29 resultados para network block-device
em Universidade do Minho
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The authors acknowledge to Sofia Neves from ICVS for her help in the antibodies selection.
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The development of organic materials displaying high two-photon absorption (TPA) has attracted much attention in recent years due to a variety of potential applications in photonics and optoelectronics, such as three-dimensional optical data storage, fluorescence imaging, two-photon microscopy, optical limiting, microfabrication, photodynamic therapy, upconverted lasing, etc. The most frequently employed structural motifs for TPA materials are donor–pi bridge–acceptor (D–pi–A) dipoles, donor–pi bridge–donor (D–pi–D) and acceptor–pi bridge-acceptor (A–pi–A) quadrupoles, octupoles, etc. In this work we present the synthesis and photophysical characterization of quadrupolar heterocyclic systems with potential applications in materials and biological sciences as TPA chromophores. Indole is a versatile building block for the synthesis of heterocyclic systems for several optoelectronic applications (chemosensors, nonlinear optical, OLEDs) due to its photophysical properties and donor electron ability and 4H-pyran-4-ylidene fragment is frequently used for the synthesis of red light-emitting materials. On the other hand, 2-(2,6-dimethyl-4H-pyran-4-ylidene)malononitrile (1) and 1,3-diethyl-dihydro-5-(2,6-dimethyl-4H-pyran-4-ylidene)-2-thiobarbituric (2) units are usually used as strong acceptor moieties for the preparation of π-conjugated systems of the push-pull type. These building blocks were prepared by Knoevenagel condensation of the corresponding ketone precursor with malononitrile or 1,3-diethyl-dihydro-2-thiobarbituric acid. The new quadrupolar 4H-pyran-4-ylidene fluorophores (3) derived from indole were prepared through condensation of 5-methyl-1H-indole-3-carbaldehyde with the acceptor precursors 1 and 2, in the presence of a catalytical amount of piperidine. The new compounds were characterized by the usual spectroscopic techniques (UV-vis., FT-IR and multinuclear NMR - 1H, 13C).
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The structural analysis involves the definition of the model and selection of the analysis type. The model should represent the stiffness, the mass and the loads of the structure. The structures can be represented using simplified models, such as the lumped mass models, and advanced models resorting the Finite Element Method (FEM) and Discrete Element Method (DEM). Depending on the characteristics of the structure, different types of analysis can be used such as limit analysis, linear and non-linear static analysis and linear and non-linear dynamic analysis. Unreinforced masonry structures present low tensile strength and the linear analyses seem to not be adequate for assessing their structural behaviour. On the other hand, the static and dynamic non-linear analyses are complex, since they involve large time computational requirements and advanced knowledge of the practitioner. The non-linear analysis requires advanced knowledge on the material properties, analysis tools and interpretation of results. The limit analysis with macro-blocks can be assumed as a more practical method in the estimation of maximum load capacity of structure. Furthermore, the limit analysis require a reduced number of parameters, which is an advantage for the assessment of ancient and historical masonry structures, due to the difficult in obtaining reliable data.
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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.
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Nowadays, many P2P applications proliferate in the Internet. The attractiveness of many of these systems relies on the collaborative approach used to exchange large resources without the dependence and associated constraints of centralized approaches where a single server is responsible to handle all the requests from the clients. As consequence, some P2P systems are also interesting and cost-effective approaches to be adopted by content-providers and other Internet players. However, there are several coexistence problems between P2P applications and In- ternet Service Providers (ISPs) due to the unforeseeable behavior of P2P traffic aggregates in ISP infrastructures. In this context, this work proposes a collaborative P2P/ISP system able to underpin the development of novel Traffic Engi- neering (TE) mechanisms contributing for a better coexistence between P2P applications and ISPs. Using the devised system, two TE methods are described being able to estimate and control the impact of P2P traffic aggregates on the ISP network links. One of the TE methods allows that ISP administrators are able to foresee the expected impact that a given P2P swarm will have in the underlying network infrastructure. The other TE method enables the definition of ISP friendly P2P topologies, where specific network links are protected from P2P traffic. As result, the proposed system and associated mechanisms will contribute for improved ISP resource management tasks and to foster the deployment of innovative ISP-friendly systems.
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This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational in- telligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two il- lustrative Traffic Engineering methods are described, allowing to attain routing con- figurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.
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On assistive technology targeted for people with activity limitations and participation, usability issues becomes an essential tool to ensure that the product has the appropriate ergonomics characteristics, in other words, ensure that it fits the specific user´s needs. The aim of this study was to analyze the usability of an adaptive seating device for children with neuromotor impairments, by using kinematic indicators of the reaching movement. The study sample consisted of 13 children with associated neurologic conditions. The tests were developed by using a wooden bench height adjustable, integrated with the adaptive seating device under study, and a system to capture three-dimensional image, called Qualisys Track Manager. The following reaching kinematics variables were measured: maximum reaching velocity, movement duration, index of curvature, and unit movements. It was found that the use of the adaptive seating device had a positive impact on upper limb function in children with neuromotor impairments. It was also noticed an improvement in the reaching movement kinematics, which was statistical significant for the index of curvature and unit movements. As main conclusions, it is possible to point out some positive effects that the product under study seems to have on users' movements, such as the improved movement quality of the upper limb, which could mean a better postural adjustments and higher trunk postural control. By identifying new measures of usability in terms of effectiveness and efficiency for the analyzeddevice, the results obtained may serve also as performance indicators, providing new data that may help to improve the product and eventually modifying it, in order to turn it more compatible with the needs of the considered target population.
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PhD Thesis in Bioengineering
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A flexible and low cost energy harvester device based on the magnetoelectric (ME) effect has been designed using Fe64Co17Si7B12 as amorphous magnetostrictive ribbons and PVDF as the piezoelectric element. Sandwich-type laminated composite of 3 cm long has been fabricated by gluing these ribbons to the PVDF with the Devcon 5 minute epoxy. Good power output and power density of 6.4 μW and 1.5 mW/cm3, respectively, have been obtained through a multiplier circuit. All values have been measured at the magnetomechanical resonance of the laminate. The effect of the length of the ME laminate on the power output has been also studied, exhibiting a decay as the length of the ME laminate does. Nevertheless, good performance of such device has been obtained for a 0.5 cm long device, working already at 337 KHz, within the low radio frequency (LRF) range.
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Thermoplastic elastomers based on a triblock copolymer styrene-butadiene-styrene (SBS) with different butadiene/styrene ratios, block structure and carbon nanotube (CNT) content were submitted to accelerated weathering in a Xenontest set up, in order to evaluate their stability to UV ageing. It was concluded that ageing mainly depends on butadiene/styrene ratio and block structure, with radial block structures exhibiting a faster ageing than linear block structures. Moreover, the presence of carbon nanotubes in the SBS copolymer slows down the ageing of the copolymer. The evaluation of the influence of ageing on the mechanical and electrical properties demonstrates that the mechanical degradation is higher for the C401 sample, which is the SBS sample with the largest butadiene content and a radial block structure. On the other hand, a copolymer derivate from SBS, the styrene-ethylene/butadiene-styrene (SEBS) sample, retains a maximum deformation of ~1000% after 80 h of accelerated ageing. The hydrophobicity of the samples decreases with increasing ageing time, the effect being larger for the samples with higher butadiene content. It is also verified that cytotoxicity increases with increasing UV ageing with the exception of SEBS, which remains not cytotoxic up to 80 h of accelerated ageing time, demonstrating its potential for applications involving exposition to environmental conditions.
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This paper deals with the problem of estimation maintenance costs for the case of the pitch controls system of wind farms turbines. Previous investigations have estimated these costs as (traditional) “crisp” values, simply ignoring the uncertainty nature of data and information available. This paper purposes an extended version of the estimation model by making use of the Fuzzy Set Theory. The results alert decision-makers to consequent uncertainty of the estimations along with their overall level, thus improving the information given to the mainte-nance support system.
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Schizophrenia stands for a long-lasting state of mental uncertainty that may bring to an end the relation among behavior, thought, and emotion; that is, it may lead to unreliable perception, not suitable actions and feelings, and a sense of mental fragmentation. Indeed, its diagnosis is done over a large period of time; continuos signs of the disturbance persist for at least 6 (six) months. Once detected, the psychiatrist diagnosis is made through the clinical interview and a series of psychic tests, addressed mainly to avoid the diagnosis of other mental states or diseases. Undeniably, the main problem with identifying schizophrenia is the difficulty to distinguish its symptoms from those associated to different untidiness or roles. Therefore, this work will focus on the development of a diagnostic support system, in terms of its knowledge representation and reasoning procedures, based on a blended of Logic Programming and Artificial Neural Networks approaches to computing, taking advantage of a novel approach to knowledge representation and reasoning, which aims to solve the problems associated in the handling (i.e., to stand for and reason) of defective information.
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Thrombotic disorders have severe consequences for the patients and for the society in general, being one of the main causes of death. These facts reveal that it is extremely important to be preventive; being aware of how probable is to have that kind of syndrome. Indeed, this work will focus on the development of a decision support system that will cater for an individual risk evaluation with respect to the surge of thrombotic complaints. The Knowledge Representation and Reasoning procedures used will be based on an extension to the Logic Programming language, allowing the handling of incomplete and/or default data. The computational framework in place will be centered on Artificial Neural Networks.
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Olive oils may be commercialized as intense, medium or light, according to the intensity perception of fruitiness, bitterness and pungency attributes, assessed by a sensory panel. In this work, the capability of an electronic tongue to correctly classify olive oils according to the sensory intensity perception levels was evaluated. Cross-sensitivity and non-specific lipid polymeric membranes were used as sensors. The sensor device was firstly tested using quinine monohydrochloride standard solutions. Mean sensitivities of 14±2 to 25±6 mV/decade, depending on the type of plasticizer used in the lipid membranes, were obtained showing the device capability for evaluating bitterness. Then, linear discriminant models based on sub-sets of sensors, selected by a meta-heuristic simulated annealing algorithm, were established enabling to correctly classify 91% of olive oils according to their intensity sensory grade (leave-one-out cross-validation procedure). This capability was further evaluated using a repeated K-fold cross-validation procedure, showing that the electronic tongue allowed an average correct classification of 80% of the olive oils used for internal-validation. So, the electronic tongue can be seen as a taste sensor, allowing differentiating olive oils with different sensory intensities, and could be used as a preliminary, complementary and practical tool for panelists during olive oil sensory analysis.
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Dissertação de mestrado integrado em Engenharia de Telecomunicações e Informática