924 resultados para spatial data analysis
Resumo:
The occurrence of rockbursts was quite common during active mining periods in the Champion reef mines of Kolar gold fields, India. Among the major rockbursts, the ‘area-rockbursts’ were unique both in regard to their spatio-temporal distribution and the extent of damage caused to the mine workings. A detailed study of the spatial clustering of 3 major area-rockbursts (ARB) was carried out using a multi-fractal technique involving generalized correlation integral functions. The spatial distribution analysis of all 3 area-rockbursts showed that they are heterogeneous. The degree of heterogeneity (D2 – D∞) in the cases of ARB-I, II and III were found to be 0.52, 0.37 and 0.41 respectively. These differences in fractal structure indicate that the ARBs of the present study were fully controlled by different heterogeneous stress fields associated with different mining and geological conditions. The present study clearly showed the advantages of the application of multi-fractals to seismic data and to characterise, analyse and examine the area-rockbursts and their causative factors in the Kolar gold mines.
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This paper describes how the statistical technique of cluster analysis and the machine learning technique of rule induction can be combined to explore a database. The ways in which such an approach alleviates the problems associated with other techniques for data analysis are discussed. We report the results of experiments carried out on a database from the medical diagnosis domain. Finally we describe the future developments which we plan to carry out to build on our current work.
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Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined through maximum-likelihood estimation of parameters in a latent variable model closely related to factor analysis. We consider the properties of the associated likelihood function, giving an EM algorithm for estimating the principal subspace iteratively, and discuss the advantages conveyed by the definition of a probability density function for PCA.
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Principal component analysis (PCA) is a ubiquitous technique for data analysis and processing, but one which is not based upon a probability model. In this paper we demonstrate how the principal axes of a set of observed data vectors may be determined through maximum-likelihood estimation of parameters in a latent variable model closely related to factor analysis. We consider the properties of the associated likelihood function, giving an EM algorithm for estimating the principal subspace iteratively, and discuss the advantages conveyed by the definition of a probability density function for PCA.
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Discrete pathological lesions, which include extracellular protein deposits, intracellular inclusions and changes in cell morphology, occur in the brain in the majority of neurodegenerative disorders. These lesions are not randomly distributed in the brain but exhibit a spatial pattern, that is, a departure from randomness towards regularity or clustering. The spatial pattern of a lesion may reflect pathological processes affecting particular neuroanatomical structures and, therefore, studies of spatial pattern may help to elucidate the pathogenesis of a lesion and of the disorders themselves. The present article reviews first, the statistical methods used to detect spatial patterns and second, the types of spatial patterns exhibited by pathological lesions in a variety of disorders which include Alzheimer's disease, Down syndrome, dementia with Lewy bodies, Creutzfeldt-Jakob disease, Pick's disease and corticobasal degeneration. These studies suggest that despite the morphological and molecular diversity of brain lesions, they often exhibit a common type of spatial pattern (i.e. aggregation into clusters that are regularly distributed in the tissue). The pathogenic implications of spatial pattern analysis are discussed with reference to the individual disorders and to studies of neurodegeneration as a whole.
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This paper evaluates the extent of inter-industry and inter-regional wage spillovers across the UK. An extensive body of literature exists suggesting that wages elsewhere affect wage determination and levels of satisfaction, but this paper extends the analysis of wage determination to examine the effects of inward investment in the process. Thus far the specific effect of foreign wages on domestic wage determination has not been evaluated. We employ industry- and regional-level panel data for the UK, and contrast results from alternative approaches to space-time modelling. Each supports the notion that such wage spillovers do occur, though assumptions made concerning the modelling of spatial interaction are important. Further, such wage spillovers are more widespread for skilled than for unskilled workers and also lower in areas of high unemployment. © 2006 Regional Studies Association.
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This paper examines the source country determinants of FDI into Japan. The paper highlights certain methodological and theoretical weaknesses in the previous literature and offers some explanations for hitherto ambiguous results. Specifically, the paper highlights the importance of panel data analysis, and the identification of fixed effects in the analysis rather than simply pooling the data. Indeed, we argue that many of the results reported elsewhere are a feature of this mis-specification. To this end, pooled, fixed effects and random effects estimates are compared. The results suggest that FDI into Japan is inversely related to trade flows, such that trade and FDI are substitutes. Moreover, the results also suggest that FDI increases with home country political and economic stability. The paper also shows that previously reported results, regarding the importance of exchange rates, relative borrowing costs and labour costs in explaining FDI flows, are sensitive to the econometric specification and estimation approach. The paper also discusses the importance of these results within a policy context. In recent years Japan has sought to attract FDI, though many firms still complain of barriers to inward investment penetration in Japan. The results show that cultural and geographic distance are only of marginal importance in explaining FDI, and that the results are consistent with the market-seeking explanation of FDI. As such, the attitude to risk in the source country is strongly related to the size of FDI flows to Japan. © 2007 The Authors Journal compilation © 2007 Blackwell Publishing Ltd.
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Objective: To determine whether in cases of variant Creutzfeldt-Jakob disease (vCJD), the florid-type plaques are derived from the diffuse plaques or whether the 2 plaque types develop independently. Material: Blocks of frontal, parietal, occipital and temporal neocortex and cerebellar cortex from 11 cases of vCJD. Method: The density, distribution and spatial pattern of the florid and diffuse plaques were determined in each brain region using spatial pattern analysis. Results: The density of the diffuse plaques was significantly greater than that of the florid plaques in most areas. The ratio of the diffuse to florid plaques varied between brain regions and was maximal in the molecular layer of the cerebellum. The densities of the florid and diffuse plaques were positively correlated in the parietal cortex, occipital cortex, the inferior temporal gyrus and the dentate gyrus. Plaque densities were not related to disease duration. In the cerebral cortex, the diffuse plaques were more commonly evenly distributed or occurred in large clusters along the cortex parallel to the pia mater compared with the florid plaques which occurred more frequently in regularly distributed clusters. Conclusion: The florid plaques may not be derived from the diffuse plaques, the 2 plaque types appearing to develop independently with unique factors involved in their pathogenesis.
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OBJECTIVE: To study the spatial patterns of the vacuolation ("spongiform change") in the subcortical white matter in the "classical" form of sporadic Creutzfeldt-Jakob disease (sCJD). MATERIAL: Frontal, parietal, occipital and temporal lobes of 11 cases of sCJD. METHOD: Spatial patterns were studied across the white matter at the base of the gyri using spatial pattern analysis. RESULTS: In the white matter of all gyri studied, vacuoles were aggregated into clusters, 50 to > 800 microm in diameter and in 22/37 (59%) of gyri, the clusters of vacuoles exhibited a regular distribution across the base of the gyri. In the remaining gyri, the vacuoles were aggregated into large clusters, at least 400 microm or 800 microm in diameter, but without evidence of a regular distribution. In a significant proportion of gyri, the spatial patterns of the vacuolation were similar to those reported previously for spongiform change and prion protein (PrP) deposits in the corresponding grey matter. CONCLUSIONS: Degeneration of the white matter and the formation of clusters of vacuoles may occur before the degeneration of the grey matter or could be a consequence of pathology affecting the cortico-cortical pathways.
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The association between diffuse-type beta -amyloid (AP) deposits and neuronal cell bodies in Alzheimer's disease (AD) and Down's syndrome (DS) could result from the secretion of AP from clusters of neurons in situ or the diffusion of A beta from cell processes, glial cells or blood vessels. To decide between these hypotheses, spatial pattern analysis was used to study the relationship between the degree of clustering of neuronal cell bodies and the presence of diffuse deposits in the temporal lobe of patients with DS. Significant clustering of neuronal cell bodies was present in 17/24 (71%) of brain areas studied. in addition, in 23/24 (96%) of brain areas, there was a positive correlation between the presence of diffuse deposits and the density of neurons. Hence, the data support the hypothesis that diffuse deposits develop in situ mainly as a result of the secretion of A beta by local clusters of neurons rather than by significant diffusion. Furthermore, the size of a diffuse deposit is likely to be determined by the number of neurons within a cluster which secrete A beta. The number and density of neurons could also be a factor determining the evolution of a diffuse into a mature amyloid deposit.
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Analysis of variance (ANOVA) is the most efficient method available for the analysis of experimental data. Analysis of variance is a method of considerable complexity and subtlety, with many different variations, each of which applies in a particular experimental context. Hence, it is possible to apply the wrong type of ANOVA to data and, therefore, to draw an erroneous conclusion from an experiment. This article reviews the types of ANOVA most likely to arise in clinical experiments in optometry including the one-way ANOVA ('fixed' and 'random effect' models), two-way ANOVA in randomised blocks, three-way ANOVA, and factorial experimental designs (including the varieties known as 'split-plot' and 'repeated measures'). For each ANOVA, the appropriate experimental design is described, a statistical model is formulated, and the advantages and limitations of each type of design discussed. In addition, the problems of non-conformity to the statistical model and determination of the number of replications are considered. © 2002 The College of Optometrists.
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The present work describes the development of a proton induced X-ray emission (PIXE) analysis system, especially designed and builtfor routine quantitative multi-elemental analysis of a large number of samples. The historical and general developments of the analytical technique and the physical processes involved are discussed. The philosophy, design, constructional details and evaluation of a versatile vacuum chamber, an automatic multi-sample changer, an on-demand beam pulsing system and ion beam current monitoring facility are described.The system calibration using thin standard foils of Si, P, S,Cl, K, Ca, Ti, V, Fe, Cu, Ga, Ge, Rb, Y and Mo was undertaken at proton beam energies of 1 to 3 MeV in steps of 0.5 MeV energy and compared with theoretical calculations. An independent calibration check using bovine liver Standard Reference Material was performed. The minimum detectable limits have been experimentally determined at detector positions of 90° and 135° with respect to the incident beam for the above range of proton energies as a function of atomic number Z. The system has detection limits of typically 10- 7 to 10- 9 g for elements 14
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This article examines the negotiation of face in post observation feedback conferences on an initial teacher training programme. The conferences were held in groups with one trainer and up to four trainees and followed a set of generic norms. These norms include the right to offer advice and to criticise, speech acts which are often considered to be face threatening in more normal contexts. However, as the data analysis shows, participants also interact in ways that challenge the generic norms, some of which might be considered more conventionally face attacking. The article argues that face should be analysed at the level of interaction (Haugh and Bargiela-Chiappini, 2010) and that situated and contextual detail is relevant to its analysis. It suggests that linguistic ethnography, which 'marries' (Wetherell, 2007) linguistics and ethnography, provides a useful theoretical framework for doing so. To this end the study draws on real-life talk-in-interaction (from transcribed recordings), the participants' perspectives (from focus groups and interviews) and situated detail (from fieldnotes) to produce a contextualised and nuanced analysis. © 2011 Elsevier B.V.
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This thesis seeks to describe the development of an inexpensive and efficient clustering technique for multivariate data analysis. The technique starts from a multivariate data matrix and ends with graphical representation of the data and pattern recognition discriminant function. The technique also results in distances frequency distribution that might be useful in detecting clustering in the data or for the estimation of parameters useful in the discrimination between the different populations in the data. The technique can also be used in feature selection. The technique is essentially for the discovery of data structure by revealing the component parts of the data. lhe thesis offers three distinct contributions for cluster analysis and pattern recognition techniques. The first contribution is the introduction of transformation function in the technique of nonlinear mapping. The second contribution is the us~ of distances frequency distribution instead of distances time-sequence in nonlinear mapping, The third contribution is the formulation of a new generalised and normalised error function together with its optimal step size formula for gradient method minimisation. The thesis consists of five chapters. The first chapter is the introduction. The second chapter describes multidimensional scaling as an origin of nonlinear mapping technique. The third chapter describes the first developing step in the technique of nonlinear mapping that is the introduction of "transformation function". The fourth chapter describes the second developing step of the nonlinear mapping technique. This is the use of distances frequency distribution instead of distances time-sequence. The chapter also includes the new generalised and normalised error function formulation. Finally, the fifth chapter, the conclusion, evaluates all developments and proposes a new program. for cluster analysis and pattern recognition by integrating all the new features.
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This book is aimed primarily at microbiologists who are undertaking research and who require a basic knowledge of statistics to analyse their experimental data. Computer software employing a wide range of data analysis methods is widely available to experimental scientists. The availability of this software, however, makes it essential that investigators understand the basic principles of statistics. Statistical analysis of data can be complex with many different methods of approach, each of which applies in a particular experimental circumstance. Hence, it is possible to apply an incorrect statistical method to data and to draw the wrong conclusions from an experiment. The purpose of this book, which has its origin in a series of articles published in the Society for Applied Microbiology journal ‘The Microbiologist’, is an attempt to present the basic logic of statistics as clearly as possible and therefore, to dispel some of the myths that often surround the subject. The 28 ‘Statnotes’ deal with various topics that are likely to be encountered, including the nature of variables, the comparison of means of two or more groups, non-parametric statistics, analysis of variance, correlating variables, and more complex methods such as multiple linear regression and principal components analysis. In each case, the relevant statistical method is illustrated with examples drawn from experiments in microbiological research. The text incorporates a glossary of the most commonly used statistical terms and there are two appendices designed to aid the investigator in the selection of the most appropriate test.