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Fault Types01:18

Fault Types

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When analyzing a single line-to-ground fault from phase A to ground at a three-phase bus, it is important to consider the fault impedance. This impedance is zero for a bolted fault, equal to the arc impedance for an arcing fault, and represents the total fault impedance for a transmission-line insulator flashover. To derive sequence and phase currents, fault conditions are translated from the phase domain to the sequence domain.
For line-to-line faults occurring between phases B and C, the...
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Social Exchange Theory02:06

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We have discussed why we form relationships, what attracts us to others, and different types of love. But what determines whether we are satisfied with and stay in a relationship? One theory that provides an explanation is social exchange theory. According to social exchange theory, we act as naïve economists in keeping a tally of the ratio of costs and benefits of forming and maintaining a relationship with others (Rusbult & Van Lange, 2003).
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Intelligence01:27

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The term "intelligence" is complex because it refers to both behavior and individuals, and its interpretation varies across cultures. European Americans tend to link intelligence with reasoning and cognitive skills, while in Kenya, it is tied to responsible participation in family and social life. In Uganda, intelligence is seen as the ability to know the right actions and carry them out effectively, while the Iatmul people of Papua New Guinea associate it with the capacity to remember...
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Gas Exchange and Transport01:20

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Gas exchange, the intake of molecular oxygen (O2) from the environment and the outflow of carbon dioxide (CO2) into the environment, is necessary for cellular function. Gas exchange during respiration occurs largely via the movement of gas molecules along pressure gradients. Gas travels from areas of higher partial pressure to areas of lower partial pressure. In mammals, gas exchange occurs in the alveoli of the lungs, which are adjacent to capillaries and share a membrane with them.
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Quantifying Heat02:46

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Thermal Energy Microscopically, thermal energy is the kinetic energy associated with the random motion of atoms and molecules. Temperature is a quantitative measure of “hot” or “cold”, which depends on the amount of thermal energy. When the atoms and molecules in an object are moving or vibrating quickly, they have a higher average kinetic energy (KE) (or higher thermal energy), and the object is perceived as “hot”, or it is described as being at a higher temperature. When the...
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Measures of Intelligence01:29

Measures of Intelligence

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Psychologists measure intelligence by using standardized tests that produce a score known as the intelligence quotient or IQ. To understand IQ tests, it's important to recognize the key principles behind their construction: validity, reliability, and standardization.
Validity refers to how well a test measures what it claims to measure. An intelligence test should accurately assess intelligence rather than another characteristic, like anxiety. Criterion validity is one way to evaluate this;...
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Related Experiment Video

Updated: Jan 23, 2026

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
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A Fault Detection System for a Geothermal Heat Exchanger Sensor Based on Intelligent Techniques.

Héctor Aláiz-Moretón1, Manuel Castejón-Limas2, José-Luis Casteleiro-Roca3

  • 1Departamento de Ingeniería de Sistemas y Automática, Universidad de León, 24071 León, Spain. hector.moreton@unileon.es.

Sensors (Basel, Switzerland)
|June 21, 2019
PubMed
Summary
This summary is machine-generated.

This study presents a machine learning approach for identifying faulty sensors and restoring accurate data in engineering systems. The method effectively detects sensor malfunctions and ensures reliable measurements for critical applications.

Keywords:
adaptive boostingextremely randomized treesfault detectiongeothermal heat exchangergradient boostingk-nearest neighborsrandom decision forestsshallow neural networks

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Area of Science:

  • Engineering
  • Machine Learning
  • Sensor Technology

Background:

  • Real-world engineering systems often face sensor malfunctions, impacting operational reliability.
  • Accurate sensor data is critical for effective fault detection and recovery processes.

Purpose of the Study:

  • To develop a robust methodology for identifying malfunctioning sensors.
  • To establish a strategy for determining correct measurement values when sensor failures occur.

Main Methods:

  • Utilized six machine learning techniques: Random decision forests, gradient boosting, extremely randomized trees, adaptive boosting, k-nearest neighbors, and shallow neural networks.
  • Modeled sensor behavior using data from a geothermal heat exchanger in a bioclimatic house.

Main Results:

  • The proposed methodology demonstrated high effectiveness in identifying sensor faults.
  • The approach successfully established correct measurement values, validating its practical utility.

Conclusions:

  • The developed methodology offers a satisfactory solution for sensor fault detection and recovery in practical engineering systems.
  • Machine learning techniques provide a powerful tool for enhancing the reliability of sensor networks.