24results about How to "Avoid bottlenecks" patented technology

The invention discloses a multi-device cooperative management system based on cloud edge cooperation, and relates to the technical field of Internet of Things communication, and the system comprises a device management module which is used for connecting edge devices, carrying out the centralized management of the edge devices, and carrying out the optimal scheduling based on the functions and distribution positions of different edge devices; and the data acquisition module is connected with the equipment management module. According to the multi-device collaborative management system based on cloud edge collaboration, a comprehensive and accurate data basis is provided for multi-device collaborative management, and information exchange and collaborative work between devices are promoted; the optimization decision-making unit can formulate an equipment optimization management strategy according to the operation scheme generated by the big data analysis unit and the prediction result obtained by the prediction analysis unit, and continuously performs optimization adjustment according to the real-time operation condition of each piece of edge equipment; therefore, the system can adapt to continuously changing equipment operation environments and task requirements, and more efficient multi-equipment collaborative management is realized.

The invention relates to the technical field of big data, and particularly discloses a business data processing method and device, computer equipment and a readable storage medium. The method comprises the following steps: in response to a resource registration request for target service data, grouping the target service data to obtain a plurality of grouped data; the target business data comprises any business data in the business data uploaded by the plurality of resource transaction channel ends; storing the grouping information of the plurality of grouped data to a clearing task queue list corresponding to the target business data; issuing the task processing message to enable a plurality of servers subscribing the task processing message to obtain grouping information from the clearing task queue list in parallel, and executing a registration subtask on the grouping data according to the grouping information; and according to the sub-task execution states of the grouped data returned by the plurality of servers, determining resource registration operation results of the plurality of grouped data. By adopting the method, the accuracy of business data processing can be improved.

The invention relates to the technical field of data processing, in particular to an intelligent feature exploration system and method for structured data, and the system comprises a preprocessing module which obtains a structured data set; the feature acquisition module analyzes the structured data set and acquires structural features and type features; the algorithm determination module calculates an actual evaluation value based on the data structure features and the data type features, compares the actual evaluation value with a preset evaluation value, and determines an execution algorithm unit; the generation module generates an initial execution workflow according to a preset operation rule; the distribution module divides an initial execution workflow, calculates task complexity, distributes a plurality of processing nodes, and monitors a real-time load condition to perform calculation power distribution; the monitoring module executes a computing power distribution result, collects operation data and calculates an actual health score; and the adjustment module compares the actual health score with a preset health score, and adjusts the initial execution workflow to obtain a target execution workflow. According to the invention, the efficiency of the data analysis processing process is improved.

The invention discloses an RDMA high-performance network multi-service multiplexing method and system on a virtualized host. The method comprises the following operation steps that network service data programmed through a Verbs interface by using an RDMA protocol and network service data programmed through a socket interface by using a TCP / IP protocol are transmitted at the same time; and performing dynamic balance operation of each level on the network service data, transmitting the network service data subjected to the dynamic balance operation of each level to a physical network card, packaging the network service data to obtain an Ethernet message, and sending the Ethernet message to a physical network.

The invention relates to the technical field of transportation equipment, in particular to an automatic stacking device which comprises a tray collecting and delivering module, a tray centering module, a grabbing module and a tray steering module. The tray collecting and delivering module is used for delivering the collected trays to a conveying line; the tray centering module is used for centering each tray sent by the tray collecting and sending module on a conveying line; the grabbing module is used for grabbing goods to the centered tray; the tray steering module is used for steering the transportation direction of a tray loaded with goods; and the turned tray is transported to the shaping table, and the shaping table is used for adjusting the placing position of the goods on the tray. The structural design of each process module is compact, the overall occupied area is small, operation is flexible, and the transportation efficiency is high.

The invention relates to the technical field of image transmission, in particular to an energy consumption self-adaptive management method and system of a wireless image transmission module. Comprising the steps of obtaining operation data of at least one node, and analyzing a network load to adjust interaction frequency configuration; load balancing parameters are determined according to interaction frequency configuration, transmission task priorities are dynamically adjusted, node energy consumption data are collected, and resource waste points are checked to update an energy consumption distribution scheme; predicting the traffic of a transmission path according to an energy consumption distribution scheme, optimizing path allocation and reallocating resources when the traffic is greater than a set value, and updating node state shared data; and finally, the network operation state is calibrated according to the node state shared data, and energy consumption optimization configuration is obtained, so that energy consumption is reduced, and network efficiency is improved. According to the invention, the problem that the energy consumption management of the wireless image transmission network is difficult to finely regulate and control along with the load change is solved, and the self-adaptive energy conservation and stable transmission of the distributed image transmission module are realized.

The invention discloses an Internet of Things signal adjusting system, belongs to the technical field of Internet of Things, and aims to solve the problems that data reliability and accuracy are reduced due to loss of logistics data transmission and overlarge errors, and bottleneck and blockage are caused due to the fact that logistics transportation paths and modes are often influenced by signals. By testing and optimizing the signal adjusting system, the reliability and stability of the system can be improved, the system can be popularized and applied, the application range of the Internet of Things in logistics and supply chain management is expanded, and the operation efficiency and speed of the whole supply chain are improved; all the modules of the system are comprehensively tested, so that the stability and reliability of the system are ensured, and the system is optimized and improved according to the test result.

The invention relates to a sketch general configuration method and system based on a data processing unit, and belongs to the technical field of data processing. The method comprises the following steps: (1) identifying resource parameters; (2) selecting a process model; (3) resource constraint input; (4) optimizing target configuration; and (5) parameter configuration recommendation. The invention aims to optimize the communication efficiency of the DPU and the host, reasonably allocate hardware resources, and realize flexible process model selection and efficient state operation configuration, thereby achieving the goals of high accuracy and high throughput of network measurement under limited resources.

The present invention relates to the field of industrial Internet technology, and in particular to a data processing method based on an industrial Internet data platform. The method comprises the following steps: using the industrial Internet data platform to process industrial production context and generate real-time industrial production context data; constructing a production process constraint knowledge graph based on the real-time industrial production context data; using the production process constraint knowledge graph to match order priorities and generate order priority allocation data; performing production plan conflict detection based on the order priority allocation data to obtain subtask production conflict data; performing flexible scheduling processing based on the subtask production conflict data to generate conflict-free production subtask network data; performing key task path chain identification based on the conflict-free production subtask network data to obtain final production plan data. The present invention eliminates conflicts in production plans and significantly improves production efficiency through flexible scheduling of task chains.

The application provides a damping type linear generator, a design method and a damping control method, and belongs to the field of rail transit. The damping type linear generator comprises a superconducting coil, an 8-shaped coil and a damping type current collection coil. The damping type current collection coil is arranged in the superconducting coil shell on both sides of the superconducting motorized magnetic suspension train bogie, is used for collecting the energy of the air gap harmonic magnetic field of the 8-shaped coil, and directly supplies power to the on-board electrical equipment and the battery after rectification and filtering, and generates electricity by using the harmonic magnetic field in the train system. The damping type current collection coil is also used for receiving the stable current injected from the on-board power converter converted from the battery. At this time, the damping type current collection coil simulates the superconducting coil magnetic field to generate additional electromagnetic damping force, so as to reduce the vibration amplitude of the bogie in high-speed operation and improve the stability of the superconducting motorized magnetic suspension train in operation. The application improves the stability of the bogie in the operation of the magnetic suspension train.

The present invention relates to the technical field of load regulation, and in particular to a method for realizing multi-core concurrent load of a cluster file system client. The method comprises the following steps: obtaining cluster file client task data; performing task splitting on the cluster file client task data to generate subtask sorting data; performing available resource analysis on the cluster file client to generate client available resource data; performing virtualized ultra-fine-grained task division on the subtask sorting data according to the client available resource data to generate ultra-fine-grained virtual task list data; performing type judgment rule engine construction on the ultra-fine-grained virtual task list data to generate a task type judgment rule engine. The present invention improves the concurrent processing capability and overall performance of the system by performing task splitting, intelligent scheduling, asynchronous communication, and performance analysis on the cluster file client task data.

The invention relates to the technical field of stream-oriented computing, in particular to a visual computing model construction method based on stream-oriented computing. The method comprises the following steps: acquiring a streaming computing data set; performing data preprocessing on the streaming computation data set to obtain a standard streaming computation data set; extracting calculation nodes of the standard stream-oriented calculation data set to obtain calculation node data; performing correlation analysis on the calculation node data to obtain node correlation data; performing network configuration analysis on the calculation node data to obtain node network configuration data; performing node type analysis on the calculation node data to obtain node type data; and performing node function analysis according to the node type data to obtain node function data. Therefore, by means of the Internet of Things technology, the intelligent control technology, the visualization technology and the block chain technology, the dynamic adjustment and distribution capacity of flow-oriented computing is improved, and the real-time monitoring and feedback capacity of a visual computing model of flow-oriented computing is enhanced.

The application provides a memory access management method, device and electronic equipment. The method provided by the application comprises: according to a memory access request or a read-write request received in a current clock cycle, counting a total number of memory blocks that need to be accessed in the current clock cycle; according to the total number and an average value of the number of memory blocks that need to be accessed in a preset number of historical clock cycles, determining an access increment; when the access increment is greater than a preset threshold, executing a warm-up process; the warm-up process comprises: taking the average value as an initial value of the number of memory blocks that need to be accessed, gradually increasing the number of memory blocks that need to be accessed according to a preset increasing rule, until the number of memory blocks after the increase is greater than or equal to the total number, to gradually increase the access intensity, so that the on-chip storage unit completes the warm-up process and enters a stable state. The memory access management method, device and electronic equipment provided by the application can make the on-chip storage unit smoothly transit to a high-load state.

The invention relates to the field of calculation and management of decommissioned soldiers' preferential tendencies, and discloses a calculation method of decommissioned soldiers' preferential tendencies, comprising the following steps: S1, initializing variables, and inputting key information of decommissioned soldiers; s2, based on a preset condition, screening superior and standby objects meeting policy regulations; s3, verifying the identity information of the screened superior object; s4, performing authentication management on the preferential objects which need to be authenticated regularly; and S5, according to the type of the preferential object, the family condition and the service record, a preset formula or model is adopted to calculate the tending amount. By introducing an automatic process and a precise calculation model, the calculation efficiency and accuracy of the decommissioned soldier's superior tend-fund are improved, manual errors are reduced, the accuracy of identity verification and issuing is ensured by docking with a national database, and meanwhile, the security and traceability of data are enhanced by enhancing data management, so that the labor intensity of the decommissioned soldier's superior tend-fund is reduced, and the service life of the decommissioned soldier's superior tend-fund is prolonged. And a fair and reasonable T-shirt issuing service is provided.

The application provides a time-frequency-space domain resource coordination optimization method in a multi-network fusion communication scene, relates to the field of space-air-ground integration, and comprises the following steps: a multi-network fusion communication model is constructed, and a multi-network fusion communication process is divided into an access stage and a backhaul stage; in the access stage, a channel model of a ground terminal to a ground access point and a channel model of the ground terminal to a relay unmanned aerial vehicle are respectively established, and in the backhaul stage, channel models between a relay unmanned aerial vehicle and a satellite and between a ground access point and a cloud server are respectively established; an access stage optimization problem and a backhaul stage optimization problem are respectively constructed; a feasible trajectory of the unmanned aerial vehicle is generated based on K-means clustering, and a linear programming sub-problem under a fixed trajectory that can be solved is obtained; and the backhaul stage optimization problem is split into a backhaul sub-problem of the unmanned aerial vehicle to the ground access point and a short-wave backhaul sub-problem. The application globally improves system throughput, resource utilization and task reliability under the multiple constraints of unmanned aerial vehicle movement, terminal rate, minimum traffic volume and the like.

The present application provides a kind of hanger conveying system, including the hanging device with multiple workstations, control host and management terminal, wherein management terminal is connected with control host, with management information storage part, work station real-time statistics part, work station allocation part, so it can be according to the real-time state information of each work station obtained from control host Statistics the real-time hanger number of hanger in each work station, and based on real-time hanger number for hanger allocation next process work station and send to control host, control host controls hanging device according to the work station allocated and transports hanger to corresponding work station for processing, therefore, the hanger conveying system of the present application can be balanced according to the real-time state of each work station Work load allocation, avoid some work stations become bottleneck or long time idle in system, greatly improve the overall processing efficiency of system.

The present application belongs to the field of communication technology, and particularly relates to a kind of on-chip ultra-wideband white noise generation method based on chaotic micro-ring optical frequency comb, the implementation of the method includes semiconductor laser, micro-ring resonator, photodetector, characterized by: semiconductor laser, micro-ring resonator, photodetector are integrated in the same chip substrate;Semiconductor laser output continuous light injection micro-ring resonator will occur four-wave mixing, self-phase modulation, cross-phase modulation and dispersion combined action, after being output through micro-ring resonator straight-through end, equal-interval chaotic optical frequency comb is generated, and then through the beat of multiple chaotic optical frequency comb, high-bandwidth noise signal can be realized.The present application compared with existing noise source, simple structure and has smaller volume, low power consumption, high stability and bandwidth expandable advantage.

The invention relates to the technical field of parameterization design, and particularly discloses a computational fluid mechanics simulation optimization design method and system.The method comprises the steps that an automatic script is recorded in an MATLAB main program, initial values of a plurality of design variables are specified, ANSYS Workbench is called based on the automatic script to conduct modeling on the initial values of the design variables, and a geometric model is obtained; calling MESH software based on the automatic script to carry out automatic grid division on the geometric model to obtain a grid file; and calling FLUENT software to carry out fluid mechanics numerical simulation on the grid file to obtain a numerical simulation calculation result, and calling CFD-POST software to store the numerical simulation calculation result into a specified file. Reading a numerical simulation calculation result in the specified file based on MATLAB, optimizing the numerical simulation calculation result, and outputting an optimization result; and updating the initial values of the plurality of design variables and the parameters of the grid file based on the optimization result. According to the method, the workload of manually drawing the model in optimization is reduced, and the working efficiency of optimization is improved.

This invention provides a method for accelerating real-time inference of multimodal large models, relating to the field of data processing technology. The method includes: Step 1, generating a minimum envelope ellipse using the peak point of the first visual attention weight, the second visual coordinate point, and the third visual association point as boundary points, and calculating the ratio of the area to the perimeter of the ellipse as a spatial clustering index. This invention effectively improves the efficiency, accuracy, and resource utilization of real-time inference of multimodal large models by selectively enhancing spatial features, evaluating multidimensional constraint computing power and dynamically scheduling resources, lightweight cross-modal fusion, and multi-step inference attention calibration, combined with real-time decision-making and full-process data-driven evaluation parameters and dynamic updates of the model library. This ensures the real-time performance and reliability of inference results, while continuously optimizing system computing power evaluation and model adaptation, making multimodal inference more aligned with the resource constraints of heterogeneous computing and the real-time and accuracy requirements of actual business operations.

The invention provides an intelligent substation data flow scheduling model training method, scheduling method and device based on a TSN, and the method comprises the steps: equivalently reconstructing a new graph through a link topological structure and a link state of an intelligent substation, and constructing a state space in combination with parameters of newly-added periodic time sensitive flow data flow and newly-added non-periodic time sensitive flow data flow; an actor network pair in the actor commentator network is introduced to calculate and select each candidate node of a next link, and selection probabilities are constructed into an affinity set; searching, simulating and complementing subsequent walk link nodes according to a Monte Carlo tree, calculating an actual profit value, and updating an actor network and a commentator network; the next walk link node is selected in the application based on the trained actor network, the time slot update state is allocated, and the operation is repeated until the target node position is reached, so that the deterministic transmission requirement on the heterogeneous time sensitive data in the TSN network can be ensured, and the overall network stability is improved.

This invention relates to the field of medical device technology, specifically to a physiotherapy lamp. It includes a support frame, on which an irradiation assembly is mounted. The irradiation assembly includes a fixed frame, within which a housing is slidably disposed. An irradiation unit is fixedly disposed within the lower end of the housing. The housing is fixedly connected to a connecting assembly, which is slidably connected to the fixed frame and to an air pump. Multiple air tubes are disposed below the housing, with multiple nozzles fixedly connected to their lower ends. Sliding rods are slidably disposed at both ends of the fixed frame below the housing. One end of a folding plate is fixedly connected to a sliding rod, and the other end of the folding plate is fixedly connected to the fixed frame. The ends of the sliding rods are connected to the fixed frame via spring bellows, the interior of which is connected to one end of a second channel opened within the fixed frame. This invention allows the housing to move upwards and cut off the light source when the patient accidentally gets up, preventing high-temperature radiation from directly hitting the skin. The folding plate then unfolds, blocking residual heat conduction paths.

The invention provides an electronic file data processing method and system based on big data, and relates to the technical field of data processing.The electronic file data processing method comprises the steps that electronic file data are obtained, preprocessing and category splitting are conducted on the electronic file data, file splitting data packets are obtained, and then distributed storage data packets are obtained; carrying out data processing capability analysis on the obtained preset service cluster, carrying out processed capability analysis on the distributed storage data packet, respectively carrying out simulation processing service analysis, and further carrying out simulation processing judgment on the distributed storage data packet; and acquiring a cluster processing sequence and a data packet sequence, and performing actual processing and updating processing on the distributed storage data packets through the preset service clusters with the same ranking to obtain a processing result, thereby realizing comprehensive management and optimization processing on the electronic file data.

The invention relates to the field of 5G network resource management, in particular to a 5G network resource dynamic allocation method. The method comprises the following steps: acquiring resource requirements and available resources of nodes in a 5G network, forming resource states of the nodes, and further forming a resource state matrix; a multi-dimensional harmonic mapping distribution algorithm is introduced to update the resource requirements of the nodes, and the resource state matrix is further updated; calculating the global resource pressure of the node based on the updated resource state matrix; performing nonlinear resource adjustment optimization on the updated resource demand to obtain a final resource demand; and performing resource allocation based on the final resource demand. The problem that many scheduling algorithms cannot fully consider resource interaction and mutual influence between nodes is solved; in the prior art, in a high-dynamic environment, the reaction speed is low, and resource allocation is difficult to adjust according to a network state changing in real time; and in a peak load scene, an existing resource allocation algorithm is difficult to realize rapid balance of network resources.

The present invention proposes a data processing method for an intelligent gateway protocol, including: collecting data transmission data, building an adaptive deep learning model, and dynamically optimizing the protocol conversion strategy; building a load prediction model, optimizing the protocol conversion strategy and dynamically allocating network resources; building an edge computing model and training the edge computing model, and using the edge computing capability of the edge computing model to locally process data and make decisions; building a collaborative control model and a feedback mechanism, and using the collaborative control model to perform real-time collaborative control of intelligent gateway devices; using blockchain technology to encrypt and verify the data transmission process; designing the optimal configuration scheme of intelligent agent technology, and simultaneously monitoring the status of intelligent gateway devices in real time, predicting and pre-maintaining potential failures of intelligent gateway devices. The present invention improves data transmission efficiency, system performance and security by introducing adaptive deep learning, edge computing, reinforcement learning, blockchain and intelligent agent technologies.