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相关概念视频

Frustration and Conflict: Approach-Approach, Approach-Avoidance01:20

Frustration and Conflict: Approach-Approach, Approach-Avoidance

528
Frustration occurs when people are obstructed or prevented from achieving a desired goal or fulfilling a perceived need. For example, when someone's input is ignored in a discussion, it can lead to feelings of frustration. Conflict, however, arises from opposing interests, goals, or actions. Conflicts can take various forms based on the nature of these opposing desires or goals.
One common type of conflict is the Approach–Approach Conflict. In this case, a person faces two desirable...
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Structures of Solids02:22

Structures of Solids

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Solids in which the atoms, ions, or molecules are arranged in a definite repeating pattern are known as crystalline solids. Metals and ionic compounds typically form ordered, crystalline solids. A crystalline solid has a precise melting temperature because each atom or molecule of the same type is held in place with the same forces or energy. Amorphous solids or non-crystalline solids (or, sometimes, glasses) which lack an ordered internal structure and are randomly arranged. Substances that...
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Structural Isomerism02:34

Structural Isomerism

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Isomerism in Complexes
Isomers are different chemical species that have the same chemical formula. Structural isomerism of coordination compounds can be divided into two subcategories, the linkage isomers and coordination-sphere isomers.
Linkage isomers occur when the coordination compound contains a ligand that can bind to the transition metal center through two different atoms. For example, the CN− ligand can bind through the carbon atom or through the nitrogen atom. Similarly, SCN− can...
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Structure of Lipids03:38

Structure of Lipids

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Lipids include a diverse group of compounds that are largely nonpolar in nature. This is because they are hydrocarbons that include mostly nonpolar carbon-carbon or carbon-hydrogen bonds. Non-polar molecules are hydrophobic (“water fearing”), or insoluble in water. Lipids perform many different functions in a cell. Cells store energy for long-term use in the form of fats. Lipids also provide insulation from the environment for plants and animals. For example, they help keep aquatic...
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Viral Structure00:56

Viral Structure

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Viruses are extraordinarily diverse in shape and size, but they all have several structural features in common. All viruses have a core that contains a DNA- or RNA-based genome. The core is surrounded by a protective coat of proteins called the capsid. The capsid is composed of subunits called capsomeres. The capsid and genome-containing core are together known as the nucleocapsid.
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Antibody Structure01:10

Antibody Structure

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Overview
Antibodies, also known as immunoglobulins (Ig), are essential players of the adaptive immune system. These antigen-binding proteins are produced by B cells and make up 20 percent of the total blood plasma by weight. In mammals, antibodies fall into five different classes, which each elicits a different biological response upon antigen binding.
The Y-Shaped Structure of Antibodies Consists of Four Polypeptide Chains
Antibodies consist of four polypeptide chains: two identical heavy...
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相关实验视频

Updated: Jan 31, 2026

A Structured Approach to Extubation in Mechanically Ventilated Rats
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构建隐私政策:一种人工智能方法

Shani Alkoby1, Ron S Hirschprung1

  • 1Faculty of Engineering, Industrial Engineering and Management, Ariel University, Ariel, Israel.

Frontiers in artificial intelligence
|January 30, 2026
PubMed
概括
此摘要是机器生成的。

本研究介绍了一种人工智能驱动的方法,可以自动构建非结构化的隐私政策,使人们和人工智能更容易理解它们. 这种方法通过克服复杂的法律语言和文件更改的挑战来加强隐私控制.

关键词:
人工智能的人工智能是人工智能.人与计算机的互动机器学习是机器学习.政策 政策 政策 政策隐私 隐私 隐私 隐私 隐私 隐私

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科学领域:

  • 计算机科学 计算机科学
  • 信息科学 信息科学 信息科学
  • 法律信息学 法律信息学

背景情况:

  • 隐私政策是法律规定的,但由于复杂的语言和频繁的更新,用户难以理解.
  • 现有的方法很难有效地处理和结构化隐私政策的自由文本性质.
  • 隐私法规与用户访问和利用隐私政策信息的能力之间存在差距.

研究的目的:

  • 开发一种新的方法来自动将非结构化的隐私政策文本结构化为预定义的参数.
  • 提高用户对隐私政策信息的理解和可访问性.
  • 弥合隐私法规与实际用户利益之间的差距.

主要方法:

  • 一个双层人工智能 (AI) 过程被设计为接收和结构隐私政策文本.
  • 该方法专注于克服诸如认知负担和文档动态等挑战.
  • 人工智能方法旨在标准化隐私信息的呈现.

主要成果:

  • 一项实证研究评估了49个实际的隐私政策.
  • 该方法实现了平均F1得分大于0.8.8.
  • 在6个预定义参数中,有5个参数显示了非常高的分类准确性.

结论:

  • 拟议的人工智能方法有效地对隐私政策进行结构化,使其更容易获得.
  • 这种方法通过简化复杂的信息,有利于人类用户和人工智能代理.
  • 这项研究解决了在数字时代改善隐私政策可用性的关键需求.