Jove
Visualize
联系我们

相关概念视频

Classification of Systems-II01:31

Classification of Systems-II

149
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
149
Classification of Systems-I01:26

Classification of Systems-I

188
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
188
Combination Therapies and Personalized Medicine02:50

Combination Therapies and Personalized Medicine

4.9K
Combining two or more treatment methods increases the life span of cancer patients while reducing damage to vital organs or tissue from the overuse of a single treatment. Combination therapy also targets different cancer-inducing pathways, thus reducing the chances of developing resistance to treatment.
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
4.9K
Associative Learning01:27

Associative Learning

399
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
399
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

106
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
106
Response Surface Methodology01:16

Response Surface Methodology

137
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
137

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Low-dose computed tomography image denoising using pixel level non-local self-similarity prior with non-local means for healthcare informatics.

Scientific reports·2025
Same author

SnowPole Detection: A comprehensive dataset for detection and localization using LiDAR imaging in Nordic winter conditions.

Data in brief·2025
Same author

A novel approach to brain tumor detection using K-Means++, SGLDM, ResNet50, and synthetic data augmentation.

Frontiers in physiology·2024
Same author

Effective image fusion strategies in scientific signal processing disciplines: Application to cancer and carcinoma treatment planning.

PloS one·2024
Same author

ProTect: a hybrid deep learning model for proactive detection of cyberbullying on social media.

Frontiers in artificial intelligence·2024
Same author

Evaluation of platelet indices as markers of tuberculosis among children in India.

ERJ open research·2024
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关实验视频

Updated: Jul 8, 2025

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
10:43

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

5.4K

基于个性化的深度混合型电子学习模型,用于在线课程推系统.

Subha S1, Baghavathi Priya Sankaralingam2, Anitha Gurusamy2

  • 1Department of Computer Science and Engineering, Rajalakshmi Institute of Technology, Chennai, Tamil Nadu, India.

PeerJ. Computer science
|December 11, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种混合深度学习 (HDL) 模型,用于在线学习平台推课程. 该系统使用人工智能来帮助学生做出明智的课程选择,减少手工干预的需要.

关键词:
卷积神经网络是一种卷积神经网络.深度学习是一种深度学习.电子学习 (e-learning) 是一个电子学习系统.混合型深度学习模型.长期短期记忆 长期短期记忆推系统是推系统.这就是ResNet ResNet.

更多相关视频

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

3.8K
Mixed Reality for Education MRE Implementation and Results in Online Classes for Engineering
04:12

Mixed Reality for Education MRE Implementation and Results in Online Classes for Engineering

Published on: June 23, 2023

677

相关实验视频

Last Updated: Jul 8, 2025

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes
10:43

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Published on: June 10, 2021

5.4K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

3.8K
Mixed Reality for Education MRE Implementation and Results in Online Classes for Engineering
04:12

Mixed Reality for Education MRE Implementation and Results in Online Classes for Engineering

Published on: June 23, 2023

677

科学领域:

  • 人工智能的人工智能
  • 机器学习 机器学习
  • 教育技术的教育技术

背景情况:

  • 在线学习平台需要有效的课程选择,以获得学生的成功.
  • 传统方法往往缺乏个性化的建议,导致课程入学率低于最佳水平.
  • 深度学习为复杂的分析任务提供自动化解决方案.

研究的目的:

  • 为在线学习平台的课程推系统开发混合深度学习 (HDL) 模型.
  • 通过明智的建议,提高学生在课程选择中的决策能力.
  • 通过预测学生课程偏好,为大学提供最佳课程安排.

主要方法:

  • 开发了一个混合深度学习 (HDL) 框架,集成卷积神经网络 (CNN),残余网络 (ResNet) 和长短期记忆 (LSTM).
  • 该模型分析学生数据,以预测未来课程的兴趣.
  • 基于这种混合框架,设计了一个推系统.

主要成果:

  • 拟议的HDL模型有效地向学生推适当的课程.
  • 该系统鼓励对课程选择进行知情决策.
  • 它帮助学习者做出正确的学习选择.

结论:

  • 开发的混合深度学习推系统改善了在线学习中的课程选择过程.
  • 这种方法既有助于学生选择课程,也有助于安排大学.
  • 整合CNN,ResNet和LSTM为教育推系统提供了一个强大的解决方案.