Sistema automático para inspecção visual de defeitos em tecidos

Pretende-se com esta comunicação apresentar o trabalho desenvolvido no âmbito da Campanha Têxtil do IDICT, onde se aplicaram algoritmos de processamento de imagem à inspecção de defeitos em tecidos. Devido à complexidade do problema em estudo foi necessário construir um sistema de iluminação estruturada para garantir luminosidade constante no tecido a inspeccionar. Um sistema de captura e processamento de imagens a cores foi desenvolvido, para o sistema operativo Windows 98, tendo por base a placa de aquisição Matrox Meteor II e o software Microsoft Visual C++. Após a conversão de imagens a cores em níveis de cinzento foram desenvolvidos algoritmos de binarização, baseados em análise estatística e morfologia matemática. Os algoritmos desenvolvidos abrangem os seguintes defeitos em tecidos: falta de fio, fio grosso, fio duplo, borboto, mancha e nódoa. Para cada tecido a inspecionar é necessário um período de treino do sistema de forma a identificar os parâmetros estatísticos que o caracterizam, média e desvio padrão dos níveis de cinzento. O sistema inspecciona de forma automática os defeitos descritos em tecidos penteados de uma só cor, tendo sido obtidos resultados bastante satisfatórios para o número de tecidos disponibilisados pelas empresas da região

Multi-monitorização de estufa agrícola

A agricultura tem recorrido, tradicionalmente, a métodos empíricos que não rentabilizavam a produção e estava fortemente dependente das condições meteorológicas. Para melhorar a produção agrícola, surgiram as estufas agrícolas que permitem culturas de elevado valor acrescentado. Estas permitem também a elaboração de estudos de conceitos de causa-efeito, que possibilitam a construção de modelos e sistemas para melhorar a produção e a qualidade de determinada colheita. Com base nesta realidade, este artigo apresenta e descreve um trabalho que se encontra em fase de desenvolvimento por investigadores de duas escolas do Instituto Politécnico de Castelo Branco (IPCB) e que visa o desenvolvimento de um sistema para monitorização de uma estufa agrícola situada na Escola Superior Agrária (ESA) daquele Instituto

How Strongly Do Oysters Stick?

Biological adhesives are a type of interfacial material that has incredible potential to generate new biomimetic compounds that can replace current strong, but toxic, adhesives. Therefore, a study of the chemical composition and mechanical properties of those bio-adhesives is necessary. However, in the case of oysters, despite known chemical characterization of the adult’s adhesive, there are almost no studies on its mechanical properties. Furthermore, there is no available information on the adhesive properties of spat (oysters in their larvae state). Herein, we present the first mechanical characterization of the spat adhesive, measuring its adhesion strength by hydrodynamic determination using a water jet. This study suggests that the adhesion strength of spat could be as high as 70 Pascals, but is highly dependent on experimental conditions. For instance, it was found that the adhesion strength increases on hydrophobic substrates with low surface energy, and that is also dependent on the environmental conditions, like the moisture level. Nevertheless, no relationship between the area of the larvae and its adhesion strength was found. Therefore, it can be proposed that a possible strong hydrophobic interaction adhesive-surface, or an enhancement of the adhesive production over low energy substrates is required for adhesive bonding. This would direct future studies on the search of the adhesion mechanism of this species and increase the biological knowledge about oyster larvae

Greenhouse watching system using multi-technologies

Traditional agriculture uses empiric methods and is very exposed to meteorological conditions. To increase the agriculture production, greenhouses had appeared to allow crops with higher quality. Greenhouses also permit the study of cause-effect concepts that by them allow building models that improve the crop’s production and quality. Based on this reality, this paper presents a system developed by researchers of two schools of the Instituto Politécnico of Castelo Branco(IPCB) to monitor a greenhouse located in the campus of Escola Superior Agrária (ESA). This proposed system uses several different technologies

Bifurcation analysis of a DC–DC bidirectional power converter operating with constant power loads

Direct current (DC) microgrids (MGs) are an emergent option to satisfy new demands for power quality and integration of renewable resources in electrical distribution systems. This work addresses the large-signal stability analysis of a DC–DC bidirectional converter (DBC) connected to a storage device in an islanding MG. This converter is responsible for controlling the balance of power (load demand and generation) under constant power loads (CPLs). In order to control the DC bus voltage through a DBC, we propose a robust sliding mode control (SMC) based on a washout filter. Dynamical systems techniques are exploited to assess the quality of this switching control strategy. In this sense, a bifurcation analysis is performed to study the nonlinear stability of a reduced model of this system. The appearance of different bifurcations when load parameters and control gains are changed is studied in detail. In the specific case of Teixeira Singularity (TS) bifurcation, some experimental results are provided, confirming the mathematical predictions. Both a deeper insight in the dynamic behavior of the controlled system and valuable design criteria are obtained.Postprint (updated version

Al2O3 Surface Passivation Characterized on Hydrophobic and Hydrophilic c-Si by a Combination of QSSPC, CV, XPS and FTIR

Abstract In this work, the influence of the c-Si surface finishing (hydrophobic/hydrophilic) prior to the deposition of the Al2O3 passivation layer on the passivation quality is investigated. The samples are characterized by a combination of Quasi-Steady-State-PhotoConductance (QSSPC) Capacity-Conductance (CV), X-ray Photoelectron Spectroscopy (XPS) and Fourier Transformed InfraRed (FTIR) measurements. Furthermore, FTIR measurements are used to determine the thickness of interfacial SiOx layer

Olive Oil Phenolic Compounds’ Activity against Age-Associated Cognitive Decline: Clinical and Experimental Evidence

Epidemiological studies have shown that consuming olive oil rich in phenolic bioactive compounds is associated with a lower risk of neurodegenerative diseases and better cognitive performance in aged populations. Since oxidative stress is a common hallmark of age-related cognitive decline, incorporating exogenous antioxidants could have beneficial effects on brain aging. In this review, we firstly summarize and critically discuss the current preclinical evidence and the potential neuroprotective mechanisms. Existing studies indicate that olive oil phenolic compounds can modulate and counteract oxidative stress and neuroinflammation, two relevant pathways linked to the onset and progression of neurodegenerative processes. Secondly, we summarize the current clinical evidence. In contrast to preclinical studies, there is no direct evidence in humans of the bioactivity of olive oil phenolic compounds. Instead, we have summarized current findings regarding nutritional interventions supplemented with olive oil on cognition. A growing body of research indicates that high consumption of olive oil phenolic compounds is associated with better preservation of cognitive performance, conferring an additional benefit, independent of the dietary pattern. In conclusion, the consumption of olive oil rich in phenolic bioactive compounds has potential neuroprotective effects. Further research is needed to understand the underlying mechanisms and potential clinical applications

Real-time marker-less multi-person 3D pose estimation in RGB-Depth camera networks

This paper proposes a novel system to estimate and track the 3D poses of multiple persons in calibrated RGB-Depth camera networks. The multi-view 3D pose of each person is computed by a central node which receives the single-view outcomes from each camera of the network. Each single-view outcome is computed by using a CNN for 2D pose estimation and extending the resulting skeletons to 3D by means of the sensor depth. The proposed system is marker-less, multi-person, independent of background and does not make any assumption on people appearance and initial pose. The system provides real-time outcomes, thus being perfectly suited for applications requiring user interaction. Experimental results show the effectiveness of this work with respect to a baseline multi-view approach in different scenarios. To foster research and applications based on this work, we released the source code in OpenPTrack, an open source project for RGB-D people tracking.Comment: Submitted to the 2018 IEEE International Conference on Robotics and Automatio

Optimal Inspection and Maintenance Planning for Deteriorating Structural Components through Dynamic Bayesian Networks and Markov Decision Processes

Civil and maritime engineering systems, among others, from bridges to offshore platforms and wind turbines, must be efficiently managed as they are exposed to deterioration mechanisms throughout their operational life, such as fatigue or corrosion. Identifying optimal inspection and maintenance policies demands the solution of a complex sequential decision-making problem under uncertainty, with the main objective of efficiently controlling the risk associated with structural failures. Addressing this complexity, risk-based inspection planning methodologies, supported often by dynamic Bayesian networks, evaluate a set of pre-defined heuristic decision rules to reasonably simplify the decision problem. However, the resulting policies may be compromised by the limited space considered in the definition of the decision rules. Avoiding this limitation, Partially Observable Markov Decision Processes (POMDPs) provide a principled mathematical methodology for stochastic optimal control under uncertain action outcomes and observations, in which the optimal actions are prescribed as a function of the entire, dynamically updated, state probability distribution. In this paper, we combine dynamic Bayesian networks with POMDPs in a joint framework for optimal inspection and maintenance planning, and we provide the formulation for developing both infinite and finite horizon POMDPs in a structural reliability context. The proposed methodology is implemented and tested for the case of a structural component subject to fatigue deterioration, demonstrating the capability of state-of-the-art point-based POMDP solvers for solving the underlying planning optimization problem. Within the numerical experiments, POMDP and heuristic-based policies are thoroughly compared, and results showcase that POMDPs achieve substantially lower costs as compared to their counterparts, even for traditional problem settings