Damage evaluation of drilled carbon/epoxy laminates based on area assessment methods

The characteristics of carbon fibre reinforced laminates had widened their use, from aerospace to domestic appliances. A common characteristic is the need of drilling for assembly purposes. It is known that a drilling process that reduces the drill thrust force can decrease the risk of delamination. In this work, delamination assessment methods based on radiographic data are compared and correlated with mechanical test results (bearing test).

Supplier's selection model based on an empirical study

The problem of selecting suppliers/partners is a crucial and important part in the process of decision making for companies that intend to perform competitively in their area of activity. The selection of supplier/partner is a time and resource-consuming task that involves data collection and a careful analysis of the factors that can positively or negatively influence the choice. Nevertheless it is a critical process that affects significantly the operational performance of each company. In this work, there were identified five broad selection criteria: Quality, Financial, Synergies, Cost, and Production System. Within these criteria, it was also included five sub-criteria. After the identification criteria, a survey was elaborated and companies were contacted in order to understand which factors have more weight in their decisions to choose the partners. Interpreted the results and processed the data, it was adopted a model of linear weighting to reflect the importance of each factor. The model has a hierarchical structure and can be applied with the Analytic Hierarchy Process (AHP) method or Value Analysis. The goal of the paper it's to supply a selection reference model that can represent an orientation/pattern for a decision making on the suppliers/partners selection process

Fractional order inductive phenomena based on the skin effect

The Maxwell equations play a fundamental role in the electromagnetic theory and lead to models useful in physics and engineering. This formalism involves integer-order differential calculus, but the electromagnetic diffusion points towards the adoption of a fractional calculus approach. This study addresses the skin effect and develops a new method for implementing fractional-order inductive elements. Two genetic algorithms are adopted, one for the system numerical evaluation and another for the parameter identification, both with good results.

Reconfigurable weblabs based on the IEEE1451 Std

Technology plays a double role in Education: it can act as a facilitator in the teaching/learning process and it can be the very subject of that process in Science & Engineering courses. This is especially true when students perform laboratory activities where they interact with equipment and objects under experimentation. In this context, technology can also play a facilitator role if it allows students to perform experiments in a remote fashion, through the Internet, in a so-called weblab or remote laboratory. No doubt, the Internet has been revolutionizing the educational process in many aspects, and it can be stated that remote laboratories are just an angle of that on-going revolution. As any other educational tool or resource, the i) pedagogical approach and the ii) technology used in the development of a remote laboratory can dictate its general success or its ephemeral existence. By pedagogical approach we consider the way remote experiments address the process by which students acquire experimental skills and link experimental results to theoretical concepts. In respect to technology, we discuss different specification and implementation alternatives, to show the case where the adoption of a family of standards would positively contribute to a larger acceptance and utilization of remote laboratories, and also to a wider collaboration in their development.

A mobile robot platform for open learning based on serious games and remote laboratories

Within the pedagogical community, Serious Games have arisen as a viable alternative to traditional course-based learning materials. Until now, they have been based strictly on software solutions. Meanwhile, research into Remote Laboratories has shown that they are a viable, low-cost solution for experimentation in an engineering context, providing uninterrupted access, low-maintenance requirements, and a heightened sense of reality when compared to simulations. This paper will propose a solution where both approaches are combined to deliver a Remote Laboratory-based Serious Game for use in engineering and school education. The platform for this system is the WebLab-Deusto Framework, already well-tested within the remote laboratory context, and based on open standards. The laboratory allows users to control a mobile robot in a labyrinth environment and take part in an interactive game where they must locate and correctly answer several questions, the subject of which can be adapted to educators' needs. It also integrates the Google Blockly graphical programming language, allowing students to learn basic programming and logic principles without needing to understand complex syntax.

A system verification strategy based on the BST infrastructure

A good verification strategy should bring near the simulation and real functioning environments. In this paper we describe a system-level co-verification strategy that uses a common flow for functional simulation, timing simulation and functional debug. This last step requires using a BST infrastructure, now widely available on commercial devices, specially on FPGAs with medium/large pin-counts.

A framework for fault tolerant real time systems based on reconfigurable FPGAs

To increase the amount of logic available to the users in SRAM-based FPGAs, manufacturers are using nanometric technologies to boost logic density and reduce costs, making its use more attractive. However, these technological improvements also make FPGAs particularly vulnerable to configuration memory bit-flips caused by power fluctuations, strong electromagnetic fields and radiation. This issue is particularly sensitive because of the increasing amount of configuration memory cells needed to define their functionality. A short survey of the most recent publications is presented to support the options assumed during the definition of a framework for implementing circuits immune to bit-flips induction mechanisms in memory cells, based on a customized redundant infrastructure and on a detection-and-fix controller.

Innovative manufacturing process for hybrid pultruded products based on cork and polymeric pre-shapes

Pultruded products are being targeted by a growing demand due to its excellent mechanical properties and low chemical reactivity, ensuring a low level of maintenance operations and allowing an easier assembly operation process than equivalent steel bars. In order to improve the mechanical drawing process and solve some acoustic and thermal insulation problems, pultruded pipes of glass fibre reinforced plastics (GFRF) can be filled with special products that increase their performance regarding the issues previously referred. The great challenge of this work was drawing a new equipment able to produce pultruded pipes filled with cork or polymeric pre-shaped bars as a continuous process. The project was carried out successfully and the new equipment was built and integrated in the pultrusion equipment already existing, allowing to obtain news products with higher added-value in the market, covering some needs previously identified in the field of civil construction.

Sensitive bi-enzymatic biosensor based on polyphenoloxidases–gold nanoparticles–chitosan hybrid film–graphene doped carbon paste electrode for carbamates detection

A bi-enzymatic biosensor (LACC–TYR–AuNPs–CS/GPE) for carbamates was prepared in a single step by electrodeposition of a hybrid film onto a graphene doped carbon paste electrode (GPE). Graphene and the gold nanoparticles (AuNPs) were morphologically characterized by transmission electron microscopy, X-ray photoelectron spectroscopy, dynamic light scattering and laser Doppler velocimetry. The electrodeposited hybrid film was composed of laccase (LACC), tyrosinase (TYR) and AuNPs entrapped in a chitosan (CS) polymeric matrix. Experimental parameters, namely graphene redox state, AuNPs:CS ratio, enzymes concentration, pH and inhibition time were evaluated. LACC–TYR–AuNPs–CS/GPE exhibited an improved Michaelis–Menten kinetic constant (26.9 ± 0.5 M) when compared with LACC–AuNPs–CS/GPE (37.8 ± 0.2 M) and TYR–AuNPs–CS/GPE (52.3 ± 0.4 M). Using 4-aminophenol as substrate at pH 5.5, the device presented wide linear ranges, low detection limits (1.68×10− 9 ± 1.18×10− 10 – 2.15×10− 7 ± 3.41×10− 9 M), high accuracy, sensitivity (1.13×106 ± 8.11×104 – 2.19×108 ± 2.51×107 %inhibition M− 1), repeatability (1.2–5.8% RSD), reproducibility (3.2–6.5% RSD) and stability (ca. twenty days) to determine carbaryl, formetanate hydrochloride, propoxur and ziram in citrus fruits based on their inhibitory capacity on the polyphenoloxidases activity. Recoveries at two fortified levels ranged from 93.8 ± 0.3% (lemon) to 97.8 ± 0.3% (orange). Glucose, citric acid and ascorbic acid do not interfere significantly in the electroanalysis. The proposed electroanalytical procedure can be a promising tool for food safety control.

Antibacterial activity of Ionic Liquids based on ampicillin against resistant bacteria

Antibacterial activity of novel Active Pharmaceutical Ingredient Ionic Liquids (API-ILs) based on ampicillin anion [Amp] have been evaluated. They showed growth inhibition and bactericidal properties on some sensitive bacteria and especially some Gram-negative resistant bacteria when compared to the [Na][Amp] and the initial bromide and chloride salts. For these studies were analysed the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBIC) against sensitive Gram-negative bacteria Escherichia coli ATCC 25922 and Klebsiella pneumonia (clinically isolated), as well as sensitive Gram positive S. Aureus ATCC 25923, Staphylococcus epidermidis and Enterococcus faecalis and completed using clinically isolated resistent strains: E. coli TEM CTX M9, E. coli CTX M2 and E. coli AmpC Mox. From the obtained MIC values of studied APIs-ILs and standard [Na][Amp] were derived RDIC values (relative decrease of inhibitory concentration). High RDIC values of [C16Pyr][Amp] especially against two resistant Gram-negative strains E. coli TEM CTX M9 (RDIC>1000) and E. coli CTX M2 (RDIC>100) point clearly to a potential promising role of APIs-ILs as antimicrobial drugs especially against resistant bacterial strains.

Immunohistochemical molecular phenotypes of gastric cancer based on SOX2 and CDX2 predict patient outcome

Background Gastric cancer remains a serious health concern worldwide. Patients would greatly benefit from the discovery of new biomarkers that predict outcome more accurately and allow better treatment and follow-up decisions. Here, we used a retrospective, observational study to assess the expression and prognostic value of the transcription factors SOX2 and CDX2 in gastric cancer. Methods SOX2, CDX2, MUC5AC and MUC2 expression were assessed in 201 gastric tumors by immunohistochemistry. SOX2 and CDX2 expression were crossed with clinicopathological and follow-up data to determine their impact on tumor behavior and outcome. Moreover, SOX2 locus copy number status was assessed by FISH (N = 21) and Copy Number Variation Assay (N = 62). Results SOX2 was expressed in 52% of the gastric tumors and was significantly associated with male gender, T stage and N stage. Moreover, SOX2 expression predicted poorer patient survival, and the combination with CDX2 defined two molecular phenotypes, SOX2+CDX2- versus SOX2-CDX2+, that predict the worst and the best long-term patients’ outcome. These profiles combined with clinicopathological parameters stratify the prognosis of patients with intestinal and expanding tumors and in those without signs of venous invasion. Finally, SOX2 locus copy number gains were found in 93% of the samples reaching the amplification threshold in 14% and significantly associating with protein expression. Conclusions We showed, for the first time, that SOX2 combined with CDX2 expression profile in gastric cancer segregate patients into different prognostic groups, complementing the clinicopathological information. We further demonstrate a molecular mechanism for SOX2 expression in a subset of gastric cancer cases.

Localization system for pedestrians based on sensor and information fusion

Nowadays there is an increase of location-aware mobile applications. However, these applications only retrieve location with a mobile device's GPS chip. This means that in indoor or in more dense environments these applications don't work properly. To provide location information everywhere a pedestrian Inertial Navigation System (INS) is typically used, but these systems can have a large estimation error since, in order to turn the system wearable, they use low-cost and low-power sensors. In this work a pedestrian INS is proposed, where force sensors were included to combine with the accelerometer data in order to have a better detection of the stance phase of the human gait cycle, which leads to improvements in location estimation. Besides sensor fusion an information fusion architecture is proposed, based on the information from GPS and several inertial units placed on the pedestrian body, that will be used to learn the pedestrian gait behavior to correct, in real-time, the inertial sensors errors, thus improving location estimation.

An integer programming framework for sequencing cutting patterns based on interval graph completion

We derived a framework in integer programming, based on the properties of a linear ordering of the vertices in interval graphs, that acts as an edge completion model for obtaining interval graphs. This model can be applied to problems of sequencing cutting patterns, namely the minimization of open stacks problem (MOSP). By making small modifications in the objective function and using only some of the inequalities, the MOSP model is applied to another pattern sequencing problem that aims to minimize, not only the number of stacks, but also the order spread (the minimization of the stack occupation problem), and the model is tested.

Scenarios Generation for Multi-Agent simulation of Electricity Markets based on Intelligent Data Analysis

This document presents a tool able to automatically gather data provided by real energy markets and to generate scenarios, capture and improve market players’ profiles and strategies by using knowledge discovery processes in databases supported by artificial intelligence techniques, data mining algorithms and machine learning methods. It provides the means for generating scenarios with different dimensions and characteristics, ensuring the representation of real and adapted markets, and their participating entities. The scenarios generator module enhances the MASCEM (Multi-Agent Simulator of Competitive Electricity Markets) simulator, endowing a more effective tool for decision support. The achievements from the implementation of the proposed module enables researchers and electricity markets’ participating entities to analyze data, create real scenarios and make experiments with them. On the other hand, applying knowledge discovery techniques to real data also allows the improvement of MASCEM agents’ profiles and strategies resulting in a better representation of real market players’ behavior. This work aims to improve the comprehension of electricity markets and the interactions among the involved entities through adequate multi-agent simulation.

Short-term Load Forecasting Based on Load Profiling

Load forecasting has gradually becoming a major field of research in electricity industry. Therefore, Load forecasting is extremely important for the electric sector under deregulated environment as it provides a useful support to the power system management. Accurate power load forecasting models are required to the operation and planning of a utility company, and they have received increasing attention from researches of this field study. Many mathematical methods have been developed for load forecasting. This work aims to develop and implement a load forecasting method for short-term load forecasting (STLF), based on Holt-Winters exponential smoothing and an artificial neural network (ANN). One of the main contributions of this paper is the application of Holt-Winters exponential smoothing approach to the forecasting problem and, as an evaluation of the past forecasting work, data mining techniques are also applied to short-term Load forecasting. Both ANN and Holt-Winters exponential smoothing approaches are compared and evaluated.