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Related Concept Videos

Sampling Methods: Overview01:06

Sampling Methods: Overview

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A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
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Systematic Sampling Method01:17

Systematic Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
Systematic sampling is one of the simplest methods...
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Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

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Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
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Random Sampling Method01:09

Random Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
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Sampling Plans01:23

Sampling Plans

809
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
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Convenience Sampling Method00:55

Convenience Sampling Method

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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
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Related Experiment Video

Updated: Dec 24, 2025

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
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Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

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An Activity-Aware Sampling Scheme for Mobile Phones in Activity Recognition.

Zhimin Chen1, Jianxin Chen1, Xiangjun Huang1

  • 1College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China.

Sensors (Basel, Switzerland)
|April 17, 2020
PubMed
Summary

This study enhances smartphone energy efficiency for human activity recognition (HAR) by adaptively controlling sensor sampling rates. This method achieves significant energy savings while maintaining high recognition accuracy.

Keywords:
activity recognitionfeature selectionmachine learningpower consumption

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Biomedical Engineering

Background:

  • Smartphone sensors are increasingly used for human activity recognition (HAR).
  • Computational demands of HAR on smartphones limit application scope due to power constraints.
  • Energy efficiency is crucial for practical HAR applications on mobile devices.

Purpose of the Study:

  • To improve energy efficiency in smartphone-based HAR.
  • To develop an adaptive sensor sampling rate control method.
  • To maintain high recognition accuracy while reducing power consumption.

Main Methods:

  • Adaptive control of sensor sampling rates based on acceleration magnitude.
  • Feature selection using Linear Discriminant Analysis (LDA).
  • Activity classification using machine learning algorithms.

Main Results:

  • Achieved an overall energy saving of 56.39%.
  • Maintained a high recognition accuracy of 99.58%.
  • Demonstrated effectiveness on the UCI HAR dataset.

Conclusions:

  • Adaptive sensor sampling is an effective strategy for energy-efficient HAR on smartphones.
  • The proposed method balances energy savings and classification performance.
  • This approach enables more sustainable and widespread use of HAR technology.