995 resultados para Vector


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The main objective of the study presented in this paper was to investigate the feasibility using support vector machines (SVM) for the prediction of the fresh properties of self-compacting concrete. The radial basis function (RBF) and polynomial kernels were used to predict these properties as a function of the content of mix components. The fresh properties were assessed with the slump flow, T50, T60, V-funnel time, Orimet time, and blocking ratio (L-box). The retention of these tests was also measured at 30 and 60 min after adding the first water. The water dosage varied from 188 to 208 L/m3, the dosage of superplasticiser (SP) from 3.8 to 5.8 kg/m3, and the volume of coarse aggregates from 220 to 360 L/m3. In total, twenty mixes were used to measure the fresh state properties with different mixture compositions. RBF kernel was more accurate compared to polynomial kernel based support vector machines with a root mean square error (RMSE) of 26.9 (correlation coefficient of R2 = 0.974) for slump flow prediction, a RMSE of 0.55 (R2 = 0.910) for T50 (s) prediction, a RMSE of 1.71 (R2 = 0.812) for T60 (s) prediction, a RMSE of 0.1517 (R2 = 0.990) for V-funnel time prediction, a RMSE of 3.99 (R2 = 0.976) for Orimet time prediction, and a RMSE of 0.042 (R2 = 0.988) for L-box ratio prediction, respectively. A sensitivity analysis was performed to evaluate the effects of the dosage of cement and limestone powder, the water content, the volumes of coarse aggregate and sand, the dosage of SP and the testing time on the predicted test responses. The analysis indicates that the proposed SVM RBF model can gain a high precision, which provides an alternative method for predicting the fresh properties of SCC.

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A rich model based motion vector steganalysis benefiting from both temporal and spatial correlations of motion vectors is proposed in this work. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this work. Firstly, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring motion vectors for longer distances. Therefore, temporal motion vector dependency along side the spatial dependency is utilized for rigorous motion vector steganalysis. Secondly, unlike the filters previously used, which were heuristically designed against a specific motion vector steganography, a diverse set of many filters which can capture aberrations introduced by various motion vector steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent motion vector steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in motion vector steganalysis field including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.

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INTRODUCTION AND GOALS: Genus Bursaphelenchus includes several pests of the world importance for the rural economy, the most dangerous are the Bursaphelenchus xylophilus (the pinewood nematode caused decline of the pine trees in south Asia and in one spot area in Europe, Portugal, Peninsula de Setubal) and the Bursaphelenchus cocophilus, causing the decline of coco-palm plantations in Carribean and Latin American regions. The peculiarity of the host-parasite association of the genus that the nematode life cycle includes three trophic components: plant (mostly a tree), insect vector and a fungus. Goals of the presentation is to list all species of the world fauna and all efficient diagnostic characters, then create the identification tool and analyze the similarity of species and possible ways and causes of the host-parasite evolution of the group. RESULTS: Complete list of species with synonymy and a catalogue of all efficient diagnostic characters with their states, selected from papers of the most experienced taxonomists of the genus, are given for the genus Bursaphelenchus. List of known records of Bursaphelenchus species with names of natural vectors and plants and their families is given (for world pests the most important groups of trees and insects are listed). The tabular, traditional and computer-aided keys are presented. Dendrograms of species relationships (UPGMA, standard distance: mean character difference) based on all efficient taxonomic characters and separately on the spicule characters only, are given. Discussion whether the species groups are natural or purely diagnostic ones is based on the relationships dendrograms and the vector and associated plant ranges of Bursaphelenchus species; the xylophilus species group (B. xylophilus, B. abruptus, B. baujardi, B. conicaudatus, B. eroshenkii, B. fraudulentus, B. kolymensis, B. luxuriosae; B. mucronatus), the hunti group (B. hunti, B. seani, B. kevini and B. fungivorus) are probably the natural ones. CONCLUSIONS: The parasitic nematode association includes three trophic components: plant, insect vector and fungus. The initial insect-plant complex Scolytidae-Pinaceae is changeable and only in rare occasions the change of the preferred vector to Cerambycidae (the xylophilus group), Hymenoptera (the hunti group) led to formation of the natural species-groups. From the analysis it is clear that although the vector range is changeable it is comparatively more important for the evolution of the genus Bursaphelenchus than associations with plants at the family level. Data on the fungi species (3rd component in natural Bursaphelenchus associations) are insufficient for the detailed comparative analysis.

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This paper presents a non-invasive approach for diagnosing winding insulation failures in three-phase transformers, which is based on the on-line monitoring of the primary and secondary current Park's Vector. Experimental and simulated results demonstrate the effectiveness of the proposed technique, for detecting winding inter-turn insulation faults in operating three-phase transformers.

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This paper presents the application of the on-load exciting current Extended Park's Vector Approach for diagnosing incipient turn-to-turn winding faults in operating power transformers. Experimental and simulated test results demonstrate the effectiveness of the proposed technique, which is based on the spectral analysis of the AC component of the on-load exciting current Park's Vector modulus.

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This paper presents the development of a new approach for diagnosing the occurrence of inter-turn short-circuits in the windings of three-phase transformers, which is based on the on-line monitoring of the on-load exciting current Park's Vector patterns. Experimental and simulated results demonstrate the effectiveness of the proposed technique for detecting winding inter-turn insulation faults in operating three-phase transformers.

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Devido ao seu custo e importância estratégica, os transformadores de potência constituem um componente vital dos sistemas de produção, transmissão e distribuição de energia eléctrica. A sua fiabilidade constitui assim um factor crucial no funcionamento dos sistemas eléctricos de energia. Não admira, pois, que sobre estes equipamentos recaiam grandes preocupações relativamente à sua manutenção e, consequentemente, ao desenvolvimento de métodos capazes de fornecerem um diagnóstico completo e fiável do seu estado de funcionamento. Para o efeito, torna-se porém indispensável possuir um conhecimento detalhado acerca das avarias susceptíveis de ocorrerem nos transformadores, bem como dos mecanismos específicos que lhe estão subjacentes.

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Nowadays, vector sensors which measure both acoustic pressure and particle velocity begin to be available in underwater acoustic systems, normally configured as vector sensor arrays (VSA). The spatial filtering capabilities of a VSA can be used, with advantage over traditional pressure only hydrophone arrays, for estimating acoustic field directionality as well as arrival times and spectral content, which could open up the possibility for its use in bottom properties' estimation. An additional motivation for this work is to test the possibility of using high frequency probe signals (say above 2 kHz) for reducing size and cost of actual sub bottom profilers and current geoacoustic inversion methods. This work studies the bottom related structure of the VSA acquired signals, regarding the emitted signal waveform, frequency band and source-receiver geometry in order to estimate bottom properties, specially bottom reflection coefficient characteristics. Such a system was used during the Makai 2005 experiment, off Kauai I., Hawai (USA) to receive precoded signals in a broad frequency band from 8 up to 14 kHz. The agreement between the observed and the modelled acoustic data is discussed and preliminary results on the bottom reflection estimation are presented.

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This paper presents the application of the on-load exciting current Park's Vector Approach for diagnosing permanent and intermittent turn-to-turn winding faults in operating power transformers. First, an experimental investigation of the behaviour of the transformer under the occurrence of both permanent and intermittent winding faults is presented. Finally, experimental test results demonstrate the effectiveness of the proposed diagnostic technique, which is based on the on-line monitoring of the on-load exciting current Park's Vector patterns.

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Vector sensors measure both the acoustic pressure and the three components of particle velocity. Because of this, a vector sensor array (VSA) has the advantage of being able to provide substantially higher directivity with a much smaller aperture than an array of traditional scalar (pressure only) hydrophones. Although several, most of them theoretic, works were published from early nineties, only in the last years due to improvements and availability of vector sensor technology, the interest on field experiments with VSA increased in the scientific community. During the Makai Experiment, that took place off the coast of Kauai I., Hawaii, in September 2005, real data were collected with a 4 element vertical VSA. These data will be discussed in the present paper. The acoustic signals were emitted from a near source (low frequency ship noise) and two high frequency controlled acoustic sources located within a range of 2km from the VSA. The advantages of the VSA over traditional scalar hydrophone arrays in source localization will be addressed using conventional beamforming.

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This paper is a contribution for the assessment and comparison of magnet properties based on magnetic field characteristics particularly concerning the magnetic induction uniformity in the air gaps. For this aim, a solver was developed and implemented to determine the magnetic field of a magnetic core to be used in Fast Field Cycling (FFC) Nuclear Magnetic Resonance (NMR) relaxometry. The electromagnetic field computation is based on a 2D finite-element method (FEM) using both the scalar and the vector potential formulation. Results for the magnetic field lines and the magnetic induction vector in the air gap are presented. The target magnetic induction is 0.2 T, which is a typical requirement of the FFC NMR technique, which can be achieved with a magnetic core based on permanent magnets or coils. In addition, this application requires high magnetic induction uniformity. To achieve this goal, a solution including superconducting pieces is analyzed. Results are compared with a different FEM program.

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Wind speed forecasting has been becoming an important field of research to support the electricity industry mainly due to the increasing use of distributed energy sources, largely based on renewable sources. This type of electricity generation is highly dependent on the weather conditions variability, particularly the variability of the wind speed. Therefore, accurate wind power forecasting models are required to the operation and planning of wind plants and power systems. A Support Vector Machines (SVM) model for short-term wind speed is proposed and its performance is evaluated and compared with several artificial neural network (ANN) based approaches. A case study based on a real database regarding 3 years for predicting wind speed at 5 minutes intervals is presented.

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A malária, doença parasitária complexa que resulta da interacção entre parasita, hospedeiros humano e vector, constitui um dos principais problemas de saúde a nível mundial. À semelhança de outras doenças parasitárias e infecciosas a malária tem um papel importante na evolução, tendo já sido demonstrado o papel da variação genética humana na resistência à infecção. Após quase meio século de controlo, a malária persiste na ilha de Santiago onde, apesar da baixa endemicidade, os indivíduos apresentam geralmente manifestações moderadas, são diagnosticadas infecções abaixo do nível detectável pela microscopia e o vector se encontra muito próximo da população supostamente susceptível, desconhecendo-se a frequência dos principais polimorfismos genéticos humanos mais relacionados com a doença e a estrutura populacional do mosquito vector. Os objectivos gerais de trabalho desta tese assentam 1) no estudo dos dois clássicos factores genéticos do hospedeiro humano relacionados com a malária, nomeadamente os afectos à anemia das células falciformes, à deficiência em G6PD e a análise dum provável envolvimento da PK e 2) na análise genética das populações do mosquito vector, tentando contribuir para a compreensão da epidemiologia da doença na Ilha, e para a escolha de medidas de controlo apropriadas. Os trabalhos incidiram na detecção do alelo responsável pela hemoglobina S, de polimorfismos no gene da G6PD e da PK em indivíduos não aparentados (Infectados e não Infectados) com análise da sua provável associação com a infecção e, ainda, na genotipagem de loci microssatélites de Anopheles arabiensis com recurso a técnicas baseadas na PCR. Relativamente à anemia falciforme, a frequência dos portadores do traço (indivíduos HbAS) e do alelo HbS foi 6% e 5%, respectivamente, e para as variantes da G6PD, 0,8% para G6PDA- e 0,0% para a G6PDMed, não tendo sido encontrado associação entre os genótipos desses dois factores e a presença de infecção. No que concerne ao gene PKLR não foi encontrada uma associação clara entre os polimorfismos analisados e o estado de infecção, mas foi detectado um acentuado desequilíbrio de linkage entre os loci, apenas nos Não Infectados, o que pode significar que essa região do gene, aparentemente conservada, tenha sido seleccionada por fornecer protecção contra a infecção e/ou doença. A diversidade genética das populações de A. arabiensis em onze loci microssatélites foi moderada com valores médio de He, variando de 0,481 a 0,522 e a Rs de 4 a 5. O valor da diferenciação genética baseado em 7 loci polimórficos foi baixo (FST=0,012; p<0,001) mas significativo, variando entre 0,001 e 0,023 entre os pares de populações. Não foram detectados os alelos de resistência associados ao gene Kdr. A baixa frequência dos alelos associados à G6PD (A- e Med) tem implicações importantes nas estratégias de controlo definidas pelo Programa Nacional de Luta contra o Paludismo (PNLP), uma vez que a primaquina pode continuar a ser administrada como complemento aos regimes terapêuticos, em caso de necessidade. A população de A. arabiensis em Santiago revelou-se relativamente homogénea e com uma estrutura reduzida o que pode, por um lado, representar uma desvantagem por permitir uma provável dispersão dos genes de resistência. Por outro lado, essa relativa homogeneidade poderá representar uma vantagem para a introdução de um programa de controlo baseado na libertação de mosquitos transgénicos.

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Staphylococcus aureus harbors redundant adhesins mediating tissue colonization and infection. To evaluate their intrinsic role outside of the staphylococcal background, a system was designed to express them in Lactococcus lactis subsp. cremoris 1363. This bacterium is devoid of virulence factors and has a known genetic background. A new Escherichia coli-L. lactis shuttle and expression vector was constructed for this purpose. First, the high-copy-number lactococcal plasmid pIL253 was equipped with the oriColE1 origin, generating pOri253 that could replicate in E. coli. Second, the lactococcal promoters P23 or P59 were inserted at one end of the pOri253 multicloning site. Gene expression was assessed by a luciferase reporter system. The plasmid carrying P23 (named pOri23) expressed luciferase constitutively at a level 10,000 times greater than did the P59-containing plasmid. Transcription was absent in E. coli. The staphylococcal clumping factor A (clfA) gene was cloned into pOri23 and used as a model system. Lactococci carrying pOri23-clfA produced an unaltered and functional 130-kDa ClfA protein attached to their cell walls. This was indicated both by the presence of the protein in Western blots of solubilized cell walls and by the ability of ClfA-positive lactococci to clump in the presence of plasma. ClfA-positive lactococci had clumping titers (titer of 4,112) similar to those of S. aureus Newman in soluble fibrinogen and bound equally well to solid-phase fibrinogen. These experiments provide a new way to study individual staphylococcal pathogenic factors and might complement both classical knockout mutagenesis and modern in vivo expression technology and signature tag mutagenesis.

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The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.