987 resultados para cosmologia, clustering, AP-test


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Monopoles which are sources of non-Abelian magnetic flux are predicted by many models of grand unification. It has been argued elsewhere that a generic transformation of the "unbroken" symmetry group H cannot be globally implemented on such monopoles for reasons of topology. In this paper, we show that similar topological obstructions are encountered in the mechanics of a test particle in the field of these monopoles and that the transformations of H cannot all be globally implemented as canonical transformations. For the SU(5) model, if H is SU(3)C×U(1)em, a consequence is that color multiplets are not globally defined, while if H is SU(3)C×SU(2)WS×U(1)Y, the same is the case for both color and electroweak multiplets. There are, however, several subgroups KT, KT′,… of H which can be globally implemented, with the transformation laws of the observables differing from group to group in a novel way. For H=SU(3)C×U(1)em, a choice for KT is SU(2)C×U(1)em, while for H=SU(3)C×SU(2)WS×U(1)Y, a choice is SU(2)C×U(1)×U(1)×U(1). The paper also develops the differential geometry of monopoles in a form convenient for computations.

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Many grand unified theories (GUT's) predict non-Abelian monopoles which are sources of non-Abelian (and Abelian) magnetic flux. In the preceding paper, we discussed in detail the topological obstructions to the global implementation of the action of the "unbroken symmetry group" H on a classical test particle in the field of such a monopole. In this paper, the existence of similar topological obstructions to the definition of H action on the fields in such a monopole sector, as well as on the states of a quantum-mechanical test particle in the presence of such fields, are shown in detail. Some subgroups of H which can be globally realized as groups of automorphisms are identified. We also discuss the application of our analysis to the SU(5) GUT and show in particular that the non-Abelian monopoles of that theory break color and electroweak symmetries.

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This paper reports a rare investigation of stopover destination image. Although the topic of destination image has been one of the most popular in the tourism literature since the 1970s, there has been a lack of research attention in relation to the context of stopover destinations for long haul international travellers. The purpose of this study was to identify attributes deemed salient to Australian consumers when considering stopover destinations for long haul travel to the United Kingdom and Europe. Underpinned by Personal Construct Theory (PCT), the study used the Repertory Test to identify 21 salient attributes, which could be used in the development of a survey instrument to measure the attractiveness of a competitive set of stopover destinations. While the list of attributes shared some commonality with general studies of destination image reported in the literature, the elicitation of a relatively large number of stopover context specific attributes highlights the potential benefit of engaging with consumers in qualitative research, such as using the Repertory Test, during the questionnaire development stage.

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The pollen of Parthenium hysterophorus, an alien weed growing wild in India was found to be a potential source of allergic rhinitis. A clinical survey showed that 34% of the patients suffering from rhinitis and 12% suffering from bronchial asthma gave positive skin-prick test reactions to Parthenium pollen antigen extracts. Parthenium-specific IgE was detected in the sera of sixteen out of twenty-four patients suffering from seasonal rhinitis. There was 66% correlation between skin test and RAST.

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Nitrogen (N) is an essential nutrient in mango, influencing both productivity and fruit quality. In Australia, tree N is traditionally assessed once a year in the dormant pre-flowering stage by laboratory analysis of leaf N. This single assessment is insufficient to determine tree N status at all stages of the annual phenological cycle. Development of a field-based rapid N test would allow more frequent monitoring of tree N status and improved fertiliser management. This experiment examined the accuracy and useability of several devices used in other horticultural crops to rapidly assess mango leaf N in the field; the Konica Minolta 'SPAD-502 chlorophyll meter', Horiba 'Cardy Meter' and the Merck 'RQflex 10'. Regression and correlation analyses were used to determine the relationship between total leaf N and the measurements from the rapid test devices. The relationship between the chlorophyll index measured by the SPAD-502 meter and leaf N is highly significant at late fruit set (R 2=0.72, n=40) and post-harvest (R2=0.81, n=40) stages in the mango cultivar 'Kensington Pride' and significant (R2=0.51, n=40) at the flowering stage, indicating the device can be used to rapidly assess mango leaf N in the field. Correlation analysis indicated the relationship between petiole sap measured with the Cardy or Merck devices and leaf N is non-significant. © 2013 ISHS.

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The family of location and scale mixtures of Gaussians has the ability to generate a number of flexible distributional forms. The family nests as particular cases several important asymmetric distributions like the Generalized Hyperbolic distribution. The Generalized Hyperbolic distribution in turn nests many other well known distributions such as the Normal Inverse Gaussian. In a multivariate setting, an extension of the standard location and scale mixture concept is proposed into a so called multiple scaled framework which has the advantage of allowing different tail and skewness behaviours in each dimension with arbitrary correlation between dimensions. Estimation of the parameters is provided via an EM algorithm and extended to cover the case of mixtures of such multiple scaled distributions for application to clustering. Assessments on simulated and real data confirm the gain in degrees of freedom and flexibility in modelling data of varying tail behaviour and directional shape.

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We propose a family of multivariate heavy-tailed distributions that allow variable marginal amounts of tailweight. The originality comes from introducing multidimensional instead of univariate scale variables for the mixture of scaled Gaussian family of distributions. In contrast to most existing approaches, the derived distributions can account for a variety of shapes and have a simple tractable form with a closed-form probability density function whatever the dimension. We examine a number of properties of these distributions and illustrate them in the particular case of Pearson type VII and t tails. For these latter cases, we provide maximum likelihood estimation of the parameters and illustrate their modelling flexibility on simulated and real data clustering examples.

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Salt-fog tests as per International Electrotechnical Commission (IEC) recommendations were conducted on stationtype insulators with large leakage lengths. Later, tests were conducted to simulate natural conditions. From these tests, it was understood that the pollution flashover would occur because of nonuniform pollution layers causing nonuniform voltage distribution during a natural drying-up period. The leakage current during test conditions was very small and the evidence was that the leakage current did not play any significant role in causing flashovers. In the light of the experimental results, some modification of the test procedure is suggested.

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The behaviour of laterally loaded piles is considerably influenced by the uncertainties in soil properties. Hence probabilistic models for assessment of allowable lateral load are necessary. Cone penetration test (CPT) data are often used to determine soil strength parameters, whereby the allowable lateral load of the pile is computed. In the present study, the maximum lateral displacement and moment of the pile are obtained based on the coefficient of subgrade reaction approach, considering the nonlinear soil behaviour in undrained clay. The coefficient of subgrade reaction is related to the undrained shear strength of soil, which can be obtained from CPT data. The soil medium is modelled as a one-dimensional random field along the depth, and it is described by the standard deviation and scale of fluctuation of the undrained shear strength of soil. Inherent soil variability, measurement uncertainty and transformation uncertainty are taken into consideration. The statistics of maximum lateral deflection and moment are obtained using the first-order, second-moment technique. Hasofer-Lind reliability indices for component and system failure criteria, based on the allowable lateral displacement and moment capacity of the pile section, are evaluated. The geotechnical database from the Konaseema site in India is used as a case example. It is shown that the reliability-based design approach for pile foundations, considering the spatial variability of soil, permits a rational choice of allowable lateral loads.

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Thermal decomposition and combustion of lithium perchlorate ammine:ammonium perchlorate (LPA:AP) and magnesium perchlorate ammine:ammonium perchlorate (MPA:AP) pellets have been studied using DTA, TG, and strand burner techniques. The DTA results of the ammine:AP pellets show that the addition of ammines lowers the ignition temperature of AP. However, isothermal TG of the ammine:AP pellets show that in the case of LPA:AP pellets the extent of decomposition increases with the increase in the concentration of LPA; whereas in the case of MPA:AP pellets the extent of decomposition decreases with the increase in the concentration of MPA. Similarly, LPA:AP pellets show higher burning rates compared to AP pellets. On the other hand, MPA:AP pellets show lower burning rates compared to AP pellets. Increasing the concentration of MPA in MPA:AP pellets completely suppresses the combustion. These results are explained on the basis of the thermal characteristics of the additives and their decomposition products.

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The concept of feature selection in a nonparametric unsupervised learning environment is practically undeveloped because no true measure for the effectiveness of a feature exists in such an environment. The lack of a feature selection phase preceding the clustering process seriously affects the reliability of such learning. New concepts such as significant features, level of significance of features, and immediate neighborhood are introduced which result in meeting implicitly the need for feature slection in the context of clustering techniques.

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Clustering identities in a video is a useful task to aid in video search, annotation and retrieval, and cast identification. However, reliably clustering faces across multiple videos is challenging task due to variations in the appearance of the faces, as videos are captured in an uncontrolled environment. A person's appearance may vary due to session variations including: lighting and background changes, occlusions, changes in expression and make up. In this paper we propose the novel Local Total Variability Modelling (Local TVM) approach to cluster faces across a news video corpus; and incorporate this into a novel two stage video clustering system. We first cluster faces within a single video using colour, spatial and temporal cues; after which we use face track modelling and hierarchical agglomerative clustering to cluster faces across the entire corpus. We compare different face recognition approaches within this framework. Experiments on a news video database show that the Local TVM technique is able effectively model the session variation observed in the data, resulting in improved clustering performance, with much greater computational efficiency than other methods.

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The Minimum Description Length (MDL) principle is a general, well-founded theoretical formalization of statistical modeling. The most important notion of MDL is the stochastic complexity, which can be interpreted as the shortest description length of a given sample of data relative to a model class. The exact definition of the stochastic complexity has gone through several evolutionary steps. The latest instantation is based on the so-called Normalized Maximum Likelihood (NML) distribution which has been shown to possess several important theoretical properties. However, the applications of this modern version of the MDL have been quite rare because of computational complexity problems, i.e., for discrete data, the definition of NML involves an exponential sum, and in the case of continuous data, a multi-dimensional integral usually infeasible to evaluate or even approximate accurately. In this doctoral dissertation, we present mathematical techniques for computing NML efficiently for some model families involving discrete data. We also show how these techniques can be used to apply MDL in two practical applications: histogram density estimation and clustering of multi-dimensional data.

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THE addition of catalysts normally serves the purpose of imparting a desired burning rate change in a composite propellant. These may either retard or enhance the burning rate. Some often quoted catalysts are oxides, chromites and chromates of metals. A lot of work has been done on rinding the effect of the addition of some of these catalysts on the burning rate; however, none seems to have appeared on the influence of lithium fluoride (LiF). Only qualitative reduction in the burning rate of composite propellants with the addition of LiF was reported by Williams et al.1 Dickinson and Jackson2 reported a slight decrease in the specific impulse of composite propellant with the addition of LiF; however, they made no mention of the effect of its addition on the burning rate. We have studied the effect of the addition of varying amounts of LiF on the burning rate of Ammonium Perchlorate (AP)-Polyester propellant.

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Online content services can greatly benefit from personalisation features that enable delivery of content that is suited to each user's specific interests. This thesis presents a system that applies text analysis and user modeling techniques in an online news service for the purpose of personalisation and user interest analysis. The system creates a detailed thematic profile for each content item and observes user's actions towards content items to learn user's preferences. A handcrafted taxonomy of concepts, or ontology, is used in profile formation to extract relevant concepts from the text. User preference learning is automatic and there is no need for explicit preference settings or ratings from the user. Learned user profiles are segmented into interest groups using clustering techniques with the objective of providing a source of information for the service provider. Some theoretical background for chosen techniques is presented while the main focus is in finding practical solutions to some of the current information needs, which are not optimally served with traditional techniques.