79 resultados para product classification


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Organic food products are highly susceptible to fraud. Currently, administrative controls are conducted to detect fraud, but having an analytical tool able to verify the organic identity of food would be very supportive. The state-of-the-art in food authentication relies on fingerprinting approaches that find characteristic analytical patterns to unequivocally identify authentic products. While wide research on authentication has been conducted for other commodities, the authentication of organic chicken products is still in its infancy. Challenges include finding fingerprints to discriminate organic from conventional products, and recruiting sample sets that cover natural variability. Future research might be oriented towards developing new authentication models for organic feed, eggs and chicken meat, keeping models updated and implementing them into regulations. Meanwhile, these models might be very supportive to the administrative controls directing inspections towards suspicious fraudulent samples.

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Recommender systems attempt to predict items in which a user might be interested, given some information about the user's and items' profiles. Most existing recommender systems use content-based or collaborative filtering methods or hybrid methods that combine both techniques (see the sidebar for more details). We created Informed Recommender to address the problem of using consumer opinion about products, expressed online in free-form text, to generate product recommendations. Informed recommender uses prioritized consumer product reviews to make recommendations. Using text-mining techniques, it maps each piece of each review comment automatically into an ontology

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This paper deals with the product design, engineering, and material selection intended for the manufacturing of an eco-friendly chair. The final product is expected to combine design attributes with technical and legal feasibility with the implementation of new bio-based materials. Considering the industrial design, a range of objectives and trends were determined after setting the market requirements, and the final concept was proposed and modeled. The product geometry, production technology, and legal specifications were the input data for product engineering. The material selection was based on the technical requirements. Polypropylene (PP) composite materials based on coupled-fiberglass, sized-fiberglass, and coupled-stone ground wood reinforcements were prepared and characterized. Final formulations based on these PP composites are proposed and justified

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Identification of clouds from satellite images is now a routine task. Observation of clouds from the ground, however, is still needed to acquire a complete description of cloud conditions. Among the standard meteorologicalvariables, solar radiation is the most affected by cloud cover. In this note, a method for using global and diffuse solar radiation data to classify sky conditions into several classes is suggested. A classical maximum-likelihood method is applied for clustering data. The method is applied to a series of four years of solar radiation data and human cloud observations at a site in Catalonia, Spain. With these data, the accuracy of the solar radiation method as compared with human observations is 45% when nine classes of sky conditions are to be distinguished, and it grows significantly to almost 60% when samples are classified in only five different classes. Most errors are explained by limitations in the database; therefore, further work is under way with a more suitable database