Foamed Bitumen: an alternative way of producing asphalt mixtures

With the constant need to improve and make the production of asphalt mixtures more sustainable, new production techniques have been developed, the implementation of which implies the correct knowledge of their performance. One of the most promising asphalt production techniques is the use of foamed bitumen. However, it is essential to understand how this binder will behave when subject to the expansion process. The loss of volume of the foamed bitumen could be translated by a decay curve, which allows to determine the ideal temperature and water content added to the bitumen in order to assure adequate conditions to the mix the bitumen with the aggregates. On the present study, a conventional 160/220 pen grade bitumen was tested by using different temperatures and water contents, and it was concluded that the optimum temperature for the production of foamed bitumen (with the studied bitumen) is 150 ºC, which corresponds to a viscosity of 0.1 Pa.s. The water content mostly influence the half-life of the bitumen foam, resulting in quicker volume reductions for higher water contents.

Study of the interaction between asphalt and plastic wastes in new polymer modified binders (PMB)

The aim of this study is evaluating the interaction between several base pen grade asphalt binders (35/50, 50/70, 70/100, 160/220) and two different plastic wastes (EVA and HDPE), for a set of new polymer modified binders produced with different amounts of both plastic wastes. After analysing the results obtained for the several polymer modified binders evaluated in this study, including a commercial modified binder, it can be concluded that the new PMBs produced with the base bitumen 70/100 and 5% of each plastic waste (HDPE or EVA) results in binders with very good performance, similar to that of the commercial modified binder.

Marketing socioambiental: o estudo de caso da participação popular em áreas de alta densidade de postes e linhas de alta tensão em Portugal

O presente artigo centra-se na análise do marketing socioambiental, promovido por empresas do setor energético, bem como o papel da sociedade civil, por intermédio, dos movimentos populares de reivindicação, contra os postes e linhas de alta e muito alta tensão em áreas residenciais na União Europeia e, especificamente, em Portugal. O processo de urbanização crescente e o modo de vida urbano desenfreado acarretaram mudanças substanciais no tecido urbano, sobretudo, no que diz respeito ao avanço das linhas aéreas de energia elétrica. Desde a década de 1960, uma série de estudos foram desenvolvidos sobre os efeitos destas infraestruturas tecnológicas em áreas residenciais. Apesar do intenso debate ainda não existem resultados consensuais quanto à sua influência na saúde das populações. Não obstante, diversos organismos internacionais, tais como, a Organização Mundia l de Saúde (OMS) e a Comissão Internacional de Proteção Contra Radiação Não - Ionizante (ICNIRP), já estabeleceram parâmetros de precaução, a partir da fixação de valores de exposição, tanto em termos ocupacionais , quanto para a população. Neste sentido, objetiva-se com a presente comunicação analisar o papel do marketing socioambiental, a partir da participação popular, dos movimentos internacionais e nacionais contra a alta tensão, sobretudo em Portugal. A pesquisa centrou-se numa abordagem qualitativa de fontes secundárias de dois blogues e cinco jornais nacionais que apresentavam notícias sobre a constituição e as manifestações realizadas pelo Movimento Nacional Contra Linhas de Alta Tensão em Zonas Habitadas. Este Movimento teve a sua origem no Sul de Portugal e difundiu-se por todo o país recrutando indivíduos preocupados com a instalação das novas e das já existentes linhas aéreas de energia elétrica. O Movimento ganhou força a nível nacional com o apoio de partidos políticos. Também foi realizado trabalho de campo em junho de 2014.

Effects of residues on the degradation of PHA produced from mixed microbial cultures and processed in extrusion

Thermal degradation upon melting is one of the major drawbacks reported for polyhydroxyalkanoates (PHA). However, the role of residues originating from the fermentation and the extraction steps on the thermal stability of this class of biopolymers still needs to be clarified. In the particular case of PHA produced from mixed microbial cultures (MMC), this topic is even less documented in the literature. Here, two polyhydroxy(butyrate-co-valerate) (PHBV) produced from MMC enriched in PHA accumulating organisms and fed with cheese whey were studied. A micro extrusion line is used to produce filaments and assess the processability and the degradation of processed PHBV. The prototype micro extrusion line allows for studying grams of materials. The two PHBV contain 18 mol% HV. PHBV was recovered with 11 wt% residues, and further submitted to a purification procedure resulting in a second biopolyester containing less than 2 wt% impurities. The thermorheological characterization of the two PHBV is first presented, together with their semicrystalline properties. Then the processing windows of the two biopolyesters are presented. Finally, the properties of extruded filaments are reported and the thermomechanical degradation of PHBV is extensively studied. The structure was assessed by wide angle X-ray diffraction, mechanical and rheological properties are reported, thermal properties are studied with differential scanning calorimetry and thermogravimetric analysis, whereas Fourier Transform Infrared spectroscopy was used to assess the impact of the extrusion on PHBV chemical structure. All results obtained with the two PHBV are compared to assess the effects of residues on both PHBV processability and degradation.

In-line rheo-optical characterization during small-scale polymer processing and compounding

As increasingly more sophisticated materials and products are being developed and times-to-market need to be minimized, it is important to make available fast response characterization tools using small amounts of sample, capable of conveying data on the relationships between rheological response, process-induced material structure and product characteristics. For this purpose, a single / twin-screw mini-extrusion system of modular construction, with well-controlled outputs in the range 30-300 g/h, was coupled to a in- house developed rheo-optical slit die able to measure shear viscosity and normal-stress differences, as well as performing rheo-optical experiments, namely small angle light scattering (SALS) and polarized optical microscopy (POM). In addition, the mini-extruder is equipped with ports that allow sample collection, and the extrudate can be further processed into products to be tested later. Here, we present the concept and experimental set-up [1, 2]. As a typical application, we report on the characterization of the processing of a polymer blend and of the properties of extruded sheets. The morphological evolution of a PS/PMMA industrial blend along the extruder, the flow-induced structures developed and the corresponding rheological characteristics are presented, together with the mechanical and structural characteristics of produced sheets. The application of this experimental tool to other material systems will also be discussed.

[An editorial to] Recent Advances on Knowledge Discovery and Business Intelligence

Special issue guest editorial, June, 2015.

Using customer lifetime value to improve the prediction of bank deposit subscription in telemarketing campaigns

Customer lifetime value (LTV) enables using client characteristics, such as recency, frequency and monetary (RFM) value, to describe the value of a client through time in terms of profitability. We present the concept of LTV applied to telemarketing for improving the return-on-investment, using a recent (from 2008 to 2013) and real case study of bank campaigns to sell long- term deposits. The goal was to benefit from past contacts history to extract additional knowledge. A total of twelve LTV input variables were tested, un- der a forward selection method and using a realistic rolling windows scheme, highlighting the validity of five new LTV features. The results achieved by our LTV data-driven approach using neural networks allowed an improvement up to 4 pp in the Lift cumulative curve for targeting the deposit subscribers when compared with a baseline model (with no history data). Explanatory knowledge was also extracted from the proposed model, revealing two highly relevant LTV features, the last result of the previous campaign to sell the same product and the frequency of past client successes. The obtained results are particularly valuable for contact center companies, which can improve pre- dictive performance without even having to ask for more information to the companies they serve.

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.

Development of autonomous maintenance in a furniture company

This article presents a work performed in the maintenance department of a furniture company in Portugal, in order to develop and implement autonomous maintenance. The main objective of the project was related to the objective to increase and make effective the autonomous maintenance tasks performed by production operators, and in this way avoiding unplanned downtime due to equipment failures. Although some autonomous maintenance tasks were already carried out within the company, a preliminary study revealed weaknesses in the application of this tool. In the initial phase of this pilot project, the main problems encountered at the level of autonomous maintenance were related to the lack of time to carry out these tasks, showing that the stipulated procedures were far from the real needs of the company. To solve these problems a pilot project was conducted, making several changes in the performance of autonomous maintenance tasks, making them standard and adapted to reality of each production line. There was a general improvement in the factory indicators, and essentially there was a behavioral change, since the operators felt that their opinions were taking into account and began to understand the importance of small tasks performed by them.

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Generic system for human-computer gesture interaction: applications on sign language recognition and robotic soccer refereeing

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for human-computer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of visionbased interaction systems could be the same for all applications and thus facilitate the implementation. For hand posture recognition, a SVM (Support Vector Machine) model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM (Hidden Markov Model) model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications. To validate the proposed framework two applications were implemented. The first one is a real-time system able to interpret the Portuguese Sign Language. The second one is an online system able to help a robotic soccer game referee judge a game in real time.

Vision-based portuguese sign language recognition system

Vision-based hand gesture recognition is an area of active current research in computer vision and machine learning. Being a natural way of human interaction, it is an area where many researchers are working on, with the goal of making human computer interaction (HCI) easier and natural, without the need for any extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them, for example, to convey information. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. Hand gestures are a powerful human communication modality with lots of potential applications and in this context we have sign language recognition, the communication method of deaf people. Sign lan- guages are not standard and universal and the grammars differ from country to coun- try. In this paper, a real-time system able to interpret the Portuguese Sign Language is presented and described. Experiments showed that the system was able to reliably recognize the vowels in real-time, with an accuracy of 99.4% with one dataset of fea- tures and an accuracy of 99.6% with a second dataset of features. Although the im- plemented solution was only trained to recognize the vowels, it is easily extended to recognize the rest of the alphabet, being a solid foundation for the development of any vision-based sign language recognition user interface system.

Generic system for human-computer gesture interaction

Hand gestures are a powerful way for human communication, with lots of potential applications in the area of human computer interaction. Vision-based hand gesture recognition techniques have many proven advantages compared with traditional devices, giving users a simpler and more natural way to communicate with electronic devices. This work proposes a generic system architecture based in computer vision and machine learning, able to be used with any interface for humancomputer interaction. The proposed solution is mainly composed of three modules: a pre-processing and hand segmentation module, a static gesture interface module and a dynamic gesture interface module. The experiments showed that the core of vision-based interaction systems can be the same for all applications and thus facilitate the implementation. In order to test the proposed solutions, three prototypes were implemented. For hand posture recognition, a SVM model was trained and used, able to achieve a final accuracy of 99.4%. For dynamic gestures, an HMM model was trained for each gesture that the system could recognize with a final average accuracy of 93.7%. The proposed solution as the advantage of being generic enough with the trained models able to work in real-time, allowing its application in a wide range of human-machine applications.