Multi-objective robustness analysis of the polymer extrusion process

This paper presents a new approach to robustness analysis in multi-objective optimization problems aimed at obtaining the most robust Pareto front solutions and also at distributing solutions along the most robust regions of the optimal Pareto set. The methodology proposed is applied to a single screw polymer extrusion with the aim of obtaining the most robust solutions for the optimization of the extruder geometry. The non-dominated solutions obtained take into account their degree of robustness and the distribution of such solutions along the Pareto front accordingly with specific algorithm parameter values. The results obtained have physical meaning and are in accordance with the practical knowledge about the industrial process studied

Path integral learning of multidimensional movement trajectories

This paper explores the use of Path Integral Methods, particularly several variants of the recent Path Integral Policy Improvement (PI 2 ) algorithm in multidimensional movement parametrized policy learning. We rely on Dynamic Movement Primitives (DMPs) to codify discrete and rhythmic trajectories, and apply the PI 2 -CMA and PI BB methods in the learning of optimal policy parameters, according to different cost functions that inherently encode movement objectives. Additionally we merge both of these variants and propose the PI BB -CMA algorithm, comparing all of them with the vanilla version of PI 2 . From the obtained results we conclude that PI BB -CMA surpasses all other methods in terms of convergence speed and iterative final cost, which leads to an increased interest in its application to more complex robotic problems.FEDER Funding supported by the Operational Program Competitive Factors - COMPETE andNational Funding supported by the FCT - Portuguese Science Foundation through scholarship UMINHO/BI/40/2012 inserted in project PTDC/EEACRO/100655/2008 and also project FCOMP-01-0124-FEDER-02267

“YOU TAKE CARE OF THE BABY’S CLOTHES AND I TAKE CARE OF THE DELIVERY” – COMMUNICATION BETWEEN PROFESSIONALS AND PATIENTS AND DECISIONS ABOUT THE MODE OF DELIVERY IN THE PRIVATE SECTOR IN SÃO PAULO, BRAZIL

High rates of cesarean sections and invasive interventions in labor and delivery, disregarding recommendations on safety and quality of healthcare characterize childbirth care in the Brazilian private sector. We aimed to understand how professionals and patients communicate about risks and benefits of the interventions and take decisions in the Internet era. We interviewed 28 professionals and female users of the private health sector in São Paulo, including those we will call “typical” and “atypical” of the national scenario. The communication about procedures among “typical” patients was scarce, biased or actively blocked, tending to strengthen a behaved attitude. “Atypical” patients sought further information from professionals and peer groups and used more Internet resources (discussion lists, evidence websites and narrative banks). The availability of such information allows more women to seek a care aligned to their values and notions of rights, frequently confronting the medical authority, creating needs to be (or not to be) satisfied

Adaptations of a resources system selection problem of Distributed/Agile/Virtual Enterprises for using genetic algorithms

The selection of resource systems is still a difficult matter to solve in distributed / Agile / Virtual enterprises ( D/A/V Es ) integration. Attempts to solve the resources selection problem, has originated several models and consequently different algorithms have been applied to obtain solutions. The exact algorithms have good performance (in terms of computational time) for low dimension problems. However, become ineffective as the complexity increases. Genetic algorithms are considered robust and versatile. These have been applied to complex problems in several application areas and gained popularity in innumerable research works. To improve the computational time in solving the resources selection problem, we pretend to apply a genetic algorithm. Due to the characteristics of the model, the application of this algorithm forced adjustments in the initial model. In this work, we present the adaptations performed in the study model in order to use genetic algorithms.info:eu-repo/semantics/publishedVersio

A neuroevolutionary approach to feature selection using multiobjective evolutionary algorithms

Feature selection plays a central role in predictive analysis where datasets have hundreds or thousands of variables available. It can also reduce the overall training time and the computational costs of the classifiers used. However, feature selection methods can be computationally intensive or dependent of human expertise to analyze data. This study proposes a neuroevolutionary approach which uses multiobjective evolutionary algorithms to optimize neural network parameters in order to find the best network able to identify the most important variables of analyzed data. Classification is done through a Support Vector Machine (SVM) classifier where specific parameters are also optimized. The method is applied to datasets with different number of features and classes.FCT - Fundação para a Ciência e Tecnologia in the scope of the projects: PEst-OE/EEI/UI0319/2014, UID/MAT/00013/2013, UID/CEC/ 00319/2019 and the European project MSCA-RISE-2015, NEWEX, with reference 734205

O Kaizen como uma metodologia de melhoria contínua: estudo de caso de uma empresa de peças automóvel

Dissertação submetida como requisito parcial para obtenção do grau de Mestre em Ciências Empresariais – Ramo Gestão de PMENum mercado cada vez mais concorrencial e globalizado, fatores relacionados com a Qualidade e Sustentabilidade têm ganho ênfase. Este panorama tem levado as organizações a adotarem uma nova abordagem de Gestão, visando a criação de vantagem competitiva, sem grandes investimentos. Procura-se aumentar a produtividade e a competitividade pela via da minimização e/ou eliminação do desperdício e/ou da otimização dos recursos disponíveis. O foco passou a ser o desenvolvimento de uma cultura de melhoria contínua pois só assim ela se prolongará no tempo e se propagará por toda a Organização. Neste sentido, motivar e manter os colaboradores comprometidos com a Organização revela-se um dos maiores desafios para os gestores. A presente dissertação foi desenvolvida na Caetano Parts, como resposta às barreiras com que se deparava ao aumento da produtividade e da competitividade. Procurou-se, através da implementação do Kaizen Diário, a criação de um círculo virtuoso, em que o comprometimento de todos promoveria uma ação diária tendo em vista a melhoria e otimização dos processos, a eliminação do desperdício e o aumento da produtividade. Com a sua implementação verificaram-se algumas melhorias no dia-a-dia organizacional: um maior comprometimento e motivação dos colaboradores e uma atitude mais proactiva e preventiva face ao trabalho.In an increasingly competitive and globalized market, factors related to Quality and Sustainability have gained emphasis. This panorama has led the organizations to adopt a new Management approach, aiming at creating a competitive advantage without major investments. It seeks to increase productivity and competitiveness by minimizing and/or eliminating waste and/or optimizing available resources. The focus has been on developing a culture of continuous improvement because only then will it last in time and spread throughout the Organization. In this sense, motivating and maintaining employees committed to the Organization proves to be one of the greatest challenges for managers. The present dissertation was developed in Caetano Parts, in response to the barriers that faced the increase of productivity and competitiveness. Through the implementation of Daily Kaizen, we sought to create a virtuous circle in which everyone's commitment would promote daily action in order to improve and optimize processes, eliminate waste and increase productivity. With its implementation, there were some improvements in the organizational day-to-day: greater commitment and motivation of employees and a more proactive and preventive attitude towards work

Cork oak endophytic fungi as potential biocontrol agents against biscogniauxia mediterranea and diplodia corticola

An increase in cork oak diseases caused by Biscogniauxia mediterranea and Diplodia corticola has been reported in the last decade. Due to the high socio-economic and ecologic importance of this plant species in the Mediterranean Basin, the search for preventive or treatment measures to control these diseases is an urgent need. Fungal endophytes were recovered from cork oak trees with different disease severity levels, using culture-dependent methods. The results showed a higher number of potential pathogens than beneficial fungi such as cork oak endophytes, even in healthy plants. The antagonist potential of a selection of eight cork oak fungal endophytes was tested against B. mediterranea and D. corticola by dual-plate assays. The tested endophytes were more efficient in inhibiting D. corticola than B. mediterranea growth, but Simplicillium aogashimaense, Fimetariella rabenhorstii, Chaetomium sp. and Alternaria alternata revealed a high potential to inhibit the growth of both. Simplicillium aogashimaense caused macroscopic and microscopic mycelial/hyphal deformations and presented promising results in controlling both phytopathogens’ growth in vitro. The evaluation of the antagonistic potential of non-volatile and volatile compounds also revealed that A. alternata compounds could be further explored for inhibiting both pathogens. These findings provide valuable knowledge that can be further explored in in vivo assays to find a suitable biocontrol agent for these cork oak diseases.This work was supported by FEDER funds through COMPETE (Programa Operacional Factores de Competitividade) and by national funds by FCT (Fundacao para a Ciencia e a Tecnologia) in the framework of the project POCI-01-0145-FEDER-028635, as well as for financial support to BioISI (UIDB/04046/2020) and CIMO (UID/AGR/00690/2020) by national funds by FCT/MCTES/PIDDAC. D. Costa thanks FCT for PhD grant SFRH/BD/120516/2016

Optimization of single screw extrusion

Multi-objective evolutionary optimization algorithms (MOEA) are used for the optimization of plasticating single screw extrusion. For this purpose, a specific MOEA is linked to available process modelling routines. The methodology is used to set the operating conditions and identify the screw geometry for a specific case study, thus demonstrating the practical utility of this approach.Project H2020-MSCA-RISE-2016-734205info:eu-repo/semantics/publishedVersio