1329 results about "Response time" patented technology

The invention discloses an electromagnetic environment simulation method and system of a display module, a medium and a product, and relates to the field of electromagnetic variable measurement, and the method comprises the steps: receiving a test identification code inputted by a user, extracting a plurality of target scenes corresponding to the test identification code from a preset scene library, and generating a scene change sequence; determining a radio frequency interference source combination and a mechanical vibration parameter corresponding to the target scene; setting test parameters of the test time periods corresponding to the multiple target scenes, and generating a dynamic test sequence; receiving a key test scene marked by a user, and adjusting a test time period and test parameters corresponding to the key test scene to obtain a target test sequence; simulating an electromagnetic environment of the target display module, and recording simulation test parameters of the target display module; the simulation test parameters comprise display brightness, contrast and response time; and determining an electromagnetic compatibility evaluation result based on the target test sequence and the simulation test parameters. According to the invention, the accuracy of an electromagnetic compatibility test result can be improved.

The invention discloses a fusion question and answer method, device and equipment of a hybrid expert large language model and a medium, and relates to the technical field of artificial intelligence, and the method comprises the steps: inputting a question input by a user into a pre-trained routing model, obtaining k target expert models which are selected from the N expert models by the routing model and are used for answering the questions input by the user; and answering the question input by the user through the k target expert models, fusing expert answers output by the target expert models, and outputting the fused expert answers. The answers of the k target expert models are screened through the routing model and are fused and output, and the output of the model focuses on the results of the k expert models with relatively high task correlation, so that the resource consumption is reduced, the response time is shortened, and the question and answer fusion efficiency is improved. In addition, expert model outputs from different task fields are fused, so that the generalization ability of the model is enhanced, and the reliability of fused questions and answers is improved.

The invention relates to the technical field of cooperative control, in particular to a multi-machine cooperative control method and system for a bridge cable hoisting device, and the method comprises the following steps: collecting tension change characteristics through a distributed sensor array, extracting indexes through a sliding window algorithm to generate a response time window, and generating a cooperative time window through time sequence overlapping and speed trend adjustment. Calculating a compensation value by combining inertial parameters and acceleration to generate a trigger window, detecting tension and displacement difference, inputting the tension and displacement difference into a dynamic threshold function for screening and fusion, outputting a synchronous trigger condition, and generating a synchronous control instruction by encoding a device number and a tension change rate after timestamp alignment. According to the method, multi-node tension synchronous acquisition and normalization processing, dynamic response generation through a sliding window, boundary matching action triggering adjustment through an overlapping algorithm, response lag correction through inertia compensation, tension and displacement difference real-time detection, dynamic threshold screening and triggering condition fusion and timestamp alignment packaging instruction consistency are carried out; and the cooperation precision and the system robustness are improved.

The invention relates to the technical field of data storage, can be applied to business scenes such as medical health and financial science and technology, and discloses a multi-Pool storage resource adaptive writing method which comprises the following steps: monitoring available storage space, read-write input / output rate, average response time and data access frequency of each Pool; dynamically adjusting the current write-in weight of the Pool according to the monitoring result; converting the current write-in weights of all Pool into probability values, and constructing a discrete probability distribution table; selecting a target Pool through a pseudo-random number generator according to the probability distribution table; and writing the to-be-stored data into the target Pool. According to the method, the running state of each Pool is continuously monitored, and the writing weight is adjusted in real time, so that the problem of resource allocation rigidity under a fixed weight strategy is avoided; in combination with a discrete probability distribution table constructed based on normalized weight and a pseudo-random selection mechanism, selection of the target Pool has certain load balancing elasticity, and data can be more effectively guided to be written into the Pool with light load and excellent performance.

The invention discloses a rendering method and system for generating a monitoring event queue of an air conditioner host. The method comprises the steps of obtaining operation data and monitoring data of air conditioner equipment, constructing an equipment connection diagram, extracting spatio-temporal characteristic data and constructing a comprehensive data model. Constructing a multi-level event processing queue, and generating an event scheduling strategy scheme; constructing a dependency graph of the rendering process, and generating a resource allocation scheme; constructing a rendering strategy scheme in combination with pre-stored historical rendering data, and generating a time series data set; generating a version chain table in combination with the historical data version information; performing data consistency check, and outputting a synchronous rendering data set; executing the rendering task sequence to obtain a rendering result; meanwhile, the execution state of the rendering process is monitored, and a rendering execution report and a rendering state report are generated. According to the method, the average response time of the system is prolonged, the accuracy of data processing is guaranteed, the stability of the system is improved, and powerful technical support is provided for stable operation of the air conditioner host monitoring system.

The invention provides a front-end performance optimization method based on cache management, and the method comprises the steps: S1, collecting and processing user behavior data, and obtaining target data; s2, analyzing a user behavior based on the target data, constructing a user behavior model, and predicting an access demand of a user by using a prediction algorithm to obtain a prediction model; s3, generating a caching strategy based on the user behavior model and the prediction model; and S4, storing resources on the client, the server and the content distribution network node based on the caching strategy. The cache hit rate is improved; the caching strategy is dynamically adjusted according to the actual use condition of the user, and the user requirement is more accurately met; the cache preloading mechanism can shorten the response time of the user request, can adapt to different user behaviors, and improves the user experience. The system and the electronic equipment provided by the invention have corresponding advantages.

An impact apparatus and a computing system provide real-time feedback about a particular activity performed using the impact apparatus. In one general aspect, a method includes providing a user interface that displays a plurality of impact zones, the plurality of impact zones corresponding to a plurality of impact zones on an impact apparatus configured to generate voltage in response to an impact. Implementations can include determining a hit impact location and a velocity of an object for an impact event and updating the user interface with the hit location and velocity. Implementations can include determining a response time for an impact event. Implementations can include determining a location and magnitude of an impact event. Some implementations may include determining whether a location is a target location. Implementations can score an impact according to its magnitude, location, and / or response time.

The invention discloses a diagnostic method for performance detection of a pressure sensor, and relates to the technical field of sensor equipment. Comprising the following steps: initializing a pressure sensor, sensitivity and response time under different pressures, dynamic response characteristics in a rapidly changing pressure environment, changes under different temperature conditions, anti-interference capability to external factors, long-time stability, and existence of non-linear errors and zero drift; and the overall performance of the pressure sensor is comprehensively evaluated. According to the diagnosis method, the dynamic response, the anti-interference capability, the temperature adaptability and the long-term stability of the sensor can be comprehensively quantified by setting the dynamic response characteristic model and multi-working-condition environment simulation. According to the method, neglected nonlinear dynamic behaviors in a traditional evaluation means can be captured, the potential performance problem of the sensor in a complex working environment can be effectively revealed, optimization design and application deployment are guided, and the reliability and precision of the sensor in an actual scene are remarkably improved.

The invention relates to the technical field of state monitoring, in particular to an inner package production data real-time monitoring and processing system which comprises a running state acquisition module, a performance deviation evaluation module, an abnormal behavior recognition module, a task scheduling optimization module and a load balancing optimization module. According to the invention, through a cooperative acquisition mode of operation data such as temperature fluctuation, pressure change and flow velocity stability, real-time perception of dynamic collection and high-frequency change of the operation state is realized, and by means of a cross discrimination strategy of distribution uniformity and response time, non-representative data segments are eliminated, and the accuracy of performance abnormity identification is improved. Through time coupling analysis of gradient tracks and offset, abnormal behavior fragments are locked in advance, forward recognition of trend instability is achieved, intervention windows are dynamically screened, actual effect and synchronization of response are ensured, a real-time matching mechanism based on loads and demands is adopted, task priority and processing channel distribution are optimized, and intervention efficiency and scheduling adaptability are improved.

The invention relates to the technical field of artificial intelligence, in particular to a scene application operation maintenance platform based on an artificial intelligence model, which comprises a reasoning state sensing module, a load balancing scheduling module, an intelligent resource allocation module, a deployment configuration adjustment module and a scene feedback integration module. According to the method, by sensing and reasoning process resource consumption and response time migration trend, abnormal tasks caused by resource fluctuation can be accurately recognized, the state monitoring sensitivity is improved, task allocation records are analyzed to construct conflict structures, the resource conflict recognition and visualization capability is enhanced, the model operation level and the GPU vacancy rate are combined, a task migration path is optimized, and the task migration efficiency is improved. Node resource balance is realized, storage frequency, memory margin and network delay are fused during deployment, migration stability is guaranteed, drift tasks are identified through response logs and call records, an operation and maintenance list is generated, operation and maintenance accuracy and multi-scene matching capability are improved, and reasoning task stability and resource scheduling intelligent level are enhanced.

The invention provides a computing power unified access management method based on an API technology, and the method comprises the steps: monitoring the request amount and response time of each interface in real time in a current-limiting fusing assembly of an AP I gateway, carrying out the current-limiting and fusing operation when the request amount exceeds a current-limiting threshold value, and queuing requests exceeding the threshold value again; a token generation rate and a leakage rate of a leaky bucket are dynamically adjusted according to real-time flow change of an interface by applying a self-adaptive flow limiting method, fine control and smooth processing are performed on flow, and impact of burst flow on a system is avoided; the flow, response time and error rate of each interface are monitored in real time, different AP I gateway interfaces are integrated, a flow-limiting fusing model is established, a random forest method is applied, historical data are trained and learned by the model, and a flow-limiting threshold value and a fusing rule are autonomously optimized.

Systems, apparatus, articles of manufacture, and methods are disclosed to test an automated query language by interfacing with a query endpoint, generating a first test suite based on a plurality of combinations of a plurality of attributes corresponding to an API specification, transmitting the first test suite to be executed on the query endpoint, the first test suite to include instructions to cause the query endpoint to access data stored in a database accessible to a plurality of secondary endpoints, obtaining a response time corresponding to the access of the data, comparing the response time corresponding to the access of the data with a service level agreement required response time, and in response to the response time corresponding to the access of the data being longer than the service level agreement required response time, notifying a developer of the plurality of secondary endpoints.

The invention relates to the technical field of computers, discloses an intelligent scheduling method and system for server cluster load balancing, and aims to solve the defects of the existing server cluster load balancing technology in response lag, non-uniform resource utilization rate, service quality guarantee, global optimization capability, fine-grained state perception and scheduling decision. The method comprises the following steps: collecting server state and request feature data, constructing a cluster state and service capability model, and predicting a load trend; and generating an optimal routing strategy by using deep reinforcement learning and multi-objective optimization, and issuing adjustment request distribution. The system comprises a data acquisition module, an application request feature acquisition module, a state sensing and modeling module, a load prediction module, an intelligent scheduling decision module and an instruction execution module. By adopting the technical scheme, the resource utilization rate can be improved, the response time can be reduced, the throughput can be improved, the system stability and elasticity can be enhanced, and the operation cost and energy consumption can be reduced.

The embodiment of the invention provides a voice conversation method and system, electronic equipment, a storage medium and a program product. One method is implemented as follows: a voice dialogue stream (which can be an inquiry voice stream input by a user for a target commodity) of a user is subjected to streaming response, a plurality of dialogue text segments are generated in a segmented manner in the streaming response process, and the dialogue text segments are output in real time after being generated and stored in a first cache queue; and when it is detected that the reply text fragment is stored in the first cache queue, the stored reply text fragment is converted into a reply voice fragment in real time and played. The streaming response may be performed by an agent. Visibly, according to the response of the voice dialogue stream of the user, the dialogue is played while being generated, the waiting time from text to voice synthesis can be greatly shortened, and therefore the response time can be shortened.

The invention relates to the technical field of protection device testing, in particular to a verification method of an intelligent comprehensive protection device, which comprises the following steps of: extracting starting time and response time in a tripping state transition sequence of the protection device, calculating execution delay and action segment length, and comparing and identifying an abnormal link based on a state number sequence; the method comprises the following steps: realizing analysis and standard reconstruction of a state logic structure, forming an ordered tripping path, introducing a long short-term memory neural network to carry out time alignment on a state change sequence and a current signal segment, identifying a potential mismatch or abnormal change trend in a state chain through linkage analysis of a state-current abrupt change position, and reconstructing a state path. According to the method, path continuity and dynamic adaptability are enhanced, a random forest is adopted to take device numbers, the number of jump segments and response residual errors as multiple inputs for training modeling, device scores are output through an integrated tree voting mechanism, and recognition sorting of abnormal frequency significant devices is achieved.

The invention discloses a dynamic path optimization method based on response time domain attenuation, and relates to the technical field of artificial intelligence and intelligent path planning, and the method comprises the steps: generating a node network composed of navigation points, terrain units or interaction regions, and forming a node network topology structure; generating a dynamic state feature set used for describing game scene changes, and forming input data used for follow-up node priority dynamic adjustment; converting the dynamic state feature set into node-level standardized event data, and distributing the node-level standardized event data to a node state management module through an event bus; setting a current node priority for each node in a node state management module based on the node-level standardized event data; forming a time domain attenuation model of the node priority; the priority recovery coefficient is improved; in the path planning stage, executing a dynamic path search algorithm to generate a passing path with the minimum total cost and the optimal path smoothness; when it is detected that player operation or scene change causes node response mutation, a local re-planning mechanism is triggered, smooth path transition is achieved, and overall jumping is avoided. According to the method, the problems of path congestion, frequent switching and unsmoothness caused by lack of dynamic node state and event response calculation in the prior art are solved. Through node priority time domain attenuation and dynamic path optimization, the technical effects of smooth path, efficient passing and node load balancing are achieved.

The invention relates to the technical field of online learning, in particular to an interaction-based mobile English learning system, which comprises a grammar error interaction recognition module, an error item pushing frequency regulation and control module, a learning load dynamic monitoring module, a learning difficulty dynamic adjustment module and an English skill interaction aggregation module. According to the method, the error event density change in the English learning interaction information of the user is dynamically monitored, the error event time sequence is established by using the error labeling field, the error type classification and the timestamp, and the learning content pushing frequency adjustment object is accurately determined according to the error density change amplitude, so that efficient error item accurate intensified training is realized; meanwhile, according to the synchronous change amplitude of the task response time increase rate and the answer accuracy change rate, the change condition of the learning load of the user is recognized in real time, the difficulty level of the learning content is dynamically and automatically adapted, dynamic regulation and control between the learning difficulty and the learning state of the user are formed, and the learning acceptability and effect of the user are improved.

The present invention relates to a hardware acceleration method, device, equipment and medium. The method comprises: obtaining a read-write command issued by a host; parsing the read-write command to obtain a parsing command; judging whether the parsing command is a read command; if it is a read command, judging whether the parsing command is a sequential read command; if it is a sequential read command, applying for a buffer from a read cache management engine, and constructing a pre-read command, carrying a buffer address and an LBA address; according to the pre-read command, caching data in a read cache buffer; submitting the parsing command to the read cache management engine for processing; judging whether the parsing command hits the cache data of the current read cache buffer; if it hits, directly returning the corresponding data from the read cache buffer to the host, and marking the command completion. The present invention improves the pertinence and efficiency of processing, shortens the response time of commands and the transmission delay of data, and improves the overall performance of the system.

The invention discloses a multi-queue scheduling method based on total and incremental reasoning overhead merging, which comprises the following steps of: firstly, calculating the total resource demand and memory overhead of a task according to the input length and the size of a predictor model in the process of performing total reasoning on a reasoning task; distributing tasks to queues with different priorities according to the total resource demand in combination with response time requirements and task importance; dynamically scheduling tasks according to a priority queue sequence, adjusting an execution sequence in combination with a system load, and preferentially executing tasks in a high-priority queue; distributing a time slice for each task, monitoring task execution time, reducing the priority of overtime tasks, moving the overtime tasks into a secondary priority queue, and triggering new task scheduling; and after preemptive scheduling, the key value cache of the latest scheduling task in the waiting queue is swapped from the accelerator memory to the CPU memory, and is swapped back to the accelerator memory before the task is re-executed.

Latency, response times, and efficiency improvements for data querying are provided herein, particularly in the context of querying large database systems and data tables from disparate data sources. There are provided systems and methods for automatic query and data retrieval optimization through procedural generation of data tables from query patterns. A service provider may utilize different computing services for query processing and data retrieval for different applications and services used by internal and / or external users. Instead of querying large database systems and numerous data tables, pre-aggregated data tables may instead be used and searched by procedurally generating such tables based on precomputation rules and query patterns. Once patterns have been identified in queries, corresponding data may be aggregated from data sources in a pre-aggregated data table. Query optimization rules may then be used to have these data tables queried in place of their original sources.

The invention provides an elastic configuration and bidirectional collaborative adaptation system for application computing tasks, and relates to the technical field of computers. Equipment and network states are monitored in real time by applying an elastic configuration mechanism of a computing task, execution tasks and nodes in a task graph are dynamically adjusted, task response time is optimized, meanwhile, collaborative optimization is performed between an equipment end and a cloud end by applying a bidirectional collaborative adaptation algorithm of computing network resources, computing resources are reasonably distributed, and the computing efficiency is improved. The limitation of single optimization dimension in the prior art is overcome, in addition, the system adopts a self-adaptive learning mechanism, a task unloading strategy and a resource management scheme are continuously optimized by utilizing machine learning and a neural network model, the long-term performance is improved, and the technical scheme not only improves the dynamic response capability of the system, but also improves the reliability of the system. In addition, global optimization of resources is realized in a multi-user and multi-task environment, and task execution time and energy consumption are reduced.

The present disclosure relates to the technical field of Graphics Processing Units (GPUs), and in particular to a GPU scheduling method and apparatus, and a storage medium. The method comprises: acquiring a migration command, the migration command being used for migrating a workload of a source Virtual Machine (VM) from a source GPU core to a target GPU core; on the basis of the migration command, establishing an association relationship between the source VM and a corresponding hardware identifier on the target GPU core; and on the basis of the association relationship after the migration, using the target GPU core to process the workload from the source VM. According to embodiments of the present application, while the VM is not shut down, the target GPU core is used to process the workload from the source VM, and thus the workload of the source VM is migrated from a high-load source GPU core to an idle target GPU core, so that the thermal migration between multi-core GPU cores can be achieved, the load between a plurality of GPU cores can be balanced, the pressure of a high-load GPU core can be reduced, the response time can be shortened, and the throughput rate can be increased.

The invention discloses a service request scheduling method and device, electronic equipment and a storage medium, and relates to the technical field of computers. The method comprises the following steps: selecting at least one candidate service instance for processing a business request from a server cluster based on the business request to be scheduled; obtaining computing power resources and network resources of each candidate service instance; selecting a target service instance from the candidate service instances based on the computing power resources and the network resources; calculating an optimal path from the current service node to the target service instance based on the network resources; and forwarding the service request to the target service instance based on the optimal path. According to the technical scheme provided by the invention, the response time and the processing delay can be reduced, and the service quality and the user experience satisfaction can be improved.

The invention discloses an unstructured storage hierarchical strategy optimization method based on machine learning, and relates to the technical field of data storage management, and the method comprises the steps: monitoring a file access event in real time, generating an access log, and extracting a multi-dimensional feature data set; utilizing the trained multi-dimensional decision tree model to distribute a corresponding storage hierarchy for the storage object to obtain a storage hierarchy decision; according to a storage level decision, distributing the storage objects to different storage layers, and carrying out resource configuration and storage operation; monitoring the access condition of the storage object in the new storage hierarchy in real time, and collecting file access performance, storage cost and response time to obtain feedback data; by monitoring the file access event in real time and extracting the multi-dimensional feature data set containing the basic attribute, the access behavior and the context information, efficient response of hotspot data and reasonable utilization of resources are ensured, and the overall performance utilization rate and the cost effectiveness of storage are remarkably improved.

The invention relates to the technical field of data exchange, in particular to a markup language-based data exchange method and system, and the method comprises the following steps: determining a processing priority, monitoring a load and adjusting a processing sequence, optimizing IO response time, recognizing a redundant field and evaluating a key risk, and executing key updating based on the number and complexity of data packet labels. And the tag analysis accuracy and efficiency are optimized. According to the invention, through accurate analysis of the markup language in the data packet, scheduling, transmission and analysis in the data exchange process can be optimized, and evaluation of the number of labels, the complexity of the nested structure and the field length can be realized, so that each data packet can dynamically allocate priority according to the characteristics of the data packet, thereby effectively improving the data transmission efficiency, reducing the delay and improving the data exchange efficiency. By monitoring the load and the transmission opportunity of the data packets in real time, the processing sequence of the data packets can be dynamically adjusted, and resource waste caused by overload of the data exchange system is reduced.

The invention relates to a response performance test method and system of a microswitch. The method comprises the following steps: inputting a multi-pulse trigger sequence to a microswitch contact and collecting contact response original data; performing digital filtering processing on the contact response original data to obtain contact response time sequence data; comprehensive response time parameters including contact mechanical action starting time, electrical initial contact time and electrical stable contact time are calculated according to the contact response time sequence data; performing temperature compensation and contact rebound characteristic extraction on the comprehensive response time parameter to obtain contact rebound characteristic evaluation data; according to the contact rebound characteristic evaluation data and the comprehensive response time parameter, the response performance stability of the microswitch under the high-frequency operation condition is calculated, and a reliability evaluation result is generated. According to the invention, the problem of time sequence measurement error caused by the influence of contact jitter in the traditional test is effectively solved, and the accuracy and consistency of contact response time measurement are remarkably improved.

The embodiment of the invention discloses a capacity expansion and shrinkage method, system and device for a database cluster, a storage medium and a computer program product. The method comprises the steps that response time information of the database cluster with the capacity to be expanded and shrunk for different types of data access requests is obtained; based on the response time information and the type of the data access request, determining a capacity expansion and contraction strategy for the database cluster; and based on the capacity expansion and shrinkage strategy, carrying out capacity expansion and shrinkage processing on the database cluster. Therefore, the capacity expansion and shrinkage strategy of the database cluster is determined by the database cluster according to the response time information of different types of data access requests and the types of the data access requests, so that a mechanism for automatically triggering the capacity expansion and shrinkage of the database cluster based on the business requirements of the database cluster and the business processing requirements of the database is realized; the intelligence of triggering capacity expansion and shrinkage of the database cluster and the efficiency of capacity expansion and shrinkage of the database cluster are improved.

The present invention relates to the technical field of automobile curved screen detection, and in particular to a device and method for detecting the response time of an automobile curved screen, the method comprising: optimizing and affine transforming pixels on a two-dimensional plane image obtained by a 2D camera to obtain corresponding three-dimensional position information of the curved screen; determining the three-dimensional position information of a target icon on the automobile curved screen by a 3D camera, controlling a mechanical arm to accurately click the target icon on the automobile curved screen according to navigation coordinates, synchronously starting high-frame rate cameras set in different directions, obtaining continuous images and time information of changes in different areas of the curved screen when the mechanical arm operates on the automobile curved screen; inputting into a response time detection algorithm for analysis, and evaluating the response time performance of the automobile curved screen according to the output result of the response time detection algorithm. The present invention can realize accurate detection of the response time of an automobile curved screen.

The invention discloses a WebGL-based mass data particle system rendering method and device, and belongs to the technical field of computer graphic processing. The method comprises the following steps: firstly, selecting the type of a particle emitter according to scene requirements, then constructing a primitive object based on points or quadrangles, and configuring three-dimensional coordinates and texture parameters; aggregation rendering is carried out on a single-frame primitive array through a WebGL vertex shader and a fragment shader, and the drawing calling frequency is reduced; the method comprises the steps of dynamically adjusting particle attributes, including position compensation, color gradient and explicit-implicit control, determining a rendering form and playing time of an animation according to requirements of an actual application scene, and supporting fine configuration of a single particle, including texture animation, dynamic scaling and rotation parameters. When a large amount of data is processed, on the premise of ensuring the rendering quality, the rendering efficiency can be remarkably improved, the consumption of a memory and GPU resources can be reduced, the response time of the system can be optimized, and meanwhile, the interaction experience of a user can be improved.

The invention discloses a path isolation method, electronic equipment, a storage medium and a product, and relates to the technical field of network communication, and the method comprises the steps: obtaining the first time consumption of each path in a plurality of paths, the first time consumption being used for indicating the read-write response time consumption of the path; determining a target path in the plurality of paths based on the first time consumption of each path in the plurality of paths; and in response to the fact that the first deviation frequency corresponding to the target path in the first preset time window is greater than the preset deviation frequency, isolating the target path, thereby solving the technical problem that a path with poor link quality cannot be isolated in a related scheme, achieving the purpose of isolating a path with poor link quality but not having read-write overtime or read-write failure, and improving the reliability of the path. And the influence of the path with poor quality on the disk performance is avoided.