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Related Concept Videos

Thermosensation01:43

Thermosensation

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Peripheral thermosensation is the perception of external temperature. A change in temperature (on the surface of the skin and other tissues) is detected by a family of temperature-sensitive ion channels called Transient Receptor Potential, or TRP, receptors. These receptors are located on free nerve endings. Those detecting cold temperatures are closer to the surface of the skin than the nerve endings detecting warmth. These thermoTRP channels, while temperature selective, have relatively...
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Assessing Body Temperature - Temporal Artery01:19

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Here is a stepwise guide to assessing the body temperature at the temporal artery using a temporal artery thermometer
Step 1: Perform hand hygiene and don a fresh pair of gloves to prevent cross-infection and ensure patient safety.
Step 2: Explain the procedure to the patient to establish trust. Clear communication establishes trust with the patient, ensures they understand what to expect, promotes cooperation, and enhances comfort during the procedure.  
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Assessing Body Temperature - Axilla01:14

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Procedural Guide for Assessing Axillary Body Temperature using a Digital Thermometer:
Step 1: Perform hand hygiene and put on clean gloves to maintain infection control and prevent cross-contamination.
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Temperature Measurement Sites01:14

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A thermometer measures body temperature. The common sites for measuring body temperature are the oral cavity, axillary region, temporal artery, and skin surface, such as the forehead, abdomen, and axilla. True core body temperature is assessed in the rectum, tympanic membrane, pulmonary artery, esophagus, and urinary bladder.
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Assessing Body Temperature - Tympanic membrane01:14

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Assessing tympanic membrane temperature involves using a tympanic membrane thermometer (TMT). Here is a step-by-step guide:
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Step 3: Slide the probe cover in place to prevent cross-contamination.
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Temperature and Thermal Equilibrium01:11

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Heat and temperature are essential concepts for everyone every day. The study of heat and temperature is part of an area of physics known as thermodynamics. It is not always easy to distinguish heat and temperature.
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Thermal sensation prediction by soft computing methodology.

Srđan Jović1, Nebojša Arsić1, Jovana Vilimonović2

  • 1University of Priština, Faculty of Technical Sciences in Kosovska Mitrovica, Kneza Milosa 7, 38220 Kosovska Mitrovica, Serbia.

Journal of Thermal Biology
|November 28, 2016
PubMed
Summary

Predicting urban thermal comfort is crucial for planning. Extreme Learning Machine (ELM) effectively forecasts Physiological Equivalent Temperature (PET) using environmental data, aiding urban design.

Keywords:
Extreme leaning machinePETPredictionThermal comfortUrban areas

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Area of Science:

  • Environmental Science
  • Urban Planning
  • Computational Intelligence

Background:

  • Urban thermal comfort is vital for environmental design and planning.
  • Accurate thermal comfort prediction requires modeling dynamic climatic and environmental factors.
  • Existing models may not fully capture the non-linear relationships influencing thermal comfort.

Purpose of the Study:

  • To develop a predictive algorithm for thermal comfort in open urban areas.
  • To apply soft computing methodologies for accurate thermal comfort forecasting.
  • To evaluate the effectiveness of Extreme Learning Machine (ELM) for predicting Physiological Equivalent Temperature (PET).

Main Methods:

  • Utilized soft computing, specifically the Extreme Learning Machine (ELM) algorithm.
  • Input variables included temperature, pressure, wind speed, and solar irradiance.
  • Compared ELM predictions against benchmark models for validation.

Main Results:

  • ELM demonstrated effectiveness in forecasting Physiological Equivalent Temperature (PET) values.
  • The model accurately captured the non-linear dynamics of thermal comfort factors.
  • ELM performance was comparable or superior to benchmark models.

Conclusions:

  • Extreme Learning Machine (ELM) is a suitable method for predicting urban thermal comfort (PET).
  • The developed algorithm can inform urban planning and design for improved thermal environments.
  • Accurate PET forecasting aids in optimizing the use of urban spaces throughout the year.