... to Recent Advances in Multiscale Modeling and Simulation of Biomolecules is a key resource for students and researchers in biology, biophysics, biochemistry, and computational chemistry. Artificial intelligence (Interdisciplinary physics) Free energy calculations (Quantum chemistry) Machine learning...

...) Machine learning (Interdisciplinary physics) Preface Molecular simulations allow us to see the “invisible” biological world with super high time and spatial resolution. Molecular modeling and molecular dynamics (MD) simulation of biomolecules have increasingly become essential and irreplaceable tools...

...-efficient techniques like HVAC/building control. This up-to-date book: Includes the most recent developments in systems techniques including multi-scale modeling, model predictive control, and machine learning, as applied to a wide variety of energy systems Focuses on how systematic strategies can...

... choose to take capstone courses in more advanced computational physics methods (higher order integration methods; Monte Carlo simulation; Markov chains and the Metropolis algorithm), computational quantum mechanics, and data analysis with an emphasis on machine learning. From a computational literacy...

... of Physics and science and their teaching in formal education and in special-Inclusive education, with an emphasis on the creation, use and learning assessment of modern models and experimental (practice) environments (real, virtual, augmented and mixed reality), playful learning, machine learning...

... enough, and not interdisciplinary enough. These categories are not physics-specific but also represent problems in science education and generic education research. For example, the nature of science (NOS) is also an important topic in science TER, cf. Roseman et al. (1996) . Arguably...

.... For instance, price balance in a free market with P-V graph, and performance evaluation of machine learning using entropy. Even in order to enhance competencies, critical is to cope with the integrating society and interdisciplinary and creative thinking is more important than any other thing people should...

... ). 10.1119/1.2060715 Kautz , C. H. , Ph.D. dissertation ( Department of Physics, University of Washington , 1999 ). Kesidou , S. and Duit , R. , J. Res. Sci. Teach.   30 , 85 – 106 ( 1993 ). 10.1002/tea.3660300107 Kesidou , S.   et al. et al. , Learning Science...

... with multiple layers. It is a branch of machine learning which works on large amounts of data. Deep learning may be used for regression and classification tasks ( Kotu and Deshpande, 2018 ). In smart grids, deep learning can be used for false data injection attack ( Niu et al., 2019 ), demand response...

... , https://ojs.dpg-physik.de/index.php/phydid-b/article/view/1233 ( 2022 ). Woithe , J ., “ Designing, measuring and modelling the impact of the hands-on particle physics learning laboratory S’Cool LAB at CERN ,” Ph.D. thesis ( University of Kaiserslautern , 2020 ). Woithe , J...

... What difference does it make to think of physics as a human endeavor, rather than as we normally might, as a complex of conceptual insights and principles, predictive theories, experimental machines, and sophisticated technologies? The relevant contrast case is probably not with physics...

... for postgraduate students and researchers in energy-related fields and is an invaluable resource for utility managers, operators, engineers, and policymakers. Energy production transmission and distribution (Energy) Electrical grid (Energy) Electrical engineering (Interdisciplinary physics) Power electronics...

... improved optimization strategy combining analytical solution and machine learning approaches using a generalized artificial neural network, which can accurately predict the sizing curves of the PV system with a prediction error of 0.6%. Youssef et al. (2017) reviewed the recent advances in AI...

... systems will find this an invaluable reference. Artificial intelligence (Interdisciplinary physics) Applied computer science (Interdisciplinary physics) Flow control (Rheology and fluid dynamics) Preface Centrifugal pumps are rotating machines that are widely used in process operations and other...