240results about How to "Effective recovery" patented technology

The invention relates to the technical field of data storage, and discloses a lossless compression algorithm-based data storage method, which comprises the following steps of: receiving to-be-stored data through a data interface, automatically identifying a data format by using a data analysis tool, and performing feature analysis to obtain the size, the type and the complexity of the data; through deep analysis of data features, the method can flexibly select a proper Huffman coding processing mode, and optimizes a compression process according to different data types and complexity. In addition, a context modeling optimization mechanism is introduced, the coding mode is dynamically adjusted, and the compression ratio and the storage efficiency are further improved; efficient storage and reliability verification of data are ensured through a block storage strategy in combination with metadata management; the problem that an existing compression algorithm is low in efficiency is solved, the integrity and reliability of data storage are improved, and the method is suitable for storage requirements of large-scale data and diversified data.

The invention provides an abnormal data detection and recovery method and system for reports of a water plant management and control platform, and relates to the technical field of water plant data detection.The abnormal data detection and recovery method comprises the steps that report data of the water plant management and control platform are collected, then the threshold range of the report data is obtained through threshold detection, and the report data exceeding the threshold range are marked as potential abnormal data; performing exception scoring on each potential exception data in the report data by adopting an exception detection model, and then marking the potential exception data with an exceptional exception scoring result as burr data points; and deleting each burr data point in the report data, and then estimating missing data points by utilizing a linear relationship between adjacent data points of the deleted burr data points to carry out linear interpolation so as to carry out data recovery on the report data. The method has the beneficial effects that the accuracy and stability of data analysis of the water plant management and control platform are improved through multi-stage anomaly detection, and efficient detection and recovery of abnormal data are realized through combination of statistical analysis and machine learning technologies.

The invention belongs to the technical field of cloud storage, and particularly relates to an enterprise service management cloud storage system which comprises a system initialization module, a distributed data storage module, a data encryption module, an authority control module, a multi-level cache module, a data backup and recovery module, a log monitoring module and a task scheduling and dynamic extension module. The distributed data storage module is responsible for dividing data in enterprise service management into a plurality of data blocks; the data encryption module is used for encrypting the enterprise service data stored in the cloud; the authority control module is responsible for managing the access authority of the user to the data; the multi-level cache module accelerates data access by configuring a local cache and a global cache; the data backup and recovery module is responsible for backing up the stored data regularly; the log monitoring module records various operation logs of the system; and the task scheduling and dynamic extension module is used for dynamically distributing calculation and storage resources according to the priority of the task and the utilization rate of the system resources.

The invention discloses a multi-dimensional constellation diagram mapping enhanced orthogonal chirp multiplexing optical transmission sending method, receiving method and system in the field of optical communication. The method comprises the following steps: a sending end converts data to be transmitted into an original signal bit stream; mapping through a preset four-dimensional constellation diagram model to generate a four-dimensional constellation point coordinate sequence, and dividing the four-dimensional constellation point coordinate sequence into two different branches; respectively carrying out OCDM modulation on the four-dimensional constellation point coordinate sequences on the two branches to generate two time domain sending signal sequences; performing power distribution and superposition on the time domain sending signal sequence to form a final sending signal; and a receiving end receives the sending signal from the channel, performs OCDM demodulation on the sending signal, recovers constellation point signals in the two branches by using a serial interference cancellation technology, and obtains an original signal bit stream through demapping of the four-dimensional constellation diagram model. According to the invention, the problems of selective fading of signal frequency and overlong CP in DD-OFDM can be solved.

The invention discloses a real-name system information management method supporting multi-level authentication, and the method comprises the following steps: collecting basic identity information of a user, and storing the basic identity information through an asymmetric encryption algorithm; according to the use demand and the access authority requirement of the user, generating a multi-level authentication hierarchy; dividing the real-name system information into a basic information area, an authority information area and a sensitive information area according to the sensitivity of the real-name system information; carrying out distributed storage on real-name system information, and carrying out hierarchical encryption on data of different information areas by using a hierarchical encryption strategy; based on a multi-level authentication result and in combination with an access control strategy, authority distribution is carried out on the user, and controlled access of real-name system information is carried out under multi-dimensional verification; user information operation behaviors are monitored in real time, user behavior characteristics are analyzed based on an anomaly detection model, and when risk behaviors are recognized, an additional verification process is triggered or user operation is directly limited. According to the invention, safer, more flexible and more efficient real-name system information management is realized.

The invention discloses an environment situation awareness data engineering system based on multi-source data fusion, which relates to the related technical field of environment situation awareness and comprises a multi-source data acquisition module, a multi-source data processing module, an environment evolution analysis module, an ecological restoration evaluation module, an ecological system evolution module and a visual observation module. The invention further discloses an environment situation awareness method based on multi-source data fusion, which comprises the steps of collecting environment data, effectively integrating the data, and presenting the data to a terminal user in a chart by utilizing a model evolution trend, a prediction result and possible influence of environment change on human behaviors. The UEB model is suitable for various climate and topographic conditions, has high precision and reliability in a high and cold plateau complex environment, can help to analyze and predict the influence of human activities on environmental elements and the influence of environmental changes on human behaviors, deeply excavates the interaction between the human activities and the environmental changes, and improves the prediction accuracy of the human activities and the environmental changes. And insight is provided for decision makers.

The invention relates to a log counting method based on Yolov9-UNet in a complex environment, and belongs to the technical field of image processing. The method comprises the steps that a Transform is embedded into a UNet, and a Transs-UNet module is formed; the method comprises the following steps of: combining a Trans-UNet module with Yolov9 to form a Yolov9-UNet model; the method comprises the following steps: acquiring training data to train a Yov9-UNet model, and respectively training a Trans-UNet module and Yov9 by referring to a training process of a GAN network; and acquiring an image containing the end face of the log, performing normalization processing on the image, inputting the normalized image into the trained Yolov9-UNet model to obtain a log detection frame, and performing statistics on the detection frame to obtain the log number. According to the invention, effective recovery of images in different scenes can be realized, and log counting in a complex environment is realized.

The invention relates to a metal additive modified Pt-loaded CeO2 catalyst, preparation and application thereof in CO oxidation, and belongs to the technical field of industrial catalysis. The preparation process of the catalyst mainly comprises the following steps: respectively dissolving cerium salt, platinum salt and auxiliary metal salt in deionized water to prepare corresponding precursor solutions; then, mixing the three solutions, and dropwise adding ammonia water under a stirring condition until yellow precipitates are generated; and finally, drying and washing the precipitate, and calcining the solid powder in a proper atmosphere to obtain the assistant metal modified Pt / CeO2 catalyst. La, Pr, Nd or Sm auxiliary metal is introduced into the Pt / CeO2 catalyst, so that the CO catalytic oxidation performance of the catalyst can be improved, and the poisoning resistance of the catalyst in an SO2-containing environment can be enhanced. The method has important significance in the actual industrial application, especially in the catalytic oxidation process under the condition of treating complex flue gas.

The invention belongs to the technical field of fault diagnosis, and particularly relates to a gearbox fault diagnosis method and system based on cyclic pulse characteristic decomposition, and the method comprises the steps: constructing a new dictionary matrix, namely a cyclic pulse dictionary matrix, to accurately estimate a pulse cycle period contained in a signal formed by mixing a plurality of periodic pulse signals; a Goertzel algorithm is adopted to obtain corresponding frequency amplitudes according to the magnitude sequence of the energy values of the pulse cycle periods; and separating and reconstructing the CPCC corresponding to the pulse cycle period, and decomposing the signal into a plurality of CPCCs. According to the invention, the cyclic pulse dictionary matrix is constructed to carry out sparse representation on the pulse cycle period of the periodic pulse signal, and the cycle period of the fault pulse characteristic in the gear vibration signal is accurately estimated; the Goertzel algorithm is adopted to decompose and reconstruct the CPCC in the gear vibration signal according to the pulse cycle period, and the decomposed CPCC contains abundant periodic pulse characteristic information.

The invention discloses a short-distance multi-ore-bed potassic salt ore large-section long-strip comprehensive mechanized mining method, and belongs to the technical field of potassic salt ore deposit mining. The method comprises the steps that a centralized transportation roadway is arranged on an upper head mining layer, an auxiliary transportation roadway is arranged in a stable salt rock interlayer between ore layers, and combined development is achieved; arranging large-section long strip chambers in the ore blocks along the inclination direction, and reserving permanent spacing strip pillars to maintain the stope to be stable; a chamber is cut and formed at a time by a double-arm large-mining-height mining machine, and efficient stoping is realized by matching with a continuous transportation system; multiple ore beds are mined in a coordinated mode from top to bottom in sequence, and the ore block air return way and the ore block air return way of the upper ore bed are staggered by 20 m or above so as to avoid stress superposition; a full-air-pressure ventilation system combining a press-in type and a draw-out type is constructed; natural supporting is achieved through permanent spacing strip pillars and natural top and bottom plates, safety is guaranteed through a micro-seismic and top plate monitoring system, and the goaf is backfilled with tail salt slurry to achieve green mining. According to the method, safe, efficient and high-recovery-rate mining of the short-distance multi-ore-bed sylvite ore is achieved.

The invention relates to the technical field of artificial intelligence and the field of financial science and technology, and discloses a vocoder audio generation method based on frequency band segmentation, which converts an input audio signal into a Log Mel spectrum, and performs primary processing on a spectrum signal through a one-dimensional convolutional network. After up-sampling processing is carried out on the signals through transposition convolution, features of different frequency bands are extracted and processed through a multi-receptive-field module. In the frequency band segmentation process, a signal is segmented into a plurality of tensors in the channel dimension, and each tensor corresponds to a specific frequency band range and is independently processed. And the PQMF synthesis filter bank is used for carrying out up-sampling on the signals with the unified number of channels again. And after the signals are combined, processing a finally generated audio signal through another multi-receptive field module. According to the method, tensors of different frequency bands are processed through frequency band segmentation and an independent multi-receptive-field module, and the frequency aliasing phenomenon introduced in the up-sampling process by transposition convolution is reduced, so that the quality and naturalness of audio generation are improved.

The invention discloses a preparation method of a rod-like selenium nano-carrier, and belongs to the technical field of nano-pesticides. The rod-like selenium nano-carrier is formed by converting chitosan modified amorphous selenium (a-Se) into single crystal ash selenium (t-Se). The amorphous selenium is initially spherical, and after chitosan modification, the spherical amorphous selenium is converted into single crystal ash rod-shaped selenium nanoparticles. The length of the rod-like selenium nano-carrier is 590-610 nm, the diameter of the rod-like selenium nano-carrier is 20-25 nm, the effective average particle size of the rod-like selenium nano-carrier is 90-110 nm, the drug loading rate is 39.28% + / -2%, and the encapsulation efficiency is 64.90% + / -3%. In addition, the invention also provides an application of the rod-like selenium nano-carrier in a nano bactericide material.

The invention relates to the technical field of image processing, and discloses a transparent and restorable face anonymization processing method and system, and the method comprises the steps: obtaining to-be-anonymized original face images, extracting initial identity features from the original face images through a face feature extractor, and generating a group of keys for each original face image; constructing a reversible neural network, inputting the identity features and the secret keys belonging to the same original face image as a group of input data into the reversible neural network, performing affine transformation through the reversible neural network, and finally generating anonymized identity features controlled by the secret keys; and inputting the original face image and the anonymized identity features into a pre-trained generator so as to generate an anonymized face image. According to the method, the application requirements are fully met, and the dual goals of data security and privacy protection are ensured.

The invention provides a multi-reflection superposition enhanced microwave displacement measurement method and system, and the method comprises the steps: S1, constructing a microwave multi-reflection propagation path, enabling a microwave radar to transmit electromagnetic waves to the microwave multi-reflection propagation path as a transmission signal, and receiving a corresponding echo signal; s2, extracting length change information of a microwave multi-reflection propagation path according to the echo signal; s3, establishing a linear superposition relation model between the total length of the microwave propagation path and respective displacements of W reflection surfaces in the microwave multi-reflection propagation path; w2; and S4, based on the linear superposition relation model, displacement information of the corresponding reflection surface is obtained and output. According to the invention, a larger phase variation can be obtained under the condition of small displacement or weak vibration, so that the measurement sensitivity is improved and the signal-to-noise ratio is improved.

The invention discloses an electromagnetic radiation signal detection and image restoration method for a computer video interface line, and the method comprises the following steps: carrying out the sampling of a radiation signal of an HDMI / VGA interface cable according to a set sampling rate through employing a wireless electromagnetic spectrum signal receiving device, combining a VESA video standard, and aiming at a TEMPEST frequency point; performing time-frequency conversion on the sampled data, and extracting parameters such as a row period and a field initial position; on the premise of determining the line frequency and the field initial position, video period synchronization is carried out, and a field frequency parameter is obtained; performing line tracking search, and extracting image frame data; and carrying out gray processing and multi-frame overlapping processing on the image frame data to restore a video image. The computer video interface line electromagnetic radiation signal detection method is simplified, the line frequency parameters, the field initial position and the like are rapidly extracted, line tracking is carried out to extract image frame data, and the requirement for restoring video images through computer video interface line electromagnetic radiation signals is met.

The application provides a multi-agent cooperative task state management and abnormal backtracking method and system, relates to the technical field of artificial intelligence, and comprises the following steps: obtaining interaction data, state data and execution logs, constructing an initial task knowledge graph based on an ontology model, establishing a bidirectional causal chain by using a Bayesian network to form a dynamic knowledge graph, analyzing state migration rules when an abnormality is detected, identifying a propagation node, constructing an abnormal propagation subgraph, generating an influence chain, determining a recovery priority and triggering state rollback. The method can quickly trace the abnormal source, effectively control abnormal diffusion, and improve system robustness and task recovery efficiency.

The invention discloses a steel structure digital twinborn health monitoring system and method. The system comprises a data acquisition module, a data processing module, a data storage module, a model construction module, a model integration module, a user interface and visualization module, a data analysis and optimization module and an interaction and feedback module. The model construction module constructs a steel structure digital twinborn model; the model integration module integrates the steel structure digital twin model with a corresponding entity steel structure; the data analysis and optimization module comprises a data management module, a data analysis module, a data analysis module, a model management module, a model analysis module and a monitoring and early warning module. The method solves the problems that a traditional steel structure health monitoring method wastes human resources, is low in monitoring frequency and incomplete in data acquisition, and cannot efficiently acquire practical information, and although a digital twinborn technology is applied to an individual steel structure health monitoring system, a finite element simulation process is lack of detailed research, and the working efficiency is low. And application feasibility in an actual steel structure is lacked.

The invention provides a sand land natural agriophyllum squarrosum artificial induction rapid recovery method, which comprises the following steps: (1) setting sand barriers, selecting a flowing or semi-flowing dune, and when agriophyllum squarrosum seed induced germination is carried out at the initial stage of a plant growth season in April to May, arranging a row of mechanical sand barriers perpendicular to a main harmful wind direction along the contour line of the dune, and controlling the row spacing to be 4-6m; (2) turning over surface soil, and applying an organic fertilizer; (3) watering and preserving soil moisture. The agriophyllum squarrosum artificial induction efficient recovery method has the advantages that agriophyllum squarrosum is fast and efficient in recovery, and the growth period is prolonged; by utilizing the sensitivity advantage of agriophyllum squarrosum seeds to soil nutrients and moisture, the growth amount is greatly increased after the organic fertilizer is used for improving the sandy soil; the biological sand barrier belt is formed after recovery along the contour line of the dune according to a row belt mode, and compared with a natural cluster-shaped distribution structure, the wind prevention and sand fixation effects are remarkably improved.

The embodiment of the invention discloses a fuel cell recovery method, and the method comprises the steps: controlling a fuel cell to operate for a first preset time under a first preset current density and a first preset voltage through obtaining a reference voltage of the fuel cell, and reducing a cathode stoichiometric ratio to a preset cathode stoichiometric ratio to reach an oxygen-deficient state, operating for a second preset time under a second preset current density and an oxygen-deficient state, and measuring a target voltage after the fuel cell operates for the second preset time; and comparing the reference voltage with the target voltage to generate a recovery result of the fuel cell. According to the fuel cell recovery method provided by the invention, various reversible attenuation of the fuel cell can be recovered by using available reactants in the fuel cell system under the condition of no additional pipeline control system or inert gas.

The invention provides a message processing method and device, equipment and a storage medium, under the condition that a first network isolation area receives a first message, an identifier of the first network isolation area, quintuple information of the first message and a source-target MAC are stored in a corresponding session, and the session and a second message are stored. The second message is the first message which does not contain the source-target MAC address; and under the condition that the second network isolation area obtains the second message, determining a corresponding session according to the quintuple information of the second message and the identifier of the first network isolation area, restoring the source and target MAC address of the second message according to the session, and forwarding the second message. By storing the identifier of the network isolation area, the quintuple information of the message and the original source and target MAC address in the session corresponding to the message, the session can be obtained in the corresponding network isolation area by using the quintuple information of the message, so that the original source and target MAC address of the message can be effectively restored by using the session when the message is sent.

The invention discloses an image processing method and device, equipment and a storage medium. The method comprises the steps that a first image is acquired; the first image is restored based on an image restoration model to obtain a second image, the image restoration model comprises a frequency domain processing module and a spatial domain processing module, the frequency domain processing module is used for processing the first image from a frequency domain, and the spatial domain processing module is used for processing the first image from a spatial domain to obtain a second image; the second image is a restored image of the first image, and the quality of the second image is higher than that of the first image; and outputting the second image. Therefore, by means of the image restoration model, the first image can be processed from the angles of the spatial domain and the frequency domain, the frequency domain features are dynamically learned while the spatial domain features are mined, and the problem of middle image information loss caused by restoration through a single-angle model is solved. Therefore, the first image can be effectively restored to obtain the second image, and the effect of improving the quality of the image is achieved.

The application provides a three-dimensional reconstruction method based on multi-dimensional information fusion and a convolutional neural network, and comprises the following steps: acquiring polarized sub-images of a measured object under four transmission polarization directions and including multiple detection spectral bands through a multispectral polarization camera; performing image registration and joint denoising on all images; calculating polarization parameters of the measured object, combining spectral information and polarization information to calculate an azimuth angle and a zenith angle of the measured object; and acquiring surface normal vector component three-dimensional data of the measured object through a surface normal reconstruction model constructed based on a convolutional neural network and with the aid of physical prior knowledge. The method provided by the application can effectively restore the texture details of the surface of the measured object, can realize fast three-dimensional information acquisition of a measured object with a surface simultaneously having a diffuse reflection and a specular reflection characteristic in a complex indoor or outdoor scene under illumination conditions, and is helpful to expand the application range of the polarization three-dimensional reconstruction technology.

The utility model relates to the technical field of orthopedic rehabilitation exercise equipment, in particular to an orthopedic clinical rehabilitation auxiliary device. The clinical rehabilitation assisting device for the orthopedics department comprises a base, a supporting table and a threaded rod are installed on the base, a driving mechanism is installed at the end of the supporting table, a first gear is installed at the output end of the driving mechanism, and an upper limb training mechanism used for training upper limbs is arranged on the first gear; a first gear is installed at the end of the threaded rod, a second gear is installed at the end of the threaded rod, a chain is in transmission connection between the first gear and the second gear, an upper limb training mechanism used for driving the first gear to rotate is arranged on the first gear, and a lower limb training mechanism is movably connected to the threaded rod; the first gear drives the second gear to rotate so as to drive the lower limb training mechanism to move, simultaneous exercise of multiple parts of the patient is achieved, and recovery of the patient is effectively helped.

The invention relates to the field of information security passwords, in particular to a cryptographic algorithm side channel analysis method based on manifold learning, which comprises the following steps of: firstly, acquiring energy information of equipment running a cryptographic algorithm, analyzing the acquired energy trace, positioning and executing a key operation position related to a secret key, and dividing the key operation position into a plurality of operation sections; secondly, performing feature extraction on the operation section by applying a manifold learning algorithm, and mapping the operation section of a high-dimensional waveform space to a low-dimensional feature space; and finally, classifying the feature points by adopting a hierarchical clustering algorithm, recovering a key operation type according to a classification result, finally obtaining a key, and realizing automatic side channel analysis of a cryptographic algorithm.

The invention belongs to the technical field of financial quantification and artificial intelligence, and particularly relates to a self-adaptive stock investment decision generation method suitable for a high-fluctuation market, which comprises the following steps of: firstly, acquiring stock transaction data, calculating a stock price index, a correlation index and a market fluctuation index, and inputting the indexes into a Transform predictive coding model; the market volatility index is calculated based on an LSTM self-coding model with cavity convolution, and a multi-head attention module with a multi-head feedforward network is introduced into the Transform predictive coding model; fusing the multi-scale feature representations of the indexes through a multi-layer multi-head attention mechanism to obtain comprehensive features; and finally, modeling the stock transaction into an improved Markov decision process, substituting the comprehensive characteristics, and solving by adopting an SAC algorithm to obtain a stock investment decision. Compared with the prior art, the revenue capability can be further improved, and the transaction risk is controlled.

The invention relates to a sea cucumber and fish composite proliferation reef which comprises a proliferation reef base, a sea cucumber proliferation fence is arranged on the proliferation reef base, and a fish proliferation cylinder of a cylindrical structure is arranged on the inner side of the sea cucumber proliferation fence; the space between the sea cucumber proliferation fence and the fish proliferation barrel is filled with proliferation reefs, so that the proliferation reefs form a sea cucumber proliferation area; the fish proliferation barrel comprises a barrel-shaped proliferation cavity and openings located in the top end and the bottom end, and the openings are used for enabling the barrel-shaped proliferation cavity to form a fish proliferation area. By means of the sea cucumber and fish composite proliferation reef, the natural reef environment can be effectively restored and simulated, the independent biological preference of fishes and sea cucumbers is met, and the proliferation requirements of different organisms are fully met.

The invention provides a vehicle information recording management method and system, and relates to the technical field of vehicle management, and the method comprises the steps: obtaining a collection image of a monitored vehicle; obtaining vehicle characteristics of the monitored vehicle according to the collected image; obtaining a license plate contour of the monitored vehicle through an edge detection algorithm according to the vehicle characteristics; according to the license plate contour, processing the license plate contour through morphological operation to obtain an enhanced image of the license plate contour; according to the enhanced image of the license plate contour, dividing the enhanced image of the license plate contour into a non-occlusion area and an occlusion area through a deep learning model; repairing according to the non-occlusion area through the context information to obtain an occlusion image of the occlusion area; obtaining a license plate number of the monitored vehicle according to the image of the non-shielding area and the shielding image; and inputting the license plate number and the vehicle type of the monitored vehicle. According to the invention, through combination of an advanced image processing technology and a deep learning algorithm, rapid and accurate collection of vehicle information is realized.

A valuable metal recovery method includes: screening a battery slag from lithium ion battery waste; adding an acid to the battery slag; adding a sulfur compound the leachate; filtering the first processed product to obtain a first processed filtrate; adding a sulfur compound to the first processed filtrate; filtering the second processed product to obtain a second processed filtrate; adding calcium hydroxide to the second processed filtrate; filtering the third processed product to obtain a third processed filtrate; adding sodium carbonate to the third processed filtrate; filtering the processed product; heating the fourth processed filtrate; blowing carbon dioxide or adding a carbonate; and filtering the processed product, wherein a pH of the second processed product is higher than a pH of the first processed product, and a pH of the third processed product is higher than the pH of the second processed product.

This invention relates to the field of image restoration technology, specifically disclosing an image restoration method and device based on discrete wavelet transform. An image restoration network, called Multi-Wavelet Attention Memory Neural Network (MWA-MNN), is designed, consisting of three sub-networks. These sub-networks include Discrete Wavelet Attention Blocks (DWABs) and Coordinate Channel Attention Blocks (CCABs) to extract spatial and channel feature information, effectively separating degraded image layers such as rain streaks from the image to obtain a clean image. The invention leverages the expressive power of wavelet transform for high-frequency information, thereby improving image restoration performance. The sub-networks also include Supervised Selective Kernel Blocks (SSKBs) for filtering effectively extracted features in each sub-network. This invention also proposes a memristor-based cross-array MWA-MNN circuit implementation scheme. Memristors are a novel type of non-volatile memory with faster read speeds and lower power consumption. Experimental results show that this method has good performance and versatility in various image restoration tasks.

There is provided a method for recovering lead from copper smelting dust according to the present invention includes an alkali leaching step of leaching lead contained in copper smelting dust with an alkali solution, a step of performing a solid liquid separation on a post-leaching solution and a leaching residue after the alkali leaching step, a neutralization step of adding an acid to the separated post-leaching solution to precipitate a lead, and a step of recovering a precipitate containing the lead by performing a solid liqiud separation.