Modeling Vegetable Fractals by means of Fractional-order Equations

This paper characterizes four ‘fractal vegetables’: (i) cauliflower (brassica oleracea var. Botrytis); (ii) broccoli (brassica oleracea var. italica); (iii) round cabbage (brassica oleracea var. capitata) and (iv) Brussels sprout (brassica oleracea var. gemmifera), by means of electrical impedance spectroscopy and fractional calculus tools. Experimental data is approximated using fractional-order models and the corresponding parameters are determined with a genetic algorithm. The Havriliak-Negami five-parameter model fits well into the data, demonstrating that classical formulae can constitute simple and reliable models to characterize biological structures.

Entropy Analysis of Industrial Accident Data Series

Complex industrial plants exhibit multiple interactions among smaller parts and with human operators. Failure in one part can propagate across subsystem boundaries causing a serious disaster. This paper analyzes the industrial accident data series in the perspective of dynamical systems. First, we process real world data and show that the statistics of the number of fatalities reveal features that are well described by power law (PL) distributions. For early years, the data reveal double PL behavior, while, for more recent time periods, a single PL fits better into the experimental data. Second, we analyze the entropy of the data series statistics over time. Third, we use the Kullback–Leibler divergence to compare the empirical data and multidimensional scaling (MDS) techniques for data analysis and visualization. Entropy-based analysis is adopted to assess complexity, having the advantage of yielding a single parameter to express relationships between the data. The classical and the generalized (fractional) entropy and Kullback–Leibler divergence are used. The generalized measures allow a clear identification of patterns embedded in the data.

Autonomous guided vehicles applied to industrial engineering and management studies

This article presents a framework to an Industrial Engineering and Management Science course from School of Management and Industrial Studies using Autonomous Ground Vehicles (AGV) to supply materials to a production line as an experimental setup for the students to acquire knowledge in the production robotics area. The students must be capable to understand and put into good use several concepts that will be of utmost importance in their professional life such as critical decisions regarding the study, development and implementation of a production line. The main focus is a production line using AGVs, where the students are required to address several topics such as: sensors actuators, controllers and an high level management and optimization software. The presented framework brings to the robotics teaching community methodologies that allow students from different backgrounds, that normally don’t experiment with the robotics concepts in practice due to the big gap between theory and practice, to go straight to ”making” robotics. Our aim was to suppress the minimum start point level thus allowing any student to fully experience robotics with little background knowledge.

Fractional Calculus: Application in modeling and control

This contribution introduces the fractional calculus (FC) fundamental mathematical aspects and discuses some of their consequences. Based on the FC concepts, the chapter reviews the main approaches for implementing fractional operators and discusses the adoption of FC in control systems. Finally are presented some applications in the areas of modeling and control, namely fractional PID, heat diffusion systems, electromagnetism, fractional electrical impedances, evolutionary algorithms, robotics, and nonlinear system control.

Modeling and Control of a Dragonfly-Like Robot

Dragonflies demonstrate unique and superior flight performances than most of the other insect species and birds. They are equipped with two pairs of independently controlled wings granting an unmatchable flying performance and robustness. In this paper it is studied the dynamics of a dragonfly-inspired robot. The system performance is analyzed in terms of time response and robustness. The development of computational simulation based on the dynamics of the robotic dragonfly allows the test of different control algorithms. We study different movement, the dynamics and the level of dexterity in wing motion of the dragonfly. The results are positive for the construction of flying platforms that effectively mimic the kinematics and dynamics of dragonflies and potentially exhibit superior flight performance than existing flying platforms.

System Modeling and Control Through Fractional-Order Algorithms

The theory of fractional calculus goes back to the beginning of thr throry of differential calculus but its inherent complexity postponed the applications of the associated concepts. In the last decade the progress in the areas of chaos and fractals revealed subtle relationships with the fractional calculus leading to an increasing interest in the development of the new paradigm. In the area of automaticcontrol preliminary work has already been carried out but the proposed algorithms are restricted to the frequency domain. The paper discusses the design of fractional-order discrete-time controllers. The algorithms studied adopt the time domein, which makes them suited for z-transform analusis and discrete-time implementation. The performance of discrete-time fractional-order controllers with linear and non-linear systems is also investigated.

Environmental modeling with precision navigation using ROAZ autonomous surface vehicle

The use of robotic vehicles for environmental modeling is discussed. This paper presents diverse results in autonomous marine missions with the ROAZ autonomous surface vehicle. The vehicle can perform autonomous missions while gathering marine data with high inertial and positioning precision. The underwater world is an, economical and environmental, asset that need new tools to study and preserve it. ROAZ is used in marine environment missions since it can sense and monitor the surface and underwater scenarios. Is equipped with a diverse set of sensors, cameras and underwater sonars that generate 3D environmental models. It is used for study the marine life and possible underwater wrecks that can pollute or be a danger to marine navigation. The 3D model and integration of multibeam and sidescan sonars represent a challenge in nowadays. Adding that it is important that robots can explore an area and make decisions based on their surroundings and goals. Regard that, autonomous robotic systems can relieve human beings of repetitive and dangerous tasks.

Implementação do Sistema de Gestão Ambiental na Unidade Industrial de Gouveia, da Sumol+Compal

Esta dissertação descreve o levantamento da gestão de uma unidade fabril no âmbito do engarrafamento de águas, para a implementação de um Sistema de Gestão Ambiental (SGA) recorrendo á Norma NP EN ISO 14001:2012 tendo como objetivo proporcionar a melhoria contínua dos processos implementados na empresa bem como todos os benefícios que este referencial pressupõe. Foi realizada, numa primeira fase, uma auditoria diagnóstico com uma visita á fabrica no âmbito da implementação da ISO 14001, e posteriormente realizado todo o trabalho de aplicação ao referencial. Este trabalho consistiu a abordagem a todos os requisitos da norma ISO 14001 com principal foco na fase de Planeamento de um SGA, procurando-se responder essencialmente ao requisito 4.3 da referida norma. Procedeu-se á identificação das atividades da empresa (entradas e saídas), dos aspetos ambientais associados (respetiva significância) e levantamento dos requisitos legais aplicáveis (obrigações). Os restantes requisitos foram abordados e fez-se uma sugestão para o seu cumprimento, para além de que muitos já se encontram em cumprimento por compatibilidade com a norma ISO 9001 da qual a empresa já se encontra certificada. Esta dissertação pretende discutir e apresentar propostas para a implementação do SGA, possíveis vantagens daí decorrentes e as barreiras a ultrapassar (aspetos ambientais significativos) de maneiras a por em prática os requisitos do referencial normativo que venha a ser adotado. Foi realizada uma revisão bibliográfica destas temáticas e, ainda que estas medidas propostas não tenham sido implementadas, assim que implementadas esperam-se ganhos na economia de recursos como também outros benefícios descritos ao longo da dissertação que permita, com implementação do SGA não só enquanto estratégia, ser inovadora e competitiva.

Multi-agent simulation of competitive electricity markets: Autonomous systems cooperation for European market modeling

The electricity market restructuring, and its worldwide evolution into regional and even continental scales, along with the increasing necessity for an adequate integration of renewable energy sources, is resulting in a rising complexity in power systems operation. Several power system simulators have been developed in recent years with the purpose of helping operators, regulators, and involved players to understand and deal with this complex and constantly changing environment. The main contribution of this paper is given by the integration of several electricity market and power system models, respecting to the reality of different countries. This integration is done through the development of an upper ontology which integrates the essential concepts necessary to interpret all the available information. The continuous development of Multi-Agent System for Competitive Electricity Markets platform provides the means for the exemplification of the usefulness of this ontology. A case study using the proposed multi-agent platform is presented, considering a scenario based on real data that simulates the European Electricity Market environment, and comparing its performance using different market mechanisms. The main goal is to demonstrate the advantages that the integration of various market models and simulation platforms have for the study of the electricity markets’ evolution.

Análise da interoperabilidade aplicada ao projeto BIM de Estruturas Metálicas

O BIM – Building Information Modeling – é um conceito de controlo e gestão de informação desenvolvida, entre diferentes especialidades e intervenientes envolventes, durante o ciclo de vida das construções. A utilização das tecnologias BIM, no ramo da Engenharia Mecânica e Civil, tem sido uma aposta constante, e cada vez mais concisa, nos projetos de construção. A justificação para a adoção destas metodologias mais eficientes, em substituição dos processos convencionais, prende-se com o facto desses processos convencionais, ainda hoje, apresentarem muitas dificuldades e problemas associados, por exemplo, à falta de comunicação entre os intervenientes e ao ineficiente controlo na gestão de projetos. O objetivo desta dissertação centra-se na análise da interoperabilidade de softwares BIM, ou seja, na verificação da viabilidade de exportação de dados dos modelos produzidos, entre as ferramentas BIM. Para este campo de ação contribuirá a análise da passagem de informação, relativa ao modelo de uma Nave Industrial modelada, em alguns dos softwares BIM, correntemente mais utilizados. O conhecimento adquirido com a modelação do caso de estudo do presente trabalho irá permitir identificar algumas lacunas existentes ao nível da falta de recomendações práticas que sirvam de orientação na modelação recorrendo a ferramentas informáticas BIM-compatíveis. Assim, a base deste trabalho consiste na criação de uma série de recomendações ou de um roteiro de modelação em específico para a disciplina de estruturas enquanto área de aplicação concreta do estudo efetuado. Nesse sentido, a proposta deste trabalho é de apresentar alguns critérios de modelação onde são definidos os elementos a modelar em cada fase do projeto.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

Using neural networks and support vector regression to relate marchetti dilatometer test parameters and maximum shear modulus

In the last two decades, small strain shear modulus became one of the most important geotechnical parameters to characterize soil stiffness. Finite element analysis have shown that in-situ stiffness of soils and rocks is much higher than what was previously thought and that stress-strain behaviour of these materials is non-linear in most cases with small strain levels, especially in the ground around retaining walls, foundations and tunnels, typically in the order of 10−2 to 10−4 of strain. Although the best approach to estimate shear modulus seems to be based in measuring seismic wave velocities, deriving the parameter through correlations with in-situ tests is usually considered very useful for design practice.The use of Neural Networks for modeling systems has been widespread, in particular within areas where the great amount of available data and the complexity of the systems keeps the problem very unfriendly to treat following traditional data analysis methodologies. In this work, the use of Neural Networks and Support Vector Regression is proposed to estimate small strain shear modulus for sedimentary soils from the basic or intermediate parameters derived from Marchetti Dilatometer Test. The results are discussed and compared with some of the most common available methodologies for this evaluation.

The logo is not flat: evolving picture marks

From the boom of corporate identity in the 50s, 60 years have passed, and we now see picture marks become more complex and question axioms of identity design, like simplicity or bidimensionality. In these changing times, where access to technology and to information makes it possible for one to see the world as a ‘flat’ place [1], where virtually anyone with a computer can create, it is worth considering how much has changed and how much remains the same in picture marks design. Are the silent designers [2] — the technology and software — growing louder? Are picture marks mimicking each other? Are graphic marks following trendy solutions? It is clear the change of paradigms the new technologies have over the graphic zeitgeist. However, what are the consequences of the transformation in the modus operandi and its result in picture marks evolving solutions? And what does this evolution say about us? Being both a condensation of meaning about a corporation or institution and a rhetorical instrument by which to persuade an audience that a product or entity has distinctive and desirable qualities, picture marks are, therefore, a condensed representation of social identity. They are signs full of signification beyond themselves, representing ourselves and our world and by means of its analysis we can learn a bit more about our role as designers, our relation towards new technologies and foresee our role as designers in the future.

Adaptive modeling and high quality spectral estimation for speech enhancement

In this work an adaptive modeling and spectral estimation scheme based on a dual Discrete Kalman Filtering (DKF) is proposed for speech enhancement. Both speech and noise signals are modeled by an autoregressive structure which provides an underlying time frame dependency and improves time-frequency resolution. The model parameters are arranged to obtain a combined state-space model and are also used to calculate instantaneous power spectral density estimates. The speech enhancement is performed by a dual discrete Kalman filter that simultaneously gives estimates for the models and the signals. This approach is particularly useful as a pre-processing module for parametric based speech recognition systems that rely on spectral time dependent models. The system performance has been evaluated by a set of human listeners and by spectral distances. In both cases the use of this pre-processing module has led to improved results.

Análise e otimização de processo no departamento de manutenção de uma empresa industrial

As empresas no século XXI têm necessidade de reduzir os seus custos de manutenção para serem competitivas num mercado cada vez mais global, implementando a Manutenção Lean no setor diretamente responsável pela Manutenção e também estender a toda a organização. Este trabalho foi realizado no âmbito do estágio efetuado na empresa Lameirinho, empresa líder de Têxtil-Lar, localizada na zona de Guimarães e que possui um Departamento de Manutenção onde a fiabilidade e disponibilidade dos equipamentos é um aspeto importante bem como a sua manutenção a custos reduzidos. Assim, tendo como objetivo a melhoria do Departamento de Manutenção da empresa Lameirinho foi efetuada uma auditoria de Manutenção Lean com o intuito de determinar o estado atual, foram identificados problemas e oportunidades de melhoria bem como foram apresentadas soluções para os mesmos. Os benefícios que se obtêm com a implementação das soluções são, entre outros: melhor planeamento das intervenções de Manutenção com alocação no momento necessário dos recursos humanos e a disponibilização de peças assim como as intervenções de manutenção serem efetuadas quando a Produção menos necessita do equipamento produtivo; redução e eliminação das intervenções de Manutenção Corretiva de Emergência; redução dos custos de Manutenção na globalidade da empresa através dos benefícios obtidos e com impacto direto nos resultados económicos da empresa.