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相关概念视频

Classification of Systems-II01:31

Classification of Systems-II

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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,
410

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Updated: Dec 11, 2025

Demonstration of the Sequence Alignment to Predict Across Species Susceptibility Tool for Rapid Assessment of Protein Conservation
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一个机器学习驱动的自动化系统,用于安全数据表的索引.

Aatish Suman1, Misbah Khan2, Veeru Talreja2

  • 1Velocity EHS Inc, Chicago, IL, 60654, USA. asuman@ehs.com.

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|February 22, 2024
PubMed
概括
此摘要是机器生成的。

自动化安全数据表 (SDS) 索引提取关键的化学成分数据. 这种新系统有效地识别了SDS文档中的成分名称,CAS号和百分比,从而减少了人工工作.

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科学领域:

  • 化学安全与管理
  • 数据科学和机器学习
  • 环境健康与安全 (EHS)

背景情况:

  • 安全数据表 (SDS) 对化学品管理,EHS和ESG合规性至关重要.
  • 手动的SDS索引是劳动密集型,昂贵和耗时的.
  • 从SDS中进行结构化数据提取对于有效的信息检索至关重要.

研究的目的:

  • 开发一个自动化系统,从SDS文档中索引关键信息.
  • 为了提取成分名称,化学摘要服务 (CAS) 号码和重量百分比.
  • 用一种高效的,自动化的解决方案取代传统的手动SDS索引.

主要方法:

  • 一种结合机器学习模型和基于规则的系统的多阶段组合方法.
  • 输入:以PDF格式的SDS文件.
  • 输出:成分名称,CAS号和重量百分比的表格数据.

主要成果:

  • 自动化系统成功地从SDS中索引了成分信息.
  • 实现了 0.93.9 的文档级精度.
  • 在一组数据中验证了20,000份注释的SDS文件.

结论:

  • 开发的自动化系统为SDS索引提供了一种高效和准确的方法.
  • 这种方法显著改善了化学成分数据的提取.
  • 该系统支持增强化学品管理,EHS和ESG实践.