Study on the Determination of Flavor Value of Rice Based on Grid Iterative Search Swarm Optimization Support Vector Machine Model and Hyperspectral Imaging.

In the field of rice processing and cultivation, it is crucial to adopt efficient, rapid and user-friendly techniques to detect the flavor values of various rice varieties. The conventional methods for flavor value assessment mainly rely on chemical analysis and technical evaluation, which not only deplete the rice resources but also incur significant time and labor costs. In this study, hyperspectral imaging technology was utilized in combination with an improved Particle Swarm Optimization Support Vector Machine (PSO-SVM) algorithm, i.e., the Grid Iterative Search Particle Swarm Optimization Support Vector Machine (GISPSO-SVM) algorithm, introducing a new non-destructive technique to determine the flavor value of rice. The method captures the hyperspectral feature data of different rice varieties through image acquisition, preprocessing and feature extraction, and then uses these features to train a model using an optimized machine learning algorithm. The results show that the introduction of GIS algorithms in a PSO-optimized SVM is very effective and can improve the parameter finding ability. In terms of flavor value prediction accuracy, the Principal Component Analysis (PCA) combined with the GISPSO-SVM algorithm achieved 96% accuracy, which was higher than the 93% of the Competitive Adaptive Weighted Sampling (CARS) algorithm. And the introduction of the GIS algorithm in different feature selection can improve the accuracy to different degrees. This novel approach helps to evaluate the flavor values of new rice varieties non-destructively and provides a new perspective for future rice flavor value detection methods.

Method of 3D Coating Accumulation Modeling Based on Inclined Spraying.

In the process of repairing the surface of products in aviation, aerospace, and other fields by spraying, accurate 3D cumulative-coating modeling is an important research issue in spraying-process simulation. The approach to this issue is a 3D cumulative-coating model based on inclined spraying. Firstly, an oblique spraying layer cumulative model was established, which could quickly collect the coating thickness distribution data of different spray distances. Secondly, 3D cumulative-coating modeling was conducted with the distance between the measuring point and the axis of the spray gun and the spraying distance between the measuring points as the input parameters, and the coating thickness of the measuring point as the output parameter. The experimental results show that the mean relative error of the cumulative model of the oblique spraying layer is less than 4.1% in the case of a 170~290 mm spraying distance and that the model is applicable in the range of -80~80 mm, indicating that the data on the oblique spraying coating proposed in this paper is accurate and fast. The accuracy of the 3D cumulative-coating model proposed in this paper is 1.2% and 21.5% higher than that of the two similar models, respectively. Therefore, the approach of 3D cumulative-coating modeling based on inclined distance spraying is discovered, demonstrating the advantages of fast and accurate modeling and enabling accurate 3D cumulative-coating modeling for spraying process simulation.

Polymer-grafted nanoparticles prepared by surface-initiated polymerization: the characterization of polymer chain conformation, grafting density and polydispersity correlated to the grafting surface curvature.

The polymer-grafted nanoparticles prepared by the surface-initiated polymerization induced from the spherical surface is studied by coarse-grained molecular dynamics simulations combined with the stochastic reaction model. The coupling effect of the initiator density and the grafting surface curvature is mainly investigated. The confinement degree greatly changes with the grafting surface curvature, thus the initiation efficiency, the grafted chain polydispersity, as well as the chain mass distribution show great dependence on the surface curvature. The results reveal that preparing the nanoparticle with desired size (i.e., grafting surface curvature) is crucial for control of the grafted chain polydispersity and even its dispersion in the polymer matrix. Our studies shed light on better design of grafted nanoparticles and better control of dispersion in polymer matrices for improving the performance of polymer nanocomposite materials.