Incorporating label dependency into the binary relevance framework for multi-label classification

In multi-label classification, examples can be associated with multiple labels simultaneously. The task of learning from multi-label data can be addressed by methods that transform the multi-label classification problem into several single-label classification problems. The binary relevance approach is one of these methods, where the multi-label learning task is decomposed into several independent binary classification problems, one for each label in the set of labels, and the final labels for each example are determined by aggregating the predictions from all binary classifiers. However, this approach fails to consider any dependency among the labels. Aiming to accurately predict label combinations, in this paper we propose a simple approach that enables the binary classifiers to discover existing label dependency by themselves. An experimental study using decision trees, a kernel method as well as Naive Bayes as base-learning techniques shows the potential of the proposed approach to improve the multi-label classification performance.

Spatio-temporal patterns of tuberculosis incidence in Ribeirão Preto, State of São Paulo, southeast Brazil, and their relationship with social vulnerability: a Bayesian analysis

INTRODUCTION: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirão Preto, State of São Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. METHODS: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. RESULTS: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirão Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. CONCLUSIONS: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.

Auditory processing in children and adolescents in situations of risk and vulnerability

CONTEXT AND OBJECTIVE: Children and adolescents who live in situations of social vulnerability present a series of health problems. Nonetheless, affirmations that sensory and cognitive abnormalities are present are a matter of controversy. The aim of this study was to investigate aspects to auditory processing, through applying the brainstem auditory evoked potential (BAEP) and behavioral auditory processing tests to children living on the streets, and comparison with a control group. DESIGN AND SETTING: Cross-sectional study in the Laboratory of Auditory Processing, School of Medicine, Universidade de São Paulo. METHODS: The auditory processing tests were applied to a group of 27 individuals, subdivided into 11 children (7 to 10 years old) and 16 adolescents (11 to 16 years old), of both sexes, in situations of social vulnerability, compared with an age-matched control group of 10 children and 11 adolescents without complaints. The BAEP test was also applied to investigate the integrity of the auditory pathway. RESULTS: For both children and adolescents, there were significant differences between the study and control groups in most of the tests applied, with significantly worse performance in the study group, except in the pediatric speech intelligibility test. Only one child had an abnormal result in the BAEP test. CONCLUSIONS: The results showed that the study group (children and adolescents) presented poor performance in the behavioral auditory processing tests, despite their unaltered auditory brainstem pathways, as shown by their normal results in the BAEP test.

Incorporating IT & AT Convergence into Lean Thinking/Six Sigma via the Smarter Operation Transformation (SOT) Methodology

The growing demands for industrial products are imposing an increasingly intense level of competitiveness on the industrial operations. In the meantime, the convergence of information technology (IT) and automation technology (AT) is showing itself to be a tool of great potential for the modernization and improvement of industrial plants. However, for this technology fully to achieve its potential, several obstacles need to be overcome, including the demonstration of the reasoning behind estimations of benefits, investments and risks used to plan the implementation of corporative technology solutions. This article focuses on the evolutionary development of planning and adopting processes of IT & AT convergence. It proposes the incorporation of IT & AT convergence practices into Lean Thinking/Six Sigma, via the method used for planning the convergence of technological activities, known as the Smarter Operation Transformation (SOT) methodology. This article illustrates the SOT methodology through its application in a Brazilian company in the sector of consumer goods. In this application, it is shown that with IT & AT convergence is possible with low investment, in order to reduce the risk of not achieving the goals of key indicators.

Coastal flood vulnerability assessment with geomatic methods: Test sites of western Thailand, Sydney (Australia) and aeolian islands (south tyrrhenian sea, Italy)

The work undertaken in this PhD thesis is aimed at the development and testing of an innovative methodology for the assessment of the vulnerability of coastal areas to marine catastrophic inundation (tsunami). Different approaches are used at different spatial scales and are applied to three different study areas: 1. The entire western coast of Thailand 2. Two selected coastal suburbs of Sydney – Australia 3. The Aeolian Islands, in the South Tyrrhenian Sea – Italy I have discussed each of these cases study in at least one scientific paper: one paper about the Thailand case study (Dall’Osso et al., in review-b), three papers about the Sydney applications (Dall’Osso et al., 2009a; Dall’Osso et al., 2009b; Dall’Osso and Dominey-Howes, in review) and one last paper about the work at the Aeolian Islands (Dall’Osso et al., in review-a). These publications represent the core of the present PhD thesis. The main topics dealt with are outlined and discussed in a general introduction while the overall conclusions are outlined in the last section.

The Influence of Fractures on Vulnerability to Pollution of a Carbonate Aquifer: Monte Conero (Italy)

The carbonate outcrops of the anticline of Monte Conero (Italy) were studied in order to characterize the geometry of the fractures and to establish their influence on the petrophysical properties (hydraulic conductivity) and on the vulnerability to pollution. The outcrops form an analog for a fractured aquifer and belong to the Maiolica Fm. and the Scaglia Rossa Fm. The geometrical properties of fractures such as orientation, length, spacing and aperture were collected and statistically analyzed. Five types of mechanical fractures were observed: veins, joints, stylolites, breccias and faults. The types of fractures are arranged in different sets and geometric assemblages which form fracture networks. In addition, the fractures were analyzed at the microscale using thin sections. The fracture age-relationships resulted similar to those observed at the outcrop scale, indicating that at least three geological episodes have occurred in Monte Conero. A conceptual model for fault development was based on the observations of veins and stylolites. The fracture sets were modelled by the code FracSim3D to generate fracture network models. The permeability of a breccia zone was estimated at microscale by and point counting and binary image methods, whereas at the outcrop scale with Oda’s method. Microstructure analysis revealed that only faults and breccias are potential pathways for fluid flow since all veins observed are filled with calcite. According this, three scenarios were designed to asses the vulnerability to pollution of the analogue aquifer: the first scenario considers the Monte Conero without fractures, second scenario with all observed systematic fractures and the third scenario with open veins, joints and faults/breccias. The fractures influence the carbonate aquifer by increasing its porosity and hydraulic conductivity. The vulnerability to pollution depends also on the presence of karst zones, detric zones and the material of the vadose zone.

Seismic vulnerability of the ancient albergotti's manor in Arezzo, Italy

The thesis moves from the need of understanding how a historical building would behave in case of earthquake and this purpose is strongly linked to the fact that the majority of Italian structures are old ones placed in seismic sites. Primarily an architectural and chronological research is provided in order to figure out how the building has developed in time; then, after the reconstruction of the skeleton of the analyzed element (“Villa i Bossi” in Gragnone, AR), a virtual model is created such that the main walls and sections are tested according to the magnitude of expected seismic events within the reference area. This approach is basically aimed at verifying the structure’s reliability as composed by single units; the latter are treated individually in order to find out all the main critical points where rehabilitation might be needed. Finally the most harmful sections are studied in detail and proper strengthening is advised according to the current know-how.

Vulnerability and robustness indices against blackouts in power grids

In this dissertation some novel indices for vulnerability and robustness assessment of power grids are presented. Such indices are mainly defined from the structure of transmission power grids, and with the aim of Blackout (BO) prevention and mitigation. Numerical experiments showing how they could be used alone or in coordination with pre-existing ones to reduce the effects of BOs are discussed. These indices are introduced inside 3 different sujects: The first subject is for taking a look into economical aspects of grids’ operation and their effects in BO propagation. Basically, simulations support that: the determination to operate the grid in the most profitable way could produce an increase in the size or frequency of BOs. Conversely, some uneconomical ways of supplying energy are shown to be less affected by BO phenomena. In the second subject new topological indices are devised to address the question of "which are the best buses to place distributed generation?". The combined use of two indices, is shown as a promising alternative for extracting grid’s significant features regarding robustness against BOs and distributed generation. For this purpose, a new index based on outage shift factors is used along with a previously defined electric centrality index. The third subject is on Static Robustness Analysis of electric networks, from a purely structural point of view. A pair of existing topological indices, (namely degree index and clustering coefficient), are combined to show how degradation of the network structure can be accelerated. Blackout simulations were carried out using the DC Power Flow Method and models of transmission networks from the USA and Europe.