29results about How to "Improve data processing capabilities" patented technology

The invention discloses a transformer substation unmanned aerial vehicle autonomous inspection system which comprises an unmanned aerial vehicle platform, a three-dimensional modeling module, an inspection route setting module, an autonomous inspection module, a mobile monitoring platform, an image acquisition module, an image processing module, an alarm module, a visualization module, a data storage module and a wireless communication module. Wherein the three-dimensional modeling module comprises laser radar equipment and three-dimensional modeling software, the routing inspection route setting module is used for setting different routing inspection routes according to different routing inspection modes and corresponding routing inspection rules, the autonomous routing inspection module comprises a navigation system and a positioning base station, and the mobile monitoring platform comprises a remote controller and vehicle-mounted charging equipment. The image processing module is used for processing and analyzing different types of collected images and different purposes of collected images by using different algorithms so as to timely discover abnormity and give an alarm; the method has the advantages of being good in inspection abnormity processing effect, good in positioning effect, convenient to use and good in data processing effect.

The invention discloses an intelligent robot multi-task full-autonomous management method supporting environment interaction. The system is applied to an application software architecture of a robot, and the architecture comprises a main module, a data acquisition module, a monitoring module, an image sending module, a sensing planning module, a moving module, a view finding module, a visual navigation module and a data sending module. The method comprises the following steps: determining task types of a main module, a data acquisition module and a monitoring module as normal tasks, and determining task types of other modules as abnormal tasks; the data acquisition module is used for acquiring measurement data sensed by the sensor in real time and storing the measurement data; monitoring an instruction sent by the outside in real time by using a monitoring module; according to a preset scheduling cycle, judging whether the module of which the task type is an abnormal task meets a triggering condition or not by utilizing the main module; if yes, enabling each triggered module to execute a corresponding task; and if not, keeping each untriggered module in a blocked state and waiting for triggering. The execution efficiency of the robot can be improved.

The invention discloses a photovoltaic power generation energy efficiency analysis method and device suitable for a cigarette factory and a storage medium, and belongs to the technical field of photovoltaic power generation. The method comprises the following steps: acquiring historical generating capacity data and real-time monitoring data of a photovoltaic power generation system; inputting the historical generating capacity data and the real-time monitoring data into the trained gradient boosting tree prediction model for generating capacity prediction, and obtaining the theoretical generating capacity of the photovoltaic power generation system in a future period of time; acquiring the actual generating capacity of the photovoltaic power generation system in the corresponding future time period; the actual generating capacity and the theoretical generating capacity are compared and analyzed, and energy efficiency evaluation is completed; wherein on the basis of a countercurrent protection data rejecting mechanism, if the real-time monitoring data is in a countercurrent protection state, the related real-time monitoring data is rejected. According to the method, historical data, real-time monitoring data and a machine learning algorithm are combined, and accurate evaluation of the energy efficiency of the photovoltaic power generation system is realized through accurate power generation capacity prediction and a countercurrent protection data rejection mechanism.

This specification provides a data processing method, device and computing device based on a brain-like accelerator card. Before specific implementation, the brain-like accelerator card can be installed on the target computing device according to the preset installation rules; then, according to the preset construction rules, a program container image that matches the brain-like accelerator card and is compatible with the host machine's environment, software and hardware resources, permissions, etc. is prepared. During specific implementation, multiple associated algorithms related to the requested target data processing are first determined; then the image identifiers of the corresponding multiple target algorithm application container images are determined; based on the image identifiers of the multiple target algorithm application container images, a target computing device deployed with a brain-like accelerator card is constructed and called according to the target image parameter group, and target data processing is performed by running multiple target algorithm application container images. This can simplify the installation and use process of the brain-like accelerator card, and use the brain-like accelerator card to efficiently and accurately complete target data processing.

The application provides an AI computing power allocation method, system, device, storage medium and program product, and relates to the technical field of data processing. The AI computing power allocation method determines the corresponding target AI algorithm model based on the service demand of the target reasoning service in real time, and then dynamically matches the target computing power resource used to load the target AI algorithm model by combining the processing demand of multiple AI algorithm models, the preset adaptability rules of various heterogeneous computing power resources, and the current use state of the various heterogeneous computing power resources, so as to realize dynamic allocation of AI computing power resources, avoid computing power resource overload or idling, improve computing power resource utilization, reduce task reasoning delay, and thus improve data processing capability.

The invention provides a data processing device. The data processing device comprises a housing; the signal processing piece is arranged in the shell; the display assembly comprises a display module and a display frame, the display module is arranged on the display frame, the display frame is rotatably arranged on the shell, so that the display assembly has an unfolded display position and a folded closing position, and the display module is electrically connected with the signal processing part; the adjusting assembly comprises a rotating part and a telescopic mechanism, the rotating part is rotatably arranged on the shell, the display frame can drive the rotating part to rotate when rotating, the first end of the telescopic mechanism is movably arranged on the rotating part, and the second end of the telescopic mechanism can move downwards. The distance between the side, provided with the display assembly, of the shell and the supporting face is increased. Through the technical scheme provided by the invention, the problems that the heat dissipation efficiency of a processing device in the related technology is low, a gap between the bottom of the processing device and a desktop is small when a display screen is turned on, and heat dissipation is affected due to no air circulation can be solved.

The utility model provides a vehicle machine, a vehicle machine system and a vehicle. The utility model relates to the technical field of vehicles. The vehicle machine comprises a micro-control unit, a tire pressure monitoring module, a power supply module, a communication module, an antenna module, a central processing unit, an information interaction module, a video module and an audio module, the micro-control unit is in communication connection with the tire pressure monitoring module; the micro-control unit is in circuit connection with the power supply module; the micro-control unit is in communication connection with the communication module; the communication module is in communication connection with the antenna module; the communication module is in communication connection with the central processing unit; the micro-control unit is in communication connection with the central processing unit; and the central processing unit is in communication connection with the information interaction module, the video module and the audio module, so that the efficiency of information transmission between the vehicle machine and the vehicle networking communication box is improved.

Embodiments of the present application provide a data processing method and device for low-resource languages, equipment and storage medium. The method comprises: obtaining prompt data to be processed corresponding to a first language; inputting the prompt data to be processed into a preset target language model to obtain a corresponding processing result; wherein the target language model is obtained by training a preset language model based on a first loss, a second loss and a third loss; the first loss is used to indicate the adjustment of the parameters of a first semantic alignment key layer in the preset language model; the second loss is used to indicate the adjustment of the parameters of a second semantic alignment key layer in the preset language model; the third loss is used to indicate the adjustment of the parameters of a plurality of network layers contained in the preset language model, and the third loss is determined based on the difference between the predicted language response text output by the preset language model and the corresponding response text label. In this way, the data processing performance of the model for low-resource languages can be significantly improved.

The utility model belongs to the technical field of taper hole measurement, and particularly relates to a portable railway vehicle taper hole measuring instrument. The device mainly comprises two dial gauges which are respectively installed on a T-shaped workpiece, the T-shaped workpiece comprises a first installation rod and a second installation rod, and the dial gauges can be installed on a long-dimension section or a short-dimension section through fastening bolts and are used for measuring standard long and short taper holes. Besides, the first mounting rod comprises a fixed sleeve and a movable rod, and the movable rod can be inserted into the fixed sleeve and locked through a limiting knob so as to adapt to measurement of taper holes with different lengths. In order to meet the measurement requirements of different apertures, an extension rod can be installed on the measuring rod of the dial indicator. According to the utility model, the selected dial indicator has a Bluetooth wireless transmission function, so that manual intervention is reduced, and a worker can more intuitively know the measurement result of the taper hole. The device has the advantages of simple structure, convenient operation, high measurement precision and the like, and is suitable for on-site rapid measurement of railway vehicle taper holes.

This invention discloses a joint optimization method and system for task offloading and resource allocation based on SAGIN. It collects task and scheduling information through a SAG-IoT system; utilizes the task data and scheduling information to achieve optimal association between UAVs and IoT devices based on a matching game algorithm, and makes optimal decisions for task offloading to maximize the computational performance of the SAG-IoT system; based on optimal association, optimal task offloading decisions, and maximizing the computational performance of the SAG-IoT system, it constructs an online offloading framework based on deep reinforcement learning, constructing a path from input X(t) to optimal action x. * The low-complexity mapping strategy (t) is based on repeated interactions between different modules and a random environment, iterating and running sequentially to achieve joint optimization of task offloading and resource allocation. This invention achieves optimal computational performance while stabilizing the system queue. In addition to utilizing binary computation offloading, the optimization framework can also be extended to online partial computation offloading strategies consisting of multiple independent subtasks.

The invention provides an antenna configuration optimization method and device, a storage medium and a program product, relates to the technical field of communication, and is used for reducing the power consumption of terminal equipment in a beam scanning process. The method comprises the following steps: traversing a preset antenna number configuration scheme set, and determining an antenna number configuration scheme meeting a constraint condition as an optimal antenna number configuration scheme; the constraint condition comprises the lowest energy consumption of the terminal equipment in the target coverage area of the base station in the beam scanning process, and the signal quality of the terminal equipment in the target coverage area of the base station is greater than or equal to a preset signal quality threshold value; and optimizing the number of antennas of the base station based on the optimal antenna number configuration scheme.

The invention discloses a TSN management method and device based on software definition, a medium and equipment, and aims to realize centralized configuration and scheduling of a TSN switch by utilizing a northbound interface and a southbound interface through coordination of a centralized controller and the TSN switch. The centralized controller allows remote access and configuration parameter modification through a northbound interface so as to generate a specific configuration instruction and a scheduling strategy, and it is ensured that the network carries out efficient scheduling and bandwidth allocation according to real-time requirements; and the southbound interface is used for issuing the configuration instructions to the switch and executing functions of clock synchronization, network state monitoring, forwarding and control separation and the like. In this way, seamless connection between different network technologies is achieved, the certainty of data transmission is guaranteed, and meanwhile the data processing capacity and the utilization efficiency of bandwidth resources are improved.

The invention relates to the technical field of digital microfluidics, and discloses a hybrid digital microfluidics system which comprises an upper computer, a power supply, a main control unit, a programmable voltage source, a multi-way switch, a digital microfluidics chip and a micro piezoelectric pump, the upper computer is used for generating an activation signal and a liquid drop pumping signal; the main control unit is used for responding to the activation signal and activating the electrode array corresponding to the activation signal; the micro piezoelectric pump is used for responding to a liquid drop pumping signal and enabling liquid drops to flow into the digital micro-fluidic chip through the microneedle and to be adsorbed on the activated electrode array. According to the invention, the speed of an experiment and a production process is increased through an automation technology, meanwhile, errors caused by manual operation are reduced, the consistency of operation and the repeatability of a result are ensured, and the effect of liquid drop pumping in digital microfluidics is improved.

The present application relates to the field of voice interaction technology, and discloses a training method and device for a voice emotion interaction model, and an electronic device, including: obtaining target interaction data of target domain intention; when the target interaction data meets preset conditions, performing enhanced training on a first pre-trained large language model according to the target interaction data to obtain a target first pre-trained large language model; obtaining enhanced emotion text data output by the target first pre-trained large language model; and performing enhanced training on a voice emotion interaction model according to the enhanced emotion text data. Perform enhanced training on the first pre-trained large language model according to the target interaction data to obtain the target first pre-trained large language model, thereby obtaining text and speech with consistent emotions as enhanced emotion text data. Perform enhanced training on the voice emotion interaction model according to the enhanced emotion text data, and optimize the voice emotion interaction model, thereby improving the data processing capability of the voice emotion interaction model.

The invention provides a model optimization method and computing equipment, which are used for multi-engine edge computing equipment, and the method comprises the following steps: loading an original model structure of a computing model; splitting the original model structure to obtain a multi-engine model structure; inserting a synchronization operator into the multi-engine model structure to obtain a multi-engine synchronization model; and loading the multi-engine synchronization model to an edge computing device to execute model operation, the edge computing device comprising a plurality of computing engines, and the plurality of computing engines synchronously executing the multi-engine synchronization model based on the synchronization operator. According to the technical scheme, the data processing capacity of the multi-engine model can be optimized, the model execution efficiency is improved, and the complexity of the model development process is reduced.

The application discloses a distributed storage time delay optimization method and device and medium, and relates to the field of distributed systems. The method is applied to a distributed cluster, data sent by a client is received, a log and a transaction are constructed in a master OSD according to the data, the master OSD is selected in advance in all OSDs of a PG, each OSD contains a shared memory, the log and the transaction are stored in the shared memory of the master OSD, and other OSDs in the PG acquire the log and the transaction from the shared memory of the master OSD through RDMA. The above scheme realizes the shared memory between the OSD set of the PG in the distributed cluster, and uses RDMA to replace the traditional TCP / IP mode to perform the synchronization logic of the data between the master and the replica of the cluster, thereby effectively optimizing the network time delay of data synchronization and improving the data processing capacity of the whole cluster.

The application discloses a kind of three-level n-dimensional digital twin systems supporting coupling operation of coal mine robot group, including terminal layer, edge layer and cloud end layer three levels.The robot group in terminal physical layer generates single-machine behavior level twin in terminal virtual layer based on real-time data through terminal AI model, realizes virtual and real two-way control, and field operator obtains augmented information through AR equipment, feeds back decision-making opinion, and multi-modal control node;Edge virtual layer generates collaborative task level twin based on single-machine behavior level twin, and constructs n-dimensional edge twin system through edge AI model.The computer host of cloud end physical layer provides computing power support for n-dimensional cloud end twin system, and centralized control operator accesses cloud end twin system through VR equipment, to realize remote monitoring and control;Cloud end virtual layer generates global planning level twin based on edge side data, and parallel analysis of n-dimensional cloud end twin system is realized through cloud end AI model, and the optimal global planning is comprehensively obtained.

The invention discloses a video code stream transmission method and device, electronic equipment and a storage medium. The method is applied to first electronic equipment, and comprises the following steps: generating a random character string in response to triggering of a video code stream transmission event, and generating a target sequence based on the random character string; splitting an initial video code stream to be transmitted by taking bytes as units based on the target sequence to generate at least two serialized byte streams; and transmitting the at least two serialized byte streams to second electronic equipment according to corresponding serialized channels, and transmitting the random character string to the second electronic equipment. Through the technical scheme provided by the embodiment of the invention, not only is the security of video code stream transmission effectively ensured, but also the system resource expenditure is effectively reduced and the data processing performance is improved because the video code stream does not need to be subjected to encryption operation.

The invention belongs to the technical field of numerical control, and discloses a device and method for inhibiting uncertainty disturbance and improving the conveying performance of an euphausia superba conveying suction pump. The lumped disturbance of the system is estimated by using a disturbance observer, and the constraint of the disturbance upper bound on the conservative property of the control design is avoided; then, a novel sliding mode device is adopted to suppress system lumped disturbance, and the robustness of the system is improved; the novel sliding mode controller adds an exponential function item and a power function item in the reaching law to enable the system state to converge rapidly. A sigmoid function is used for replacing a switching function, continuous control input is achieved, high-frequency buffeting is weakened, and stability and continuity of control signals are guaranteed. Therefore, the positioning precision is improved, a stable control signal can be generated, the control performance of the system is obviously improved, the tracking error is reduced, high-frequency oscillation is avoided, and the control precision of the euphausia superba conveying suction pump servo system is further improved.

The application relates to a project management method, device, computer equipment and storage medium. The project management method comprises the following steps: acquiring project data; splitting the project data, acquiring data segments, mapping the data segments, and acquiring mapping data; according to the type of the mapping data, merging the mapping data of the same type to acquire marking data; according to the type of the marking data, aggregating the marking data of the same type to acquire a first data unit; presetting a second data unit, comparing the first data unit with the second data unit, positioning problems, and acquiring a management result. Through acquisition of a large amount of project data, the project data is classified, aggregated and analyzed, automatic management of the project is realized, the data processing capacity of the system is enhanced, the data has more definite identification, the work efficiency is improved, and the problem positioning accuracy is improved.

The present application relates to the technical field of online car-hailing risk control, and particularly relates to a method for implementing an online car-hailing pick-up and drop-off abnormality risk control dynamic rule engine based on flink CEP. In the online car-hailing service, after a passenger issues an order on a mobile phone, the driver is affected by external environmental factors, vehicle condition factors, other human factors and complex environments during the process of picking up and dropping off the passenger, which may result in a variety of abnormal situations such as pick-up timeout, driver driving in the opposite direction, driver not moving and the like. A related risk control system is established in each service system. The present application uses mysql to dynamically load rules to ensure the dynamic scalability of the rules, and uses flink CEP to calculate the rules to ensure the timeliness and accuracy of the calculation results. The overall scheme supports the timeliness and dynamic scalability requirements of abnormal indicators in the risk control system under the premise of not stopping service when the rules are changed.

The invention relates to the field of agent development, in particular to a zero-code AI agent development and deployment data management system and method.The zero-code AI agent development and deployment data management system comprises a data flow testing module, a model connection module, a feedback processing module, a project migration module and a secondary development module; the model communication module is used for forward connection of a conversion interface and generation of a conversion queue, the feedback processing module is used for sharing input data streams among models, the project migration module is used for adjusting the shared data proportion of the models, and the secondary development module is used for developing new models according to the service providing proportion of the models. According to the method, more accurate output content can be generated through sharing data, the structure of the intelligent agent is continuously optimized, a good performance optimization curve is obtained in the service process of the intelligent agent, the data processing capacity is improved, and the operation efficiency of the intelligent agent system is enhanced.

The application provides a communication method and system based on multi-partition independent cache of FC equipment, which comprises an FPGA arranged in the FC equipment and a DDR connected with the FPGA. The FPGA is used to realize data communication between the FC equipment and a target cache partition of a peer device. The data flow direction of the target cache partition to the peer device is a sending direction, and vice versa. In the data flow receiving direction, the FPGA receives an IU and stores the IU in a small queue mode by default, divides the IU according to the size of a dma_buffer, pushes the IU into a corresponding block in the DDR for storage, and reads out the IU when a condition is met; the FPGA switches to a large queue mode for storage when the condition is met, stores the IU in the same block used by the large queue in the DDR by splicing, and reads out the data stored in the block by using an aging timeout report. The communication method can fully improve the buffer use efficiency, dynamically adjust the number of DDR storage blocks, dynamically solve the multi-channel concurrency problem, and improve the overall system performance.

The application relates to the technical field of air conditioning systems, and discloses an intelligent air conditioning management and control and scene mode adjustment system, which comprises the following: a comprehensive monitoring module that monitors air quality parameters and user physiological data indoors and outdoors in real time; a strategy generation module that analyzes and processes the collected data to generate an intelligent air conditioning control strategy; a control execution module that adjusts the operation parameters of the air conditioning system in real time according to the generated control strategy; a scene mode identification module that analyzes the air quality parameters and user physiological data to identify the current scene; a scene mode adjustment module that adjusts the operation parameters of the air conditioning system to match the operation state of the current scene mode; and a user interaction interface that provides a user interaction mode and can realize manual switching of the scene mode and adjustment of the operation parameters of the air conditioning system. The application significantly improves the intelligent level of the air conditioning system, optimizes energy consumption management, and improves the comfort and use experience of users.

This application discloses a method, system, device, and medium for processing blockchain consensus data, including: packaging business data generated by a database and sending it to a block-producing node; the block-producing node generating first signature data to be agreed upon based on the business data; sending the business data and the first signature data to a consensus node for consensus processing based on a target compressed data packet structure to obtain consensus data; wherein the target compressed data packet structure includes a target file header, a data area, and a file tail; wherein the target file header includes the original file header and file tail; packaging the consensus-adjusted business data into blocks for on-chain processing and storing the consensus data; when the number of consensus data groups stored in the blockchain blocks reaches a preset threshold, performing backup-based deletion processing on the consensus data. This application can improve consensus efficiency and block generation speed, reduce the storage pressure on nodes, effectively improve the operational stability of the blockchain system, and can be widely applied in the field of blockchain technology.

The application provides a strip product process parameter step-by-step recommendation method and system based on representation learning and a storage medium, and relates to the technical field of information. The method comprises the following steps: obtaining strip product production whole-process data and constructing a structured representation through a knowledge graph; embedding modeling entities and relationships in the knowledge graph based on a RotatE representation learning algorithm of complex space relationship rotation to generate vector representation of complex relationships; generating multi-process process parameter recommendation based on a step-by-step recommendation strategy of time sequence dependence, and realizing cross-process parameter constraint through dynamic updating of the knowledge graph. The application solves the complex relationship modeling problem based on the RotatE representation learning algorithm of complex space relationship rotation; improves the implicit knowledge capturing capability through the construction of a modular semantic aggregation knowledge representation model; in addition, a step-by-step recommendation strategy is proposed to process the time sequence dependence through a "link prediction-graph completion-link prediction" iterative process.

The invention discloses a mine monitoring communication system and method, and belongs to the technical field of wireless communication, the mine monitoring communication system comprises a radio frequency transceiver, a first node, a second node and a third node; the radio frequency transceiver is arranged in a vertical mine tunnel; the first node is deployed at a preset monitoring position in a mine; the second node is deployed in the wearable device; the third node is deployed at a transfer position between the radio frequency transceiver and the first node and a transfer position between the radio frequency transceiver and the second node; according to the invention, the first node and the second node are used for monitoring static and dynamic physical quantities respectively, and the third node is used for transferring to ensure comprehensive monitoring in a complex mine environment; in the uplink communication and downlink communication process, data transmission and state confirmation between nodes are realized, the reliability and coverage range of communication are enhanced, the accuracy and reliability of data are ensured, and the overall stability is improved; the problems of limited signal transmission distance and serious signal attenuation in a mine environment are solved.

The present invention discloses a method, system and storage medium for identifying and counting IoT terminals, which are applied to the field of communication technology and can distinguish and count data information of different types of IoT terminals, effectively improving the data processing capability of IoT platforms. The method comprises: obtaining a communication message reported by an IoT terminal; wherein the communication message comprises a preset optional field; parsing the preset optional field according to a preset parsing rule to obtain parsed data; identifying the parsed data to obtain terminal identification information; wherein the terminal identification information comprises terminal type information; and counting the connected IoT terminals according to the terminal type information to obtain terminal statistical data.

The invention provides a big data analysis method and device supporting SAS language analysis and execution and application, a keyword segment in a to-be-operated SAS code is recognized, word segmentation processing is performed according to the keyword segment to obtain a word segmentation result, for a macro code field in the word segmentation result, an mac field is stored in a system mac library, a user-defined field is stored in a user-defined mac library, and the user-defined field is stored in a user-defined mac library. Wherein for macro variables in word segmentation results, the macro variables are stored in a system macro variable library, self-defined local variables are stored in a self-defined macro variable library, and the word segmentation results are gradually put into a pre-operation code pool according to the code sequence of SAS codes to be operated; the codes in the to-be-run code pool are segmented sentence by sentence according to the scores to obtain single-sentence codes to be executed, and analysis and execution of SAS are achieved on the premise of not depending on SAS software.