142results about How to "Fast execution" patented technology

The invention relates to the technical field of smart home, and discloses an AI-based fan intelligent temperature regulation control system, which comprises a multi-dimensional data acquisition module for acquiring environment temperature, humidity, air quality, illumination intensity and human body state data; the data fusion and preprocessing module is used for carrying out denoising, standardization and time synchronization on the multi-dimensional data and fusing the multi-source data; the AI decision and control module is used for generating a speed regulation and mode control instruction of the fan based on the human body comfort evaluation model and an AI algorithm; and the feedback optimization and execution module is used for executing the control instruction. Through a multi-dimensional data perception and fusion technology, comprehensive monitoring of environment temperature and humidity, air quality and a human body state is realized. The AI intelligent regulation and control algorithm is combined, the fan speed and mode are dynamically adjusted, and the user comfort and energy consumption are balanced; through edge calculation and cloud optimization, real-time response and continuous adaptive optimization of the system are ensured, and the accuracy and stability of the system are improved.

The invention provides a defense system for complex cooperative attacks in a power distribution network, and relates to the technical field of power system network security. The defense system comprises a data behavior analysis unit, an attack identification early warning unit and a system response and report unit; the data behavior analysis unit comprises a data acquisition preprocessing module, a feature extraction module, a behavior baseline establishment module, an anomaly detection module and an attack source positioning module; the data acquisition preprocessing module is in one-way connection with the feature extraction module; the feature extraction module is in one-way connection with the behavior baseline establishment module; the behavior baseline establishment module is in one-way connection with the anomaly detection module; the anomaly detection module is in one-way connection with the attack source positioning module; according to the invention, real-time data of key nodes are collected through the data acquisition and preprocessing module, and deep analysis is carried out by using the feature extraction module, the behavior baseline establishment module and the anomaly detection module, so that multiple sections of abnormal behaviors and potential threats in the power distribution system can be accurately identified.

The invention discloses a task migration method and device and a storage medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining a calculation graph corresponding to a calculation task of a source device; through a linear programming model, target equipment is allocated to each computing node in the computing graph, and the target equipment is used for executing each computing node; and optimizing the operation of each computing node according to the device resource vector of the target device and the computing demand of each computing node. According to the method, the calculation graph is reconstructed, so that the task can be efficiently executed on the target equipment after being migrated, and the execution efficiency of the task is improved.

The invention belongs to the technical field of virtual power plant instruction decomposition, and particularly relates to a virtual power plant dispatching instruction rapid decomposition method based on multiple agents. According to the method, the change and demand fluctuation of the power system can be more flexibly coped with, the compensation value is calculated based on the historical data and the current state of the intelligent agent, reasonable distribution and optimal use of system resources, loads and power are ensured, the overall operation efficiency of the virtual power plant is improved, and through the setting of the instruction decomposition level, the operation efficiency is improved. Task allocation of the intelligent agents can be dynamically adjusted according to actual conditions, overload of a single intelligent agent is avoided, execution efficiency of scheduling instructions is improved, high-energy-consumption tasks can be preferentially arranged when power is low by combining current power data, or generating capacity and operation cost are reduced when the power is high, economic benefits are improved, and the method is suitable for large-scale popularization and application. Compensation value calculation and decision making are carried out by utilizing historical data of the intelligent agent, so that the scientificity and accuracy of dispatching instruction decomposition are improved, and the influence of uncertain factors in the dispatching process is reduced.

The invention discloses a method for automatically testing an interface based on RPA. The method comprises the following steps: making a test plan; building a test framework; compiling a test script; performing integrated testing; executing the test script; analyzing a test result; and maintaining the test script. Based on an RPA tool, through a graphical interface and predefined operation, a tester can create an automatic test script without writing any code, and the tester can define a complex test process only through simple dragging, clicking and configuration; an RPA tool is generally designed to be visual and easy to use, even a tester without any programming experience can quickly master the RPA tool, and the tester can master the basic skill of automatic testing through simple training and practice; the RPA has a unique verification mode for the login system needing to be verified, targeted system verification can be carried out, and the login interface can obtain the token conveniently.

The invention discloses a dance formation self-organization control method based on a robot group. The method comprises the following steps: S1, obtaining dynamic changes of light frequency, color and intensity through a spectrum camera; s2, judging an effective light source and an invalid light source, and removing the invalid light source to form a target light signal; s3, converting the optical signal into a digital signal through a photoelectric converter and a digital signal processor, and extracting the characteristics of the digital signal to form a characteristic instruction; s4, comparing the feature instruction with a predefined action matching database in real time, and outputting a robot action instruction; s5, analyzing the characteristics of the received digital signal, predicting an action instruction at the next moment, and generating the next action instruction in advance; s6, generating a robot action track by using a path planning algorithm; and S7, adopting a distributed control strategy, dynamically adjusting the motion track, and completing dance arrangement. According to the invention, dance arrangement of the robot group is controlled through light, and diversity of dance of the robot group is realized.

According to the temperature compensation method and system of the pressure sensor, the temperature compensation precision of the sensor can be improved by combining a hardware and neural network composite method, and the measurement accuracy is improved; and the neural network can process a complex non-linear relationship, so that the temperature compensation characteristic of the sensor can be modeled more accurately. In addition, the neural network is deployed on the FPGA, and due to the parallel computing advantage of the FPGA, the execution speed of the algorithm can be increased; a feedback mechanism is adopted to take sensor output as new training data for adjusting parameters of the neural network model, and the performance of the neural network model can be further optimized to adapt to a new working environment of the sensor.

The invention discloses a knowledge-driven and data-driven magnaporthe oryzae AVR (Automatic Voltage Regulation) gene RNA (Ribonucleic Acid) secondary structure generator, which is characterized in that an on-chip memory of an ARM (Advanced RISC Machines) chip and an external DRAM (Dynamic Random Access Memory) chip are adopted for respectively storing RNA original data and intermediate results; an FPGA chip is adopted to realize mapping from an RNA sequence to a knowledge graph, and features such as base pairing are fused through LUT; a multi-core AI chip is adopted, an encoder-decoder network is executed in parallel, and knowledge and data are fused to generate a secondary structure; and the VAE-GAN network is executed in a streamlined manner through an AI chip, the quality of the generated structure is evaluated and iteratively optimized, and an accurate RNA secondary structure is generated. The invention further discloses a knowledge-driven and data-driven fused magnaporthe oryzae AVR gene RNA secondary structure prediction method, RNA physicochemical characteristics are utilized, deep learning, transfer learning and knowledge distillation technologies are combined, and the prediction accuracy and operation efficiency are improved.

The invention discloses a method, a system, equipment and a medium for analyzing biological characteristic correlation in biomics data, and belongs to the technical field of bioinformatics. In particular to a method, a system, equipment and a medium for analyzing correlation of biomics data. According to the method, the system, the equipment and the medium, a high-performance and parallel block matrix algorithm is used for processing large-scale correlation and clustering tasks, excellent performance is shown in the aspect of calculating a correlation matrix, and downstream analysis can exceed computer memory resources; according to the method, the approximate P value can be quickly and effectively estimated without repeated complex cumulative distribution function calculation, and the corresponding approximate correction P value can be quickly and effectively estimated based on the P value sampling subset without being based on all the P values; and a top-k algorithm is realized, and faster execution and lower memory consumption are realized by utilizing a partial sorting method based on heaps.

The embodiment of the invention provides a simulation method and device for chip design and related equipment, and the method comprises the steps: obtaining the design data of each partition in the chip design; for each partition, determining a corresponding data extraction strategy based on the type of the design data; extracting the design data of the corresponding type by using the data extraction strategy to obtain extracted data; the data extraction of each type of design data is performed in parallel; merging the extracted data corresponding to each type of design data to form chip power consumption model data of each partition; and performing simulation of chip design by using the chip power consumption model data of each partition. According to the technical scheme provided by the embodiment of the invention, the extraction efficiency of the chip power consumption model data can be optimized, and the simulation efficiency of chip design is improved.

The invention discloses a decentralized application-oriented smart contract program generation method, device and equipment and a storage medium, and belongs to the field of block chain smart contracts, and the method comprises the steps of persisting an executable code and state data of a fragmented smart contract in block data; in response to a calling instruction for the fragmented smart contract, extracting the executable code and the state data persisted in the block data to execute the fragmented smart contract, and updating the state data persisted in the block data according to execution of the fragmented smart contract; and in response to a reconstruction instruction for the fragment smart contract in execution, extracting persistent executable codes and state data from the block data, and reconstructing the fragment smart contract in execution through the extracted executable codes and state data. The problems of complex cross-fragment calling, low execution speed and difficult fault recovery of the smart contract are solved, and the performance and stability of the block chain system in decentralized application processing are improved.

The invention discloses a Rydberg atom low-frequency voltage measurement signal processing system, and the system comprises an ADC data collection module which is used for converting EIT spectrum data into an electric signal and carrying out the data collection; the wavelet transform denoising module is used for carrying out denoising processing on the data acquired by the ADC data acquisition module; the automatic peak searching module is used for performing automatic peak searching on the de-noised data to obtain a peak position difference; and the voltage inversion module is used for performing voltage inversion and frequency calculation according to the peak position difference and completing Rydberg atom low-frequency voltage measurement. Wherein the ADC data acquisition module and the wavelet transform denoising module are realized by a PL end; and the automatic peak searching module and the voltage inversion module are realized by a PS end. The system is simple in structure and good in stability and real-time performance, meets the requirements of miniaturization and low power consumption, and lays a foundation for engineering application of a Rydberg atom low-frequency voltage measurement system.

The invention provides a distributed computing system based on pre-scheduling resource collaborative adaptation, and relates to the technical field of resource collaborative allocation systems. The distributed computing system based on pre-scheduling resource collaborative adaptation aims at solving the problems that in the prior art, resource scheduling is not flexible, and application configuration and resource scheduling are lack of coordination. By introducing a dynamic scheduling mechanism of the resources, organic combination of resource pre-scheduling and flexible allocation is realized. Meanwhile, through cooperation of application configuration and resource scheduling, optimal distribution and execution of calculation tasks are achieved, the system is composed of a server side and a client side, the client side has pre-scheduling resources and is used for feeding back the resource state in real time and receiving and executing the calculation tasks, and the server side is responsible for monitoring and scheduling of global resources and task distribution. And through a designed heuristic collaborative adaptation algorithm, the server can dynamically schedule resources in the pre-scheduling resources, and high efficiency and stability of task execution are ensured.

The invention discloses an Android malicious application detection method based on a multi-view deep neural network, and relates to the technical field of information. The invention provides an Android malicious application detection method based on a multi-view deep neural network in view of the technical problems of numerous attack means, complex and changeable semantics, difficulty in ensuring the coverage rate of attack behaviors by executing detection only from a single view and the like of the current Android malicious application. According to the method, multi-view static feature information is organically fused, the synergistic effect of static features under all views is fully exerted, a target object is comprehensively described, limitation and fuzziness caused by application analysis from a single view are avoided, and finally accurate detection of malicious applications is achieved.

The invention relates to the technical field of flood control dispatching, and discloses a reservoir flood control water level dynamic control and flood recycling method and system, and the method comprises the steps: obtaining a surface rainfall forecast value of a reservoir basin based on real-time rainwater condition data and numerical weather forecast; a hydrodynamics and hydrology coupled drainage basin runoff model is driven, and an in-reservoir flood hydrograph in a predicted period is generated; judging the flood scale and grade based on the hydrograph, and when the flood is medium and small flood, calculating the dynamic flood control storage capacity of a downstream flood control object by adopting an equivalent flood control effect algorithm taking into account the pre-discharge scheduling capability; according to the dynamic flood control storage capacity, a dynamic flood control water level control value is obtained through backstepping of a water level-storage capacity relation curve of the reservoir; and finally, generating and executing a reservoir dispatching instruction based on the control value, and storing the water level of the reservoir to not exceed the dynamic value. The problems that a fixed flood control water level method is low in water resource utilization rate and inflexible in dispatching are solved, and flood resource efficient utilization on the premise of flood control safety is achieved.

The invention relates to the field of computer information communication, in particular to an automatic process service system and method based on resource application, and the method comprises the following specific steps: a user selects an applied resource type through a selection field in a form, and determines which module enters next according to the selected resource type; each resource application process module has an independent dynamic form, form fields can be automatically adjusted according to different resource types, forms meeting resource application requirements are dynamically generated through a configuration rule engine and a system, and form data are processed and verified; the system controls an access module according to the role authority of the user; in a process execution process, a resource application form submitted by a user passes preliminary auditing, and a system can automatically select an approval module needing to be transferred according to form content.

The invention relates to a self-adaptive loop optimization method, a reconfigurable processor and a device, and the method comprises the steps: carrying out the classification processing of a to-be-optimized initial loop code, obtaining a classification result representing the characteristics of a loop structure in the initial loop code, determining a target optimization strategy from a plurality of pre-established candidate optimization strategies according to the classification result, and carrying out the optimization of the target optimization strategy. And performing optimization processing on the initial loop code by adopting a target optimization strategy to obtain a target loop code. The loop optimization code is automatically generated, manual writing is not needed, the optimization efficiency is improved, the performance of the reconfigurable processor can be improved for the loop-intensive application program through loop optimization, the optimized loop structure can more effectively utilize computing resources and memory bandwidth of the processor, and the performance of the reconfigurable processor is improved. And the execution speed of circulation is accelerated, so that the performance of the whole application program is improved.

The invention discloses a master station type cross-station one-key sequential control method and system based on a centralized control system, and relates to the technical field of power system automation and control, and the method comprises the steps: collecting power grid operation data and equipment state information in real time through various sensors of the centralized control system, carrying out the multi-modal data fusion, and carrying out the multi-modal data fusion through the fused data, the operation process is monitored in real time, and possible errors or abnormal conditions are detected; analyzing the collected data, constructing a prediction model, and intelligently generating an optimal operation strategy and an execution sequence according to a real-time power grid state and an operation history; operation and maintenance personnel start sequential control operation through one key, and the system automatically executes corresponding operation steps according to the operation order. Through the one-key starting function, operation and maintenance personnel can quickly select and execute the pre-generated operation order, and a tedious manual process in traditional operation is avoided. The control instruction automatically generated by the system is analyzed according to the operation order, so that the execution of the operation steps is quicker and more accurate.

The invention discloses a task scheduling method and device based on reinforcement learning, a medium and a product, and relates to the technical field of computers, and the method comprises the steps: determining a task scheduling action of a current time step according to a current action empirical value table and a preset scheduling constraint condition; updating the current system environment information and the current task load information of the embedded operating system based on the current reward information after the embedded operating system executes the task scheduling action; and based on the current system environment information, the current task load information and the current reward information, updating an empirical value in the current action empirical value table, and skipping to the step of determining the task scheduling action of the current time step according to the current action empirical value table and a preset scheduling constraint condition, and executing the task until the target task is scheduled to the target processor core meeting the preset condition. Tasks can be accurately allocated to appropriate hardware resources, and idle or overuse of the resources is avoided.

The present invention discloses a method for implementing timeout retry execution based on Rocket MQ, comprising the following steps: Step S1: when the application is started, the task triggering methods of all asynchronous tasks that need timeout retry are bound to a corresponding task triggering strategy, and are saved in the application cache; Step S2: the parameters of the task triggering method, the task triggering strategy, the time of the timeout retry, and the maximum number of retries are assembled into a task message, and sent to Rocket MQ; and the delay time of the task message is set; Step S3: according to the delay time, Rocket MQ pushes the task message to the application, and the application obtains the corresponding task triggering method saved in the application cache according to the task triggering strategy, matches the parameters of the task triggering method according to the task triggering method, and completes the timeout retry. The present invention has high query efficiency, fast execution speed, less CPU resource occupation, and versatility.

The invention discloses a test and evaluation method for live-action modeling of a nerve radiation field, and the method comprises the following steps: S10, carrying out data set preparation: collecting a public data set, carrying out the live-action shooting of a forward data set and a reverse data set with a designed place, carrying out the targeted enhancement of a data set, and generating a data set through employing AIGC; the data set is used for training a modeling model or a test model of the system; s20, based on the situation that a user may use different functions of applications in parallel in an actual user scene, policy task issuing is carried out in an interface calling mode; s30, carrying out system equipment performance monitoring and modeling duration recording, analyzing state data and a trend thereof, analyzing whether a task is abnormal or not and whether performance consumption and task duration are reasonable or not, and carrying out targeted optimization based on a target; and S40, after task operation is completed and operation data is recorded, the modeling success rate and the modeling effect are evaluated.

The invention belongs to the field of data storage, and particularly relates to an integrated circuit big data storage optimization system which comprises a data control module, a storage unit module, a data caching module, an error detection and correction module, a data compression module, an address mapping module and a power management module. And the storage unit module is used for controlling and managing the read-write operation of the data, and is used for determining the structural design of the storage unit and monitoring the state of the storage unit. According to the integrated circuit big data storage optimization system, the storage capacity is greatly improved by adopting a novel nonvolatile memory technology and an optimized storage unit structure and material, and meanwhile, the read-write speed of data is remarkably improved by adopting an intelligent cache replacement strategy, a multi-level cache structure, a cache prefetching technology and the like, so that the storage efficiency of the integrated circuit big data is improved. In this way, in a big data storage scene, a large amount of data can be quickly stored and read, and the high requirement of the modern information technology for data processing is met.

The invention provides a quantum compiling method, a quantum compiling device, electronic equipment and a non-instantaneous computer readable storage medium, and the quantum compiling method comprises the steps: determining a compiling workflow of a quantum circuit in response to a compiling instruction of the quantum circuit; compiling the quantum circuit according to the compiling workflow to obtain a compiled quantum circuit; and updating and replacing the variable parameters in the compiling quantum circuit. According to the embodiment of the invention, the variable parameters in the compiling quantum circuit can be directly updated and replaced, and the whole quantum circuit does not need to be recompiled, so that the compiling overhead is saved, and the execution speed of a quantum algorithm is improved.

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.

The invention discloses an interactive system of an intelligent network detection terminal based on the Internet of Things, which comprises an Internet of Things detection terminal module, a data processing module, an interactive interface module, a control management module and a remote access module, and relates to the technical field of the Internet of Things. Through organic combination of the Internet of Things detection terminal module, the data processing module, the interactive interface module, the control management module and the remote access module, integrated support of network operation state monitoring, data processing and analysis, visual interaction, resource optimization configuration and remote management is realized, and all the modules work cooperatively. Compared with the prior art, resource consumption and management complexity caused by multi-tool switching in a traditional system are reduced, the network management efficiency is remarkably improved, data transmission delay is remarkably reduced by adopting the application of the edge computing technology, and real-time monitoring and abnormal quick response of the network state are achieved.

The utility model discloses an FPC antenna tail angle shaping mechanism, comprising a negative pressure adsorption block and a telescoping mechanism installed on the negative pressure adsorption block, the telescoping mechanism is provided with a guide block moving along a first direction, the guide block is provided with a shaping positioning block moving along a second direction through a sliding assembly, and the shaping positioning block is provided with a positioning block. The first direction is perpendicular to the second direction; a first shaping surface is arranged on the negative pressure adsorption block, and a second shaping surface matched with the first shaping surface is arranged on the shaping positioning block; the device further comprises a first limiting mechanism and a second limiting mechanism, the first limiting mechanism is used for limiting the moving distance of the guide block relative to the negative pressure adsorption block, and the second limiting mechanism is used for limiting the moving distance of the shaping positioning block relative to the guide block. The positioning condition that the antenna is shaped and attached to the interior of the mobile phone shell is solved, and the antenna attaching efficiency is improved.

The invention discloses a high-speed flexible removing mechanism for cigarette cartons in a lifting conveying channel. The high-speed flexible removing mechanism comprises a mounting bracket, a rotatable driving assembly, a synchronous belt wheel set, a fixed bracket, a locking assembly, a cigarette pressing plate, a cigarette pushing assembly and a protection assembly, the installation support is installed on one side of an elevator channel through bolts, the installation support and the rotatable driving assembly are fixedly installed, and the synchronous belt wheel set is installed on the rotatable driving assembly and driven by the rotatable driving assembly to rotate. The driven wheel drives the main synchronous belt wheel through the rotatable driving assembly, continuous movement is achieved through the synchronous belt, the cigarette pushing plates are fixed to the accessory pushing plate of the synchronous belt to be used in pairs, the guiding effect on running cigarette cartons is achieved, the cigarette cartons are prevented from inclining at a removing opening of the elevator, cigarette clamping is avoided, and the quality of the cigarette cartons is improved. And the cigarette pushing plate on the synchronous belt circularly moves along with the synchronous belt, so that the risk that the cigarette pushing plate collides with the cigarette supporting block on the lifting conveying channel in a reciprocating motion mode is avoided.

The stringing and expanding device for manufacturing the rope belt and the braid comprises a working table, a plurality of first air cylinders are horizontally arranged on the upper surface of the working table, the first air cylinders form an annular shape in a circumferential arrangement mode, and output shafts of the first air cylinders can stretch or retract in the axial direction of the circumference. A push plate is connected to an output shaft of the first air cylinder, driven arms are horizontally and fixedly arranged on the surface of the side, back on to the first air cylinder, of the push plate, the ends of the multiple driven arms all extend towards the circle center, and the top ends of the driven arms bend and extend upwards and are arranged in parallel. According to the technical scheme, the first air cylinders are horizontally arranged, so that the driven arms are far away from one another in the horizontal direction, the locking ring can be hooked through the L-shaped driven arms, the locking ring is expanded in the process that the driven arms are far away from one another, a rope belt body is conveniently inserted into the locking ring, and stringing of a rope belt braid is facilitated.

The specification provides a transaction execution method, a node and a blockchain system. The method is applied to a first node in a blockchain system, the first node comprising a control process and a plurality of computing processes, and the method comprises: the control process acquiring a first transaction to be executed in a first block; the control process, in a case where it is determined that there is a second block in an execution stage, sending the first transaction to a first computing process in the plurality of computing processes in response to the first transaction not depending on a second transaction in the second block; and the first computing process executing the received first transaction.

The invention discloses an HTML (Hypertext Markup Language) code rendering method and device of a Web page and a computer program product.The method comprises the following steps: firstly, acquiring a Vue component of a target Web page, and then compiling the Vue component into an HTML file, a CSS (Cascading Style Sheet) file and a JavaScript file; then, a preset code is injected into the HTML file to generate a DSL code; then, a CSS file and a JavaScript file can be used for converting the DSL code into a GoTemplate file, and then, the DSL code is converted into the GoTemplate file; secondly, compiling the dynamic object into a binary file, and obtaining real-time data of the dynamic object in the binary file; finally, then HTML rendered text may be generated based on the real-time data and the binary file; therefore, rendering of a traditional Node.js server side is converted into server side rendering of the Go language, so that a Go program is directly operated in a binary file after being compiled; on the basis of the method, the execution speed of code rendering can be increased without additionally deploying a running environment and carrying out code interpretation, so that the loading response speed of the Web page is increased.