Jove
Visualize
Contáctanos

Videos de Conceptos Relacionados

Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

2.1K
A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
2.1K
Reducing Line Loss01:18

Reducing Line Loss

193
In a three-phase circuit, line loss is an indicator of energy dissipated as heat due to the resistance of transmission lines. To address this, incorporating transformers into the system—a step-up transformer at the source and a step-down transformer at the load—is a strategic solution. Two three-phase transformers are introduced to improve this.
With a step-up transformer at the source, the voltage is increased, thereby reducing the current in the transmission lines since power loss...
193
Differential Leveling01:12

Differential Leveling

308
Differential leveling is a precise method in surveying used to determine the elevation difference between two points. Its primary goal is to establish accurate vertical measurements to create level surfaces or grade lines critical for designing and constructing infrastructures such as roads, bridges, and buildings.The procedure for differential leveling begins with setting up and leveling the instrument at a point where the benchmark can be seen. The level rod is held on the benchmark (BM), and...
308
Improving Translational Accuracy02:07

Improving Translational Accuracy

11.8K
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
11.8K
Deconvolution01:20

Deconvolution

247
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
247
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

7.8K
The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
7.8K

También podría leer

Artículos Relacionados

Artículos vinculados a este trabajo por autores compartidos, revista y gráfico de citas.

Ordenar por
Same author

Few and Different: Detecting Examinees With Preknowledge Using Extended Isolation Forests.

Applied psychological measurement·2025
Same author

Outlier Detection Using t-test in Rasch IRT Equating under NEAT Design.

Applied psychological measurement·2022
Same author

Application of Sampling Variance of Item Response Theory Parameter Estimates in Detecting Outliers in Common Item Equating.

Applied psychological measurement·2022
Same author

A Seed Usage Issue on Using catR for Simulation and the Solution.

Applied psychological measurement·2020
Same author

Evaluating Robust Scale Transformation Methods With Multiple Outlying Common Items Under IRT True Score Equating.

Applied psychological measurement·2020
Same author

On a New Algorithm for Removing Repeating Patterns in Similarity Analysis.

Educational and psychological measurement·2020
Same journal

The EM Algorithm and Its Variants in Cognitive Diagnostic Models: Comparing Their Propensity for Boundaries, Extremes, Convergence, and Suboptimal Solutions.

Applied psychological measurement·2026
Same journal

When Perceptions of Social Desirability Differ: Implications for the Multidimensional Nominal Response Model of Faking.

Applied psychological measurement·2026
Same journal

csemGT: An R Package for Estimating Raw-Score Conditional Standard Errors of Measurement in Generalizability Theory.

Applied psychological measurement·2026
Same journal

Confirmatory Factor Analysis with Adaptive Quadrature Estimator Using Four Link Functions.

Applied psychological measurement·2026
Same journal

Automatic Item Generation Measurement Models Respecting the Stochastic Sampling Space for Cross-Classified and Two-Level Sampling of Subjects and Incidentals.

Applied psychological measurement·2026
Same journal

Multistage Testing for Cognitive Diagnosis Based on Skill-Space Partitioning.

Applied psychological measurement·2026
Ver todos los artículos relacionados
JoVE
x logofacebook logolinkedin logoyoutube logo
ACERCA DE JoVE
Visión GeneralLiderazgoBlogCentro de Ayuda JoVE
AUTORES
Proceso de PublicaciónConsejo EditorialAlcance y PolíticasRevisión por ParesPreguntas FrecuentesEnviar
BIBLIOTECARIOS
TestimoniosSuscripcionesAccesoRecursosConsejo Asesor de BibliotecasPreguntas Frecuentes
INVESTIGACIÓN
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchivo
EDUCACIÓN
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualCentro de Recursos para ProfesoresSitio de Profesores
Términos y Condiciones de Uso
Política de Privacidad
Políticas

Video Experimental Relacionado

Updated: Sep 9, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.2K

Utilizando el aprendizaje profundo para elegir los valores de suavizado óptimos para la ecuación

Chunyan Liu1, Zhongmin Cui2

  • 1Psychometrics and Data Analysis, National Board of Medical Examiners, Philadelphia, PA, USA.

Applied psychological measurement
|August 29, 2025
PubMed
Resumen
Este resumen es generado por máquina.

Este estudio automatizó la puntuación de las pruebas utilizando el aprendizaje profundo. Una red neuronal convolucional logró un acuerdo del 71% con expertos humanos en la selección de valores de suavizado óptimos para igualar las formas de prueba.

Palabras clave:
la automatizaciónred neuronal convolucionalEspinilla cúbicaaprendizaje profundola equiparaciónel alisado

Más Videos Relacionados

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders
05:49

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

960
Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.3K

Videos de Experimentos Relacionados

Last Updated: Sep 9, 2025

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches
09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.2K
Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders
05:49

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

960
Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.3K

Área de la Ciencia:

  • Psicometría
  • Aprendizaje automático
  • La medición educativa

Sus antecedentes:

  • Para mantener la integridad de la puntuación de la prueba, se utilizan formularios de prueba alternativos.
  • La equiparación ajusta las puntuaciones entre las diferentes formas de prueba debido a las variaciones de dificultad.
  • Se aplican métodos de alisado durante la igualación para minimizar los errores de muestreo.

Objetivo del estudio:

  • Automatizar la selección de los valores óptimos de suavizado en la ecuación de ensayo.
  • Evaluar la eficacia del aprendizaje profundo, específicamente las redes neuronales convolucionales (CNN), para esta tarea.
  • Para comparar el rendimiento de una CNN con el juicio de expertos humanos en la elección de parámetros de suavizado.

Principales métodos:

  • Una red neuronal convolucional fue entrenada en parcelas de post-aplanamiento clasificadas por humanos.
  • La CNN entrenada se utilizó para determinar los valores óptimos de suavizado para los datos de pruebas empíricas.
  • Las elecciones de la CNN fueron comparadas con las de expertos humanos.

Principales resultados:

  • El modelo de aprendizaje profundo logró una tasa de acuerdo del 71% con expertos humanos.
  • Esto indica un alto grado de concordancia entre el método automatizado y la selección manual.

Conclusiones:

  • El aprendizaje profundo ofrece un enfoque automatizado viable para seleccionar valores de suavizado óptimos en la ecuación de prueba.
  • Esta automatización tiene el potencial de mejorar la eficiencia y la coherencia del proceso de equiparación.