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Creating a Robust SoC Estimation Algorithm Based on LSTM Units and Trained with Synthetic Data
(MDPI, 2023)
Creating SoC algorithms for Li-ion batteries based on neural networks requires a large amount of training data, since it is necessary to test the batteries under different conditions so that the algorithm learns the ...
Deobfuscating leetspeak with deep learning to improve spam filtering
(UNIR - Universidad Internacional de La Rioja, 2023)
The evolution of anti-spam filters has forced spammers to make greater efforts to bypass filters in order to distribute content over networks. The distribution of content encoded in images or the use of Leetspeak are ...
Local gradient analysis of human brain function using the Vogt-Bailey Index
(Springer, 2024)
In this work, we take a closer look at the Vogt-Bailey (VB) index, proposed in Bajada et al. (NeuroImage 221:117140, 2020) as a tool for studying local functional homogeneity in the human cortex. We interpret the VB index ...
Evolution of the European offshore renewable energy resource under multiple climate change scenarios and forecasting horizons via CMIP6
(Elsevier, 2024)
The design of the different offshore renewable energy (ORE) technologies depends on the characteristics of wind/wave resources. However, these characteristics are not stationary under climate change. In this study the ...
A comprehensive experimental investigation of the rate-dependent interlaminar delamination behaviour of CFRP composites
(Elsevier, 2023)
The paper presents a systematic experimental study of the interlaminar delamination behaviour of a carbon composite subjected to Mode I, Mode II and Mixed-mode delamination at both quasi-static (QS) and high-rate (HR) ...
Machine learning model of acoustic signatures: Towards digitalised thermal spray manufacturing
(Elsevier, 2024)
Thermal spraying, an important industrial surface manufacturing process in sectors such as aerospace, energy and biomedical, remains a skill intensive process often involving multiple trial runs impacting the yield. The ...
Testing the verification and validation capability of a DCP-based interface for distributed real-time applications
(MDPI, 2023)
Cyber–physical systems (CPS) integrate diverse elements developed by various vendors, often dispersed geographically, posing significant development challenges. This paper presents an improved version of our previously ...
Development and Comparison of Rule- and Machine Learning-Based EMS for HESS Providing Grid Services
(IEEE, 2024)
In this paper, a smart machine-learning-based energy management system (MLBEMS) is developed for a hybrid energy storage system (HESS). This HBESS consists of batteries with high-energy (HE) and high-power (HP) characteristics, ...
Predicting the effect of voids generated during RTM on the low-velocity impact behaviour by machine learning-based surrogate models
(Elsevier, 2023)
The main objective of the present paper is to demonstrate the feasibility of machine-learning-based surrogate models for predicting low-velocity impact behaviour considering void content and location generated during the ...
Aproximación multimétodo para medir el impacto de los factores de diseño en la apropiación de un software de inteligencia competitivaMultimethod approach to measure the design factor impact on the appropriation of a competitive intelligence interface
(Dyna, 2020)
La industria 4.0 y una vida laboral en continua transmutación, plantean preguntas acerca de cuáles serán las competencias que requerirán las personas para la correcta apropiación tecnológica y la mejora del desempeño. Este ...