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Related Concept Videos

Boundary Conditions: Lossless Lines01:21

Boundary Conditions: Lossless Lines

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Consider a single-phase, two-wire, lossless transmission line terminated by an impedance at the receiving end and a source with Thevenin voltage and impedance at the sending end. The line, with length, has a surge impedance and wave velocity determined by the line's inductance and capacitance.
At the receiving end, the boundary condition states that the voltage equals the product of the receiving-end impedance and current. This relationship is expressed as a function of the incident and...
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Sample Proportion and Population Proportion01:20

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Collecting samples or responses from an entire population takes significant time and effort, so a researcher collects responses from only a sample of that population. Suppose a study needs to collect information about a specific mobile application. After sample collection, the researcher analyzes the data and discovers that most individuals in the sample use that specific mobile application. The sample proportion measures the number of individuals in a sample who either use or don't use the...
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Probability Histograms01:17

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A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
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Relative Frequency Histogram01:14

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The relative frequency depicts the proportion of data points that have each value. The frequency tells the number of data points that have each value. Like the histogram, a relative frequency histogram also has the same shape with a horizontal scale (the x-axis), but the vertical scale (the y-axis) is marked with relative frequencies (percentages of the whole) instead of actual frequencies. A relative frequency histogram is a graphical representation of a frequency distribution where the...
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Buffers: Buffer Capacity01:09

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Buffer capacity is the quantitative measure of a buffer to resist the change in pH. As shown in the following equation, the buffer capacity, denoted by 'beta', is expressed as the number of moles of acid or base needed to change the pH of a one-liter buffer solution by 1 unit. Here, Ca and Cb indicate the number of moles of acid and base, respectively. Note that dpH represents the change in pH.
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The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
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Related Experiment Video

Updated: Mar 12, 2026

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
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Proportional Borda allocations.

Andreas Darmann1, Christian Klamler1

  • 1Institute of Public Economics, University of Graz, Graz, Austria.

Social Choice and Welfare
|November 8, 2016
PubMed
Summary

This study explores fair division of indivisible items using the Borda rule. We demonstrate that proportional allocations are achievable and computationally efficient under specific assumptions.

Area of Science:

  • Computer Science
  • Economics
  • Game Theory
  • Fair Division

Background:

  • Fair division of indivisible items is a growing research area.
  • Proportionality is a key fairness criterion, ensuring each agent receives at least 1/n of the total value.
  • Determining item values from ordinal rankings can be complex.

Purpose of the Study:

  • To investigate the feasibility of achieving proportional allocations of indivisible items.
  • To utilize the Borda rule for simplifying value determination from ordinal rankings.
  • To assess the computational complexity of finding such proportional allocations.

Main Methods:

  • Employing the Borda rule from voting theory to derive item values from agent rankings.

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  • Analyzing the conditions under which proportionality can be guaranteed.
  • Developing algorithms to find proportional allocations.
  • Main Results:

    • Proportional allocations are possible under certain assumptions, even with indivisible items.
    • The Borda rule facilitates value determination from ordinal rankings.
    • Finding proportional allocations is computationally efficient in these scenarios.

    Conclusions:

    • The Borda rule offers a practical approach to fair division problems involving indivisible items.
    • Proportionality can be achieved efficiently in fair division contexts with specific constraints.
    • This research contributes to the computational aspects of fair allocation mechanisms.