Abstract: A method for feature extraction and data prediction based on pre-training, includes building a first neural network, inputting first processed data to the first neural network to perform a first training operation to generate a first trained neural network, inputting second processed data to the first trained neural network and fixing a first portion of neurons of the first trained neural network to perform a second training operation to generate a second trained neural network, and inputting third processed data to the second trained neural network to generate a predicted result. A first portion of neurons of the second trained neural network is the same as the first portion of neurons of the first trained neural network.

Abstract: A method for predicting operational indicators includes performing a training operation according to first data to train a demand model, inputting second data into the demand model to generate predicted demand data, collecting actual demand data, and performing an adjustment operation according to the predicted demand data and the actual demand data to update the demand model.

Abstract: A method for allocating perishable products based on machine learning, includes using a sales estimation model to evaluate estimated sales of a plurality of perishable products in a predetermined period, using a rating model to calculate a predetermined rate of the plurality of perishable products in the predetermined period according to the estimated sales, using an allocation model to adjust an allocation ratio of the plurality of perishable products in a plurality of marketing channels according to the estimated sales and the predetermined rate if a current rate is lower than the predetermined rate, and determining the numbers of perishable products allocated to the plurality of marketing channels according to the allocation ratio.

Abstract: A rate adjustment method includes a rate estimation model generating a plurality of estimated rates according to a plurality of training data, a revenue estimation model generating an estimated revenue according to the plurality of estimated rates, updating the rate estimation model according to the estimated revenue to generate an updated rate estimation model, and inputting a plurality of current data into the updated rate estimation model to update the plurality of estimated rates.

Abstract: Manufacturing of a shoe or a portion of a shoe is enhanced by executing various shoe-manufacturing processes in an automated fashion. For example, information describing a shoe part may be determined, such as an identification, an orientation, a color, a surface topography, an alignment, a size, etc. Based on the information describing the shoe part, automated shoe-manufacturing apparatuses may be instructed to apply various shoe-manufacturing processes to the shoe part, such as a pickup and placement of the shoe part with a pickup tool.

Abstract: The invention discloses an interpenetrating biopolymers network (IPN) hydrogel loaded with herbal extracts, preparation and application thereof. The IPN hydrogel can increase the preservation time of herbal extracts and achieve a long-term release mechanism of herbal extracts. The interpenetrating biopolymers network (IPN) hydrogel makes itself have microporous and macroporous network structure and reinforced gel structure. The gel itself has good hydrophilicity and high biocompatibility. In addition, the present invention will be subsequently applied to the development of hydrogel patches and preparation methods, which are composed of bidirectional elastic non-woven fabrics, hydrogels containing extracts and a cover film layer, and solve the common the problem of allergies caused by patches.