The Impact of a Construction Play on 5- to 6-Year-Old Children’s Reasoning About Stability
Frontiers in Psychology, 2020 TheoryYoung children have an understanding of basic science concepts such as stability, yet their theoretical assumptions are often not concerned with stability.
Anke Maria Weber +2 more
doaj +1 more source
Probability Based Stochastic Iterative Learning Control for Batch Processes With Actuator Faults
IEEE Access, 2019 This paper proposes a new stochastic composite iterative learning control for batch processes with actuator faults that happen with a certain kind of probability.
Limin Wang, Bingyun Li
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An Actor-Critic Framework for Online Control With Environment Stability Guarantee
IEEE Access, 2023 Online actor-critic reinforcement learning is concerned with training an agent on-the-fly via dynamic interaction with the environment. Due to the specifics of the application, it is not generally possible to perform long pre-training, as it is commonly ...
Pavel Osinenko +3 more
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BACKPROPAGATION TRAINING ALGORITHM WITH ADAPTIVE PARAMETERS TO SOLVE DIGITAL PROBLEMS [PDF]
ICTACT Journal on Soft Computing, 2011 An efficient technique namely Backpropagation training with adaptive parameters using Lyapunov Stability Theory for training single hidden layer feed forward network is proposed.
R. Saraswathi
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Dynamic ILC for Linear Repetitive Processes Based on Different Relative Degrees
Mathematics, 2022 The current research on iterative learning control focuses on the condition where the system relative degree is equal to 1, while the condition where the system relative degree is equal to 0 or greater than 1 is not considered.
Lei Wang +3 more
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Identifying an efficient, thermally robust inorganic phosphor host via machine learning
Nature Communications, 2018 Identifying phosphors with good thermal stability and quantum efficiency is a prerequisite to improve the performance of white LED light sources. Here, a combined machine learning and density functional theory method is introduced to identify next ...
Ya Zhuo +4 more
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Stable Rough Extreme Learning Machines for the Identification of Uncertain Continuous-Time Nonlinear Systems [PDF]
Control and Optimization in Applied Mathematics, 2019 Rough extreme learning machines (RELMs) are rough-neural networks with one hidden layer where the parameters between the inputs and hidden neurons are arbitrarily chosen and never updated.
Ghasem Ahmadi
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Mental models vs cell schemes [PDF]
Investigações em Ensino de Ciências, 2002 Student's mental representations of cell are examined from the perspectives of Johnson-Laird's mental models theory five years after instruction. The observed identity and stability of such representations are then interpreted under the framework of ...
Mª Luz Rodríguez Palmero +1 more
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Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source