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Related Concept Videos

Kinematic Equations: Problem Solving01:15

Kinematic Equations: Problem Solving

When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
Anatomical Movements00:51

Anatomical Movements

Anatomical movements refer to the various actions or motions that can be performed by the body's joints and muscles. These movements are described using specific terms to provide a standardized way of discussing and understanding the range of motion at different joints.
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Flexion and extension motions are in the sagittal (anterior–posterior) plane of motion. These movements take place at the shoulder, hip, elbow, knee, wrist, metacarpophalangeal,...
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
Kinematic Equations for Rotation01:30

Kinematic Equations for Rotation

In mechanics, when one observes a rigid body in rotational motion with constant angular acceleration, it is possible to establish equations for its rotational kinematics. This process resembles how linear kinematics are dealt with in simpler motion studies.
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Kinematic Equations - II01:17

Kinematic Equations - II

The second kinematic equation expresses the final position of an object in terms of its initial position, the distance traveled with the initial constant velocity, and the distance traveled due to a change in velocity. Similar to the first kinematic equation, this equation is also only valid when the acceleration is constant throughout the motion of an object.
Suppose a car merges into freeway traffic on a 200 m long ramp. If its initial velocity is 10 m/s and it accelerates at 2 m/s2, then the...
Kinematic Equations - III01:18

Kinematic Equations - III

The first two kinematic equations have time as a variable, but the third kinematic equation is independent of time. This equation expresses final velocity as a function of the acceleration and distance over which it acts. The fourth kinematic equation does not have an acceleration term and provides the final position of the object at time t in terms of the initial and final velocities. This equation is useful when the value of the constant acceleration is unknown.
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Subject-specific Musculoskeletal Model for Studying Bone Strain During Dynamic Motion
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Published on: April 11, 2018

Kinematic mental simulations in abduction and deduction.

Sangeet Suresh Khemlani1, Robert Mackiewicz, Monica Bucciarelli

  • 1Navy Center for Applied Research in Artificial Intelligence, Naval Research Laboratory, Washington, DC 20375.

Proceedings of the National Academy of Sciences of the United States of America
|October 2, 2013
PubMed
Summary

This study reveals that mental simulations enable informal algorithm creation and deduction. Individuals utilize kinematic mental models, favoring "while-loops" for complex problem-solving tasks.

Keywords:
cognitive processesinformal programmingproblem solvingreasoning

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Area of Science:

  • Cognitive Science
  • Computer Science
  • Psychology

Background:

  • Mental simulations are hypothesized to play a role in human reasoning and problem-solving.
  • Understanding how individuals develop and utilize algorithms is crucial for cognitive modeling.

Purpose of the Study:

  • To present and test a theory on how mental simulations underpin the abduction and deduction of informal algorithms.
  • To investigate the influence of kinematic mental models on algorithm formulation and execution.

Main Methods:

  • Developed a theory and computer implementation of mental simulation for algorithm abduction and deduction.
  • Conducted three experiments using a simplified railway track and siding environment, analogous to a universal Turing machine.
  • Analyzed participants' algorithm descriptions and their ability to deduce consequences without direct environmental access.

Main Results:

  • Participants successfully abducted and described algorithms, favoring 'while-loops' over 'for-loops' as predicted by simulation theory.
  • Problem difficulty was linked to the number of moves/cars for execution and Kolmogorov complexity for formulation/deduction.
  • Reliable individual differences in task performance were observed.

Conclusions:

  • The findings support the use of kinematic mental models in creating and testing informal algorithms.
  • Mental simulations are integral to how humans generate and reason with algorithms.
  • Cognitive abilities related to algorithmic thinking vary among individuals.