Publications

@article{760f1c40554947a3a2ced73834a1c13f,
title = "3D convolutional and recurrent neural networks for reactor perturbation unfolding and anomaly detection",
abstract = "With Europe's ageing fleet of nuclear reactors operating closer to their safety limits, the monitoring of such reactors through complex models has become of great interest to maintain a high level of availability and safety. Therefore, we propose an extended Deep Learning framework as part of the CORTEX Horizon 2020 EU project for the unfolding of reactor transfer functions from induced neutron noise sources. The unfolding allows for the identification and localisation of reactor core perturbation sources from neutron detector readings in Pressurised Water Reactors. A 3D Convolutional Neural Network (3D-CNN) and Long Short-Term Memory (LSTM) Recurrent Neural Network (RNN) have been presented, each to study the signals presented in frequency and time domain respectively. The proposed approach achieves state-of-the-art results with the classification of perturbation type in the frequency domain reaching 99.89% accuracy and localisation of the classified perturbation source being regressed to 0.2902 Mean Absolute Error (MAE).",
keywords = "Machine Learning, Deep Learning, nuclear reactors, signal processing",
author = "Aiden Durrant and Georgios Leontidis and Stefanos Kollias",
note = "The research conducted was made possible through funding from the Euratom research and training programme 2014-2018 under grant agreement No 754316 for the {\textquoteleft}CORe Monitoring Techniques And EXperimental Validation And Demonstration (CORTEX){\textquoteright} Horizon 2020 project, 2017-2021. We would like to thank the Chalmers University of Technology, particularly Dr C. Demaziere, Dr P. Vinai, Dr A. Milonakis and the Paul Scherrer Institute, particularly Dr A. Dokhane and Dr V. Verma for providing the frequency and domain data respectively, for assisting us with their understanding and for collaborating with us in the analysis process.",
year = "2019",
doi = "10.1051/epjn/2019047",
language = "English",
volume = "5",
journal = "EPJ Nuclear Sciences & Technologies",

}

@inproceedings{AILS:conf/dlog/ChortarasGS19,
author = {Alexandros Chortaras and
Michalis Giazitzoglou and
Giorgos Stamou},
title = {Inside the Query Space of {DL} Knowledge Bases},
booktitle = {Proceedings of the 32nd International Workshop on Description Logics,
Oslo, Norway, June 18-21, 2019.},
year = {2019},
url = {http://ceur-ws.org/Vol-2373/paper-11.pdf}
}

@inproceedings{AILS:conf/smap/KaldeliTGCTS19,
author = {Eirini Kaldeli and
Gianna Tsakou and
Danilo Giglitto and
Francesca Cesaroni and
Vassilis Tzouvaras and
Giorgos Stamou},
title = {CultureLabs: Cultural Heritage and Digital Technology at the Service
of Social Innovation},
booktitle = {Proceedings of the Workshop on Cultural Informatics co-located with
the 14th International Workshop On Semantic And Social Media Adaptation
And Personalization, CI@SMAP 2019, Larnaca, Cyprus, June 9, 2019.},
year = {2019},
url = {http://ceur-ws.org/Vol-2412/paper9.pdf}
}

@inproceedings{AILS:conf/visapp/KonidarisTSS19,
author = {Filippos Konidaris and
Thanos Tagaris and
Maria Sdraka and
Andreas Stafylopatis},
title = {Generative Adversarial Networks as an Advanced Data Augmentation Technique
for {MRI} Data},
booktitle = {Proceedings of the 14th International Joint Conference on Computer
Vision, Imaging and Computer Graphics Theory and Applications, {VISIGRAPP}
2019, Volume 5: VISAPP, Prague, Czech Republic, February 25-27, 2019.},
pages = {48--59},
year = {2019},
url = {https://doi.org/10.5220/0007363900480059},
doi = {10.5220/0007363900480059}
}

@inproceedings{AILS:conf/www/AlexandridisTSS19,
author = {Georgios Alexandridis and
Thanos Tagaris and
Giorgos Siolas and
Andreas Stafylopatis},
title = {From Free-text User Reviews to Product Recommendation using Paragraph
Vectors and Matrix Factorization},
booktitle = {Companion of The 2019 World Wide Web Conference, {WWW} 2019, San Francisco,
CA, USA, May 13-17, 2019.},
pages = {335--343},
year = {2019},
url = {https://doi.org/10.1145/3308560.3316601},
doi = {10.1145/3308560.3316601}
}

@inproceedings{AILS:conf/eann/PotamiasSS19,
author = {Rolandos Alexandros Potamias and
Georgios Siolas and
Andreas Stafylopatis},
title = {A Robust Deep Ensemble Classifier for Figurative Language Detection},
booktitle = {Engineering Applications of Neural Networks - 20th International Conference,
{EANN} 2019, Hersonissos, Crete, Greece, May 24-26, 2019, Proceedings},
pages = {164--175},
year = {2019},
url = {https://doi.org/10.1007/978-3-030-20257-6\_14},
doi = {10.1007/978-3-030-20257-6\_14}
}

@inproceedings{AILS:conf/evoW/PapagiannisAS19,
author = {Tasos Papagiannis and
Georgios Alexandridis and
Andreas Stafylopatis},
title = {{GAMER:} {A} Genetic Algorithm with Motion Encoding Reuse for Action-Adventure
Video Games},
booktitle = {Applications of Evolutionary Computation - 22nd International Conference,
EvoApplications 2019, Held as Part of EvoStar 2019, Leipzig, Germany,
April 24-26, 2019, Proceedings},
pages = {156--171},
year = {2019},
url = {https://doi.org/10.1007/978-3-030-16692-2\_11},
doi = {10.1007/978-3-030-16692-2\_11}
}