Andrés Tello

1. Graph Neural Networks for Pressure Estimation in Water Distribution Systems (H. Truong, A. Tello, A. Lazovik and V. Degeler), In Water Resources Research, 2024.

   Abstract

   Abstract Pressure and flow estimation in water distribution networks (WDNs) allows water management companies to optimize their control operations. For many years, mathematical simulation tools have been the most common approach to reconstructing an estimate of the WDNs hydraulics. However, pure physics-based simulations involve several challenges, for example, partially observable data, high uncertainty, and extensive manual calibration. Thus, data-driven approaches have gained traction to overcome such limitations. In this work, we combine physics-based modeling and graph neural networks (GNN), a data-driven approach, to address the pressure estimation problem. Our work has two main contributions. First, a training strategy that relies on random sensor placement making our GNN-based estimation model robust to unexpected sensor location changes. Second, a realistic evaluation protocol that considers real temporal patterns and noise injection to mimic the uncertainties intrinsic to real-world scenarios. As a result, a new state-of-the-art model, GAT with Residual Connections, for pressure estimation is available. Our model surpasses the performance of previous studies on several WDNs benchmarks, showing a reduction of absolute error of ≈40% on average.

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   BibTeX

   
   @article{huy2024gatres, title = "Graph Neural Networks for Pressure Estimation in Water Distribution Systems", abstract = "Abstract Pressure and flow estimation in water distribution networks (WDNs) allows water management companies to optimize their control operations. For many years, mathematical simulation tools have been the most common approach to reconstructing an estimate of the WDNs hydraulics. However, pure physics-based simulations involve several challenges, for example, partially observable data, high uncertainty, and extensive manual calibration. Thus, data-driven approaches have gained traction to overcome such limitations. In this work, we combine physics-based modeling and graph neural networks (GNN), a data-driven approach, to address the pressure estimation problem. Our work has two main contributions. First, a training strategy that relies on random sensor placement making our GNN-based estimation model robust to unexpected sensor location changes. Second, a realistic evaluation protocol that considers real temporal patterns and noise injection to mimic the uncertainties intrinsic to real-world scenarios. As a result, a new state-of-the-art model, GAT with Residual Connections, for pressure estimation is available. Our model surpasses the performance of previous studies on several WDNs benchmarks, showing a reduction of absolute error of ≈40\% on average.", author = "H. Truong and A. Tello and A. Lazovik and V. Degeler", year = "2024", month = jun, language = "English", doi = "https://doi.org/10.1029/2023WR036741", url = "https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2023WR036741", journal = "Water Resources Research", }

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   urldoi
2. Large-scale multipurpose benchmark datasets for assessing data-driven deep learning approaches for water distribution networks (A. Tello, H. Truong, A. Lazovik and V. Degeler), In Engineering Proceedings, MDPI, volume 69, 2024.

   BibTeX

   
   @article{tello2024:wdsa-ccwi, title={Large-scale multipurpose benchmark datasets for assessing data-driven deep learning approaches for water distribution networks}, author={A. Tello and H. Truong and A. Lazovik and V. Degeler}, journal={Engineering Proceedings}, volume={69}, number={1}, pages={50}, year={2024}, publisher={MDPI} }

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3. Graph neural networks for pressure estimation in water distribution systems (H. Truong, A. Tello, A. Lazovik and V. Degeler), In Water Resources Research, Wiley Online Library, volume 60, 2024.

   BibTeX

   
   @article{truong2024:wrr, title={Graph neural networks for pressure estimation in water distribution systems}, author={H. Truong and A. Tello and A. Lazovik and V. Degeler}, journal={Water Resources Research}, volume={60}, number={7}, pages={e2023WR036741}, year={2024}, publisher={Wiley Online Library} }

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4. DiTEC: Digital Twin for Evolutionary Changes in Water Distribution Networks (V. Degeler, M. Hadadian, E. Karabulut, H. A. Lazovik, H. van het Loo, A. Tello and H. Troung), In , 2024.

   BibTeX

   
   @article{degeler2024ditec, title={DiTEC: Digital Twin for Evolutionary Changes in Water Distribution Networks}, author={V. Degeler and M. Hadadian and E. Karabulut and H. A. Lazovik and H. van het Loo and A. Tello and H. Troung}, year={2024} }

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5. DiTEC: Digital Twin for Evolutionary Changes in Water Distribution Networks (V. Degeler, M. Hadadian, E. Karabulut, A. Lazovik, H. Loo, A. Tello and H. Truong), In Leveraging Applications of Formal Methods, Verification and Validation. Application Areas, Springer Nature Switzerland, 2024.

   Abstract

   Conventional digital twins (DT) for critical infrastructures are widely used to model and simulate the system's state. But fundamental environment changes bring challenges for DT adaptation to new conditions, leading to a progressively decreasing correspondence of the DT to its physical counterpart. This paper introduces the DiTEC system, a Digital Twin for Evolutionary Changes in Water Distribution Networks (WDN). This framework combines novel techniques, including semantic rule learning, graph neural network-based state estimation, and adaptive model selection, to ensure that changes are adequately detected, processed and the DT is updated to the new state. The DiTEC system is tested on the Dutch Oosterbeek region WDN, with results showing the superiority of the approach compared to traditional methods.

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   BibTeX

   
   @inproceedings{victoria2024:ditec, title = "DiTEC: Digital Twin for Evolutionary Changes in Water Distribution Networks", abstract = "Conventional digital twins (DT) for critical infrastructures are widely used to model and simulate the system's state. But fundamental environment changes bring challenges for DT adaptation to new conditions, leading to a progressively decreasing correspondence of the DT to its physical counterpart. This paper introduces the DiTEC system, a Digital Twin for Evolutionary Changes in Water Distribution Networks (WDN). This framework combines novel techniques, including semantic rule learning, graph neural network-based state estimation, and adaptive model selection, to ensure that changes are adequately detected, processed and the DT is updated to the new state. The DiTEC system is tested on the Dutch Oosterbeek region WDN, with results showing the superiority of the approach compared to traditional methods.", author = "V. Degeler and M. Hadadian and E. Karabulut and A. Lazovik and H. Loo and A. Tello and H. Truong", year = "2024", month = oct, language = "English", doi = "10.1007/978-3-031-75390-9_5", url = "https://link.springer.com/chapter/10.1007/978-3-031-75390-9_5", publisher = "Springer Nature Switzerland", booktitle = "Leveraging Applications of Formal Methods, Verification and Validation. Application Areas", }

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   urldoi
6. Large-Scale Multipurpose Benchmark Datasets for Assessing Data-Driven Deep Learning Approaches for Water Distribution Networks (A. Tello, H. Truong, A. Lazovik and V. Degeler), In 3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI), 2024.

   Abstract

   Currently, the number of common benchmark datasets that researchers can use straight away for assessing data-driven deep learning approaches is very limited. Most studies provide data as configuration files. It is still up to each practitioner to follow a particular data generation method and run computationally intensive simulations to obtain usable data for model training and evaluation. In this work, we provide a collection of datasets that includes several small- and medium-sized publicly available Water Distribution Networks (WDNs), including Anytown, Modena, Balerma, C-Town, D-Town, L-Town, Ky1, Ky6, Ky8, and Ky10. In total, 1,394,400 h of WDN data operating under normal conditions are made available to the community.

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   BibTeX

   
   @inproceedings{tello2024:wdsa, title = "Large-Scale Multipurpose Benchmark Datasets for Assessing Data-Driven Deep Learning Approaches for Water Distribution Networks", abstract = "Currently, the number of common benchmark datasets that researchers can use straight away for assessing data-driven deep learning approaches is very limited. Most studies provide data as configuration files. It is still up to each practitioner to follow a particular data generation method and run computationally intensive simulations to obtain usable data for model training and evaluation. In this work, we provide a collection of datasets that includes several small- and medium-sized publicly available Water Distribution Networks (WDNs), including Anytown, Modena, Balerma, C-Town, D-Town, L-Town, Ky1, Ky6, Ky8, and Ky10. In total, 1,394,400 h of WDN data operating under normal conditions are made available to the community.", author = "A. Tello and H. Truong and A. Lazovik and V. Degeler", year = "2024", month = sep, language = "English", doi = "10.3390/engproc2024069050", url = "https://www.mdpi.com/2673-4591/69/1/50", booktitle = "3rd International Joint Conference on Water Distribution Systems Analysis & Computing and Control for the Water Industry (WDSA/CCWI)", }

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   urldoi
7. Too Good To Be True: accuracy overestimation in (re) current practices for Human Activity Recognition (A. Tello, V. Degeler and A. Lazovik), In 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops), 2024.

   BibTeX

   
   @inproceedings{tello2024:percom, title={Too Good To Be True: accuracy overestimation in (re) current practices for Human Activity Recognition}, author={A. Tello and V. Degeler and A. Lazovik}, booktitle={2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)}, pages={511--517}, year={2024}, organization={IEEE} }

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8. Smartphone-based real-time indoor positioning using BLE beacons (R. Riesebos, V. Degeler and A. Tello), In 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE), 2022.

   BibTeX

   
   @inproceedings{riesebos2022:case, title={Smartphone-based real-time indoor positioning using BLE beacons}, author={R. Riesebos and V. Degeler and A. Tello}, booktitle={2022 IEEE 18th International Conference on Automation Science and Engineering (CASE)}, pages={1281--1288}, year={2022}, organization={IEEE} }

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9. Digital Twins: an enabler for digital transformation (A. Tello and V. Degeler), Chapter in The Digital Transformation handbook, 2021.

   BibTeX

   
   @incollection{Tello2021:digitaltwins, author = "A. Tello and V. Degeler", title = "Digital Twins: an enabler for digital transformation", booktitle = "The Digital Transformation handbook", year = 2021, URL = {https://www.rug.nl/gdbc/blog/digital-twins} }

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   url
10. Digital Twins: an enabler for digital transformation (A. Tello and V. Degeler), Chapter in The Digital Transformation handbook, 2021.

    BibTeX

    
    @incollection{tello2021:digitaltwins, author = "A. Tello and V. Degeler", title = "Digital Twins: an enabler for digital transformation", booktitle = "The Digital Transformation handbook", year = 2021, URL = {https://www.rug.nl/gdbc/blog/digital-twins} }

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    url
11. Temporal Analysis of 911 Emergency Calls Through Time Series Modeling (Robles, Pablo, Tello, Andrés, Solano-Quinde, Lizandro and Zúñiga-Prieto, Miguel), In The International Conference on Advances in Emerging Trends and Technologies, 2019.

    BibTeX

    
    @inproceedings{robles2019temporal, title={Temporal Analysis of 911 Emergency Calls Through Time Series Modeling}, author={Robles, Pablo and Tello, Andr{\'e}s and Solano-Quinde, Lizandro and Z{\'u}{\~n}iga-Prieto, Miguel}, booktitle={The International Conference on Advances in Emerging Trends and Technologies}, pages={136--145}, year={2019}, organization={Springer, Cham} }

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12. Prediction of Imports of Household Appliances in Ecuador Using LSTM Networks (Tello, Andrés, Izquierdo, Ismael, Pacheco, Gustavo and Vanegas, Paúl), In Conference on Information Technologies and Communication of Ecuador, 2019.

    BibTeX

    
    @inproceedings{tello2019prediction, title={Prediction of Imports of Household Appliances in Ecuador Using LSTM Networks}, author={Tello, Andr{\'e}s and Izquierdo, Ismael and Pacheco, Gustavo and Vanegas, Pa{\'u}l}, booktitle={Conference on Information Technologies and Communication of Ecuador}, pages={194--207}, year={2019}, organization={Springer, Cham} }

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13. Modeling 911 emergency events in Cuenca-Ecuador using geo-spatial data (Robles, Pablo, Tello, Andrés, Zúñiga-Prieto, Miguel and Solano-Quinde, Lizandro), In International Conference on Technology Trends, 2018.

    BibTeX

    
    @inproceedings{robles2018modeling, title={Modeling 911 emergency events in Cuenca-Ecuador using geo-spatial data}, author={Robles, Pablo and Tello, Andr{\'e}s and Z{\'u}{\~n}iga-Prieto, Miguel and Solano-Quinde, Lizandro}, booktitle={International Conference on Technology Trends}, pages={564--577}, year={2018}, organization={Springer, Cham} }

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14. LOD-GF: an integral linked open data generation framework (Saquicela, Víctor, Segarra, José, Ortiz, José, Tello, Andrés, Espinoza, Mauricio, Lupercio, Lucía and Villazón-Terrazas, Boris), In Conference on Information Technologies and Communication of Ecuador, 2018.

    BibTeX

    
    @inproceedings{saquicela2018lod, title={LOD-GF: an integral linked open data generation framework}, author={Saquicela, V{\'\i}ctor and Segarra, Jos{\'e} and Ortiz, Jos{\'e} and Tello, Andr{\'e}s and Espinoza, Mauricio and Lupercio, Luc{\'\i}a and Villaz{\'o}n-Terrazas, Boris}, booktitle={Conference on Information Technologies and Communication of Ecuador}, pages={283--300}, year={2018}, organization={Springer, Cham} }

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15. Semantic web and augmented reality for searching people, events and points of interest within of a university campus (Contreras, Pablo, Chimbo, David, Tello, Andrés and Espinoza, Mauricio), In 2017 XLIII Latin American Computer Conference (CLEI), 2017.

    BibTeX

    
    @inproceedings{contreras2017semantic, title={Semantic web and augmented reality for searching people, events and points of interest within of a university campus}, author={Contreras, Pablo and Chimbo, David and Tello, Andr{\'e}s and Espinoza, Mauricio}, booktitle={2017 XLIII Latin American Computer Conference (CLEI)}, pages={1--10}, year={2017}, organization={IEEE} }

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16. Tv program recommender using user authentication on middleware ginga (Crespo, Jorge, Tello, Andres, Saquicela, Victor, Palacio-Baus, Kenneth and Espinoza, Mauricio), In 2017 IEEE Second Ecuador Technical Chapters Meeting (ETCM), 2017.

    BibTeX

    
    @inproceedings{crespo2017tv, title={Tv program recommender using user authentication on middleware ginga}, author={Crespo, Jorge and Tello, Andres and Saquicela, Victor and Palacio-Baus, Kenneth and Espinoza, Mauricio}, booktitle={2017 IEEE Second Ecuador Technical Chapters Meeting (ETCM)}, pages={1--6}, year={2017}, organization={IEEE} }

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17. Methodological guidelines for publishing library data as linked data (Hidalgo-Delgado, Yusniel, Estrada-Nelson, Reina, Xu, Bin, Villazon-Terrazas, Boris, Leiva-Mederos, Amed and Tello, Andrés), In 2017 International Conference on Information Systems and Computer Science (INCISCOS), 2017.

    BibTeX

    
    @inproceedings{hidalgo2017methodological, title={Methodological guidelines for publishing library data as linked data}, author={Hidalgo-Delgado, Yusniel and Estrada-Nelson, Reina and Xu, Bin and Villazon-Terrazas, Boris and Leiva-Mederos, Amed and Tello, Andr{\'e}s}, booktitle={2017 International Conference on Information Systems and Computer Science (INCISCOS)}, pages={241--246}, year={2017}, organization={IEEE} }

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18. Challenges and trends about smart big geospatial data: A position paper (Saquicela, Víctor, Vilches-Blázquez, Luis M and Tello, Andrés), In 2017 IEEE International Conference on Big Data (Big Data), 2017.

    BibTeX

    
    @inproceedings{saquicela2017challenges, title={Challenges and trends about smart big geospatial data: A position paper}, author={Saquicela, V{\'\i}ctor and Vilches-Bl{\'a}zquez, Luis M and Tello, Andr{\'e}s}, booktitle={2017 IEEE International Conference on Big Data (Big Data)}, pages={3471--3475}, year={2017}, organization={IEEE} }

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19. Automatic RDF-ization of big data semi-structured datasets (Gualán, Ronald, Freire, Renán, Tello, Andrés, Espinoza, Mauricio and Saquicela, Víctor), In Maskana, volume 7, 2016.

    BibTeX

    
    @article{gualan2016automatic, title={Automatic RDF-ization of big data semi-structured datasets}, author={Gual{\'a}n, Ronald and Freire, Ren{\'a}n and Tello, Andr{\'e}s and Espinoza, Mauricio and Saquicela, V{\'\i}ctor}, journal={Maskana}, volume={7}, pages={117--127}, year={2016} }

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20. Detecting similar areas of knowledge using semantic and data mining technologies (Sumba, Xavier, Sumba, Freddy, Tello, Andres, Baculima, Fernando, Espinoza, Mauricio and Saquicela, Victor), In Electronic Notes in Theoretical Computer Science, Elsevier, volume 329, 2016.

    BibTeX

    
    @article{sumba2016detecting, title={Detecting similar areas of knowledge using semantic and data mining technologies}, author={Sumba, Xavier and Sumba, Freddy and Tello, Andres and Baculima, Fernando and Espinoza, Mauricio and Saquicela, Victor}, journal={Electronic Notes in Theoretical Computer Science}, volume={329}, pages={149--167}, year={2016}, publisher={Elsevier} }

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21. Integration and massive storage of hydro-meteorological data combining big data & semantic web technologies (Tello, Andrés, Freire, Renán, Espinoza, Mauricio and Saquicela, Víctor), In Maskana, volume 6, 2015.

    BibTeX

    
    @article{tello2015integration, title={Integration and massive storage of hydro-meteorological data combining big data \& semantic web technologies}, author={Tello, Andr{\'e}s and Freire, Ren{\'a}n and Espinoza, Mauricio and Saquicela, V{\'\i}ctor}, journal={Maskana}, volume={6}, pages={165--172}, year={2015} }

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22. An automatic method for the enrichment of dicom metadata using biomedical ontologies (Pérez, Wilson, Tello, Andrés, Saquicela, Víctor, Vidal, Maria-Esther and La Cruz, Alexandra), In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015.

    BibTeX

    
    @inproceedings{perez2015automatic, title={An automatic method for the enrichment of dicom metadata using biomedical ontologies}, author={P{\'e}rez, Wilson and Tello, Andr{\'e}s and Saquicela, V{\'\i}ctor and Vidal, Maria-Esther and La Cruz, Alexandra}, booktitle={2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)}, pages={2551--2554}, year={2015}, organization={IEEE} }

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23. Rdf-ization of dicom medical images towards linked health data cloud (Tello, Andrés, La Cruz, Alexandra, Saquicela, Víctor, Espinoza, Mauricio and Vidal, Maria-Esther), In VI Latin American Congress on Biomedical Engineering CLAIB 2014, Paraná, Argentina 29, 30 & 31 October 2014, 2015.

    BibTeX

    
    @inproceedings{tello2015rdf, title={Rdf-ization of dicom medical images towards linked health data cloud}, author={Tello, Andr{\'e}s and La Cruz, Alexandra and Saquicela, V{\'\i}ctor and Espinoza, Mauricio and Vidal, Maria-Esther}, booktitle={VI Latin American Congress on Biomedical Engineering CLAIB 2014, Paran{\'a}, Argentina 29, 30 \& 31 October 2014}, pages={757--760}, year={2015}, organization={Springer, Cham} }

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24. WebMedSA: a web-based framework for segmenting and annotating medical images using biomedical ontologies (Vega, Francisco, Pérez, Wilson, Tello, Andrés, Saquicela, Victor, Espinoza, Mauricio, Solano-Quinde, Lizandro, Vidal, Maria-Esther and La Cruz, Alexandra), In 11th International Symposium on Medical Information Processing and Analysis, volume 9681, 2015.

    BibTeX

    
    @inproceedings{vega2015webmedsa, title={WebMedSA: a web-based framework for segmenting and annotating medical images using biomedical ontologies}, author={Vega, Francisco and P{\'e}rez, Wilson and Tello, Andr{\'e}s and Saquicela, Victor and Espinoza, Mauricio and Solano-Quinde, Lizandro and Vidal, Maria-Esther and La Cruz, Alexandra}, booktitle={11th International Symposium on Medical Information Processing and Analysis}, volume={9681}, pages={968110}, year={2015}, organization={International Society for Optics and Photonics} }

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