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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

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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

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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

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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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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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Video Experimental Relacionado

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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Reconocimiento facial eficiente y que preserva la privacidad basado en codificación de características y cifrado

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
Resumen

Este estudio presenta un sistema de reconocimiento facial que preserva la privacidad utilizando el método de codificación de características faciales (FFCM) y cifrado homomórfico. El enfoque novedoso mejora la eficiencia y la seguridad al reducir la entropía computacional para una mejor protección de la privacidad facial.

Palabras clave:
reconocimiento facialcifrado homomórficoprivacidad

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Área de la Ciencia:

  • Ciencias de la Computación
  • Criptografía
  • Biometría

Sus antecedentes:

  • Los sistemas de reconocimiento facial que preservan la privacidad enfrentan desafíos con la ineficiencia computacional y la alta entropía.
  • Los métodos existentes a menudo luchan por equilibrar la seguridad, la eficiencia y la protección de la privacidad.

Objetivo del estudio:

  • Proponer un método eficiente y seguro de reconocimiento facial que preserve la privacidad.
  • Reducir la entropía computacional y mejorar la eficiencia del sistema mientras se protegen los datos faciales.

Principales métodos:

  • Se utilizó el método de codificación de características faciales (FFCM) y cifrado homomórfico simétrico.
  • Se construyó un árbol de características N-ario utilizando un FFCM basado en redes neuronales para acelerar la coincidencia.
  • Se empleó cifrado homomórfico simétrico ligero para el cálculo seguro de la similitud del coseno en texto cifrado.

Principales resultados:

  • Se lograron mejoras significativas en la eficiencia de la búsqueda de cifrados.
  • Se demostró una eficiencia de autenticación facial un 4% a 6% mayor en comparación con las soluciones de vanguardia.
  • El análisis de seguridad confirmó la resiliencia contra ataques pasivos y activos.

Conclusiones:

  • El método propuesto ofrece un enfoque eficiente, seguro y consciente de la entropía para el reconocimiento facial que preserva la privacidad.
  • Esta técnica muestra mejoras sustanciales para aplicaciones a gran escala.
  • La privacidad facial se protege eficazmente sin comprometer el rendimiento del sistema.