Elements of scalable data processing

Cooperating objects (COs) is a recently coined term used to signify the convergence of classical embedded computer systems, wireless sensor networks and robotics and control. We present essential elements of a reference architecture for scalable data processing for the CO paradigm.

Data mining languages for business intelligence

Doctoral Thesis in Information Systems and Technologies Area of Engineering and Manag ement Information Systems

Task-based occupational exposure assessment and particle number concentration: two important data resources to perform risk assessment for occupational exposure to particles

Environment monitoring has an important role in occupational exposure assessment. However, due to several factors is done with insufficient frequency and normally don´t give the necessary information to choose the most adequate safety measures to avoid or control exposure. Identifying all the tasks developed in each workplace and conducting a task-based exposure assessment help to refine the exposure characterization and reduce assessment errors. A task-based assessment can provide also a better evaluation of exposure variability, instead of assessing personal exposures using continuous 8-hour time weighted average measurements. Health effects related with exposure to particles have mainly been investigated with mass-measuring instruments or gravimetric analysis. However, more recently, there are some studies that support that size distribution and particle number concentration may have advantages over particle mass concentration for assessing the health effects of airborne particles. Several exposure assessments were performed in different occupational settings (bakery, grill house, cork industry and horse stable) and were applied these two resources: task-based exposure assessment and particle number concentration by size. The results showed interesting results: task-based approach applied permitted to identify the tasks with higher exposure to the smaller particles (0.3 μm) in the different occupational settings. The data obtained allow more concrete and effective risk assessment and the identification of priorities for safety investments.

Deported Mexican migrants: health status and access to care

OBJECTIVE To describe the health status and access to care of forced-return Mexican migrants deported through the Mexico-United States border and to compare it with the situation of voluntary-return migrants. METHODS Secondary data analysis from the Survey on Migration in Mexico’s Northern Border from 2012. This is a continuous survey, designed to describe migration flows between Mexico and the United States, with a mobile-population sampling design. We analyzed indicators of health and access to care among deported migrants, and compare them with voluntary-return migrants. Our analysis sample included 2,680 voluntary-return migrants, and 6,862 deportees. We employ an ordinal multiple logistic regression model, to compare the adjusted odds of having worst self-reported health between the studied groups. RESULTS As compared to voluntary-return migrants, deportees were less likely to have medical insurance in the United States (OR = 0.05; 95%CI 0.04;0.06). In the regression model a poorer self-perceived health was found to be associated with having been deported (OR = 1.71, 95%CI 1.52;1.92), as well as age (OR = 1.03, 95%CI 1.02;1.03) and years of education (OR = 0.94 95%CI 0.93;0.95). CONCLUSIONS According to our results, deportees had less access to care while in the United States, as compared with voluntary-return migrants. Our results also showed an independent and statistically significant association between deportation and having poorer self-perceived health. To promote the health and access to care of deported Mexican migrants coming back from the United States, new health and social policies are required.

Miocene lithological, foraminiferal and palynological data from the Belverde borehole (Portugal)

XVIII Jornadas de Paleontología, 2002

Analysis of financial data series using fractional Fourier transform and multidimensional scaling

The goal of this study is the analysis of the dynamical properties of financial data series from worldwide stock market indexes during the period 2000–2009. We analyze, under a regional criterium, ten main indexes at a daily time horizon. The methods and algorithms that have been explored for the description of dynamical phenomena become an effective background in the analysis of economical data. We start by applying the classical concepts of signal analysis, fractional Fourier transform, and methods of fractional calculus. In a second phase we adopt the multidimensional scaling approach. Stock market indexes are examples of complex interacting systems for which a huge amount of data exists. Therefore, these indexes, viewed from a different perspectives, lead to new classification patterns.

Lesion detection performance in an anthropomorphic chest phantom: comparative analysis of low-dose CT data on two hybrid imaging systems

Introduction: multimodality environment; requirement for greater understanding of the imaging technologies used, the limitations of these technologies, and how to best interpret the results; dose optimization; introduction of new techniques; current practice and best practice; incidental findings, in low-dose CT images obtained as part of the hybrid imaging process, are an increasing phenomenon with advancing CT technology; resultant ethical and medico-legal dilemmas; understanding limitations of these procedures important when reporting images and recommending follow-up; free-response observer performance study was used to evaluate lesion detection in low-dose CT images obtained during attenuation correction acquisitions for myocardial perfusion imaging, on two hybrid imaging systems.

Hospitalization flow in the public and private systems in the state of Sao Paulo, Brazil

OBJECTIVE To describe the migration flows of demand for public and private hospital care among the health regions of the state of Sao Paulo, Brazil. METHODS Study based on a database of hospitalizations in the public and private systems of the state of Sao Paulo, Southeastern Brazil, in 2006. We analyzed data from 17 health regions of the state, considering people hospitalized in their own health region and those who migrated outwards (emigration) or came from other regions (immigration). The index of migration effectiveness of patients from both systems was estimated. The coverage (hospitalization coefficient) was analyzed in relation to the number of inpatient beds per population and the indexes of migration effectiveness. RESULTS The index of migration effectiveness applied to the hospital care demand flow allowed characterizing health regions with flow balance, with high emigration of public and private patients, and with high attraction of public and private patients. CONCLUSIONS There are differences in hospital care access and opportunities among health regions in the state of Sao Paulo, Brazil.

Spatial data infrastructures model for developing countries: A case study of Nigeria

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Contextual determinants of induced abortion: a panel analysis

ABSTRACT OBJECTIVE Analyze the contextual and individual characteristics that explain the differences in the induced abortion rate, temporally and territorially. METHODS We conducted an econometric analysis with panel data of the influence of public investment in health and per capita income on induced abortion as well as a measurement of the effect of social and economic factors related to the labor market and reproduction: female employment, immigration, adolescent fertility and marriage rate. The empirical exercise was conducted with a sample of 22 countries in Europe for the 2001-2009 period. RESULTS The great territorial variability of induced abortion was the result of contextual and individual socioeconomic factors. Higher levels of national income and investments in public health reduce its incidence. The following sociodemographic characteristics were also significant regressors of induced abortion: female employment, civil status, migration, and adolescent fertility. CONCLUSIONS Induced abortion responds to sociodemographic patterns, in which the characteristics of each country are essential. The individual and contextual socioeconomic inequalities impact significantly on its incidence. Further research on the relationship between economic growth, labor market, institutions and social norms is required to better understand its transnational variability and to reduce its incidence.

Dynamic network data envelopment analysis for university hospitals evaluation

ABSTRACT OBJECTIVE To develop an assessment tool to evaluate the efficiency of federal university general hospitals. METHODS Data envelopment analysis, a linear programming technique, creates a best practice frontier by comparing observed production given the amount of resources used. The model is output-oriented and considers variable returns to scale. Network data envelopment analysis considers link variables belonging to more than one dimension (in the model, medical residents, adjusted admissions, and research projects). Dynamic network data envelopment analysis uses carry-over variables (in the model, financing budget) to analyze frontier shift in subsequent years. Data were gathered from the information system of the Brazilian Ministry of Education (MEC), 2010-2013. RESULTS The mean scores for health care, teaching and research over the period were 58.0%, 86.0%, and 61.0%, respectively. In 2012, the best performance year, for all units to reach the frontier it would be necessary to have a mean increase of 65.0% in outpatient visits; 34.0% in admissions; 12.0% in undergraduate students; 13.0% in multi-professional residents; 48.0% in graduate students; 7.0% in research projects; besides a decrease of 9.0% in medical residents. In the same year, an increase of 0.9% in financing budget would be necessary to improve the care output frontier. In the dynamic evaluation, there was progress in teaching efficiency, oscillation in medical care and no variation in research. CONCLUSIONS The proposed model generates public health planning and programming parameters by estimating efficiency scores and making projections to reach the best practice frontier.

Calculation of fractional derivatives of noisy data with genetic algorithms

This paper addresses the calculation of derivatives of fractional order for non-smooth data. The noise is avoided by adopting an optimization formulation using genetic algorithms (GA). Given the flexibility of the evolutionary schemes, a hierarchical GA composed by a series of two GAs, each one with a distinct fitness function, is established.

Reconstructing the architectural evolution of volcanic islands from combined K/AR, morphologic, tectonic, and magnetic data. The Faial Island exemple (Azores)

The morpho-structural evolution of oceanic islands results from competition between volcano growth and partial destruction by mass-wasting processes. We present here a multi-disciplinary study of the successive stages of development of Faial (Azores) during the last 1 Myr. Using high-resolution digital elevation model (DEM), and new K/Ar, tectonic, and magnetic data, we reconstruct the rapidly evolving topography at successive stages, in response to complex interactions between volcanic construction and mass wasting, including the development of a graben. We show that: (1) sub-aerial evolution of the island first involved the rapid growth of a large elongated volcano at ca. 0.85 Ma, followed by its partial destruction over half a million years; (2) beginning about 360 ka a new small edifice grew on the NE of the island, and was subsequently cut by normal faults responsible for initiation of the graben; (3) after an apparent pause of ca. 250 kyr, the large Central Volcano (CV) developed on the western side of the island at ca 120 ka, accumulating a thick pile of lava flows in less than 20 kyr, which were partly channelized within the graben; (4) the period between 120 ka and 40 ka is marked by widespread deformation at the island scale, including westward propagation of faulting and associated erosion of the graben walls, which produced sedimentary deposits; subsequent growth of the CV at 40 ka was then constrained within the graben, with lava flowing onto the sediments up to the eastern shore; (5) the island evolution during the Holocene involves basaltic volcanic activity along the main southern faults and pyroclastic eruptions associated with the formation of a caldera volcano-tectonic depression. We conclude that the whole evolution of Faial Island has been characterized by successive short volcanic pulses probably controlled by brief episodes of regional deformation. Each pulse has been separated by considerable periods of volcanic inactivity during which the Faial graben gradually developed. We propose that the volume loss associated with sudden magma extraction from a shallow reservoir in different episodes triggered incremental downward graben movement, as observed historically, when immediate vertical collapse of up to 2 m was observed along the western segments of the graben at the end of the Capelinhos eruptive crises (1957-58).

Assessment of data-driven modeling strategies for water delivery canals

Conferência: CONTROLO’2012 - 16-18 July 2012 - Funchal

Data analytics in the cloud with flexible mapreduced workflows

Data analytic applications are characterized by large data sets that are subject to a series of processing phases. Some of these phases are executed sequentially but others can be executed concurrently or in parallel on clusters, grids or clouds. The MapReduce programming model has been applied to process large data sets in cluster and cloud environments. For developing an application using MapReduce there is a need to install/configure/access specific frameworks such as Apache Hadoop or Elastic MapReduce in Amazon Cloud. It would be desirable to provide more flexibility in adjusting such configurations according to the application characteristics. Furthermore the composition of the multiple phases of a data analytic application requires the specification of all the phases and their orchestration. The original MapReduce model and environment lacks flexible support for such configuration and composition. Recognizing that scientific workflows have been successfully applied to modeling complex applications, this paper describes our experiments on implementing MapReduce as subworkflows in the AWARD framework (Autonomic Workflow Activities Reconfigurable and Dynamic). A text mining data analytic application is modeled as a complex workflow with multiple phases, where individual workflow nodes support MapReduce computations. As in typical MapReduce environments, the end user only needs to define the application algorithms for input data processing and for the map and reduce functions. In the paper we present experimental results when using the AWARD framework to execute MapReduce workflows deployed over multiple Amazon EC2 (Elastic Compute Cloud) instances.