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ABSTRACT In soybeans from different years, the infrared spectroscopy waveforms exhibit similarities, yet variations in aging time lead to significant differences in their fatty acid content. To rapidly discern the year of soybean production, this study employed ten feature extraction algorithms in conjunction with Convolutional Neural Networks (CNN) to establish models for classifying soybeans from different years (2019, 2020, and 2021). The research findings reveal the following: (1) The CNN models, after feature extraction, all demonstrated improved accuracy. Notably, the optimal models for both powdered and granulated states were the Kpca-CNN models, achieving an accuracy of 100%. The corresponding loss function values were 0.0002 and 0.0007, with processing times of 0.19 seconds and 0.20 seconds, respectively. (2) The modeling results of all models suggest that the classification accuracy of soybean powder spectral data is higher compared to soybean particle spectral data. (3) Validation of the optimal Kpca-CNN model confirmed its consistent accuracy of 100% when introducing new data or reducing the size of the training dataset. In conclusion, the fusion of near-infrared spectroscopy analysis and CNN technology is considered an effective method for classifying soybeans from different years. This method provides a practical solution for the rapid and precise determination of seed production years.

El presente trabajo constituye un análisis desde una perspectiva subléxica de la polisemia de expresiones que contienen el verbo 爱(ài) ‘amar’ en chino, como爱儿子(ài érzǐ) ‘amar al hijo’, 爱眼睛(ài yǎnjīng) ‘cuidar los ojos’, 爱土豆(ài tǔdòu) ‘gustar comer patatas’, 爱员 工(ài yuángōng) ‘apreciar a los empleados’, 爱豪车(ài háochē) ‘desear tener coche lujoso’ o 爱国 守法(ài guó shǒu fǎ) ‘respetar el país y las leyes’. La hipótesis que subyace a este trabajo se inscribe en el modelo de la Teoría del Lexicón Generativo (Pustejovsky, 1995) y defiende que el verbo psicológico del chino 爱(ài) ‘amar’ cuenta con un significado mínimo o definición infraespecificada (‘sentir una emoción agradable e intensa’) que se extiende o materializa en distintos significados en función de la concordancia léxica entre el contenido del verbo y las informaciones contenidas en forma de rasgos semánticos en sus complementos. Los procesos de concordancia léxica que legitiman las distintas acepciones del verbo son lo que se conoce como mecanismos generativos, en términos de la TLG, cuya operación vamos a analizar.

There is as much abundance of archaeological heritage in East Asia as there is diversity in the methodology for its reconstruction and representation. The Re-relic program in China recognizes the uniqueness of archaeological heritage in East Asia and has developed a tailored virtual reconstruction methodology that is both scientifically robust and popular for public interpretation. The theoretical consideration and field experience over the years shall contribute to the global understanding of the value and technique in virtual reconstruction, while testifying to the very principles of Seville Charter.