818 resultados para Inward Rectifier


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The low-temperature low-pressure hydrogen based plasmas were used to study the influence of processes and discharge conditions on corrosion removal. The capacitive coupled RF discharge in the continuous or pulsed regime was used at operating pressure of 100-200 Pa. Plasma treatment was monitored by optical emission spectroscopy. To be able to study influence of various process parameters, the model corroded samples with and without sandy incrustation were prepared. The SEM-EDX analyzes were carried out to verify corrosion removal efficiency. Experimental conditions were optimized for the selected most frequent materials of original metallic archaeological objects (iron, bronze, copper, and brass). Chlorides removal is based on hydrogen ion reactions while oxides are removed mainly by neutral species interactions. A special focus was kept for the samples temperature because it was necessary to avoid any metallographic changes in the material structure. The application of higher power pulsed regime with low duty cycle seems be the best treatment regime. The low pressure hydrogen plasma is not applicable for objects with a very broken structure or for nonmetallic objects due to the non-uniform heat stress. Due to this fact, the new developed plasmas generated in liquids were applied on selected original archaeological glass materials.

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A plasma gas bubble-in-liquid method for high production of selectable reactive species using a nanosecond pulse generator has been developed. The gas of choice is fed through a hollow needle in a point-to-plate bubble discharge, enabling improved selection of reactive species. The increased interface reactions, between the gas-plasma and water through bubbles, give higher productivity. H2O2 was the predominant species produced using Ar plasma, while predominantly  and NO2 were generated using air plasma, in good agreement with the observed emission spectra. This method has nearly 100% selectivity for H2O2, with seven times higher production, and 92% selectivity for , with nearly twice the production, compared with a plasma above the water.

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The development of new learning models has been of great importance throughout recent years, with a focus on creating advances in the area of deep learning. Deep learning was first noted in 2006, and has since become a major area of research in a number of disciplines. This paper will delve into the area of deep learning to present its current limitations and provide a new idea for a fully integrated deep and dynamic probabilistic system. The new model will be applicable to a vast number of areas initially focusing on applications into medical image analysis with an overall goal of utilising this approach for prediction purposes in computer based medical systems.

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A self-consistent relativistic two-fluid model is proposed for one-dimensional electron-ion plasma dynamics. A multiple scales perturbation technique is employed, leading to an evolution equation for the wave envelope, in the form of a nonlinear Schrödinger type equation (NLSE). The inclusion of relativistic effects is shown to introduce density-dependent factors, not present in the non-relativistic case - in the conditions for modulational instability. The role of relativistic effects on the linear dispersion laws and on envelope soliton solutions of the NLSE is discussed.

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Displays are a feature of animal contest behaviour and have been interpreted as a means of gathering information on opponent fighting ability, as well as signalling aggressive motivation. In fish, contest displays often include frontal and lateral elements, which in the latter involves contestants showing their flanks to an opponent. Previous work in a range of fish species has demonstrated population-level lateralization of these displays, preferentially showing one side to their opponent. Mirrors are commonly used in place of a real opponent to study aggression in fish, yet they may disrupt the normal pattern of display behaviour. Here, using Siamese fighting fish, Betta splendens, we compare the aggressive behaviour of males to a mirror image and real opponent behind a transparent barrier. As this species is a facultative air-breather, we also quantify surface breathing, providing insights into underlying fight motivation. Consistent with previous work, we found evidence of population-level lateralization, with a bias to present the left side and use the left eye when facing a real opponent. Contrary to expectations, there were no differences in the aggressive displays to a mirror and real opponent, with positive correlations between the behaviour in the two scenarios. However, there were important differences in surface breathing, which was more frequent and of longer duration in the mirror treatment. The reasons for these differences are discussed in relation to the repertoire of contest behaviour and motivation when facing a real opponent.

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Insights into the potential for pain may be obtained from examination of behavioural responses to noxious stimuli. In particular, prolonged responses coupled with long-term motivational change and avoidance learning cannot be explained by nociceptive reflex but are consistent with the idea of pain. Here, we placed shore crabs alternately in two halves of a test area divided by an opaque partition. Each area had a dark shelter and in one repeated small electric shocks were delivered in an experimental but not in a control group. Crabs showed no specific avoidance of the shock shelter either during these trials or in a subsequent test in which both were offered simultaneously; however they often emerged from the shock shelter during a trial and thus avoided further shock. More crabs emerged in later trials and took less time to emerge than in early trials. Thus, despite the lack of discrimination learning between the two shelters they used other tactics to markedly reduce the amount of shock received. We note that a previous experiment using simultaneous presentation of two shelters demonstrated rapid discrimination and avoidance learning but the paradigm of sequential presentation appears to prevent this. Nevertheless, the data show clearly that the shock is aversive and tactics, other than discrimination learning, are used to avoid it. Thus, the behaviour is only partially consistent with the idea of pain.

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Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

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The measurement of fast changing temperature fluctuations is a challenging problem due to the inherent limited bandwidth of temperature sensors. This results in a measured signal that is a lagged and attenuated version of the input. Compensation can be performed provided an accurate, parameterised sensor model is available. However, to account for the influence of the measurement environment and changing conditions such as gas velocity, the model must be estimated in-situ. The cross-relation method of blind deconvolution is one approach for in-situ characterisation of sensors. However, a drawback with the method is that it becomes positively biased and unstable at high noise levels. In this paper, the cross-relation method is cast in the discrete-time domain and a bias compensation approach is developed. It is shown that the proposed compensation scheme is robust and yields unbiased estimates with lower estimation variance than the uncompensated version. All results are verified using Monte-Carlo simulations.

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Purpose: To clarify the most appropriate treatment regimen for congenital nasolacrimal duct obstruction (CNLDO). Methods: A retrospective observational analysis was performed of patients undergoing probing with or without intubation to treat CNLDO in a single institution (Royal Victoria Hospital, Belfast) from 2006 to 2011. Results: Based on exclusion criteria, 246 eyes of 177 patients (aged 0 to 9.8 years with a mean age of 2.1 years) were included in this study: 187 (76%) eyes had successful outcome at first intervention with primary probing, whereas 56 (23%) eyes underwent secondary intervention. There were no significant differences by gender, age, or obstruction complexity between the successful and unsuccessful patients with first intervention. For those patients requiring secondary intervention, 16 of 24 (67%) eyes had successful probing, whereas 22 of 24 (92%) had successful intubation. Patients with intubation as a secondary procedure were significantly more likely to have a successful outcome (P = .037). Statistical analysis was performed using the Fisher's exact test and Barnard's exact test. Conclusions: Primary probing for CNLDO has a high success rate that is not adversely affected by increasing age. This study also indicates that if initial probing is unsuccessful, nasolacrimal intubation rather than repeat probing yields a significantly higher success rate.

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To maintain the pace of development set by Moore's law, production processes in semiconductor manufacturing are becoming more and more complex. The development of efficient and interpretable anomaly detection systems is fundamental to keeping production costs low. As the dimension of process monitoring data can become extremely high anomaly detection systems are impacted by the curse of dimensionality, hence dimensionality reduction plays an important role. Classical dimensionality reduction approaches, such as Principal Component Analysis, generally involve transformations that seek to maximize the explained variance. In datasets with several clusters of correlated variables the contributions of isolated variables to explained variance may be insignificant, with the result that they may not be included in the reduced data representation. It is then not possible to detect an anomaly if it is only reflected in such isolated variables. In this paper we present a new dimensionality reduction technique that takes account of such isolated variables and demonstrate how it can be used to build an interpretable and robust anomaly detection system for Optical Emission Spectroscopy data.

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This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

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This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

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Permanent magnet synchronous motors (PMSMs) provide a competitive technology for EV traction drives owing to their high power density and high efficiency. In this paper, three types of interior PMSMs with different PM arrangements are modeled by the finite element method (FEM). For a given amount of permanent magnet materials, the V-shape interior PMSM is found better than the U-shape and the conventional rotor topologies for EV traction drives. Then the V-shape interior PMSM is further analyzed with the effects of stator slot opening and the permanent magnet pole chamfering on cogging torque and output torque performance. A vector-controlled flux-weakening method is developed and simulated in Matlab to expand the motor speed range for EV drive system. The results show good dynamic and steady-state performance with a capability of expanding speed up to four times of the rated. A prototype of the V-shape interior PMSM is also manufactured and tested to validate the numerical models built by the FEM.

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The aim of this article is to forecast the present situation of citizenship formation in the field of Swedish education. In highlighting trends and tendencies in the educational assignment to provide for democratic citizenship in the first decade of the 21st century, which can be characterised as lacking collective visions for change, three depictions of citizenship are prevailing: citizenship formation for deliberation, for entrepreneurship and for therapeutic intervention. These depictions are analysed in terms of the direction for action taking and attention that they stress and produce as concerns citizenship in the making. The first one, citizenship formation for deliberation, stresses an inward-looking and inward-feeling citizenship. The second one, citizenship formation for entrepreneurship, stresses an inward-looking and outward-making citizenship, and the third one, citizenship formation for therapeutic intervention, stresses an inward-looking and outward-making citizenship. Taking on this forecast, which actualises democracy as something that is already achieved as a consequence of an assumedly post political situation, we argue that citizenship as well as society itself risks being pictured as apolitical and democratically “saturated.” This situation is hazardous, we argue, as it does not open up for change to come into question as desirable or even possible. Put differently, it leaves us with the notion that things have to be as they are, as we are living in the best of worlds. 

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Citizenship in the making for a new millenium – education and citizen formation in 21st century Sweden. The aim of this article is to analyse citizenship formation in Swedish education. In highlighting trends regarding the assignment of the educational system to provide for democratic citizenship there are certain depictions of citizenship prevail- ing. The first stresses an inward-looking and inward-feeling citizenship, characterizing the citizen as deliberative and emotional. The second stresses an inward-looking and outward-making citizenship, characterizing the citizen as entrepreneurial and willing. Here, democracy is portrayed as already achieved. This, we argue, is hazardous as society risk being pictured as apolitical and democratically ‘saturated’. This situation does not open up for democratic change to come into question as desirable or even possible. Put differently, it leaves us with the notion that things have to be as they are, as we are living in the best of worlds.