374 results about "Data storage system" patented technology

A dynamic marketplace system leveraging store and warehouse mobility features a neuroevolution (NE) engine, an electronic device, and a request handler facilitating communication between the electronic device and the NE engine. The NE engine interfaces with a data storage system and an event handler receiving real-time event data from a public cloud services processor. An intentions handler interprets user intention data to predict user behavior. The NE engine, integrated with a processor, generates a predictive evolutionary model for the marketplace based on request, event, and intention data. An AI agent processor within the NE engine creates a recommendation model for mobile retail vendors, devises route plans, and deploys vendors to strategic locations.

The invention discloses an intelligent RAG enhanced large model auxiliary writing system, and relates to the technical field of artificial intelligence auxiliary writing. In order to overcome the defects of an existing writing auxiliary tool, the adopted scheme comprises an interface and user layer for receiving a writing demand and redisplaying a generation result; the service layer is used for deploying three types of intelligent agents including writing, interactive writing enhancement and checking; the platform layer is used for carrying out industry adaptation analysis, mixed retrieval and RAG enhancement on writing demands and then sending the writing demands to the large model layer; three intelligent agents of writing, interactive writing enhancement and checking are called in sequence based on the output of the large model layer, and then a text is redisplayed to the interface and user layer after fact accuracy verification is completed through a tense knowledge graph; the data layer is used for providing a multi-type data storage system; the large model layer outputs a paragraph-level text and a reference index based on a writing large model, the paragraph-level text is returned to the platform layer, and reference index information is fed back to the interpretability and security layer for tracing; and the infrastructure layer is used for providing bottom layer resource support for each layer.

The invention discloses a life omics knowledge graph construction method and system based on a large language model, and relates to the technical field of computer data processing. The method comprises the following steps: acquiring and preprocessing multivariate life omics data, wherein the multivariate life omics data at least comprises an unstructured biomedical text; performing information extraction on the text data based on a large language model to obtain entity mention and relation description; standardizing and normalizing the entity mention and the relation description on the basis of a large language model in combination with an external knowledge base to obtain a standard knowledge triple; and storing the triple into a graph data storage system, and constructing the knowledge graph. According to the method, the powerful natural language understanding ability of the large language model is utilized, efficient information extraction is achieved through structured prompt or field fine tuning, the model is innovatively utilized for entity standardization of relation perception, and the accuracy of knowledge fusion is remarkably improved.

An illustrative data storage management system comprises a management database that stores administrative preferences and system configurations, as well as results and / or statistics of completed secondary storage operations, i.e., information needed by the system to protect customers' data and to track and recover the protected data, including secondary copies such as backup copies, archive copies, etc. The disclosed data storage management system is configured to protect its own system data subject to a very aggressive (short) Recovery Point Objective (RPO), by using an innovative infrastructure that enables the system's storage manager to fail over to any number of other failover destination storage managers, each one comprising a destination management database. An illustrative database granularly tracks whether each and every transaction log file has been successfully applied to each and every destination management database to synchronize with the source management database.

The invention discloses a distributed cooperative processing method, system and equipment for mass spectrum data analysis, and relates to the field of biological information distributed processing, and the method comprises the steps: receiving original mass spectrum data submitted by a user, and analyzing flow configuration and global parameter configuration; analyzing the analysis process configuration into a directed acyclic graph taking the mass spectrum data processing step as a node; splitting the directed acyclic graph into a plurality of parallel atomic tasks according to the quantity of the original mass spectrum data and the space occupation amount; each atomic task is allocated to a Worker node storing corresponding associated data, and the atomic tasks are executed in parallel; when it is detected that the atomic tasks fail to be executed, the Worker nodes are distributed to the atomic tasks which fail to be executed again; different data storage systems are adopted to store original mass spectrum data, intermediate results and final analysis results. According to the invention, efficient parallel processing of mass spectrum data is realized, and continuity and reliability of an analysis process are guaranteed.

A semiconductor device includes: a conductive layer; a stack structure including gate electrodes spaced apart from each other and sequentially stacked in a first direction, in a first region and a second region, a first separation region and a second separation region penetrating through the stack structure, and extending in a second direction, perpendicular to the first direction, and spaced apart from each other in a third direction, perpendicular to the first direction and the second direction; channel structures respectively including a channel layer and penetrating through the stack structure in the first direction, in the first region; and contact plugs extending by different lengths by penetrating through at least one of the gate electrodes of the stack structure, electrically connected to each of the gate electrodes, and spaced apart from each other, in the second region.

The invention discloses a building cluster cloud-edge collaborative optimization control method and device and an application architecture. The architecture comprises an edge device, a radio frequency communication LoRa module and a cloud platform. The edge device and the cloud platform realize cloud edge two-way communication through the LoRa module; the edge device comprises a sensing layer, an edge calculation core and a control layer and is used for collecting real-time building data, executing a local model predictive control algorithm MPC based on a building thermodynamics RC model and generating an optimal control instruction to drive air conditioning equipment; the cloud platform comprises a network service interface module, an optimization algorithm module and a data storage system and is used for operating a global coordination algorithm based on an alternating direction multiplier method (ADMM) and generating differentiated price signals; the edge device uploads data such as power requirements to the cloud platform, the cloud platform issues differential excitation signals to the edge device, and the edge device and the cloud platform perform collaborative iteration. According to the invention, distributed optimization control of the building cluster is realized through cloud-side cooperation, and the value of the building cluster as a power grid flexible resource is significantly improved.

The present disclosure is directed to key-value data storage systems using content addressable memory. A memory system includes a memory device comprising a content addressable memory (CAM) block storing a plurality of stored search keys and a value data block. The memory system additionally includes a processing device that receives an input search key and identifies one of the plurality of stored search keys that matches the input search key, the one of the plurality of stored search keys having an associated matching orientation in the CAM block. The processing device further determines a corresponding value orientation in the value data block using the associated matching orientation and retrieves data representing a value associated with the input search key from the value orientation in the value data block.

Example embodiments disclose a method for performing queries on properties of data items stored in a data storage infrastructure (1) comprising data storage systems; wherein the data items have associated metadata and are identifiable by attributes characterizing a logical and physical location of the data items within the data storage infrastructure; the method comprises: i) performing (501) scans on the data storage systems for the associated metadata and attributes (511); ii) mapping (502) the data storage infrastructure to a rooted tree; wherein the date items are represented as leaf nodes thereby defining respective hierarchical paths along one or more internal nodes to the root node; and wherein the internal nodes are defined according to a predefined hierarchical ruleset; iii) ordering (503) the nodes according to a depth-first ordering rule in an ordered list; iv) adding references to sibling nodes of the respective nodes; v) adding (504), aggregated metadata to internal nodes based on metadata or aggregated metadata of descendant child nodes; vi) providing user definable hierarchical querying based on the aggregated metadata; vii) perform a query by traversing through the nodes in the ordered list, and thereby evaluating aggregated metadata of an internal node according to the query, and based on the evaluation, proceed to evaluating the next node in the ordered list or proceed to the sibling node.

A system is configured for automatic recognition of data store architecture and tracking dynamic changes and evolution in data store architecture. The system is a complementary system, which can be added onto an existing data store system using the existing interfaces or can be integrated with a data store system. The system comprises three main components that are configured to compose an approximation of the data store architecture. The first of these components is adapted to execute an analysis of the architecture of the data store; the second of the components is adapted to collect and compile statistics from said data store; and the third of the components is adapted to compose an approximation of the architecture of said data store.

The present disclosure relates to a controller, a memory device, and a data storage system. The data storage system improves access performance to a memory device by having a plurality of channels, and improves operation performance, prevents operation errors, and improves efficiency by controlling timing of transmitting an operation command to a storage area based on occupancy state information of the storage area included in the memory device.

The invention relates to a data synchronization method, system and device for a hybrid load service and electronic equipment. The method comprises the following steps: analyzing a log file generated by a source end data storage system to obtain all transaction data, and filtering the transaction data according to a preset white list rule to obtain target transaction data related to a target service; performing multi-dimensional analysis on the target transaction data, and generating at least one transaction judgment feature representing transaction behavior characteristics according to an analysis result; determining a target data synchronization optimization strategy matched with the transaction judgment feature, and obtaining corresponding transaction data in the target transaction data according to the target data synchronization optimization strategy; and buffering and sorting the obtained transaction data, and synchronizing the transaction data to a target data storage system through playback processing. The technical problems that analysis of operators is time-consuming, misjudgment is easy to occur, and a synchronization channel is blocked due to high-load mixed services are solved.

According to the quantitative analysis method for the detectability of the technical institution, intelligent recognition of multi-format documents is achieved through self-adaptive layout analysis and an OCR engine, the data cleaning and automatic correction technology is combined, the data collection accuracy is remarkably improved (the manual intervention requirement is reduced), and complex layouts and unstructured data are effectively processed. By adopting intelligent data analysis and structured processing, automatic extraction of key fields is realized based on the analysis capability of a Transform model, and a structured data storage system is established through dynamic modeling, so that the limitation of traditional template matching is solved, and the generalization capability and structured efficiency of data processing are improved. A scientific ability evaluation model is established, outlier rejection and normal distribution modeling are adopted to optimize data quality, objective and quantitative ability evaluation is realized in combination with a Z-ratio score comparison mechanism, subjective deviation is eliminated, and it is ensured that an evaluation result meets statistical specification requirements.

A data storage system may include a memory device and a controller. The memory device may include a plurality of virtual blocks. The controller may include at least one processor and a memory. The memory may include instructions stored thereon, that when executed by the at least one processor, cause the at least one processor to: monitor a number of program / erase cycles for the plurality of virtual blocks; collect read errors for the plurality of virtual blocks; select a virtual block of the plurality of virtual blocks to open based on the number of program / erase cycles and the collected read errors; and write data to the selected open virtual block.

A data platform for providing large scale data discovery with near real time data cataloguing and detailed lineage. Data is received from one or more sources, and the received data is written to a data storage systems. The received data is processed at the data storage systems using sensors at the data storage systems. Metadata and data definitions associated with the data are sent to a data service in near real-time. A data catalog is generated at the data service based on the metadata and data definitions associated with the data. Data lineage for the data is created at the data service. The data catalog and data lineage are presented at a data discovery interface.

The invention provides a magnetoelectric disk, a magnetoelectric memory and a data storage system. The magnetoelectric disc comprises a magnetic tape and a tape winding disc used for winding the magnetic tape, the magnetic tape comprises a data tape and non-data tapes arranged on the two sides of the data tape in the length direction of the data tape, and the non-data tape on at least one side of the data tape is provided with a magnetic head brush. When the magnetic head brush passes through the magnetic head, the magnetic head brush can be used for cleaning the magnetic head.

This specification provides a data storage method and device for string data. During data storage, for each string in the string dataset to be stored, a pattern dataset is used for pattern matching. Each pattern in the pattern dataset is common string data among multiple strings in the string dataset and is stored in the pattern data storage area of ​​the data storage system. In response to a string containing matching pattern data, proprietary string data (excluding the matching pattern data) is extracted from the string and stored in the proprietary data storage area of ​​the data storage system. An index relationship is formed between the stored proprietary string data and the corresponding pattern data stored in the pattern data storage area. In response to a string not containing matching pattern data, the entire original string data is stored in the proprietary data storage area.

Disclosed herein are various embodiments for a sensitive data management system. An embodiment operates by receiving a request to generate a new data object based on a file comprising unstructured data. Raw data is extracted from the file, the raw data comprising a string comprising the unstructured data. A prompt for a large language model (LLM) is generated, the prompt corresponding to creating a mapping between the raw data and fields for the data object. A mapping between at least a subset of the fields and the raw data is received from the LLM. The mapping is for display via a user interface, an approval of the mapping is received, and the data object is generated in a data storage system responsive to receiving the approval.

This application relates to a cloud-native resource description framework (RPF) data storage system, method, and computer device. The system includes: a storage layer for storing triples sharing the same attribute in RPF graph data as a subgraph and storing them in cloud object storage, constructing a range-aware offset index for each subgraph; and a computation layer for receiving RPF queries, decomposing the RPF queries into multiple subqueries according to attributes, querying the range-aware offset index, obtaining the byte offset of the target data value in each subquery in the corresponding subgraph, and, based on a query processing efficiency model, determining a target access method for each subquery from multiple preset data access methods according to the byte offset, executing the target access method to output the subquery result, and concatenating the results of each subquery to generate the query answer. Using this system can significantly reduce storage and query operating costs while maintaining competitive query performance.

A data storage system includes a memory device and a controller. The memory device includes a set of planes and a wordline including a set of pages. The controller includes a first and second minimum write cache control buffer (mWCCBs), processor(s), and a memory. The memory includes instructions, that when executed the processor(s), cause the processor(s) to: determine that an amount of outstanding data of a data stream is not sufficient to occupy the set of planes; store a first portion of the outstanding data in the first mWCCB; release the first portion to the memory device; in coordination with the release of the first portion of the outstanding data, store a second portion of the outstanding data in the second mWCCB; release the second portion to the memory device; and write the first and second portions of the outstanding data to a subset of the set of pages.

A system and method of property collection management and architecture that can organize patient data while maintaining context is presented. The present disclosure provides for a database system implementing a ‘Property Collection’ as a collection of ‘property name’ and ‘property value’ pairs, which are used to describe a ‘data entity.’ Further, the present disclosure can provide for historical access to data to track data changes. The present disclosure solves the technological problem of accessing data having differing data for the same person. The immutable electronic health record data storage system solves the aforementioned technological problem by providing a blockchain, transaction blockchain API, serialization module, and a deserialization module, among others that can format, process, and store data in a Global Patient Record (GPR).

The present technology enhances workload management of data storage systems by using an internal copy function and / or a zone-append technology. The internal copy function is used, e.g., in merge operations to move data between locations on a disk without using off-disk resources (e.g., processing or memory of a CPU). Zone-append technology uses nameless writes (e.g., write instruction without an assigned destination address on the disk) to combine IO units from different threads to be written to a common zone of a disk (e.g., a shingled magnetic recording (SMR) disk). Sequential addresses are assigned to IO units from different threads based on their order in the write queue, reducing the latency and seek time typically associated with random writes. The zone-append technology, e.g., uses sequential write operations within specified zones, allowing the disk to determine the actual write location and to report post-write logical block addresses (LBAs).

An application programming interface, API, server comprising an API gateway and at least one API comprising a plurality of callable API endpoints, and an associated method, the server further comprising: an API monitor configured to retrieve API call data related to API calls made by a client to one or more API endpoints of one or more APIs in order to time-stamp each API call in the retrieved API call data, and to send the time-stamped API call data to a data storage system; the data storage system that is configured to store the received time-stamped API call data; an artificial intelligence, AI, copilot configured to be trained using the data stored in the data store and usable in a development environment in order to provide the user with suggestions for generating code for a new application.

A portable container has a payload chamber for holding medicines, vaccines, biological samples or other medical goods and a lid operable to access the payload chamber. The portable container also has an electronic system with one or more power storage devices, circuitry that wirelessly communicates via a cell radio with a cloud-based data storage system or a remote electronic device, and an electronic display screen. The electronic system can a) automatically switch sender and recipient information on the electronic display screen to facilitate return of the portable container to the sender or b) automatically contact a parcel carrier to alert the parcel carrier that the portable container is ready for pickup.

The invention provides a multi-dimensional construction data storage system and method, relates to the technical field of data storage, and realizes significant improvement of construction data storage efficiency and breakthrough of intelligent management capability by introducing multi-dimensional feature extraction, resolution factor calculation and a dimension perceptual hash algorithm. Firstly, original feature values of four dimensions are extracted from each construction data unit, standardized coding processing is carried out, a unified dimension code is generated, the precision degree and the association strength of data are quantitatively evaluated by calculating a time resolution factor, a space resolution factor and a coding similarity factor, and therefore a storage strategy is dynamically adjusted, and the storage efficiency is improved. According to the dimension perceptual hash algorithm, logic storage coordinates are intelligently generated through the factors, data with similar characteristics are naturally gathered on physical storage, data items are temporarily stored by maintaining an ordered structure on the memory management level, sorting is conducted according to the logic coordinates, disk random write-in operation is effectively reduced, and write-in performance is improved.

The invention relates to the field of paper data storage, in particular to a data storage system. A data storage system comprises two first hydraulic rods, the moving end of each first hydraulic rod is fixedly connected with a rotating disc, each rotating disc is provided with two key grooves, each key groove is internally connected with a clamping rotating mechanism in a sliding mode, each first hydraulic rod is further fixedly connected with a sleeve, and the outside of each sleeve is fixedly connected with a support. Each clamping and rotating mechanism comprises a key, a connecting rod is fixedly connected to the key, a clamping plate is fixedly connected to the connecting rod, the position of the clamping plate is slightly lower than that of the key, a supporting plate is further fixedly connected to one end of the connecting rod, and the connecting rod on each clamping and rotating mechanism is in sliding connection with the clamping plate on the other clamping and rotating mechanism on the same side. According to the system, paper files are rolled up and stored, and the problem that paper is damaged by traditional folding storage is solved.

Various embodiments of the present disclosure relate to compression techniques that can be used for data storage, indexing, and retrieval. In an example embodiment, a controller of or in communication with a data storage system can obtain a request to store a file in the data storage system. The controller identifies time-series data associated with input / output of the file and metrics of the file, generates a feature vector for the file, and compresses the feature vector using a compression technique, resulting in a compressed feature vector having a compression ratio. The controller performs a hash algorithm using the compression ratio to determine a storage device at which to store the compressed feature vector, the compression ratio associated with the file, and an indication of the compression technique. Upon receiving a query for a file, the controller compares compression ratios to identify a storage device storing the requested file.

A set of metadata is generated for a file based on file characteristics and a vector embedding is calculated using the set of metadata. A distance between the vector embedding and at least one other vector embedding is used to determine the file storage location. The at least one other vector embedding represents at least one other corresponding set of metadata generated for at least one other file. In one aspect, a combined access latency for the file and the at least one other file is considered in determining the storage location. In another aspect, a text based request is received to search for at least one file indicating a criterion not specifically identifying the at least one file. The text based request is converted into a structured command using a Large Language Model (LLM) to identify at least one storage location for the at least one file.