Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.

Lightweight concrete masonry units based on processed granulate of corn cob as aggregate

A research work was performed in order to assess the potential application of processed granulate of corn cob (PCC) as an alternative lightweight aggregate for the manufacturing process of lightweight concrete masonry units (CMU). Therefore, CMU-PCC were prepared in a factory using a typical lightweight concrete mixture for non-structural purposes. Additionally, lightweight concrete masonry units based on a currently applied lightweight aggregate such as expanded clay (CMU-EC) were also manufactured. An experimental work allowed achieving a set of results that suggest that the proposed building product presents interesting material properties within the masonry wall context. Therefore, this unit is promising for both interior and exterior applications. This conclusion is even more relevant considering that corn cob is an agricultural waste product.

Smart platform towards batteries analysis based on internet-of-things

This paper presents a new approach of pre-defined profiles, based in different voltage and current values, to control the charging and discharging processes of batteries in order to assess their performance. This new approach was implemented in a prototype that was specially developed for such purpose. This prototype is a smart power electronics platform that allows to perform batteries analysis and to control the charging and discharging processes through a web application using pre-defined profiles. This platform was developed aiming to test different batteries technologies. Considering the relevance of the energy storage area based in batteries, especially for the batteries applied to electric mobility systems, this platform allows to perform controlled tests to the batteries, in order to analyze the batteries performance under different scenarios of operation. Besides the results obtained with the batteries, this work also intends to produce results that can contribute to an involvement in the strengthening of the Internet-of-Things.

Hand gesture recognition system based in computer vision and machine learning

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

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.

Enzymatic processing of protein-based fibers

Wool and silk are major protein fiber materials used by the textile industry. Fiber protein structure-function relationships are briefly described here, and the major enzymatic processing routes for textiles and other novel applications are deeply reviewed. Fiber biomodification is described here with various classes of enzymes such as protease, transglutaminase, tyrosinase, and laccase. It is expected that the reader will get a perspective on the research done as a basis for new applications in other areas such as cosmetics and pharma.

High performance electromechanical actuators based on ionic liquid/poly(vinylidene fluoride)

Due to the increasing need of low voltage actuators, independent from electrochemical processes, electroactive actuators based on poly(vinylidene fluoride) composites with 10, 25 and 40 % of 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, [C2mim] [NTf2], ionic liquid are prepared by solvent casting and melting. We show that the charge structure of [C2mim] [NTf2] induces the complete piezoelectric -phase crystallization of the PVDF within the composite and decreases its crystallinity fraction significantly. [C2mim] [NTf2] also works as a plasticizer of PVDF, reducing the elastic modulus down to 12 % of the initial value. Moreover, the composites show significant displacement and bending under applied voltages of 2, 5 and 10 Vpp. The displacement and bending of the composite membranes are also evaluated as a function of [C2mim] [NTf2] content and sample thickness. Increasing amounts of ionic liquid result in larger deformations independently of the applied voltage.

Tailored magnetic and magnetoelectric responses of polymer-based composites

The manipulation of electric ordering with applied magnetic fields has been realized on magnetoelectric (ME) materials, however, their ME switching is often accompanied by significant hysteresis and coercivity that represents, for some applications, a severe weakness. To overcome this obstacle, this work focus on the development of a new type of ME polymer nanocomposites that exhibits tailored ME response at room temperature. The multiferroic nanocomposites are based on three different ferrite nanoparticles, Zn0.2Mn0.8Fe2O4 (ZMFO), CoFe2O4 (CFO) and Fe3O4 (FO), dispersed in a piezoelectric co-polymer poly(vinylindene fluoride-trifluoroethylene), P(VDF-TrFE), matrix. No substantial differences were detected on the time-stable piezoelectric response of the composites (≈ -28 pC.N−1) with distinct ferrite fillers and for the same ferrite content of 10wt.%. Magnetic hysteresis loops from pure ferrite nanopowders showed different magnetic responses. ME results of the nanocomposite films with 10wt.% ferrite content revealed that the ME induced voltage increases with increasing DC magnetic field until a maximum of 6.5 mV∙cm−1∙Oe−1, at an optimum magnetic field of 0.26 T, and 0.8 mV∙cm−1∙Oe−1, at an optimum magnetic field of 0.15T, for the CFO/P(VDF-TrFE) and FO/P(VDF-TrFE) composites, respectively. On the contrary, the ME response of the ZMFO/P(VDF-TrFE) exposed no hysteresis and high dependence on the ZMFO filler content. Possible innovative applications such as memories and information storage, signal processing, ME sensors and oscillators have been addressed for such ferrite/PVDF nanocomposites.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Mechanical, fatigue and wear properties of sintered Carbon Nanotube-based functionally graded materials

Tese de Doutoramento Engenharia Mecânica

Design of assemblies based on polymer-coated quantum dots and organic dye

During last years, photophysical properties of complexes of semiconductor quantum dots (QDs) with organic dyes have attracted increasing interest. The development of different assemblies based on QDs and organic dyes allows to increase the range of QDs applications, which include imaging, biological sensing and electronic devices.1 Some studies demonstrate energy transfer between QDs and organic dye in assemblies.2 However, for electronic devices purposes, a polymeric matrix is required to enhance QDs photostability. Thus, in order to attach the QDs to the polymer surface it is necessary to chemically modify the polymer to induce electronic charges and stabilize the QDs in the polymer. The present work aims to investigate the design of assemblies based on polymer-coated QDs and an integrated acceptor organic dye. Polymethylmethacrylate (PMMA) and polycarbonate (PC) were used as polymeric matrices, and nile red as acceptor. Additionally, a PMMA matrix modified with 2-mercaptoethylamine is used to improve the attachment between both the donor (QDs) and the acceptor (nile red), as well as to induce a covalent bond between the modified PMMA and the QDs. An enhancement of the energy transfer efficiency by using the modified PMMA is expected and the resulting assembly can be applied for energy harvesting.

Extreme value Birnbaum-Saunders regression models applied to environmental data

Extreme value models are widely used in different areas. The Birnbaum–Saunders distribution is receiving considerable attention due to its physical arguments and its good properties. We propose a methodology based on extreme value Birnbaum–Saunders regression models, which includes model formulation, estimation, inference and checking. We further conduct a simulation study for evaluating its performance. A statistical analysis with real-world extreme value environmental data using the methodology is provided as illustration.

Postharvest shelf life extension of blueberries using a chitosan-based edible coating containing aloe vera juice

Poster

Assessment and management of the geomorphological heritage of Monte Pindo (NW Spain): a landscape as a symbol of identity

This study focuses on the granite mountain known as Monte Pindo (627 m above sea level) in the Autonomous Community of Galicia (NW Spain). This territory is included in the area classified as “Costa da Morte” in the “Politica de Ordenación Litoral” (POL) (Coastal Planning Policy) for the region of Galicia. This coastal unit, located between “Rías Baixas” and “Cape Fisterra” has great potential for demonstrating geological processes and its geomorphological heritage is characterized by a high degree of geodiversity of granite landforms. The main objective of our work is to assess the geomorphological heritage of the site, thus revealing its wide geodiversity. We shall analyze and highlight: its scientific value, developing an inventory of granite landforms; its educational valuel and its geotouristic potential. It must be ensured that the Administration understands that natural diversity is composed of both geodiversity and biodiversity. Only then will the sustainable management of Monte Pindo become possible by integrating natural and cultural heritage values. The goal is to ensure that Monte Pindo and its immediate surroundings become a geopark with the aim of promoting local development projects based on the conservation and valorization of its geological heritage.

Single-function approach to calibrating whatman n.º 42 filter paper based on suction versus water content relationships

Several suction–water-content (s-w) calibrations for the filter paper method (FPM) used for soil-suction measurement have been published. Most of the calibrations involve a bilinear function (i.e., two different equations) with an inflection point occurring at 60 kPaapplied herein to data obtained from three establish bilinear calibrations (six equations) for W42 filter paper to determine the two fitting parameters of the continuous function. An experimental evaluation of the new calibration show that the suctions estimated by the contact FPM test using the proposed function compare well with suctions measured by other laboratory techniques for two different soils for the suction range of 50 kPa