900 resultados para supplementary stabilizers


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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This work presents the application of the Decentralized Modal Control method for pole placement in multimachine power systems utilizing FACTS (Flexible AC Transmission Systems), STATCOM (Static Synchronous Compensator) and UPFC (Unified Power Flow Controller) devices. For this, these devices are equipped with supplementary damping controllers, denominated POD ( Power Oscillation Damping), achieving a coordinated project with local controllers (Power System Stabilizers - PSS). Comparative analysis on the function of damping of the FACTS, STATCOM and UPFC is performed using the New England System that has 10 generators, 39 buses and 46 transmission lines. (c) 2011 Elsevier Ltd. All rights reserved.

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Adjuvant use of nutritional and herbal medicines has potential to increase the efficacy of synthetic pharmaceuticals, and perhaps also decrease their side-effects by allowing lower doses to be prescribed. We evaluated current evidence for adjuvant use of nutritional and herbal medicines with antidepressants, mood stabilizers and benzodiazepines; and explored novel future areas of research. The paper also critiques current evidence for co-administration of St. John’s wort with synthetic antidepressants. We performed a systematic search of MEDLINE, CINAHL, PsycINFO, The Cochrane database, China National Knowledge Infrastructure and the Chinese Science Citation Database. Search results were supplemented by a review of reference lists and a forward search using the Web of Science. Where possible we calculated effect sizes. Encouraging evidence exists for the use of omega-3 fatty acids, SAMe, folic acid and l-tryptophan adjuvantly with antidepressants to enhance response and improve efficacy. Various nutrients also have emerging evidence as effective adjuncts with antipsychotics and mood stabilizers. While some evidence supports nutritional adjuvancy with various psychopharmacotherapies, adjuvant use of herbal therapies has not been sufficiently studied to warrant standard clinical application. This remains a promising area of research via robust, safety-conscious studies.

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This paper investigates the problem of appropriate load sharing in an autonomous microgrid. High gain angle droop control ensures proper load sharing, especially under weak system conditions. However it has a negative impact on overall stability. Frequency domain modeling, eigenvalue analysis and time domain simulations are used to demonstrate this conflict. A supplementary loop is proposed around a conventional droop control of each DG converter to stabilize the system while using high angle droop gains. Control loops are based on local power measurement and modulation of the d-axis voltage reference of each converter. Coordinated design of supplementary control loops for each DG is formulated as a parameter optimization problem and solved using an evolutionary technique. The sup-plementary droop control loop is shown to stabilize the system for a range of operating conditions while ensuring satisfactory load sharing.

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In April 2007, the Australian Learning and Teaching Council (ALTC)commissioned a study to examine the diverse approaches to ePortfolio use by students in Australian universities. The goals were to consider the scope, penetration and reasons for use of ePortfolios, and to examine the issues associated with their implementation in higher education. One of the central research activities in the project was a national audit which sought to establish a picture of current and emerging ePortfolio activities in Australian academic institutions. The data collection activities took place in late 2007 and the findings were presented and discussed in the final project report, published in October 2008. In 2010, the idea of a ‘follow up survey’ was developed. The resulting supplementary research activity was undertaken to update the data collected by the AeP project team in late 2007. The plan behind this ‘postscript to AeP’ project was to refresh the picture of ePortfolio practice in Australia by collecting new data to identify and map the use of ePortfolios in adult learning across the higher education, vocational education and training (VET) and the adult community education (ACE) sectors. The supplementary project has been referred to as the ‘AeP PS survey’.

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To ensure the small-signal stability of a power system, power system stabilizers (PSSs) are extensively applied for damping low frequency power oscillations through modulating the excitation supplied to synchronous machines, and increasing interest has been focused on developing different PSS schemes to tackle the threat of damping oscillations to power system stability. This paper examines four different PSS models and investigates their performances on damping power system dynamics using both small-signal eigenvalue analysis and large-signal dynamic simulations. The four kinds of PSSs examined include the Conventional PSS (CPSS), Single Neuron based PSS (SNPSS), Adaptive PSS (APSS) and Multi-band PSS (MBPSS). A steep descent parameter optimization algorithm is employed to seek the optimal PSS design parameters. To evaluate the effects of these PSSs on improving power system dynamic behaviors, case studies are carried out on an 8-unit 24-bus power system through both small-signal eigenvalue analysis and large-signal time-domain simulations.

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This item provides supplementary materials for the paper mentioned in the title, specifically a range of organisms used in the study. The full abstract for the main paper is as follows: Next Generation Sequencing (NGS) technologies have revolutionised molecular biology, allowing clinical sequencing to become a matter of routine. NGS data sets consist of short sequence reads obtained from the machine, given context and meaning through downstream assembly and annotation. For these techniques to operate successfully, the collected reads must be consistent with the assumed species or species group, and not corrupted in some way. The common bacterium Staphylococcus aureus may cause severe and life-threatening infections in humans,with some strains exhibiting antibiotic resistance. In this paper, we apply an SVM classifier to the important problem of distinguishing S. aureus sequencing projects from alternative pathogens, including closely related Staphylococci. Using a sequence k-mer representation, we achieve precision and recall above 95%, implicating features with important functional associations.

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Genomic sequences are fundamentally text documents, admitting various representations according to need and tokenization. Gene expression depends crucially on binding of enzymes to the DNA sequence at small, poorly conserved binding sites, limiting the utility of standard pattern search. However, one may exploit the regular syntactic structure of the enzyme's component proteins and the corresponding binding sites, framing the problem as one of detecting grammatically correct genomic phrases. In this paper we propose new kernels based on weighted tree structures, traversing the paths within them to capture the features which underpin the task. Experimentally, we and that these kernels provide performance comparable with state of the art approaches for this problem, while offering significant computational advantages over earlier methods. The methods proposed may be applied to a broad range of sequence or tree-structured data in molecular biology and other domains.

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Next Generation Sequencing (NGS) has revolutionised molecular biology, resulting in an explosion of data sets and an increasing role in clinical practice. Such applications necessarily require rapid identification of the organism as a prelude to annotation and further analysis. NGS data consist of a substantial number of short sequence reads, given context through downstream assembly and annotation, a process requiring reads consistent with the assumed species or species group. Highly accurate results have been obtained for restricted sets using SVM classifiers, but such methods are difficult to parallelise and success depends on careful attention to feature selection. This work examines the problem at very large scale, using a mix of synthetic and real data with a view to determining the overall structure of the problem and the effectiveness of parallel ensembles of simpler classifiers (principally random forests) in addressing the challenges of large scale genomics.

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In moderate to high sea states, the effectiveness of ship fin stabilizers can severely deteriorate due to nonlinear effects arising from unsteady hydrodynamic characteristics of the fins: dynamic stall. These nonlinear effects take the form of a hysteresis, and they become very significant when the effective angle of attack of the fins exceeds a certain threshold angle. Dynamic stall can result in a complete loss of control action depending on how much the fins exceed the threshold angle. When this is detected, it is common to reduce the gain of the controller that commands the fins. This approach is cautious and tends to reduce performance when the conditions leading to dynamic stall disappear. An alternative approach for preventing the effects while keeping high performance, consists of estimating the effective angle of attack and set a conservative constraint on it as part of the control objectives. In this paper, we investigate the latter approach, and propose the use of a model predictive control (MPC) to prevent the development of these nonlinear effects by considering constraints on both the mechanical angle of the fins and the effective angle of attack.