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相关概念视频

Infrared (IR) Spectroscopy: Overview01:09

Infrared (IR) Spectroscopy: Overview

1.5K
When electromagnetic radiation passes through a material, atoms or molecules transition from a lower to a higher energy state by absorbing radiation corresponding to the energy difference between the two states. The absorption of infrared (IR) radiation causes transitions between vibrational energy levels in a molecule. Therefore, IR spectroscopy is a useful analytical tool for determining the molecular structure of molecules.
Different compounds display unique properties due to their...
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Applications of IR Spectroscopy: Overview01:11

Applications of IR Spectroscopy: Overview

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The non-destructive nature and ability to provide valuable chemical information make IR spectroscopy a versatile technique with broad applications in various scientific and industrial fields. IR spectroscopy is commonly used to identify and characterize organic and inorganic compounds. It provides information about the functional groups present in a molecule and the bonding between atoms. This helps in the structural elucidation of compounds during organic synthesis, pharmaceutical research,...
493
IR Spectrometers01:25

IR Spectrometers

1.1K
There are two main infrared (IR) spectrophotometers: dispersive IR spectrometers and Fourier transform infrared (FTIR) spectrometers. In a dispersive IR spectrometer, a beam of infrared radiation produced by a hot wire is divided into two parallel equal-intensity beams using mirrors. One beam passes through the sample, while another is a reference beam. The beams then move through the monochromator, which separates the radiations into a continuous spectrum of different frequencies. The...
1.1K
IR Spectrum01:19

IR Spectrum

936
When infrared (IR) radiation passes through a molecule, the bonds stretch or bend by absorbing the radiation. This absorption creates the molecule's absorption spectrum, which is the plot of its percentage transmittance versus wavenumber.
Transmittance is defined as the ratio of the radiant power passing through a sample to that from the radiation's source. Multiplying the transmittance by 100 gives the percent transmittance (%T), which varies between 100% (no absorption) and 0%...
936
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

766
IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
766
Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview01:13

Attenuated Total Reflectance (ATR) Infrared Spectroscopy: Overview

291
Attenuated total reflectance (ATR) infrared spectroscopy is a powerful analytical technique used to study the composition of materials. It is widely employed in chemistry, materials science, forensic science, and other fields where sample characterization is required. ATR has several advantages over traditional transmission IR spectroscopy, including the requirement of little to no sample preparation and the ability to analyze a wide range of samples.
The ATR process begins by directing a beam...
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相关实验视频

Updated: Jun 8, 2025

O-cresol Concentration Online Measurement Based On Near Infrared Spectroscopy Via Partial Least Square Regression
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评估机器学习和可变选择方法的性能,以识别使用红外光谱数据识别文档纸张.

Yong Ju Lee1, Soon Wan Kweon1, Chang Woo Jeong2

  • 1Department of Forest Products and Biotechnology, Kookmin University, 77 Jeongneung-ro, Seongbuk-gu, Seoul 02707 Republic of Korea.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
|November 3, 2024
PubMed
概括

机器学习模型使用红外光谱学准确识别文档纸制造商. 这种法医技术通过快速,非破坏性测试和降低计算成本来增强文档分析.

关键词:
功能重要性 功能重要性输送前传神经网络 (FNN) 是一个前传神经网络.被质疑的文件是有问题的文件.随机森林 (RF) 是一个随机的森林.支持矢量机器 (SVM) 是一个支持矢量机器.

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科学领域:

  • 法医科学 法医科学 法医科学
  • 分析化学 分析化学
  • 机器学习 机器学习

背景情况:

  • 红外 (IR) 光谱技术提供了对法医检查至关重要的非破坏性和快速分析.
  • 机器学习 (ML) 和化学测量越来越多地应用于法医科学,包括质疑的文档检查.
  • 识别文档纸制造商对于法医调查至关重要.

研究的目的:

  • 开发和评估ML模型,使用IR光谱数据识别文档纸制造商.
  • 确定特定的IR频谱区域在模型培训中的有效性.
  • 评估不同ML算法的性能和计算效率.

主要方法:

  • 从文档纸样本收集红外 (IR) 光谱数据.
  • 支持矢量机器 (SVM),前神经网络 (FNN) 和随机森林 (RF) 模型被构建.
  • 来自射频模型的重要变量指导了红外光谱区域的选择 (1500-800 cm-1).
  • 模型被训练并使用在所选范围内的二导IR光谱进行评估.

主要成果:

  • FNN和RF模型实现了高性能,F1分数分别为0.978和1.000.
  • 选择特定的IR光谱区域显著提高了模型性能.
  • 选择的光谱范围将计算成本降至最低,同时保持高精度.
  • 这些模型在识别文档纸制造商方面表现出了可靠性.

结论:

  • 机器学习方法,特别是FNN和RF,对于法医文档分析非常有效.
  • 优化光谱数据选择可以提高法医应用中的ML模型性能和效率.
  • 这种方法为识别文档纸张来源提供了一种强大且计算成本低廉的工具.