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Related Concept Videos

Distance Measurements by Taping01:18

Distance Measurements by Taping

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Tapes are essential in surveying for accurate, durable, and short-distance measurements. Made from lightweight, nylon-coated steel, they offer flexibility and strength for rugged outdoor use. The nylon coating protects against rust and wear, extending the tape's life. Standard lengths, around 30 meters, are marked in meters and millimeters for precision.Surveyors select tapes based on site conditions and accuracy needs. Lightweight, nylon-coated tapes are commonly used for ease of handling and...
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Time-Series Graph00:54

Time-Series Graph

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A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
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Distance Corrections01:15

Distance Corrections

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To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
26
Design Example: Measuring Distance Between Two Points with Obstructions01:10

Design Example: Measuring Distance Between Two Points with Obstructions

28
When measuring distances in areas with physical obstructions, such as a lake in a field, surveyors must employ techniques to calculate accurate lengths without direct line measurements. One effective method is the offset technique, which allows for precise distance estimation over inaccessible stretches.In this scenario, a surveyor must measure a side of an area that crosses a lake. Since the measuring tape cannot span the lake, the surveyor begins by establishing a baseline that aligns with...
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Per-Unit Sequence Models01:26

Per-Unit Sequence Models

71
An ideal Y-Y transformer, grounded through neutral impedances, displays per-unit sequence networks akin to those of a single-phase ideal transformer when subjected to balanced positive- or negative-sequence currents. These currents do not produce neutral currents, and their associated voltage drops.
Zero-sequence currents, which are identical in magnitude and phase, generate a neutral current, resulting in voltage drops across the neutral impedance and the low-voltage winding. If the...
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Ogive Graph01:07

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An ogive graph is sometimes called a cumulative frequency polygon. It is one type of frequency polygon that shows cumulative frequency. In other words, the cumulative percentages are added to the graph from left to right. An ogive graph plots cumulative frequency on the vertical y-axis and class boundaries along the horizontal x-axis. It’s very similar to a histogram; only instead of rectangles, an ogive displays a single point where the top right of the rectangle would be. Creating this...
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Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
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An embedding-based distance for temporal graphs.

Lorenzo Dall'Amico1, Alain Barrat2, Ciro Cattuto3

  • 1ISI Foundation, Turin, 10126, Italy. lorenzo.dallamico@isi.it.

Nature Communications
|November 17, 2024
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Summary
This summary is machine-generated.

We introduce a novel distance metric for temporal graphs, enabling whole-graph comparison. This method effectively quantifies similarity even for graphs with varying nodes and time spans, advancing temporal network analysis.

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Area of Science:

  • Complex Systems
  • Network Science
  • Data Mining

Background:

  • Temporal graphs model dynamic relationships in systems.
  • Existing methods struggle to quantify overall temporal graph similarity.
  • Comparing temporal graphs with different structures remains challenging.

Purpose of the Study:

  • To develop a robust method for quantifying similarity between temporal graphs.
  • To introduce a distance metric applicable to graphs with varying nodes and time spans.
  • To enable comprehensive analysis of temporal network evolution.

Main Methods:

  • Utilizing embeddings derived from time-respecting random walks.
  • Defining a novel distance measure for temporal graph comparison.
  • Adapting the metric for both matched and unmatched graph pairs.

Main Results:

  • The proposed distance metric effectively discriminates temporal graphs based on topological and temporal properties.
  • The method is applicable to temporal graphs with differing numbers of nodes and time spans.
  • Empirical and synthetic data validate the distance's efficacy.

Conclusions:

  • A new, well-defined distance metric for temporal graphs has been established.
  • This metric provides a powerful tool for analyzing temporal network dynamics.
  • An efficient implementation supports large-scale temporal graph analysis.