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Related Concept Videos

Entropy02:39

Entropy

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Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
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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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Entropy is a state function, so the standard entropy change for a chemical reaction (ΔS°rxn) can be calculated from the difference in standard entropy between the products and the reactants.
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Decision Making: Traditional Method01:14

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The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
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Maslow's Need Hierarchy Theory01:27

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Abraham Maslow's theory of motivation, introduced in 1943, is widely known as the "Hierarchy of Needs." This theory posits that human needs are arranged in a hierarchical structure, starting with basic survival needs and progressing toward more complex psychological and self-fulfillment desires. The hierarchy is typically a pyramid, and the lower needs must be satisfied to reach the next level.
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Related Experiment Video

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Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
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Settlement Dynamics and Hierarchy from Agent Decision-Making: a Method Derived from Entropy Maximization.

Mark Altaweel1

  • 1Institute of Archaeology, University College London, 31-34 Gordon Square, London, WC1H 0PY UK.

Journal of Archaeological Method and Theory
|January 26, 2018
PubMed
Summary
This summary is machine-generated.

This study simulates settlement changes using agent-based modeling and entropy maximization. Individual decisions and social-environmental factors significantly influence settlement size hierarchies, impacting urban development.

Keywords:
Agent basedComplexityEntropy maximizationModelingSpatial interactionUrbanism

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Area of Science:

  • Complex systems science
  • Archaeological modeling
  • Urban studies

Background:

  • Entropy maximization is established for analyzing settlement structure change across time and space.
  • Few studies have applied entropy maximization to understand how individual decisions influence settlement size distributions.

Purpose of the Study:

  • To develop and apply a novel agent-based simulation integrating entropy maximization principles.
  • To investigate the impact of individual and household decisions on settlement size hierarchies.
  • To model urbanism from both top-down and bottom-up perspectives.

Main Methods:

  • Agent-based complex system simulation incorporating entropy maximization.
  • Modeling of individual decision-making based on social-environmental factors, geography, and relative benefits.
  • Incorporation of movement ability and site attractiveness feedbacks influencing settlement size.

Main Results:

  • Simulations reveal distinct settlement factors and household choices driving settlement size hierarchies.
  • Case study analysis using Middle Bronze Age (MBA) and Iron Age (IA) settlement patterns from the Iraqi North Jazirah Survey (NJS).
  • Conflict and socio-political cohesion significantly affect observed settlement hierarchies.

Conclusions:

  • The developed model successfully replicates settlement size hierarchies observed in historical periods.
  • The approach is adaptable to various empirical settings and can incorporate data uncertainty.
  • Understanding individual choices is crucial for comprehending urban development dynamics.