Listar por tema "Machine learning"
Mostrando ítems 1-20 de 76
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A Comparison of Feature Selection and Forecasting Machine Learning Algorithms for Predicting Glycaemia in Type 1 Diabetes Mellitus
(IOAP-MPDI, 2021-02-16)Type 1 diabetes mellitus (DM1) is a metabolic disease derived from falls in pancreatic insulin production resulting in chronic hyperglycemia. DM1 subjects usually have to undertake a number of assessments of blood glucose ... -
A cross-dataset evaluation of wearable fall detection systems
The popularity of wearables and their seamless integration into our daily lives have transformed these devices into an appealing resource to deploy automatic fall detection systems. During last years, a massive literature ... -
A generic LSTM neural network architecture to infer heterogeneous model transformations.
Models capture relevant properties of systems. During the models’ life-cycle, they are subjected to manipulations with different goals such as managing software evolution, performing analysis, increasing developers’ ... -
A Gesture Recognition Algorithm for Hand-Assisted Laparoscopic Surgery.
López-Casado, Carmen; Bauzano-Núñez, Enrique
; Rivas-Blanco, Irene; Pérez-del-Pulgar-Mancebo, Carlos Jesús; Muñoz-Martínez, Víctor Fernando (MDPI, 2019-11-26)
Minimally invasive surgery (MIS) techniques are growing in quantity and complexity to cover a wider range of interventions. More specifically, hand-assisted laparoscopic surgery (HALS) involves the use of one surgeon’s ... -
A Machine Learning Based Full Duplex System Supporting Multiple Sign Languages for the Deaf and Mute
Imran Saleem, Muhammad; Siddiqui, Atif Ahmed; Noor, Shaheena; Luque-Nieto, Miguel Ángel; Nava-Baro, Enrique (MDPI, 2023-02-28)
This manuscript presents a full duplex communication system for the Deaf and Mute (D-M) based on Machine Learning (ML). These individuals, who generally communicate through sign language, are an integral part of our society, ... -
A methodology for the development of soft sensors with Kafka-ML
Chaves, Antonio; Martín-Fernández, Cristian; Llopis-Torres, Luis Manuel; Soler-Castillo, Enrique; Díaz-Rodríguez, Manuel (Springer, 2023)
Advances in the Internet-of-Things (IoT) field have allowed a wide variety of devices to be connected and send information continuously to the Internet. Thanks to this increase in data communication, machine learning (ML) ... -
A novel embedded min-max approach for feature selection in nonlinear Support Vector Machine classification
Jiménez-Cordero, María Asunción; Morales-González, Juan Miguel; Pineda-Morente, Salvador (Elsevier, 2021)
In recent years, feature selection has become a challenging problem in several machine learning fields, such as classification problems. Support Vector Machine (SVM) is a well-known technique applied in classification ... -
A Novel System to Increase Yield of Manufacturing Test of an RF Transceiver through Application of Machine Learning
Siddiqui, Atif Ahmed; Otero-Roth, Pablo; Zubair, Muhammad (IOAP-MDPI, 2023-01-08)
Electronic manufacturing and design companies maintain test sites for a range of products. These products are designed according to the end-user requirements. The end user requirement, then, determines which of the proof ... -
Active Learning Methodology for Expert-Assisted Anomaly Detection in Mobile Communications
Trujillo, José Antonio; De la Bandera Cascales, Isabel; Burgueño Romero, Jesús; Palacios, David; Baena-Martínez, Eduardo (IOAP-MDPI, 2022-12-23)
Due to the great complexity, heterogeneity, and variety of services, anomaly detection is becoming an increasingly important challenge in the operation of new generations of mobile communications. In many cases, the ... -
AI-Assisted Fatigue and Stamina Control for Performance Sports on IMU-Generated Multivariate Times Series Datasets
Biró, Attila; Cuesta-Vargas, Antonio; Szilágyi, László (MDPI, 2023-12-26)
Background: Optimal sports performance requires a balance between intensive training and adequate rest. IMUs provide objective, quantifiable data to analyze performance dynamics, despite the challenges in quantifying athlete ... -
Analysis of functional connectome pipelines for the diagnosis of autism spectrum disorders
Maza Quiroga, Rosa María; López-Rodríguez, Domingo; Thurnhofer-Hemsi, Karl; Luque-Baena, Rafael Marcos; Jiménez Valverde, Clara; López-Rubio, Ezequiel[et al.] (2022-05)
This paper explores the effect of using different pipelines to compute connectomes (matrices representing brain connections) and use them to train machine learning models with the goal of diagnosing Autism Spectrum ... -
Ann-based predictive model of geometrical deviations in dry turning of AA7075 (Al-Zn) alloy
Trujillo-Vilches, Francisco Javier; Martín-Béjar, Sergio; Bañón-García, Fermín; Andersson, Tobias; Sevilla-Hurtado, Lorenzo (Elsevier, 2024)
This work presents the use of a shallow feedforward artificial neural network (ANN) to develop a prediction model for geometrical deviations in the dry turning of the AA7075 (Al-Zn) alloy. The study focuses on the influence ... -
Aplicación de técnicas de Deep Learning al Alineamiento Múltiple de Secuencias
(2021)En la última década, Deep Learning (DL) ha sido una de las técnicas más em pleadas en diversos campos de estudio, incluida la Bioinformática. Sin embargo, a día de hoy no existen demasiados estudios en los que se aplique ... -
Application of data augmentation techniques towards metabolomics
(Elsevier, 2022-07-27)Niemann–Pick Class 1 (NPC1) disease is a rare and debilitating neurodegenerative lysosomal storage disease (LSD). Metabolomics datasets of NPC1 patients available to perform this type of analysis are often limited in the ... -
Applications of the Internet of Medical Things to Type 1 Diabetes Mellitus
(IOAP-MDPI, 2023-02-02)Type 1 Diabetes Mellitus (DM1) is a condition of the metabolism typified by persistent hyperglycemia as a result of insufficient pancreatic insulin synthesis. This requires patients to be aware of their blood glucose level ... -
Artificial intelligence to assist specialists in the detection of haematological diseases
Díaz-del-Pino, Sergio; Trelles-Martínez, Roberto; González-Fernández, F.A.; Guil-Mata, Nicolás (Elsevier, 2023)
Artificial intelligence, particularly the growth of neural network research and development, has become an invaluable tool for data analysis, offering unrivalled solutions for image generation, natural language processing, ... -
Automatic Prediction of Developers’ Resolutions for Software Merge Conflicts
Aldndni, Waad; Meng, Na; Servant-Cortés, Francisco Javier (Elsevier, 2023)
In collaborative software development, developers simultaneously work in parallel on different branches that they merge periodically. When edits from different branches textually overlap, conflicts may occur. Manually ... -
BiPred: A Bilevel Evolutionary Algorithm for Prediction in Smart Mobility.
Toutouh-el-Alamin, Jamal; Arellano-Verdejo, Javier; Alba-Torres, Enrique (MDPI, 2018-11-24)
This article develops the design, installation, exploitation, and final utilization of intelligent techniques, hardware, and software for understanding mobility in a modern city. We focus on a smart-campus initiative in ... -
CAD system for Parkinson's Disease with penalization of non-significant or high-variability input data sources.
(Springer Nature, 2022)In the last decade, the progressive development of new machine learning schemas in combination with novel biomarkers have led us to more accurate models to diagnose and predict the evolution of neurological disorders like ... -
Clasificación de información táctil para la detección de personas
Este artículo presenta el diseño de un efector final táctil y la aplicación de técnicas de inteligencia artificial para la detección de personas mediante un brazo manipulador ligero de 6 grados de libertad. Este efector ...