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Closed-loop state trajectories under P control with K = −3 with a depolarizing error parameter of 0.05 in the simulations labeled “0.05, Noise” a depolarizing error parameter of 0.005 in the simulations labeled “0.005, Noise,” and a depolarizing error parameter of 0.0005 in the simulations labeled “0.0005, Noise.” 1 shot is used in all cases.
Published: March 2023
FIG. 8.20 Closed-loop state trajectories under P control with K = −3 with a depolarizing error parameter of 0.05 in the simulations labeled “0.05, Noise” a depolarizing error parameter of 0.005 in the simulations labeled “0.005, Noise,” and a depolarizing error parameter of 0.0005 More about this image found in Closed-loop state trajectories under P control with K = −3...
Images
Closed-loop state trajectories under P control with K = −3 with a depolarizing error parameter of 0.05 in the simulations labeled “1 Shot, Noise” and “10 Shots, Noise.” These two simulations use 1 shot and 10 shots, respectively.
Published: March 2023
FIG. 8.19 Closed-loop state trajectories under P control with K = −3 with a depolarizing error parameter of 0.05 in the simulations labeled “1 Shot, Noise” and “10 Shots, Noise.” These two simulations use 1 shot and 10 shots, respectively. More about this image found in Closed-loop state trajectories under P control with K = −3...
Images
The training and validation errors of the DP model: the square root of loss for training (solid yellow) and validation (dashed yellow), root mean square errors (RMSEs) in force for training (solid blue) and validation (dashed blue), and RMSEs in energy for training (solid grey) and validation (dashed grey). The RMSEs in the energy are normalized by the number of atoms in the system.
Published: January 2023
FIG. 6.2 The training and validation errors of the DP model: the square root of loss for training (solid yellow) and validation (dashed yellow), root mean square errors (RMSEs) in force for training (solid blue) and validation (dashed blue), and RMSEs in energy for training (solid grey More about this image found in The training and validation errors of the DP model: the square root of loss...
Book Chapter
Book cover for Energy Systems and Processes:  Recent Advances in Design and Control
Series: AIPP Books, Methods
Published: March 2023
10.1063/9780735425743_009
EISBN: 978-0-7354-2574-3
ISBN: 978-0-7354-2572-9
... dynamic relationship between the temperature setpoint, the space indoor air temperature, and the sensible cooling or heating rate of the HVAC equipment. Two training approaches for the RC model parameter estimation are proposed on the basis of prediction error methods. These training approaches try...
Images
(a) Multi-frame averaged STEM image of silicon measured with [110] zone axis and histogram of inter-atomic distance along the (b) x and (c) y direction (Yankovich et al., 2014). The scale bar in (a) is 400 pm. The error bars in (b) and (c) are the square root of the frequency, the curves are the best-fit normal distributions, and σ represents the standard deviations.
Published: March 2023
FIG. 5.14 (a) Multi-frame averaged STEM image of silicon measured with [110] zone axis and histogram of inter-atomic distance along the (b) x and (c) y direction ( Yankovich et al., 2014 ). The scale bar in (a) is 400 pm. The error bars in (b) and (c) are the square More about this image found in (a) Multi-frame averaged STEM image of silicon measured with [110] zone axi...
Book Chapter

Series: AIPP Books, Professional
Published: March 2023
10.1063/9780735425514_024
EISBN: 978-0-7354-2551-4
ISBN: 978-0-7354-2548-4
... depart from the normal distribution, a 95% confidence interval may be more appropriate. The reporting of confidence intervals is growing in popularity in the broader education research community, as discussed in Sec. 24.8 . Some studies also report the standard error of the mean, SE. The standard error...
Book Chapter
Book cover for Energy Systems and Processes:  Recent Advances in Design and Control
Series: AIPP Books, Methods
Published: March 2023
10.1063/9780735425743_005
EISBN: 978-0-7354-2574-3
ISBN: 978-0-7354-2572-9
... deflection issues. Escobar-Toledo et al. (2014) concentrated on the change in position of the spot center along the horizontal and vertical axes. They did not, however, take into account the errors reflected in the spot shape variation. Sánchez-González et al. (2017) also investigated...
Book Chapter
Book cover for Energy Systems and Processes:  Recent Advances in Design and Control
Series: AIPP Books, Methods
Published: March 2023
10.1063/9780735425743_008
EISBN: 978-0-7354-2574-3
ISBN: 978-0-7354-2572-9
... the results of the mesh independence test for a fixed time step of 0.01 s computed at the line indicated in Fig. 8.7 . These results inform that a medium mesh size may be sufficient as the error between the small and medium mesh size was less than 1%. To check whether the medium mesh case with a time step...
Book Chapter

Series: AIPP Books, Professional
Published: March 2023
10.1063/9780735425514_014
EISBN: 978-0-7354-2551-4
ISBN: 978-0-7354-2548-4
... address the teacher's perspective, especially the teacher's needs and expectations regarding content, form and additional support. Be context-based CB The physics content should be embedded in some kind of (real or fictional) context. Be error-free EF The textbook should be free of errors...
Book Chapter
Book cover for Energy Systems and Processes:  Recent Advances in Design and Control

Series: AIPP Books, Methods
Published: March 2023
EISBN: 978-0-7354-2574-3
ISBN: 978-0-7354-2572-9
... and flatten the flux map in solar power tower plants ,” Sol. Energy   188 , 185 – 189 ( 2019 ). 10.1016/j.solener.2019.06.001 Coquand , M. , Caliot , C. , and Hénault , F. , “ Backward-gazing method for heliostats shape errors measurement and calibration ,” AIP Conf. Proc.   1850...
Book Chapter
Series: AIPP Books, Professional
Published: March 2023
10.1063/9780735425514_023
EISBN: 978-0-7354-2551-4
ISBN: 978-0-7354-2548-4
... estimates is due to a sampling error (i.e., from different participants across trials), whereas random effects meta-analyses assume two sources of error: sampling error and differences in the true effects across interventions. Because random effects meta-analyses quantify the differences in true...
Book Chapter
Book cover for Energy Systems and Processes:  Recent Advances in Design and Control

Series: AIPP Books, Methods
Published: March 2023
EISBN: 978-0-7354-2574-3
ISBN: 978-0-7354-2572-9
... is behind soaring energy prices and what happens next?” Report No. 636, International Energy Agency ( 2021 ); available at https://www.iea.org/reports/what-is-behind-soaring-energy-prices-and-what-happens-next . Astrom , K. J. , “ Maximum likelihood and prediction error methods...
Book Chapter
Book cover for Energy Systems and Processes:  Recent Advances in Design and Control
Series: AIPP Books, Methods
Published: March 2023
10.1063/9780735425743_012
EISBN: 978-0-7354-2574-3
ISBN: 978-0-7354-2572-9
... such as proppant concentration and flow rate of the injected fracturing fluids. To deal with large computational requirements due to the dynamic simulation of highly-coupled PDEs, a reduced-order model is developed by applying the multi-variable output error state-space (MOESP) algorithm to the data obtained from...
Book
Book cover for Energy Systems and Processes:  Recent Advances in Design and Control
Series: AIPP Books, Methods
Published: March 2023
10.1063/9780735425743
EISBN: 978-0-7354-2574-3
ISBN: 978-0-7354-2572-9
Book Chapter

Series: AIPP Books, Professional
Published: March 2023
10.1063/9780735425514_017
EISBN: 978-0-7354-2551-4
ISBN: 978-0-7354-2548-4
.... ( Ruggieri, 2020 ), and probably in many other western countries. Some online resources are not peer reviewed and may have physics errors; but others, such as the Khan Academy ( https://www.khanacademy.org/ ), offer valuable alternative learning paths for students. These online education resources encourage...
Book Chapter
Series: AIPP Books, Professional
Published: March 2023
10.1063/9780735425712_006
EISBN: 978-0-7354-2571-2
ISBN: 978-0-7354-2568-2
... are the scientists of tomorrow, it is vital that they work with data during their school education ( Harvey and Kumar, 2019 ). An important issue during the data analysis phase is dealing with uncertainties and errors. In majority of experiments based on virtual educational environments and serious games are error...
Book Chapter

Series: AIPP Books, Professional
Published: March 2023
EISBN: 978-0-7354-2571-2
ISBN: 978-0-7354-2568-2
... 10.1088/0143-0807/28/3/s08 ). Sokoloff , D. R.   et al. , RealTime Physics: Active Learning Laboratories, Module 1: Mechanics , 3rd ed. ( Wiley , 2011 ). Taylor , J. R. , An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements ( University Science...
Book Chapter
Series: AIPP Books, Professional
Published: March 2023
10.1063/9780735425514_016
EISBN: 978-0-7354-2551-4
ISBN: 978-0-7354-2548-4
... change; it was described in a theoretical sense through formulas, while its implication was neglected. Incorrect definitions There are also errors in the definition of concepts identified in textbooks. Researchers usually compared a number of physics textbooks extensively for a certain concept...
Book Chapter

Series: AIPP Books, Professional
Published: March 2023
10.1063/9780735425514_020
EISBN: 978-0-7354-2551-4
ISBN: 978-0-7354-2548-4
... to identify relationships in the graph data; and (3) reading beyond the data, or the ability to make inferences and predictions from the graph data, where the third level has been shown to be most difficult for students. Students have fewer difficulties when “reading the data,” but they make errors...
Book Chapter

Series: AIPP Books, Professional
Published: March 2023
EISBN: 978-0-7354-2547-7
ISBN: 978-0-7354-2544-6
.... Learn. Sci.   121 ( 9–10 ), 729 – 747 ( 2020 ). 10.1108/ILS-01-2020-0017 Cuzzolino , M. P. , Sci. Educ.   105 ( 4 ), 681 – 706 ( 2021 ). 10.1002/sce.21625 Damasio , A. R. , Descartes’ Error-Emotion, Reason and the Human Brain ( G. P. Putnam's Sons , New York , 1994...