60 results about "Cloud computing big data" patented technology

The invention provides a deep reinforcement learning optimization algorithm based on an adaptive encryption framework, and the algorithm comprises ten steps: data input preprocessing, data sensitivity evaluation, system resource state acquisition, state vector construction, strategy decision, encryption execution, calculation reward, model updating, result output, and loop optimization. The method aims at solving the problems that encrypted data processing efficiency is low and safety is difficult to consider. According to the method, intelligent optimization of the encryption strategy is realized through the data sensitivity evaluation module, the adaptive encryption strategy adjustment module, the deep reinforcement learning optimization module, the parallel processing module, the resource scheduling module and the like. On the premise that the data security is ensured, the processing efficiency of the system is remarkably improved, and the method is suitable for scenes such as cloud computing, big data processing and the Internet of Things which need to process a large amount of sensitive data.

The invention relates to the technical field of production scheduling of manufacturing workshops, in particular to a distributed intelligent production scheduling decision-making system based on cloud computing. The system is composed of a cloud computing platform, a data acquisition module, a data processing module, an intelligent production scheduling engine and a distributed execution control module. The problems of performance bottleneck, data acquisition limitation, lack of flexibility and adaptability of a production scheduling scheme and the like in a traditional production scheduling system are solved, intelligent distribution and scheduling of production tasks can be realized through fusion application of advanced technologies such as cloud computing, big data and artificial intelligence, the production efficiency and the product quality are improved, and the production cost is reduced. And greater economic benefits and social benefits are created for enterprises.

The invention relates to the technical field of data analysis and calculation, in particular to a distributed scheduling method based on tasks, nodes and link resources, which is applied to a solution for task scheduling and management in a large-scale distributed system. The method is particularly suitable for cloud computing, big data processing and distributed storage systems which need to process mass data and high-concurrency requests. And dynamically adjusting resource allocation by using real-time monitoring data and a prediction algorithm in combination with task priorities and resource requirements. Compared with traditional static resource allocation, a dynamic resource allocation mechanism is adopted, resource allocation can be intelligently adjusted in real time according to task requirements and node resource conditions, and therefore the resource utilization rate and the task execution efficiency are improved.

The invention provides a data blood relationship analysis method and device based on a large model, equipment and a medium, and relates to the technical field of artificial intelligence, in particular to the technical fields of large models, cloud computing, big data and the like. The data consanguinity analysis method based on the large model comprises the steps of performing static analysis on to-be-analyzed content to obtain a static analysis result; generating prompt information based on the to-be-analyzed content and the static analysis result; inputting the prompt information into a large model to obtain initial blood relationship information output by the large model; and obtaining target blood relationship information based on the initial blood relationship information.

The invention provides an early warning method and device based on a large model, electronic equipment and a storage medium, and relates to the technical field of computers, in particular to the technical fields of large models, cloud computing, big data and the like. The specific implementation scheme is as follows: acquiring to-be-processed information of a target service; processing the to-be-processed information based on the large model to obtain at least one information analysis rule screened by the large model for the to-be-processed information; processing the to-be-processed information based on at least one information analysis rule to analyze potential risks and / or faults in the target service; and executing a corresponding early warning strategy under the condition of analyzing that the potential risk and / or fault exists in the target service.

The invention provides an intelligent conference management system, method and device based on a large model and a medium, and belongs to the technical field of computers. The system comprises a pre-meeting module used for automatically generating and sending a meeting invitation through an integrated enterprise schedule system, using telephone notification and IVR interaction to confirm a meeting participation form, and counting a meeting participation condition and a meeting arrival state; the in-conference module is used for collecting multi-source audios based on a microphone array in the conference process, transferring conference content in real time and generating subtitles in combination with a voice recognition technology, synchronously recording videos, recording process information of the conference, and performing structured analysis; and the post-conference module is used for extracting key indication information and backlogs in the process information of the conference, generating a standardized conference summary, automatically distributing tasks, tracking the progress and supporting semantic retrieval of historical conference records. According to the invention, a large model technology is utilized, and technologies of cloud computing, big data, artificial intelligence and the like are combined, so that automatic management of the whole conference process is realized.

The utility model belongs to the technical field of servers, and discloses a cloud computing big data storage server which comprises a cabinet body, a memory placing space located in the cabinet body and a hard disk quick pop-up structure assembled in the memory placing space, and the hard disk quick pop-up structure comprises a partition plate and a hard disk support located on the left side of the partition plate. By means of the design of the hard disk rapid pop-up structure, the installation process of the hard disk is greatly simplified, a user only needs to place the hard disk on the inner wall of the hard disk support and then push the hard disk support, the action can promote the movable plate to move backwards, meanwhile, the sliding blocks smoothly move in the sliding grooves, and the hard disk can be rapidly popped up. In the moving process of the sliding block, the stopping block and the limiting plate act together to limit the moving path of the sliding block, and the sliding block gradually slides into the clamping groove along with the continuation of the pushing action, so that the positions of the movable plate and the hard disk bracket are locked, and rapid installation of the hard disk is realized.

The invention relates to the field of cloud computing big data secure storage, in particular to a cloud computing-based big data secure storage method and system. The method comprises the following steps: performing encryption and fragmentation processing on an original data stream to generate a fragmentation sequence with an index; generating a dynamic key sequence and a verification key group based on the fragment information; constructing a secure transmission channel through a quantum key distribution mechanism in combination with a geographic position weight and a load balancing strategy, and realizing encapsulation and transmission of a secure fragment packet; node state monitoring and redundancy management are implemented, and an update mapping table is generated; and finally, a complete data stream is recovered through fragment positioning retrieval, data recombination and dynamic decryption. According to the invention, the security and reliability of data storage and the overall load balancing capability of the system are improved.

The invention discloses a personnel feature series-parallel method based on an organizational structure diagram. Historical related personnel elements are input for sample training; analyzing and generating key element features; forming a key element and related object decision tree; inputting a new related object condition set; performing intelligent mining analysis based on a decision tree; and the abnormal object is accurately pushed. According to the personnel feature series-parallel method based on the organizational structure diagram, based on new technologies such as cloud computing and big data, an existing big data resource system is fully utilized, through algorithms and means such as data mining and machine learning, an intelligent mining analysis model based on historical cases is constructed, the latest machine learning and deep learning algorithms are integrated, and the personnel feature series-parallel method based on the organizational structure diagram is obtained. The method improves the accuracy of related behavior recognition, provides an intelligent application handling scene for a worker through automatic learning of historical case investigation experience, intelligent analysis and inference, and precise pushing of an abnormal object of a new event, and achieves a new situation of intelligent handling and intelligent application handling.

The invention provides a personnel passing verification method and system based on space-time rule dynamic matching. The method comprises the following steps: identifying the identity of a passing person to obtain an identity label; acquiring current spatio-temporal information including current time and current position; according to the current spatio-temporal information, dynamic matching is carried out from a preset spatio-temporal rule set, a dynamic permission group is generated, and the rule set comprises a permission group template formed by combining authorization rules of a time dimension and authorization rules of a space dimension; and judging the passing authority according to the identity label and the dynamic authority group and outputting a decision result. The system comprises an identity recognition module, a spatio-temporal information acquisition module, an authority verification and decision module and an execution module which are used for executing the method. The invention relates to the technical field of personnel access verification, and in addition, the invention also relates to the field of Internet, cloud computing and big data service.

The invention relates to internet data services such as databases and cloud database services, more particularly belongs to the field of internet and cloud computing and big data services, and particularly relates to a method and a system for realizing intelligent sorting of data assets based on a self-research algorithm, which comprises the following steps of: constructing an intelligent sorting link of a target database; generating an initial field description set of the target database through a field description generation module of the intelligent carding link; according to the semantic consistency consensus level and the field description accuracy of the initial field description set, establishing a quality evaluation matrix corresponding to the intelligent carding link; according to the quality evaluation matrix, reconstructing a dynamic increment Schema processing mechanism corresponding to the intelligent carding link; and performing vectorization storage on the data assets finally confirmed by the dynamic increment Schema processing mechanism to complete data asset sorting of the business system to be sorted. According to the method, the storage result of the data assets can be ensured, and database Schema dynamic change in a complex business scene can be accurately adapted.

The invention discloses a risk assessment method based on mobile phone card information of a newly opened bank card. An information exchange technical specification channel is built; the public safety industry carries out risk resource construction by gathering, integrating and managing basic fraud-related source information; risk feature model construction is carried out by integrating financial and communication new card activating resources, and model monitoring is carried out on new card activating personnel; risk measurement construction is carried out according to the monitoring model information, and financial and communication risk assessment results are pushed; through integration of financial and communication new card resources, risk control construction is carried out, and a risk assessment model is corrected. Based on new technologies such as cloud computing and big data, an existing big data resource system is fully utilized, criminal activities are effectively prevented and fished, legitimate rights and interests of banks, operators and individuals are protected, property loss of the masses is reduced, and a safe and ordered social environment is created.

The present disclosure provides a commonality extraction method and device of an object, electronic equipment and storage medium, which can be applied to the fields of cloud computing, big data, intelligent supply chain, etc. The method comprises: obtaining a plurality of to-be-processed objects, and querying and obtaining dimension values of each to-be-processed object under a plurality of to-be-analyzed dimensions; determining a plurality of dimension groups according to the plurality of to-be-analyzed dimensions; determining a dimension value group under each dimension group and a co-occurrence probability of the dimension value group according to the dimension values of each to-be-processed object under each to-be-analyzed dimension; constructing a dimension tree based on the dimension value group and the co-occurrence probability thereof; and determining a commonality dimension result of the plurality of to-be-processed objects according to the dimension tree. The method can statistically process the dimension values under a plurality of dimensions, quickly determine the dimension value group that can be retained as the commonality dimension result of the to-be-processed objects by constructing the dimension tree, and achieve the effect of efficiently and accurately extracting commonality.

The present disclosure provides a cycle length determination method, device and equipment of traffic signal light and storage medium, relates to the fields of intelligent transportation, cloud computing, big data and the like. The specific implementation scheme is: according to the coordinate position and time stamp of each trajectory point in the target moving trajectory of a plurality of target objects in a set period, determine the switching point in the plurality of target moving trajectories;Wherein, the switching point is the trajectory point of the target object switching from the stop state to the moving state;According to the difference between the time stamp of each switching point, the cycle length of the traffic signal light is determined. Therefore, according to a large number of moving trajectories, the cycle length of the traffic signal light can be determined, which can improve the accuracy and reliability of the determination result.

The invention provides a data volume migration method which can be applied to the technical field of cloud computing and big data. The method comprises the following steps: in response to a data volume migration instruction, carrying out standardized identification on a demand document; based on the standardized recognition result, mapping the content of the demand document to a test scheme target chapter; generating chapter content according to the mapping result and the target chapter type; and generating a target test scheme based on the chapter content, wherein the standardized identification of the demand document comprises the following steps: determining a target keyword based on a preset rule or a historical reference statistical result; and if it is determined that the demand document contains the target keyword, determining that the demand document is a standardized document. The invention further provides a data volume migration device and equipment, a storage medium and a program product.

The invention relates to the technical field of operation and maintenance management in a distributed computing environment, and discloses a federated multi-cluster unified log and monitoring method and system, and the method comprises a log data collection module, a feature analysis module, a monitoring strategy generation module and a monitoring execution module. The log data acquisition module acquires historical log records, performance indexes and abnormal event data through a cross-cluster interface; the feature analysis module performs cleaning and feature extraction on the data by adopting a time window method and quantile calculation to generate log, performance and abnormal feature parameters; the monitoring strategy generation module performs strategy retrieval based on the knowledge graph space, and dynamically matches an optimal monitoring strategy; and the monitoring execution module carries out monitoring according to the strategy and analyzes the result. Uniform collection, intelligent feature analysis and self-adaptive monitoring of log data in a multi-cluster environment are achieved, the operation and maintenance efficiency and monitoring precision of a cross-cluster system are improved, and the method is suitable for distributed scenes such as cloud computing and big data.

The invention relates to the technical field of servers, and discloses a cold and hot data management method and system and a server. According to the method, data access behavior information is obtained, multi-dimensional prediction and business rule collaborative decision are combined, a data storage scheduling strategy is generated, and corresponding storage resource allocation operation is executed. According to the invention, the utilization efficiency of storage resources can be improved, the response capability of the system to high-value data is enhanced, and the compliance and safety requirements under the scenes of finance, e-commerce and the like are met. The method can be widely applied to cloud computing, big data platforms and distributed storage systems.

The invention relates to the technical field of operating systems, in particular to a method and a system for desensitizing file data of an operating system, which comprises the following steps of: in an operating system kernel, searching a kernel function table based on kprobe, replacing an openat system call function by registering an ftracefunction function, and executing a desensitization process on the file data of the operating system; constructing and storing an ftrace hook data structure containing a function name, a new function address, an original function address and ftrace operation information; the method has the beneficial effects that a file data desensitization security module is realized, file name capital writing, file data reverse-order writing and user keyword star number display are supported, a data desensitization function on an operating system level is realized, the security of the operating system is improved, and higher security capability is provided for applications such as cloud computing, big data and databases.

The present disclosure provides a method, apparatus, device, and medium for obtaining live videos, which relates to the field of artificial intelligence, and particularly relates to technical fields such as natural language processing, cloud computing, big data, computer vision, speech technology, and deep learning. The specific implementation solution is as follows: in response to a viewing request initiated by a first user, obtain a first video indicated by the viewing request; wherein, the sign language identifier in the viewing request represents whether the sign language recognition function is enabled; the status identifier of the first video represents whether the first video is a composite video in a co-hosting state; if it is determined that the sign language identifier represents that the sign language recognition function is enabled and the status identifier represents that the first video is a composite video in a co-hosting state, then convert the voice information in the first video into sign language information, and obtain and push the first video with sign language information to the first user. Through the above method, the first user can accurately obtain the effective information in the first video in the co-hosting state, improving the viewing experience of the first user.

The invention provides a security group configuration method and device, electronic equipment, a storage medium and a computer program product, and relates to the technical field of cloud computing big data, and the method comprises the following steps: detecting security group update information corresponding to a current service session; wherein the security group update information is the same as the communication metadata of the current service session; determining a current security group flow table corresponding to the current service session in a preset information set based on the security group update information; wherein the preset information set comprises a corresponding relationship between the communication metadata of each service session and the corresponding security group flow table; and deleting the current security group flow table, and configuring the security group update information based on the current service session.

The invention discloses a non-exchange data center internal network architecture based on free space optical communication, and belongs to the technical field of optical communication and data center networks. According to the framework, a server with a tunable light emitter, a light distribution beam combiner and the like are arranged in a cabinet, and non-line-of-sight communication is realized through a spatial light element; all-optical routing is completed through wavelength, spatial mode and time slot joint multiplexing, and a traditional electric / optical switch is not needed. The optical path routing in the architecture adopts passive devices, optical fiber wiring is avoided, online expansion of a cabinet and a server is supported, deployment and energy consumption cost is remarkably reduced, high-bandwidth, low-delay and low-power-consumption green data center communication is achieved, and the system can be widely applied to scenes such as cloud computing and big data.

1. The name of this design product: Smart Light Cloud Box. 2. Purpose of this design product: to serve as a link between cloud computing, big data and pan-intelligent life. 3. The design key point of this appearance design product lies in the shape. 4. The picture or photo that best illustrates the design points: three-dimensional picture.

The present invention discloses a cloud computing big data platform system based on microservices, including a big data platform and a cloud computing platform connected by a microservice module, wherein the cloud computing platform includes a virtual machine module, a container module, a CloudAgent module, a computing module, a mirror module, and a network module, and the big data platform includes a database module, a distributed file system module, a big data management module, a big data development module, and a big data application module. The present invention integrates the installation, configuration, and use of various open source big data technologies Hadoop, HBase, Hive, Spark, Zookeeper, Sqoop, Pig, Kafka, Flume, and Mahout, as well as program codes, sample programs, and running scripts into a virtual machine or container, and in this virtual machine or container, the CloudAgent program is installed and configured to realize functions such as configuring a big data cluster service, starting a big data cluster service, stopping a big data cluster service, and running a big data operation service. The present invention can realize centralized deployment of big data resources and on-demand use.

The utility model relates to the technical field of cloud computing technology, and discloses a display device for cloud computing big data management, which comprises a storage box and a lifting plate, door plates are rotatably connected to two ends of the upper part of the storage box, universal wheels are fixedly connected to four corners of the lower surface of the storage box, a two-way screw rod is arranged in the storage box, and the lifting plate is fixedly connected with the two-way screw rod. A first servo motor is fixedly connected to the side face of the storage box, the output end of the first servo motor penetrates through the storage box to be fixedly connected with one end of a two-way lead screw, the other end of the two-way lead screw is rotationally connected with the inner wall of the storage box, and the forward thread end and the reverse thread end of the two-way lead screw are both in threaded connection with sliding rods; the upper surfaces of the sliding rods are rotationally connected with supporting rods, the top ends of the supporting rods are rotationally connected with the lower surface of the lifting plate, the whole device can be folded into a storage box through cooperation of the bidirectional lead screws, the sliding rods, worm gears and worms, carrying and transferring are convenient, displaying can be conveniently conducted at different places, and the flexibility and convenience of displaying are improved.

The utility model discloses an instruction signal processing circuit based on a SW 831 EEB server, comprising an instruction receiving module used for receiving an instruction signal remotely sent by a user terminal and carrying out matching processing on the instruction signal; the amplifying and conditioning module is used for amplifying and conditioning the output signal of the instruction receiving module so as to adapt to subsequent processing; the SW 831 EEB server is used for receiving the instruction signal output by the amplifying and conditioning module and processing and executing the instruction signal; the instruction receiving module uses an impedance matching network and an isolator to reduce signal distortion and interference, so that weak instruction signals are effectively received; the amplification conditioning module effectively improves the transmission quality of instruction signals, and improves the anti-interference capability and reliability of the whole system. The SW 831 EEB server can provide stable and efficient services, and the strict requirements of the fields of cloud computing, big data analysis, the Internet of Things and the like on a high-performance computing platform are met.

According to the urban rail system based on the rail transit intelligent operation platform and the scene disposal method thereof, the technologies of the Internet of Things, cloud computing, big data, artificial intelligence and the like are fully utilized, and the dilemma that a traditional urban rail system is closed, isolated, solidified and isolated in information is broken through; a plurality of general technology platforms are integrated into a multi-field and multi-service fusion rail transit intelligent operation platform, the rail transit intelligent operation platform is used for system equipment access, data processing and analysis, algorithm construction and scene flow arrangement, customized construction and implementation can be carried out according to differentiated construction requirements of cities, a scene function design mode is adopted, and multi-field and multi-service fusion is realized. Rail transit application scenes such as intelligent passenger service, intelligent transportation, safety emergency command, intelligent train operation, station service management, section field comprehensive management, intelligent energy management, infrastructure protection and enterprise network management are constructed based on the rail transit intelligent operation platform, and the intelligent level and the application development efficiency of an urban rail system are improved.

The invention relates to the technical field of electric power safety monitoring, and particularly discloses an electric power safety monitoring system and method based on a cloud platform. Comprising the steps of constructing a cloud platform module, a self-adaptive data acquisition module, a power balance analysis and judgment module, a power grid anomaly analysis and judgment module, a power data error adjustment module, a power safety analysis module, a power safety evaluation module and a man-machine interaction module; according to the invention, the cloud platform is constructed to carry out adaptive data acquisition and analysis to obtain the power balance evaluation coefficient and the power grid abnormity evaluation coefficient, the power safety evaluation index is obtained through analysis, and the power safety evaluation index is compared with the preset safety threshold to judge whether the power system has safety abnormity or not. The on-cloud and under-cloud adaptive joint protection technology is introduced, and through integration of cloud computing, big data analysis and artificial intelligence advanced technologies, many defects of a traditional system are overcome, and the safety and stability of a power system are significantly improved.

The invention relates to the technical field of Internet, cloud computing and big data service, and discloses a staff education platform system integration method and system, and the method comprises the steps: obtaining a real-time behavior event set of a platform user, extracting a cross-behavior association rule, and generating a dynamic feature vector group; collecting interface response time delay parameters and load state data of each subsystem, and constructing a resource state topological graph; superposing the dynamic feature vector group on a resource state topological graph in a time dimension, marking a space-time mismatching region of resource distribution and demand density, and generating a demand overflow coordinate set; if the resource gap density of the demand overflow coordinate set exceeds a preset system pressure-bearing threshold value, dynamically adjusting default service priorities among subsystems, and constructing a dynamic compensation channel of the staff education platform; and configuring the dynamic compensation channel to the platform integrated gateway, outputting a resource redistribution instruction set, and executing cross-system deployment verification. According to the invention, the integration efficiency of the staff education platform system can be improved.

The utility model discloses a cloud computing big data storage device, which comprises a mounting seat and a big data storage device body, the bottom of the big data storage device body is fixedly connected with the top of the mounting seat, and the left side of the rear side of the top of the mounting seat is fixedly connected with an electric telescopic rod. The right side of the front side of the top of the mounting base is fixedly connected with a time relay. According to the big data storage device, the electric telescopic rod is arranged, the electric telescopic rod is started to drive the transmission frame to move left and right, then the transmission frame drives the scraping strip to scrape dust on the surface of the big data storage device body, and the problems that the installation position of the storage device is usually exposed, and if dust in the installation environment is too much, dust cannot be scraped off are solved. The problems that when the storage device is used for a long time, dust in air is prone to being attached to and accumulated on the surface of a shell of the storage device, heat dissipation of the storage device is affected, and the use effect of the storage device is reduced are solved, and the auxiliary cleaning effect is achieved.