Approximate processing of massive continuous quantile queries over high-speed data streams

Quantile computation has many applications including data mining and financial data analysis. It has been shown that an is an element of-approximate summary can be maintained so that, given a quantile query d (phi, is an element of), the data item at rank [phi N] may be approximately obtained within the rank error precision is an element of N over all N data items in a data stream or in a sliding window. However, scalable online processing of massive continuous quantile queries with different phi and is an element of poses a new challenge because the summary is continuously updated with new arrivals of data items. In this paper, first we aim to dramatically reduce the number of distinct query results by grouping a set of different queries into a cluster so that they can be processed virtually as a single query while the precision requirements from users can be retained. Second, we aim to minimize the total query processing costs. Efficient algorithms are developed to minimize the total number of times for reprocessing clusters and to produce the minimum number of clusters, respectively. The techniques are extended to maintain near-optimal clustering when queries are registered and removed in an arbitrary fashion against whole data streams or sliding windows. In addition to theoretical analysis, our performance study indicates that the proposed techniques are indeed scalable with respect to the number of input queries as well as the number of items and the item arrival rate in a data stream.

A Bayesian hierarchical model for categorical longitudinal data from a social survey of immigrants

The paper investigates a Bayesian hierarchical model for the analysis of categorical longitudinal data from a large social survey of immigrants to Australia. Data for each subject are observed on three separate occasions, or waves, of the survey. One of the features of the data set is that observations for some variables are missing for at least one wave. A model for the employment status of immigrants is developed by introducing, at the first stage of a hierarchical model, a multinomial model for the response and then subsequent terms are introduced to explain wave and subject effects. To estimate the model, we use the Gibbs sampler, which allows missing data for both the response and the explanatory variables to be imputed at each iteration of the algorithm, given some appropriate prior distributions. After accounting for significant covariate effects in the model, results show that the relative probability of remaining unemployed diminished with time following arrival in Australia.

Constructing internationally comparable real income aggregates by combining sparse benchmark data with annual national accounts data: A state-space approach

The importance of availability of comparable real income aggregates and their components to applied economic research is highlighted by the popularity of the Penn World Tables. Any methodology designed to achieve such a task requires the combination of data from several sources. The first is purchasing power parities (PPP) data available from the International Comparisons Project roughly every five years since the 1970s. The second is national level data on a range of variables that explain the behaviour of the ratio of PPP to market exchange rates. The final source of data is the national accounts publications of different countries which include estimates of gross domestic product and various price deflators. In this paper we present a method to construct a consistent panel of comparable real incomes by specifying the problem in state-space form. We present our completed work as well as briefly indicate our work in progress.

JUVENTUDE, EDUCAÇÃO ESCOLAR E SENTIDO DE VIDA: UM ESTUDO A PARTIR DOS PROJETOS EDUCACIONAIS NO ENSINO MÉDIO

Este estudo parte de uma reflexão sobre a juventude atual e as imagens sócioideológicas construídas em torno desta fase do desenvolvimento humano, com a intenção de reforçar a importância dos espaços educacionais, principalmente das escolas formais, na construção do sentido de vida dos alunos, jovens e adolescentes do Ensino Médio. A juventude é uma etapa da vida que tem sido socialmente considerada, na maioria das vezes, como uma fase problemática, o que tem levado alguns adultos, pais ou professores, a não acreditarem e investirem nas potencialidades dos jovens adolescentes, dificultando sua inserção social de forma mais dinâmica e otimista. O corpo teórico desta pesquisa foi composto pelo conceito de sentido de vida, em Viktor Frankl, perpassando pela concepção de uma educação dialógica, em Paulo Freire, pelo conceito de complexidade, em Edgar Morin, e pela proposta do trabalho educacional por projetos, em Fernando Hernández. Como instrumentos metodológicos, foram utilizados a observação participante, técnicas de análise de questionários exploratórios e grupo focal. A análise dos dados permitiu reconhecer o impacto da proposta do trabalho educacional por projetos, no sentido de contribuir para que a juventude tenha vários elementos para trabalhar aspectos concretos da vida humana, principalmente, naquilo que diz respeito à construção do sentido de vida.(AU)

GESTÃO DO CONHECIMENTO: UM ESTUDO SOBRE A RELAÇÃO ENTRE A LIDERANÇA TRANSFORMACIONAL, A CONVERSÃO DO CONHECIMENTO E A EFICÁCIA ORGANIZACIONAL

Este estudo teve como objetivo principal analisar a relação entre a Liderança Transformacional, a Conversão do Conhecimento e a Eficácia Organizacional. Foram considerados como pressupostos teóricos conceitos consolidados sobre os temas desta relação, além de recentes pesquisas já realizadas em outros países e contextos organizacionais. Com base nisto identificou-se potencial estudo de um modelo que relacionasse estes três conceitos. Para tal considera-se que as organizações que buscam atingir Vantagem Competitiva e incorporam a Knowledge-Based View possam conquistar diferenciação frente a seus concorrentes. Nesse contexto o conhecimento ganha maior destaque e papel protagonista nestas organizações. Dessa forma criar conhecimento através de seus colaboradores, passa a ser um dos desafios dessas organizações ao passo que sugere melhoria de seus indicadores Econômicos, Sociais, Sistêmicos e Políticos, o que se define por Eficácia Organizacional. Portanto os modos de conversão do conhecimento nas organizações, demonstram relevância, uma vez que se cria e se converte conhecimentos através da interação entre o conhecimento existente de seus colaboradores. Essa conversão do conhecimento ou modelo SECI possui quatro modos que são a Socialização, Externalização, Combinação e Internalização. Nessa perspectiva a liderança nas organizações apresenta-se como um elemento capaz de influenciar seus colaboradores, propiciando maior dinâmica ao modelo SECI de conversão do conhecimento. Se identifica então na liderança do tipo Transformacional, características que possam influenciar colaboradores e entende-se que esta relação entre a Liderança Transformacional e a Conversão do Conhecimento possa ter influência positiva nos indicadores da Eficácia Organizacional. Dessa forma esta pesquisa buscou analisar um modelo que explorasse essa relação entre a liderança do tipo Transformacional, a Conversão do Conhecimento (SECI) e a Eficácia Organizacional. Esta pesquisa teve o caráter quantitativo com coleta de dados através do método survey, obtendo um total de 230 respondentes válidos de diferentes organizações. O instrumento de coleta de dados foi composto por afirmativas relativas ao modelo de relação pesquisado com um total de 44 itens. O perfil de respondentes concentrou-se entre 30 e 39 anos de idade, com a predominância de organizações privadas e de departamentos de TI/Telecom, Docência e Recursos Humanos respectivamente. O tratamento dos dados foi através da Análise Fatorial Exploratória e Modelagem de Equações Estruturais via Partial Least Square Path Modeling (PLS-PM). Como resultado da análise desta pesquisa, as hipóteses puderam ser confirmadas, concluindo que a Liderança Transformacional apresenta influência positiva nos modos de Conversão do Conhecimento e que; a Conversão do Conhecimento influencia positivamente na Eficácia Organizacional. Ainda, concluiu-se que a percepção entre os respondentes não apresenta resultado diferente sobre o modelo desta pesquisa entre quem possui ou não função de liderança.

Rule induction for data exploration

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.

Probabilistic principal component analysis

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.

Probabilistic principal component analysis

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.

Macro determinants of FDI inflows to Japan:an analysis of source country characteristics

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.

The application of analysis of variance (ANOVA) to different experimental designs in optometry

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.

Advanced data driven visualisation for geo-spatial data

Most current 3D landscape visualisation systems either use bespoke hardware solutions, or offer a limited amount of interaction and detail when used in realtime mode. We are developing a modular, data driven 3D visualisation system that can be readily customised to specific requirements. By utilising the latest software engineering methods and bringing a dynamic data driven approach to geo-spatial data visualisation we will deliver an unparalleled level of customisation in near-photo realistic, realtime 3D landscape visualisation. In this paper we show the system framework and describe how this employs data driven techniques. In particular we discuss how data driven approaches are applied to the spatiotemporal management aspect of the application framework, and describe the advantages these convey.

Development and evaluation of an ion induced x-ray emission system for the analysis of light and medium weight elements

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 14data analysis and calculations of areal density of thin foils using Rutherford backscattering data.  Amniotic fluid samples supplied by South Sefton Health Authority were successfully analysed for their low base line elemental concentrations. In conclusion the findings of this work are discussed with suggestions for further work .

Negotiating face in feedback conferences:a linguistic ethnographic analysis

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.

A regional analysis of contraction rate in written Standard American English

The goal of this study is to determine if various measures of contraction rate are regionally patterned in written Standard American English. In order to answer this question, this study employs a corpus-based approach to data collection and a statistical approach to data analysis. Based on a spatial autocorrelation analysis of the values of eleven measures of contraction across a 25 million word corpus of letters to the editor representing the language of 200 cities from across the contiguous United States, two primary regional patterns were identified: easterners tend to produce relatively few standard contractions (not contraction, verb contraction) compared to westerners, and northeasterners tend to produce relatively few non-standard contractions (to contraction, non-standard not contraction) compared to southeasterners. These findings demonstrate that regional linguistic variation exists in written Standard American English and that regional linguistic variation is more common than is generally assumed.

A study of cluster analysis techniques and their applications

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.