Impact of taxes on competition: the legal status quo in the European Union

Dissertação de mestrado em Direito dos Negócios, Europeu e Transnacional

Can oil, plastic and RAP wastes have a new life in novel asphalt mixtures?

The pavement recycling allows to reuse reclaimed asphalt pavement (RAP) or other waste materials in new asphalt mixtures for road construction or rehabilitation, thus re-ducing the use of virgin materials (aggregates and bitumen). Thus, the main aim of this study is to minimize the use of natural resources through the reuse of three waste materials: HDPE, mo-tor oil and RAP. Different amounts of waste motor oil and HDPE were added to an asphalt binder with 50% aged bitumen. The best solutions to produce the modified binders (4.5 to 5.0% HDPE and 10 % waste motor oil) performed as well as a conventional bitumen although they only used 35 % of virgin bitumen. Asphalt mixtures with 50 % RAP were produced with the selected modified binders, improving some characteristics in comparison with conventional asphalt mixtures. In conclusion, these wastes can revive in new asphalt mixtures.

Plastic waste use as aggregate and binder modifier in open-graded asphalts

Road pavements are very important infrastructures for the Society, but they can cause serious environmental impacts during construction, operation and rehabilitation phases. Thus, it is essential to develop surface paving solutions that promote not only the durability but also a comfortable and safe use. In fact, this work aims to study the properties of new opengraded mixtures for surface layers produced with plastic wastes. First, HDPE and EVA wastes were used as bitumen modifiers, and then another plastic waste (PEX) replaced part of the aggregates. After studying the modified binders, the open-graded mixtures were designed, and then they were tested concerning their particle loss, rutting resistance, surface texture and damping effect. It was concluded that both ways of using the plastic wastes can improve the mechanical and functional properties of the open-graded mixtures related to the pavement performance.

Business intelligence in banking: A literature analysis from 2002 to 2013 using Text Mining and latent Dirichlet allocation

telligence applications for the banking industry. Searches were performed in relevant journals resulting in 219 articles published between 2002 and 2013. To analyze such a large number of manuscripts, text mining techniques were used in pursuit for relevant terms on both business intelligence and banking domains. Moreover, the latent Dirichlet allocation modeling was used in or- der to group articles in several relevant topics. The analysis was conducted using a dictionary of terms belonging to both banking and business intelli- gence domains. Such procedure allowed for the identification of relationships between terms and topics grouping articles, enabling to emerge hypotheses regarding research directions. To confirm such hypotheses, relevant articles were collected and scrutinized, allowing to validate the text mining proce- dure. The results show that credit in banking is clearly the main application trend, particularly predicting risk and thus supporting credit approval or de- nial. There is also a relevant interest in bankruptcy and fraud prediction. Customer retention seems to be associated, although weakly, with targeting, justifying bank offers to reduce churn. In addition, a large number of ar- ticles focused more on business intelligence techniques and its applications, using the banking industry just for evaluation, thus, not clearly acclaiming for benefits in the banking business. By identifying these current research topics, this study also highlights opportunities for future research.

An immunity based configuration for multilayer single featured biometric authentication algorithms

Immune systems have been used in the last years to inspire approaches for several computational problems. This paper focus on behavioural biometric authentication algorithms’ accuracy enhancement by using them more than once and with different thresholds in order to first simulate the protection provided by the skin and then look for known outside entities, like lymphocytes do. The paper describes the principles that support the application of this approach to Keystroke Dynamics, an authentication biometric technology that decides on the legitimacy of a user based on his typing pattern captured on he enters the username and/or the password and, as a proof of concept, the accuracy levels of one keystroke dynamics algorithm when applied to five legitimate users of a system both in the traditional and in the immune inspired approaches are calculated and the obtained results are compared.

Enrollment time as a requirement for biometric hand recognition systems

Biometric systems are increasingly being used as a means for authentication to provide system security in modern technologies. The performance of a biometric system depends on the accuracy, the processing speed, the template size, and the time necessary for enrollment. While much research has focused on the first three factors, enrollment time has not received as much attention. In this work, we present the findings of our research focused upon studying user’s behavior when enrolling in a biometric system. Specifically, we collected information about the user’s availability for enrollment in respect to the hand recognition systems (e.g., hand geometry, palm geometry or any other requiring positioning the hand on an optical scanner). A sample of 19 participants, chosen randomly apart their age, gender, profession and nationality, were used as test subjects in an experiment to study the patience of users enrolling in a biometric hand recognition system.

Uma metodologia de diagnóstico de problemas de qualidade em PME

Este artigo propõe uma nova metodologia para Pequenas e Médias Empresas (PME), destinada a caracterizar o seu desempenho na gestão da qualidade, destacando pontos fracos e áreas de melhoria. A metodologia visa identificar as principais causas dos problemas de qualidade e ajuda a estabelecer prioridades na definição de iniciativas de melhoria. Trata-se de uma metodologia de diagnóstico fácil de implementar por empresas com baixo nível de maturidade na gestão da qualidade. A metodologia está organizada em seis etapas diferentes que incluem a recolha de informação sobre processos e subprocessos de gestão da qualidade, definidos com base na Trilogia de Juran, e sobre categorias de resultados preestabelecidas. Para aperfeiçoar e validar a metodologia proposta, foram realizados dois casos de estudo. A aplicação da metodologia foi bem sucedida em ambos os casos. Posteriormente, foi elaborado um relatório sobre o estado da qualidade em cada empresa, que inclui a definição de prioridades de eliminação das causas na origem de maus desempenhos. A metodologia pode ser adaptada para melhor se adequar às necessidades de empresas de diferentes setores, quer pela revisão dos seus processos, quer pela integração de novas ferramentas ou pelo aperfeiçoamento das existentes. Devido à sua simplicidade e abrangência, considera-se que a metodologia desenvolvida pode ser aplicada como ferramenta de autodiagnóstico para a melhoria contínua.

Implementation of a lean six sigma project in a production line

Companies from the motorcycles components branch are dealing with a dynamic environment, resulting from the introduction of new products and the increase of market demand. This dynamic environment requires frequent changes in production lines and requires flexibility in the processes, which can cause reductions in the level of quality and productivity. This paper presents a Lean Six Sigma improvement project performed in a production line of the company's machining sector, in order to eliminate losses that cause low productivity, affecting the fulfillment of the production plan and customer satisfaction. The use of Lean methodology following the DMAIC stages allowed analyzing the factors that influence the line productivity loss. The major problems and causes that contribute to a reduction on productivity and that were identified in this study are the lack of standardization in the setup activities and the excessive stoppages for adjustment of the processes that caused an increase of defects. Control charts, Pareto analysis and cause-and-effect diagrams were used to analyze the problem. On the improvement stage, the changes were based on the reconfiguration of the line layout as well as the modernization of the process. Overall, the project justified an investment in new equipment, the defective product units were reduced by 84% and an increase of 29% of line capacity was noticed.

Predicting plateau pressure in intensive medicine for ventilated patients

Barotrauma is identified as one of the leading diseases in Ventilated Patients. This type of problem is most common in the Intensive Care Units. In order to prevent this problem the use of Data Mining (DM) can be useful for predicting their occurrence. The main goal is to predict the occurence of Barotrauma in order to support the health professionals taking necessary precautions. In a first step intensivists identified the Plateau Pressure values as a possible cause of Barotrauma. Through this study DM models (classification) where induced for predicting the Plateau Pressure class (>=30 cm

Clustering barotrauma patients in ICU–A data mining based approach using ventilator variables

Lecture Notes in Computer Science, 9273

Intelligent decision support to predict patient barotrauma risk in intensive care units

The occurrence of Barotrauma is identified as a major concern for health professionals, since it can be fatal for patients. In order to support the decision process and to predict the risk of occurring barotrauma Data Mining models were induced. Based on this principle, the present study addresses the Data Mining process aiming to provide hourly probability of a patient has Barotrauma. The process of discovering implicit knowledge in data collected from Intensive Care Units patientswas achieved through the standard process Cross Industry Standard Process for Data Mining. With the goal of making predictions according to the classification approach they several DM techniques were selected: Decision Trees, Naive Bayes and Support Vector Machine. The study was focused on identifying the validity and viability to predict a composite variable. To predict the Barotrauma two classes were created: “risk” and “no risk”. Such target come from combining two variables: Plateau Pressure and PCO2. The best models presented a sensitivity between 96.19% and 100%. In terms of accuracy the values varied between 87.5% and 100%. This study and the achieved results demonstrated the feasibility of predicting the risk of a patient having Barotrauma by presenting the probability associated.

Foreword [Occupational Safety and Hygiene III]

[Excerpt] This book is the third edition of this series of publications that are entitled “Occupational Safety and Hygiene”. The main contributions for this book were, once again, the works previously submitted and approved to be presented at the annual Symposium of the Portuguese Society of Occupational Safety and Hygiene (SPOSHO), which is celebrating its 11th edition in 2015. The SHO2015—International Symposium on Occupational Safety and Hygiene, similarly to the past seven years, was held in the School of Engineering at University of Minho in Guimarães, Portugal.

Strategic planning of electricity systems: Integrating renewable energies

Tese de Doutoramento - Programa Doutoral em Engenharia Industrial e Sistemas (PDEIS)