DI-Artículos
URI permanente para esta colecciónhttps://hdl.handle.net/10953/218
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Examinando DI-Artículos por Materia "004.8 - Artificial intelligence"
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Ítem A GPU-Based Framework for Generating Implicit Datasets of Voxelized Polygonal Models for the Training of 3D Convolutional Neural Networks(IEEE, 2020-01-10) Ogáyar-Anguita, Carlos-Javier; Rueda-Ruiz, Antonio-Jesús; Segura-Sánchez, Rafael-Jesús; Díaz-Medina, Miguel; García-Fernández, Ángel-LuisIn this paper we present an efficient GPU-based framework to dynamically perform the voxelization of polygonal models for training 3D convolutional neural networks. It is designed to manage the dataset augmentation by using efficient geometric transformations and random vertex displacements in GPU. With the proposed system, every voxelization is carried out on-the-fly for directly feeding the network. The computing performance with this approach is much better than with the standard method, that carries out every voxelization of each model separately and has much higher data processing overhead. The core voxelization algorithm works by using the standard rendering pipeline of the GPU. It generates binary voxels for both the interior and the surface of the models. Moreover, it is simple, concise and very compatible with commodity hardware, as it neither uses complex data structures nor needs vendor-specific hardware or additional dependencies. This framework dramatically reduces the input/output operations, and completely eliminates the storage footprint of the voxelization dataset, managing it as an implicit dataset.Ítem Fuzzy intelligent system for patients with preeclampsia in wearable devices(Wiley, 2017-10-12) Espinilla-Estévez, Macarena; Medina-Quero, Javier; García-Fernández, Ángel Luis; Campaña, Sixto; Londoño, JorgePreeclampsia affects from 5% to 14% of all pregnant women and is responsible for about 14% of maternal deaths per year in the world. This paper is focused on the use of a decision analysis tool for the early detection of preeclampsia in women at risk. This tool applies a fuzzy linguistic approach implemented in a wearable device. In order to develop this tool, a real dataset containing data of pregnant women with high risk of preeclampsia from a health center has been analyzed, and a fuzzy linguistic methodology with two main phases is used. Firstly, linguistic transformation is applied to the dataset to increase the interpretability and flexibility in the analysis of preeclampsia. Secondly, knowledge extraction is done by means of inferring rules using decision trees to classify the dataset. The obtained linguistic rules provide understandable monitoring of preeclampsia based on wearable applications and devices. Furthermore, this paper not only introduces the proposed methodology, but also presents a wearable application prototype which applies the rules inferred from the fuzzy decision tree to detect preeclampsia in women at risk. The proposed methodology and the developed wearable application can be easily adapted to other contexts such as diabetes or hypertension.Ítem Intelligent multi-dose medication controller for fever: From wearable devices to remote dispensers(Elsevier, 2018-02-02) Medina-Quero, Javier; Espinilla-Estévez, Macarena; García-Fernández, Ángel-Luis; Martínez-López, LuisIn this work, an Intelligent Medication Controller which analyzes the data streams from body temperature provided by a wearable device is proposed in order to dispense in a low-cost remote dispenser installed at home. The main innovation of our approach is a pharmacokinetic and pharmacodynamic analysis based on the successful fuzzy linguistic approach and fuzzy logic. This analysis provides accuracy and adherence to patient fever in the decision making of medication intakes, adequating the doses and waiting time based on previous intakes. In order to show its efficiency, a case study is presented, in which a complete range of fever episodes is analyzed to compare the decision making in medication intakes of antipyretics between the human expert and the proposed Intelligent Medication Controller. Our proposal has obtained an encouraging performance when recommending medication intakes in a flexible way and assuring a secure response for contraindication cases.