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Related Concept Videos

Symmetric Member in Bending01:07

Symmetric Member in Bending

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In the study of the mechanics of materials, analyzing the behavior of prismatic members under opposing couples is crucial for understanding internal stress distributions, which are essential for structural design. When subjected to couples, a prismatic member experiences internal forces that maintain equilibrium. A couple, characterized by two equal and opposite forces, creates a moment but no resultant force. The internal forces at any section cut of the member must balance these external...
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Encoding01:19

Encoding

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Information enters the brain through encoding, which is the input of information into the memory system. Once sensory information is received from the environment, the brain labels or codes it. The information is then organized with similar information and connected to existing concepts. Encoding occurs through automatic processing and effortful processing.
Automatic processing involves the encoding of details like time, space, frequency, and the meaning of words, usually done without conscious...
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Deformations in a Symmetric Member in Bending01:18

Deformations in a Symmetric Member in Bending

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When analyzing the deformation of a symmetric prismatic member subjected to bending by equal and opposite couples, it becomes clear that as the member bends, the originally straight lines on its wider faces curve into circular arcs, with a constant radius centered at a point known as Point C. This phenomenon helps to understand the stress and strain distribution within the member more clearly.
When the member is segmented into tiny cubic elements, it is observed that the primary stress...
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Beams with Symmetric Loadings01:15

Beams with Symmetric Loadings

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The moment-area method is an analytical tool used in structural engineering to determine the slope and deflection of beams under various loads. Consider a cantilever with a concentrated load and moment at the free end. The first step is constructing a free-body diagram to calculate the reactions at the fixed end. Next, the bending moment diagram is plotted to visualize how the bending moment varies along the beam's length, focusing on points where the bending moment equals zero.
The M/EI...
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Gravitation Between Spherically Symmetric Masses01:14

Gravitation Between Spherically Symmetric Masses

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The gravitational potential energy between two spherically symmetric bodies can be calculated from the masses and the distance between the bodies, assuming that the center of mass is concentrated at the respective centers of the bodies.
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IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

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Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single...
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Related Experiment Video

Updated: Jan 29, 2026

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
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Efficient Privacy-Preserving Face Recognition Based on Feature Encoding and Symmetric Homomorphic Encryption.

Limengnan Zhou1, Qinshi Li2, Hui Zhu3

  • 1School of Electronic and Information Engineering, University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan 528402, China.

Entropy (Basel, Switzerland)
|January 28, 2026
PubMed
Summary

This study introduces a privacy-preserving face recognition system using Face Feature Coding Method (FFCM) and homomorphic encryption. The novel approach enhances efficiency and security by reducing computational entropy for better facial privacy protection.

Keywords:
face recognitionhomomorphic encryptionprivacy

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Area of Science:

  • Computer Science
  • Cryptography
  • Biometrics

Background:

  • Privacy-preserving face recognition systems face challenges with computational inefficiency and high entropy.
  • Existing methods often struggle to balance security, efficiency, and privacy protection.

Purpose of the Study:

  • To propose an efficient and secure privacy-preserving face recognition method.
  • To reduce computational entropy and enhance system efficiency while protecting facial data.

Main Methods:

  • Utilized Face Feature Coding Method (FFCM) and symmetric homomorphic encryption.
  • Constructed an N-ary feature tree using a neural network-based FFCM to accelerate matching.
  • Employed lightweight symmetric homomorphic encryption for secure cosine similarity computation in ciphertext.

Main Results:

  • Achieved significant improvements in ciphertext search efficiency.
  • Demonstrated a 4% to 6% higher facial authentication efficiency compared to state-of-the-art solutions.
  • Security analysis confirmed resilience against passive and active attacks.

Conclusions:

  • The proposed method offers an efficient, secure, and entropy-aware approach for privacy-preserving face recognition.
  • This technique shows substantial improvements for large-scale applications.
  • Facial privacy is effectively protected without compromising system performance.