Classification and choice in product design

Life is full of difficult choices. Everyone has their own way of dealing with these, some effective, some not. The problem is particularly acute in engineering design because of the vast amount of information designers have to process. This paper deals with a subset of this set of problems: the subset of selecting materials and processes, and their links to the design of products. Even these, though, present many of the generic problems of choice, and the challenges in creating tools to assist the designer in making them. The key elements are those of classification, of indexing, of reaching decisions using incomplete data in many different formats, and of devising effective strategies for selection. This final element - that of selection strategies - poses particular challenges. Product design, as an example, is an intricate blend of the technical and (for want of a better word) the aesthetic. To meet these needs, a tool that allows selection by analysis, by analogy, by association and simply by 'browsing' is necessary. An example of such a tool, its successes and remaining challenges, will be described.

一种面向不完整数据流上的k-支配skyline查询算法

skyline查询是数据挖掘一个重要的研究方向,在基于数据的决策支持等应用中有着重要的作用.由于现实应用中存在着大量的不完整数据流,但大多数现有的skyline查询算法都依赖于如下的假设:1)任意数据点的所有维度值都是已知的;2)数据集是稳定、有界的并且可以随意访问.此外,随着数据维度的增加,skyline数据点的个数会变得过多,因此引入了k-支配skyline的概念,但是不完整数据的k-支配关系并不具有传递性,现有的skyline查询算法都无法适用.基于这些问题,考虑到数据流高维、无界、顺序性的特点,并且在某些维度上可能具有缺失值的特性,提出了一种新的基于滑动窗口的不完整数据流的k-支配skyline查询算法,实验结果表明,算法不仅可以支持不完整数据流上的k-支配skyline计算,并能够保证效率和性能.

Image reconstruction by an alternating minimisation

This paper focuses on the problem of incomplete data in the applications of the circular cone-beam computed tomography. This problem is frequently encountered in medical imaging sciences and some other industrial imaging systems. For example, it is crucial when the high density region of objects can only be penetrated by X-rays in a limited angular range. As the projection data are only available in an angular range, the above mentioned incomplete data problem can be attributed to the limited angle problem, which is an ill-posed inverse problem. This paper reports a modified total variation minimisation method to reduce the data insufficiency in tomographic imaging. This proposed method is robust and efficient in the task of reconstruction by showing the convergence of the alternating minimisation method. The results demonstrate that this new reconstruction method brings reasonable performance. (C) 2010 Elsevier B.V. All rights reserved.

Cesarean section and rate of subsequent stillbirth, miscarriage and ectopic pregnancy: a Danish register-based cohort study

Background: With cesarean section rates increasing worldwide, clarity regarding negative effects is essential. This study aimed to investigate the rate of subsequent stillbirth, miscarriage, and ectopic pregnancy following primary cesarean section, controlling for confounding by indication. Methods and Findings: We performed a population-based cohort study using Danish national registry data linking various registers. The cohort included primiparous women with a live birth between January 1, 1982, and December 31, 2010 (n = 832,996), with follow-up until the next event (stillbirth, miscarriage, or ectopic pregnancy) or censoring by live birth, death, emigration, or study end. Cox regression models for all types of cesarean sections, sub-group analyses by type of cesarean, and competing risks analyses for the causes of stillbirth were performed. An increased rate of stillbirth (hazard ratio [HR] 1.14, 95% CI 1.01, 1.28) was found in women with primary cesarean section compared to spontaneous vaginal delivery, giving a theoretical absolute risk increase (ARI) of 0.03% for stillbirth, and a number needed to harm (NNH) of 3,333 women. Analyses by type of cesarean section showed similarly increased rates for emergency (HR 1.15, 95% CI 1.01, 1.31) and elective cesarean (HR 1.11, 95% CI 0.91, 1.35), although not statistically significant in the latter case. An increased rate of ectopic pregnancy was found among women with primary cesarean overall (HR 1.09, 95% CI 1.04, 1.15) and by type (emergency cesarean, HR 1.09, 95% CI 1.03, 1.15, and elective cesarean, HR 1.12, 95% CI 1.03, 1.21), yielding an ARI of 0.1% and a NNH of 1,000 women for ectopic pregnancy. No increased rate of miscarriage was found among women with primary cesarean, with maternally requested cesarean section associated with a decreased rate of miscarriage (HR 0.72, 95% CI 0.60, 0.85). Limitations include incomplete data on maternal body mass index, maternal smoking, fertility treatment, causes of stillbirth, and maternally requested cesarean section, as well as lack of data on antepartum/intrapartum stillbirth and gestational age for stillbirth and miscarriage. Conclusions: This study found that cesarean section is associated with a small increased rate of subsequent stillbirth and ectopic pregnancy. Underlying medical conditions, however, and confounding by indication for the primary cesarean delivery account for at least part of this increased rate. These findings will assist women and health-care providers to reach more informed decisions regarding mode of delivery.

Génération efficace de graphes d’appels dynamiques complets

Analyser le code permet de vérifier ses fonctionnalités, détecter des bogues ou améliorer sa performance. L’analyse du code peut être statique ou dynamique. Des approches combinants les deux analyses sont plus appropriées pour les applications de taille industrielle où l’utilisation individuelle de chaque approche ne peut fournir les résultats souhaités. Les approches combinées appliquent l’analyse dynamique pour déterminer les portions à problèmes dans le code et effectuent par la suite une analyse statique concentrée sur les parties identifiées. Toutefois les outils d’analyse dynamique existants génèrent des données imprécises ou incomplètes, ou aboutissent en un ralentissement inacceptable du temps d’exécution. Lors de ce travail, nous nous intéressons à la génération de graphes d’appels dynamiques complets ainsi que d’autres informations nécessaires à la détection des portions à problèmes dans le code. Pour ceci, nous faisons usage de la technique d’instrumentation dynamique du bytecode Java pour extraire l’information sur les sites d’appels, les sites de création d’objets et construire le graphe d’appel dynamique du programme. Nous démontrons qu’il est possible de profiler dynamiquement une exécution complète d’une application à temps d’exécution non triviale, et d’extraire la totalité de l’information à un coup raisonnable. Des mesures de performance de notre profileur sur trois séries de benchmarks à charges de travail diverses nous ont permis de constater que la moyenne du coût de profilage se situe entre 2.01 et 6.42. Notre outil de génération de graphes dynamiques complets, nommé dyko, constitue également une plateforme extensible pour l’ajout de nouvelles approches d’instrumentation. Nous avons testé une nouvelle technique d’instrumentation des sites de création d’objets qui consiste à adapter les modifications apportées par l’instrumentation au bytecode de chaque méthode. Nous avons aussi testé l’impact de la résolution des sites d’appels sur la performance générale du profileur.

The significance of volcanic eruption strength and frequency for climate

A simple physical model of the atmospheric effects of large explosive volcanic eruptions is developed. Using only one input parameter - the initial amount of sulphur dioxide injected into the stratosphere - the global-average stratospheric optical-depth perturbation and surface temperature response are modelled. The simplicity of this model avoids issues of incomplete data (applicable to more comprehensive models), making it a powerful and useful tool for atmospheric diagnostics of this climate forcing mechanism. It may also provide a computationally inexpensive and accurate way of introducing volcanic activity into larger climate models. The modelled surface temperature response for an initial sulphur-dioxide injection, coupled with emission-history statistics, is used to demonstrate that the most climatically significant volcanic eruptions are those of sufficient explosivity to just reach into the stratosphere (and achieve longevity). This study also highlights the fact that this measure of significance is highly sensitive to the representation of the climatic response and the frequency data used, and that we are far from producing a definitive history of explosive volcanism for at least the past 1000 years. Given this high degree of uncertainty, these results suggest that eruptions that release around and above 0.1 Mt SO2 into the stratosphere have the maximum climatic impact.

Local influence for Student-t partially linear models

In this paper we extend partial linear models with normal errors to Student-t errors Penalized likelihood equations are applied to derive the maximum likelihood estimates which appear to be robust against outlying observations in the sense of the Mahalanobis distance In order to study the sensitivity of the penalized estimates under some usual perturbation schemes in the model or data the local influence curvatures are derived and some diagnostic graphics are proposed A motivating example preliminary analyzed under normal errors is reanalyzed under Student-t errors The local influence approach is used to compare the sensitivity of the model estimates (C) 2010 Elsevier B V All rights reserved

On estimation and influence diagnostics for the Grubbs` model under heavy-tailed distributions

The Grubbs` measurement model is frequently used to compare several measuring devices. It is common to assume that the random terms have a normal distribution. However, such assumption makes the inference vulnerable to outlying observations, whereas scale mixtures of normal distributions have been an interesting alternative to produce robust estimates, keeping the elegancy and simplicity of the maximum likelihood theory. The aim of this paper is to develop an EM-type algorithm for the parameter estimation, and to use the local influence method to assess the robustness aspects of these parameter estimates under some usual perturbation schemes, In order to identify outliers and to criticize the model building we use the local influence procedure in a Study to compare the precision of several thermocouples. (C) 2008 Elsevier B.V. All rights reserved.

Assessing relationships between genetic evaluations using robust regression with an application to holsteins in Uruguay

Globalization of dairy cattle breeding has created a need for international sire proofs. Some early methods for converting proofs from one population to another are based on simple linear regression. An alternative robust regression method based on the t-distribution is presented, and maximum likelihood and Bayesian techniques for analysis are described, including the situation in which some proofs are missing. Procedures were used to investigate the relationship between Holstein sire proofs obtained by two Uruguayan genetic evaluation programs. The results suggest that conversion equations developed from data including only sires having proofs in both populations can lead to distorted results, relative to estimates obtained using techniques for incomplete data. There was evidence of non-normality of regression residuals, which constitutes an additional source of bias. A robust estimator may not solve all problems, but can provide simple conversion equations that are less sensitive to outlying proofs and to departures from assumptions.

Detecção de outliers espaciais: refinamento de similaridade e desempenho

Pós-graduação em Ciência da Computação - IBILCE

A comparative analysis of caries and fluorosis among cities with and without public water supply fluoridation in São Paulo State, Brazil

Purpose: This population-based, cross-sectional study aimed to record the DMFT index for 12 year-old children with dental caries and fluorosis levels in cities with and without public water supply fluoridation. Methods: From the 101 municipalities belonging to the Health Regional Department XV (DRSXV-SJRP) of the São Paulo state in the Southeast region of Brazil, 85 cities were selected after exclusion of those with incomplete data and less than ten years of fluoridation treatment in 2004. The criteria adopted for the assessment of dental caries and fluorosis levels were based on the guidelines published in the WHO Manual 4th edition. The data were analyzed using Fisher’s exact tests at a significance level of 5%. Results: The prevalence of caries in 12 year-old children had no significant association with fluoridated water, and was considered “moderate” and “high” in cities without fluoridation and “low” and “moderate” in cities with fluoridation. A significant association was found between water fluoridation and fluorosis (P=0.001), but not between water fluoridation and the DMFT index (P=0.119). Conclusion: The prevalence of fluorosis was related to water fluoridation in this study. However, fluorosis was also observed in non-fluoridated cities, which may result from fluoride intake through other sources.

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model. (C) 2012 Elsevier B.V. All rights reserved.

Influence Assessment in an Heteroscedastic Errors-in-Variables Model

The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential influential elements and also to quantify the effects of perturbations in these elements on some results of interest. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease.

Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance

In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regression models. Specifically, we present some aspects related to BS and log-BS distributions and their generalizations from the Student-t distribution, and develop BS-t regression models, including maximum likelihood estimation based on the EM algorithm and diagnostic tools. In addition, we apply the obtained results to real data from insurance, which shows the uses of the proposed model. Copyright (c) 2011 John Wiley & Sons, Ltd.

Global Change and the World's Mountains-Research Needs and Emerging Themes for Sustainable Development A Synthesis From the 2010 Perth II Conference

The conference on Global Change and the World’s Mountains held in Perth, Scotland, in 2010 offered a unique opportunity to analyze the state and progress of mountain research and its contribution to sustainable mountain development, as well as to reflect on required reorientations of research agendas. In this paper we provide the results of a three-step assessment of the research presented by 450 researchers from around the world. First, we determined the state of the art of mountain research and categorized it based on the analytical structure of the Global Land Project (GLP 2005). Second, we identified emerging themes for future research. Finally, we assessed the contribution of mountain research to sustainable development along the lines of the Grand Challenges in Global Sustainability Research (International Council for Science 2010). Analysis revealed that despite the growing recognition of the importance of more integrative research (inter- and transdisciplinary), the research community gathered in Perth still focuses on environmental drivers of change and on interactions within ecological systems. Only a small percentage of current research seeks to enhance understanding of social systems and of interactions between social and ecological systems. From the ecological systems perspective, a greater effort is needed to disentangle and assess different drivers of change and to investigate impacts on the rendering of ecosystem services. From the social systems perspective, significant shortcomings remain in understanding the characteristics, trends, and impacts of human movements to, within, and out of mountain areas as a form of global change. Likewise, sociocultural drivers affecting collective behavior as well as incentive systems devised by policy and decision makers are little understood and require more in-depth investigation. Both the complexity of coupled social– ecological systems and incomplete data sets hinder integrated systems research. Increased understanding of linkages and feedbacks between social and ecological systems will help to identify nonlinearities and thresholds (tipping points) in both system types. This presupposes effective collaboration between ecological and social sciences. Reflections on the Grand Challenges in Sustainability Research put forth by the International Council for Science (2010) reveal the need to intensify research on effective responses and innovations. This will help to achieve sustainable development in mountain regions while maintaining the core competence of mountain research in forecasting and observation.