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Noise attenuation prediction and analysis in rectangular lined ducts
(ISMA, 2022)
The noise of Heating, Ventilating and Air Conditioning (HVAC) systems is an important aspect when the comfort of the users is compromised. Thus, solutions to attenuate that noise need to be proposed. Linings in ducts are ...
Data-driven energy resource planning for Smart Cities
(IEEE, 2020)
Cities are growing and, therefore, the primary needs, such as the energy resources. Hence, managing them in the proper way becomes essential for a sustainable growth. This paper proposes a data-driven tool based on IoT ...
Towards an Asset Administration Shell scenario: a use case for interoperability and standardization in Industry 4.0
(IEEE, 2020)
The new paradigm of the Industry 4.0 centers on the digitalization of assets to realize a new industrial revolution. Standardization and interoperability are key for the successful implementation of this digitalization ...
Addressing the Patient Experience through Human-Centred Design: A Scoping Review
(Ubiquity Press, 2023)
Federated Explainability for Network Anomaly Characterization
(ACM, 2023)
Machine learning (ML) based systems have shown promising results for intrusion detection due to their ability to learn complex patterns. In particular, unsupervised anomaly detection approaches offer practical advantages ...
Search-based Test Case Selection for PLC Systems using Functional Block Diagram Programs
(IEEE, 2023)
Programmable Logic Controllers (PLCs) are the core unit of the production system, which frequently need to implement new processes to address customer needs. These changes must be fully tested to ensure the reliability of ...
Towards robust defect detection in casting using contrastive learning
(Springer, 2023)
Defect detection plays a vital role in ensuring product quality and safety within industrial casting processes. In these dynamic environments, the occasional emergence of new defects in the production line poses a significant ...
Mondragon ZTIM-HUB: the collaborative network for the development of stem vocations
(2022)
It is well known that STEM (Science, Technology, Engineering & Mathematics) is one of the most heard concepts both in the field of education and in the business sphere, when talking about the socio-economic needs of the ...
Application of Computer Vision and Deep Learning in the railway domain for autonomous train stop operation
(IEEE, 2020)
The purpose of this paper is to present the results of the analysis of the application of Deep Learning in the railway domain with a particular focus on a train stop operation. The paper proposes an approach consisting of ...