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相关概念视频

Associative Learning01:27

Associative Learning

579
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...
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Cognitive Learning01:21

Cognitive Learning

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Cognitive learning is based on purposive behavior, incidental learning, and insight learning.
E. C. Tolman's theory of purposive behavior emphasizes that much behavior is goal-directed. He argued that to understand behavior, we must look at the entire sequence of actions leading to a goal. For instance, high school students study hard, not just due to past reinforcement but also to achieve the goal of getting into a good college.
Tolman introduced the idea that behavior is influenced by...
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Avoidance Learning and Learned Helplessness01:14

Avoidance Learning and Learned Helplessness

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Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
Avoidance learning occurs when an organism learns that a specific behavior can prevent an unpleasant outcome. For example, a student who receives a bad grade may start studying harder to avoid future poor grades. This behavior persists even when the negative outcome is no longer present. Avoidance learning is powerful because it maintains behavior in the absence of the...
1.9K
Observational Learning01:12

Observational Learning

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Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
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Improving Translational Accuracy02:07

Improving Translational Accuracy

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Introduction to Learning01:18

Introduction to Learning

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Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
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相关实验视频

Updated: Sep 14, 2025

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
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DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

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使用XAI转移学习以获得强大的恶意软件和物联网网络安全.

Ahmad Almadhor1, Shtwai Alsubai2, Natalia Kryvinska3

  • 1Department of Computer Engineering and Networks, College of Computer and Information Sciences, Jouf University, Sakaka, 72388, Saudi Arabia.

Scientific reports
|July 24, 2025
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种深度学习模型,用于检测利用隐私的恶意软件,利用转移学习来提高通过内存分析和网络入侵检测来提高网络安全威胁的准确性.

关键词:
深度神经网络是一种深度神经网络.入侵检测系统的入侵检测系统恶意软件攻击是恶意软件的攻击.记忆倾倒分析的分析沙普利添加剂的解释转移学习转移学习

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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

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相关实验视频

Last Updated: Sep 14, 2025

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning
04:17

DNA Virus Detection System Based on RPA-CRISPR/Cas12a-SPM and Deep Learning

Published on: May 10, 2024

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Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

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科学领域:

  • 网络安全 网络安全
  • 机器学习 机器学习
  • 数字法医学数字法医学

背景情况:

  • 越来越多的利用隐私的恶意软件需要先进的检测方法.
  • 模糊技术使得实时恶意软件检测具有挑战性.
  • 传统的法医分析需要复杂的模式识别.

研究的目的:

  • 开发一个深度学习模型来分类隐藏的恶意软件.
  • 通过转移学习提高物联网和网络流量的入侵检测.
  • 提高恶意软件检测模型的透明度和互操作性.

主要方法:

  • 开发了一个在MalwareMemoryDump数据集上训练的深度学习模型.
  • 实施转移学习以适应NF-TON-IoT和UNSW-NB15数据集的模型.
  • 综合可解释的人工智能 (XAI) 为模型透明度.

主要成果:

  • 在MalwareMemoryDump上达到99.9%的准确性,在NF-TON-IoT和UNSW-NB15数据集上达到96%的准确性.
  • 在跨域检测中证明了提高准确性和效率.
  • 通过转移学习来减少培训时间和计算成本.

结论:

  • 拟议的深度学习模型有效地处理各种网络安全威胁.
  • 转移学习显著提高了跨不同领域的恶意软件检测.
  • 该模型提供了一种高效和可通用的方法,其性能优于现有的安全技术.