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7,619 results on '"PETIT, STEPHANIE"'

1. Enabling Collagen Quantification on HE-stained Slides Through Stain Deconvolution and Restained HE-HES

Author

Balezo, Guillaume, Bertram, Christof A., Tilmant, Cyprien, Petit, Stéphanie, Hadj, Saima Ben, and Fick, Rutger H. J.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

In histology, the presence of collagen in the extra-cellular matrix has both diagnostic and prognostic value for cancer malignancy, and can be highlighted by adding Saffron (S) to a routine Hematoxylin and Eosin (HE) staining. However, Saffron is not usually added because of the additional cost and because pathologists are accustomed to HE, with the exception of France-based laboratories. In this paper, we show that it is possible to quantify the collagen content from the HE image alone and to digitally create an HES image. To do so, we trained a UNet to predict the Saffron densities from HE images. We created a dataset of registered, restained HE-HES slides and we extracted the Saffron concentrations as ground truth using stain deconvolution on the HES images. Our model reached a Mean Absolute Error of 0.0668 $\pm$ 0.0002 (Saffron values between 0 and 1) on a 3-fold testing set. We hope our approach can aid in improving the clinical workflow while reducing reagent costs for laboratories., Comment: This work has been submitted to the IEEE for possible publication

Published
2022

2. Interpretable HER2 scoring by evaluating clinical Guidelines through a weakly supervised, constrained Deep Learning Approach

Author

Pham, Manh Dan, Tilmant, Cyprien, Petit, Stéphanie, Salmon, Isabelle, Hadj, Saima Ben, and Fick, Rutger H. J.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

The evaluation of the Human Epidermal growth factor Receptor-2 (HER2) expression is an important prognostic biomarker for breast cancer treatment selection. However, HER2 scoring has notoriously high interobserver variability due to stain variations between centers and the need to estimate visually the staining intensity in specific percentages of tumor area. In this paper, focusing on the interpretability of HER2 scoring by a pathologist, we propose a semi-automatic, two-stage deep learning approach that directly evaluates the clinical HER2 guidelines defined by the American Society of Clinical Oncology/ College of American Pathologists (ASCO/CAP). In the first stage, we segment the invasive tumor over the user-indicated Region of Interest (ROI). Then, in the second stage, we classify the tumor tissue into four HER2 classes. For the classification stage, we use weakly supervised, constrained optimization to find a model that classifies cancerous patches such that the tumor surface percentage meets the guidelines specification of each HER2 class. We end the second stage by freezing the model and refining its output logits in a supervised way to all slide labels in the training set. To ensure the quality of our dataset's labels, we conducted a multi-pathologist HER2 scoring consensus. For the assessment of doubtful cases where no consensus was found, our model can help by interpreting its HER2 class percentages output. We achieve a performance of 0.78 in F1-score on the test set while keeping our model interpretable for the pathologist, hopefully contributing to interpretable AI models in digital pathology., Comment: Submitted to Elsevier

Published
2022

3. Robust Mitosis Detection Using a Cascade Mask-RCNN Approach With Domain-Specific Residual Cycle-GAN Data Augmentation

Author

Roy, Gauthier, Dedieu, Jules, Bertrand, Capucine, Moshayedi, Alireza, Mammadov, Ali, Petit, Stéphanie, Hadj, Saima Ben, and Fick, Rutger H. J.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

For the MIDOG mitosis detection challenge, we created a cascade algorithm consisting of a Mask-RCNN detector, followed by a classification ensemble consisting of ResNet50 and DenseNet201 to refine detected mitotic candidates. The MIDOG training data consists of 200 frames originating from four scanners, three of which are annotated for mitotic instances with centroid annotations. Our main algorithmic choices are as follows: first, to enhance the generalizability of our detector and classification networks, we use a state-of-the-art residual Cycle-GAN to transform each scanner domain to every other scanner domain. During training, we then randomly load, for each image, one of the four domains. In this way, our networks can learn from the fourth non-annotated scanner domain even if we don't have annotations for it. Second, for training the detector network, rather than using centroid-based fixed-size bounding boxes, we create mitosis-specific bounding boxes. We do this by manually annotating a small selection of mitoses, training a Mask-RCNN on this small dataset, and applying it to the rest of the data to obtain full annotations. We trained the follow-up classification ensemble using only the challenge-provided positive and hard-negative examples. On the preliminary test set, the algorithm scores an F1 score of 0.7578, putting us as the second-place team on the leaderboard., Comment: Gauthier Roy and Jules Dedieu contributed equally to this work

Published
2021

7. Domain-Specific Cycle-GAN Augmentation Improves Domain Generalizability for Mitosis Detection

Author

Fick, Rutger H. J., Moshayedi, Alireza, Roy, Gauthier, Dedieu, Jules, Petit, Stéphanie, Hadj, Saima Ben, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Aubreville, Marc, editor, Zimmerer, David, editor, and Heinrich, Mattias, editor

Published
2022
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8. TARA Mediterranean Expedition: Assessing the Impact of Microplastics on Mediterranean Ecosystem

Author

Pedrotti, Maria Luiza, Mazzocchi, Maria Grazia, Lombard, Fabien, Galgani, François, Kerros, Marie Emmanuelle, Henry, Maryvonne, Elineau, Amanda, Petit, Stéphanie, Fernandez-de-Puelles, María Luz, Gasparini, Stéphane, Tirelli, Valentina, Jamet, Jean-Louis, Gorsky, Gabriel, Cocca, Mariacristina, editor, Di Pace, Emilia, editor, Errico, Maria Emanuela, editor, Gentile, Gennaro, editor, Montarsolo, Alessio, editor, and Mossotti, Raffaella, editor

Published
2018
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9. Grambank reveals the importance of genealogical constraints on linguistic diversity and highlights the impact of language loss

Author

Skirgård, Hedvig, primary, Haynie, Hannah J., additional, Blasi, Damián E., additional, Hammarström, Harald, additional, Collins, Jeremy, additional, Latarche, Jay J., additional, Lesage, Jakob, additional, Weber, Tobias, additional, Witzlack-Makarevich, Alena, additional, Passmore, Sam, additional, Chira, Angela, additional, Maurits, Luke, additional, Dinnage, Russell, additional, Dunn, Michael, additional, Reesink, Ger, additional, Singer, Ruth, additional, Bowern, Claire, additional, Epps, Patience, additional, Hill, Jane, additional, Vesakoski, Outi, additional, Robbeets, Martine, additional, Abbas, Noor Karolin, additional, Auer, Daniel, additional, Bakker, Nancy A., additional, Barbos, Giulia, additional, Borges, Robert D., additional, Danielsen, Swintha, additional, Dorenbusch, Luise, additional, Dorn, Ella, additional, Elliott, John, additional, Falcone, Giada, additional, Fischer, Jana, additional, Ghanggo Ate, Yustinus, additional, Gibson, Hannah, additional, Göbel, Hans-Philipp, additional, Goodall, Jemima A., additional, Gruner, Victoria, additional, Harvey, Andrew, additional, Hayes, Rebekah, additional, Heer, Leonard, additional, Herrera Miranda, Roberto E., additional, Hübler, Nataliia, additional, Huntington-Rainey, Biu, additional, Ivani, Jessica K., additional, Johns, Marilen, additional, Just, Erika, additional, Kashima, Eri, additional, Kipf, Carolina, additional, Klingenberg, Janina V., additional, König, Nikita, additional, Koti, Aikaterina, additional, Kowalik, Richard G. A., additional, Krasnoukhova, Olga, additional, Lindvall, Nora L. M., additional, Lorenzen, Mandy, additional, Lutzenberger, Hannah, additional, Martins, Tânia R. A., additional, Mata German, Celia, additional, van der Meer, Suzanne, additional, Montoya Samamé, Jaime, additional, Müller, Michael, additional, Muradoglu, Saliha, additional, Neely, Kelsey, additional, Nickel, Johanna, additional, Norvik, Miina, additional, Oluoch, Cheryl Akinyi, additional, Peacock, Jesse, additional, Pearey, India O. C., additional, Peck, Naomi, additional, Petit, Stephanie, additional, Pieper, Sören, additional, Poblete, Mariana, additional, Prestipino, Daniel, additional, Raabe, Linda, additional, Raja, Amna, additional, Reimringer, Janis, additional, Rey, Sydney C., additional, Rizaew, Julia, additional, Ruppert, Eloisa, additional, Salmon, Kim K., additional, Sammet, Jill, additional, Schembri, Rhiannon, additional, Schlabbach, Lars, additional, Schmidt, Frederick W. P., additional, Skilton, Amalia, additional, Smith, Wikaliler Daniel, additional, de Sousa, Hilário, additional, Sverredal, Kristin, additional, Valle, Daniel, additional, Vera, Javier, additional, Voß, Judith, additional, Witte, Tim, additional, Wu, Henry, additional, Yam, Stephanie, additional, Ye, Jingting, additional, Yong, Maisie, additional, Yuditha, Tessa, additional, Zariquiey, Roberto, additional, Forkel, Robert, additional, Evans, Nicholas, additional, Levinson, Stephen C., additional, Haspelmath, Martin, additional, Greenhill, Simon J., additional, Atkinson, Quentin D., additional, and Gray, Russell D., additional

Published
2023
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10. Grambank reveals the importance of genealogical constraints on linguistic diversity and highlights the impact of language loss. Science Advances

Author

Skirgård, Hedvig, Haynie, Hannah J., Blasi, Damián E., Hammarström, Harald, Collins, Jeremy, Latarche, Jay J., Lesage, Jakob, Weber, Tobias, Witzlack-Makarevich, Alena, Passmore, Sam, Chira, Angela, Maurits, Luke, Dinnage, Russell, Dunn, Michael, Reesink, Ger, Singer, Ruth, Bowern, Claire, Epps, Patience, Hill, Jane, Vesakoski, Outi, Robbeets, Martine, Abbas, Noor Karolin, Auer, Daniel, Bakker, Nancy A., Barbos, Giulia, Borges, Robert D., Danielsen, Swintha, Dorenbusch, Luise, Dorn, Ella, Elliott, John, Falcone, Giada, Fischer, Jana, Ate, Yustinus Ghanggo, Gibson, Hannah, Gï¿œbel, Hans-Philipp, Goodall, Jemima A., Gruner, Victoria, Harvey, Andrew, Hayes, Rebekah, Heer, Leonard, Miranda, Roberto E. Herrera, Hï¿œbler, Nataliia, Huntington-Rainey, Biu, Ivani, Jessica K., Johns, Marilen, Just, Erika, Kashima, Eri, Kipf, Carolina, Klingenberg, Janina V., Kï¿œnig, Nikita, Koti, Aikaterina, Kowalik, Richard G. A., Krasnoukhova, Olga, Lindvall, Nora L. M., Lorenzen, Mandy, Lutzenberger, Hannah, Martins, Tï¿œnia R. A., German, Celia Mata, Meer, Suzanne van der, Samamï¿œ, Jaime Montoya, Mï¿œller, Michael, Muradoglu, Saliha, Neely, Kelsey, Nickel1, Johanna, Norvik, Miina, Oluoch, Cheryl Akinyi, Peacock, Jesse, Pearey, India O. C., Peck, Naomi, Petit, Stephanie, Pieper, Sï¿œren, Poblete, Mariana, Prestipino, Daniel, Raabe, Linda, Raja, Amna, Reimringer, Janis, Rey, Sydney C., Rizaew, Julia, Ruppert, Eloisa, Salmon, Kim K., Sammet, Jill, Schembri, Rhiannon, Schlabbach, Lars, Schmidt, Frederick W. P., Skilton, Amalia, Smith, Wikaliler Daniel, Sousa, Hilï¿œrio de, Sverredal, Kristin, Valle, Daniel, Vera, Javier, Voï¿œ, Judith, Witte, Tim, Wu, Henry, Yam, Stephanie, Ye, Jingting, Yong, Maisie, Yuditha, Tessa, Zariquiey, Roberto, Forkel, Robert, Evans, Nicholas, Levinson, Stephen C., Haspelmath, Martin, Greenhill1, Simon J., Atkinson, Quentin D., Gray, Russell D., Skirgård, Hedvig, Haynie, Hannah J., Blasi, Damián E., Hammarström, Harald, Collins, Jeremy, Latarche, Jay J., Lesage, Jakob, Weber, Tobias, Witzlack-Makarevich, Alena, Passmore, Sam, Chira, Angela, Maurits, Luke, Dinnage, Russell, Dunn, Michael, Reesink, Ger, Singer, Ruth, Bowern, Claire, Epps, Patience, Hill, Jane, Vesakoski, Outi, Robbeets, Martine, Abbas, Noor Karolin, Auer, Daniel, Bakker, Nancy A., Barbos, Giulia, Borges, Robert D., Danielsen, Swintha, Dorenbusch, Luise, Dorn, Ella, Elliott, John, Falcone, Giada, Fischer, Jana, Ate, Yustinus Ghanggo, Gibson, Hannah, Gï¿œbel, Hans-Philipp, Goodall, Jemima A., Gruner, Victoria, Harvey, Andrew, Hayes, Rebekah, Heer, Leonard, Miranda, Roberto E. Herrera, Hï¿œbler, Nataliia, Huntington-Rainey, Biu, Ivani, Jessica K., Johns, Marilen, Just, Erika, Kashima, Eri, Kipf, Carolina, Klingenberg, Janina V., Kï¿œnig, Nikita, Koti, Aikaterina, Kowalik, Richard G. A., Krasnoukhova, Olga, Lindvall, Nora L. M., Lorenzen, Mandy, Lutzenberger, Hannah, Martins, Tï¿œnia R. A., German, Celia Mata, Meer, Suzanne van der, Samamï¿œ, Jaime Montoya, Mï¿œller, Michael, Muradoglu, Saliha, Neely, Kelsey, Nickel1, Johanna, Norvik, Miina, Oluoch, Cheryl Akinyi, Peacock, Jesse, Pearey, India O. C., Peck, Naomi, Petit, Stephanie, Pieper, Sï¿œren, Poblete, Mariana, Prestipino, Daniel, Raabe, Linda, Raja, Amna, Reimringer, Janis, Rey, Sydney C., Rizaew, Julia, Ruppert, Eloisa, Salmon, Kim K., Sammet, Jill, Schembri, Rhiannon, Schlabbach, Lars, Schmidt, Frederick W. P., Skilton, Amalia, Smith, Wikaliler Daniel, Sousa, Hilï¿œrio de, Sverredal, Kristin, Valle, Daniel, Vera, Javier, Voï¿œ, Judith, Witte, Tim, Wu, Henry, Yam, Stephanie, Ye, Jingting, Yong, Maisie, Yuditha, Tessa, Zariquiey, Roberto, Forkel, Robert, Evans, Nicholas, Levinson, Stephen C., Haspelmath, Martin, Greenhill1, Simon J., Atkinson, Quentin D., and Gray, Russell D.

Published
2023
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11. Grambank reveals the importance of genealogical constraints on linguistic diversity and highlights the impact of language loss

Author

Skirgård, Hedvig, primary, Haynie, Hannah J., additional, Blasi, Damián E., additional, Hammarström, Harald, additional, Collins, Jeremy, additional, Latarche, Jay J., additional, Lesage, Jakob, additional, Weber, Tobias, additional, Witzlack-Makarevich, Alena, additional, Passmore, Sam, additional, Chira, Angela M., additional, Maurits, Luke, additional, Dinnage, Russell, additional, Dunn, Michael, additional, Reesink, Ger, additional, Singer, Ruth, additional, Bowern, Claire, additional, Epps, Patience L, additional, Hill, Jane, additional, Vesakoski, Outi, additional, Robbeets, Martine, additional, Abbas, Noor Karolin, additional, Auer, Daniel, additional, Bakker, Nancy A., additional, Barbos, Giulia, additional, Borges, Robert D., additional, Danielsen, Swintha, additional, Dorenbusch, Luise, additional, Dorn, Ella, additional, Elliott, John, additional, Falcone, Giada, additional, Fischer, Jana, additional, Ate, Yustinus Ghanggo, additional, Gibson, Hannah, additional, Göbel, Hans-Philipp, additional, Goodall, Jemima A., additional, Gruner, Victoria, additional, Harvey, Andrew, additional, Hayes, Rebekah, additional, Heer, Leonard, additional, Miranda, Roberto E. Herrera, additional, Hübler, Nataliia, additional, Huntington-Rainey, Biu H., additional, Ivani, Jessica K., additional, Johns, Marilen, additional, Just, Erika, additional, Kashima, Eri, additional, Kipf, Carolina, additional, Klingenberg, Janina V., additional, König, Nikita, additional, Koti, Aikaterina, additional, Kowalik, Richard G. A., additional, Krasnoukhova, Olga, additional, Lindvall, Nora L. M., additional, Lorenzen, Mandy, additional, Lutzenberger, Hannah, additional, Martins, Tânia R.A., additional, German, Celia Mata, additional, van der Meer, Suzanne, additional, Samamé, Jaime Montoya, additional, Müller, Michael, additional, Muradoglu, Saliha, additional, Neely, Kelsey, additional, Nickel, Johanna, additional, Norvik, Miina, additional, Oluoch, Cheryl Akinyi, additional, Peacock, Jesse, additional, Pearey, India O.C., additional, peck, naomi, additional, Petit, Stephanie, additional, Pieper, Sören, additional, Poblete, Mariana, additional, Prestipino, Daniel, additional, Raabe, Linda, additional, Raja, Amna, additional, Reimringer, Janis, additional, Rey, Sydney C., additional, Rizaew, Julia, additional, Ruppert, Eloisa, additional, Salmon, Kim K., additional, Sammet, Jill, additional, Schembri, Rhiannon, additional, Schlabbach, Lars, additional, Schmidt, Frederick W.P., additional, Skilton, Amalia, additional, Smith, Wikaliler Daniel, additional, de Sousa, Hilário, additional, Sverredal, Kristin, additional, Valle, Daniel, additional, Vera, Javier, additional, Voß, Judith, additional, Witte, Tim, additional, Wu, Henry, additional, Yam, Stephanie, additional, 葉婧婷, Jingting Ye, additional, Yong, Maisie, additional, Yuditha, Tessa, additional, Zariquiey, Roberto, additional, Forkel, Robert, additional, Evans, Nicholas, additional, Levinson, Stephen C., additional, Haspelmath, Martin, additional, Greenhill, Simon J., additional, Atkinson, Quentin, additional, and Gray, Russell D., additional

Published
2022
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12. The new foundations of open source.

Author

Meeker, Heather and Petit, Stephanie

Subjects
Foundations (Endowments) -- Models -- Services, Open source software -- Analysis, Open source software
Abstract

In recent years, the news about open source software development has been full of new community players: OpenStack Foundation, CloudFoundry.org Foundation, the Document Foundation, and the Open Source Robotics Foundation. [...]

Published
2017

14. An integrative assessment of the plastic debris load in the Mediterranean Sea

Author

Pedrotti, Maria Luiza, primary, Lombard, Fabien, additional, Baudena, Alberto, additional, Galgani, François, additional, Elineau, Amanda, additional, Petit, Stephanie, additional, Henry, Maryvonne, additional, Troublé, Romain, additional, Reverdin, Gilles, additional, Ser-Giacomi, Enrico, additional, Kedzierski, Mikaël, additional, Boss, Emmanuel, additional, and Gorsky, Gabriel, additional

Published
2022
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16. An integrative assessment of the plastic debris load in the Mediterranean Sea

Author

Pedrotti, Maria Luiza, Lombard, Fabien, Baudena, Alberto, Galgani, Francois, Elineau, Amanda, Petit, Stephanie, Henry, Maryvonne, Troublé, Romain, Reverdin, Gilles, Ser-giacomi, Enrico, Kedzierski, Mikaël, Boss, Emmanuel, Gorsky, Gabriel, Pedrotti, Maria Luiza, Lombard, Fabien, Baudena, Alberto, Galgani, Francois, Elineau, Amanda, Petit, Stephanie, Henry, Maryvonne, Troublé, Romain, Reverdin, Gilles, Ser-giacomi, Enrico, Kedzierski, Mikaël, Boss, Emmanuel, and Gorsky, Gabriel

Abstract

The Mediterranean Sea is recognized as one of the most polluted areas by floating plastics. During the Tara Mediterranean expedition, an extensive sampling of plastic debris was conducted in seven ecoregions, from Gibraltar to Lebanon with the aim of providing reliable estimates of regional differences in floating plastic loads and plastic characteristics. The abundance, size, surface, circularity and mass of 75,030 pieces were analyzed and classified in a standardized multi-parameter database. Their average abundance was 2.60 × 105 items km−2 (2.25 × 103 to 8.50 × 106 km−2) resulting in an estimate of about 650 billion plastic particles floating on the surface of the Mediterranean. This corresponds to an average of 660 metric tons of plastic, at the lower end of literature estimates. High concentrations of plastic were observed in the northwestern coastal regions, north of the Tyrrhenian Sea, but also off the western and central Mediterranean basins. The Levantine basin south of Cyprus had the lowest concentrations. A Lagrangian Plastic Pollution Index (LPPI) predicting the concentration of plastic debris was validated using the spatial resolution of the data. The advanced state of plastic degradation detected in the analyses led to the conclusion that stranding/fragmentation/resuspension suggests it is a key process in the dynamics of floating plastic in Mediterranean surface waters. This is supported by the significant correlation between pollution sources and areas of high plastic concentration obtained by the LPPI.

Published
2022
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18. Highlight results of the Smart4RES project on weather modelling and forecasting dedicated to renewable energy applications

Author

Kariniotakis, Georges, Camal, Simon, Meer, Dennis van Der, Stratigakos, Akylas, Giebel, Gregor, Göçmen, Tuhfe, Pinson, Pierre, Bessa, Ricardo, Goncalves, Carla, Aleksovska, Ivana, Alonzo, Bastien, Cassas, Marie, Libois, Quentin, Raynaud, Laure, Deen, Gerrit, Houf, Daan, Verzijlbergh, Remco, Lange, Matthias, Witha, Björn, Lezaca, Jorge, Nouri, Bijan, Wilbert, Stefan, Marques, Maria Ines, Silva, Manuel, Boer, Wouter De, Eijgelaar, Marcel, Sauba, Ganesh, Karakitsios, John, Konstantinou, Theodoros, Lagos, Dimitrios, Sideratos, George, Anastopoulou, Theodora, Korka, Efrosini, Vitellas, Christos, Petit, Stephanie, Centre Procédés, Énergies Renouvelables, Systèmes Énergétiques (PERSEE), Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Danmarks Tekniske Universitet = Technical University of Denmark (DTU), Institute for Systems and Computer Engineering, Technology and Science [Porto] (INESC TEC), Météo-France Direction Interrégionale Sud-Est (DIRSE), Météo-France, WHIFFLE, energy (EMSYS - Energy & Meteo Systems), Deutsches Zentrum für Luft- und Raumfahrt (DLR), EDP New Energy World – Center for New Energy Technologies, EDP Distribuição, DNV GL, National Technical University of Athens [Athens] (NTUA), DEDDIE, Dowel Innovation, and European Project: 864337,Smart4RES

Subjects
[STAT.AP]Statistics [stat]/Applications [stat.AP], Data Science, [SPI.NRJ]Engineering Sciences [physics]/Electric power, Uncertainty, Predictive analytics, Renewable energy forecasting, Weather forecasting, [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], Digitalisation, Prescriptive anaytics, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Artificial Intelligence, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], European project, Renewable Energy, [MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC], SDG 7 - Affordable and Clean Energy, Energy Meteorology
Abstract

In this presentation we detail highlight results obtained from the research work within the European Horizon 2020 project Smart4RES (http://www.smart4res.eu). The project, which started in 2019 and runs until 2023, aims at a better modelling and forecasting of weather variables necessary to optimise the integration of weather-dependent renewable energy (RES) production (i.e. wind, solar, run-of-the-river hydro) into power systems and electricity markets. Smart4RES gathers experts from several disciplines, from meteorology and renewable generation to market- and grid-integration. It aims to contribute to the pathway towards energy systems with very high RES penetrations by 2030 and beyond, through thematic objectives including:Improvement of weather and RES forecasting, Streamlined extraction of optimal value through new forecasting products, data market places, and novel business models; New data-driven optimization and decision-aid tools for market and grid management applications; Validation of new models in living labs and assessment of forecasting value vs costly remedies to hedge uncertainties (i.e. storage). In this presentation we will focus on our results on models that permit to improve forecasting of weather variables with focus on extreme situations and also through innovative measuring settings (i.e. a network of sky cameras). Also results will be presented on the development of seamless approach able to couple outputs from different ensemble numerical weather prediction (NWP) models with different temporal resolutions. Advances on the contribution of ultra-high resolution NWPs based on Large Eddy Simulation will be presented with evaluation results on real case studies like the Rhodes island in Greece.When it comes to forecasting the power output of RES plants, mainly wind and solar, the focus is on improving predictability using multiple sources of data. The proposed modelling approaches aim to efficiently combine highly dimensionally input (various types of satellite images, numerical weather predictions, spatially distributed measurements etc.). A priority has been to propose models that permit to generate probabilistic forecasts for multiple time frames in a seamless way. Thus, the objective is not only to improve accuracy and uncertainty estimations, but also to simplify complex forecasting modelling chains for applications that use forecasts at different time frames (i.e. a virtual power plant - VPP- with or without storage that participates in multiple markets). Our results show that the proposed seamless models permit to reach these performance objectives. Results will be presented also on how these approaches can be extended to aggregations of RES plants which is relevant for forecasting VPP production.

Published
2022

23. William & Kate's U.S. Visit: Keeping Calm & Carrying On.

Author

PERRY, SIMON, TAUBER, MICHELLE, HENNI, JANINE, HILL, ERIN, and PETIT, STEPHANIE

Subjects
ROYAL houses, ACADEMY Awards, ROYAL weddings, PUBLIC demonstrations
Abstract

THE PRINCE AND PRINCESS HIGHLIGHT THE FUTURE OF OUR PLANET DURING A WHIRLWIND BOSTON TRIP - BUT NOT WITHOUT A FEW HEADWINDS WILL AND KATE TAKE BOSTON! CHRIS JACKSON/GETTY IMAGES(5); THE EARTHSHOT PRIZE(5) PHOTO (COLOR): Facing the SpotlightPrince William and Princess Kate hit the green carpet for the Earthshot Prize Awards in Boston on Dec. 2. [Extracted from the article]

Published
2022

27. Smart4RES: Towards next generation forecasting tools of renewable energy production

Author

Kariniotakis, George, primary, Camal, Simon, additional, Bessa, Ricardo, additional, Pinson, Pierre, additional, Giebel, Gregor, additional, Libois, Quentin, additional, Legrand, Raphaël, additional, Lange, Matthias, additional, Wilbert, Stefan, additional, Nouri, Bijan, additional, Neto, Alexandre, additional, Verzijlbergh, Remco, additional, Sauba, Ganesh, additional, Sideratos, George, additional, Korka, Efrosyni, additional, and Petit, Stephanie, additional

Published
2020
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