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A modeled pendulum in <em>Algodoo</em> with dynamic <span class="search-highlight">vector</span> arrows a...
Published: March 2023
FIG. 21.6 A modeled pendulum in Algodoo with dynamic vector arrows as they change throughout the pendulum swing—velocity in black, external forces on the bob in white, and the sum of all external forces in green (left). A constructed “car” in Algodoo with motors on the front and rear wheels ascends a slope (right). Dynamic vector arrows are displayed for the orange box, while the graph above shows the time dependence of the box's gravitational potential energy. More about this image found in A modeled pendulum in Algodoo with dynamic vector arrows a...
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Screenshots of the MAGNA AR visualization tool, superimposing the magnetic ...
Published: March 2023
FIG. 21.3 Screenshots of the MAGNA AR visualization tool, superimposing the magnetic field vectors around a bar magnet (left) and around a current-carrying loop (right). Retrieved from https://www.magna-ar.net More about this image found in Screenshots of the MAGNA AR visualization tool, superimposing the magnetic ...
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(a) The schematic of the pseudocubic unit cell of BFO indicating the polari...
Published: March 2023
FIG. 7.4 (a) The schematic of the pseudocubic unit cell of BFO indicating the polarization vector pointing toward [111] direction and the schematic of the PFM tip approaching from the top, (b) out-of-plane phase contrast, and (c) in-plane phase contrast obtained from a PFM for a BFO/STO superlatti... More about this image found in (a) The schematic of the pseudocubic unit cell of BFO indicating the polari...
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(a) The schematic of the pseudocubic unit cell of BFO indicating the polari...
Published: March 2023
FIG. 7.5 (a) The schematic of the pseudocubic unit cell of BFO indicating the polarization vector pointing toward [001] direction and the schematic of the PFM tip approaching from the top, (b) out-of-plane phase contrast, and (c) in-plane phase contrast obtained from a PFM for a BFO/STO superlatti... More about this image found in (a) The schematic of the pseudocubic unit cell of BFO indicating the polari...
Book Chapter
Series: AIPP Books, Professional
Published: March 2023
10.1063/9780735425477_005
EISBN: 978-0-7354-2547-7
ISBN: 978-0-7354-2544-6
..., and Electrodynamics Diagnostic Testing of Conceptual Understanding Integration and Vector Calculus in Electrodynamics Electromagnetic Induction and Faraday's Law Gauss' Law and Ampère's Law Conclusion We have reviewed the physics education literature concerning students' understanding of electrostatics...
Book Chapter
Series: AIPP Books, Methods
Published: March 2023
10.1063/9780735425743_009
EISBN: 978-0-7354-2574-3
ISBN: 978-0-7354-2572-9
.... Preliminaries The class of parameterized models considered in this chapter and standard prediction error methods are described. Notation Time-dependent vectors are denoted by x k ∈ R n where k ∈ Z . An estimated variable is denoted with ⋅ ^ , i.e., the estimated variable...
Book Chapter
Series: AIPP Books, Methods
Published: March 2023
10.1063/9780735425743_007
EISBN: 978-0-7354-2574-3
ISBN: 978-0-7354-2572-9
... on the relevant topics. Preliminaries System description In this chapter, we consider a general class of nonlinear continuous-time systems of the following form: (7.1) x ˙ ( t ) = f ( x ( t ) , u ( t ) ) where x ( t ) ∈ X ⊆ R n denotes the vector of the state variables...
Book Chapter
Series: AIPP Books, Principles
Published: March 2023
10.1063/9780735425590_001
EISBN: 978-0-7354-2559-0
ISBN: 978-0-7354-2556-9
... to describe physical state or properties of crystalline solids. Tensors are often described as generalizations of scalars, vectors, and matrices. A tensor of rank r contains 3r components in a three-dimensional Euclidean space. The components are represented using an indicial...
Book Chapter
Series: AIPP Books, Professional
Published: March 2023
10.1063/9780735425514_018
EISBN: 978-0-7354-2551-4
ISBN: 978-0-7354-2548-4
... of mathematics and physics in complex situations. However, there are some first assessments on handling and understanding graphs (see Chapter 20), on understanding calculus, the vector concept, or on the nature of negativity. But up to now there is no comprehensive test for assessment of how students handle...
Book Chapter
Series: AIPP Books, Principles
Published: March 2023
10.1063/9780735425590_006
EISBN: 978-0-7354-2559-0
ISBN: 978-0-7354-2556-9
... Ginzburg–Landau–Devonshire (GLD) theory to define the total free energy of a ferroelectric material. GLD theory expresses the total free energy as the function of a vector-valued order parameter field, termed as spontaneous polarization field P ( r ). Note that all components of P go to zero...
Book Chapter
Series: AIPP Books, Professional
Published: March 2023
10.1063/9780735425514_026
EISBN: 978-0-7354-2551-4
ISBN: 978-0-7354-2548-4
... A and B. Self-force does not exist. K2. The force exerted by body A has exactly the same magnitude as the force exerted by body B, and they are simultaneous (Newton's 3rd Law). Both forces have the same line of action and yet have opposite directions. Vector nature of the force. Learning objectives...
Book Chapter
Series: AIPP Books, Professional
Published: March 2023
EISBN: 978-0-7354-2547-7
ISBN: 978-0-7354-2544-6
... is not peculiar to quantum observables Difference between state vector and vector property Contradiction of experimental results and hypothesis that a photon possesses the properties that determine a measurement result Transmission probability Observables and operators QMCA (N = 39 MC + 3 ME...
Book Chapter
Series: AIPP Books, Principles
Published: March 2023
10.1063/9780735425613_006
EISBN: 978-0-7354-2561-3
ISBN: 978-0-7354-2560-6
.... Flatten layer Aims to convert the data obtained from the last pooling layer into a 1-D array (i.e., a single long feature vector). Then, this vector is fed into a fully connected layer (i.e., NN). A regularization technique (Dropout) can be used to randomly drop a number of neurons in the NN during...
Book Chapter
Series: AIPP Books, Methods
Published: March 2023
10.1063/9780735425743_010
EISBN: 978-0-7354-2574-3
ISBN: 978-0-7354-2572-9
... using artificial neural networks, least squares regression, support vector regression, and Gaussian process regression. Also, modal decomposition-based techniques such as proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) are commonly used for reduced-order modeling and control...
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
... metric is common. The Euclidean metric treats each data record as a vector in a k-dimensional space. For conceptual inventories, this would be a vector of zeros and ones representing whether each item was answered correctly. The distance between two response vectors is calculated by extending...
Book Chapter
Series: AIPP Books, Professional
Published: March 2023
10.1063/9780735425477_008
EISBN: 978-0-7354-2547-7
ISBN: 978-0-7354-2544-6
... state vector and vector property Contradiction of experimental results and hypothesis that a photon possesses the properties that determine a measurement result Transmission probability Observables and operators QMCA (N = 39 MC + 3 ME) ( Sadaghiani and Pollock, 2015 ) Level: University...
Book Chapter
Series: AIPP Books, Professional
Published: March 2023
10.1063/9780735425514_021
EISBN: 978-0-7354-2551-4
ISBN: 978-0-7354-2548-4
... visualization tool, superimposing the magnetic field vectors around a bar magnet (left) and around a current-carrying loop (right). Retrieved from https://www.magna-ar.net FIG. 21.4 The PhET visualization tool Ohm's Law. FIG. 21.5 GeoGebra screenshot showing a model of an inclined plane...
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