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Issues And Trends In Healthcare Delivery System01:29

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
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Introduction to Learning01:18

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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.
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Associative Learning01:27

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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.
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Avoidance learning and learned helplessness are critical concepts in understanding behavioral responses to negative stimuli.
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E. C. Tolman emphasized the purposiveness of behavior — the idea that much of our behavior is goal-directed. For instance, employees who aim for a promotion work diligently to meet their targets. Tolman argued that when classical conditioning and operant conditioning occur, the organism acquires certain expectations. In classical conditioning, a child might fear a dog because they expect it to bite. In operant conditioning, a person might consistently work overtime because they expect a...
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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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基于区块链的框架,用于生成和管理无法学习的例子,以加强数据隐私和访问控制.

Ruijia Li1, Zijiao Zhang2, Shouli Fu1

  • 1School of Cyberspace Security, Zhengzhou University.

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概括
此摘要是机器生成的。

本研究引入了使用区块链和不可学习的例子 (UE) 的新框架,以保护大型语言模型 (LLM) 培训中使用的敏感数据. 这种方法增强了数据隐私,防止未经授权的滥用和反向攻击.

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科学领域:

  • 人工智能的人工智能
  • 网络安全 网络安全
  • 数据科学数据科学数据科学

背景情况:

  • 大型语言模型 (LLM) 在庞大的数据集上使用对比学习,引发了数据隐私方面的担忧.
  • 无法学习的例子 (UE) 通过破坏模型训练来保护敏感数据,但面临诸如扰乱逆转和数据可追溯性等挑战.

研究的目的:

  • 为强大的数据隐私提出一个区块链集成的不可学习的示例生成和管理框架 (B-UEGMF).
  • 解决现有的UE生成方法在可逆性和数据管理方面的局限性.

主要方法:

  • 开发了一个区块链集成的不可学习的示例生成和管理框架 (B-UEGMF).
  • 利用区块链进行不变的存储,例如哈希值和用于动态访问控制的智能合约.
  • 使用动态误差最小化噪声 (DEM),一种多目标扰动技术生成的UE.

主要成果:

  • B-UEGMF框架表现出针对扰乱逆转攻击的增强强性.
  • 定量评估证实了生成的UE的改善隐私保护能力.
  • 该框架确保有效的数据隐私管理和可追溯性.

结论:

  • 拟议的B-UEGMF有效地保护敏感数据免受未经授权的访问和滥用在LLM培训中.
  • 区块链集成提供了一个安全和透明的机制来管理无法学习的例子.
  • DEM技术显著提高了UE对复杂的逆转方法的弹性.