Product extension services deployment platform

Due to the progresses made in the branch of embedded technologies, manufacturers are becoming able to pack their shop floor level manufacturing resources with even more complex functionalities. This technological progression is radically changing the way production systems are designed and deployed, as well as, monitored and controlled. The dissemination of smart devices inside production processes confers new visibility on the production system while enabling for a more efficient and effective management of the operations. By turning the current manufacturing resources functionalities into services based on a Service Oriented Architecture (SOA), in order to expose them as a service to the user, the binomial manufacturing resource/service will push the entire manufacturing enterprise visibility to another level while enabling the global optimization of the operations and processes of a production system while, at the same time, supporting its accommodation to the operational spike easily and with reduced impact on production. The present work implements a Cloud Manufacturing infrastructure for achieving the resource/service value-added i.e. to facilitate the creation of services that are the composition of currently available atomic services. In this context, manufacturing resource virtualization (i.e. formalization of resources capabilities into services accessible inside and outside the enterprise) and semantic representation/description are the pillars for achieving resource service composition. In conclusion, the present work aims to act on the manufacturing resource layer where physical resources and shop floor capabilities are going to be provided to the user as a SaaS (Software as a Service) and/or IaaS (Infrastructure as a Service).

Comuns: An Open-Data Provider, Explorer and Analytic Toolbox Based on FOSS

Contém resumo

Unilever food solutions new digital CRM platform- what is the combination of tools, processes and content that will help Unilever food solutions grow his business?

Unilever Food Solutions new digital CRM1 Platform - What is the combination of tools, processes and content that will help Unilever Food Solutions grow his business? Unilever Food Solutions (UFS) intend to create a new online platform to enable it to communicate with segments of the markets, which have previously been too difficult to reach. Specifically targeted at Chefs and other food professionals, the aim is to create an interactive website, which delivers value to its intended users by providing a variety of relevant content and functions, while simultaneously opening up a potential transactional channel to those same users.

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.

Estudo de viabilidade de paralelização de códigos de análise de dados em PROOF

Dissertação de mestrado em Engenharia Informática

Monitoring and analysis of queries in distributed databases

Dissertação de Mestrado em Engenharia Informática

Pervasive business intelligence platform to improve the quality of decision process in primary and secondary education – A Portuguese case study

Business Intelligence (BI) can be seen as a method that gathers information and data from information systems in order to help companies to be more accurate in their decision-making process. Traditionally BI systems were associated with the use of Data Warehouses (DW). The prime purpose of DW is to serve as a repository that stores all the relevant information required for making the correct decision. The necessity to integrate streaming data became crucial with the need to improve the efficiency and effectiveness of the decision process. In primary and secondary education, there is a lack of BI solutions. Due to the schools reality the main purpose of this study is to provide a Pervasive BI solution able to monitoring the schools and student data anywhere and anytime in real-time as well as disseminating the information through ubiquitous devices. The first task consisted in gathering data regarding the different choices made by the student since his enrolment in a certain school year until the end of it. Thereafter a dimensional model was developed in order to be possible building a BI platform. This paper presents the dimensional model, a set of pre-defined indicators, the Pervasive Business Intelligence characteristics and the prototype designed. The main contribution of this study was to offer to the schools a tool that could help them to make accurate decisions in real-time. Data dissemination was achieved through a localized application that can be accessed anywhere and anytime.

A relational algebra approach to ETL modeling

The MAP-i Doctoral Programme in Informatics, of the Universities of Minho, Aveiro and Porto

A cost study of common surface finish systems for steel structures

This paper presents part of a study aimed at finding a suitable, yet cost-effective, surface finish for a steel structure subject to the car washing environment and corrosive chemicals. The initial, life cycle and average equivalent annual (AEAC) costs for surface finishing methods were calculated for a steel structure using the LCCC algorithm developed by American Galvanizers Association (AGA). The cost study consisted of 45 common surface finish systems including: hot-dip galvanization (HDG), metallization, acrylic, alkyd and epoxy as well as duplex coatings such as epoxy zinc and inorganic zinc (IOZ). The results show that initial, life cycle and AEAC costs for hot dip galvanization are the lowest among all the other methods, followed by coal tar epoxy painting. The annual average cost of HDG for this structure was estimated about €0.22/m2, while the other cost-effective alternatives were: IOZ, polyurea, epoxy waterborne and IOZ/epoxy duplex coating.

Poly(vinylidene fluoride-trifluoroethylene)/NAY zeolite hybrid membranes as a drug release platform applied to ibuprofen release

Poly(vinylidene fluoride-trifluoroethylene)/NaY zeolite composite membranes were prepared by solvent casting and evaluated as a suitable drug release platform through the evaluation of loading and release of ibuprofen. The membranes were characterized at the morphological, structural and mechanical levels. The 1H-NMR spectra indicate that only the membranes with 16 and 32 % of NaY were useful for IBU encapsulation and the drug release was followed by UV-Vis spectroscopy. The release profile is independent of the zeolite content and can be described by the Korsmeyer-Peppas model. The membrane with 32 % zeolite content releases more than double IBU amount when compared with the membrane with 16 % showing that zeolite content allows tailoring membrane drug release content for specific applications. The drug release platform developed in this work is suitable for other drugs and applications.

Color change using HSB color system of dental resin composites immersed in different common Amazon region beverages

The purpose of this study is to evaluate in vitro the color stability of composite resins when exposed to beverages with high coloring contents from the Amazon region. 240 samples from four different composite brands (Natural Look, Z350, 4Seasons and Opallis) of hue A3 were fabricated using an acrylic matrix. The samples were stored in distilled water at 37ºC for 24 hours. The initial color (T0) was registered using a Canon EOS Rebel XTi 10 mp camera, and then the samples were divided into four groups (n=15): G1 (coffee), G2 (açaí juice), G3 (energetic guaraná) and G4 (control - distilled water). The samples were exposed to solutions of DES (6hs) and RE (18hs) and placed in a double boiler under constant agitation, at 37ºC for 30 days. The samples were immersed in the coloring solutions for 15 minutes daily. After 7, 15 and 30 days, new photographic registers were made (T1, T2 and T3). The images were analyzed using Corel PHOTO-PAINT 12 software to identify the colors through the HSB system. The Kruskal-Wallis and t tests (p<0.05) demonstrated significant differences in color (hue, saturation and brightness). The results revealed that none of the tested composites showed color stability when exposed to coloring solutions, and that the Amazon region beverages (açaí juice and energetic guaraná) showed to be less coloring than coffee.

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Segmentação do tecido tumoral cerebral em imagens de ressonância magnética

Dissertação de mestrado integrado em Engenharia Biomédica (área de especialização em Eletrónica Médica)

Common symptoms of Nepalese soft contact lens wearers: A pilot study

Aim: To determine the common symptoms in current soft contact lens (CL) wearers and theirassociation with other factors among Nepalese population.Methods: All the current CL wearers who started to wear soft CL in Nepal Eye Hospital between July 2007 and June 2012 were invited for the participation. Frequency of the ten most common symptoms, divided into never, occasionally, frequently and consistent were recorded. Association between degree of symptoms with other factors, e.g. age, gender, profession, cigarette smoking, ethnicity, level of education and duration and wearing modality of CL wear were analyzed.Results: Out of 129 subjects participated in this study, 67% were female; the mean age of the subjects was 23.9 ± 4.3 years. Ninety seven percent of them had at least one symptom occasionally or frequently or consistently. Discomfort was found in 88.4% of the total subjects.Other common symptoms were foreign body sensation in 73.6%, redness in 65.9%, reduced wearing time in 63.6% and dryness in 62.8%. Symptoms were found occasionally in the majority of subjects. Degree of symptoms was not associated with age, gender, profession, education status, ethnicity of subjects and duration or modality of lens wear (p > 0.05) but was positively associated with passive cigarette smoking (p < 0.001).Conclusion: Almost all of the Nepalese soft CL wearers had some types of symptoms at least occasionally. Discomfort was the most common symptom. Degree of symptoms was associated with the passive smoking but not with other factors like age, sex, profession and duration of lens wear.

Common mental disorders among medical students

OBJECTIVE: Common mental disorders (CMD) have a high impact on interpersonal relationships and quality of life and are potential underlying causes for the development of more serious disorders. Medical students have been indicated as a risk population for the development of CMD. The aim of this study was to determine the frequency of CMD in undergraduate medical students and to identify related factors. METHODS: A cross-sectional study was performed in a sample population of medical students. CMD was identified according to the 20-item Self-Report Questionnaire. RESULTS: Two hundred and twenty-three students completed the questionnaire. The overall prevalence of CMD was 29.6% and its presence was independently associated with sleep disorders, not owning a car, not working and sedentary lifestyle. CONCLUSIONS: These findings indicate a high prevalence of CMD in the sample studied and are important for supporting actions to prevent mental disorders in future doctors and for reflecting on the curricula currently in use in medical schools.