Entropy analysis of integer and fractional dynamical systems

This paper investigates the adoption of entropy for analyzing the dynamics of a multiple independent particles system. Several entropy definitions and types of particle dynamics with integer and fractional behavior are studied. The results reveal the adequacy of the entropy concept in the analysis of complex dynamical systems.

Reply to: Comments on “Particle Swarm Optimization with Fractional-Order Velocity”

We agree with Ling-Yun et al. [5] and Zhang and Duan comments [2] about the typing error in equation (9) of the manuscript [8]. The correct formula was initially proposed in [6, 7]. The formula adopted in our algorithms discussed in our papers [1, 3, 4, 8] is, in fact, the following: ...

Dispatch of distributed Energy Resources to Provide Energy and Reserve in Smart Grids using a Particle Swarm Optimization Approach

The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.

Particle Swarm Optimization of Electricity Market Negotiating Players Portfolio

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi- Agent System for Competitive Electricity Markets), which performs realistic simulations of the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from each market context. However, it is still necessary to adequately optimize the players’ portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering different market opportunities (bilateral negotiation, market sessions, and operation in different markets) and the negotiation context such as the peak and off-peak periods of the day, the type of day (business day, weekend, holiday, etc.) and most important, the renewable based distributed generation forecast. The proposed approach is tested and validated using real electricity markets data from the Iberian operator – MIBEL.

Electricity Markets Portfolio Optimization using a Particle Swarm Approach

Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player’s portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and offpeak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator – OMIE.

Scalable Intelligence for Scheduling Systems

A personalização é um aspeto chave de uma interação homem-computador efetiva. Numa era em que existe uma abundância de informação e tantas pessoas a interagir com ela, de muitas maneiras, a capacidade de se ajustar aos seus utilizadores é crucial para qualquer sistema moderno. A criação de sistemas adaptáveis é um domínio bastante complexo que necessita de métodos muito específicos para ter sucesso. No entanto, nos dias de hoje ainda não existe um modelo ou arquitetura padrão para usar nos sistemas adaptativos modernos. A principal motivação desta tese é a proposta de uma arquitetura para modelação do utilizador que seja capaz de incorporar diferentes módulos necessários para criar um sistema com inteligência escalável com técnicas de modelação. Os módulos cooperam de forma a analisar os utilizadores e caracterizar o seu comportamento, usando essa informação para fornecer uma experiência de sistema customizada que irá aumentar não só a usabilidade do sistema mas também a produtividade e conhecimento do utilizador. A arquitetura proposta é constituída por três componentes: uma unidade de informação do utilizador, uma estrutura matemática capaz de classificar os utilizadores e a técnica a usar quando se adapta o conteúdo. A unidade de informação do utilizador é responsável por conhecer os vários tipos de indivíduos que podem usar o sistema, por capturar cada detalhe de interações relevantes entre si e os seus utilizadores e também contém a base de dados que guarda essa informação. A estrutura matemática é o classificador de utilizadores, e tem como tarefa a sua análise e classificação num de três perfis: iniciado, intermédio ou avançado. Tanto as redes de Bayes como as neuronais são utilizadas, e uma explicação de como as preparar e treinar para lidar com a informação do utilizador é apresentada. Com o perfil do utilizador definido torna-se necessária uma técnica para adaptar o conteúdo do sistema. Nesta proposta, uma abordagem de iniciativa mista é apresentada tendo como base a liberdade de tanto o utilizador como o sistema controlarem a comunicação entre si. A arquitetura proposta foi desenvolvida como parte integrante do projeto ADSyS - um sistema de escalonamento dinâmico - utilizado para resolver problemas de escalonamento sujeitos a eventos dinâmicos. Possui uma complexidade elevada mesmo para utilizadores frequentes, daí a necessidade de adaptar o seu conteúdo de forma a aumentar a sua usabilidade. Com o objetivo de avaliar as contribuições deste trabalho, um estudo computacional acerca do reconhecimento dos utilizadores foi desenvolvido, tendo por base duas sessões de avaliação de usabilidade com grupos de utilizadores distintos. Foi possível concluir acerca dos benefícios na utilização de técnicas de modelação do utilizador com a arquitetura proposta.

Biological effects of acrylic engineered particulate-systems

Polymeric particulate-systems are of great relevance due to their possible biomedical applications, among them as carriers for the nano- or microencapsulation of drugs. However, due to their unique specific properties, namely small size range, toxicity issues must be discarded before allowing its use on health-related applications. Several polymers, as poly(methyl methacrylate) (PMMA), have proved to be suitable for the preparation of particulate-systems. However, a major drawback of its use refers to incomplete drug release from particles matrix. Recent strategies to improve PMMA release properties mention the inclusion of other acrylic polymers as Eudragit (EUD) on particles formulation. Though PMMA and EUD are accepted by the FDA as biocompatible, their safety on particle composition lacks sufficient toxicological data. The main objective of this thesis was to evaluate the biological effects of engineered acrylic particulate-systems. Preparation, physicochemical characterization and in vitro toxicity evaluation were assessed on PMMA and PMMA-EUD (50:50) particles. The emulsification-solvent evaporation methodology allowed the preparation of particles with spherical and smooth surfaces within the micrometer range (±500 nm), opposing surface charges and different levels of hydrophobicity. It was observed that particles physicochemical properties (size and charge) were influenced by biological media composition, such as serum concentration, ionic strength or pH. In what concerns to the in vitro toxicological studies, particle cellular uptake was observed on different cell lines (macrophages, osteoblasts and fibroblasts). Cytotoxicity effects were only found after 72 h of cells exposure to the particles, while no oxidative damage was observed neither on osteoblasts nor fibroblasts. Also, no genotoxicity was found in fibroblast using the comet assay to assess DNA damage. This observation should be further confirmed with other validated genotoxicity assays (e.g. Micronucleus Assay). The present study suggests that the evaluated acrylic particles are biocompatible, showing promising biological properties for potential use as carriers in drug-delivery systems.

Complex networks and data mining: toward a new perspective for the understanding of complex systems

Complex systems, i.e. systems composed of a large set of elements interacting in a non-linear way, are constantly found all around us. In the last decades, different approaches have been proposed toward their understanding, one of the most interesting being the Complex Network perspective. This legacy of the 18th century mathematical concepts proposed by Leonhard Euler is still current, and more and more relevant in real-world problems. In recent years, it has been demonstrated that network-based representations can yield relevant knowledge about complex systems. In spite of that, several problems have been detected, mainly related to the degree of subjectivity involved in the creation and evaluation of such network structures. In this Thesis, we propose addressing these problems by means of different data mining techniques, thus obtaining a novel hybrid approximation intermingling complex networks and data mining. Results indicate that such techniques can be effectively used to i) enable the creation of novel network representations, ii) reduce the dimensionality of analyzed systems by pre-selecting the most important elements, iii) describe complex networks, and iv) assist in the analysis of different network topologies. The soundness of such approach is validated through different validation cases drawn from actual biomedical problems, e.g. the diagnosis of cancer from tissue analysis, or the study of the dynamics of the brain under different neurological disorders.

The emergence of product certification systems as trade barriers

This paper addresses the growing difficulties automobile manufacturers face within their after sales business: an increasing number of trade obstacles set up by import countries discriminates against the foreign suppliers and impedes the international sales of genuine parts. The purpose of the study is to explore the emergence of trade restrictive product certification systems, which affect spare parts exports of automobile manufacturers. The methodology used includes review of the literature and an empirical study based on qualitative interviews with representatives of major stakeholders of the automotive after sales business. Relevant key drivers, which initiate the introduction of technical regulations in importing countries, are identified and analysed to evaluate their effect on the emerging trade policy. The analysis of the key drivers outlines that several interacting components, such as the global competitiveness of the country, macroeconomic and microeconomic factors, and certain country-specific variables induce trade restrictive product certification systems. The findings allow for an early detection of the emergence of product certification systems and provide a means to early recognise the risks and opportunities for the sales of automotive spare parts in the automakers’ target markets. This allows the manufacturers to react immediately and adapt in time to the upcoming changes.

Interacting and making personalized recommendations of places of interest to tourists

Advances in Intelligent Systems and Computing, 353

Search for long-lived, weakly interacting particles that decay to displaced hadronic jets in proton--proton collisions at s√=8 TeV with the ATLAS detector

A search for the decay of neutral, weakly interacting, long-lived particles using data collected by the ATLAS detector at the LHC is presented. This analysis uses the full dataset recorded in 2012: 20.3 fb−1 of proton--proton collision data at s√=8 TeV. The search employs techniques for reconstructing decay vertices of long-lived particles decaying to jets in the inner tracking detector and muon spectrometer. Signal events require at least two reconstructed vertices. No significant excess of events over the expected background is found, and limits as a function of proper lifetime are reported for the decay of the Higgs boson and other scalar bosons to long-lived particles and for Hidden Valley Z′ and Stealth SUSY benchmark models. The first search results for displaced decays in Z′ and Stealth SUSY models are presented. The upper bounds of the excluded proper lifetimes are the most stringent to date.

In-line rheo-optical microstructural characterization of complex polymer systems

Tese de Doutoramento em Ciência e Engenharia de Polímeros e Compósitos.

Desarrollo de sistemas nano/micro-particulados con aplicación en la fotodegradación selectiva de contaminantes orgánicos en solución. Development of nano / micro-particles systems with application to selective photodegradation of organic pollutants in solution.

IDENTIFICACIÓN DEL PROBLEMA DE ESTUDIO. Las sustancias orgánicas solubles en agua no biodegradables tales como ciertos herbicidas, colorantes industriales y metabolitos de fármacos de uso masivo son una de las principales fuentes de contaminación en aguas subterráneas de zonas agrícolas y en efluentes industriales y domésticos. Las reacciones fotocatalizadas por irradiación UV-visible y sensitizadores orgánicos e inorgánicos son uno de los métodos más económicos y convenientes para la descomposición de contaminantes en subproductos inocuos y/o biodegradables. En muchas aplicaciones es deseable un alto grado de especificidad, efectividad y velocidad de degradación de un dado agente contaminante que se encuentra presente en una mezcla compleja de sustancias orgánicas en solución. En particular son altamente deseables sistemas nano/micro -particulados que formen suspensiones acuosas estables debido a que estas permiten una fácil aplicación y una eficaz acción descontaminante en grandes volúmenes de fluidos. HIPÓTESIS Y PLANTEO DE LOS OBJETIVOS. El objetivo general de este proyecto es desarrollar sistemas nano/micro particulados formados por polímeros de impresión molecular (PIMs) y foto-sensibilizadores (FS). Un PIMs es un polímero especialmente sintetizado para que sea capaz de reconocer específicamente un analito (molécula plantilla) determinado. La actividad de unión específica de los PIMs en conjunto con la capacidad fotocatalizadora de los sensibilizadores pueden ser usadas para lograr la fotodescomposición específica de moléculas “plantilla” (en este caso un dado contaminante) en soluciones conteniendo mezclas complejas de sustancias orgánicas. MATERIALES Y MÉTODOS A UTILIZAR. Se utilizaran técnicas de polimerización en mini-emulsión para sintetizar los sistemas nano/micro PIM-FS para buscar la degradación de ciertos compuestos de interés. Para caracterizar eficiencias, mecanismos y especificidad de foto-degradación en dichos sistemas se utilizan diversas técnicas espectroscópicas (estacionarias y resueltas en el tiempo) y de cromatografía (HPLC y GC). Así mismo, para medir directamente distribuciones de afinidades de unión y eficiencia de foto-degradación se utilizaran técnicas de fluorescencia de molécula/partícula individual. Estas determinaciones permitirán obtener resultados importantes al momento de analizar los factores que afectan la eficiencia de foto-degradación (nano/micro escala), tales como cantidad y ubicación de foto- sensibilizadores en las matrices poliméricas y eficiencia de unión de la plantilla y los productos de degradación al PIM. RESULTADOS ESPERADOS. Los estudios propuestos apuntan a un mejor entendimiento de procesos foto-iniciados en entornos nano/micro-particulados para aplicar dichos conocimientos al diseño de sistemas optimizados para la foto-destrucción selectiva de contaminantes acuosos de relevancia social; tales como herbicidas, residuos industriales, metabolitos de fármacos de uso masivo, etc. IMPORTANCIA DEL PROYECTO. Los sistemas nano/micro-particulados PIM-FS que se propone desarrollar en este proyecto se presentan como candidatos ideales para tratamientos específicos de efluentes industriales y domésticos en los cuales se desea lograr la degradación selectiva de compuestos orgánicos. Los conocimientos adquiridos serán indispensables para construir una plataforma versátil de sistemas foto-catalíticos específicos para la degradación de diversos contaminantes orgánicos de interés social. En lo referente a la formación de recursos humanos, el proyecto propuesto contribuirá en forma directa a la formación de 3 estudiantes de postgrado y 2 estudiantes de grado. En las capacidades institucionales se contribuirá al acondicionamiento del Laboratorio para Microscopía Óptica Avanzada (LMOA) en el Dpto. de Química de la UNRC y al montaje de un sistema de microscopio de fluorescencia que permitirá la aplicación de técnicas avanzadas de espectroscopia de fluorescencia de molecula individual. Water-soluble organic molecules such as certain non-biodegradable herbicides, industrial dyes and metabolites of widespread use drugs are a major source of pollution in groundwater from agricultural areas and in industrial and domestic effluents. Photo-catalytic reactions by UV-visible irradiation and organic sensitizers are one of the most economical and convenient methods for the decomposition of pollutants into harmless byproducts. In many applications it is highly desirable a high degree of specificity, effectiveness and speed of degradation of specific pollutants present in a complex mixture. In particular nano/micro-particles systems that form stable aqueous suspensions are highly desirable because they allow for easy application and effective decontamination of large volumes of fluids. Herein we propose the development of nano/micro particles composed by molecularly imprinted polymers (MIP) and photo-sensitizers (PS). The specific binding of MIP and the photo-catalytic ability of the sensitizers are used to achieve the photo-decomposition of specific "template" molecules in complex mixtures. Mini-emulsion polymerization techniques will be used to synthesize nano/micro MIP-FS systems. Spectroscopy (steady-state and time resolved) and chromatography (GC and HPLC) will be used to characterize efficiency, mechanisms and specificity of photo-degradation in these systems. In addition single molecule/particle fluorescence spectroscopy techniques will be used to directly measure distributions of binding affinities and photo-degradation efficiency in individual particles. The proposed studies point to a more detailed understanding of the factors affecting the photo-degradation efficiency in nano/micro-particles and to apply that knowledge in the design of optimized systems for photo-selective destruction of socially relevant aqueous pollutants.

Embodied Autonomy in Digital Ecosystems: From Bio-Inspired Agents to Cognitive Systems

This paper proposes to promote autonomy in digital ecosystems so that it provides agents with information to improve the behavior of the digital ecosystem in terms of stability. This work proposes that, in digital ecosystems, autonomous agents can provide fundamental services and information. The final goal is to run the ecosystem, generate novel conditions and let agents exploit them. A set of evaluation measures must be defined as well. We want to provide an outline of some global indicators, such as heterogeneity and diversity, and establish relationships between agent behavior and these global indicators to fully understand interactions between agents, and to understand the dependence and autonomy relations that emerge between the interacting agents. Individual variations, interaction dependencies, and environmental factors are determinants of autonomy that would be considered. The paper concludes with a discussion of situations when autonomy is a milestone