38results about How to "Reduced execution time" patented technology

The invention provides a natural language SQL (Structured Query Language) conversion method based on a data platform and a large language model, which relates to the technical field of data processing and comprises the following steps of: performing vectorization storage on metadata, blood relationship, indexes and historical query information, performing intention judgment and vector matching on a user query request, and determining a query condition based on a matching result. An association path is constructed according to data consanguinity, and an optimal SQL statement is generated by utilizing a historical query optimization table connection sequence and combining index matching. According to the method, intelligent conversion from the natural language to the efficient SQL can be realized, the query efficiency is improved, and the use threshold of a user is reduced.

The invention discloses a heterogeneous computing architecture testing method of an ISP module, and belongs to the technical field of heterogeneous computing. According to the technical scheme, a high-level synthesis tool is used for generating and verifying an IP to be tested; a target algorithm IP application system is constructed by using a microprocessor IP hardcore and an AXI bus connector of a heterogeneous computing platform, a target algorithm IP core is operated by using software to carry out an application test, and actually measured data is stored in a nonvolatile storage medium; transplanting an operation system and an OpenCV library to the heterogeneous computing platform for the development board, and storing a target algorithm software operation result to a data file after a test program is operated; and evaluating the function correctness and the performance index of the target algorithm IP by using the actually measured data and the software operation result. The method has the advantages that effective testing and optimization of the heterogeneous computing architecture of the ISP module are achieved through the software and hardware co-simulation and IP core verification technology, middle-level optimization, a comprehensive testing framework and other methods, and powerful support is provided for technology development, application and popularization in related fields.

The invention discloses a database query method, device and system and a medium, and the method comprises the steps: receiving a database query statement, analyzing the query statement to generate an execution plan of a tree structure, segmenting the execution plan, and obtaining a plurality of execution plan subtrees; matching the plurality of execution plan sub-trees with the intermediate result set in the cache, and determining whether intermediate result set sub-trees equal to the execution plan sub-trees exist in the intermediate result set or not; if an intermediate result set sub-tree equal to the execution plan sub-tree exists in the cache, replacing the successfully matched execution plan sub-tree with the equal intermediate result set sub-tree, and generating a replacement execution plan; and performing scheduling execution according to the replacement execution plan to obtain a corresponding database query result. The subtrees in the execution plan are matched and replaced through the intermediate result set in the cache, so that the intermediate result set in the cache can be directly used in subsequent execution operators, resource consumption and execution time are reduced, and database query performance is improved.

The application discloses a memory fault detection method and system based on a four-cell coupling model, and relates to the field of memory fault detection.In the method, four adjacent memory cells arranged in a square are taken as a basic test unit, four data backgrounds, namely, a full zero background, a horizontal alternating background, a chessboard background and a double-row alternating background, are generated by a preset or dynamic generation method, and an optimization strategy of performing read and write operations on only the cells needing to change states when the data background is switched is adopted, so that full coverage detection of various non-associated static fault types, including single-cell faults and various coupling faults such as adjacent double cells, diagonal double cells, right-angle type triple cells and square type four cells, can be realized.The complete test sequence complexity of the algorithm is low, the test time is reduced under the premise of ensuring high fault coverage, and the test efficiency of high-density memory is effectively improved.The algorithm has high flexibility and configurability.

A method for facilitating playing a legacy game is described. The method includes receiving user input during the playing of the legacy game, determining whether one or more code blocks for servicing the user input are cached, and accessing one or more instructions of legacy game code upon determining that the one or more code blocks are not cached. The method also includes compiling the one or more code blocks from the one or more instructions of the legacy game code, caching the one or more code blocks, and executing the one or more code blocks to display a virtual environment.

This invention discloses a cloud platform computing power resource allocation system and method based on load balancing, relating to the field of computing power resource allocation technology. The application includes: constructing a computing power supply and demand matching platform, connecting with idle computing power resource providers, and receiving computing power requests from computing power resource lessors; based on the computing power requests from the lessors, determining the cluster time, and allocating idle computing power resources to the lessors in the cluster; the lessors setting up key communication, and after key verification, the system accessing the cloud platform of the allocated lessor, achieving intelligent decision-making and optimizing the scheduling of allocated idle computing power resources in the cloud platform. This invention can maximize overall resource utilization, reduce operating costs, minimize task execution latency, and improve user experience. Simultaneously, dynamic allocation based on computing power sharing and cluster processing according to different time nodes improves the overall utilization efficiency of computing power resources.

This utility model discloses a gripping and rotating coordinated apple-picking end effector, installed at the end of a picking robotic arm, comprising a cylindrical housing, a linear motor, a transmission mechanism, and a gripper assembly. The transmission mechanism converts the linear motion output by the linear motor into linear and rotational motions. The gripper assembly opens and rotates via an upward motion, and closes and rotates in the opposite direction via a downward motion to twist and break the fruit stem. The transmission mechanism uses a pin sleeve in cooperation with a central groove shaft, and achieves step-by-step movement through a spiral groove and a limiting groove structure. The gripper assembly completes clamping and twisting through a guide ridge and a hinge seat. This design simplifies the drive structure, reduces costs, improves reliability and picking efficiency, and is suitable for apple picking scenarios with short stems and dense branches.

The invention relates to a chained SVG control system and a configuration method thereof, and belongs to the technical field of power electronics. The method is used for configuring a chained SVG control system of which a controller adopts a heterogeneous dual-core processor architecture based on an FPGA (Field Programmable Gate Array), and comprises the following steps: a control algorithm in the chained SVG control system is realized by an FPGA core, and a control logic in the chained SVG control system is realized by another core; the control algorithm comprises a virtual synchronous control function, commutation chain voltage sharing, control instruction generation and harmonic suppression; the control logic comprises chain type SVG control system start-stop control, unlocking and locking sequence control logic, chain type SVG control system state conversion and main and standby system switching. The control system comprises the controller, the controller adopts a heterogeneous dual-core processor architecture based on the FPGA, and the controller is configured by adopting the method. According to the method, on the premise that control hardware configuration is not changed, the execution time of a control algorithm is greatly shortened, and the cost is low while the control capability of the controller is improved.

The invention belongs to the technical field of artificial intelligence, and relates to a target detection method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining a playback image set and a pre-trained target detection model which comprises a front layer, a playback layer and a full connection layer; during forward propagation, inputting a training playback image to a front layer, extracting image features, obtaining an activation value corresponding to the training playback image from playback storage, connecting the image features and the activation value in a playback layer, inputting a connection data structure to a full connection layer, and determining a category result of a target object; and during back propagation, calculating a gradient according to a category result, updating a weight parameter of the full connection layer, and obtaining a trained target detection model. In addition, the invention also relates to a block chain technology, and data such as a target detection model can be stored in a block chain. According to the method and the device, disastrous forgetting of the model can be overcome, and accurate and efficient object detection can be realized on the edge equipment with limited resources.

The invention relates to the technical field of approximate network-on-chip, discloses a convolutional neural network acceleration-oriented high-real-time approximate network-on-chip, and provides an approximate compression and segmented recovery scheme based on data classification in combination with the data distribution condition of a neural network, so that the reasoning precision of the neural network is kept while the communication overhead is reduced; a quality control model is provided, and the model can quickly search threshold values of all layers of the neural network meeting quality loss constraints, so that the network is ensured to keep accuracy while performing approximate communication; a threshold value dynamic adjustment scheme based on congestion sensing is further provided, and the approximate threshold value of each layer is dynamically adjusted by sensing the congestion condition in the network, so that the real-time optimization of the data compression rate is realized, and the congestion problem in the communication network is effectively relieved; and in combination with activated data distribution characteristics in a network after approximate communication, an approximate calculation module in the calculation array is optimized, the overall efficiency of the calculation array is improved, and calculation acceleration is realized.

The invention discloses a construction method of an application algorithm execution cost prediction cost model and an end-to-end application algorithm perception graph division method. The method comprises the following steps: firstly, constructing a calculation cost prediction model through machine learning so as to accurately quantify the real calculation and communication cost of processing graph data by a specific application algorithm on a calculation node; then, a cost sensitive graph neural network model named CoSTA-SAGE is designed, and the predicted cost is used as a direct optimization target; through end-to-end learning, a load balancing (variance minimization) and efficient (bottleneck minimization) division scheme on real cost is generated. In order to realize the target, the method comprises two core parts: cost model construction for predicting the execution cost of the application algorithm and a graph neural network division process for performing end-to-end optimization based on the prediction cost.

The invention discloses a model training method and system based on artificial intelligence, a medium and a product, and relates to the field of data processing systems or methods specially suitable for administrative, commercial, financial, management, supervision or prediction purposes. Tasks with the same preposed continuous logic units are aggregated into a practical training task group, the preposed units serve as common baseline workflows to be separated from the tasks, and remaining independent training logics of the tasks are converted into personalized derivative workflows. A first computing resource is allocated to perform single centralized execution on the common baseline workflow to generate a reference context slice. And distributing a second computing resource for each derivative workflow, distributing the reference context slice for environment reconstruction, and executing each personalized derivative workflow in parallel, thereby completing concurrent training of multiple tasks. According to the method, the computing power redundancy consumption caused by high-similarity training tasks is reduced, and the overall efficiency of task scheduling is improved.

The invention relates to an automatic discovery and link construction technology of network equipment applied to equipment management and network operation and maintenance in an optical network, in particular to automatic sniffing, equipment identification, link construction and topology generation of PON (Passive Optical Network) equipment realized through a remote TELNET protocol. The method comprises the following steps: S.1, obtaining PON equipment information based on a TELNET protocol; s.2, automatic sniffing and link construction of the ONU are carried out; and S.3, visualizing the network topology. Through the TELNET protocol-based instruction library, OLT and ONU equipment of different manufacturers can be supported, the limitation that a traditional PON network management system only supports equipment of a single manufacturer is broken through, and automatic sniffing and interconnection of multi-brand equipment are realized; according to the invention, the PON equipment can be automatically identified and the link relationship can be constructed, the complexity and error rate of traditional manual configuration are reduced, the automation level of equipment management is improved, and the cost and time of manual intervention are remarkably reduced.

The invention discloses a secure absolute value evaluation method for cloud computing, which belongs to the field of cloud computing data security, and designs a secure absolute value evaluation protocol SABS based on a Paillier partial homomorphic encryption algorithm variant with rapid encryption and decryption capabilities and a double-server architecture. According to the safe absolute value evaluation protocol SABS, a server S0 inputs a Paillier ciphertext # imgabs0 # for interactive communication calculation, and another server S1 outputs a Paillier ciphertext # imgabs1 # of an absolute value x * of x. The safe absolute value evaluation protocol based on the Paillier partial homomorphic encryption algorithm solves the problems that in an existing safe absolute value evaluation protocol based on the Paillier partial homomorphic encryption algorithm, efficiency is low, and communication overhead is large.

The invention discloses a six-stage pipeline CPU based on RISC-V instruction set, which can implement RV32I basic instruction set, multiplication instruction, CSR read and write instruction, and set interrupt register to suspend pipeline; the remarkable feature of CPU is that it has six-stage pipeline structure, namely IF level, FD level, CSG level, EXE level, MEM level, WB level, with higher main frequency; relevant circuits are designed to solve the risk problems in pipeline; data risk is solved by internal forward push, load_use risk is solved by suspending pipeline, and control risk is solved by static prediction. The CPU has the characteristics of small area, low power consumption and multi-function, and can be widely used in the field of Internet of Things and embedded system.

The present invention provides a text processing device and method for a bank peripheral system, which can be used in the field of distributed technology. The device includes: a text receiving module, which is used to receive text after receiving a call instruction, and filter out texts that need to be processed according to the configured text name; a text processing module, which is used to process the texts that need to be processed after receiving the processing instruction, put them into a first database, and update the processing status of the text; a text dependency checking module, which is used to check whether the processing status of all texts required by the configured program is successful after receiving the checking instruction, and if so, execute the text requirement module; the text requirement module is used to process the text in the first database and put it into the second database; the text generation module is used to generate a sending text according to the text in the second database; and the text sending module is used to configure the sending text into the text sending configuration table. The present invention has good timeliness.

The present invention discloses a method for concealed communication of unmanned aerial vehicle cooperative interference for cognitive radio network. The method comprises the following steps: taking concealed rate maximization as optimization goal, under the conditions that the probability of eavesdropper detection error satisfies the minimum detection error probability constraint, the primary user transmission rate satisfies the minimum transmission rate constraint, the trajectory of the unmanned aerial vehicle satisfies the flight speed and flight altitude constraints, and the transmission power of the unmanned aerial vehicle satisfies the maximum transmission power constraint, the transmission power of the unmanned aerial vehicle and the flight trajectory are jointly optimized to form an iterative update data stream of the transmission power scheme and the flight trajectory scheme, construct a generative adversarial migration network, train and generate the optimal transmission power and flight trajectory of the unmanned aerial vehicle according to the environmental state information and the position information of each node, and operate the action of the unmanned aerial vehicle in the communication area. The present invention makes full use of the advantages of big data, and effectively shortens the execution time of unmanned aerial vehicle cooperative interference resource optimization by migrating the source domain features with similar communication environment as the target domain.

The application discloses a workflow execution optimization method based on a random time Petri net, which comprises the following steps: S1, a service time model is constructed, total average service time of activities under different structures is calculated, and current load is updated to obtain a target function of minimum workflow service time; S2, according to the target model of minimum load balancing service time, executor capacity and actual task quantity allocated to the executor are converted into executor load to perform a traversal cycle to find an optimal candidate executor; S3, a waiting time model is constructed, and a target function of minimum workflow execution time is calculated based on the target function of minimum workflow service time; and S4, according to the target function of minimum workflow execution time, optimization of the random time Petri net execution time is performed. The application constructs a workflow execution time model based on the random time Petri net, which is used for analyzing, calculating and reducing workflow process execution time.

The invention provides an automatic regression test method and system for process step files of battery test software. The method comprises the following steps: establishing a golden sample library containing a process step file set passing historical verification and corresponding standard output time sequence data; starting to-be-tested software and loading a virtual battery simulation engine, wherein the virtual battery simulation engine is configured to simulate battery response characteristics and respond to a hardware control instruction of the to-be-tested software; obtaining a to-be-tested step file associated with the to-be-tested software, loading the to-be-tested step file in batches, driving the virtual battery simulation engine to execute a test, and collecting actual measurement output time sequence data; and comparing the actual measurement output time sequence data corresponding to the part, contained in the gold sample library, in the to-be-tested work step file with standard output time sequence data to judge a regression test result and output a report. According to the method, the automatic regression test of the battery test software working step file which runs at an ultra-real-time speed and automatically performs high-precision data comparison is realized.

The invention provides a data processing system, a storage medium storing a program, and a data processing method. The data processing system includes an Isin machine that calculates a first partition candidate based on an Isin-type evaluation function; and an information processing device configured to: obtain, from an Isin machine, partition candidate information representing a first partition candidate of an individual first partition pattern; selecting one of the first division candidates and dividing the first cluster into a second cluster and a third cluster; storing division candidate information of the first division candidate which is not selected; determining whether there is an unselected first partition candidate corresponding to a second partition pattern of a second cluster based on the stored partition candidate information; and when it is determined that there is an unselected first partition candidate, selecting one of the second partition candidates of the second cluster and dividing the second cluster into a fourth cluster and a fifth cluster.

The present invention relates to the technical field of drug delivery, and provides a management system for a mobile nursing service robot, including: a patient information management module determines the obstacle priority and speed priority of the robot in the process of performing drug delivery tasks according to the information of the target patient in the database; a local path planning model determines the corresponding obstacle weight based on the obstacle density response obstacle priority, determines the corresponding speed weight based on the obstacle density response speed priority, generates a corresponding evaluation function in response to the obstacle weight and the speed weight, and selects the best path and the best speed group for controlling the execution of the mobile nursing service robot according to the evaluation function. The adaptive weight of the present invention can match the stability and speed requirements of different emphasis in different situations of drug delivery tasks, and can plan shorter paths in areas with dense obstacles.

The invention discloses a data query method, device and equipment based on a two-fusion scene, a medium and a product. The method comprises the steps of obtaining a two-fusion data query problem text of a target user, performing text analysis on the two-fusion data query problem text, and determining query problem time dimension features; if it is determined that the two-fusion data query problem text does not meet preset data query judgment conditions of the day according to the text initiation time and query problem time dimension features of the two-fusion data query problem text, obtaining a prompt word template; according to the two-fusion data query problem text and the prompt word template, based on a pre-selected intelligent question and answer model, obtaining a target SQL query statement corresponding to the two-fusion data query problem text; and executing the target SQL query statement, performing data query on a pre-constructed and stored summary statistical table or a pre-acquired and stored transaction flow table, generating a two-fusion data query result, and feeding back the two-fusion data query result to the target user.

The application relates to the technical field of computer program optimization, and discloses a Go language program memory optimization method and system based on life period analysis, which comprises the following steps: abstract syntax trees of Go source codes are traversed, extended escape analysis is performed, and an escape graph is constructed; a life period equivalence graph is constructed based on the escape graph; context-sensitive life period analysis is performed, life period end function of each object under corresponding calling context is determined by traversing a life period path; code conversion is performed based on an allocation handle, a memory management handle is created at the entrance of the life period end function, a release primitive is inserted before a return statement of the end function, and an object is registered to a management range of a corresponding handle at an object allocation point. Through light life period analysis, the application realizes compiler-assisted explicit recovery of a heap object without high-precision pointing analysis, effectively reduces recovery pressure, and improves runtime performance of a Go program.

The utility model discloses a plasma operation electrode for treating rhinitis, and relates to the technical field of medical instruments. In order to solve the problems that solution instillation and waste suction are inconvenient and the ablation effect is poor in the existing rhinitis plasma ablation electrode, the following technical scheme is provided: the rhinitis plasma ablation electrode comprises an electrode tip, an electrode rod, a handle and a cable joint which are connected in sequence, the electrode rod comprises an inner tube and an outer tube, the tail end of the electrode tip is arranged between the inner tube and the outer tube, and the cable joint is connected with the handle. The inner tube and the outer tube extend into the handle; the tail end of the handle is connected with an instillation tube and a suction tube; an instillation hole is formed in an insulating head, close to the electrode tip, of the front end of the outer tube, and the instillation hole is communicated with the instillation tube through a gap between the inner tube and the outer tube; a suction hole is formed in the middle or the rear portion of the upper end face of the insulating head and communicated with the inner tube, and tissue generated in the operation is sucked out through the suction tube. According to the utility model, the performance of an operation tool is improved, the safety, efficiency and effect of an operation are improved, and a more effective and safer method is provided for treating rhinitis.

The invention discloses an unmanned aerial vehicle trajectory planning method and device for edge data recovery, relates to the field of navigation, and is used for improving the reliability of a data recovery task under the condition of ensuring the data recovery efficiency. The method comprises the following steps: acquiring edge node information of all target edge nodes; acquiring basic parameters and initial state information of the unmanned aerial vehicle, and further acquiring unit energy consumption of the unmanned aerial vehicle; calculating the flight energy consumption of the unmanned aerial vehicle between every two nodes, and constructing an edge node geographic information model; iterating the following steps until all the edge nodes are accessed to obtain a flight trajectory of the unmanned aerial vehicle: planning an access trajectory corresponding to the maximum number of access nodes by adopting a greedy strategy according to the geographic information model of the edge nodes and the state information of the unmanned aerial vehicle; and the unmanned aerial vehicle accesses the nodes according to the access track in sequence and updates the state information of the unmanned aerial vehicle. The data recovery reliability can be effectively improved, and the data recovery efficiency and the energy consumption efficiency of the system are ensured.

The present application relates to a workflow execution method and system based on RPA technology, and to the technical field of automatic workflow execution, wherein the method includes steps such as building a database, receiving requests, data analysis, selecting RPA robots, reinforcement learning, business execution and output. The system includes: a database building module, a request receiving module, a data analysis module, an RPA robot selection module, a reinforcement learning module, a business execution module and an output module. The present application can reasonably set the RPA workflow according to the type of user requirements, further reducing resource overhead and workflow execution time.

The invention discloses a database container redistribution method and device, electronic equipment and a storage medium. The method comprises the steps that the node resource utilization rate unhealthy degree of a database is calculated based on the CPU utilization rate, the memory utilization rate and the local disk utilization rate; calculating node flow unevenness of the database based on the network flow of each node; calculating the container flow unevenness of the database based on the flow between the calculation type container and the storage type container of each node; obtaining the path length between the calculation type container and the storage type container of each node, and calculating the container forwarding complexity of the database; calculating the disk traffic unevenness of the database based on the disk read-write traffic; and evaluating the cluster scheduling health condition of the database, and carrying out container redistribution on the database based on a health condition evaluation result. According to the invention, the technical problem of unbalanced database node load in the prior art is solved.

The present application relates to the technical field of rotorcraft, and proposes a quadrotor UAV nest protection method and system based on blade angle regulation, which comprises: performing folding angle optimization analysis on each blade of the UAV to obtain the optimal folding angle of each blade; performing deviation analysis on the actual azimuth angle information and the optimal folding angle to obtain the angle deviation amount corresponding to each blade in the UAV; dynamically correcting the preset flexible contact force control curve, and based on the correction result and the angle deviation amount, calculating the control parameter of the lever motion; decomposing the lever motion control parameter into a sub-control instruction sequence and synchronously sending it to the multi-axis motion controller of the external motor lever mechanism; based on the received take-off preparation instruction, performing blade unfolding reset control on the UAV in the folded state, and turning the blades to the target flight preparation angle, effectively improving the folding safety and unfolding precision of the quadrotor UAV.

A training method for a scheduling determination model, a method for determining index data, and a device disclosed in an embodiment of the present application, the training method includes obtaining a training data set, the training data set includes multiple pending task sets and a reference index data set corresponding to each pending task set, the reference index data set is a plurality of index data obtained by executing each pending task set based on a reference schedule, the training data set is input into the model to be trained, and a prediction index data set corresponding to each pending task set is obtained, the prediction index data in the prediction index data set corresponds to the reference index data in the reference index data set, and the model to be trained is trained according to the reference index data set and the prediction index data set to obtain a scheduling determination model. The embodiment of the present application selects appropriate scheduling according to the requirements of each pending task in the pending task set, which can reduce congestion and reduce the total execution time of the pending task set.