Técnicas de controlo não-linear baseadas em redes neuronais - do algoritmo à implementação

O presente trabalho analisa soluções de controlo não-linear baseadas em Redes Neuronais e apresenta a sua aplicação a um caso prático, desde o algoritmo de treino até à implementação física em hardware. O estudo inicial do estado da arte da utilização das Redes Neuronais para o controlo leva à proposta de soluções iterativas para a definição da arquitectura das mesmas e para o estudo das técnicas de Regularização e Paragem de Treino Antecipada, através dos Algoritmos Genéticos e à proposta de uma forma de validação dos modelos obtidos. Ao longo da tese são utilizadas quatro malhas para o controlo baseado em modelos, uma das quais uma contribuição original, e é implementado um processo de identificação on-line, tendo por base o algoritmo de treino Levenberg-Marquardt e a técnica de Paragem de Treino Antecipada que permite o controlo de um sistema, sem necessidade de recorrer ao conhecimento prévio das suas características. O trabalho é finalizado com um estudo do hardware comercial disponível para a implementação de Redes Neuronais e com o desenvolvimento de uma solução de hardware utilizando uma FPGA. De referir que o trabalho prático de teste das soluções apresentadas é realizado com dados reais provenientes de um forno eléctrico de escala reduzida.The present work analyses non-linear control solutions based on Neural Networks and presents its application to a case study, from the training algorithm to the hardware implementation. The initial study of the state of the art of Neural Networks use in control led to a proposal of iterative solutions for architecture definition and establishment of the Regularization and Early Stopping parameters, through the use of Genetic Algorithms and to the proposal of a new validation technique for the models. Throughout this thesis, four different loops for model based control are used, one of which is an original contribution, and an on-line identification procedure, based on the Levenberg-Marquardt algorithm with Early Stopping that allows system identification without previous knowledge of its characteristics. The work is finalized with a commercial hardware study for Neural Networks and with the development of a hardware solution based on a FPGA. It is worth mentioning that proposed solutions are tested with real data provided by a reduced scale electric kiln

Kinetics and thermodynamics of poly (9,9-dioctylfluorene) beta-phase formation in dilute solution

Poly(9,9-dioctylfluorene) (PFO) adopts a particular type of conformation in dilute solutions of the poor solvent methylcyclohexane (MCH) below 273 K, which is revealed by the appearance of a red-shifted absorption peak at 437−438 nm. The formation of this ordered conformation depends on the temperature but is independent of polymer concentration over the range studied (3−25 μg/mL). On the basis of absorption, steady-state, and time-resolved fluorescence data, the new absorption peak at 437−438 nm is assigned to a highly ordered conformation of PFO chains, analogous to the so-called β-phase first identified in PFO films. From the study of PFO solutions in MCH as a function of temperature, we conclude that these ordered segments (β-conformation) coexist with less ordered domains in the same chain. When the ordered domains are present, they act as efficient energy traps and the fluorescence from the disordered regions is quenched. The transition between the disordered and the ordered PFO conformations is adequately described by a mechanism that involves two steps:  a first, essentially intramolecular, one from a relatively disordered (α) to an ordered conformation (β), followed by aggregation of chains containing β-conformation into anisotropic ordered domains. From the temperature dependence of the 437−438 nm peak intensity, the transition temperature Tβ = 261 K, enthalpy ΔHβ = −18.0 kcal mol-1, and entropy ΔSβ = −68.4 cal K-1 mol-1 were obtained. The formation of the β-conformation domains were also followed as a function of time at 260 K. The rate constants at 260 K were determined, showing an order of magnitude around 10-3 s-1 (kα→β = 5.9 × 10-4 s-1; kβ→α = 9 × 10-4 s-1; kagg = 2.3 × 10-3 M-1 s-1; kdiss = 4.4 × 10-4 s-1). This small magnitude explains the long times required for a “complete” conversion to the β-conformation

Heuristic Optimization of Deep and Shallow Classifiers: An Application for Electroencephalogram Cyclic Alternating Pattern Detection

Methodologies for automatic non-rapid eye movement and cyclic alternating pattern analysis were proposed to examine the signal from one electroencephalogram monopolar derivation for the A phase, cyclic alternating pattern cycles, and cyclic alternating pattern rate assessments. A population composed of subjects free of neurological disorders and subjects diagnosed with sleep-disordered breathing was studied. Parallel classifications were performed for non-rapid eye movement and A phase estimations, examining a one-dimension convolutional neural network (fed with the electroencephalogram signal), a long short-term memory (fed with the electroencephalogram signal or with proposed features), and a feed-forward neural network (fed with proposed features), along with a finite state machine for the cyclic alternating pattern cycle scoring. Two hyper-parameter tuning algorithms were developed to optimize the classifiers. The model with long short-term memory fed with proposed features was found to be the best, with accuracy and area under the receiver operating characteristic curve of 83% and 0.88, respectively, for the A phase classification, while for the non-rapid eye movement estimation, the results were 88% and 0.95, respectively. The cyclic alternating pattern cycle classification accuracy was 79% for the same model, while the cyclic alternating pattern rate percentage error was 22%.info:eu-repo/semantics/publishedVersio

A Matlab Tool for Analyzing and Improving Fault Tolerance of Artificial Neural Networks

Abstract: FTSET is a software tool that deals with fault tolerance of Artificial Neural Networks. This tool is capable of evaluating the fault tolerance degree of a previously trained Artificial Neural Network given its inputs ranges, the weights and the architecture. The FTSET is also capable of improving the fault tolerance by applying a technique of splitting the connections of the network that are more important to form the output. This technique improves fault tolerance without changing the network's output. The paper is concluded by two examples that show the application of the FTSET to different Artificial Neural Networks and the improvement of the fault tolerance obtained

A global monitoring system for electricity consumption and production of household roof-top PV systems in Madeira

This paper describes recent work on the development of a wireless-based remote monitoring system for household energy consumption and generation in Madeira Island, Portugal. It contains three different main sections: (1) a monitoring system for consumed and produced energy of residencies equipped with photovoltaic (PV) systems, (2) developing a tool to predict the electricity production, (3) and proposing a solution to detect the PV system malfunctions. With the later tool, the user (owner) or the energy management system can monitor its own PV system and make an efficient schedule use of electricity at the consumption side. In addition, currently, the owners of PV systems are notified about a failure in the system only when they receive the bill, whereas using the proposed method conveniently would notify owners prior to bill issue. The artificial neural network was employed as a tool together with the hardware-based monitoring system which allows a daily analysis of the performance of the system. The comparison of the predicted value of the produced electricity with the actual production for each day shows the validity of the method.info:eu-repo/semantics/publishedVersio

Educational Media in Portugal: The next decade (2011-2020)

A discussion on the future developments on educational media in the context of higher education in Portugal will be the focus of this panel. This panel will represent different lines of research and development as well as a variety of experiences on implementing innovation in higher education. The panelists will share their expectations and visions for a next decade of development and innovation in the area of educational media in Portugal.info:eu-repo/semantics/publishedVersio

Dinamika roda Acartia (Calanoida: Copepoda) u temperiranom plitkom estuariju (ušće rijeke Mondego) na zapadnoj obali Portugala

The purpose of this work was to review the dynamics of the Acartia species in the Mondego estuary (a temperate North-Atlantic shallow estuary in Western Portugal) in a genus integrated perspective. The Acartia genus is represented in the system by the species Acartia clausi and Acartia tonsa; the samples were taken between July 1999 and June 2000, with 63 and 125 µm mesh size nets, and between January 2003 and January 2004, with a 335 µm mesh size net, in the downstream and upstream areas of the estuary. Significant differences in abundance were found between months and sampling stations for the two species (ANOVA, P < 0.05). A. clausi dominated in the downstream estuary, registering peaks in June (156 ind. m-3) and September (73 ind. m-3); in the upstream estuary this species showed a maximum of density in September (35 ind. m-3). A. tonsa dominated in the upstream estuary with peaks of abundance occurring in December (2372 ind. m-3) and October (1056 ind. m-3) in the downstream estuary this species exhibited higher abundance in August (52 ind. m-3). The two species of the genus coexist in time exhibiting a strong spatial segregation behavior in the estuary.Cilj ovog rada je dati pregled dinamike vrsta Acartia u estuariju Mondego (temperirani sjevernoatlantski plitki estuarij u zapadnom Portugalu) za sve nađene vrste toga roda. Rod Acartia je prisutan s tri vrste: Acartia clausi, Acartia bifilosa var. inermis i Acartia tonsa; uzorci uzeti od srpnja 1999 do lipnja 2000 su dobiveni pomoću mreže veličine oka 63 i 125 µm, a od siječnja 2003 do siječnja 2004 pomoću mreže veličine oka 335 µm, u nizvodnom i uzvodnom dijelu estuarija. Nađene su znatne razlike u abundanciji dviju vrsta (ANOVA, P < 0.05). A. clausi je bila dominantna u nizvodnom estuariju s maksimumom u lipnju (156 ind. m -3) i rujnu (73 ind. m-3); u uzvodnom estuariju ova vrsta je imala maksimum gustoće u rujnu (35 ind. m-3). A. tonsa je bila dominantna u uzvodnom estuariju s makmimumom gustoće u prosincu (2372 ind. m-3) i listopadu (1056 ind. m-3). U nizvodnom estuariju ova je vrsta bila obilatije zastupljena u rujnu (52 ind. m-3). Dvije vrste se u estuariju javljaju istovremeno, ali su prostorno izrazito odijeljen

9-Borafluoren-9-yl and diphenylboron tetracoordinate complexes of F- and Cl-substituted 8-quinolinolato ligands: synthesis, molecular and electronic structures, fluorescence and application in OLED devices

Six new four-coordinate tetrahedral boron complexes, containing 9-borafluoren-9-yl and diphenylboron cores attached to orthogonal fluorine- and chlorine-substituted 8-quinolinolato ligand chromophores, have been synthesised, characterised, and applied as emitters in organic light-emitting diodes (OLEDs). An extensive steady-state and time-resolved photophysical study, in solution and in the solid state, resulted in the first-time report of delayed fluorescence (DF) in solid films of 8-quinolinolato boron complexes. The DF intensity dependence on excitation dose suggests that this emission originates from triplet–triplet annihilation (TTA). Density functional theory (DFT) and time-dependent density functional theory (TDDFT) studies give insight into the ground and excited state geometries, electronic structures, absorption energies, and singlet–triplet gaps in these new organoboron luminophores. Finally, given their highly luminescent behaviour, organic light-emitting diode (OLED) devices were produced using the synthesised organoboron compounds as emissive fluorescent dopants. The best OLED displays green-blue (λmaxEL = 489 nm) electroluminescence with an external quantum efficiency (EQE) of 3.3% and a maximum luminance of 6300 cd m−2

DeepDyve: Dynamic Verification for Deep Neural Networks

Deep neural networks (DNNs) have become one of the enabling technologies in many safety-critical applications, e.g., autonomous driving and medical image analysis. DNN systems, however, suffer from various kinds of threats, such as adversarial example attacks and fault injection attacks. While there are many defense methods proposed against maliciously crafted inputs, solutions against faults presented in the DNN system itself (e.g., parameters and calculations) are far less explored. In this paper, we develop a novel lightweight fault-tolerant solution for DNN-based systems, namely DeepDyve, which employs pre-trained neural networks that are far simpler and smaller than the original DNN for dynamic verification. The key to enabling such lightweight checking is that the smaller neural network only needs to produce approximate results for the initial task without sacrificing fault coverage much. We develop efficient and effective architecture and task exploration techniques to achieve optimized risk/overhead trade-off in DeepDyve. Experimental results show that DeepDyve can reduce 90% of the risks at around 10% overhead

Uma capitania dos novos tempos: economia, sociedade e política na São Paulo restaurada (1765-1822)

O artigo reflete sobre a trajetória da Capitania de São Paulo, a partir de 1750, apontando sua transformação, de fronteira e "boca do sertão", para território estratégico da conquista e defesa das partes meridionais e área economicamente integrada aos circuitos mercantis atlânticos.In this article, we reflect upon the history of the Captaincy of São Paulo as from 1750, drawing attention to its transformation from frontier land and "door to the backcountry" into a territory of strategic value for the purposes of conquest and defense of the southern regions, and economically integrated into the Atlantic trade routes