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Thermal expansion and Thermal stress: Problem Solving01:27

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San Francisco's Golden Gate Bridge is exposed to temperatures ranging from -15 °C to 40 °C. At its coldest, the main span of the bridge is 1275 m long. Assuming that the bridge is made entirely of steel, what is the change in its length between these temperatures?
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Thermal strain is a concept that arises when we consider how temperature changes affect structures. Unlike the conventional assumption that structures remain constant under load, real-world scenarios often involve temperature fluctuations that can significantly impact these structures. Consider a homogeneous rod with a uniform cross-section resting freely on a flat horizontal surface. If the rod's temperature increases, the rod elongates. This elongation is proportional to the temperature...
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The expansion of alcohol in a thermometer is one of many commonly encountered examples of thermal expansion, which is the change in size or volume of a given system as its temperature changes. The most visible example is the expansion of hot air. When air is heated, it expands and becomes less dense than the surrounding air, which then exerts an upward force on the hot air to, for example, make steam and smoke rise, and hot air balloons float. The same behavior happens in all liquids and gases,...
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If the temperature of an object is changed while it is prevented from expanding or contracting, the object is subjected to stress. The stress is compressive if the object expands in the absence of constraint and tensile if it contracts. This stress resulting from temperature change is known as thermal stress. It can be quite large and can cause damage. To avoid this stress, engineers may design components so they can expand and contract freely. For instance, on highways, gaps are deliberately...
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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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In hot, dry climates, the thermal mass of masonry walls can be beneficial, absorbing heat during the day and releasing it at night, thereby stabilizing indoor temperatures. However, in most other climates, additional insulation is necessary to enhance thermal resistance.
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Exploring the Use of Isolated Expressions and Film Clips to Evaluate Emotion Recognition by People with Traumatic Brain Injury
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Thermal Augmented Expression Recognition.

Shangfei Wang, Bowen Pan, Huaping Chen

    IEEE Transactions on Cybernetics
    |June 15, 2018
    PubMed
    Summary
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    This study introduces a novel method for facial expression recognition using visible images, enhanced by thermal infrared data during training. This approach improves recognition accuracy, even with unpaired data.

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    Area of Science:

    • Computer Vision
    • Machine Learning
    • Biometrics

    Background:

    • Visible facial images capture expression cues but are sensitive to lighting. Thermal facial images offer illumination robustness by recording temperature distribution.
    • Facial expression recognition benefits from fusing visible and thermal data, but thermal cameras are costly, limiting their widespread use.
    • Existing methods often rely solely on visible data, potentially missing crucial thermal information.

    Purpose of the Study:

    • To develop a novel visible facial expression recognition method using thermal infrared (IR) data as privileged information during training.
    • To enhance facial representations and expression classifiers for visible images by leveraging thermal IR data.
    • To address challenges with partially unpaired visible and thermal data in expression recognition.

    Main Methods:

    • Learning deep models for both visible and thermal images, followed by training Support Vector Machine (SVM) classifiers.
    • Jointly refining deep models and SVM classifiers by enforcing similarity constraints on outputs from both data views.
    • Extending the method to handle partially unpaired visible and thermal image data, where recordings may not be synchronous.

    Main Results:

    • The proposed thermal augmented expression recognition method effectively utilizes thermal IR images' supplementary role during training.
    • Improved facial representations and a more accurate visible expression classifier were achieved.
    • State-of-the-art expression recognition performance was demonstrated for both paired and unpaired facial image datasets.

    Conclusions:

    • Thermal IR data, even when only available during training, significantly enhances visible facial expression recognition.
    • The proposed method offers a robust solution for expression recognition, overcoming limitations of visible-only approaches and handling data asynchrony.
    • This approach achieves superior performance, highlighting the value of privileged thermal information in visible-based facial expression analysis.