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We propose herein an algorithm to resample the Raman spectra which aims to correct the predicted error induced by spectral shift. The same set of training data for both human and nonhuman blood Raman spectra was applied to build the model using partial least squares (PLS) method. Several kinds of Raman spectra of the blood samples originating from human, goose, monkey, chicken, sheep and duck without spectral shift were used to validate the model. The Raman spectra of the same blood samples with a shift of 9.18 cm-1 were used to illustrate the influence of the spectral shift to the model. To demonstrate the effectiveness of the algorithm proposed, Raman spectra with spectral shift were resampled. The results show that the resampling algorithm can improve both the stability and accuracy of the model and reduce the impact of the spectral shift, which is promising for quantitative or qualitative analysis in Raman spectroscopy for complex samples. [ABSTRACT FROM AUTHOR]

This paper presents an online method for calculating the glucose concentration based on laser ranging and radio frequency identification (RFID). We derive a theoretical formula on the reading distance and received signal backscattering power of the RFID tag attached to the surface of glucose solution. Subsequently, the former measurement values are converted to the corresponding glucose concentration. Finally, a fitted model of the relationship of glucose concentration, reading distances and received power is established. The experimental data are compliant to the theoretical counterparts. This online method could be applied to dynamic measurement in automatic assembly line and has the advantages of excellent versatility, high measuring accuracy, stable performance and quick response speed. [ABSTRACT FROM AUTHOR]

Dynamic performance parameters of multiple tags in radio frequency identification (RFID) system include reading efficiency, reading distance, and so on. The reading performance of multiple tags could be hardly satisfied due to existing algorithms, so the geometric distribution of multiple tags is arranged reasonably to improve the reading performance of RFID system in this paper. An online detection system based on laser ranging is designed to measure the reading distance and extract the location of RFID tags. Simultaneously, a support vector machine (SVM) is used to analyse and predict the reading distance of RFID tags under various geometric distributions. The results show that the optimal geometric distribution of tags could be obtained by analysing the predicted reading distance of tags. This method could improve the dynamic performance of multiple tags and reduce the corresponding reading error in RFID system effectively. [ABSTRACT FROM AUTHOR]

According to the function of self-diagnosis and self-healing for smart composite structures health monitoring system, this paper proposed a smart structure based on liquid core optical fibre (LCOF) sensor network. A model of loads recognition algorithm based on particle swarm optimization-support vector regression (PSO-SVR) is presented to achieve the self-diagnosis of the LCOF sensor system. Furthermore, the loading experiments were conducted on the E-51 composite structures plate embedded with eight liquid core fibre sensors. The relationship between the changes of light intensity in fibre sensor and loads positions was researched on. The support vector regression (SVR) model was established using sample data to predict loads position. And the parameters were optimized by particle swarm optimization (PSO) algorithm. And the test error is 0.245%. The study showed that this method can effectively determine the loads positions with small size training sample. It realized the self-diagnosis system for liquid core fibre sensors and it provides a foundation for the future research on the self-repairing for smart composite structures. [ABSTRACT FROM AUTHOR]