Estructura salarial y segmentación en el mercado laboral de Colombia: un análisis de las siete principales ciudades, 2001-2005

Este documento se concentra en el estudio de las diferencias salariales mediante la comparación de las distribuciones de los salarios para las siete principales ciudades colombianas en el periodo 2001-2005 con datos de la Encuesta Continua de Hogares. Se detectan diferencias significativas que se explican a la luz de la teoría del capital humano y de segmentación laboral; mediante la estimación de ecuaciones de salarios a partir de las características socioeconómicas de los trabajadores junto con efectos particulares para región y rama de actividad económica que resultan significativos dando evidencia de segmentación del mercado laboralen Colombia. El componente de los salarios que es particular a la región y a la actividad económica se explica a partir de variables macroeconómicas como el crecimiento económico, la dotación sectorial de factores, el costo de vida y el desempleo a nivel regional.

Heterogeneity and the formation of risk - sharing coalitions

We offer a new explanation of partial risk sharing based on coalition formation and segmentation of society in a risky environment, without assuming limited commitment and imperfect information. Heterogenous individuals in a society freely choose with whom they will share risk. A partition belonging to the core of the membership game obtains. Perfect risk sharing does not necessarily arise. Focusing on mutual insurance rule and assuming that individuals only differ with respect to risk, we show that the core partition is homophily-based. The distribution of risk affects the number and size of these coalitions. Individuals may pay a lower risk premium in riskier societies. A higher heterogeneity in risk leads to a lower degree of risk sharing. We discuss how the endogenous partition of society into risk-sharing coalitions may shed light on empirical evidence on partial risk sharing. The case of heterogenous risk aversion leads to similar results.

Klapcast

Es una plataforma de doble lado que tiene como objetivo fundamental acercar a los buscadores de talento de una forma eficaz y precisa a los actores. Esta propuesta empresarial quiere mejorar las condiciones laborales de estos últimos mediante la tecnología disponible y un know know digital. Así mismo, generar el primer banco consolidado de talentos del país y contribuir a la solidificación de un segmento cultural.

Influencia de la relación estratégica comunitaria y el marketing en la salud financiera de las organizaciones en mercados internacionales

La globalización de mercados ha generado una serie de cambios en la estructura del comercio internacional, como el surgimiento de áreas de libre comercio, que son el resultado de las integraciones económicas, las cuales han facilitado los flujos de capital, recursos y personas. La internacionalización no solamente se ha convertido en una estrategia para aprovechar las oportunidades que se dan en los mercados internacionales, sino también en un medio de diversificación del riesgo para reducir la dependencia del mercado doméstico. Sin embargo, para emprender un proceso de internacionalización, es necesario conocer muy bien el contexto dentro del cual se desarrollan los clientes, puesto que la falta de conocimiento del entorno puede perjudicar la salud financiera de la empresa. De ahí la importancia de utilizar una definición de comunidad y unas estrategias comunitarias con las cuales se identifiquen las necesidades, objetivos e intereses de la comunidad, para establecer un relación a largo plazo que procure el desarrollo de ambas partes. La relación estratégica comunitaria y el marketing impactan positivamente la salud financiera de la empresa, en la medida en que este desarrollo mutuo, tanto de la comunidad como de la empresa, no solamente incrementa el interés y el compromiso por seguir interactuando; también crea vínculos afectivos entre ambas partes, lo cual consolida aún más la perdurabilidad de la relación, logrando así una fidelización de los clientes y por ende aumentando la rentabilidad de la empresa.

Automatic diagnosis of voltage disturbances in power distribution networks

This thesis proposes a framework for identifying the root-cause of a voltage disturbance, as well as, its source location (upstream/downstream) from the monitoring place. The framework works with three-phase voltage and current waveforms collected in radial distribution networks without distributed generation. Real-world and synthetic waveforms are used to test it. The framework involves features that are conceived based on electrical principles, and assuming some hypothesis on the analyzed phenomena. Features considered are based on waveforms and timestamp information. Multivariate analysis of variance and rule induction algorithms are applied to assess the amount of meaningful information explained by each feature, according to the root-cause of the disturbance and its source location. The obtained classification rates show that the proposed framework could be used for automatic diagnosis of voltage disturbances collected in radial distribution networks. Furthermore, the diagnostic results can be subsequently used for supporting power network operation, maintenance and planning.

An approach to coded structured light to obtain three dimensional information

The human visual ability to perceive depth looks like a puzzle. We perceive three-dimensional spatial information quickly and efficiently by using the binocular stereopsis of our eyes and, what is mote important the learning of the most common objects which we achieved through living. Nowadays, modelling the behaviour of our brain is a fiction, that is why the huge problem of 3D perception and further, interpretation is split into a sequence of easier problems. A lot of research is involved in robot vision in order to obtain 3D information of the surrounded scene. Most of this research is based on modelling the stereopsis of humans by using two cameras as if they were two eyes. This method is known as stereo vision and has been widely studied in the past and is being studied at present, and a lot of work will be surely done in the future. This fact allows us to affirm that this topic is one of the most interesting ones in computer vision. The stereo vision principle is based on obtaining the three dimensional position of an object point from the position of its projective points in both camera image planes. However, before inferring 3D information, the mathematical models of both cameras have to be known. This step is known as camera calibration and is broadly describes in the thesis. Perhaps the most important problem in stereo vision is the determination of the pair of homologue points in the two images, known as the correspondence problem, and it is also one of the most difficult problems to be solved which is currently investigated by a lot of researchers. The epipolar geometry allows us to reduce the correspondence problem. An approach to the epipolar geometry is describes in the thesis. Nevertheless, it does not solve it at all as a lot of considerations have to be taken into account. As an example we have to consider points without correspondence due to a surface occlusion or simply due to a projection out of the camera scope. The interest of the thesis is focused on structured light which has been considered as one of the most frequently used techniques in order to reduce the problems related lo stereo vision. Structured light is based on the relationship between a projected light pattern its projection and an image sensor. The deformations between the pattern projected into the scene and the one captured by the camera, permits to obtain three dimensional information of the illuminated scene. This technique has been widely used in such applications as: 3D object reconstruction, robot navigation, quality control, and so on. Although the projection of regular patterns solve the problem of points without match, it does not solve the problem of multiple matching, which leads us to use hard computing algorithms in order to search the correct matches. In recent years, another structured light technique has increased in importance. This technique is based on the codification of the light projected on the scene in order to be used as a tool to obtain an unique match. Each token of light is imaged by the camera, we have to read the label (decode the pattern) in order to solve the correspondence problem. The advantages and disadvantages of stereo vision against structured light and a survey on coded structured light are related and discussed. The work carried out in the frame of this thesis has permitted to present a new coded structured light pattern which solves the correspondence problem uniquely and robust. Unique, as each token of light is coded by a different word which removes the problem of multiple matching. Robust, since the pattern has been coded using the position of each token of light with respect to both co-ordinate axis. Algorithms and experimental results are included in the thesis. The reader can see examples 3D measurement of static objects, and the more complicated measurement of moving objects. The technique can be used in both cases as the pattern is coded by a single projection shot. Then it can be used in several applications of robot vision. Our interest is focused on the mathematical study of the camera and pattern projector models. We are also interested in how these models can be obtained by calibration, and how they can be used to obtained three dimensional information from two correspondence points. Furthermore, we have studied structured light and coded structured light, and we have presented a new coded structured light pattern. However, in this thesis we started from the assumption that the correspondence points could be well-segmented from the captured image. Computer vision constitutes a huge problem and a lot of work is being done at all levels of human vision modelling, starting from a)image acquisition; b) further image enhancement, filtering and processing, c) image segmentation which involves thresholding, thinning, contour detection, texture and colour analysis, and so on. The interest of this thesis starts in the next step, usually known as depth perception or 3D measurement.

Apendice: version portugaise de la série sur l'exposition / a revolução museológica faz-se a partir da exposição

Version adaptée de la série française, préparée par Luisa Rogado, pour servir à deux projets (Musée de la forge, Casa museu de la misericorde), dans la Municipalité d’Alcoutin, en Algarve. Le projet avait, entre autres , pour but d’éviter les erreurs qui firent du Musée du Guadiana, à Guerreiro dos Rios, un semi échec, les contrôles du design et du programme d’animation ayant échappé à la muséologue, coordonnatrice du projet, qui servira néanmoins de leçon au projet pilote de Carrapateira (Musée de la Terre et de la Mer) tous deux devant être jumelés comme les premiers prototypes de musées locaux de la nouvelle génération. Le musée de Carapateira introduira dans sa toute dernière phase le récit donnant sa cohésion à l’ensemble de la segmentation thématique. Cet épisode est rapporté dans l´étude de cas de carapateira sur le rapport exposition-institution (tutelle) dans le texte d’une communication intitutée «L’exposition, la face déchaînée du musée» Pierre Mayrand, ACFAS, 2008.

Manta: una ciudad-puerto en el siglo XIX. Economía regional y mercado mundial (Estudios)

El ensayo analiza el surgimiento de la ciudad de Manta como estación de enlace entre la región de Manabí y el mercado mundial en el siglo XIX. Esta región económica estuvo integrada por un sistema de pequeñas localidades, cada una de las cuales cumplía una función determinada. El puerto de Manta experimentó un sorprendente despegue debido al auge manufacturero de los sombreros de paja toquilla y, más tarde, al auge agroexportador de la tagua y el cacao. Estudia, además, el proceso de recolonización por parte de grupos blanco-mestizos y la segmentación del espacio entre los nuev s inmigrantes y los descendientes de los antiguos indios.

DTM generation from LIDAR data using skewness balancing

LIght Detection And Ranging (LIDAR) data for terrain and land surveying has contributed to many environmental, engineering and civil applications. However, the analysis of Digital Surface Models (DSMs) from complex LIDAR data is still challenging. Commonly, the first task to investigate LIDAR data point clouds is to separate ground and object points as a preparatory step for further object classification. In this paper, the authors present a novel unsupervised segmentation algorithm-skewness balancing to separate object and ground points efficiently from high resolution LIDAR point clouds by exploiting statistical moments. The results presented in this paper have shown its robustness and its potential for commercial applications.

Enhancing change detection in low-quality surveillance footage using markov random fields

Urban surveillance footage can be of poor quality, partly due to the low quality of the camera and partly due to harsh lighting and heavily reflective scenes. For some computer surveillance tasks very simple change detection is adequate, but sometimes a more detailed change detection mask is desirable, eg, for accurately tracking identity when faced with multiple interacting individuals and in pose-based behaviour recognition. We present a novel technique for enhancing a low-quality change detection into a better segmentation using an image combing estimator in an MRF based model.

Evaluation of probabilistic occupancy map people detection for surveillance systems

In this paper, we evaluate the Probabilistic Occupancy Map (POM) pedestrian detection algorithm on the PETS 2009 benchmark dataset. POM is a multi-camera generative detection method, which estimates ground plane occupancy from multiple background subtraction views. Occupancy probabilities are iteratively estimated by fitting a synthetic model of the background subtraction to the binary foreground motion. Furthermore, we test the integration of this algorithm into a larger framework designed for understanding human activities in real environments. We demonstrate accurate detection and localization on the PETS dataset, despite suboptimal calibration and foreground motion segmentation input.

An empirical study of process-related attributes in segmented software cost-estimation relationships

Parametric software effort estimation models consisting on a single mathematical relationship suffer from poor adjustment and predictive characteristics in cases in which the historical database considered contains data coming from projects of a heterogeneous nature. The segmentation of the input domain according to clusters obtained from the database of historical projects serves as a tool for more realistic models that use several local estimation relationships. Nonetheless, it may be hypothesized that using clustering algorithms without previous consideration of the influence of well-known project attributes misses the opportunity to obtain more realistic segments. In this paper, we describe the results of an empirical study using the ISBSG-8 database and the EM clustering algorithm that studies the influence of the consideration of two process-related attributes as drivers of the clustering process: the use of engineering methodologies and the use of CASE tools. The results provide evidence that such consideration conditions significantly the final model obtained, even though the resulting predictive quality is of a similar magnitude.

Learning enhanced 3D models for vehicle tracking

This paper presents an enhanced hypothesis verification strategy for 3D object recognition. A new learning methodology is presented which integrates the traditional dichotomic object-centred and appearance-based representations in computer vision giving improved hypothesis verification under iconic matching. The "appearance" of a 3D object is learnt using an eigenspace representation obtained as it is tracked through a scene. The feature representation implicitly models the background and the objects observed enabling the segmentation of the objects from the background. The method is shown to enhance model-based tracking, particularly in the presence of clutter and occlusion, and to provide a basis for identification. The unified approach is discussed in the context of the traffic surveillance domain. The approach is demonstrated on real-world image sequences and compared to previous (edge-based) iconic evaluation techniques.

Driving saccade to pursuit using image motion

Within the context of active vision, scant attention has been paid to the execution of motion saccades—rapid re-adjustments of the direction of gaze to attend to moving objects. In this paper we first develop a methodology for, and give real-time demonstrations of, the use of motion detection and segmentation processes to initiate capture saccades towards a moving object. The saccade is driven by both position and velocity of the moving target under the assumption of constant target velocity, using prediction to overcome the delay introduced by visual processing. We next demonstrate the use of a first order approximation to the segmented motion field to compute bounds on the time-to-contact in the presence of looming motion. If the bound falls below a safe limit, a panic saccade is fired, moving the camera away from the approaching object. We then describe the use of image motion to realize smooth pursuit, tracking using velocity information alone, where the camera is moved so as to null a single constant image motion fitted within a central image region. Finally, we glue together capture saccades with smooth pursuit, thus effecting changes in both what is being attended to and how it is being attended to. To couple the different visual activities of waiting, saccading, pursuing and panicking, we use a finite state machine which provides inherent robustness outside of visual processing and provides a means of making repeated exploration. We demonstrate in repeated trials that the transition from saccadic motion to tracking is more likely to succeed using position and velocity control, than when using position alone.

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy. The accuracy was reduced in urban areas partly because of TerraSAR-X’s restricted visibility of the ground surface due to radar shadow and layover.