps walked by the subjects of our study.

The importance of the program for the promotion of physical activity in perceived fatigue in people with multiple sclerosis

The aims of the study is to examine for intervention program of physical activity in the perception of fatigue, in patients with multiple sclerosis.

Implication of an intervention program for the promotion of physical activity in the quality of life of people with multiple sclerosis

The aims of this study is to examine the interest for quality of life of an implementation of program physical activity, with patients of multiple sclerosis.

Modalidades síncronas e assíncronas no ensino da radiologia do sistema nervoso: estilos e resultados de aprendizagem

Lidar com as problemáticas da saúde, implica um domínio dos processos cognitivos (raciocínio, resolução de problemas e tomada de decisão) e de desempenhos práticos, o que obriga a afectação de um conjunto de atitudes e comportamentos específicos. Este estudo, implementou e avaliou o impacto de experiências pedagógicas desenvolvidas com os estudantes da unidade curricular Radiologia do Sistema Nervoso (RSN) da Escola Superior de Tecnologia da Saúde de Lisboa (ESTeSL). Aplicaram-se metodologias de ensino mistas (presenciais e virtuais) utilizadas na leccionação teórica e prática no ano curricular 2008/2009. Para a avaliação do perfil de aprendizagem dos estudantes foi aplicado o método de Honey & Munford e para a avaliação e monitorização dos conhecimentos aplicaram-se check list baseadas nos conteúdos programáticos. A monitorização das ferramentas da plataforma moodle complementaram a restante informação. Verificou-se uma progressão de aprendizagem positiva para um grupo de estudantes maioritariamente do estilo reflexivo (média=10,6 estudantes). As conclusões apontaram para um impacto positivo quanto à aplicação das metodologias híbridas com maior índice de sucesso para a metodologia assíncrona. Verificou-se também mais flexibilidade no acesso aos conteúdos porém com algumas limitações tais como residência inicial por parte dos estudantes, maior carga de trabalho para os docentes, falta de terminais para acesso à plataforma e pouca experiência de todos os envolvidos no domínio e manipulação da plataforma. ABSTRACT - This study focused on the role of cognitive processes (reasoning, problem solving and decision making) and performance practice in the formation of attitudes and behaviours relating to health issues. It was conducted to evaluate the effects of pedagogical experiences on students who participated in the course in radiography in the Nervous System Imaging Unit (RSN) of the Lisbon Health School of Technology. Mixed (face-to-face and virtual) teaching methodologies were used in theory and practice sessions. Honey and Munford’s method was used to evaluate the learning profile of students. To monitor and evaluate students’ knowledge acquisition, check lists based on program topics were applied. Other information was supplied through the learning platform of Moodle. The student group with mostly a reflective learning style increased their knowledge. The asynchronous method was shown to produce a higher success rate and more flexibility in accessing content but also registered some limitations such as resistance by students, increased workload for teachers, lack of access to the platform and inexperience of all involved in handling the platform.

A Hexanuclear Mixed-Valence Oxovanadium(IV,V) Complex as a Highly Efficient Alkane Oxidation Catalyst

The new hexanuclear mixed-valence vanadium complex [V3O3(OEt)(ashz)(2)(mu-OEt)](2) (1) with an N,O-donor ligand is reported. It acts as a highly efficient catalyst toward alkane oxidations by aqueous H2O2. Remarkably, high turnover numbers up to 25000 with product yields of up to 27% (based on alkane) stand for one of the most active systems for such reactions.

Implications of the Intervention Program for Physical Activity (IPPA) in the perception of illness and wellbeing in people with Multiple Sclerosis (MS)

The aim of this study is to examine the implications of the IPPA in the perception of illness and wellbeing in MS patients. Methods - This is a quasi experimental study non-randomized study with 24 MS patients diagnosed at least 1 year before, and with an EDSS score of under 7. We used the IPPA in 3 groups of eight people in 3 Portuguese hospitals (Lisbon, Coimbra, and Porto). The sessions were held once a week for 90 minutes, over a period of 7 weeks. The instruments used were: We asked the subjects the question “Please classify the severity of your disease?” and used the Personal Wellbeing Scale (PWS) at the beginning (time A) and end (time B) of the IPPA. We used the SPSS version 20. A non-parametric statistical hypothesis test (Wilcoxon test) was used for the variable analysis. The intervention followed the recommendations of the Helsinki Declaration. Results – The results suggest that there are differences between time A and B, the perception of illness decreased (p<0.08), while wellbeing increased (p<0.01). Conclusions: The IPPA can play an important role in modifying the perception of disease severity and personal wellbeing.

3D-2D image registration by nonlinear regression

We propose a 3D-2D image registration method that relates image features of 2D projection images to the transformation parameters of the 3D image by nonlinear regression. The method is compared with a conventional registration method based on iterative optimization. For evaluation, simulated X-ray images (DRRs) were generated from coronary artery tree models derived from 3D CTA scans. Registration of nine vessel trees was performed, and the alignment quality was measured by the mean target registration error (mTRE). The regression approach was shown to be slightly less accurate, but much more robust than the method based on an iterative optimization approach.