@article{3132,

title = {Human Activity Recognition From Sensorised Patient's Data in Healthcare: A Streaming Deep Learning-Based Approach},

author = {Sandro Hurtado and José García-Nieto and Anton Popov and Ismael Navas-Delgado},

url = {https://www.ijimai.org/journal/sites/default/files/2023-02/ijimai8_1_3.pdf},

doi = {10.9781/ijimai.2022.05.004},

issn = {1989-1660},

year  = {2023},

date = {2023-03-01},

journal = {International Journal of Interactive Multimedia and Artificial Intelligence},

volume = {8},

number = {1},

pages = {23-37},

abstract = {Physical inactivity is one of the main risk factors for mortality, and its relationship with the main chronic diseases has experienced intensive medical research. A well-known method for assessing people’s activity is the use of accelerometers implanted in wearables and mobile phones. However, a series of main critical issues arise in the healthcare context related to the limited amount of available labelled data to build a classification model. Moreover, the discrimination ability of activities is often challenging to capture since the variety of movement patterns in a particular group of patients (e.g. obesity or geriatric patients) is limited over time. Consequently, the proposed work presents a novel approach for Human Activity Recognition (HAR) in healthcare to avoid this problem. This proposal is based on semi-supervised classification with Encoder-Decoder Convolutional Neural Networks (CNNs) using a combination strategy of public labelled and private unlabelled raw sensor data. In this sense, the model will be able to take advantage of the large amount of unlabelled data available by extracting relevant characteristics in these data, which will increase the knowledge in the innermost layers. Hence, the trained model can generalize well when used in real-world use cases. Additionally, real-time patient monitoring is provided by Apache Spark streaming processing with sliding windows. For testing purposes, a real-world case study is conducted with a group of overweight patients in the healthcare system of Andalusia (Spain), classifying close to 30 TBs of accelerometer sensor-based data. The proposed HAR streaming deep-learning approach properly classifies movement patterns in real-time conditions, crucial for long-term daily patient monitoring.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/jss/HorcasPF23,

title = {A modular metamodel and refactoring rules to achieve software product 

 line interoperability},

author = {José Miguel Horcas and Mónica Pinto and Lidia Fuentes},

url = {https://doi.org/10.1016/j.jss.2022.111579},

doi = {10.1016/j.jss.2022.111579},

year  = {2023},

date = {2023-01-01},

journal = {J. Syst. Softw.},

volume = {197},

pages = {111579},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/jss/HorcasGHFB23,

title = {A Monte Carlo tree search conceptual framework for feature model analyses},

author = {José Miguel Horcas and José A. Galindo and Ruben Heradio and David Fernández-Amorós and David Benavides},

url = {https://doi.org/10.1016/j.jss.2022.111551},

doi = {10.1016/j.jss.2022.111551},

year  = {2023},

date = {2023-01-01},

journal = {J. Syst. Softw.},

volume = {195},

pages = {111551},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/compsec/MunozRRL23,

title = {A survey on the (in)security of trusted execution environments},

author = {Antonio Muñoz and Ruben Rios and Rodrigo Román and Javier López},

url = {https://doi.org/10.1016/j.cose.2023.103180},

doi = {10.1016/j.cose.2023.103180},

year  = {2023},

date = {2023-01-01},

journal = {Comput. Secur.},

volume = {129},

pages = {103180},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/fgcs/GonzalezManzanoBFDA23,

title = {Cybersecurity in the digital world},

author = {Lorena González-Manzano and Marta Beltrán and José Mar'ıa Fuentes and Gianluca Dini and Cristina Alcaraz},

url = {https://doi.org/10.1016/j.future.2023.03.001},

doi = {10.1016/j.future.2023.03.001},

year  = {2023},

date = {2023-01-01},

journal = {Future Gener. Comput. Syst.},

volume = {144},

pages = {242–243},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/kbs/MunozPF23,

title = {Detecting feature influences to quality attributes in large and partially 

 measured spaces using smart sampling and dynamic learning},

author = {Daniel-Jesus Munoz and Mónica Pinto and Lidia Fuentes},

url = {https://doi.org/10.1016/j.knosys.2023.110558},

doi = {10.1016/j.knosys.2023.110558},

year  = {2023},

date = {2023-01-01},

journal = {Knowl. Based Syst.},

volume = {270},

pages = {110558},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/kbs/MunozPF23b,

title = {Detecting feature influences to quality attributes in large and partially 

 measured spaces using smart sampling and dynamic learning},

author = {Daniel-Jesus Munoz and Mónica Pinto and Lidia Fuentes},

url = {https://doi.org/10.1016/j.knosys.2023.110558},

doi = {10.1016/j.knosys.2023.110558},

year  = {2023},

date = {2023-01-01},

journal = {Knowl. Based Syst.},

volume = {270},

pages = {110558},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/sosym/HorcasPF23,

title = {Empirical analysis of the tool support for software product lines},

author = {José Miguel Horcas and Mónica Pinto and Lidia Fuentes},

url = {https://doi.org/10.1007/s10270-022-01011-2},

doi = {10.1007/s10270-022-01011-2},

year  = {2023},

date = {2023-01-01},

journal = {Softw. Syst. Model.},

volume = {22},

number = {1},

pages = {377–414},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/cbm/NematzadehGDM23,

title = {Ensemble-based genetic algorithm explainer with automized image segmentation: 

 A case study on melanoma detection dataset},

author = {Hossein Nematzadeh and José Garc'ıa-Nieto and Ismael Navas-Delgado and José Francisco Aldana Montes},

url = {https://doi.org/10.1016/j.compbiomed.2023.106613},

doi = {10.1016/j.compbiomed.2023.106613},

year  = {2023},

date = {2023-01-01},

journal = {Comput. Biol. Medicine},

volume = {155},

pages = {106613},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/cbm/SeguraOrtizGMD23,

title = {GENECI: A novel evolutionary machine learning consensus-based 

 approach for the inference of gene regulatory networks},

author = {Adrián Segura-Ortiz and José Garc'ıa-Nieto and José Francisco Aldana Montes and Ismael Navas-Delgado},

url = {https://doi.org/10.1016/j.compbiomed.2023.106653},

doi = {10.1016/j.compbiomed.2023.106653},

year  = {2023},

date = {2023-01-01},

journal = {Comput. Biol. Medicine},

volume = {155},

pages = {106653},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{GALLEGO2023100241,

title = {Maintaining flexibility in smart grid consumption through deep learning and deep reinforcement learning},

author = {Fernando Gallego and Cristian Martín and Manuel Díaz and Daniel Garrido},

url = {https://www.sciencedirect.com/science/article/pii/S2666546823000137},

doi = {https://doi.org/10.1016/j.egyai.2023.100241},

issn = {2666-5468},

year  = {2023},

date = {2023-01-01},

journal = {Energy and AI},

volume = {13},

pages = {100241},

abstract = {The smart grid concept is key to the energy revolution that has been taking place in recent years. Smart Grids have been present in energy research since their emergence. However, the scarcity of data from different energy sources, hardware power, or co-simulation environments has hindered their development. With advances in multi-agent-based systems, the possibility of simulating the behavior of different energy sources, combining real building consumption, and simulated data, storage batteries and vehicle charging points, has opened up. This development has resulted in much research published using both simulated and physical data. All these investigations show that the main problem is that the machine learning algorithms do not fully match the real behavior, it is complex to use them to replicate the different actions to be performed. This paper aims to combine the approach of behavior prediction with state-of-the-art techniques, such as deep learning and deep reinforcement learning, to simulate unknown or critical system scenarios. A very important element in smart grids is the possibility of maintaining consumption within specific ranges (flexibility). For this purpose, we have made use of Tensorflow libraries that predict energy consumption and deep reinforcement learning to select the optimal actions to be performed in our system. The developed platform is flexible enough to include new technologies such as smart batteries, electric vehicles, etc., and it is oriented to real-time operation, being applied in an on-going real project such as the European ebalance-plus project.11Ebalance-plus: https://www.ebalanceplus.eu.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{article,

title = {Portable motorized telescope system for wind turbine blades damage detection},

author = {Alejandro Carnero Hijano and Cristian Martín and Manuel Díaz},

doi = {10.1002/eng2.12618},

year  = {2023},

date = {2023-01-01},

journal = {Engineering Reports},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/bmcbi/BenitezHidalgoMDG23,

title = {SALON ontology for the formal description of sequence alignments},

author = {Antonio Ben'ıtez-Hidalgo and José Francisco Aldana Montes and Ismael Navas-Delgado and Mar'ıa Mar Roldán Garc'ıa},

url = {https://doi.org/10.1186/s12859-023-05190-7},

doi = {10.1186/s12859-023-05190-7},

year  = {2023},

date = {2023-01-01},

journal = {BMC Bioinform.},

volume = {24},

number = {1},

pages = {69},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/bmcbi/BenitezHidalgoMDG23b,

title = {SALON ontology for the formal description of sequence alignments},

author = {Antonio Ben'ıtez-Hidalgo and José Francisco Aldana Montes and Ismael Navas-Delgado and Mar'ıa Mar Roldán Garc'ıa},

url = {https://doi.org/10.1186/s12859-023-05190-7},

doi = {10.1186/s12859-023-05190-7},

year  = {2023},

date = {2023-01-01},

journal = {BMC Bioinform.},

volume = {24},

number = {1},

pages = {69},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/ase/PanizoG23,

title = {STAn: analysis of data traces using an event-driven interval temporal 

 logic},

author = {Laura Panizo and Mar'ıa-del-Mar Gallardo},

url = {https://doi.org/10.1007/s10515-022-00367-5},

doi = {10.1007/s10515-022-00367-5},

year  = {2023},

date = {2023-01-01},

journal = {Autom. Softw. Eng.},

volume = {30},

number = {1},

pages = {3},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/computing/BrogiCDPS22,

title = {Self-healing trans-cloud applications},

author = {Antonio Brogi and Jose Carrasco and Francisco Durán and Ernesto Pimentel and Jacopo Soldani},

url = {https://doi.org/10.1007/s00607-021-00977-z},

doi = {10.1007/s00607-021-00977-z},

year  = {2022},

date = {2022-01-01},

journal = {Computing},

volume = {104},

number = {4},

pages = {809–833},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/cn/AumayrCBDAGKBGK22,

title = {Service-based Analytics for 5G open experimentation platforms},

author = {Erik Aumayr and Giuseppe Caso and Anne-Marie Bosneag and Almudena D'ıaz-Zayas and Özgü Alay and Bruno Garc'ıa and Konstantinos Kousias and Anna Brunström and Pedro Merino Gómez and Harilaos Koumaras},

url = {https://doi.org/10.1016/j.comnet.2021.108740},

doi = {10.1016/j.comnet.2021.108740},

year  = {2022},

date = {2022-01-01},

journal = {Comput. Networks},

volume = {205},

pages = {108740},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{DBLP:journals/network/Luque-SchemppPG22,

title = {Toward Zero Touch Configuration of 5G Non-Public Networks for Time 

 Sensitive Networking},

author = {Francisco Luque-Schempp and Laura Panizo and Mar'ıa-del-Mar Gallardo and Pedro Merino and Javier Rivas},

url = {https://doi.org/10.1109/MNET.006.2100442},

doi = {10.1109/MNET.006.2100442},

year  = {2022},

date = {2022-01-01},

journal = {IEEE Netw.},

volume = {36},

number = {2},

pages = {50–56},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Roman2023a,

title = {Current Perspectives on Securing Critical Infrastructures’ Supply Chains},

author = {Rodrigo Roman and Cristina Alcaraz and Javier Lopez and Kouichi Sakurai},

issn = {1540-7993},

journal = {IEEE Security & Privacy},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{doi:10.1177/01655515231161562,

title = {LEGO: Linked electronic government ontology},

author = {Carlos Brys and Ismael Navas-Delgado and José F Aldana-Montes and María Mar Roldán-García},

url = {https://doi.org/10.1177/01655515231161562},

doi = {10.1177/01655515231161562},

journal = {Journal of Information Science},

volume = {0},

number = {0},

pages = {01655515231161562},

abstract = {E-government services are subject to a growing level of complexity, which requires a disruptive approach that better support the citizen needs concerning the government administration. Nowadays, available information technologies facilitate the description and online execution of administrative tasks, saving time and reducing possible errors. These technologies reduce administrative costs but require a complex electronic government system.We propose using semantic technologies to describe the e-government organisational units and services in the Open Government Data and Services context. The use of semantics improves government management, service delivery and decision-making processes.This article presents an extension of related work, introducing the evolution of the Ontology for Electronic Government (EGO): integrating other existing ontologies, supporting new features to describe e-government services and widening the usage scenarios. This extension enables the use in a real scenario with four use cases: the electronic government in the Province of Misiones (Argentina). However, the use in the domain of electronic government in a provincial context is also a proof of concept that this approach is general enough to expand into superior domains of countries that adopt the republican system of government with the division of government into the executive, legislative and judicial branches.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}