589 results about "Data retention" patented technology

The invention discloses a self-adaptive management method and system for intelligent terminal equipment of a distributed power distribution network. According to the method, a self-organizing peer-to-peer communication network covering the whole network is constructed, and neighbor discovery and information sharing among intelligent terminal devices are achieved; the terminal independently completes control instruction calculation based on the local electrical parameters and a preset multi-objective function and optimizes an area control effect through a cooperation mechanism; introducing a self-adaptive adjustment strategy of a control algorithm; when abnormal operation is detected, the terminal can autonomously complete fault positioning and isolation, and power supply recovery is realized based on standby path judgment or micro-grid switching; the central management unit periodically carries out acceptance capacity evaluation, and terminal model parameters are aggregated in a federated learning mode; the terminal has an edge autonomous capability, and can maintain local control and data retention when communication is interrupted. The system has the characteristics of quick response, flexible structure, intelligent cooperation, high adaptability and the like, and is suitable for intelligent operation and management and control scenes of various types of power distribution systems.

The invention discloses an optimization method and device for reading performance of a flash memory in a controller and a storage medium, and belongs to the technical field of flash memories.The method comprises the steps that a preset characteristic quantity, the number of erasing and writing reading times and data retention time are input into a current prediction model to obtain a reading voltage offset interval; the method for predicting the threshold voltage distribution of the flash memory according to the use condition of the flash memory is more real-time; on the basis of reading the voltage offset interval, performing read retry operation; during read retry operation, only one offset value of read voltage is adjusted to change in each page, and other voltage offset values in the same page change along with the change of the offset value of the read voltage; through the correlation of different read voltage deviation values of the same page, the number of times of re-reading is greatly reduced, the re-reading time is shortened, the reading performance is improved, the current prediction model is further updated and stored by utilizing threshold voltage distribution data determined by the read re-try operation, and the updated prediction model is used for the next read operation, so that the prediction accuracy is improved.

The embodiment of the invention discloses an in-memory computing circuit based on a magnetic cache, and the circuit comprises at least one magnetic cache unit, at least one in-memory computing unit, and a timer. The magnetic cache unit in the at least one magnetic cache unit is used for caching data output by the corresponding in-memory computing unit as to-be-processed data within the corresponding data retention time; the timer is used for respectively setting data retention time for the at least one magnetic cache unit; and the in-memory computing unit in the at least one in-memory computing unit is used for extracting the data to be processed from the corresponding magnetic cache unit for calculation and outputting the computed data to other magnetic cache units. According to the embodiment of the invention, the invention achieves the flexible adjustment of the data retention time of the magnetic cache unit in various in-memory calculation scenes, and achieves the provision of a high-capacity cache for the data needed by in-memory computing under the lower power consumption.

An AI and machine learning-based system for automating employee management and work information processing within an organizational structure, the system comprising: a central processing module configured to aggregate and pre-process data from multiple sources, including attendance records, performance logs, task management systems, and communication channels, with the central processing module normalizing and filtering the data to ensure consistency and accuracy in real-time analysis; a machine learning-based analysis unit operatively connected to the central processing module, the analysis unit comprising a natural language processing (NLP) sub-module, a sentiment analysis sub-module, and a pattern recognition sub-module, and configured to extract, analyze, and interpret both structured and unstructured data for insights into employee behavior and performance assessment, and further configured to adapt and refine models based on continuous data inputs from the central processing module; a predictive task scheduling component comprising a reinforcement learning-based model that leverages employee skill profiles, historical task completion rates, and workload patterns to dynamically distribute tasks, with the predictive task scheduling component further configured to self-optimise based on real-time feedback regarding task completion efficiency, priority changes, and schedule adjustments within the organization; a performance tracking unit configured to receive inputs from the central processing module and the machine learning-based analytics unit, wherein the performance tracking unit continuously monitors employee performance, challenges, and areas for improvement and stores these insights in individualized, encrypted employee profiles that can be accessed in real time, thus supporting data-driven performance reviews and improvement plans; an input / output interface for user interaction, the interface providing managers with interactive access to review employee metrics, task assignments, and performance feedback, and enabling employees to securely view individual performance metrics, feedback, and task details, the interface further being configured with user-level access controls based on historiographical organizational roles; a secure data storage component configured to securely store employee data, task logs, and performance metrics, where the data storage component supports both local and cloud-based storage solutions, uses encryption protocols for secure data retention, and provides access control mechanisms for authorized retrieval of stored data; a communication interface module operatively connected to the central processing module and configured with multi-protocol communication capabilities, including Wi-Fi, Ethernet, and Bluetooth, wherein the communication interface module facilitates real-time data synchronization between remote and local devices and is integrated with an AI-based anomaly detection system that flags irregularities or potential security threats in data transmissions; and an adaptive learning module operatively connected to the machine learning-based analytics unit and configured to continuously retrain machine learning models based on real-time data inputs, where the adaptive learning module uses reinforcement learning and unsupervised learning techniques to refine task recommendations, adjust performance metrics, and optimize task assignment rules based on the evolving needs of the organization.

A controller, of a solid state drive (SSD), may perform, on one or more blocks of a non-volatile memory device of the SSD, read operations using pre-determined threshold voltages associated with two overlapped charge states. The read operations may be performed after a power-on condition following a power-off condition on the non-volatile memory device. The controller may determine, using a machine learning model, a change in threshold voltages associated with the two overlapped charge states, after the power-off condition. The machine learning model may determine the change in threshold voltages using bit error rates associated with the read operations. The machine learning model may be trained to determine changes in threshold voltages for the two overlapped charge states, after power-off conditions. The controller may determine adjusted threshold voltages associated with the two overlapped charge states based on the change in threshold voltages.

The invention provides a dynamic latch, comprising an input terminal for inputting a first data; an output terminal for outputting a second data; a clock signal terminal for supplying a clock signal; a data transmission unit for transmitting the first data under control of the clock signal; and a data output unit for converting the first data into the second data. The data transmission unit and the data output unit are sequentially connected in series between the input terminal and the output terminal, and a node is provided between the data transmission unit and the data output unit. The dynamic latch further comprises a data retention unit electrically connected to the node. The retention time of data can be effectively extended, thereby improving data security and accuracy.

The invention provides a method and system for optimizing reading reference voltage of a three-dimensional NAND flash memory, and relates to the technical field of semiconductor memorizes.The method comprises the steps that the erasing frequency and the data retention time of the three-dimensional NAND flash memory are obtained; if the data retention time is not clear, inversely deducing the time through a sampling adjustment method, inputting the inversely deduced data retention time and erasing times into an optimal read reference voltage prediction model, and outputting an average optimal offset value of each read reference voltage; if so, substituting the two parameters into an optimal read reference voltage prediction model to output an average optimal offset value of each read reference voltage; and finally, compensating the average optimal offset value of each read reference voltage by using the interlayer difference table, and outputting all optimal read reference voltages of each layer. According to the method and the device, the accuracy of reading reference voltage optimization strategy prediction can be improved, the time overhead is reduced, and the reading performance is improved.

Systems and methods for novel uses and / or improvements to data migration. In particular, systems and methods for data migration of metadata stored in object storage from one container to another, especially in instances when the metadata is destined for ingestion by an artificial intelligence application. The systems and methods ensure that all metadata (e.g., metadata stored in object storage) is preserved during data migration, including metadata such as content type, object lock mode, object lock retain until date, and / or custom metadata.

An apparatus, including: a first multiplexer including inputs configured to receive an input data signal and a scan signal, and a select input configured to receive shift control signal; a first latch including an input coupled to an output of the first multiplexer, and a complementary (e.g., inverting) clock input configured to receive a clock signal; a second latch including an input coupled to the output of the first multiplexer, and a non-complementary clock input configured to receive the clock signal; and a second multiplexer including inputs coupled to outputs of the first and second latches, respectively, a select input configured to receive the clock signal, and an output configured to generate an output data or scan signal.

The invention discloses a security storage chip energy consumption optimization method based on multi-objective optimization, and relates to the technical field of energy consumption optimization, and the method comprises the steps: inputting the threshold voltage distribution characteristics of a security storage chip of a candidate parameter set into an aging model, fitting the rule of the threshold voltage distribution characteristics along with the time under an accelerated aging condition, and obtaining an aging model; aging model parameters are obtained; calculating the data retention failure rate of the security storage chip in the target life cycle by using the aging model parameters, and obtaining an extended feasible region of the instant erasure security constraint and the long-term retention security constraint in combination with a data retention judgment standard; and establishing a multi-objective optimization function with reduction of operation energy consumption and maintenance energy consumption as optimization objectives in the extended feasible region, and obtaining a candidate solution set through a multi-objective optimization algorithm. According to the method, data retention prediction in the life cycle is realized, and energy consumption optimization and long-term reliability constraint are combined.

A data storage device tracks information about the ages and read counts of blocks of memory, which are indicative of data retention and read disturb issues, respectively. The data storage device uses a machine-learning model to predict which blocks in the memory are likely to contain errors based on the tracked information, and a read scrub operation is performed only on those blocks. Limiting the number of blocks that are read scrubbed reduces read amplification and reduces the time required for the read scrub process.

The invention provides a memory structure and a preparation method thereof. The method comprises the following steps: providing a substrate; depositing a floating gate layer on one side of the substrate; etching the floating gate layer to form a plurality of floating gate structures; a plurality of separated floating gates are formed through photoetching, a gap is formed between every two adjacent floating gates, the section of each floating gate is of a trapezoidal structure, the upper bottom of each trapezoidal structure faces the corresponding gap, and the lower bottom of each trapezoidal structure faces the corresponding selection gate; performing ion implantation on the substrate in alignment with a gap position between the floating gates to form a source end; a control gate is formed on one side of the source end, the control gate is located between every two adjacent floating gates, and the two floating gates located on the two sides of the control gate are symmetrically arranged relative to the control gate. The data retention capability of the memory is improved by changing the shape of the floating gate, damage to the tunneling oxide layer during source end ion implantation is avoided, part of existing process steps are reduced, the quality of the memory is improved, and the preparation efficiency is improved.

The invention belongs to the technical field of aerospace, and discloses an aviation electrical system insulation detection device which comprises a shell and an overall frame serving as the insulation detection device. The display screen is used for displaying measurement data in real time; the function key group integrates the functions of measurement mode switching, data retention and insulation test starting; according to the conversion assembly, through the linkage design of the rotating disc and the rotating switch, the problem that functions cannot be switched when the two hands of a traditional insulation detection device are occupied is thoroughly solved, a worker only needs to rotate the rotating disc with the hand of supporting equipment, the rotating switch can be driven through the driving mechanism, switching of insulation test voltage gears is completed with one hand, and the working efficiency is improved. Compared with a traditional device which needs to frequently put down a connecting line and manually rotate a switch, the design simplifies the operation steps from three steps to one step, shortens the single function switching time, and remarkably improves the efficiency and safety of high-altitude operation or narrow space detection.

A computer-implemented method of using a blockchain to provide proof of a data retention policy, wherein a smart contract defines one or more respective data retention requirements for storing data items at a storage location, and wherein the method comprises: receiving a data item and / or an encrypted version thereof, and one or more data retention details of a retention policy; supplying, to a smart contract, the data item and / or the encrypted version thereof, and the data retention details; and executing the smart contract, wherein the smart contract is configured to, when executed: determine whether the data retention details satisfy the data retention requirements; and if so, submit a transaction to the blockchain, wherein the transaction comprises the data retention details and at least one of: the data item, the encrypted version thereof, a reference to where to the data item is stored at the storage location.

The invention relates to the technical field of unmanned aerial vehicle autonomous control or cloud-side cooperative robot control, in particular to an unmanned aerial vehicle harmful gas distribution monitoring system based on a cloud platform, and the system comprises a communication quality analysis unit which generates a communication quality comprehensive index; the decision authorization migration unit generates a decision authorization factor; the cloud fusion updating unit generates a cloud planning waypoint; the airborne data processing unit generates airborne autonomous waypoints and data retention factors; the collaborative path planning unit is used for performing weighted fusion on the cloud planning waypoint and the airborne autonomous waypoint when the decision authorization factor is lower than an autonomous mode activation threshold value, and generating a final execution waypoint; when the decision authorization factor is greater than or equal to the autonomous mode activation threshold, setting the cloud planning waypoint as a final execution waypoint; according to the invention, the inherent contradiction between cloud centralized control and airborne autonomous detection is solved, and the overall toughness and efficient execution of a monitoring task are ensured.

The invention relates to application of a transistor device with a storage function, and belongs to the technical field of semiconductor devices. In order to solve the problems of poor reliability, low integration level and the like caused by lack of a proper charge trap medium in the existing two-dimensional charge trap memory, the invention proposes that two-dimensional lead iodide (PbI2) is adopted as a charge trap layer, and efficient charge trapping is realized by utilizing the natural iodine vacancy defect of the two-dimensional lead iodide (PbI2). According to the device, a two-dimensional semiconductor material (such as WSe2) and PbI2 are integrated through a Van der Waals heterostructure to form a grid-control storage unit. The device has the advantages of large storage window, high switch ratio, high writing speed, multi-level storage capability, high durability and long data retention time. The invention provides an innovative solution for the nonvolatile memory with high integration level and low power consumption.

The invention relates to the technical field of storage, and discloses a threshold voltage processing method of a solid state disk, a data reading method and related equipment. The threshold voltage processing method comprises the following steps: selecting a crystal grain in a frequent rereading state in a solid state disk as a target crystal grain; obtaining the optimal threshold voltage of the target crystal grain; and setting the optimal threshold voltage as the threshold voltage of all the blocks in the closed state in the target crystal grain. According to the method, the threshold voltage deviation problem of the solid state disk can be compensated, the read-write performance of the solid state disk under the scenes of data retention, read interference, cross temperature and the like is effectively stabilized, performance reduction and stability fluctuation caused by repeated rereading are reduced, the data reading efficiency is remarkably improved, the maintenance cost is reduced, and the service life of the solid state disk is prolonged. Reliability of the solid state disk is further improved, and service life of the disk is prolonged.

The invention discloses a surgical suture sample detection method, system, storage medium and device, and the method comprises the steps: obtaining a shot image of a suture sample, the shot image comprising a front image and a back image; after the shot image is preprocessed, a region of interest is extracted, and the region of interest corresponds to a binary suture region image; edge optimization is carried out on the region of interest, and defect detection is carried out on the optimized binary suture region image; and extracting a defect detection result, calculating a qualified rate to output a detection report, and binding the defect detection result with the current suture sample number for filing. Through double-camera design, the transparent conveyor belt and an optimized image processing algorithm, the problems of low detection efficiency, single-angle detection and insufficient data retention in the prior art are solved, and high-efficiency, comprehensive and real-time surgical suture quality detection is realized.

The invention relates to the technical field of solid state disks, and discloses an optimization method and device for SSD open data block timeout check, computer equipment and a storage medium. The method comprises the following steps: traversing all open blocks one by one to obtain a next open block; obtaining the temperature of the current SSD, and querying a corresponding data retention coefficient; calculating according to the data retention coefficient to obtain a timeout accumulated record value of the open block; judging whether the overtime accumulated record value of the open block exceeds a processing threshold value or not; and if the overtime accumulated record value of the open block exceeds a processing threshold, triggering open block processing to obtain a processing result. According to the method, the SSD temperature is introduced to correct the timeout time of the open block, the time accuracy of timeout processing can be improved, and write amplification caused by open block processing is reduced as much as possible on the premise of avoiding the data retention problem.

The embodiment of the invention discloses an application upgrading method and device, equipment, a terminal, a storage medium and a program.The method is applied to an operation system of a WebAssembly virtual machine and comprises the steps that a first upgrading instruction initiated by a to-be-upgraded application is received; the first upgrading instruction comprises application data retention indication information of the to-be-upgraded application; obtaining an old-version application corresponding to the to-be-upgraded application and an application data object of the old-version application according to application data retention indication information included in the first upgrading instruction, and storing application data in the application data object of the old-version application; receiving a second upgrading instruction initiated by the to-be-upgraded application; and recovering the application data in the application data object of the old-version application to the application data object of the new-version application corresponding to the old-version application according to the second upgrading instruction. According to the technical scheme provided by the embodiment of the invention, the application upgrading flexibility in the operation system of the WebAssembly virtual machine can be improved.

To reduce cost of the cloud in retaining data at an on-premise side and cloud side.SOLUTION: A first storage system 100 stores data related to execution of a first server in a logical volume, and transmits the data stored in the logical volume to a second storage system 300. The second storage system 300 provides a virtual volume to the second server, and stores the data received from the first storage system 100 in the virtual volume. The second storage system 300 executes a process by using data stored in the virtual volume at each execution timing. Then, the second storage system 300 determines whether the data stored in the virtual volume is left in the virtual volume or is discarded based on the presence or absence of an access and the type of access, which are access statuses to the data at each execution timing, and discards the data determined to be discarded from the virtual volume.SELECTED DRAWING: Figure 21

The embodiment of the invention provides a visual model system, a visual model construction method, a visual task processing method, an image generation method, a video generation method, an information processing method based on a visual model and a cloud training platform. The visual model comprises at least two feature processing modules and at least one tuning module, the feature processing module comprises a plurality of feature processing layers, the tuning module comprises a plurality of tuning layers, and the plurality of tuning layers are respectively connected with the feature processing layers of the corresponding levels in the at least two feature processing modules; and the tuning layer is used for receiving the feature data output by the connected feature processing layer and performing tuning processing on the feature data to obtain a tuning result, and the tuning result is used for generating visual data. According to the method, detail information on multiple levels is reserved, more accurate visual data is generated, a feature processing module and an adjustment and optimization module are decoupled, the universality and generation efficiency of a visual model system are improved, the training overhead is reduced, and the training efficiency is improved.

The invention relates to the technical field of 5G wireless image transmission, in particular to a 5G wireless image transmission low-latency transmission method based on dynamic code rate hierarchical coding, which comprises the following steps of: coding each frame of image according to divided levels; dividing the transmission priority of each frame of image; and periodically determining whether the processing for the video is qualified based on the determined jitter influence parameter, adjusting a preset kurtosis used for dividing the hierarchy to a corresponding value when the processing for the video is determined to be abnormal, and adjusting the processing parameter for the video based on the transmission elasticity quantized value and the data retention characterization value. The transmission priority and the coding hierarchy are divided based on the actual recording condition and the transmission condition, and the coding transmission is carried out by adopting the targeted code rate, so that the video transmission efficiency is improved.

The invention relates to a memristor and a preparation method thereof. The preparation method comprises the following steps: providing an insulating substrate with a bottom electrode formed on the surface; depositing an aluminum oxide thin film on the bottom electrode by adopting electron beam evaporation under a room temperature condition to form a resistive function layer, and not performing high-temperature annealing treatment after deposition is completed, so that a primary oxygen vacancy defect is reserved in the thin film; and then depositing a top electrode on the resistive function layer through thermal evaporation or electron beam evaporation to obtain the memristor. The resistive function layer is an aluminum oxide film which is not densified through annealing, and internal defects of the resistive function layer provide a channel for metal ion migration, so that the reversible resistive characteristic is achieved. The memristor device is simple in structure and suitable for normal-temperature process preparation, the stable resistance switching behavior can be achieved, excessive densification of a film layer and thermal damage of an ITO electrode interface caused by high-temperature annealing are avoided, and the memristor has high cycle durability and nonvolatile data retention capacity and has the stable bipolar resistance change characteristic.

The invention relates to the technical field of flash memories, and particularly discloses a method and related equipment for improving data retention capability of NOR FLASH, and the method comprises the following steps: S1, in the working process of the NOR FLASH, periodically triggering detection and repair operation of the data retention capability based on preset timing, the detection and repair operation of the data retention capability comprises the steps of first reading, second reading and programming repair; in the detection and repair operation process of the data retention capability, if a client operation instruction is obtained, stopping the detection and repair operation of the data retention capability to execute the client operation instruction; according to the method, continuous detection and repair of the data retention capability under long-term work of the NOR FLASH are realized, long-time waiting caused by one-time full-chip scanning after power-on in a traditional method is avoided, a customer request can be responded preferentially, and the problem that customer access is blocked in the maintenance process is solved.

A computer-implemented method and apparatus to generate an image-based localization model for mobile robot navigation. The method includes performing data collection at a plurality of different service locations, to which a fleet of mobile robots is deployable, to generate collected data, performing a data retention operation with respect to the collected data based on a data retention policy, generating a first image-based localization model and a second image-based localization model for a first and respectively, second service location of the plurality of different service locations, using the collected data. The method further includes deploying the first image-based localization model and the second image-based localization model to a first and, respectively, second mobile robot of the fleet of mobile robots, the first image-based localization model and the second image-based localization model being used to navigate the first and, respectively, the second service location of the plurality of different service locations.

The invention discloses a coal-fired boiler combustion optimization method, system and equipment based on machine learning and a medium, and belongs to the technical field of boiler operation optimizing.The method comprises the steps that operation parameter data and generated fly ash carbon content data are collected; constructing a machine learning model, and performing primary training on the machine learning model; the number of operation parameter data is reduced, secondary training is performed on the machine learning model, and the optimal parameter number is determined according to the fitting effect; screening the operation parameter data, and reserving the operation parameter data of which the quantity accords with the optimal parameter quantity; the method comprises the following steps: constructing a fly ash carbon content prediction model, optimizing an extreme value of the fly ash carbon content prediction model through an optimization algorithm, and determining an optimal boiler combustion operation parameter, and solves the problems that the actual measurement workload is large and the lowest fly ash carbon content cannot be obtained by only depending on a thermal-state multi-working-condition test and easily deviating from the optimal working condition; the existing prediction method has the problems that a local optimal solution is easy to generate and the generalization ability of a model is low.

Various embodiments include techniques for managing cache memory in a computing system. The disclosed techniques include a cache policy manager that monitors activity of various components that access a common cache memory. The cache policy manager establishes cache rules that determine what data remains stored in cache memory and what data is removed from cache memory in order to make room for new data. As the activities of these components change over time, cache rules that work well for a previous activity profile may no longer work well for the current activity profile. Therefore, the cache policy manager dynamically modifies the cache rules as the activity profile changes in order to select cache rules at any given time that work well with the current activity profile. These techniques are advantageous over conventional approaches that employ static cache rules that work well only for specific activity profiles.

The invention discloses a display panel and a display device. The display panel comprises a plurality of sub-pixels and a pixel circuit connected with the sub-pixels. The driving circuit comprises a plurality of cascaded shift registers, and the shift registers are used for outputting primary scanning signals based on the clock signals; the gating circuits correspond to the shifting registers, the shifting registers are connected with the pixel circuits through the gating circuits, and the gating circuits provide scanning signals for the pixel circuits; the display area comprises a first sub-display area and a second sub-display area, and the data refreshing frequency of the first sub-display area is larger than that of the second sub-display area; in the first display mode, data refreshing is carried out on each sub display area; in the second display mode, the first sub-display area performs data refreshing, and the second sub-display area performs data retention; in the first display mode and the second display mode, the shift registers corresponding to the first sub-display area and the second sub-display area receive clock signals of the first clock frequency.

An image processing method and a device configured to implement the same are disclosed. The method comprises: from an imaging device, obtaining image data that comprises temporally consecutive image frames; performing feature extraction on each of the obtained image frames; dynamically retaining extracted feature data of the obtained image frames in a feature accumulation database by regulating data retention in the feature accumulation database to a selective subset of the extracted feature data from the obtained image frames; performing Random Sample Consensus (RANSAC) operation on the selective subset of the extracted feature data from the feature accumulation database; and generating an estimation model from output of the RANSAC operation based on at least one of an extracted feature data of a current image frame or extracted feature data of one or more temporally preceding image frames of the obtained image frames.