Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News ; Research findings on food safety are d iscussed in a new report. According to newsreporting originating from Qingdao, People’s Republic of China, by NewsRx correspondents, research stated,“In the f ield of food safety testing, variety, brand, origin, and adulteration are four i mportant factors.”Our news reporters obtained a quote from the research from Qingdao Agricultural University: “Inthis study, a novel food safety testing method based on infrared spectroscopy is proposed to investigatethese factors. Fourier transform infrar ed spectroscopy data are analyzed using negentropy-sorted kernelindependent com ponent analysis (NS-kICA) as the feature optimization method. To rank the components, negentropy is performed to measure the non-Gaussian independent components . In our experiment,the proposed method was run on four datasets to comprehensi vely investigate the variety, brand, origin,and adulteration of agricultural pr oducts. The experimental results show that NS-kICA outperformsconventional feat ure selection methods. The support vector machine model outperforms the backpropagation artificial neural network and partial least squares models.”
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