La literatura clandestina en la España de Carlos IV.

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Détermination automatique du seuil de binarisation des modules des gradients par modélisation de leur histogramme

National audienceThis paper presents an enhanced method of image thresholding presented in [6]. The goal is to obtain the edges of objects in an image using a gradient magnitude histogram to automatically determine the threshold value. The method must be simple to be fast and easy to implement on an FPGA circuit. The computed edges will be used within a 3D perception task for high-speed machining security.Nous présentons dans cette communication une amélioration d'une méthode présentée dans [6]. Notre objectif est d'obtenir les contours dans une image à partir de la binarisation des modules des gradients. Ces contours sont obtenus à partir d'un seuil calculé automatiquement sur l'histogramme du module des gradients. La méthode doit être simple pour être rapide, implantable sur un circuit FPGA, et doit exploiter les gradients calculés par ailleurs. La méthode sera intégrée dans une tâche de perception 3D pour la vérification de montage d'usinage en vue de sécuriser l'opération d'usinage grande vitesse

Scleroderma mimics – Clinical features and management

Systemic sclerosis is a severe immune-mediated rheumatic disease by virtue of its clinical impact and mortality. There are a number of other sclerosing skin diseases that should be considered in the differential diagnosis and these are important because they may require specialist investigation and management. In addition, long-term follow up of the different conditions should reflect the risk of associated complications and anticipated duration of therapy. This article reviews the clinical features of potential mimics of scleroderma (systemic sclerosis) including localised forms of scleroderma (morphoea) and other conditions that lead to skin thickening and connective tissue fibrosis or scarring

Aprenentatge automàtic aplicat a la valoració d'allotjaments d'Airbnb

Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2024, Director: Santi Seguí Mesquida[en] The evaluation of accommodations on the Airbnb platform is a critical factor for both travelers and hosts. In this study, we delve into how machine learning models can predict and contribute to improving the customer experience. Initially, we propose a solution to address the question “what improvements can be made to an accommodation to increase its rating and what will be the resulting gain?”. The goal is to provide useful informa- tion to hosts, enabling them to make informed decisions to enhance the quality of their services and, consequently, elevate customer satisfaction and ratings. This study tackles a fundamental part of this solution: obtaining data, preprocessing, and training predictive models to anticipate accommodation ratings. Through this research, we explore the possibilities at the intersection of artificial intelligence and the shared accommodation industry. We contribute to the growing field of practical application of machine learning, laying the groundwork for future improvements and innovations in this domain

La restauración de la Azucarera de Monzón

El proyecto parte de la preexistencia de una antigua fábrica azucarera en la ciudad de Monzón (Huesca), y de cómo a través de la investigación histórica tanto del emplazamiento como del contexto económico-social de los años 30’ hasta los últimos 60´ del siglo XX se consigue dibujar y descubrir un marco mucho mas amplio de la intervención, incluyendo la matriz geofísica del lugar y las infraestructuras industriales esenciales que dotaron de identidad a esta parcela. Partiendo de este análisis completamente necesario, se desarrolla un proyecto arquitectónico de restauración y ampliación de la nave azucarera en un museo de la industria y una sala polivalente

La literatura clandestina en la España de Carlos IV.

Sin resume

Automatic Inspection of Aeronautical Mechanical Assemblies by Matching the 3D CAD Model and Real 2D Images

International audienceIn the aviation industry, automated inspection is essential for ensuring quality of production. It allows acceleration of procedures for quality control of parts or mechanical assemblies. As a result, the demand of intelligent visual inspection systems aimed at ensuring high quality in production lines is increasing. In this work, we address a very common problem in quality control. The problem is verification of presence of the correct part and verification of its position. We address the problem in two parts: first, automatic selection of informative viewpoints before the inspection process is started (offline preparation of the inspection) and, second, automatic treatment of the acquired images from said viewpoints by matching them with information in 3D CAD models is launched. We apply this inspection system for detecting defects on aeronautical mechanical assemblies with the aim of checking whether all the subparts are present and correctly mounted. The system can be used during manufacturing or maintenance operations. The accuracy of the system is evaluated on two kinds of platform. One is an autonomous navigation robot, and the other one is a handheld tablet. The experimental results show that our proposed approach is accurate and promising for industrial applications with possibility for real-time inspection