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A new effective robust nonlinear controller based on PSO for interleaved DC–DC boost converters for fuel cell voltage regulation
A new effective robust nonlinear controller based on PSO for interleaved DC–DC boost converters for fuel cell voltage regulation
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A new effective robust nonlinear controller based on PSO for interleaved DC–DC boost converters for fuel cell voltage regulation

Abdelmalek, Samir ; Dali, Ali ; Bettayeb, Maamar ; Bakdi, Azzeddine

Soft computing (Berlin, Germany), 2020-11, Vol.24 (22), p.17051-17064 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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2
A framework for determining lowest navigable water levels with nonstationary characteristics
A framework for determining lowest navigable water levels with nonstationary characteristics
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A framework for determining lowest navigable water levels with nonstationary characteristics

Wang, Lu ; Xie, Ping ; Xu, Chong-Yu ; Sang, Yan-Fang ; Chen, Jie ; Yu, Tao

Stochastic environmental research and risk assessment, 2022-02, Vol.36 (2), p.583-608 [Periódico revisado por pares]

Berlin/Heidelberg: Springer Berlin Heidelberg

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3
Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires
Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires
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Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires

Miho, Enkelejda ; Yermanos, Alexander ; Weber, Cédric R ; Berger, Christoph T ; Reddy, Sai T ; Greiff, Victor

Frontiers in immunology, 2018-02, Vol.9, p.224-224 [Periódico revisado por pares]

Switzerland: Frontiers Research Foundation

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4
A review on deep reinforcement learning for fluid mechanics
A review on deep reinforcement learning for fluid mechanics
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A review on deep reinforcement learning for fluid mechanics

Garnier, Paul ; Viquerat, Jonathan ; Rabault, Jean ; Larcher, Aurélien ; Kuhnle, Alexander ; Hachem, Elie

Computers & fluids, 2021-07, Vol.225, p.104973, Article 104973 [Periódico revisado por pares]

Amsterdam: Elsevier Ltd

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5
Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery
Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery
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Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery

Wilman, Wiktoria ; Wróbel, Sonia ; Bielska, Weronika ; Deszynski, Piotr ; Dudzic, Paweł ; Jaszczyszyn, Igor ; Kaniewski, Jędrzej ; Młokosiewicz, Jakub ; Rouyan, Anahita ; Satława, Tadeusz ; Kumar, Sandeep ; Greiff, Victor ; Krawczyk, Konrad

Briefings in bioinformatics, 2022-07, Vol.23 (4) [Periódico revisado por pares]

Oxford: Oxford University Press

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6
Does intrinsic motivation mediate perceived artificial intelligence (AI) learning and computational thinking of students during the COVID-19 pandemic?
Does intrinsic motivation mediate perceived artificial intelligence (AI) learning and computational thinking of students during the COVID-19 pandemic?
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Does intrinsic motivation mediate perceived artificial intelligence (AI) learning and computational thinking of students during the COVID-19 pandemic?

Martín-Núñez, José Luis ; Ar, Anil Yasin ; Fernández, Rodrigo Pérez ; Abbas, Asad ; Radovanović, Danica

Computers and education. Artificial intelligence, 2023, Vol.4, p.100128-100128, Article 100128 [Periódico revisado por pares]

Elsevier Ltd

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7
Machine learning analysis of gene expression data reveals novel diagnostic and prognostic biomarkers and identifies therapeutic targets for soft tissue sarcomas
Machine learning analysis of gene expression data reveals novel diagnostic and prognostic biomarkers and identifies therapeutic targets for soft tissue sarcomas
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Machine learning analysis of gene expression data reveals novel diagnostic and prognostic biomarkers and identifies therapeutic targets for soft tissue sarcomas

van IJzendoorn, David G P ; Szuhai, Karoly ; Briaire-de Bruijn, Inge H ; Kostine, Marie ; Kuijjer, Marieke L ; Bovée, Judith V M G Ioshikhes, Ilya

PLoS computational biology, 2019-02, Vol.15 (2), p.e1006826-e1006826 [Periódico revisado por pares]

United States: Public Library of Science

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8
miRAW: A deep learning-based approach to predict microRNA targets by analyzing whole microRNA transcripts
miRAW: A deep learning-based approach to predict microRNA targets by analyzing whole microRNA transcripts
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miRAW: A deep learning-based approach to predict microRNA targets by analyzing whole microRNA transcripts

Pla, Albert ; Zhong, Xiangfu ; Rayner, Simon Ioshikhes, Ilya

PLoS computational biology, 2018-07, Vol.14 (7), p.e1006185-e1006185 [Periódico revisado por pares]

United States: Public Library of Science

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9
QUINT: Workflow for Quantification and Spatial Analysis of Features in Histological Images From Rodent Brain
QUINT: Workflow for Quantification and Spatial Analysis of Features in Histological Images From Rodent Brain
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QUINT: Workflow for Quantification and Spatial Analysis of Features in Histological Images From Rodent Brain

Yates, Sharon C ; Groeneboom, Nicolaas E ; Coello, Christopher ; Lichtenthaler, Stefan F ; Kuhn, Peer-Hendrik ; Demuth, Hans-Ulrich ; Hartlage-Rübsamen, Maike ; Roßner, Steffen ; Leergaard, Trygve ; Kreshuk, Anna ; Puchades, Maja A ; Bjaalie, Jan G

Frontiers in neuroinformatics, 2019-12, Vol.13, p.75-75 [Periódico revisado por pares]

Switzerland: Frontiers Research Foundation

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10
A subsampling approach for Bayesian model selection
A subsampling approach for Bayesian model selection
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A subsampling approach for Bayesian model selection

Lachmann, Jon ; Storvik, Geir ; Frommlet, Florian ; Hubin, Aliaksandr

International journal of approximate reasoning, 2022-12, Vol.151, p.33-63 [Periódico revisado por pares]

Elsevier Inc

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