29results about How to "Reduce data loss" patented technology

The invention discloses a dynamic allocation management system for monitoring computing power resources in real time, relates to the technical field of computing power resource management, and is used for solving the problem that an existing dynamic allocation management system for the computing power resources cannot efficiently match, optimally utilize, accurately evaluate and dynamically allocate heterogeneous computing power resources. Comprising a central cloud and a plurality of edge nodes in communication connection with the central cloud, and a real-time monitoring prediction unit, a dynamic distribution management unit and a fault detection processing unit are arranged in the central cloud; according to the method, the utilization rate and delay information of the heterogeneous computing power resources are analyzed in detail, so that the resources most suitable for the target processing task can be efficiently matched; by eliminating the computing power resource with a relatively low delay value, the utilization efficiency of the whole resource is improved, and resource waste is avoided; and resource demand prediction is performed in combination with a plurality of parameters, so that the performance and value of the computing power resources to be allocated can be evaluated more accurately. And effective management and optimal utilization of heterogeneous computing power resources are realized.

The invention provides a diabetic retinopathy image recognition method based on federated learning and differential privacy, and belongs to the field of federated learning. The method comprises the following steps: carrying out preprocessing and Poisson sampling on a diabetic retinopathy image data set to initialize a global model located in a central server; the local client obtains parameters of the global model from the central server and constructs a local model; the local client performs training and differential privacy processing on a local model by using local data; the central server receives the parameters uploaded by the clients for secure aggregation, and updates the global model by using the parameters after secure aggregation; if the number of training iterations does not reach the threshold value specified by the user, a result is transmitted to the local model to continue the training process; and when the number of training iterations reaches a threshold value specified by the user, terminating a further iteration process to obtain a trained model. And the problems of gradient leakage and data loss possibly existing in privacy protection by introducing differential privacy in federated learning are balanced.

The invention provides an unmanned aerial vehicle communication interference detection method and system, and belongs to the technical field of signal detection, and the method comprises the steps: monitoring the current communication state of an unmanned aerial vehicle in real time, determining real-time communication data, and obtaining the historical communication parameters of the unmanned aerial vehicle in a normal flight state; analyzing the real-time communication data and the historical communication parameters, and determining an abnormal frequency band signal, an abnormal strength signal and an abnormal power signal; determining a sub-autocorrelation matrix of each abnormal sub-signal and the actual interference time and the actual interference position of the interference source; and carrying out interference classification on the actual interference time and the actual interference position of the interference source of all the abnormal sub-information, and determining an interference suppression strategy of each interference classification. The communication abnormity of the unmanned aerial vehicle can be found in time, communication interruption, data loss or flight deviation caused by interference are reduced, the task success rate and flight safety of the unmanned aerial vehicle are improved, the communication stability and reliability of the unmanned aerial vehicle are improved, and the stability of a communication link is ensured.

The invention relates to the technical field of picture rendering, in particular to a media picture rendering optimization method and system based on artificial intelligence. The method comprises the following steps: acquiring a terminal video stream; performing RGB format conversion on the terminal video stream to generate an RGB type frame image set; pixel partitioning is carried out on the RGB type frame image set, and RGB pixel matrix blocks are generated; performing color space acceleration conversion on the RGB pixel matrix block to generate a YUV cache data matrix; the YUV storage data matrix is sent to a DSP internal processing unit for key frame selection, and YUV key video frame data and YUV non-key video frame data are obtained; and performing intra-frame coding on the YUV key video frame data so as to generate YUV key frame coded data. According to the method, the media picture rendering efficiency is improved by optimizing data processing, transmission and rendering and combining user visual focus analysis.

The embodiment of the invention discloses a power management method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring state information of a chip, wherein the state information comprises a power management state of the chip; if the power management state represents that the target management item of the chip is power-off management, generating a power control instruction based on the power-off management; electric connection between the Ethernet and the chip is cut off based on the power supply control instruction, and a power-on state between the Ethernet and the controller is kept; and if the power-off between the Ethernet and the chip is completed, controlling the power-off operation between the Ethernet and the controller. According to the embodiment of the invention, electric leakage of the input and output ports can be avoided, the problem of chip burnout caused by electric leakage is solved, and the chip can be ensured to quickly respond and be switched to a correct power supply state when needed through fine power supply management.

The invention discloses a new energy station cross-gatekeeper remote data acquisition method and system, and the method comprises the following steps: a station first area data acquisition server collects data from new energy station equipment, and carries out the analysis and conversion of the data, and forms standardized station real-time data; 2, according to the standardized station real-time data, the data are transmitted in a one-way mode through an isolation device, and the station data are set to be transmitted from the inside to the outside; step 3, according to the data transmitted by the isolation device, the station three-area data forwarding server performs deep standardization processing on the data of different protocols, uniformly converts the data into an internal format, and adjusts a data forwarding strategy according to a dynamic configuration requirement; and step 4, according to the data in the unified internal standardized format, publishing the data by using message middleware, and carrying out serialized compression by using a Probuf technology for data acquisition and transmission in a new energy station cross-gatekeeper environment. The efficiency of operation and maintenance personnel is improved, and the reliability management level of auxiliary equipment is improved.

The invention discloses a communication method and system for on-line monitoring data of a power transmission line. Relates to a signal processing method and device. In order to overcome the problem of data loss or transmission errors caused by the fact that existing power transmission line data are transmitted through a power line, the method comprises the following steps: collecting power transmission line state data, modulating the power transmission line state data to a power transmission line state carrier signal, and transmitting the power transmission line state carrier signal through the power line; detecting the real-time state of the power line at the moment t; taking the real-time state of the power line at the t moment as input, and predicting an estimated state of the power line at the t + 1 moment through a power line state prediction model; and according to the estimated state of the power line at the t + 1 moment, selecting a corresponding signal processing strategy at the t + 1 moment to process the state carrier signal of the power transmission line.

The invention discloses a medical information cloud platform data dynamic encryption uploading method, and relates to the technical field of medical information cloud platform data. Acquiring various parameter information generated in the process of uploading the locally encrypted medical information to the cloud, wherein the parameter information comprises network security information and network transmission quality information; by monitoring the network security and transmission quality information in real time, potential abnormal hidden dangers are recognized in time, and the data loss and damage risks in the medical information uploading process are remarkably reduced. By means of comparison between the transmission abnormal index and the preset reference threshold value, the system can quickly judge the risk state of the uploading process and take corresponding early warning measures. The intelligent monitoring and feedback mechanism not only ensures the integrity and accuracy of medical information, but also can quickly respond in emergency, and reduces the risk of misdiagnosis, treatment delay or drug use error, thereby effectively protecting the health and safety of patients.

The invention relates to the technical field of low-rank tensor recovery, in particular to a low-rank tensor recovery method and device based on a weighted tensor tubular nuclear norm partial sum and a storage medium. By introducing a weighted partial singular value threshold WPSVT, different weights are distributed in the singular value of the tensor, and a more accurate low-rank tensor recovery model is formed. Specifically, the method comprises the following steps: firstly, defining a weighted tensor tubular nuclear norm part and a WPSTNN model, ignoring first r singular values of a tensor sheet, and distributing decreasing weights for the residual singular values; and then, converting a minimization problem into a weighted truncated nuclear norm form, and carrying out step-by-step solution by using an alternating direction multiplier method ADMM. The method shows an excellent recovery effect in tasks of image completion, image denoising, video separation and the like, and can still realize higher peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) when data is incomplete or noise exists, so that the data recovery precision is remarkably improved.

This invention discloses a method for optimizing positioning trajectory data loss in low power mode, which is applied to a mobile terminal with single Beidou positioning function. The method includes the following steps: (1) Hardware configuration: The main control module controls the power supply of the Beidou chip and interacts with the Beidou chip through the serial port; the antenna module is configured, the antenna material selection and placement are optimized, a backup power supply is configured for the Beidou module, and the low noise amplification factor of the antenna LAN is increased. This method for optimizing positioning trajectory data loss in low power mode ensures stable power supply of the Beidou chip and sensitive antenna signal reception by optimizing antenna selection and placement, configuring backup power supply, and increasing low noise amplification factor. It reduces positioning failure and data loss caused by weak signal and power interruption, and lays the hardware foundation for continuous trajectory recording.

This invention discloses an integrated intelligent monitoring system for air, space, and water using a wind-solar hybrid power supply, specifically relating to the field of intelligent monitoring. It includes a wind-solar hybrid power supply module, a sensing and monitoring module, a wireless self-organizing network communication module, and an intelligent management and control module. The wind-solar hybrid power supply module provides clean energy; the sensing and monitoring module collects environmental and operational data; the wireless self-organizing network communication module enables bidirectional data transmission and interaction between monitoring nodes; and the intelligent management and control module performs fusion analysis of multi-source data, water quality level prediction, and early warning triggering. The operation of the wind-solar hybrid power supply module specifically includes the following: classifying power supply differences into different levels based on power supply evaluation differences. This invention achieves long-term unattended, accurate, and efficient monitoring in outdoor scenarios without mains power through stable wind-solar hybrid power supply, comprehensive air, space, and water monitoring, reliable Mesh network transmission, and intelligent analysis, early warning, and dynamic optimization.

The invention relates to the technical field of signal enhancement, in particular to a high-efficiency wireless signal enhancement method and system, and the method comprises the steps: obtaining a current wireless signal and a historical wireless signal, determining a signal transmitting position and a signal receiving position according to the current wireless signal, the method comprises the following steps: screening historical wireless signals based on a receiving and transmitting range between a signal transmitting position and a signal receiving position to obtain reference wireless signals, performing signal transmission fluctuation analysis on the reference wireless signals to obtain a signal transmission curve and a transmission label, training a signal enhancement model to obtain a signal enhancement model, and performing signal transmission analysis on the signal enhancement model to obtain a signal enhancement result. And performing signal transmission fluctuation analysis on the current wireless signal to obtain a current signal curve, inputting the current signal curve into the signal enhancement model for enhancement to obtain an enhanced current signal curve, and generating a wireless signal to be transmitted based on the enhanced current signal curve. According to the invention, the transmission efficiency of the wireless signal is improved.

The embodiment of the invention provides a GPU fault early warning processing method and computing equipment, the method is applied to first computing equipment, and the method comprises the steps that early warning information of a target GPU is acquired; the early warning information is determined based on working feature information of the target GPU in a computing node; determining a check point adjustment strategy according to the early warning information; the check point adjustment strategy is a strategy used for adjusting the trigger frequency of a check point of a target GPU instance, and the target GPU instance is a GPU instance running a calculation task in the target GPU; and adjusting the trigger frequency of the check point of the target GPU instance according to the check point adjustment strategy. According to the method provided by the embodiment of the invention, the progress loss caused by the GPU fault can be effectively and reasonably reduced, the data loss caused by the GPU fault can also be reduced, the utilization efficiency of computing resources is improved, and the overall performance and stability of the system are also improved.

The present invention discloses a hospital internal audit data processing system and method. According to the technical solution provided by the present invention, the system includes: an audit plan module, an audit preparation module, an audit implementation module, an audit report module and an audit rectification module; the audit plan module is used to prepare various types of audit plans, establish and manage audit projects; the audit preparation module is used to manage pre-audit matters of audit projects; the audit implementation module is used to perform data analysis and manuscript management during the audit process, and obtain audit results; the audit report module is used to feedback audit results and generate audit reports; the audit rectification module is used to send audit rectification notices, obtain feedback on rectification, and identify rectification. Through the present invention, different audit plans and audit projects are created according to the demand type, and data is sorted or encrypted, which enhances data standardization and transmission security, completes the integration from data collection to report sending and automatic archiving, and improves efficiency.

The invention discloses a method for screening toxic components of traditional Chinese medicine by using a MACCS structural similarity model constructed based on vibrio fischeri, and belongs to the technical field of toxicity evaluation. In order to solve the technical problems of partial data loss and low screening efficiency when a model constructed based on conventional QSAR is used for screening drug toxic components, an MACCS structural similarity model is constructed based on Vibrio fischeri toxicity data, and screened traditional Chinese medicine components and toxic components in the model can be directly subjected to similarity matching; and the data loss of the data in the processes of model construction, data conversion and the like is reduced. The model can be used for screening toxic components of the traditional Chinese medicine, can detect trace toxicity of the traditional Chinese medicine or evaluate compatibility toxicity of the traditional Chinese medicine, and has the advantages of rapidness, repeatability, economy, high efficiency and the like.

The utility model relates to the technical field of storehouse control cabinet protection, and discloses an intelligent storehouse control cabinet which comprises a cabinet body, a dustproof cover, a protective door, a top air outlet dustproof net, a heat dissipation device composed of a fan, a heat dissipation piece and high heat conduction silica gel, and an air inlet filtering device composed of a bottom air inlet dustproof net, an intermediate filtering net and a fine filtering net. The top of the cabinet body is provided with a dustproof cover, the bottom of the dustproof cover is cooperatively connected with the top of the cabinet body through adaptive screws, the side wall of the cabinet body is provided with two protective doors which are distributed in an axial symmetry manner, the cabinet body is internally provided with a heat dissipation device, and the top of the heat dissipation device is provided with a top air-out dustproof net. According to the control cabinet for the intelligent storeroom, the internal structure is simple and reasonable, and efficient work of electronic devices in the control cabinet is effectively guaranteed through the matching effect of the heat dissipation device and the air inlet filtering device.

The utility model relates to force sensor technical field, concretely is robot six -dimensional force sensor, including the casing, the casing one side is equipped with the apron, the other side is equipped with the movable end connecting seat, and the movable end connecting seat is connected with robot movable arm, and the casing is away from the movable end connecting seat one side and is connected with the drive end of robot, and the casing middle part is provided with the intermediate body, and the intermediate body outside is equipped with a plurality of elastic beams, and the elastic beam outer end is equipped with the strain gauge. In the robot six -dimensional force sensor, through the elastic beam of intermediate body outside annular equidistance arrangement, the strain gauge of combination outside end installation, form the efficient force - electricity conversion structure, can accurate perception three -dimensional space in the force and the moment change, provide accurate force sense information feedback for robot, effectively promote the operation accuracy of robot in precision assembly, force control polishing etc.

The invention provides a power state monitoring management system and method for an intelligent terminal assembly, and the system comprises a data collection module which is used for periodically obtaining real-time power utilization data and chip temperature from a power management chip of the assembly, and the power utilization data comprises voltage and current; the data analysis module is used for recording and analyzing the data acquired by the data acquisition module and judging whether a power supply abnormal condition exists or not; and the power supply exception handling module is used for executing three-level exception handling including power supply exception state alarm reporting, component resetting and system restarting. Through innovative comprehensive power supply management, a more comprehensive and efficient power supply working state monitoring and exception handling scheme is provided for the intelligent terminal equipment, so that the reliability and stability of the intelligent terminal can be improved, the power supply use efficiency can be optimized, the service life of the equipment is prolonged, and the cost is reduced. And a normal working state can be quickly recovered when an abnormality occurs, so that potential data loss and equipment damage risks are reduced.

The invention relates to the technical field of software running monitoring, and particularly discloses a method and device for monitoring the running state of an application program and computer equipment. The method comprises the steps that real-time running parameters and a real-time code execution path of the application program are collected; the real-time operation parameters and the real-time code execution path are input into a monitoring model, and the monitoring model is used for executing a real-time monitoring step and outputting the operation lagging probability of the application program and the real-time code execution path; and receiving the running lagging probability and the real-time code execution path output by the monitoring model, and sending a lagging early warning notification. According to the method and the device, the running lagging condition of the application program can be predicted in time, and the user can be notified, so that the user can clean the memory or reduce the CPU proportion in time according to the early warning notification, the application program data can be stored in time, the data loss caused by application program lagging and crash is reduced, and the stability of the application program is improved.

The invention relates to a multi-modal data correction method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining target multi-modal data, and generating a corresponding initial text based on the target multi-modal data, the target multi-modal data at least comprising voice data; sending the initial text to a plurality of terminals, so that the plurality of terminals perform real-time labeling operation based on the initial text to obtain collaborative labeling data; receiving collaborative annotation data sent by the plurality of terminals, and generating a collaborative annotation result according to the collaborative annotation data; and based on the collaborative labeling result, correcting the initial text to generate a corrected text. Therefore, a multi-user real-time collaborative labeling and dynamic correction mechanism is introduced in a multi-mode voice transcription process, and adaptive optimization and elastic computing power scheduling are combined, so that real-time editability, collaborative consistency and high accuracy of a transcription text are realized, and meanwhile, stable operation of a system in a high-concurrency scene is guaranteed.

The present invention relates to the field of cultural heritage protection and restoration technology, and specifically to an artificial intelligence-assisted cultural relic digital reproduction system, including a data acquisition module, a data processing module, a data storage module, an artificial intelligence analysis module, an interactive display module, and a user interaction module, wherein the data acquisition module acquires the geometric shape, color, material, and surface texture data of the cultural relic, the data processing module generates a three-dimensional model of the cultural relic, the data storage module stores the three-dimensional model data, the artificial intelligence analysis module extracts the historical information and cultural background of the cultural relic, the interactive display module combines virtual reality technology to realize the interactive display of the cultural relic, and the user interaction module dynamically adjusts the display content of the cultural relic according to the user's input information. The artificial intelligence analysis module of the present invention analyzes the three-dimensional model data of the cultural relic, extracts the historical information and cultural background of the cultural relic, and while viewing the cultural relic, understands the historical and cultural stories behind it, thereby increasing the educational significance of the cultural relic display.

This invention relates to the field of electricity meter fault identification, specifically a method and system for electricity meter fault identification. The electricity meter data acquisition module comprehensively collects the meter's display status, communication signal strength, current parameters, and voltage parameters. The electricity meter data analysis module analyzes these parameters and sends the analyzed signals to a fault identification and repair module. The fault identification and repair module accurately determines the fault type of the electricity meter and performs repairs. This invention improves the accuracy of electricity meter monitoring; comprehensive parameter acquisition combined with accurate fault type identification allows for timely detection of potential problems and rapid location and repair. This invention aims to improve the accuracy of electricity meter monitoring, the reliability of communication, and the efficiency of management through the acquisition, analysis, and processing of multiple electricity meter parameters, providing strong support for the stable operation and intelligent management of power systems.

This invention belongs to the technical field of runtime dependency environment consistency assurance, and particularly relates to a method and system for ensuring runtime dependency environment consistency of synchrotron radiation source IOCs. It involves real-time file event monitoring of a preset control resource directory on a beamline control host. The control resource directory includes control interface files, control scripts, and configuration files that IOC instances depend on for startup and operation. If file creation, modification, deletion, movement, or attribute change events are detected in the control resource directory, the target control resource file that has been changed is extracted. Based on a pre-constructed IOC runtime dependency relationship model, at least one target IOC instance affected by the change in the target control resource file is identified. The IOC runtime dependency relationship model is used to characterize the one-to-one correspondence between each IOC instance and the set of control resource files it depends on.

The invention relates to the technical field of management, and discloses a machine room construction management system. Comprising a hardware infrastructure module, a virtualization technology unit, a cloud management platform unit, a data storage and management unit, a monitoring and alarm unit, a computing resource management module, a report analysis module, a user management and authority control unit, a safety management unit, an energy consumption management unit, an environment monitoring module and a central processing unit. Based on the cloud computing technology, through centralized computing and resource storage of cloud computing, accessed computers can obtain strong processing capacity without high configuration, different computer rooms tend to be balanced due to reduction of computing requirements, the overall resource use is more efficient, the centralized management of cloud computing simplifies the work of system maintenance, and the service life of the system is prolonged. And after the computer room adopts the cloud computing technology, high-level safety guarantee measures can be enjoyed, and the risks of data loss and system crash are reduced.

The disclosed embodiments provide a method, device, storage medium and electronic device for detecting anomalies in SQL logs, which relate to the fields of network technology and security technology, and are used to solve the problem of low efficiency of SQL log anomaly detection methods in related technologies. The SQL log anomaly detection method involved includes: obtaining a structured query language SQL log to be tested; extracting SQL operation data from the SQL log to be tested, and obtaining a test sequence based on the SQL operation data; generating a word vector for each word in the test sequence based on the test sequence and the word vector library obtained by pre-training, and obtaining a test word vector sequence; calculating the similarity between the word vectors in the test word vector sequence; and determining whether there is an abnormal SQL operation in the SQL log to be tested based on the similarity. The disclosed embodiments can quickly locate anomalies in SQL logs and reduce data loss caused by SQL log anomalies.

The invention discloses a trusted computing protection method and system based on a desktop terminal, and the method comprises the following steps: (1) obtaining the current of each power line of the desktop terminal at each time point and the radio frequency of each signal line at each time point, and analyzing the qualification index of the electromagnetic compatibility of the desktop terminal; (2) performing virus detection on each system of the desktop terminal to obtain a virus immune coefficient of each system of the desktop terminal, acquiring the virus immune coefficient of each system of the desktop terminal, and analyzing a body safety protection qualification index of the desktop terminal; (3) detecting the desktop terminal by using IP encryption and full self-developed firmware to obtain backup data of the desktop terminal; (4) analyzing and displaying a trusted computing protection conformity index of the desktop terminal based on the obtained electromagnetic compatibility qualification index of the desktop terminal, the body safety protection qualification index of the desktop terminal and the data backup safety index of the desktop terminal; the occurrence rate of the problem of data loss of the desktop terminal is reduced, and then the occurrence rate of the problem of virus infection of the desktop terminal is reduced.

The invention relates to a virtual bus equipment transmission method based on BLE (Bluetooth Low Energy) and WiFi (Wireless Fidelity) P2P (Peer-to-Peer), which comprises the following steps of: initializing and registering virtual bus equipment, and acquiring registration information such as name, type, network configuration and the like; broadcast pairing is carried out through the BLE technology, a pairing request is obtained, and target virtual receiving equipment is screened out; and establishing network connection through a WiFi P2P technology, and establishing a data transmission path between the virtual bus equipment and the target virtual receiving equipment. And performing data transmission by using the path, wherein the result comprises a success or failure state. If the data transmission succeeds, the data transmission is completed; if the data transmission fails, data transmission is tried again; the problem that connection is unstable or data transmission fails under the condition of poor signal quality although the WiFi P2P technology in the traditional method has a high rate during connection establishment and data transmission is solved.

The invention relates to physiological multi-parameter monitoring equipment suitable for a plateau tunnel environment. Belongs to the technical field of environmental monitoring and biomedical engineering. Comprising a power supply module, a gateway, a network management module, a health monitoring module and an environment monitoring module, the power supply module is connected with the gateway, the gateway is connected with the network management module, the health monitoring module is connected with the gateway, and the environment monitoring module is connected with the gateway; the environment monitoring module comprises a temperature sensor, a humidity sensor, an air pressure sensor, a positioning sensor, an oxygen concentration sensor, a carbon dioxide concentration sensor and an environment display module; the health monitoring module comprises a blood pressure module, a blood oxygen module, a body temperature module, a respiratory rate module, a heart rate module and a health display module. The system has the advantages of equipment integration, comprehensive monitoring indexes, stable data transmission, intelligent processing, visual interface, good applicability, energy saving and environmental protection.

The invention provides a data communication gateway machine for improving communication quality of a serial port and a network port, and the data communication gateway machine adopts an advanced signal processing algorithm and a high-performance hardware architecture in a software and hardware combination mode; specifically, a main control unit, a serial port interface module, a network port interface module and a power supply module are arranged for hardware, and a shielding layer and grounding are improved to increase the anti-interference capability of the hardware so as to reduce signal interference at a physical level; software sets data caching and optimization, a protocol management module and error detection and correction, a TCP congestion control algorithm is adopted to realize priority-based flow control, and the transmission rate is controlled mainly through four core stages of slow start, congestion avoidance, rapid retransmission and rapid recovery. And the functions of congestion signal sensing, SP strategy, long-term target, stability improvement, efficient communication and intelligence are set, the influence of high-frequency noise is reduced by using a moving average filtering algorithm, and the improvement of the communication quality of the serial port and the network port is effectively realized.