论文标题
部分可观测时空混沌系统的无模型预测
A reconfigurable integrated electronic tongue and its use in accelerated analysis of juices and wines
论文作者
论文摘要
电位计算电子舌（ETS）杠杆化趋势和物联网（IoT）的趋势（IoT）对复杂多组分液体（例如饮料）的轻松移动化学分析有望。在这项工作中，将一系列低型微型聚合物传感器阵列的瞬态电位计量响应从瞬态电位计量响应中提取与数据管道结合使用，以在云后端或边缘设备上部署训练有素的机器学习模型。传感器阵列表现出对不同有机酸的敏感性，并表现出有趣的表现，可以表现出果汁和葡萄酒的指纹，包括通过有感觉描述符和预测老化果汁样品的消费者可接受性的样品来区分样品。产品身份验证，质量控制和感官评估的支持是一些预期的应用，这些应用将受益于综合电子舌，从而有助于表征多组分液体的复杂性能。
Potentiometric electronic tongues (ETs) leveraging trends in miniaturization and internet of things (IoT) bear promise for facile mobile chemical analysis of complex multicomponent liquids, such as beverages. In this work, hand-crafted feature extraction from the transient potentiometric response of an array of low-selective miniaturized polymeric sensors is combined with a data pipeline for deployment of trained machine learning models on a cloud back-end or edge device. The sensor array demonstrated sensitivity to different organic acids and exhibited interesting performance for the fingerprinting of fruit juices and wines, including differentiation of samples through supervised learning based on sensory descriptors and prediction of consumer acceptability of aged juice samples. Product authentication, quality control and support of sensory evaluation are some of the applications that are expected to benefit from integrated electronic tongues that facilitate the characterization of complex properties of multi-component liquids.
