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Related Concept Videos

Magnetic Fields01:27

Magnetic Fields

7.4K
A moving charge or a current creates a magnetic field in the surrounding space, in addition to its electric field. The magnetic field exerts a force on any other moving charge or current that is present in the field. Like an electric field, the magnetic field is also a vector field. At any position, the direction of the magnetic field is defined as the direction in which the north pole of a compass needle points.
A magnetic field is defined by the force that a charged particle experiences...
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Relative Strengths of Conjugate Acid-Base Pairs02:29

Relative Strengths of Conjugate Acid-Base Pairs

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Brønsted-Lowry acid-base chemistry is the transfer of protons; thus, logic suggests a relation between the relative strengths of conjugate acid-base pairs. The strength of an acid or base is quantified in its ionization constant, Ka or Kb, which represents the extent of the acid or base ionization reaction. For the conjugate acid-base pair HA / A−, the ionization equilibrium equations and ionization constant expressions are
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Magnetic Field of a Solenoid01:18

Magnetic Field of a Solenoid

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A solenoid is a conducting wire coated with an insulating material, wound tightly in the form of a helical coil. The magnetic field due to a solenoid is the vector sum of the magnetic fields due to its individual turns. Therefore, for an ideal solenoid, the magnetic field within the solenoid is directly proportional to the number of turns per unit length and the current. Conversely, the magnetic field outside the solenoid is zero.
Consider a solenoid with 100 turns wrapped around a cylinder of...
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Magnetic Field Lines01:19

Magnetic Field Lines

5.8K
The representation of magnetic fields by magnetic field lines is very useful in visualizing the strength and direction of the magnetic field. Each of the magnetic field lines forms a closed loop. The field lines emerge from the north pole (N), loop around to the south pole (S), and continue through the bar magnet back to the north pole.
Magnetic field lines follow several hard-and-fast rules:
5.8K
Energy In A Magnetic Field01:24

Energy In A Magnetic Field

2.8K
If a magnetic field is sustained, there must be a current in a closed circuit or loop, implying some energy has been spent in creating the field. If this energy is not dissipated via the circuit's resistance, it is stored in the field.
Take an ideal inductor with zero resistance. Although it's practically impossible, assume that the coil's resistance is so small that it is practically negligible. The loss of the field's energy to dissipate thermal energy (or heat) is thus...
2.8K
Acid and Bases: Ka, pKa, and Relative Strengths02:35

Acid and Bases: Ka, pKa, and Relative Strengths

33.6K
This lesson delves into a critical aspect of the relative strengths of acids and bases. The strength of an acid is evaluated by the acid dissociation into its conjugate base and a hydronium ion in water. The complete dissociation of a strong acid is confirmed with a very high concentration of hydronium ions. As a result, an incomplete dissociation process affirms a weak acid. Therefore, the equilibrium is in the forward direction for strong acids and backward for weak acids in these reactions.
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Related Experiment Video

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Simulation of Human-induced Vibrations Based on the Characterized In-field Pedestrian Behavior
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mPILOT-Magnetic Field Strength Based Pedestrian Indoor Localization.

Imran Ashraf1, Soojung Hur2, Yongwan Park3

  • 1Department of Information and Communication Engineering, Yeungnam University, Gyeongsan, Gyeongbuk 38541, Korea. ashrafimran@live.com.

Sensors (Basel, Switzerland)
|July 18, 2018
PubMed
Summary

This study presents an infrastructure-independent indoor localization system using smartphone sensors. It achieves 2-3m accuracy by analyzing magnetic field patterns, overcoming device differences and eliminating database updates.

Keywords:
deep learningfingerprintinggeomagnetismindoor localizationpattern matchingpedestrian dead reckoningsmartphone sensors

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Area of Science:

  • Indoor localization
  • Sensor fusion
  • Machine learning

Background:

  • Traditional indoor localization methods like WiFi fingerprinting require frequent database updates and struggle with device heterogeneity.
  • Geomagnetic fingerprinting offers infrastructure independence but faces challenges with magnetic field variations and device differences.

Purpose of the Study:

  • To develop an infrastructure-independent indoor localization system leveraging smartphone sensors.
  • To address device heterogeneity and database update issues in fingerprinting-based localization.
  • To achieve accurate indoor positioning without prior user location knowledge.

Main Methods:

  • Utilizes magnetometer, accelerometer, and gyroscope data from off-the-shelf smartphones.
  • Employs a fingerprinting database of magnetic flux intensity patterns.
  • Applies a deep learning-based artificial neural network for user state identification (walking/stationary) with 95% accuracy.
  • Implements a pattern matching approach to mitigate device heterogeneity.

Main Results:

  • Achieves 2-3m accuracy at the 50th percentile across different buildings.
  • Demonstrates comparable performance between Samsung Galaxy S8 and LG G6.
  • Attains 4m accuracy at the 75th percentile, irrespective of the device used.
  • System is entirely infrastructure independent, requiring no external technology.

Conclusions:

  • The proposed pattern matching approach effectively overcomes device heterogeneity in indoor localization.
  • The system provides accurate and infrastructure-independent indoor positioning using readily available smartphone sensors.
  • This method offers a robust solution for indoor localization challenges, reducing reliance on external infrastructure and frequent updates.