34results about How to "Improve resource usage efficiency" patented technology

The invention relates to the technical field of environmental monitoring, in particular to a stored material controlled atmosphere maintenance early warning method and system based on environmental monitoring, and the method comprises the following steps: collecting real-time gas composition, temperature and humidity data, carrying out the time sorting of the collected data, recognizing the change trend of multiple parameters at each time point, and obtaining a parameter trend prediction result. According to the method, by combining data time sorting and change trend analysis, analyzing the relation between parameters and environment safety values and recognizing the variables exceeding the threshold value, accurate adjustment of gas, temperature and humidity is ensured, pertinence of parameter control is improved, early warning marking is carried out on the high-frequency fluctuation area through continuous monitoring and dynamic data classification, and the accuracy of the high-frequency fluctuation area is improved. The storage article quality guarantee condition monitoring capability is improved, so that article loss caused by environment change is reduced, a data analysis method and a real-time monitoring method are integrated, the operation logic of an environment controller is optimized, and the overall efficiency and the resource utilization efficiency of the system are improved.

The invention relates to the technical field of intelligent water affair management, and discloses a method and system for dynamically adjusting the reporting moment of an NB water meter, and the system comprises NB water meter terminal equipment which is responsible for collecting water meter data in real time and uploading the data to a data management platform through an NB-IoT network; the data management platform is responsible for receiving, processing and storing data from the plurality of NB water meter terminal devices; the reporting moment adjusting module is used for dynamically adjusting the reporting moment of the NB water meter terminal equipment according to the strategy generated by the data management platform; the communication management module is responsible for communication between the NB water meter terminal equipment and the data management platform; the intelligent alarm and event processing module is responsible for monitoring the running state of the system in real time; and an equipment remote control module. By dynamically adjusting the reporting time, the system can reduce unnecessary frequent reporting, especially in a time period when the water consumption is relatively small or relatively stable, so that the power consumption of the equipment is remarkably reduced. Therefore, the battery life of the NB water meter terminal equipment can be prolonged, and the maintenance cost is reduced.

The invention discloses an Internet of Things multi-stage communication method and system for city management, and relates to the technical field of Internet of Things communication, and the method comprises the following steps: monitoring the state of Internet of Things equipment, collecting the state data of the equipment, analyzing the historical use data of the Internet of Things equipment, and determining the data transmission demands of the Internet of Things equipment. According to the Internet of Things multi-stage communication method and system for city management, through the energy consumption and performance analysis module, the operation state and performance of the Internet of Things equipment are monitored and evaluated in real time, the energy consumption bottleneck and the performance decline sign of the equipment are identified, early warning is given out in time, and corresponding optimization measures are suggested to be taken, so that the city management efficiency is improved. The service life of the equipment is effectively prolonged, downtime and maintenance cost caused by equipment faults are reduced, meanwhile, parameter settings such as a dormancy awakening strategy are intelligently adjusted according to the actual use condition of the equipment, and the energy consumption and operation cost of the equipment are further reduced.

The invention relates to the technical field of digital video devices, in particular to a digital video device control method and device. The method comprises the following steps: acquiring digital monitoring data, performing real-time scene acquisition and dynamic region optimization according to the data, and generating optimized dynamic region data; video frames are read based on the dynamic region optimization data, and abnormal behavior analysis and behavior intention evaluation are carried out; calculating the complexity of monitoring behaviors by combining video frame data and behavior intention data, and evaluating resource consumption increase; the processing bottleneck is evaluated according to the resource consumption growth data, and the processing capability attenuation analysis is carried out, so that the monitoring device is adjusted, and the system performance is optimized; according to the method, the resource allocation and processing capability of the video device is dynamically adjusted through real-time analysis and processing of monitoring data. According to the invention, the digital video device is adjusted, so that the prediction identification of the digital video device is more accurate and efficient.

The invention provides a data acquisition and monitoring analysis system based on an MES platform, and relates to an industrial software application system. Comprising a low-code development module, a factory modeling module, a monitoring module and a data acquisition module, the low-code development module realizes cross-device linkage development and control program generation through combination of a dragging interface and a device API library in an MES platform integration environment, and guarantees efficient communication control of the device, the factory modeling module integrates two production modes, and the monitoring module is connected with the monitoring module. The monitoring module is used for realizing dynamic modeling and optimizing a production process according to multi-dimensional parameters, the monitoring module is used for realizing ultra-low-delay transmission processing and real-time monitoring of data under high concurrency by applying a dual-cache and message middleware mechanism, and the data acquisition module is used for realizing real-time monitoring of the data based on a machine learning algorithm and a complex event processing technology. Dynamically adjusting the acquisition frequency precision based on the production state; the system aims at improving the efficiency, quality and management level of industrial production, and has wide application prospects and important industrial software application value.

The invention discloses a coaxial powder feeding MIG wire powder composite additive manufacturing device and method, and belongs to the field of electric arc additive manufacturing. The device comprises an MIG wire powder composite welding gun for coaxial powder feeding; the composite welding gun comprises a wire powder coaxial copper nozzle with a wire feeding port in the middle, an ion gas shell and a powder feeding shell. Powder feeding ports are formed in the left end and the right end of the wire feeding port. The wire powder coaxial copper nozzle is located at the bottom end of the plasma arc welding gun and connected with the welding gun shell. A second channel between the ion gas shell and the powder feeding shell is used for feeding powder; the MIG electrode comprises a welding wire tube used for arranging a welding wire, and one end of the welding wire is sent out through a wire feeding port. A slotting sleeve is arranged on the outer side of a welding wire tube of an MIG electrode of the composite welding gun and located on the inner side of an ion gas shell. According to the device, the welding wire and the powder can synchronously enter the molten pool, so that the problem of component regulation and control in multi-component alloy additive manufacturing is effectively solved, and the utilization efficiency of the powder is improved.

The invention discloses a fixed budget sorting preferential method and system and a storage medium, and relates to the technical field of network architectures, and the method comprises the following steps: S1, dividing all candidate schemes into a plurality of groups, and carrying out the initialization setting; s2, based on a multi-round mechanism, independently executing a local selection process of a group of candidate schemes by each processor to obtain a local optimal candidate scheme; s3, each processor generates an additional observation value for the local optimal candidate scheme by using the remaining sampling budget; and then, calculating a sample mean value of the additional observation value of each local optimal candidate scheme, and selecting the optimal candidate scheme with the maximum sample mean value as the optimal candidate scheme. According to the method, the problem of large-scale fixed budget sorting preferential selection can be efficiently solved, the friendliness of user experience is ensured, and good expandability is achieved.

The invention relates to the technical field of behavior analysis, in particular to an AI-based behavior recognition monitoring system which comprises a facial expression analysis module, a behavior pattern recognition module, an abnormal behavior judgment module and a monitoring adjustment decision module. According to the method, the emotion is monitored in real time by using the AI, the facial expression change can be accurately evaluated, the emotion fluctuation can be accurately analyzed, the monitoring of the emotion state is more accurate, the behavior type and the possible abnormal condition are identified through the speed and position information of the action, the judgment speed and accuracy of the abnormal behavior are improved, and the accuracy of the abnormal behavior is improved. Therefore, safety monitoring in a complex environment is more effective, potential abnormal behaviors such as invasion or theft behaviors can be accurately identified, response speed and effectiveness of prevention measures are improved, distribution of monitoring resources can be dynamically optimized by adjusting a monitoring strategy according to a behavior risk level, and safety of a user is improved. Therefore, the response capability and the resource use efficiency of the monitoring system are improved, and the overall safety is enhanced.

The invention discloses a data leakage prevention method and device, computer equipment and a storage medium, and belongs to the technical field of big data. According to the application, a pre-constructed log cloud platform is deployed at a cloud end, and the log cloud platform is accessed to a service system; deploying a request interceptor in the service system, and connecting the request interceptor with each interface; monitoring by using a docking interface, and when a user request is monitored, obtaining the request; obtaining log data matched with the request, and intercepting a log field corresponding to the identity information and the access address information from the log data; synchronizing the log field to a log cloud platform, and performing log anomaly detection on the log field by using a log anomaly detection model to obtain a detection result; and determining the data query permission of the user according to the detection result. The invention further relates to the technical field of block chains, and the log data are stored on the block chain nodes. According to the invention, the data leakage prevention capability of the system is improved, and the memory consumption of the system is reduced.

The invention discloses a GSLB dynamic scheduling method and system based on a proximity water line. The objective of the invention is to optimize flow distribution in a multi-data center scene. According to the method, by adding a proximity water level line module and a weight polling module, fine control over a delay proximity data center and flow scheduling according to application types are achieved. A user can set different water level intervals and load proportions, load distribution of a data center service address is dynamically adjusted according to actual network delay, and it is ensured that a user request is routed to the optimal data center. The method not only improves the user experience, but also improves the reliability and flexibility of the system by reducing the waiting time and providing faster response, and adapts to different network environments and service requirements.

The invention provides a method, a device, equipment and a medium for allocating virtual machine resources by host machines, and relates to the technical field of host machine resource allocation, the method comprises the following steps: acquiring allocated logic core number and residual logic core number corresponding to each physical core on each host machine to obtain a logic core array list; each host machine is automatically checked according to the logic core array list, it is ensured that when any host machine is crashed and unavailable, enough resources can be provided for migrating virtual machine resources on the host machine, the stability of the cloud platform environment is improved, and normal operation of services is guaranteed; meanwhile, a large number of CPU resources do not need to be reserved manually, the resource use efficiency is improved, and the cost is reduced.

The invention discloses a container terminal storage yard management and control digital twinborn simulation method and system and a storage medium. The method comprises the steps of obtaining production data, related to storage yard management and control, of a current container terminal, and generating an initial state of a digital twin platform; according to the historical operation rule of the container wharf, container entry random event probability distribution is set in the digital twin platform; simulating an approach container position selection process based on a digital twin platform, and simulating a random event according to the set probability distribution; and selecting positions of entering containers through the container wharf storage yard management and control gravitational field model. According to the method, the defect that a container terminal storage yard management and control digital twinborn system is lack of future storage yard operation state mapping can be overcome through random event generation in cooperation with a storage yard management and control gravitational field model.

The invention provides a wrist-worn device identity authentication method based on vibration feedback. A vibration signal is generated through equipment such as a smart watch, and vibration response data of a user is collected in real time by using a built-in accelerometer. The method comprises the steps of signal noise filtering, direction correction and normalization preprocessing, then vibration characteristics are extracted through multi-order difference, and a multi-branch convolutional neural network (MCNN) is used for characteristic extraction and fusion so as to capture vibration characteristics of different time scales. And finally, identity matching is carried out through a Softmax classifier. The method shows good stability and recognition precision in various wearing postures, hand action changes and complex use scenes, and has high anti-interference capability.

The invention relates to the technical field of convolutional neural networks, and discloses a data processing method, device and chip based on a sensing, storage and calculation integrated framework, the method is used for processing convolution calculation of input matrixes [A1, A2,..., AM] of M * N input data, the size of a convolution kernel W is k, and the step length is s, the method comprises the following cycle steps: constructing an input sub-matrix Yi, forming a recombined convolution kernel Wi, and constructing the input sub-matrix Yi; and performing convolution calculation on Yi and Wi, and judging whether circulation is completed or not. According to the method, the device and the chip disclosed by the invention, the number of analog registers required by convolution operation in the sensing, storing and computing integrated chip can be effectively reduced through circulating control on input and weight, the area, the cost and the power consumption of the sensing, storing and computing integrated chip are greatly reduced, and the computing speed is improved.

The present invention provides a resource configuration method, apparatus and equipment, the method comprising: obtaining reference information of a first device; determining a second device that can currently use wireless resources based on the reference information of at least one first device; wherein, when the wireless resources are being occupied, the at least one first device comprises: a device requesting to use the wireless resources and a device occupying the wireless resources; when the wireless resources are not occupied, the at least one first device comprises: a device requesting to use the wireless resources; the embodiment of the present invention can dynamically adjust the right to use the wireless resources based on the reference information of each first device, solve the problem of simultaneous deployment of multiple communication systems when the wireless resources are limited, and can also improve the efficiency of resource utilization.

The invention discloses a big data management method and system based on semantic analysis, and relates to the technical field of big data management. A multilayer semantic abstract data organization structure comprising a base layer, a mode layer and a statistical layer is constructed, real-time semantic analysis is performed on input data, and semantic descriptors are generated; the high-frequency data instance in the base layer is stored to a corresponding level according to a central semantic index, a semantic folding operation is triggered based on a preset rule, the high-frequency data instance in the base layer is automatically abstracted into a modeled representation of a mode layer, and similar representations in the mode layer are further aggregated into an aggregated representation of a statistical layer; when the query is responded, the system analyzes a query intention and determines a target data abstraction level, high-level aggregation or modeling representation is restored into bottom-layer detailed data as required through reverse expansion operation, and a query result is generated; through the multi-layer semantic abstract data organization structure and the data folding operation, the storage efficiency of mass complex data and the performance of multi-granularity intelligent query are effectively improved.

The invention belongs to the field of radar signal processing, and discloses a joint resource scheduling and transmission zeroing method and system based on reinforcement learning. According to the method, in a scene that a plurality of transmitting nodes and a plurality of receiving nodes cooperatively execute a target tracking task in a receiving and transmitting separated MIMO radar network, aiming at the problem that a traditional radar resource allocation method lacks dynamic real-time adjustment capability and lacks comprehensive consideration on long-term performance of radar system resources, firstly, the dynamic real-time adjustment capability and the comprehensive consideration on the long-term performance of the radar system resources are considered; according to the method, joint optimization is carried out by considering transmission zero setting and resource scheduling, emission waveforms, residence time and power distribution of nodes are taken as optimization variables, then, cumulative signal-to-noise ratio constraints and the low interception probability of a whole task are considered at the same time, an optimization model for minimizing the interception probability is provided, and finally, for the optimization model, the optimization model is optimized. An algorithm based on reinforcement learning is adopted for solving, specifically, a PPO algorithm is adopted, and finally the low interception probability and the resource management efficiency are improved.

The application relates to the technical field of data processing, can be applied to business scenes such as financial technology and medical health, and discloses a data hierarchical storage method and device based on access representation, equipment and a medium, which comprises the following steps: collecting access behavior features of original data, identifying the heat state, writing data into a matched first target storage equipment according to a preset equipment performance corresponding relationship; after data storage, continuously monitoring subsequent access features, dynamically judging whether the heat state changes; if the heat state changes and meets specific migration conditions, a second target storage equipment is re-allocated and a data migration operation is completed, so that automatic hierarchical storage management of cold and hot data is realized. Through the acquisition of data access representation and the dynamic identification of the heat state, hierarchical migration of different heat data between different performance storage equipment is realized, the resource use efficiency and the access performance of the storage system are improved, and the storage cost is reduced.

A source base station and a transmission method. A source base station transmits a radio resource control reconfiguration message to a user equipment. The radio resource control reconfiguration message includes an indication message and a candidate base station list, and the candidate base station list is used for indicating a plurality of candidate base stations. The source base station determines a non-target base station among the plurality of candidate base stations based on a prediction report received from the user equipment. And the source base station transmits a handover cancellation request to the non-target base station in the plurality of candidate base stations, so that the non-target base station releases a reserved resource corresponding to the user equipment. The transmission technology provided by the invention can improve the resource use efficiency of the mobile communication system.

The invention discloses a data error correction method based on BCH coding, a storage medium and an integrated chip, and relates to the technical field of chip design and application, the data error correction method based on BCH coding comprises the following steps: obtaining target data obtained by BCH coding, and according to a target vector of the target data and a preset check matrix, correcting the target vector of the target data; determining each syndrome corresponding to the target vector; if the syndromes representing data errors exist in the determined syndromes, generating an error equation according to the syndromes; constructing a target number of verification equations based on the coefficient of the error equation, grouping the constructed verification equations, and solving each group of verification equations by adopting the same group of summation modules to obtain error position data; and performing error correction on the target data according to the error position data to obtain an error correction result. By applying the scheme provided by the embodiment of the invention, resources occupied for realizing the error correction function can be reduced.

The invention provides a marketing method and system combined with a third-party platform, electronic equipment and a storage medium. The method comprises the following steps: constructing a first prediction model on a target platform; the first prediction model is a model obtained by encrypting first behavior data of the target platform by adopting a privacy computing technology and training according to the encrypted first behavior data; acquiring parameters of a second prediction model of the third-party platform, and optimizing the first prediction model according to the parameters of the second prediction model; the second prediction model is obtained by training the third-party platform according to the encrypted second behavior data; using the optimized first prediction model to predict behaviors and preferences of the user to obtain a prediction result; a marketing strategy is optimized according to the prediction result; namely, by obtaining the model parameters of the third-party platform, the user is comprehensively understood, favorable data support is provided for formulating the marketing strategy, and the effectiveness of the strategy and the resource use efficiency are improved.

The utility model relates to the technical field of cold rolling, and provides a rolling device for a four-roll cold rolling mill, which comprises a base, the top of the base is fixedly connected with a device shell through screws, one side of the device shell is fixedly connected with two symmetrically arranged motor mounting seats through screws, servo motors are mounted on the motor mounting seats, and the servo motors are fixedly connected with the device shell through screws. The servo motor is started to drive the driving gear and the driven gear, then the driving shaft and the driven shaft are driven to rotate, the synchronous belt and the protruding block enable the swing block to swing in a reciprocating mode through the synergistic effect of the limiting groove, automatic rotation of the smearing shaft and the smearing brush is achieved, and rolling oil smearing is effectively conducted on the driving roller and the driven roller; no extra motor is needed in the smearing process, and cost can be reduced; and meanwhile, the water suction pump is started to ensure that the rolling oil is conveyed to the smearing brush from the liquid storage tank, after the iron plate is rolled, the cleaning brush removes redundant rolling oil and impurities on the surface, cyclic utilization of the rolling oil is achieved, and the resource use efficiency is improved.

The present invention discloses a digital twin method and system for edge computing, wherein the method includes: using an external network to network a MEC physical system with a digital twin of the MEC system; the MEC physical system is communicated through an external network based on information, and the digital twin of the MEC system is communicated through an external network to monitor the MEC physical system to obtain monitoring results, and the monitoring results are analyzed and evaluated to obtain evaluation results, so as to complete the mirroring of the MEC physical system; and the constructed MEC physical system is digitally twinned, and the closed-loop optimization control of the MEC physical system is completed based on the evaluation results; the unconstructed MEC physical system is digitally twinned, and the optimization design of the MEC physical system is completed based on the evaluation results. The present invention can continuously optimize the MEC physical system through the digital twin of the MEC physical system, improve the management efficiency and resource utilization efficiency of the system, and reduce the operating cost and investment expenditure cost of the MEC service.

The utility model relates to the technical field of low-temperature gas cold energy recovery, in particular to a low-temperature gas cold energy recovery system which comprises a cold liquid storage tank, heat exchange equipment and a water cooling tower, and a low-temperature gas medium is arranged in the cold liquid storage tank; the heat exchange equipment comprises a medium inlet and a medium outlet communicated with the medium inlet, the medium inlet is communicated with the cold liquid storage tank through a first pipeline, a to-be-cooled liquid medium is arranged in the heat exchange equipment, and the to-be-cooled liquid medium can exchange heat with a low-temperature gas medium to form a cold liquid medium; the water cooling tower communicates with the medium outlet through a second pipeline, and the cold liquid medium is transmitted to the water cooling tower through the second pipeline. According to the technical scheme, the low-temperature gas cooling capacity recovery system can recover the cooling capacity in the low-temperature gas.

The present invention relates to the technical field of convolutional neural networks, and discloses a data processing method, device and chip based on a sensing-storage-computing integrated architecture, the method is used to process the convolution calculation of the input matrix [A1, A2, ..., AM] of M×N input data, the size of the convolution kernel W is k, the step length is s, and the method includes the following loop steps: constructing an input submatrix Yi, forming a reorganized convolution kernel Wi, Yi and Wi convolution calculation, and judging whether the loop is completed. The method, device and chip of the present invention can effectively reduce the number of analog registers required for convolution operations in a sensing-storage-computing integrated chip by cyclically controlling the input and weights, greatly reducing the area, cost and power consumption of the sensing-storage-computing chip, and improving the calculation speed.

The embodiment of the invention provides a data scheduling method, a data access method, a cloud storage platform and computing device.The data scheduling method is applied to a data scheduling end of the cloud storage platform and comprises the steps of obtaining historical use data of resources on at least one cloud storage service cluster, acquiring historical access data of a plurality of storage containers on at least one cloud storage service cluster; performing data analysis based on the historical use data and the historical access data, and predicting a matching relationship between the at least one cloud storage service cluster and the plurality of storage containers in a target time period; based on the matching relationship, the plurality of storage containers are deployed on the corresponding target cloud storage service clusters, and the resource use condition of each cloud storage service cluster and the access demand of the storage container are predicted in advance through data analysis of the historical use data and the historical access data, so that reasonable container deployment is completed in advance, and the user experience is improved. The problem of service response delay is solved, and the resource use efficiency and the overall performance of the cloud storage platform are improved.

The invention discloses a GPU computing power scheduling system based on a DPDK, and the system comprises a DPDK separation processing model layer which is in communication connection with an external application layer, and is used for distributing a task to a processor suitable for processing the task according to the nature and demands of the task issued by the application layer; the dynamic task scheduling layer is in communication connection with the DPDK separation processing model layer and is used for receiving the tasks distributed by the DPDK separation processing model layer so as to schedule and distribute the tasks; the water level monitoring layer is in communication connection with an external GPU (Graphics Processing Unit) and a CPU (Central Processing Unit) and is also in communication connection with the DPDK separation processing model layer; and the bottom hardware layer comprises hardware components such as a processor and network equipment and is used for providing physical resources required by system operation. According to the GPU computing power scheduling system based on the DPDK, system performance is improved, task scheduling is optimized, deep learning reasoning is accelerated, network data packet processing efficiency is improved, and a flexible resource dynamic allocation mechanism is provided. The purposes aim at promoting technical innovation and improving the efficiency and performance of the system.

The invention relates to a data acquisition device for a visual modeling platform, which comprises a supporting plate, a perforated column fixedly mounted at the top, a telescopic cylinder fixedly mounted on the outer surface of the perforated column, a box fixedly mounted on one side surface of the telescopic cylinder, a positioning hole formed in the perforated column, a first limiting block movably mounted in the positioning hole, and a second limiting block movably mounted in the first limiting block. One end of the first limiting block extends to the telescopic cylinder, a pull rod is fixedly installed at one end of the first limiting block, one end of the pull rod penetrates through the interior of the box body, and a first spring is installed between the first limiting block and the box body; a supporting table is fixedly mounted at the top of the telescopic cylinder, an opening is formed in the first end face of the supporting table, sliding grooves are formed in the two side faces of the supporting table, and mounting plates are movably mounted in the sliding grooves; and an image data collector is mounted on the top surface of the mounting plate. According to the embodiment of the invention, the convenience of image acquisition and the security of the image data acquisition device are enhanced.

The application relates to a database backup machine incremental reconstruction idempotent retry method and device. The method comprises the following steps: dividing a reconstruction process into three stages of pre-preparation, intermediate transmission and post-closing, and allowing retry only in the first two stages; first calculating and persisting a master-standby common WAL consistency site common-checkpoint and a difference structure filemap, then sequentially copying a WAL, a serialized change-block mirror and a filemaptarget to a disk; after fault recovery, reverse serializing and continuing transmission, realizing incremental level idempotent retry; if the error context is the same for two times in succession, immediately converging. Through accurate retry control and state persistence, the application significantly reduces the full amount construction triggering probability, improves the data consistency guarantee capability, simultaneously has the non-invasive integration advantage, and can effectively improve the availability and operation and maintenance efficiency of a database system.

This invention relates to the field of financial marketing technology, specifically to an integrated financial marketing management method and system based on marketing data domains. The method includes the following steps: collecting customer transaction and preference data, calculating the magnitude of change and normalizing it into feature vectors; analyzing group differences, calculating the rate of change, and generating a judgment result; combining lifecycle data clustering stage numbers and conversion progress matching rhythm parameters to generate personalized marketing plans; calculating ad placement frequency and consultant service ratio according to multi-group needs for optimized resource allocation; collecting interaction and transaction data after resource allocation, inputting it into a regression model for analysis, and generating marketing effectiveness evaluation results. In this invention, by collecting customer transaction and preference data, quantifying changes, and normalizing them into feature vectors, analyzing group differences to dynamically identify states, combining lifecycle clustering matching rhythm parameters to generate strategies, optimizing ad placement frequency and consultant service ratio according to group needs, and using regression analysis to form a closed-loop optimization management system.