CEIG2022

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https://diglib.eg.org/handle/10.2312/2633203

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Browsing CEIG2022 by Subject "Applied computing"

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    Cylindrical Transform Slicing of Revolute Parts with Overhangs for Laser Metal Deposition
    (The Eurographics Association, 2022) Montoya-Zapata, Diego; Moreno, Aitor; Ortiz, Igor; Ruiz-Salguero, Oscar; Posada, Jorge; Posada, Jorge; Serrano, Ana
    In the context of Laser Metal Deposition (LMD), temporary support structures are needed to manufacture overhanging features. In order to limit the need for supports, multi-axis machines intervene in the deposition by sequentially repositioning the part. Under multi-axis rotations and translations, slicing and toolpath generation represent significant challenges. Slicing has been partially addressed by authors in multi-axis LMD. However, tool-path generation in multi-axis LMD is rarely touched. One of the reasons is that the required slices for LMD may be strongly non-developable. This fact produces a significant mismatch between the tool-path speeds and other parameters in Parametric space vs. actual Euclidean space. For the particular case of developable slices present in workpieces with cylindrical kernel and overhanging neighborhoods, this manuscript presents a methodology for LMD tool path generation. Our algorithm takes advantage of existing cylindrical iso-radial slicing by generating a path in the (?, z) parameter space and isometrically translating it into the R3 Euclidean space. The presented approach is advantageous because it allows the path-planning of complex structures by using the methods for conventional 2.5-axis AM. Our computer experiments show that the presented approach can be effectively used in manufacturing industrial/mechanical pieces (e.g., spur gears). Future work includes the generation of the machine g-code for actual LMD equipment.
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    Kalathos+: Construcción de datasets para la clasificación automática de fragmentos de vasijas cerámicas de torno
    (The Eurographics Association, 2022) Segura, Rafael J.; Rueda, Antonio J.; Ogáyar, Carlos J.; Fuertes, José M.; García-Fernández, Ángel L.; Lucena, Manuel J.; López, Alfonso; Moreno, Isabel; Molinos, Manuel; Posada, Jorge; Serrano, Ana
    En los últimos años las técnicas de aprendizaje profundo se han convertido en una poderosa alternativa a técnicas clásicas de aprendizaje automático orientadas a tareas de clasificación. Esta tecnología se ha aplicado con gran éxito en diversos campos, si bien es necesaria la existencia de un conjunto de datos etiquetados muy grande para afrontar el entrenamiento de las mismas. En este trabajo se presenta un framework para la generación automática de fragmentos de vasijas de cerámica de torno, convenientemente etiquetados, de manera que permitan el entrenamiento de CNNs para la clasificación de dichos fragmentos, y su posterior utilización en tareas de reconstrucción.
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    NeodiagVR: Virtual Reality Apgar test environment
    (The Eurographics Association, 2022) Ferry, Lucas; Gimeno, Jesús; Estañ, Francisco Javier; Núñez, Francisco; Balaguer, Evelin; Fernández, Marcos; Portalés, Cristina; Posada, Jorge; Serrano, Ana
    Owing to the lack of accessibility of postpartum rooms nowadays, which are needed to teach the correct assessment of newborn health status to medical students, virtual reality and simulation are increasingly used for teaching and assessing visual perception tests that evaluate the condition of the newborn. This paper aims to explain the operation of the Apgar test evaluation simulator in a virtual reality environment. This virtual environment can be manipulated externally from a web browser to visualize and control the course of the simulation in real-time. In addition, an offline version would allow initialization and visualization of the Apgar test parameters without the need for synchronization with the virtual environment.