68 results about "Online database" patented technology

The invention discloses an artificial intelligence-based bid invitation file automatic auditing method and system, and the method comprises the steps: setting an online database and a local database in the system, carrying out the format auditing, compliance auditing and other abnormal auditing of a bid invitation file through a bid invitation file auditing module, generating auditing suggestions, and carrying out the automatic auditing of the bid invitation file. After the auditing opinions are manually confirmed by a system using unit, a final bid invitation file manuscript is generated, and the system comprises the following modules: a database module, a file uploading module, a bid invitation file auditing module, a suggestion modification module, a bid invitation file generation module, a user interaction interface and a learning module. The method is convenient to use, intelligent auditing of the bid invitation file is achieved through the artificial intelligence technology, and the overall quality and efficiency of the bid invitation file are improved.

The invention discloses a gas prediction method based on the combination of a whale optimization algorithm and a bidirectional long-short term memory network, and belongs to the technical field of gas prediction of iron and steel enterprises. The method comprises the following steps: S1, reading real-time gas data from an online database, preprocessing the data, and constructing a data set required by an experiment; s2, a training set and a test set are divided, the training set is used for determining model parameters, and the test set is used for judging the model effect; s3, constructing a BiLSTM gas prediction model; s4, parameters of the model obtained in the step S4 are optimized; and S5, loading the model of the optimal parameter combination for training and prediction, and storing a predicted value in a database. According to the method, the global optimal search strategy of the whale optimization algorithm (WOA) and the performance of the bidirectional long-short term memory network (BiLSTM) on time sequence data modeling are fused, and the accuracy and efficiency of gas prediction can be remarkably improved.

The invention relates to a data comparison method and device, computer equipment and a storage medium. The method comprises the steps that when a data comparison instruction is received at a first moment, first to-be-compared data of a first database at the first moment and second to-be-compared data of second data at the first moment are acquired; performing full-quantity comparison on the first to-be-compared data and the second to-be-compared data within a first preset duration from the first moment to obtain a difference set; within a second preset duration, the first database and the second database are used for conducting multi-round difference comparison on the difference data in the difference set, a target comparison result is obtained, and the target comparison result comprises real difference data of the first database and the second database at the first moment. Multi-round difference comparison is carried out on the difference part subjected to full-amount comparison, pseudo differences generated by time differences in the difference part are removed, only real differences are reserved, and therefore the problem of how to determine the real differences between different online databases is solved.

The invention provides a power distribution network transformer health state on-line monitoring method and device, and belongs to the technical field of transformer state monitoring, and the method comprises the steps: building a state monitoring on-line database and a historical database according to a normal operation state, a historical operation state, an aging state and a fault state of a power distribution network transformer; the method comprises the following steps: establishing feature data of different periodic weights based on multi-source time series data in a historical database, integrating the expanded multi-source time series data into a reconstructed feature data set by applying the periodic weights, integrating the reconstructed feature data set into a single fusion index, and establishing a monitoring model of the fusion index and a state result based on a random degradation model; constructing an optimization objective function of parameters and feature weights of the monitoring model based on the deviation value of the prediction state and the actual state; and performing reverse optimization adjustment on the parameters and the feature weights of the monitoring model based on the historical database, and monitoring the health state in the online database according to the optimized monitoring model.

The invention builds on the previous inventions of one of the inventors herein and includes a group of habitats connected to online databases and programs, where data from the habitats is used to update the databases and programs about the best conditions for the creatures, plants, and possibly other lifeforms inside the habitats. The invention also includes systems for helping students and others to learn, by examining the actions and well-being of the lifeforms inside a habitat, and writing research notes about those lifeforms. The invention also includes methods and systems by which research notes about a certain species, from many students or other observers, can be examined with text analysis tools, which will locate words or phrases that are common, and other information, within the research notes. This will help to discover the optimal ranges for measured parameters like temperature and Ph for the species inside the container.

The invention relates to the technical field of time series prediction, and discloses a time series prediction system and method based on expert denoising, and the method comprises the steps: reading an online database, obtaining historical time series data, and building a conditional diffusion model frame which comprises a time context embedding model and a training model, and inputting the historical time series data into a conditional diffusion model, and obtaining historical data characterization. According to the time series prediction system and method based on expert denoising provided by the invention, through establishing a conditional diffusion model framework, after inputting the historical time series data, a complex time series mode is effectively captured, and time-rich characterization is extracted; meanwhile, time characterization is combined with time context embedding, a multi-expert de-noising device is adopted to carry out segmented noise adding and de-noising, and each time of de-noising is refined, so that the model capacity can be remarkably improved while the high reasoning speed can be kept, and then the prediction precision under different noise conditions is improved.

The invention relates to the technical field of data processing and the field of financial science and technology, and discloses a sensitive word online detection method which comprises the following steps: obtaining a to-be-detected text according to a request, and segmenting the to-be-detected text to obtain a first preset number of sub-texts; storing each sub-text into a detection queue, and dynamically generating a second preset number of computing nodes according to the first preset number of the sub-texts; establishing connection between the second preset number of computing nodes and a preset shared online database, and loading a sensitive word online detection model in the preset shared online database to each computing node; and calling a corresponding sensitive word online detection model according to each computing node, sequentially obtaining the sub-texts from the detection queue for detection, obtaining a detection result of each computing node on at least one sub-text, and fusing the detection results corresponding to each sub-text to obtain a detection report of the to-be-detected text. According to the method, real-time, accurate and expansible detection can be provided for the sensitive words.

The invention provides a method for screening and verifying kelp chloroplast prosthesis protein ACE (angiotensin converting enzyme) inhibitory peptide, which comprises the following two steps of: 1, carrying out computer-assisted enzymolysis on kelp protein, selecting a representative protein sequence in kelp by using an online database, selecting specific protease by using an online enzymolysis platform to carry out virtual enzymolysis, and screening and verifying the ACE inhibitory peptide according to an enzymolysis result; establishing a kelp protein polypeptide classification database; and step 2, establishing a QSAR model of the ACE inhibitory active peptide, and predicting the activity of the ACE inhibitory active peptide, so that the invention provides a research and development method system for a functional product rich in the ACE inhibitory active peptide based on the combination of kelp bioinformatics and experimental verification.

The present invention is a system and method for high-bandwidth digital content protection, to be implemented on an array of platforms. The disclosed invention utilizes convolutional neural networks to scan a plurality of online databases, datasets, and content libraries to determine the authentication and origination of digital content and to prevent the appropriation of digital media and content. The present invention implements metadata preservation schemas and utilizes artificial intelligence to determine whether an image has been doctored or appropriated. In addition, the present invention provides a marketplace for brands and content creators to professionally interact and collaborate.

The invention relates to a resource scheduling method and device, computer equipment and a storage medium. The method comprises the following steps: acquiring a current data fragment in an offline data bin, calculating the number of data rows in the current data fragment, determining the number of nodes of a distributed computing framework according to the number of data rows in the current data fragment and the number of data rows processed by each node in the distributed computing framework, sending the number of nodes to the distributed computing framework, and sending the distributed computing framework to the offline data bin. Enabling the distributed computing framework to start a corresponding number of nodes, and synchronizing the data of the current data fragment to an online database through the started nodes. By adopting the method, the node number of the distributed computing framework can be dynamically adjusted, the dynamic scheduling of resources is realized, and the reasonable utilization of the resources is further realized.

The application provides a cross-source synchronization table index creation method and device, equipment, storage medium and program product, which can be applied to the technical field of big data. The method comprises the following steps: receiving a query statement for obtaining data from a data warehouse; extracting a query field set and a condition field set from the query statement; obtaining data from the data warehouse according to the query statement, and synchronizing the obtained data to a target table in an online database, wherein the target table comprises data columns corresponding to the query field set; merging the condition field set into a candidate index field set of the target table; calculating a dispersion index of each field in the candidate index field set based on the condition value distribution corresponding to each field in the candidate index field set; selecting a target field set from the candidate index field set based on the dispersion index; and creating an index for each field in the target field set on the target table.

The invention discloses a method and a device of an online car-hailing vehicle detection and classification system based on deep learning, and particularly relates to the technical field of image processing. Online car-hailing image data including vehicle images under different vehicle types, different angles and different illumination conditions are randomly selected from an online database, and corresponding vehicle types are labeled; preprocessing and feature engineering processing are carried out on the collected data to generate a training set, a test set and a verification set, the feature engineering processing is to extract pixel values, color histograms and size features of vehicle images from the preprocessed images, and according to the existing vehicle image data, the vehicle images are processed to generate a training set, a test set and a verification set; the method comprises the following steps of: rotating, overturning, scaling, changing brightness and contrast of existing vehicle image data by adopting a data enhancement technology to generate a plurality of groups of vehicle image samples, and carrying out model training by adopting a convolutional neural network and a recurrent neural network algorithm to optimize a classification effect.

The invention discloses an FTP storage method of a software compilation file, an FTP server and a client, and the FTP storage method applied to the FTP server comprises the following steps: monitoring the software compilation client in real time through connection, and storing the software compilation file to an online database when the client uploads the software compilation file, the software compiling file comprises a software compiling file and a corresponding storage period; traversing the stored time of each software compiling file in the online database according to a preset interval period; judging whether the stored time reaches a storage deadline corresponding to the software compiling file or not; and if the storage deadline is reached, removing the software compiling file from the online database.

According to at least one aspect, a distributed database system is provided. In some implementations, the distributed system comprises an online database, an archive database, and a data processing entity adapted to receive a query of a single logical database, the single logical database being stored across the online database and offline database. In some examples, the data processing entity archives data from the online database to the offline database responsive to one or more archive rules.

The present invention discloses a method for intelligent data analysis and automated operation, which relates to the field of data processing technology. Configuration management, parsing business database, establishing data connection; in an offline environment, regularly executing bash scripts, business classification; integrating datav dashboards, reading configuration analysis dimensions, retrieving matching data, rendering as data dashboards of historical periodic statistics; setting the ranking proportion of job information; executing bi‑analyse.sh scripts, doing classification and sorting, synchronizing the sorting data of the offline environment to the specified environment, uploading to the online database, displaying it in the application, importing it into the dashboard platform, recording data updates and data extraction logs, and tracing data changes and extraction. The present invention realizes the internal data integration of small and medium-sized enterprises, reduces the difficulty of data extraction, has high security, improves real-time decision-making capabilities, and improves the overall work efficiency of the enterprise.

The invention relates to the technical field of data management, and discloses an online database management system and method based on enterprise management, and the system comprises a data acquisition module, an authority filling module, a data division module, a display module, a training module and a database background. The method corresponds to the system. According to the application, the structure of the database is optimized through the data acquisition module and the data division module, so that the phenomenon of confusion of the database is avoided; grading permission filling of the data is achieved through the permission filling module, and the risk of data leakage is reduced; a display file is generated through the display module, a data basis is provided for a salesman to display to a client by using an online database, and manpower waste is avoided; a training file is generated through the training module, a data basis is provided for training a salesman by using an online database, and material resource waste is avoided; and recording of the whole process of the data and management of the authority of the personnel are realized through the database background. And finally, realizing optimized online database management based on enterprise management.

An embodiment of the present invention provides a method, device and system for warehousing incremental data in an online database, wherein the method includes: obtaining incremental files to be stored; loading the data in the incremental files to be stored into a pre-created intermediate database; generating a script file for the data of the incremental files to be stored in the intermediate database to obtain a target script file, wherein the target script file is used to instruct to update the data of the incremental files to be stored in the intermediate database to the online target database; executing the target script file to update the data of the incremental files to be stored in the intermediate database to the online target database, thereby realizing automatic online incremental data storage of the online target database.

A method of providing Wi-Fi access point (AP) information in a user equipment (UE) is disclosed. The method comprises performing a scan by a Wi-Fi radio of the UE to obtain scan results of APs operating adjacent to the UE while the UE operates in a sleep mode with one or more processors of the UE operating in the sleep mode. Sending one or more of the scan results of the APs from the Wi-Fi radio to an always on processor (AOP) of the UE. Storing the scan results in an always on database (AON DB). And accessing the AON DB by the one or more processors of the UE when the UE is not operating in the sleep mode to enable the UE to display information for the one or more of the scan results stored in the AON DB.

This specification discloses a distributed data processing method, apparatus, storage medium, and electronic device. The method includes: acquiring streaming change events and node baseline dimension data for target business data nodes in an online database through a preset non-intrusive log data capture method; transmitting the streaming change events to a stream-batch integrated distributed storage system; using a real-time computing engine to perform dynamic time sharding processing on the streaming change events according to a preset time window strategy; calculating the multi-dimensional incremental aggregation value of each target business node in the current time window based on the baseline dimension data and superimposing it with the underlying baseline state snapshot to obtain a real-time aggregated state value; and updating the data of the target business nodes based on this.

Methods and systems are presented for providing a framework to generate a computer model to detect fraudulent electronic transactions. The framework selects and retrieves a set of transaction records from an online database system based on one or more indicators. The framework then enriches the set of transaction records with additional data associated with the set of transaction records. The additional data for each transaction record may include transaction data of another transaction record selected based on a common attribute shared with the transaction record. The framework serializes the transaction data and additional data associated with the set of transaction records. A feature set is derived based on analyzing the serialized data. The framework then generates a computer model for detecting fraudulent electronic transactions based on the feature set.

A waste analysis and certification station provides fully automated waste analysis and certification for verifying waste recovery for recycling and / or verifying the legitimacy of the recovery process, with different units fully controlled by an electronics, which automatically monitors and certifies the waste so that the certificates and / or the certified material can be securely sold. The station includes an automated transport unit, a subsequent connected sensing unit with a sensor, most preferred a camera, recording images, a subsequent detecting and certification unit effect-connected to a computational unit, a storage and display unit where certified data of each collected certified waste item is saved and made securely online accessible in an online database to the public and a waste collection and a guiding to a waste treatment process for recycling or destruction.

The invention, "QRistall," is a system for creating and managing QR codes for physical objects. QRRistall provides a platform where users can generate custom QR codes and affix them to physical objects. These QR codes contain detailed product information such as warranty information, user manuals, and product application videos. The unique QR codes serve as a link between the physical objects and an online database. Users can scan the QR codes for instant access to relevant information. Private users can create QR codes for their own products and store information such as purchase date, warranty status, and repair history. Manufacturers use QR codes to provide customers with warranty terms, troubleshooting instructions, and user guides.Businesses and service providers can create QR codes for their devices to provide information such as occupational safety inspections and work instructions. Retailers and vendors also have access to the QR codes to efficiently support customers and manage device histories. QRistall improves information delivery, promotes efficient device management, and offers comprehensive customer support. This system revolutionizes the interaction between physical objects and their users and has the potential to change how product information is provided and used.

The application relates to the technical field of databases and discloses a stored procedure-oriented online database migration method and system, which comprises the following steps: S1, performing deduplication filtering on stored procedures in a source file; S2, assigning an identifier to each stored procedure and initializing a triple dictionary; S3, serializing stored procedure request, forwarding the stored procedure to a source database based on the triple dictionary, and recording the frequency of each stored procedure; S4, translating the stored procedure with the highest frequency; S5, forwarding the translated stored procedure from the source database to a target database based on the triple dictionary, and executing the translated stored procedure by the target database; S6, checking the execution result of the stored procedure and performing data synchronization between the target database and the source database; and S7, repeating S3-S6 until the migration task is completed. The application can identify and classify stored procedures, and realizes the target of database migration through progressive translation reform.

The invention relates to a data processing and storage method and device, equipment, a medium and a product, and the method comprises the steps: obtaining step: obtaining incremental data from an offline database; in the processing step, the obtained incremental data is processed into processing data, and the processing data comprises data needing to be updated, data needing to be newly added and data needing to be deleted; in the monitoring step, data processing is monitored, and if data processing fails, an alarm is given; and a storage step: storing the processing data in an online database using one cluster. According to the data processing method and device, the technical problems that in a traditional mode, the data processing performance is poor, and storage resources are wasted are solved, the data processing performance is improved, and the storage space is saved.

The present application provides an offline voice word question-and-answer apparatus and method. The offline voice word question-and-answer apparatus comprises an offline database, a control module and an offline voice module; the offline database interacts with the control module to provide a word question-and-answer question, a word question-and-answer answer and a functional instruction; the control module interacts with the offline database to obtain the word question-and-answer question and the word question-and-answer answer, and interacts with the offline voice module to obtain a recognition instruction and send a determination result; and the offline voice module interacts with a user to recognize a user speech to obtain the recognition instruction, and play the determination result. The offline voice word question-and-answer apparatus of the present application uses an offline voice module and an online database, so that word question-and-answer can be carried out without the need for a network connection, and the application scenarios are broad; moreover, the offline voice word question-and-answer apparatus is not affected by network restrictions across different countries or regions, and is thus convenient to use and suitable for a wide variety of usage scenarios.

The invention discloses a method and a device of an online car-hailing voice assistant system based on deep learning, and particularly relates to the technical field of artificial intelligence. Online car-hailing order data is randomly selected from an online database, including recording of a user voice instruction and corresponding text conversion, and feature engineering processing is performed on the collected voice instruction data; the method comprises the following steps: generating a training set, a test set and a verification set, loading the training set and the test set, carrying out multiple rounds of training until a loss function converges, generating an auto-encoder model, reading verification set data, inputting the verification set data into the auto-encoder model, verifying the effect of the model on the verification set, and analyzing an output result. And inputting the data after real-time processing into a trained auto-encoder model to obtain a voice recognition and understanding result based on each order, and automatically processing the orders according to an output result of the model.

The present application discloses a quality information feedback method, an electronic device and a medium, the method comprising: collecting device information of a device to be tested, and generating a quality information feedback sample form according to the device information; generating a universal identification code according to the quality information feedback sample form; when it is detected that the universal identification code is scanned, receiving quality feedback information through the quality information feedback sample form, obtaining a feedback form, and sending the feedback form to an online database, wherein the quality feedback information is the information filled in by the user in the quality information feedback sample form; sending the feedback form to an instant messaging software, and generating a dynamic identification code according to the link address of the feedback form in the online database; generating an identification code label according to the feedback form and the dynamic identification code; when the dynamic identification code on the identification code label is scanned, displaying the target feedback information. According to the technical solution of the present application, there is no need to repeatedly record the information, so that the information can be updated in a timely manner and the efficiency of information feedback can be improved.

The invention discloses an online database recombination method, device and equipment, a medium and a product. The method comprises the following steps: determining a current positioning page located in a leaf layer in a B + tree of a database; exclusively locking all data pages on a path from a root node of the B + tree to the current positioning page and brother pages of the current positioning page; acquiring a right brother page of the current positioning page; and copying the records of the right brother page to the last part of the current positioning page in sequence until the current positioning page is full or the records of the right brother page are completely copied to the current positioning page, adjusting the structure of the B + tree and releasing all exclusive locks of the B + tree. The fragmentation problem of the current positioning page is solved, and the data orderliness of the B + tree is maintained; and when the index is recombined, exclusive blocking is not carried out on the whole data table, so that the influence on service logic is reduced, the recombined index and concurrent DML operation performance is better, the concurrency and availability of the database system are improved, and the overall performance of the database system is improved.

Computer-implemented method for verifying at least one postal item, preferably a letter, a parcel, a packet or a package; the method comprising at least the following steps: a. generate at least one encrypted data record in an online database on at least one server; b. create at least one transmission link to the data record by the server; c. Encoding the shipment link into at least one machine-readable shipment code, preferably a barcode and / or a QR code, by the server; d. affix, preferably by printing and / or engraving, the shipment code to at least one packaging element, preferably an envelope, a shipping bag, a shipping box and / or a sticker, for the postal shipment; e. transmit, preferably hand over or send, the packaging element to a sender of the postal item; f. Reading the transmission code and decoding the transmission link with at least one sender device, preferably a smartphone, tablet computer, laptop computer and / or desktop computer; of the sender; g. opening the encrypted data set with the sender's terminal device using the sender's personal key; h. activating the shipment code by entering shipment information comprising at least one electronic signature to authenticate the sender and preferably at least one name and / or address of a recipient of the mail item into the encrypted data record with the sender's terminal device; i. sending the postal item with the packaging unit by a postal service provider to the recipient; j. Reading the shipment code and decoding the shipment link with at least one authentication device, preferably a smartphone, tablet computer, laptop computer and / or desktop computer; of the postal service provider and / or the recipient; k. Opening at least part of the encrypted data set with the authentication device using a personal key of the postal service provider and / or the recipient; and I. Authenticate the sender using the electronic signature with the authentication device.

The invention discloses an intelligent mining method for ionic liquid lubrication performance data based on multi-modal deep learning, which comprises the following steps of: firstly, acquiring literature abstracts and key text segments in the field of ionic liquid from an online database, and constructing a field corpus; constructing an entity identification data set and a relation extraction data set containing predefined entity types by utilizing a labeling tool; secondly, on the basis of the general BERT model and the established corpus, continuous pre-training is carried out through tasks such as a mask language model, and a pre-training language model ILsBERT with a specific field is established; afterwards, the ILsBERT is finely adjusted by utilizing the entity identification data set, and named entity identification is carried out by adopting a mixed architecture of Transformer (ILsBERT), BiLSTM and CRF, so that enhanced semantic vector representation is obtained, and a text sequence tag is predicted; thirdly, utilizing the relation extraction data set to finely adjust ILsBERT, mining semantic relations between entities through a relation classification model, and forming a structured lubrication performance data set; and finally, carrying out standardization processing on the extracted data set, storing the data set into a structured database, providing data export, an API interface and a visual interface based on a Web framework, and supporting interactive data retrieval, filtering, statistical analysis and display. According to the method, efficient information extraction, standardized storage and visual analysis of the ionic liquid lubrication literature are realized through the field pre-training model and the specific downstream task architecture.