Author Affiliations
Abstract
1 Engineering Research Centre of Optical Instrument and System, Ministry of Education, Shanghai Key Laboratory of Modern Optical System, University of Shanghai for Science and Technology, Shanghai 200093, China
2 Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 200092, China
3 Sino-England International College, University of Shanghai for Science and Technology, Shanghai 200093, China
This study provides a rapid method for quantification of mineral oil in rapeseed oil using near-infrared spectroscopy. The data were processed by direct orthogonal signal correction (DOSC), successive projections algorithm (SPA), partial least squares, and principal component regression (PCR). Good correlation coefficients (R) of 0.998 and root-mean-squared error (RMSE) of 0.005 were obtained, and the DOSC-SPA-PCR model was identified as the optimal method. A satisfactory accuracy with R and RMSE of prediction by DOSC-SPA-PCR of 0.990 and 0.006, was obtained. The results demonstrate that the proposed methodology is a promising method for the rapid quantitative detection of mineral oil in vegetable oil.
near-infrared spectroscopy mineral oil oil quality control DOSC-SPA-PCR Chinese Optics Letters
2020, 18(4): 043001
Author Affiliations
Abstract
University of Shanghai for Science and Technology, Shanghai 200093, China
A method is presented for one-to-many information encryption transmission by using temporal ghost imaging and code division multiple access. In the encryption transmission process, code division multiple access technologies combine multiple information sources, and the chip sequence corresponding to each set of information is used as the first key. The transmission end loads the transmission information onto a series of temporal random patterns of temporal ghost imaging and transmits it to the receivers. A series of temporal random patterns is the second key. During the decryption, each receiver can get the same encrypted information and use the second key to obtain the transmitted information. Finally, each receiver uses the unique chip sequence to get corresponding information. This encryption transmission method realizes one-to-many information encryption transmission at the same time over the same channel. Double encryption ensures the security of information. Simulation and experiment results verify the effectiveness and security of the method. The method has strong antinoise ability and can effectively resist various attack modes. At the same time, this method solves the problem that the use of code division multiple access enlarges the signal bandwidth, and ensures that no cross talk occurs between various sources of information.
Photonics Research
2019, 7(12): 12001370
1 上海理工大学 光电信息与计算机工程学院, 上海 200093
2 上海理工大学 医疗器械与食品学院, 上海 200093
高光谱成像(HSI)检测技术在农业生产检测、地质勘探以及城市规划等方面已经得到了广泛的应用。随着高光谱技术的不断发展,基于反射式高光谱成像效应,在可见光到近红外波段(400~1 100 nm),对人体组织的实时、快速和精准的非损伤检测技术也已经成为医学领域的一个重点研究方向。简要回顾了高光谱技术在医学方面的发展现状以及不同的高光谱技术在人体组织检测方面的对比,综述了反射式高光谱技术在不同人体组织检测方面的应用和成果,包括皮肤水肿、舌肿瘤以及肺癌等方面的研究进展,并提出了高光谱技术在医学领域亟待解决的问题。
反射式高光谱 可见光 近红外光 人体组织检测 reflection hyperspectra visible light near infrared light human tissue detection
上海理工大学, 教育部光学仪器与系统工程中心, 上海市现代光学系统重点实验室, 上海 200093
以喷洒不同浓度杜邦万灵的香梨作为研究对象, 探讨了应用高光谱成像技术检测香梨表面农药残留的方法。运用376~1051nm高光谱成像系统采集200个香梨的高光谱图像, 其中120个香梨为建模集, 80个香梨为预测集。运用多元散射校正(MSC)对光谱数据进行预处理, 然后采用连续投影算法(SPA)提取了11个特征波长。基于处理后的光谱数据, 分别运用多元线性回归法(MLR)和主成分回归法(PCR)两种算法分别建立农药残留检测的模型, 比较两种模型的结果。通过比较, 采用MLR建立的农药残留检测模型效果较优, 其校正集相关系数(Rc)为0.973, 校正均方根误差(RMSEC)为0.260, 预测的正确率可以达到91.7%, 对较低浓度残留的预测正确率达到80%。研究表明, 应用高光谱成像技术可以成功地检测香梨表面农药残留, 并且对低浓度检测也有很好的效果。
光谱学 农药残留 低浓度 高光谱成像 可见-近红外 无损 连续投影算法 香梨 spectroscopy pesticide residue low concentration hyperspectral imaging visible-near infrared non-destructive SPA pears
1 上海理工大学上海市现代光学系统重点实验室, 上海 200093
2 上海理工大学教育部光学仪器与系统工程中心, 上海 200093
为无损检测辣椒粉中苏丹红一号浓度 (C), 本文运用高光谱成像检测技术得到 120个含有不同 C的辣椒粉高光谱图像, 其中 60个作为校正集剩余为预测集, 采用连续投影算法(SPA)从校正集的海量光谱数据中优选出 45个特征波长, 再通过偏最小二乘回归法 (PLSR)、多元线性回归法 (MLR)和主成分回归法 (PCR)建立预测模型。结果表明, MLR模型较优, 其校正集相关系数为 0.998, 校正均方根误差为 0.737 3 μg/ml, 预测集相关系数为 0.987, 预测均方根误差为 1.921 3 μg/ml, 该方法可以实现辣椒粉中 C的无损检测。
高光谱成像技术 无损检测 辣椒粉 苏丹红一号浓度 hyper-spectral imaging technique non-destructive detection chili powders concentration of Sudan red No. 1
