Informality and overeducation in the labor market of a developing country

In this paper, we explore the connection between labor market segmentation in two sectors, a modern protected formal sector and a traditional- unprotected-informal sector, and overeducation in a developing country. Informality is thought to have negative consequences, primarily through poorer working conditions, lack of social security, as well as low levels of productivity throughout the economy. This paper considers an aspect that has not been previously addressed, namely the fact that informality might also affect the way workers match their actual education with that required performing their job. We use micro-data from Colombia to test the relationship between overeducation and informality. Empirical results suggest that, once the endogeneity of employment choice has been accounted for, formal male workers are less likely to be overeducated. Interestingly, the propensity of being overeducated among women does not seem to be closely related to the employment choice.

University and Network Society : research report (synthesis document)

Document de síntesi d'aquest estudi que analitza -seguint una metodologia quantitativa basada en una mostra representativa de 2.093 professors i 23.864 estudiants i reforçada amb elements qualitatius- la transició que es produeix en el sistema universitari públic català cap a un model més adaptat a les noves necessitats de la societat xarxa. Per a això, es posa especial èmfasi en l'anàlisi dels usos que es fa d'Internet (l'eina clau de la societat xarxa) en el món universitari i en les transformacions que es donen o es donaran com a conseqüència d'aquests usos.

Health literacy [Document électronique] : an economic perspective and data for Switzerland. Part 2, A review of health literacy measures and a cost assessment of limited health literacy

Summary : 1. Measuring health literacy in Switzerland: a review of six surveys: 1.1 Comparison of questionnaires - 1.2 Measures of health literacy in Switzerland - 1.3 Discussion of Swiss data on HL - 1.4 Description of the six surveys: 1.4.1 Current health trends and health literacy in the Swiss population (gfs-UNIVOX), 1.4.2 Nutrition, physical exercise and body weight : opinions and perceptions of the Swiss population (USI), 1.4.3 Health Literacy in Switzerland (ISPMZ), 1.4.4 Swiss Health Survey (SHS), 1.4.5 Survey of Health, Ageing and Retirement in Europe (SHARE), 1.4.6 Adult literacy and life skills survey (ALL). - 2 . Economic costs of low health literacy in Switzerland: a rough calculation. Appendix: Screenshots cost model

Rank estimation of trajectory matrix in motion segmentation

A novel technique for estimating the rank of the trajectory matrix in the local subspace affinity (LSA) motion segmentation framework is presented. This new rank estimation is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built with LSA. The result is an enhanced model selection technique for trajectory matrix rank estimation by which it is possible to automate LSA, without requiring any a priori knowledge, and to improve the final segmentation

Enhanced Model Selection for motion segmentation

In this paper a novel rank estimation technique for trajectories motion segmentation within the Local Subspace Affinity (LSA) framework is presented. This technique, called Enhanced Model Selection (EMS), is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built by LSA. The results on synthetic and real data show that without any a priori knowledge, EMS automatically provides an accurate and robust rank estimation, improving the accuracy of the final motion segmentation

Consensus document on allergic conjunctivitis (DECA).

Allergic conjunctivitis (AC) is an inflammatory disease of the conjunctiva caused mainly by an IgE-mediated mechanism. It is the most common type of ocular allergy. Despite being the most benign form of conjunctivitis, AC has a considerable effect on patient quality of life, reduces work productivity, and increases health care costs. No consensus has been reached on its classification, diagnosis, or treatment. Consequently, the literature provides little information on its natural history, epidemiological data are scarce, and it is often difficult to ascertain its true morbidity. The main objective of the Consensus Document on Allergic Conjunctivitis (Documento dE Consenso sobre Conjuntivitis Alérgica [DECA]), which was drafted by an expert panel from the Spanish Society of Allergology and Spanish Society of Ophthalmology, was to reach agreement on basic criteria that could prove useful for both specialists and primary care physicians and facilitate the diagnosis, classification, and treatment of AC. This document is the first of its kind to describe and analyze aspects of AC that could make it possible to control symptoms.

Segmentation and grid generation for numerical simulations of vad connections with patient-specific data

Objectives: We are interested in the numerical simulation of the anastomotic region comprised between outflow canula of LVAD and the aorta. Segmenta¬tion, geometry reconstruction and grid generation from patient-specific data remain an issue because of the variable quality of DICOM images, in particular CT-scan (e.g. metallic noise of the device, non-aortic contrast phase). We pro¬pose a general framework to overcome this problem and create suitable grids for numerical simulations.Methods: Preliminary treatment of images is performed by reducing the level window and enhancing the contrast of the greyscale image using contrast-limited adaptive histogram equalization. A gradient anisotropic diffusion filter is applied to reduce the noise. Then, watershed segmentation algorithms and mathematical morphology filters allow reconstructing the patient geometry. This is done using the InsightToolKit library (www.itk.org). Finally the Vascular Model¬ing ToolKit (www.vmtk.org) and gmsh (www.geuz.org/gmsh) are used to create the meshes for the fluid (blood) and structure (arterial wall, outflow canula) and to a priori identify the boundary layers. The method is tested on five different patients with left ventricular assistance and who underwent a CT-scan exam.Results: This method produced good results in four patients. The anastomosis area is recovered and the generated grids are suitable for numerical simulations. In one patient the method failed to produce a good segmentation because of the small dimension of the aortic arch with respect to the image resolution.Conclusions: The described framework allows the use of data that could not be otherwise segmented by standard automatic segmentation tools. In particular the computational grids that have been generated are suitable for simulations that take into account fluid-structure interactions. Finally the presented method features a good reproducibility and fast application.

A multidimensional segmentation evaluation for medical image data.

Evaluation of segmentation methods is a crucial aspect in image processing, especially in the medical imaging field, where small differences between segmented regions in the anatomy can be of paramount importance. Usually, segmentation evaluation is based on a measure that depends on the number of segmented voxels inside and outside of some reference regions that are called gold standards. Although some other measures have been also used, in this work we propose a set of new similarity measures, based on different features, such as the location and intensity values of the misclassified voxels, and the connectivity and the boundaries of the segmented data. Using the multidimensional information provided by these measures, we propose a new evaluation method whose results are visualized applying a Principal Component Analysis of the data, obtaining a simplified graphical method to compare different segmentation results. We have carried out an intensive study using several classic segmentation methods applied to a set of MRI simulated data of the brain with several noise and RF inhomogeneity levels, and also to real data, showing that the new measures proposed here and the results that we have obtained from the multidimensional evaluation, improve the robustness of the evaluation and provides better understanding about the difference between segmentation methods.

Brain tissue segmentation of fetal MR images

We present a segmentation method for fetal brain tissuesof T2w MR images, based on the well known ExpectationMaximization Markov Random Field (EM- MRF) scheme. Ourmain contribution is an intensity model composed of 7Gaussian distribution designed to deal with the largeintensity variability of fetal brain tissues. The secondmain contribution is a 3-steps MRF model that introducesboth local spatial and anatomical priors given by acortical distance map. Preliminary results on 4 subjectsare presented and evaluated in comparison to manualsegmentations showing that our methodology cansuccessfully be applied to such data, dealing with largeintensity variability within brain tissues and partialvolume (PV).

Dense Deformation Field Estimation for Atlas Registration using the Active Contour Framework

In this paper, we propose a new paradigm to carry outthe registration task with a dense deformation fieldderived from the optical flow model and the activecontour method. The proposed framework merges differenttasks such as segmentation, regularization, incorporationof prior knowledge and registration into a singleframework. The active contour model is at the core of ourframework even if it is used in a different way than thestandard approaches. Indeed, active contours are awell-known technique for image segmentation. Thistechnique consists in finding the curve which minimizesan energy functional designed to be minimal when thecurve has reached the object contours. That way, we getaccurate and smooth segmentation results. So far, theactive contour model has been used to segment objectslying in images from boundary-based, region-based orshape-based information. Our registration technique willprofit of all these families of active contours todetermine a dense deformation field defined on the wholeimage. A well-suited application of our model is theatlas registration in medical imaging which consists inautomatically delineating anatomical structures. Wepresent results on 2D synthetic images to show theperformances of our non rigid deformation field based ona natural registration term. We also present registrationresults on real 3D medical data with a large spaceoccupying tumor substantially deforming surroundingstructures, which constitutes a high challenging problem.

Implementing statistical learning methods through Bayesian networks (Part 2): bayesian evaluations for results of black toner analyses in forensic document examination

This paper presents and discusses the use of Bayesian procedures - introduced through the use of Bayesian networks in Part I of this series of papers - for 'learning' probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software.

Document Tècnic de l'Edificació i annexes : cobertes, lluernaris i claraboies

El document és una recopilació de tota una informació prèvia per tal derealitzar un Document Tècnic de l’Edificació que s’ha servit de guia de les actuals NTE(Normes Tecnològiques de l’Edificació), però sense posar en dubte les NTE ni substituir-les.Aquest DTE consisteix en refer la NTE-QLC-1973 (NormaTecnològica de l’Edificació – Cubiertas Lucernarios Claraboyas), que passaràanomenar-se DTE-CLC-CP / CLC-CT. (Document Tècnic de l’Edificació – CobertesLluernaris Claraboies – Claraboies de Catàleg / Claraboies Tubulars).El meu interès per la llum natural va fer que em decidís per triar el tema de lesClaraboies, i el meu estudi es base en les claraboies de catàleg, de les quals ja parlade l’actual NTE i, a més a més, el DTE incorpora un nou tipus de claraboia com són lestubulars

Iowa Airport Directory, 2003 ***NOTE*** This document is for historical viewing, the internal information is no longer current or accurate! ***NOTE*** Current information can be found at http://www.iowadot.gov/aviation/aircraftregistration/registration.aspx ***NOTE***

Iowa has 8 commercial service airports and 105 general aviation airports, of which three serve as reliever airports. ***NOTE*** This document is for historical viewing, the internal information is no longer current or accurate! ***NOTE*** Current information can be found at http://www.iowadot.gov/aviation/aircraftregistration/registration.aspx ***NOTE***

Learning spatial filters for multispectral image segmentation

We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.