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Hindsight Biases01:12

Hindsight Biases

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Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
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The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
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Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

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Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
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Types of Errors: Detection and Minimization01:12

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Error is the deviation of the obtained result from the true, expected value or the estimated central value. Errors are expressed in absolute or relative terms.
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Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
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Identification of Panoramic Photographic Image Composition Using Fuzzy Rules.

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Related Experiment Video

Updated: Sep 5, 2025

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers
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A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

Published on: January 5, 2018

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Multilayer Reversible Information Hiding with Prediction-Error Expansion and Dynamic Threshold Analysis.

I-Hui Pan1, Ping-Sheng Huang2, Te-Jen Chang3

  • 1Air Command and Staff College, National Defense University, Taoyuan 335, Taiwan.

Sensors (Basel, Switzerland)
|July 9, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel reversible information hiding technique for digital images, enhancing data security and enabling complete restoration of original data. The method offers improved embedding capacity and image quality compared to existing algorithms.

Keywords:
dynamic threshold analysishigh-capacitymultilayerpredicted parameters adjustmentreversible information hiding

Related Experiment Videos

Last Updated: Sep 5, 2025

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers
08:05

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

Published on: January 5, 2018

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Area of Science:

  • Computer Science
  • Information Security
  • Digital Image Processing

Background:

  • The proliferation of the internet and social media necessitates robust solutions for information sharing and intellectual property protection.
  • Reversible information hiding is crucial for ensuring data security, as it guarantees the complete restoration of original and embedded data.
  • Existing methods often face trade-offs between embedding capacity and the quality of the stego image.

Purpose of the Study:

  • To present a high-capacity and multilayer reversible information hiding technique for digital images.
  • To improve the quality of the stego image while maintaining the ability to fully restore the cover image.
  • To offer a superior embedding capacity versus image quality performance compared to current algorithms.

Main Methods:

  • Utilized the integer Haar wavelet transform to convert the cover image from the spatial to the frequency domain.
  • Applied dynamic threshold analysis and a multilayer embedding strategy.
  • Incorporated parameters of a predicted model and a location map for enhanced performance.

Main Results:

  • The proposed technique demonstrates high embedding capacity.
  • The quality of the stego image is improved.
  • Complete restoration of the cover image is achieved.
  • The algorithm shows better embedding capacity versus image quality performance than existing methods.

Conclusions:

  • The developed high-capacity, multilayer reversible information hiding technique effectively balances embedding capacity and image quality.
  • The method provides a secure approach for digital image information embedding and restoration.
  • This technique offers a significant advancement in the field of information security for digital images.