An agent based architecture for material handling systems

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Petri net based development of globally-asynchronous locally-synchronous distributed embedded systems

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores

An agent based architecture to support monitoring in plug and produce manufacturing systems using knowledge extraction

In recent years a set of production paradigms were proposed in order to capacitate manufacturers to meet the new market requirements, such as the shift in demand for highly customized products resulting in a shorter product life cycle, rather than the traditional mass production standardized consumables. These new paradigms advocate solutions capable of facing these requirements, empowering manufacturing systems with a high capacity to adapt along with elevated flexibility and robustness in order to deal with disturbances, like unexpected orders or malfunctions. Evolvable Production Systems propose a solution based on the usage of modularity and self-organization with a fine granularity level, supporting pluggability and in this way allowing companies to add and/or remove components during execution without any extra re-programming effort. However, current monitoring software was not designed to fully support these characteristics, being commonly based on centralized SCADA systems, incapable of re-adapting during execution to the unexpected plugging/unplugging of devices nor changes in the entire system’s topology. Considering these aspects, the work developed for this thesis encompasses a fully distributed agent-based architecture, capable of performing knowledge extraction at different levels of abstraction without sacrificing the capacity to add and/or remove monitoring entities, responsible for data extraction and analysis, during runtime.

Machine diagnosis based on artificial immune systems

Nowadays, many of the manufactory and industrial system has a diagnosis system on top of it, responsible for ensuring the lifetime of the system itself. It achieves this by performing both diagnosis and error recovery procedures in real production time, on each of the individual parts of the system. There are many paradigms currently being used for diagnosis. However, they still fail to answer all the requirements imposed by the enterprises making it necessary for a different approach to take place. This happens mostly on the error recovery paradigms since the great diversity that is nowadays present in the industrial environment makes it highly unlikely for every single error to be fixed under a real time, no production stop, perspective. This work proposes a still relatively unknown paradigm to manufactory. The Artificial Immune Systems (AIS), which relies on bio-inspired algorithms, comes as a valid alternative to the ones currently being used. The proposed work is a multi-agent architecture that establishes the Artificial Immune Systems, based on bio-inspired algorithms. The main goal of this architecture is to solve for a resolution to the error currently detected by the system. The proposed architecture was tested using two different simulation environment, each meant to prove different points of views, using different tests. These tests will determine if, as the research suggests, this paradigm is a promising alternative for the industrial environment. It will also define what should be done to improve the current architecture and if it should be applied in a decentralised system.

Abstract computation in schizophrenia detection through artificial neural network based systems

Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.

Testing Nelder-Mead based repulsion algorithms for multiple roots of nonlinear systems via a two-level factorial design of experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

Fine time scaling of purifying selection on human nonsynonymous mtDNA mutations based on the worldwide population tree and mother-child pairs

A high-resolution mtDNA phylogenetic tree allowed us to look backward in time to investigate purifying selection. Purifying selection was very strong in the last 2,500 years, continuously eliminating pathogenic mutations back until the end of the Younger Dryas (∼11,000 years ago), when a large population expansion likely relaxed selection pressure. This was preceded by a phase of stable selection until another relaxation occurred in the out-of-Africa migration. Demography and selection are closely related: expansions led to relaxation of selection and higher pathogenicity mutations significantly decreased the growth of descendants. The only detectible positive selection was the recurrence of highly pathogenic nonsynonymous mutations (m.3394T>C-m.3397A>G-m.3398T>C) at interior branches of the tree, preventing the formation of a dinucleotide STR (TATATA) in the MT-ND1 gene. At the most recent time scale in 124 mother-children transmissions, purifying selection was detectable through the loss of mtDNA variants with high predicted pathogenicity. A few haplogroup-defining sites were also heteroplasmic, agreeing with a significant propensity in 349 positions in the phylogenetic tree to revert back to the ancestral variant. This nonrandom mutation property explains the observation of heteroplasmic mutations at some haplogroup-defining sites in sequencing datasets, which may not indicate poor quality as has been claimed.

Development of advanced cell/tissue culture systems, based on enhanced polymeric scaffolds and sophisticated bioreactors, for tissue engineering applications

Programa Doutoral em Engenharia Biomédica

Sensores basados en nanocavidades de sistemas supramoleculares. Sensors based on nanocavities of supramolecular systems.

Uno de los grandes desafíos analíticos es resolver la complejidad del análisis de cantidades trazas de compuestos orgánicos debido a la baja sensibilidad analítica de las técnicas usuales que permiten una determinación específica como IR o RMN. El uso de espectrofotometría UV-Visible y espectroluminiscencia, técnicas que presentan mayor sensibilidad, se ve dificultada en muchos casos por el efecto matriz producido en el tratamiento de muestras reales y complejas o pérdida de la selectividad debido a la superposición de bandas.La interacción por formación de complejos entre determinados sustratos y receptores macrocíclicos que presentan poros o cavidades nanométricas, puede afectar las propiedades espectroscópicas de los sustratos. La respuesta de técnicas sensibles puede traducirse así en un análisis selectivo debido al reconocimiento molecular que se establece entre un dado receptor y el sustrato de interés. Por otra parte puede mejorar la sensibilidad debido a efectos de micropolaridad del medio, a efectos de restricciones de grados de libertad, por compartamentalización o protección de los estados excitados de los sustratos incluidos. El uso analítico de receptores selectivos es un área actualmente en desarrollo, que permite una rápida determinación de especies químicas, disminuyendo el efecto de interferentes, mejorando la sensibilidad y disminuyendo el tratamiento de la muestra.Se estudiarán los mecanismos involucrados en las interacciones y los factores que los modifican por técnicas espectroscópicas como UV-visible, RMN y luminiscencia. Se determinarán los parámetros analíticos por luminiscencia en los medios y condiciones en que la sensibilidad analítica muestre el mayor incremento. Se realizarán las pruebas de validación en las mejores condiciones para cada uno y mezclas de analitos relacionados en muestras reales.

Reusability evaluation of component-based embedded automative software systems

Magdeburg, Univ., Fak. für Informatik, Diss., 2012

Designing crystallization based-enantiomeric separation for chiral compound-forming systems in consideration of polymorphism and solvate formation

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2014

Towards effective research-paper recommender systems and user modeling based on mind maps

Magdeburg, Univ., Fak. für Informatik, Diss., 2015

Verification of system properties of polynomial systems using discrete-time approximations and set-based analysis

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2015