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Range00:59

Range

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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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Time and frequency -Domain Interpretation of PI Control01:27

Time and frequency -Domain Interpretation of PI Control

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Proportional-Integral (PI) controllers are essential in many control systems to improve stability and performance. They are commonly used in everyday devices like thermostats to enhance system damping and reduce steady-state error. When the zero in the controller's transfer function is optimally placed, the system benefits significantly in terms of stability and accuracy.
Acting as a low-pass filter, the PI controller slows the system's response and extends settling times. This requires...
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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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Structural Joints: Synovial Joints01:16

Structural Joints: Synovial Joints

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Synovial joints are the most common type of joint in the body. A key structural characteristic for a synovial joint is the presence of a joint cavity. This fluid-filled space is where the articulating surfaces of the bones contact each other. Also, unlike fibrous or cartilaginous joints, the articulating bone surfaces at a synovial joint are not directly connected to each other with fibrous connective tissue or cartilage. This gives the bones of a synovial joint the ability to move smoothly...
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Structural Joints: Fibrous Joints01:03

Structural Joints: Fibrous Joints

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Fibrous joints are a type of joint where the bones are connected by fibrous connective tissue. These joints provide stability and minimal to no movement between the articulating bones. There are three types of fibrous joints.
Suture
All the bones of the skull, except for the mandible, are joined to each other by a fibrous joint called a suture. The fibrous connective tissue found at a suture strongly unites the adjacent skull bones and thus helps to protect the brain and form the face. In...
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Structural Joints: Cartilaginous Joints01:17

Structural Joints: Cartilaginous Joints

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As the name indicates, at a cartilaginous joint, the adjacent bones are united by cartilage, a tough but flexible type of connective tissue. Unlike synovial joints, these types of joints lack a joint cavity and involve bones joined together by either hyaline cartilage or fibrocartilage.
There are two types of cartilaginous joints:
Synchondrosis
A synchondrosis ("joined by cartilage") is a cartilaginous joint where bones are connected by hyaline cartilage. Synchondrosis may be temporary...
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Performance of High Efficiency Avalanche Poly-SiGe Devices for Photo-Sensing Applications.

Sensors (Basel, Switzerland)ยท2022
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Related Experiment Video

Updated: Feb 15, 2026

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
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Joint Bearing and Range Estimation of Multiple Objects from Time-Frequency Analysis.

Jeng-Cheng Liu1, Yuang-Tung Cheng2, Hsien-Sen Hung3

  • 1Department of Electrical Engineering, National Taiwan Ocean University, No.2 Pei-ning Rd., Keelung 20224, Taiwan. d96530001@mail.ntou.edu.tw.

Sensors (Basel, Switzerland)
|January 20, 2018
PubMed
Summary

This study introduces a new Hilbert-Huang Transform (HHT) method for joint direction-of-arrival (DOA) and range estimation using micro-electro-mechanical systems (MEMS) hydrophones. The approach enables real-time, single-snapshot target localization for Autonomous Underwater Vehicles (AUVs).

Keywords:
AUVDOAHHTMEMSTFDULA

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Area of Science:

  • Sonar signal processing
  • Underwater acoustics
  • Array signal processing

Background:

  • Direction-of-arrival (DOA) and range estimation are critical for sonar systems.
  • Existing methods often require multiple data snapshots and complex computations.
  • Micro-electro-mechanical systems (MEMS) offer advantages for underwater sensor arrays.

Purpose of the Study:

  • To propose a novel Hilbert-Huang Transform (HHT) based approach for joint DOA and range estimation.
  • To utilize a uniform linear array (ULA) of MEMS hydrophones for target localization.
  • To enable real-time processing with a single data snapshot.

Main Methods:

  • Application of Hilbert-Huang Transform (HHT) for time-frequency distribution (TFD) analysis.
  • Development of a novel algorithm simplifying nonlinear estimation problems.
  • Utilizing a uniform linear array (ULA) of MEMS hydrophones.

Main Results:

  • The proposed method achieves joint bearing and range estimation for multiple targets.
  • Real-time processing is feasible with a single data snapshot.
  • Simulations confirm the effectiveness of the HHT-based localization method.

Conclusions:

  • The HHT-based approach provides an efficient and effective solution for target localization.
  • The method simplifies complex nonlinear estimation problems for sonar signal processing.
  • The use of MEMS hydrophones enhances suitability for Autonomous Underwater Vehicle (AUV) operations.