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

Systems and methods for processing streaming media by selectively removing a portion of the streaming media data, e.g., for storage and / or delivery over a computer network medium. The amount of data in a media stream itself may be selectively reduced for delivery and / or storage and, in one exemplary embodiment, the amount of data in the media stream may be selected for delivery and / or storage so that it is reduced in a manageable and substantially consistent fashion. In another exemplary embodiment, data within a media stream of a given temporal duration may be selected for delivery and / or storage in such a way that leads to a proportional increase in the maximum speed at which data from the given temporal duration of the media stream may be transmitted and reviewed while simultaneously providing the benefit of reducing overall storage capacity requirements. The disclosed systems and methods may be advantageously implemented with any type of streaming media and video transport technology that employs media streams that comprise multiple frames including, but not limited to, any type of streaming media that employs video compression technology.

The invention relates to an environmental monitoring system, in particular to a remote wireless environment real-time data acquisition method and a device. The device comprises a management work station and at least one ZigBee wireless sensor network, wherein, the wireless sensor network comprises a coordinator node which is connected with at least one router node; the router node is connected with at least one functional module, and the coordinator node is connected with the management work station by an RS232 interface. The acquisition device in the invention is developed by utilizing an advanced ZigBee wireless sensor network system, has the characteristics of low cost, high reliability, convenience and strong commonality, and can carry out wireless real-time acquisition on outdoor environmental information.

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.

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.

The present invention discloses a single board software storing and loading method and system. The present invented method includes network administrator classifying and packing the loading needed single board software into number of single board software packages respectively down sending to plurality of net element equipment in network system and saving; said net element equipment judging whether itself storing said equipment service board loading needed single board software, if it is then down sending said single board software to said service board, otherwise obtaining loading needed single board software from other net element equipment and down sending to service board. The present invented system includes single board software classifying packing module, judging module and single board software memory module. The present invented system and method reduce net element equipment master control board storage capacity requirement and master control board cost, and raising software-loading speed.

The invention discloses a satellite borne shared storage exchange device which comprises a wire in processing unit, a plurality of memorizers and a wire out processing unit. The wire in processing unit comprises a plurality of interface processing units, a plurality of packet processing units, an address list management module, a parallel writing-in control module and a multiplexing module. The wire out processing unit comprises a demultiplexing module, a parallel reading control module, a plurality of output caching modules and a plurality of sending modules. Each input interface corresponds to an interface processing module, a packet processing module and a memorizer. Each output interface corresponds to an output caching module and a sending module. The number of the input interfaces and the output interfaces is identical to the number of the interface memorizers. The satellite borne shared storage exchange device can effectively reduce the requirements on the access rates and the capacity of the memorizers, and meet the development requirements of a high-speed large-capacity satellite borne routing switch.

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.

The invention discloses a software loading system and method, the system not only includes business panel, but also includes: the dedicated storage veneer and the veneer software distribution module; the dedicated storage veneer, installed at the network element equipment, and independent to the network element master control board, used to store the veneer software package of network management issued; the veneer software distribution module, installed at the network element equipment master control board, used to access the veneer software from the said dedicated storage veneer storage and distribute to the corresponding business panel. Using the system and method of this invention, it can not only reduce storage capacity requirements of network element equipment master control board, greatly reducing the master control board costs, but also can increase the speed of software loading.

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.

The invention discloses repeating data processing technology which includes two methods including static file segmenting and dynamic file segmenting. Static file segmenting refers to segmenting files according to a fixed size, and dynamic file segmenting includes the following steps: looking up border positions of data blocks according to a certain algorithm; solving data fingerprints; using the data fingerprints to judge whether two data blocks are same or not; storing the same data blocks into one portion, and storing index values of the same data blocks for the convenience of being used during recovery. By adopting the technical scheme, needs of data on storage capacity can be reduced; on the basis of in-depth study on storage capacity optimization technology in disaster recovery backup, a certain technological improvement on repeating data deleting technology is made, and high-quality storage is realized.

The invention discloses a data storage method and belongs to the technical field of data storage. The method comprises the steps that data are stored in a storage space; the storage space is divided into at least one first storage area; each first storage area is divided into a first storage area block and a second storage area block, wherein each first storage area block is divided into multiple first storage blocks with equal storage capacity used for holding data in real time, each second storage area block is divided into multiple second storage blocks with equal storage capacity used for holding corresponding merge data, real-time data which have been subjected to merge calculation and are held in multiple consecutive first storage blocks are cleared to clear the first storage blocks, and merge data held in at least one second storage block are cleared to clear the second storage blocks. The technical scheme has the advantages that the problem existing in the prior art that large amounts of data are inconvenient to hold is solved, the demand of storage capacity is lowered, and the system load and the system resource usage are relieved.

The invention discloses a memory control system, an address mapping method and an address mapping device. A first-level mapping table and a second-level mapping table are stored in the memory. The address mapping method comprises the following steps: loading a first-level mapping table into a cache chip; when a host accesses the memory, obtaining a logic address of user data; searching a first-level mapping table in the cache chip by taking the logic address as an index to obtain an index address; and searching a second-level mapping table in the flash memory chip by taking the index address as an index to obtain the physical address of the user data, wherein the second-level mapping table is stored on a selected physical block of the memory, and the logic block address of the index address in the first-level mapping table is used for indicating the block address of the storage position of the second-level mapping table. According to the address mapping method, multi-level address mapping and block address compression are adopted to reduce the storage capacity requirement of the cache chip.

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.

The invention discloses a distributed processing method oriented to streaming audio-video data and a device thereof. The method comprises the following steps: S1, dividing multiple physical machines into different types with specific functions as follows: a distributed resource management function, a distributed data memorization function, a distributed encapsulation slicing function, a distributed decoding function, and other audio-video distributed processing function, and establishing a mapping relation among the physical machines of different types; S2, extracting the audio-video code streams from all transmission channels to save in the memory; S3, directly encapsulating the fragments of the audio-video code streams stored in the memory as an audio-video short fragment capable of independently performing coding and decoding; S4, coding and decoding the audio-video short fragment under the situation of not needing to maintain the coding and decoding context of each path; and S5, performing further audio-video processing on the decoded YUV data or independently coded and decoded audio-video short fragment .

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.

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.

A multi-scale approximate explicit model predictive control method for disk drive systems comprises the following steps: 1) modeling the disk drive system to obtain a parameter optimization problem; 2) performing a piecewise linear insertion method to obtain an approximate control law; 3) converting the form of the approximate control law into an adaptive layered function approximation; 4) introducing a center of gravity function to obtain an approximate control law base on the center of gravity function by using the center of gravity interpolation; 5) performing multi-scale approximate explicit model predictive control of the disk drive system. The invention improves the real-time performance of the disk drive control system, reduces the control complexity, reduces the requirement of thestorage capacity of the controller, saves the on-line calculation time, and has good control effect.

A multi-scale approximate explicit model predictive control method for a brushless DC motor comprises the following steps: (1) modeling a brushless DC motor system to obtain a parameter optimization problem, that is, an object to be approximated below; 2) piecewise linear insertion method to obtain an approximate control law; 3) convert that form of the approximate control law into an adaptive layered function approximation; 4) introducing a barycenter function to obtain an approximate control law based on that barycenter function by use the barycenter interpolation value; and 5) multi-scale approximate explicit model predictive control of the motor control system. The invention improves the real-time property of the motor control, reduces the requirement of the memory capacity of the control, saves the on-line calculation time, and has a good control effect.

The invention relates to a log processing method and device, equipment and a storage medium. The equipment acquires a starting state of the equipment; wherein the starting state comprises a normal starting completion state and an abnormal starting state; then, according to the starting state of the equipment, logs of the corresponding type are selected and stored; and the content integrity of a log stored in the abnormal starting state is higher than that of a log stored in the normal starting completion state. The requirement on the storage capacity of the equipment can be reduced, and the log storage cost performance is improved; furthermore, the equipment can analyze abnormal starting of the equipment according to the log with high content integrity, and a more accurate analysis resultis obtained.

The invention relates to a digital image scaler for saving hardware resources, belonging to the video image processing field. The image scaler comprises an interpolator module and a coefficient generation module. A concrete connection mode comprises the following steps that: original image data and clock signals are input to the interpolator module; under the action of an external clock, the coefficient generation module generates a position coefficient needed in interpolation operation, and the coefficient is input into the interpolator module as well; the interpolator module carries out the interpolation operation according to the input original image data and the interpolation position coefficient; and then the interpolator module outputs an image processed by the interpolation operation. The scaler is based on the hierarchical factorization of scaling algorithm, remarkably reduces the quantity of multipliers, only needs an accumulator, a register and a corresponding auxiliary control unit as hardware resources, and is applicable to the scaling in any proportion. The image scaler adopting a multi-stage interpolation algorithm can complete the image scaling functions in any proportion.

The invention discloses a method for recording a motion track of a robot and method for displaying the motion track of the robot. The method for recording the motion track of the robot comprises the following steps that the robot is controlled to only record the track parameters of key position points in the process of traveling according to a preset control mode, each position point in the traveling process does not need to be recorded, so that the data volume needing to be recorded by the robot is greatly reduced, the requirement of the robot for the storage capacity is reduced, and the costperformance of the robot is improved. According to the method for displaying the motion track of the robot, the recorded track key points are converted into the track connecting points in the globalmap, then the track connecting points are connected in series, only some track connecting points need to be processed, and each track point does not need to be processed, so that the data processing efficiency of a processor is improved, and operation resources are greatly saved.

The invention relates to the technical field of interaction, in particular to an interactive introduction identification system which comprises a mobile phone client, the mobile phone client is in signal connection with a streaming media server, the streaming media server can integrate audio, video and shared data in the mobile phone client, and the mobile phone client is connected with the streaming media server. The data processing module is used for integrating data and transmitting the integrated data to the data collection module to achieve data collection, collected data information is transmitted to the encoding module through the GPRS output module and the network transmission module, the encoding module encodes the data information, and the encoded data information is transmitted to the data processing module to achieve data processing. According to the invention, the transmission mode that the multimedia file is played while being downloaded is realized, so that the starting delay is greatly shortened, and the final target of selecting proper codes is to realize smooth playing and transmission of audio and video resources.

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.

The invention discloses a method for recording a motion track of a robot and a method for displaying a motion track of a robot. The method for recording a motion track of a robot only records key position points during the process of controlling the robot to walk according to a preset control mode. Trajectory parameters do not need to record every position point during the walking process, which greatly reduces the amount of data that the robot needs to record, reduces the robot's demand for storage capacity, and improves the cost performance of the robot. The method for displaying the trajectory of the robot is to convert the recorded trajectory key points into trajectory connection points in the global map, and then connect these trajectory connection points in series. Since only some trajectory connection points need to be processed, no Each trajectory point is processed, thereby improving the data processing efficiency of the processor and greatly saving computing resources.

The invention discloses a distributed processing method oriented to streaming audio-video data and a device thereof. The method comprises the following steps: S1, dividing multiple physical machines into different types with specific functions as follows: a distributed resource management function, a distributed data memorization function, a distributed encapsulation slicing function, a distributed decoding function, and other audio-video distributed processing function, and establishing a mapping relation among the physical machines of different types; S2, extracting the audio-video code streams from all transmission channels to save in the memory; S3, directly encapsulating the fragments of the audio-video code streams stored in the memory as an audio-video short fragment capable of independently performing coding and decoding; S4, coding and decoding the audio-video short fragment under the situation of not needing to maintain the coding and decoding context of each path; and S5, performing further audio-video processing on the decoded YUV data or independently coded and decoded audio-video short fragment .

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.

The invention discloses an enterprise training monitoring video abstract generation method based on a difference change operator, which belongs to the technical field of computer file management, andaims to achieve the purpose of extracting key information of the classroom monitoring video file to obtain a video abstract by finding out most representative key frames of the monitoring video file and storing the frames in the form of an image file after the classroom monitoring video file is input. According to the invention, the key information can be extracted from the enterprise training monitoring video file; on one hand, key information in the training process is reserved for subsequent teaching quality inspection, on the other hand, storage is simplified, an original video file is simplified into a small number of picture files, and the requirement for the storage capacity of a computer system is reduced under the condition that the resolution ratio is not reduced; the method hashigh application value in the fields of training centers of schools and enterprises and recording teaching conditions of teaching tutoring institutions.

The invention discloses a software loading system and method, the system not only includes business panel, but also includes: the dedicated storage veneer and the veneer software distribution module;the dedicated storage veneer, installed at the network element equipment, and independent to the network element master control board, used to store the veneer software package of network management issued; the veneer software distribution module, installed at the network element equipment master control board, used to access the veneer software from the said dedicated storage veneer storage and distribute to the corresponding business panel. Using the system and method of this invention, it can not only reduce storage capacity requirements of network element equipment master control board, greatly reducing the master control board costs, but also can increase the speed of software loading.