40 results about "Computerized databases" patented technology

A system and method for accuracy-enhanced processing of query data within a multi-digital agent architecture may include receiving unrefined query data including textual data; retrieving historical user dialogue data from a computer database associated with the unrefined query data; transforming the unrefined query data to refined query data based on the retrieved historical user dialogue data; generating at least one digital agent classification inference using the refined query data; routing the refined query data to a digital agent based on the at least one digital agent classification inference; generating, by the digital agent, a digital response to the unrefined query data; and returning the digital response to an interactive graphical user interface.

The invention belongs to the technical field of railway vehicle command, and provides a list type metallurgical enterprise railway shunting operation command system, which comprises a plan management system, an existing vehicle management system, a centralized dispatching system, a locomotive positioning system, a microcomputer interlocking system and a horizontal dispatching system, the system utilizes computer enterprise cloud, a computer database and a computer network communication technology to construct a data exchange and storage platform so as to realize integration and sharing of information in the system; a shunting operation plan of the plan management system is transmitted to each subsystem in the system through a wireless network, and each subsystem feeds back an execution result to the data exchange and storage platform. The system adopts a list type current vehicle dispatching mode and a dispatching centralized type current vehicle dispatching mode to generate a shunting instruction, under the condition that the system can clearly master all attributes of vehicles in a whole plant area, rapid shunting instruction compilation is carried out according to one or several attributes, and on the basis that the plan editing efficiency is improved by dozens of times, the scheduling efficiency is greatly improved. And the safety risk caused by wrong picking and hanging of the vehicle is reduced.

A system and method for accuracy-enhanced processing of query data within a multi-digital agent architecture may include receiving unrefined query data including textual data; retrieving historical user dialogue data from a computer database associated with the unrefined query data; transforming the unrefined query data to refined query data based on the retrieved historical user dialogue data; generating at least one digital agent classification inference using the refined query data; routing the refined query data to a digital agent based on the at least one digital agent classification inference; generating, by the digital agent, a digital response to the unrefined query data; and returning the digital response to an interactive graphical user interface.

A computer monitoring system and method for determining one or more periodicity clusterings of alarm events in a computer database managed by an automated and industrial control system (AIC), wherein each alarm event has a time spaced repeat duration period relative to a succeeding alarm event. Captured from an AIC computer database is alarm data containing a plurality of alarm events, which are then clustered into one or more repeat period clusters based upon a repeat duration period for each alarm event, using one or more algorithmic techniques. Each determined repeat period cluster is analyzed to determine certain metadata associated with each repeat period cluster, which metadata for each repeat period cluster is analyzed to identify repeat period clusters as a valid alarm periodicity cluster. A tangible output is then provided indicating identified valid alarm periodicity clusters.

The application discloses a kind of distributed log's memory database parallel recovery method and system, belong to computer database technical field, the method is: the command log generated in memory database is stored by log partitioning and is physically isolated, and the metadata of each log partition is recorded;Based on pre-received recovery instruction and the metadata, the corresponding recovery plan is generated for each log partition;Parallelly start multiple recovery threads, and based on the recovery plan, the snapshot information pre-acquired in each recovery thread is loaded corresponding log partition, and according to the recovery plan and the snapshot information, the log fragment that needs to be replayed is determined, and the log fragment that needs to be replayed is replayed to corresponding log partition, to carry out parallel recovery to memory database.Therefore, by implementing the present application, the problem that the data recovery reliability of prior art distributed log memory data recovery process is complex and dependent on manual intervention can be solved.

The invention discloses a multi-environment consistency database script execution structure verification method, relates to computer and database technologies, is applied to database script consistency verification in a multi-database environment, and comprises the following steps: acquiring a request instruction by utilizing an agent program, and generating a standardized request object based on the request instruction; sending the standardized request object to each database environment; performing data source switching based on the standardized request object in any database environment, and executing the standardized request object after switching; and comparing the execution results returned by the database environments, and judging that the database script execution structure passes verification under the condition that the execution results are consistent. The method is used for database script consistency verification in a multi-database environment, the script consistency verification efficiency is improved, and the database test development efficiency is improved.

Methods and systems identify commonly used CAD parts and apply machine learning techniques to predict the matable entities and corresponding mating types of these parts to automatically add the parts to the CAD model. An example method includes accessing information about CAD model parts and related mating information stored in a computer database, and dividing the parts into multiple clusters of parts with similar global shape signatures. In response to adding a new part, a contextual signature of an entity of the new part is input into a mating predictor neural network to determine the matable entities of the new part. (i) The contextual signature of the matable entity and (ii) the contextual signature of an entity of another part of the CAD model are input into a mating type predictor neural network to determine the mating type between the entities. A mating between the new part and another part is automatically added based on the determined mating type.

The embodiment of the present disclosure provides a language generation method and device based on a computer database, and an entity space relation model construction method and equipment. The method comprises the following steps: constructing an entity space relation model based on the spatial position relation among entities in a real scene, and storing the entity space relation model in the database; finding a target node and an auxiliary node having a mapping relation with the target node based on an entity word data set through the mapping relation in the database; finding a directed edge associated with the target node and the auxiliary node from the directed edge data set based on the mapping relation; generating a data segment describing the spatial position relation of the target node through the target node, the auxiliary node and the directed edge; and generating a sentence describing the spatial position relation of the target node after encoding the data segment based on an encoder. The present disclosure makes the language generation process more accurate, the position relation among entities more clear, and the position recognition rate among entities greatly improved.

The application relates to a database mode matching method based on relationship perception and incremental learning, and belongs to the technical field of computer databases. First, the modal information of a target database and a source database is found. Then, feature extraction is performed on the sub-modal text information. After that, the feature extraction information is input into a Bayesian network for selection and screening. In this process, the quality of the features is also measured to ensure the accuracy and stability of the sub-modal classification. At the same time, neuron regularization and Bayesian incremental learning methods are introduced to fully exploit the continuous learning ability of the model. Finally, the obtained target database sub-modal and source database sub-modal are matched through a feature relationship perception mode to obtain a mode matching result. The application can effectively improve the query and mode matching processing efficiency and accuracy between different databases.

A computer method and system for providing information results in response to a natural language information request. The system and method include receiving a natural language information request from a user and compiling a computer executable query from the natural language information request from a user wherein the query is formatted to extract data from one or more computer databases. The query is then presented to the user prior to execution of the query so as to enable the user to change the query prior to its execution. The query is then executed to extract data from one or more computer databases whereby extracted data is presented to the user in a certain presentation format.

The invention relates to a system (100) for updating an item of data representative of the weight of a product in a database (105), the system comprising: - a sensor (110) for detecting a value representative of the weight of a product; - a timestamp module (115) configured to associate a timestamp value with a capture of the weight value of a product that is represented, in a database by a product identifier; - a software module (120) for determining an item of data representative of the weight of a product according to at least: - a minimum number of weight values for a product identifier; - a validity time interval of the weight values captured for a product identifier; and / or - a maximum validity period of the weight values captured for a product identifier; and - a module (125) for updating a weight value of a product in a database.

Provided herein are diffractometer-based global diagnostic systems and uses thereof. The systems may comprise one or more diffraction apparatus operatively coupled to a computer database over a network. The one or more diffraction apparatus may be configured for transfer of data such as pathology lab image data, diffraction pattern data, subject data, or any combination thereof to the computer database over the network. The systems may further comprise one or more computer processors operatively coupled to the one or more diffraction apparatus, which computer processors may be configured to receive the data from the diffraction apparatus, transmit the data to the computer database, and process the data using a data analytics algorithm which may provide a computer-aided diagnostic indicator for the individual subject.

The application relates to an automatic learning index method and system, in particular to a method and system for automatically recommending an optimal index according to computer data characteristics, to solve the problems that, when learning indexes of a computer are established, the number of layers of the learning indexes and corresponding models of each node need to be defined manually, the space cost of index establishment is large, the establishment process is difficult, and the establishment time is long, and the application relates to a method and system for automatically recommending an optimal index according to computer data characteristics, which comprises the following steps: constructing a learning index model, the learning index model comprising a regression model and a random forest model; training the learning index model by using a computer database as a training set; inputting a key key of training data; and outputting the position of the training data in the computer database. The application belongs to the field of database indexes.

There is disclosed a system for scanning data from items, wherein each item is provided both with a radio frequency identification, RFID, tag and with an optically-readable identifier. The system comprises a scanner configured to read first data from the RFID tag by way of an RFID reader and to read second data from the optically-readable identifier by way of an optical reader. The second data comprises data having a data format selected from a group of different predetermined data formats. The scanner is configured to communicate at least the first data and the second data to a signal splitter. The signal splitter is configured to inspect the second data so as to determine whether or not the data format of the second data matches a given one of the predetermined data formats. The signal splitter is configured to direct the first data and the second data in the given one of the predetermined data formats to a first computer database in the event that the data format of the second data matches the data format of the given one of the predetermined data formats. The signal splitter is configured to direct the second data but not the first data to a second computer database in the event that the data format of the second data matches any one of the predetermined data formats.

The invention discloses a computer database server convenient to install, and the computer database server convenient to install is characterized in that a plurality of layers of isolation plates are fixedly installed at the inner end of an installation frame, each isolation plate is provided with a plurality of installation groove positions, and computer groups are arranged in the groove positions; a plurality of stabilizing racks are arranged at the upper end of the isolation plate at intervals, a sliding plate is slidably mounted on the upper surface of the isolation plate, and the computer unit is detachably mounted at the upper end of the sliding plate. The problems that when the computer unit is installed, due to the influence of the dead weight of the computer unit, the computer unit can be inserted into the rack with large force, the environment of the rack is possibly narrow and complex, the risk of misoperation is large, and the computer unit cannot be inserted into the rack when being pulled are solved. An operator cannot accurately control the force, so that the risk that a case falls off is increased, especially in a busy machine room. Therefore, the computer database server convenient to install is provided.

An index recommendation method and system based on caching and deep learning, specifically relating to an index recommendation method and system for a computer database based on a caching database and deep learning. To solve the problem that the index recommendation method of a computer database during data query does not utilize historical data, and the index recommendation algorithm cannot determine whether an index needs to be created for a specific column in a certain list of the computer, resulting in a relatively low query accuracy rate. The workload and index configuration of the encoded computer database are merged to obtain a feature vector; the columns and data corresponding to the computer database are inserted into the established caching database for storage; the feature vector is input into a database tuning model established based on a long short-term memory network, and in combination with the caching database, vector B is output. If the i-th element in vector B is 1, an index is created for the i-th column in the computer database list, otherwise no index is created, and data query is completed based on the columns for which indexes are created. It belongs to the field of index recommendation.

The present application relates to the technical field of computer database and basic algorithm transplantation, and particularly relates to a method for accelerating database hash operation by using SIMD and transplanting to ARM platform.The method of the present application comprises: according to a basic hash query algorithm, modifying and implementing a hash query method based on SIMD technology; according to a basic hash table building algorithm, modifying and implementing a hash table building method based on SIMD technology; defining a SIMD conversion library, implementing a conversion module ATN from an SSE instruction set and an AVX instruction set to a Neon instruction set, and providing a quick conversion process.The flow is shown in Fig. 1.The method improves the execution speed of hash query and hash table building operation by fully utilizing CPU computing capacity.The method reduces the operation complexity and coding amount of developers by defining a conversion library.

Search indexes can be automatically generated and used for expediting searching of a computerized database. For example, a system can access an inquiry dataset that includes relationships between prior inquiries and returned records from a database. The system can then generate a set of Boolean indexes based on the prior inquiries. The system can then identify frequent indexes that occur at least a threshold number of times in the set of Boolean indexes and that have estimated candidate sizes that are less than a threshold size. The system can then select the frequent index with the highest frequency from among the frequent indexes. The selected frequent index can be subsequently used to expedite searching of the database in response to receiving a search query associated with the frequent index from a client device.

The invention discloses a self-adaptive index optimization system based on timing context driving, and relates to the field of computer databases. The context extraction unit is used for initializing a lock-free circular queue by applying a sliding window accumulation mechanism, calculating feature data in combination with a time sequence data stream and a query log, performing normalization processing on the feature data and constructing a context feature vector; the self-adaptive decision-making unit is used for taking the context feature vector and an algorithm library as input and outputting an optimal algorithm and a corresponding weight through an attention network; and the index reconstruction execution unit is used for executing a dynamic adjustment mechanism of the index structure in a linkage manner according to the output optimal algorithm and the corresponding weight, evaluating and updating the current state based on a dynamic adjustment result, and feeding back an updating result to the context extraction unit. According to the method, high-precision spatial-temporal feature modeling can be realized, the problem of mismatching of a strategy and a load is solved, and index expansion and delay peak are avoided.

The present application discloses a method and system for deploying vault elements, which involves computer and database technologies, and includes the following steps: obtaining a version list of vault elements to be deployed; performing configuration verification based on the obtained version list, wherein the configuration verification includes YAML syntax verification, field existence verification, field type verification, and field value verification based on the version list; obtaining service components corresponding to the vault elements to be deployed from the target address according to a preset configuration file, and arranging and archiving them; performing calculations and allocations according to a specific deployment template based on the arranged and archived data to complete the deployment. The present application embodiment proposes a one-click deployment system to simplify and automate the software deployment process, ensure the closed-loop delivery of productized services, and improve deployment efficiency and the accuracy of product delivery.

Various aspects of the present disclosure relate to periodicity clusterings of alarm events ‎in a computer database managed by an automated and industrial control system ‎(AIC)‎, wherein ‎each alarm event has a time spaced repeat duration period relative to a succeeding alarm event. Alarm data is captured from an AIC computer database including a plurality of alarm events, which are then clustered into one or more repeat period clusters based upon a repeat duration ‎period for each alarm event, using one or more algorithmic techniques. Each determined repeat period cluster is analyzed to determine metadata associated with each ‎repeat period cluster, which metadata for each repeat period cluster is analyzed to identify repeat period clusters as a ‎valid alarm periodicity cluster. A tangible output is then provided indicating identified valid alarm periodicity clusters.‎

The invention discloses a distributed architecture-oriented time sequence library high-concurrency writing method, which relates to the technical field of computer databases, and comprises the following steps of: constructing a self-adaptive multi-stage writing path of time sequence data, and dynamically selecting the writing path of the time sequence data and adjusting a load in real time by embedding an intelligent scheduling layer and a cross-layer feedback control mechanism; based on a sliding time window and an additional recording queue mechanism, performing isolation and combination on out-of-order data and historical complement data written in the distributed time sequence database; and based on version conflict detection of a vector clock and a latest version priority merging strategy, merging and writing confirmation are carried out on the time sequence data after out-of-order writing and historical additional recording processing. According to the method, a layered write-in path design and a lightweight consistency protocol are adopted, high-concurrency write-in and final consistency guarantee of data are realized aiming at complex scenes such as out-of-order write-in, historical compensation and network jitter, and the write-in performance and reliability of a system are improved.

A system and method for scanning data from items such as histopathology cassettes 1 or histopathology slides 4. Each item is provided with both a radio frequency identification (RFID) tag and with an

A system and method for evaluating socio-economic and / or environmental impact automatically identifies and transmits to a user computing device a socio-economic and / or environmental impact web page of an organization. A computer database coupled to a server contains data for various socio-economic and / or environmental impact web pages, defining formatting elements configured to display impact data. The computer database receives a data feed of the impact data from the organization and / or from one or more of the organization's vendors and automatically updates the organization's socio-economic and / or environmental impact web page. The system automatically generates in the socio-economic and / or environmental impact web page, a socio-economic and / or environmental impact quotient depiction representing socio-economic and / or environmental impact of resource allocations of the associated organization. The system uses hybrid input-output, econometric and environmental models to calculate a total economic impact ratio of the SGA (Selling, General & Administrative) costs of the organization on local communities.

Provided is a method for evaluating the seismic margin of a simple and efficient transmission tower. 【Solution means】Based on various data of all the towers G belonging to the tower group G in the computer database 1 lim , m-n , lim , p , p , T ,the static elastic response deformation φ at the top of the tower G caused by the seismic load Q acting on the panel i stacked in the height direction of the tower G m-n is calculated, where the seismic load Q is replaced by the equivalent bending rigidity E·I m-n and the equivalent shear rigidity G·A i of each panel i to form an equivalent cantilever beam model of the tower G i ,and the deformation φ at the top when the web members of the panel i buckle under the seismic load Q si ,the deformation φ at the top when the main column material reaches the compressive endurance limit m-n are calculated from predetermined approximate formulas respectively. The values of the top deformations φ e ,φ i are substituted into a predetermined formula to calculate the elastoplastic response deformation φ y occurring at the top of the tower G,and the ratio φ lim / φ e is calculated as the seismic index value DCR y of the tower G. The above procedure is executed for all the towers.​​​​​​​​​​​​​​

The application relates to a learning index method and system based on a prefix Bloom filter, and aims to solve the problem that, when computer query data does not exist in a computer database, the existing index needs to traverse the whole structure of the corresponding index or a machine learning model to determine whether the computer query data exists in the computer database and the existing position of the computer query data in the database, so that the computer data query time is too long. The application comprises the following steps: constructing a tree-shaped learning index; the learning index comprises non-leaf nodes and leaf nodes; for the non-leaf nodes, a prefix Bloom filter is used to determine whether computer data exists in a computer database; if the computer data does not exist in the computer database, a result that the computer data does not exist in the computer database is returned; if the computer data exists in the computer database, a machine learning model is used to query the position of the computer data in the computer database in the leaf nodes. The application belongs to the field of database indexes.

A computer-implemented method and system for facilitating a sending of a gift from a first machine to a second machine may include a processor of a computer server reviewing a first list of one or more names of people maintained in a computer database. The processor may review context information related to the one or more names to determine if a moment exists for sending a gift from a first machine to a second machine. Each of the one or more names is associated with a respective second machine. The processor may automatically generate a second list of one or more names of people associated with a moment for receiving a gift. The processor of the computer server may receive from a first machine a selection of at least one of the names on the second list who have been identified as associated with a moment for receiving a gift.

The present application relates to the field of computer database and the field of verifiable computing, more particularly to a verifiable index construction, update and verification method for high read-write contention workloads, comprising a verifiable index structure and construction method based on Merkle parallel tree, a concurrent update method of verifiable index, a query verification method based on verifiable index; while supporting data verifiability, the present application solves the lock-free concurrent control of read-write conflict, batch parallel can bring very good performance in terms of query and batch update, and the characteristics of multi-version index enable historical versions to be retained, thus supporting verification of historical version data.

A computer-implemented method for automated data record resolution includes: receiving an unmapped data record comprising a plurality of data fields, wherein at least one data field of the plurality of data fields causes a mapping error between the unmapped data record and a plurality of validated data records; generating, from the plurality of validated records, a resolution candidate record for the unmapped data record based on detecting the mapping error between the unmapped data record and the plurality of validated data records; and automatically re-assigning one or more data records of the computer database that are digitally associated with the unmapped data record to the resolution candidate record.

A system, method, and computer-program product includes obtaining, from a computer database, claim data associated with a digital claim that has an adverse decision, extracting, using one or more feature extractors, one or more corpora of feature vectors from the claim data associated with the digital claim, computing, using a claim assessment machine learning model, a claim assessment inference that includes a likelihood of the adverse decision being reversed for the digital claim based on the claim assessment machine learning model receiving the one or more corpora of feature vectors, and automatically routing the digital claim to a target claim handling queue of a plurality of distinct claim handling queues based on the likelihood of the adverse decision being reversed for the digital claim.