7results about How to "Implement Adaptive Processing" patented technology

Embodiments of the present specification disclose a kind of finished cigarette warehouse's adaptive control method, device and electronic equipment.The method includes determining to be processed object, and the basic information of to-be-processed object is acquired;Based on cigarette factory information and cigarette type, the stacking type timing diagram of to-be-processed object is inquired;Based on the code position information of sticking, to-be-processed object is scanned, and the control information of to-be-processed object is determined based on stacking type timing diagram and control type;Based on control information, control execution object is grabbed and moves to-be-processed object.The embodiments of the present specification can automatically identify to-be-processed object, and the basic information of to-be-processed object is acquired, then the stacking type timing diagram of to-be-processed object is inquired, finally to generate control information to realize the control of unstacking and restacking process, different control information can be adaptively generated according to the different to-be-processed object, realize the adaptive processing of different types of cigarettes of different cigarette factory production in warehouse, save manpower cost, improve the efficiency of in and out of warehouse.

The present application relates to the technical field of feed processing, and particularly relates to a preparation method of Maotai-flavor distiller's grains fermented feed, which comprises the following steps: drying treatment based on the moisture content of Maotai-flavor distiller's grains to obtain basic distiller's grains; determining the strain ratio of brewer's yeast, bacillus subtilis and aspergillus niger based on the tannin content of the basic distiller's grains to obtain a compound fermentation inoculant; inoculating and then fermenting; determining state evaluation parameters based on the total polyphenol accumulation rate, the dissolved oxygen consumption rate and the microbial activity index during the fermentation process, and performing qualified evaluation, and dynamically adjusting when unqualified; determining the fermentation end point based on the tannin degradation rate and the total polyphenol accumulation rate; and mixing the fermented distiller's grains with the basic feed at a mass ratio of 1% after low-temperature drying of the fermented distiller's grains. The present application realizes three-layer control of raw material evaluation, process control and end point determination, significantly improves the stability and content of functional active ingredients in the product, reduces the tannin and safety risk, and has a good intestinal health improvement effect on animals.

The present application relates to security equipment technical field, especially to a kind of compatible different model's X ray image line data supplement method.A kind of compatible different model's X ray image line data supplement method, comprising: obtaining article original X ray image data, target height;Compare original X ray image height with target height;Target height is higher than original image height then line data supplement is carried out;Target height is not higher than original height, no need to supplement, output original data;Line data supplement processing is carried out to the original image data of first view, obtains line data set A1 under the first view;Process the original image data under second view, obtain line data set A2 under the second view;Integrate line data set A1 under the first view and line data set A2 under the second view, obtain line data set A of the double-view X ray image;Output double-view X ray image.The present application makes the X ray image height obtained by supplementing line data uniform.

The invention relates to a self-adaptive quantum random number generation method based on real-time entropy estimation, and belongs to the technical field of quantum random number generation. According to an existing integrated quantum random number generator, due to the non-stationary characteristic of a physical entropy source, the entropy rate dynamically drifts, and after-processing parameters are fixed, randomness safety and generation efficiency are difficult to guarantee at the same time. According to the method, the state transition probability of the original random bit stream is counted in real time, the confidence interval correction is introduced to calculate the minimum entropy, the input bit width is dynamically adjusted accordingly, the Toeplitz matrix is reconstructed for random extraction, and self-adaptive adjustment of the compression ratio is achieved. According to the method, the compression ratio is increased to ensure the security of the output random number when the entropy source quality is reduced, and the compression ratio is reduced to improve the generation efficiency when the entropy source quality is improved, so that the dynamic balance between the randomness security and the generation efficiency is realized on the premise of keeping integration and low cost.

The invention provides a video deblurring method and device, electronic equipment, a computer storage medium and a computer program product, and the method is applied to the technical field of computers, and comprises the steps: determining each fuzzy video frame in a to-be-processed video; for each fuzzy video frame, acquiring a fuzzy level of the fuzzy video frame, and according to the fuzzy level, adjusting the number of first residual channel attention blocks included in each encoder in the trained deblurring network to obtain a target deblurring network; the first residual channel attention block is a residual channel attention block with a shared weight in the encoder; performing multi-stage deblurring processing on the fuzzy video frame by using the target deblurring network to obtain a target video frame; and combining the target video frame of each fuzzy video frame with an unprocessed clear video frame in the to-be-processed video to obtain a target video.

The invention provides an intelligent high-temperature collecting, counting and stacking device for paper pulp environment-friendly tableware, which comprises an in-mold state monitoring unit for collecting temperature data and tableware state images in a shaping lower mold, and an adsorption transfer unit for adsorbing and transferring the tableware subjected to high-temperature shaping treatment in the shaping lower mold, the blowing demolding unit is used for assisting demolding when tableware subjected to high-temperature shaping treatment in the shaping lower mold is stuck to the mold, the transfer counting unit is used for collecting counting data in real time in the tableware transfer process, and the lifting limiting stacking unit is used for stacking and counting the tableware of different specifications. And the AI control unit is used for generating collecting, counting and stacking parameters matched with the current tableware to be transferred. Through the collaborative linkage design of all the units, the full-process intelligent high-temperature collecting, counting and stacking system is constructed, the problem that tableware is stuck to a mold after high-temperature setting is solved, and the labor cost and debugging errors caused by manual intervention are reduced.

The invention discloses a thermal power plant pollutant concentration prediction method based on frequency domain residual error and multi-expert fusion, and aims to solve the problems of insufficient frequency domain feature utilization, weak model generalization ability and low prediction precision of the existing method. A frequency domain information residual extraction module is introduced, time domain features are transformed, enhanced frequency domain information is fused into the time domain features in a residual mode, and frequency domain information residual features containing rich periodicity and fluctuation information are obtained. Further, a feed-forward network in a Transform model is replaced by a multi-expert fusion module based on frequency domain residual gating, and expert knowledge is adaptively selected and fused according to data characteristics. The method disclosed by the invention shows remarkably higher prediction precision and stronger generalization ability in the task of predicting the concentration of the pollutant nitrogen oxide discharged by the thermal power plant. The method is suitable for prediction of various time sequences, especially prediction of industrial data with complex periodicity and fluctuation characteristics.