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37results about How to "Reduced storage capacity requirements" patented technology

Beekeeping management and control system

The invention discloses a beekeeping management and control system, and relates to a beekeeping system. The beekeeping management and control system comprises an intelligent beehive, wherein the intelligent beehive comprises a beehive body, a control module, detection devices and an execution device, the control module is used for receiving detection signals transmitted by the detection devices, comparing the detection signals with set characteristic signals, and outputting control signals to the execution device according to the comparison result, the detection devices comprise the inner detection device and the outer detection device, the inner detection device is installed in the intelligent beehive, and is used for detecting the temperature factor, the sound factor and the pressure factor of the interior of the intelligent beehive, the outer detection device is installed outside the intelligent beehive and is used for detecting the temperature of the exterior of the intelligent beehive, the execution device is installed in the intelligent beehive, and is used for carrying out the control signals output by the control module, the input end of the control module is connected with the output ends of the detection devices, and the output end of the control module is connected with the input end of the execution device. According to the beekeeping management and control system, automation of the whole management and control process of beekeeping can be achieved, labor intensity of beekeeping is greatly reduced, working efficiency is high, the cost is low, and the beekeeping management and control system is easy to popularize and use.
Owner:LIUZHOU VOCATIONAL & TECHN COLLEGE

Protocol-independent network redundant flow eliminating method

The invention discloses a protocol-independent network redundant flow eliminating method. According to the method, a certain number of data packets are grabbed from a network in advance, the data packets are grouped according to the magnitudes of loads, statistics of the data size cumulative probability of grouping is conducted, a corresponding load threshold value is determined, and a sending end conducts redundant flow elimination on the data packet the load of which is larger than the load threshold value; the loads are partitioned according to the weak Hash values, the strong Hash value of each data block is taken as a fingerprint to be matched with a fingerprint in a fingerprint base, the fingerprint which is not matched with the fingerprint in the fingerprint base and the corresponding data block are updated to the fingerprint base and a data block base, the sending end takes the initial positions of all the data blocks in the data packets and the positions of all the data blocks in the data block base as loads to regenerate data packets and sends the data packets to a receiving end, and the receiving end conducts recovery on the data packets after receiving the data block information in the data packets. The method is used for processing redundant data among the data packets without being affected by the application layer communication protocol and has a good redundant flow elimination effect and a good processing time effect.
Owner:SOUTHWEAT UNIV OF SCI & TECH

Pipeline magnetic flux leakage testing on-line data compression method

The invention provides a pipeline magnetic flux leakage testing on-line data compression method mainly used for compressing mass data in pipeline magnetic flux leakage on-line testing, and belongs to the field of signal processing. The method comprises the following steps that (1) detected magnetic flux leakage data are divided into data segments having the same number of bytes; (2) whether each data segment contains pipeline defect information is judged by means of average absolute deviation statistical magnitude, and only the data segments containing the defect information are stored; (3) if multiple data segments contain a large amount of redundant signal data, main content of the data segments is analyzed, and only the first little main content is stored; (4) integral promotion wavelet decomposition is conducted on each detecting signal of each data segment after two-stage compression, threshold processing is conducted on wavelet coefficients produced after decomposition, then adaptive coding is conducted on the processed wavelet coefficients, and finally only bit stream data after corresponding coding are stored. Therefore, the method can achieve high-efficiency compression of pipeline magnetic flux leakage testing on-line data.
Owner:SOUTHWEST PETROLEUM UNIV

Junk image fine-grained classification method based on incremental learning

The invention relates to a junk image fine-grained classification method based on incremental learning. The junk image fine-grained classification method comprises the following steps: step 1, constructing a new and old category junk image database; step 2, respectively training a deep convolutional feature extraction network and an incremental classifier: firstly, training a resnet18-based deep convolutional neural network, called a resnet18 network, by utilizing the selected old category garbage image data set; removing a full connection layer from the trained resnet18 network to serve as adeep convolution feature extraction network of incremental learning; and finally, using the deep convolution feature extraction network to extract the deep convolution features of the old type of junkimages; extracting a deep convolution feature of a newly-added class garbage image by using a deep convolution feature extraction network as a negative class sample data set of an incremental SVM classifier, extracting a deep convolution feature of the newly-added class garbage image by using the deep convolution feature extraction network as a positive class sample data set of the incremental SVM classifier, and training the incremental SVM classifier; and step 3, establishing a classification incremental learning model.
Owner:TIANJIN UNIV

Decentralized data verification processing method, device and system and medium

The embodiment of the invention discloses a decentralized data verification processing method, device and system and a medium. The method comprises the following steps: receiving a data analysis request initiated by a data user; according to the data analysis request, reading data of at least one data unit required by analysis from one or more data centers to a trusted storage space of a trusted computing device; based on the data fingerprint of each data unit stored in the block chain network, verifying the read data, and if the verification is passed, confirming that the read data is valid;analyzing and processing the read data based on an analysis algorithm running in the trusted computing device according to the data analysis request to generate a processing result, and storing the processing result in the trusted storage space; and feeding back a processing result to the data user. According to the technical scheme provided by the embodiment of the invention, the data joint analysis processing can be realized, the credibility and safety of the data analysis processing process are ensured, and meanwhile, the calculation amount of data verification is reduced.
Owner:BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD

Electrocardiosignal compression sampling device and method based on random demodulation structure

The invention relates to the field of medical care electronic appliances, in particular to an electrocardiosignal compression sampling device and method based on a random demodulation structure. The device comprises an FPGA controller, a pseudo-random signal generator, a frequency mixer, a filter, an AD converter, an FIFO memory, a data transmission chip, an upper computer OMP algorithm and the like. The FPGA control circuit is adopted as a main controller to control the pseudo-random signal generator to generate pseudo-random sequence signals, electrocardiosignals and the pseudo-random sequence signals pass through the frequency mixer at the same time, frequency components of the electrocardiosignals are distributed on the whole frequency axis, low-frequency components are intercepted through the low-pass filter, AD low-frequency sampling is finally achieved, correct information can be obtained, sampling information is stored and then transmitted to an upper computer end of a computer, and electrocardiosignals can be accurately reconstructed through an OMP algorithm. The device has the advantages that the electrocardiosignal sampling power consumption is reduced, the endurance time of sampling equipment is prolonged, the storage capacity requirement of a memory in the equipment is reduced, and the storage cost is reduced.
Owner:NANCHANG UNIV

Multi-scale approximate explicit model predictive control method for three-degree-of-freedom helicopter

InactiveCN109062038AOvercome the defects of predictive controlEasy to find onlineAdaptive controlGravity centerOptimization problem
The invention discloses a multi-scale approximate explicit model predictive control method for a three-degree-of-freedom helicopter. The multi-scale approximate explicit model predictive control method comprises the following steps that step (1), modeling is carried out on the three-degree-of-freedom helicopter to obtain a parameter optimization problem, namely an object to be approximated below;step (2), a piecewise linear insertion method is carried out to initially obtain an approximate control law; step (3), self-adaptive separation function approximation is carried out, and the form of the approximate control law is transformed; step (4), a barycenter function is introduced, and barycenter interpolation is utilized to obtain an approximate control law based on the barycenter function; and step (5), multi-scale approximate explicit model predictive control over a three-degree-of-freedom helicopter system is carried out. According to the multi-scale approximate explicit model predictive control method, the real-time performance of the three-degree-of-freedom helicopter control system is improved, the control complexity is reduced, the storage capacity requirement of a controller is reduced, the online calculation time is saved, and a good control effect is achieved.
Owner:ZHEJIANG COLLEGE OF ZHEJIANG UNIV OF TECHOLOGY

A Protocol-Independent Method for Eliminating Redundant Traffic in Networks

The invention discloses a protocol-independent network redundant flow eliminating method. According to the method, a certain number of data packets are grabbed from a network in advance, the data packets are grouped according to the magnitudes of loads, statistics of the data size cumulative probability of grouping is conducted, a corresponding load threshold value is determined, and a sending end conducts redundant flow elimination on the data packet the load of which is larger than the load threshold value; the loads are partitioned according to the weak Hash values, the strong Hash value of each data block is taken as a fingerprint to be matched with a fingerprint in a fingerprint base, the fingerprint which is not matched with the fingerprint in the fingerprint base and the corresponding data block are updated to the fingerprint base and a data block base, the sending end takes the initial positions of all the data blocks in the data packets and the positions of all the data blocks in the data block base as loads to regenerate data packets and sends the data packets to a receiving end, and the receiving end conducts recovery on the data packets after receiving the data block information in the data packets. The method is used for processing redundant data among the data packets without being affected by the application layer communication protocol and has a good redundant flow elimination effect and a good processing time effect.
Owner:SOUTHWEAT UNIV OF SCI & TECH

On-line data compression method for pipeline magnetic flux leakage detection

The invention provides a pipeline magnetic flux leakage testing on-line data compression method mainly used for compressing mass data in pipeline magnetic flux leakage on-line testing, and belongs to the field of signal processing. The method comprises the following steps that (1) detected magnetic flux leakage data are divided into data segments having the same number of bytes; (2) whether each data segment contains pipeline defect information is judged by means of average absolute deviation statistical magnitude, and only the data segments containing the defect information are stored; (3) if multiple data segments contain a large amount of redundant signal data, main content of the data segments is analyzed, and only the first little main content is stored; (4) integral promotion wavelet decomposition is conducted on each detecting signal of each data segment after two-stage compression, threshold processing is conducted on wavelet coefficients produced after decomposition, then adaptive coding is conducted on the processed wavelet coefficients, and finally only bit stream data after corresponding coding are stored. Therefore, the method can achieve high-efficiency compression of pipeline magnetic flux leakage testing on-line data.
Owner:SOUTHWEST PETROLEUM UNIV

Meshless Galerkin Method Structural Topology Optimization Method Based on GPU Parallel Acceleration

The invention discloses a grid-free Galerkin method structural topology optimization method based on GPU parallel acceleration. The grid-free Galerkin method structural topology optimization method mainly comprises the steps of 1 reading data into a host machine memory, arranging integral points through a CPU, establishing the relation of nodes, the integral points and local lattice searching, computing node influence domain radiuses and the integral point definition domain radiuses, confirming the relation of the nodes and the integral points and then copying the data into a GPU global memory; 2 setting different GPU thread blocks and the thread number according to different calculating data; 3 performing asynchronous assembly through the CPU and a GPU and solving a grid-free Galerkin method global discrete system equation to obtain a displacement approximate solution; 4 performing structural topology optimization calculation in the GPU and judging whether iteration is finished or not and a result is output or not according to residual errors of design variables. The grid-free Galerkin method structural topology optimization method is low in hardware cost and good in universality and can reduce a large amount of time consumption on the premise that the engineering accuracy requirement is met.
Owner:XIANGTAN UNIV
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