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Related Concept Videos

Range00:59

Range

14.1K
The range is one of the measures of variation. It can be defined as the difference between a dataset's highest and lowest values. For example, in the study of seven 16-ounce soda cans, the filled volume of soda was measured, thus producing the following amount (in ounces) of soda:
15.9; 16.1; 15.2; 14.8; 15.8; 15.9; 16.0; 15.5
Measurements of the amount of soda in a 16-ounce can vary since different subjects record these measurements or since the exact amount - 16 ounces of liquid, was not...
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¹H NMR: Long-Range Coupling01:27

¹H NMR: Long-Range Coupling

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The coupling interactions of nuclei across four or more bonds are usually weak, with J values less than 1 Hz. While these are usually not observed in spectra, the presence of multiple bonds along the coupling pathway can result in observable long-range coupling.
In alkenes, spin information is communicated via σ–π overlap, as seen in allylic (four-bond) and homoallylic (five-bond) couplings. These coupling interactions are stronger when the σ bond is parallel to the alkene...
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Variation: Normal Distribution, Range, and Standard Deviation02:32

Variation: Normal Distribution, Range, and Standard Deviation

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In the field of psychology, there are several ways to organize measurements of a trait, feature, or characteristic (i.e., variables). Qualitative data, such as ethnicity, can be tabulated into a frequency count to provide information about the proportion, as well as the variety of groups in a sample or population. On the other hand, researchers can perform a wider set of calculations on quantitative data. The mean, mode, and median, for instance, are central tendency measures to identify a...
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Angle of Twist - Elastic Range01:13

Angle of Twist - Elastic Range

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Consider a cylindrical shaft with a length denoted by L and a consistent cross-sectional radius referred to as r. This shaft undergoes a torque at the free end. The highest shearing strain within the shaft is directly proportional to the twist angle and the radial distance from the shaft axis. When the shaft behaves elastically, this shearing strain can be articulated using variables such as the applied torque, radial distance, the polar moment of inertia, and the modulus of rigidity. By...
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Range Rule of Thumb to Interpret Standard Deviation01:13

Range Rule of Thumb to Interpret Standard Deviation

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The range rule of thumb in statistics helps us calculate a dataset's minimum and maximum values with known standard deviation. This rule is based on the concept that 95% of all values in a dataset lie within two standard deviations from the mean.
For instance, the range rule of thumb can be used to find the tallest and the shortest student in a class, given the mean student height and standard deviation. If the mean student height is 1.6 m and the standard deviation, s is 0.05 m, the height...
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Magnetic Field due to Moving Charges01:23

Magnetic Field due to Moving Charges

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A stationary charge creates and interacts with the electric field, while a moving charge creates a magnetic field.
Consider a point charge moving with a constant velocity. Like the electric field, the magnetic field at any point is directly proportional to the magnitude of the charge and inversely proportional to the square of the distance between the source point and the field point. However, unlike the electric field, the magnetic field is always perpendicular to the plane containing the line...
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Moving target ranging method for a photon-counting system.

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    This study introduces a Hough transform-based ranging method to accurately track moving targets in laser ranging systems, even with significant noise. The new approach improves target track extraction, reduces processing time, and lowers ranging errors compared to existing methods.

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    Area of Science:

    • Optics and Photonics
    • Signal Processing
    • Robotics and Automation

    Background:

    • Photon-counting techniques offer high sensitivity and time resolution for laser ranging.
    • Extracting moving target tracks from intense noise in photon-counting laser ranging remains a challenge, especially for non-cooperative targets.

    Purpose of the Study:

    • To develop an accurate and efficient laser ranging method for extracting moving target tracks from noisy backgrounds.
    • To improve the performance of photon-counting laser ranging systems for non-cooperative targets.

    Main Methods:

    • A novel ranging method based on the Hough transform is proposed, leveraging target distribution characteristics in point cloud data.
    • The method employs a two-stage approach: an initial stage for accurate distance/velocity measurement using extensive data, and a tracking stage for real-time updates with minimal data.
    • Comparison with local distance statistics and density-based filtering methods.

    Main Results:

    • The proposed Hough transform-based method effectively extracts target tracks from noisy data.
    • Demonstrated decreased time consumption and lower ranging errors compared to existing methods.
    • Effective performance across various detection conditions.

    Conclusions:

    • The Hough transform-based ranging method provides a robust solution for tracking moving targets in challenging photon-counting laser ranging scenarios.
    • The two-stage approach balances accuracy and real-time processing efficiency.
    • This method offers significant advantages over traditional techniques for non-cooperative target ranging.