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Related Concept Videos

Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

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In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
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Sampling Methods: Overview01:06

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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. 
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Sampling Plans01:23

Sampling Plans

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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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Sampling Theorem01:15

Sampling Theorem

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In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
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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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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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Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking
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Effects-Driven Participatory Design: Learning from Sampling Interruptions.

Morten Brandrup1, Kija Lin Østergaard1, Morten Hertzum2

  • 1Roskilde University, Denmark.

Studies in Health Technology and Informatics
|January 27, 2017
PubMed
Summary
This summary is machine-generated.

Participatory design (PD) for healthcare technology needs real-world feedback. An effects-driven approach using experience sampling method (ESM) showed electronic whiteboards did not reduce interruptions.

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Area of Science:

  • Health Informatics
  • Human-Computer Interaction
  • Organizational Studies

Background:

  • Healthcare information technologies (HIT) offer benefits but require effective implementation strategies.
  • Participatory design (PD) is crucial for HIT success, necessitating integration of real-world usage feedback.
  • Traditional PD methods may not fully capture the dynamic nature of technology use in clinical settings.

Purpose of the Study:

  • To describe and evaluate an effects-driven PD approach.
  • To assess the utility of the experience sampling method (ESM) for collecting real-use feedback in PD.
  • To investigate the impact of electronic whiteboards on clinical coordination and interruptions.

Main Methods:

  • An effects-driven PD approach focusing on pursued effects.
  • Utilized the experience sampling method (ESM) via a custom app for data collection.
  • Case study involving the implementation of electronic whiteboards at a Danish hospital.

Main Results:

  • Electronic whiteboards demonstrated limited potential for reducing phone call interruptions in the operating ward.
  • The combination of quantitative and qualitative ESM data facilitated assumption alignment and in-situ reflection.
  • Participant-driven refinement of ESM data capture enhanced the PD process.

Conclusions:

  • Effects-driven PD, incorporating real-use feedback via ESM, is vital for optimizing healthcare technology.
  • ESM serves as a valuable tool for triggering reflection and informing design iterations in clinical environments.
  • The study highlights the importance of continuous feedback loops in participatory design for healthcare settings.