Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Raman Spectroscopy: Overview01:20

Raman Spectroscopy: Overview

281
The underlying principle of Raman spectroscopy is based on the interaction between light and matter, specifically molecules' inelastic scattering of photons. When a monochromatic beam of light, typically from a laser source, interacts with a sample, most scattered light has the same frequency as the incident light. This is known as Rayleigh scattering.
However, a small fraction of the scattered light exhibits a frequency shift due to the exchange of energy between the incident photons and...
281
Raman Spectroscopy Instrumentation: Overview01:26

Raman Spectroscopy Instrumentation: Overview

256
A conventional Raman spectrophotometer includes a laser source, a sample holding system, a wavelength selector, and a detector.
The monochromatic laser source, typically using visible or near-infrared radiation, generates a highly focused beam of light. This light interacts with the molecules of the sample, scattering some of the light. Liquid and gaseous samples are usually tested in ordinary glass capillaries, while solids can be analyzed as powders packed in capillaries or as potassium...
256
Applications of IR Spectroscopy: Overview01:11

Applications of IR Spectroscopy: Overview

431
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,...
431
Mass Spectrometry: Complex Analysis01:21

Mass Spectrometry: Complex Analysis

660
Mass spectrometry is an important technique for the identification of pure compounds. However, it has some limitations for the analysis of complex mixtures, often due to excessive fragmentation making the spectrum too complicated to decipher. Mass spectrometry can be combined with suitable separation methods in sequence, forming hyphenated methods, which are useful in the analysis of complex mixtures.
GC–MS is a powerful hyphenated method commonly used in forensics and environmental...
660
IR Frequency Region: Fingerprint Region01:03

IR Frequency Region: Fingerprint Region

666
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...
666
NMR Spectroscopy and Mass Spectrometry of Aldehydes and Ketones01:15

NMR Spectroscopy and Mass Spectrometry of Aldehydes and Ketones

3.6K
In aldehydes, the hydrogen atom connected to the carbonyl carbon helps distinguish aldehydes from other carbonyl compounds using ¹H NMR spectroscopy. The closeness of aldehydic hydrogen to the electrophilic carbonyl carbon highly deshields the hydrogen atom causing its signal to appear around 10 ppm in the ¹H NMR spectra. α hydrogens split the aldehydic proton signal, which helps identify the number of α hydrogens in the molecule. For instance, one α hydrogen creates a...
3.6K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Classification of Traditional Handmade Papers from China, Japan, and Korea Using NIR Hyperspectral Imaging.

Molecules (Basel, Switzerland)·2026
Same author

Case Report: Refractory Lupus Intestinal Pseudo-Obstruction Successfully Treated With Obinutuzumab.

International journal of rheumatic diseases·2026
Same author

Allomorphic Transformation of Cellulose for Enhancing Enzymatic Accessibility.

Polymers·2026
Same author

Signal or noise? Apply myositis autoantibody line-blot immunoassays in real-world settings: implications for diagnostic accuracy.

Clinical rheumatology·2026
Same author

The Taiwan College of Rheumatology Consensus for the Management of Systemic Lupus Erythematosus.

International journal of rheumatic diseases·2026
Same author

Controlling the Porous Structure of Cellulose Acetate Derived by Fatty Acid Molecules in Breath-Figure Templating.

ACS omega·2026

相关实验视频

Updated: May 16, 2025

Rejection of Fluorescence Background in Resonance and Spontaneous Raman Microspectroscopy
15:04

Rejection of Fluorescence Background in Resonance and Spontaneous Raman Microspectroscopy

Published on: May 18, 2011

13.1K

拉曼光谱和机器学习用于法医文档检查.

Yong Ju Lee1, Chang Woo Jeong2, Hong Taek Kim3

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

The Analyst
|April 1, 2025
PubMed
概括

拉曼光谱学与机器学习相结合,将文档文件分类为法医分析. 这种方法提高了识别纸张来源的准确性和解释性,这对于欺诈调查至关重要.

更多相关视频

Raman and IR Spectroelectrochemical Methods as Tools to Analyze Conjugated Organic Compounds
09:11

Raman and IR Spectroelectrochemical Methods as Tools to Analyze Conjugated Organic Compounds

Published on: October 12, 2018

18.2K
Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall
07:51

Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall

Published on: June 10, 2017

11.8K

相关实验视频

Last Updated: May 16, 2025

Rejection of Fluorescence Background in Resonance and Spontaneous Raman Microspectroscopy
15:04

Rejection of Fluorescence Background in Resonance and Spontaneous Raman Microspectroscopy

Published on: May 18, 2011

13.1K
Raman and IR Spectroelectrochemical Methods as Tools to Analyze Conjugated Organic Compounds
09:11

Raman and IR Spectroelectrochemical Methods as Tools to Analyze Conjugated Organic Compounds

Published on: October 12, 2018

18.2K
Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall
07:51

Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall

Published on: June 10, 2017

11.8K

科学领域:

  • 法医科学 法医科学 法医科学
  • 分析化学 分析化学
  • 计算机科学 计算机科学

背景情况:

  • 文档纸张分析在法医科学中对于检测伪造和欺诈至关重要.
  • 传统的纸张分类方法可能耗时且主观.
  • 开发客观和有效的纸张差异化方法至关重要.

研究的目的:

  • 用机器学习集成的拉曼光谱学来对文档文件进行分类.
  • 为此分类任务评估不同机器学习模型 (随机森林,SVM,FNN) 的性能.
  • 确定关键的光谱区域和预处理技术,以提高分类准确性.

主要方法:

  • 拉曼光谱法用于从文档文件中获取光谱数据.
  • 机器学习模型,包括随机森林 (RF),支持矢量机器 (SVM) 和前神经网络 (FNN),都被训练在光谱数据上.
  • 频谱数据经过预处理,包括第一个导数转换,并通过专注于200-1650厘米-1范围来减少维度.

主要成果:

  • 随机森林模型在识别重要的光谱特征和区域方面表现出有效性.
  • 第一个衍生谱预处理显著改善了跨模型的分类性能.
  • 送神经网络模型实现了最高的分类准确性,F1得分为0.968.8.
  • 200-1650厘米-1的信息光谱范围减少了输入变量,同时提高了模型的准确性.

结论:

  • 将拉曼光谱与机器学习相结合,为法医文档检查提供了一种可解释,高效和强大的方法.
  • 该研究强调了这种综合方法在准确可靠的纸张分类方面的潜力.
  • 这种技术为法医文档分析提供了有希望的进步,有助于欺诈和伪造调查.