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Related Concept Videos

Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

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The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation  between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
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Entropy01:18

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The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
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In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Scientists refer to the measure of randomness or disorder within a system as entropy. High entropy means high disorder and low energy. To better understand entropy, think of a student’s bedroom. If no energy or work were put into it, the room would quickly become messy. It would exist in a very disordered state, one of high entropy. Energy must be...
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In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Processes that involve an increase in entropy of the system (ΔS > 0) are very often spontaneous; however, examples to the contrary are plentiful. By expanding consideration of entropy changes to include the surroundings, a significant conclusion regarding the relation between this property and spontaneity may be reached. In thermodynamic...
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Third Law of Thermodynamics02:38

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A pure, perfectly crystalline solid possessing no kinetic energy (that is, at a temperature of absolute zero, 0 K) may be described by a single microstate, as its purity, perfect crystallinity,and complete lack of motion means there is but one possible location for each identical atom or molecule comprising the crystal (W = 1). According to the Boltzmann equation, the entropy of this system is zero.
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Entropy Change in Reversible Processes01:10

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In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
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Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
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The Role of Thermodynamic and Informational Entropy in Improving Real Estate Valuation Methods.

Ünsal Özdilek1

  • 1Business School, Department of Strategy, Social and Environmental Responsibility, University of Quebec, Montreal, QC H3C 3P8, Canada.

Entropy (Basel, Switzerland)
|June 28, 2023
PubMed
Summary

This study integrates entropy measurements into real estate valuation, improving the precision of price, cost, and income (PCI) estimates. This enhances economic decision-making and reduces errors in property appraisal.

Keywords:
Entropy weighting method (EWM)evaluation methodsinformationmulti-criteria decision making (MCDM)real estate appraisalvalue state measure

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Area of Science:

  • Economics
  • Real Estate Appraisal
  • Information Theory

Background:

  • Price, Cost, and Income (PCI) are crucial economic indicators for commodity valuation.
  • Inaccurate PCI measurements due to inherent uncertainties lead to significant economic decision-making errors, especially in real estate.
  • Current valuation methodologies struggle with inherent uncertainties affecting accuracy.

Purpose of the Study:

  • To address measurement errors in real estate valuation caused by inherent uncertainties in value states.
  • To improve the accuracy of economic decision-making in property markets.
  • To enhance the appraisal system's final stage for definitive value decisions.

Main Methods:

  • Incorporation of entropy measurements into real estate valuation processes.
  • Adjustment and integration of triadic Price, Cost, and Income (PCI) estimates using entropy.
  • Application of a mathematical technique to refine value measurements.

Main Results:

  • Significant improvement in the precision of value measurements through entropy integration.
  • Reduction in economic decision-making errors within the real estate market.
  • Enhanced accuracy of appraisal systems for definitive value decisions.

Conclusions:

  • Entropy integration offers a promising approach to enhance the accuracy of real estate valuation.
  • Informed production and trading strategies can be developed by market agents using improved value estimates.
  • The methodology shows potential for reducing economic losses associated with inaccurate property valuations.