48results about How to "Strong data processing ability" patented technology

The invention discloses an intelligent nursing data task scheduling management system based on cloud computing, and relates to the technical field of nursing scheduling management. The cloud computing platform is in communication connection with a data acquisition module, a data storage module, a data processing and analysis module, a nursing evaluation module, a task scheduling module, a report generation module and a user interaction module, and all the modules are in electric signal connection. According to the intelligent nursing data task scheduling management system based on cloud computing, through calculation of the task scheduling evaluation model and the emergency degree evaluation value, the emergency degree and priority of the nursing tasks are evaluated, priority ranking is carried out on the nursing tasks, intelligent scheduling of the nursing tasks is achieved, it is ensured that the emergency and important tasks are processed preferentially, and the task scheduling efficiency is improved. The nursing efficiency and quality are improved, meanwhile, reasonable allocation can be carried out according to the priority of the tasks and available nursing resources, and resource utilization is further optimized.

The invention relates to the field of electric digital data processing, in particular to a control system and method for an all-electric drive aircraft tractor. The method mainly comprises nine steps from S1 to S9. The system comprises a data storage module, a data acquisition module, a data expansion module, a data processing module, a tractor control module and an execution module. An existing full-electric drive aircraft tractor control system has the problems that the data processing capacity is poor and the decision-making accuracy is low. The control system and method for the all-electric drive aircraft tractor are high in data processing capacity and high in decision-making accuracy.

The invention discloses a nonlinear ultrasonic guided wave detection system based on multi-channel receiving, and the system comprises a high-energy fundamental frequency ultrasonic excitation module which is controlled by a trigger signal to generate an electric signal and carries out the amplification and filtering processing; the transmitting transducer generates ultrasonic waves to act on a target object under the excitation of the high-energy fundamental frequency ultrasonic excitation module; the variable-angle receiving transducer array is used for receiving the ultrasonic guided wave signal fed back by the target object and converting the ultrasonic guided wave signal into a feedback electric signal; the ultrasonic acquisition module is used for amplifying the feedback electric signal, sampling the feedback electric signal and converting the feedback electric signal into a digital signal under the instruction of the control and signal processing module; the control and signal processing module comprises an FPGA (Field Programmable Gate Array) chip and an ARM (Advanced RISC Machines) main processor, and is used for controlling the generation of an instruction and performing time domain-frequency domain-space domain information extraction on the digital signal sent by the ultrasonic acquisition module, and calculating to obtain a material nonlinear parameter carried by the guided wave signal; and performing micro-damage evaluation and life prediction based on the nonlinear parameters of the material.

The invention discloses an environment situation awareness data engineering system based on multi-source data fusion, which relates to the related technical field of environment situation awareness and comprises a multi-source data acquisition module, a multi-source data processing module, an environment evolution analysis module, an ecological restoration evaluation module, an ecological system evolution module and a visual observation module. The invention further discloses an environment situation awareness method based on multi-source data fusion, which comprises the steps of collecting environment data, effectively integrating the data, and presenting the data to a terminal user in a chart by utilizing a model evolution trend, a prediction result and possible influence of environment change on human behaviors. The UEB model is suitable for various climate and topographic conditions, has high precision and reliability in a high and cold plateau complex environment, can help to analyze and predict the influence of human activities on environmental elements and the influence of environmental changes on human behaviors, deeply excavates the interaction between the human activities and the environmental changes, and improves the prediction accuracy of the human activities and the environmental changes. And insight is provided for decision makers.

The invention discloses an intelligent parking lot vehicle monitoring system, and belongs to the technical field of parking lot vehicle management. Comprising a vehicle end, and the vehicle end is connected with an intelligent monitoring platform. The vehicle end comprises a vehicle running state information acquisition module, an AI intelligent early warning module and an active braking module; the intelligent monitoring platform comprises a real-time monitoring module, a data processing module and a remote control module. Through the Internet of Things, big data and AI technologies, all-weather monitoring, data analysis and abnormal early warning of the vehicle are realized; through the active brake module and the passive infrared detector, the safety performance of the equipment in emergency is enhanced, and automatic deceleration or emergency stop can be realized to avoid accidents; the active braking module assists operators, the influence of the environment and dense personnel on operation is reduced, and the operation safety and stability are improved. And meanwhile, intelligent scheduling is supported, vehicle operation is optimized, and the empty driving rate is reduced. A mobile terminal management function enables a manager to master the dynamic state of a field at any time and efficiently deal with emergencies.

Coronary artery disease is the most common disease in the cardiovascular field and is also one of important factors causing death in the global range, and by conducting blood vessel segmentation and stenosis detection on coronary angiography images, doctors can diagnose the coronary heart disease more accurately. The invention provides a brand new deep learning architecture SAM-VMNet, and the model combines the powerful feature extraction capability of MedSAM and the linear complexity advantage of a visual state space model of VM-UNet, so that the model has higher reasoning speed and stronger data processing capability than Transformer, and higher segmentation accuracy and stability of coronary angiography images are realized. Moreover, a'dynamic queue 'is used for capturing the narrow part of the blood vessel, and the narrow part is compared with the normal blood vessel diameter before and after the narrow part, so that quantitative calculation of the blood vessel stenosis degree is realized. The algorithm is high in operation speed, and full-automatic blood vessel contour extraction and stenosis degree detection can be achieved. The kit can be applied to the clinical diagnosis process of coronary heart disease.

The invention discloses a trusted system for realizing digital asset right confirmation through an agricultural block chain technology, and belongs to the technical field of computer programs. User data verification, data storage, data right confirmation, data cleaning (redundancy), data comparison and data classification operations are realized in a distributed bookkeeping mode, data storage in a data lake is realized, the stored data is subjected to ownership certification, data distribution of digital asset right confirmation is carried out on the data (group) subjected to right confirmation certification, and data distribution is carried out on the data (group) subjected to right confirmation certification. A verification algorithm proves ownership, use right and management right of data assets, ownership confirmation of the data is achieved, traceable trace information is generated, and records generated in the test process comprise the whole process node of user operation. The core algorithm adopts the most advanced computer algorithm model to build the whole system in the aspects of safety, data intelligent classification, data cleaning and data right confirmation, and it is ensured that the trust of a user to the system in the using process reaches 100%.

The invention discloses an on-chain enterprise risk identification method and system based on a credit chain large model. The system comprises a data preprocessing module, a model matching module, a weight parameter loading module, a data operation reasoning module, a risk prediction output module and the like. Large model training and optimization are carried out by integrating industry, region, type and other multi-dimensional data sets, a credit chain vertical type general model and a special model are formed, and the method can adapt to credit and risk prediction evaluation, monitoring and early warning of a single enterprise or an integrated enterprise in different supply chain and industry chain scenes. A more comprehensive, accurate and real-time solution is provided for enterprise management and industry supervision, and remarkable beneficial effects and advantages are achieved.

The invention discloses a general data processing system based on a PSOC. A Flash module is connected with the PSOC; the memory chip is connected with the PSOC; the Ethernet interface module is connected with the PSOC chip; the Cameralink module is connected with the PSOC chip, and the Cameralink module is connected with the The CAN transceiver is connected with the PSOC chip; the CAN FD module is connected with the PSOC chip; the RS485 module is connected with the PSOC chip; the RS422 module is connected with the PSOC chip; the synchronous bus interface is connected with the PSOC chip; the SRIO interface is connected with the PSOC chip; the PCIE interface is connected with the PSOC chip; and the parallel bus interface is connected with the PSOC chip. The PSOC is adopted as a processor, so that the data processing requirement can be met, and abundant peripheral interfaces can be expanded through on-chip logic resources.

The invention discloses an urban drainage waterlogging prevention data monitoring method and system, and particularly relates to the technical field of urban drainage, and the method comprises the steps: S1, determining a drainage waterlogging prevention region: determining data in a target city as a target drainage waterlogging prevention region, and then dividing the target drainage waterlogging prevention region into sub-regions according to an equal-time and equal-area division mode, the sub-regions in the target drainage and waterlogging prevention region are sequentially numbered as 1, 2,..., i,..., n according to the equal time, and are sequentially numbered as 1, 2,..., j,..., m according to the equal area; s2, drainage system data acquisition: obtaining drainage system data in the target drainage waterlogging prevention area in real time, and transmitting the drainage system data to a drainage system data processing step; according to the method, the drainage system data and the meteorological data are analyzed and judged at the same time, the data from multiple different sources can be smoothly integrated and analyzed, the comprehensiveness and depth of the monitoring data are ensured, and the overall monitoring effect is improved.

The utility model relates to the technical field of electrical engineering, and discloses a transformer capacity tester. The transformer capacity tester comprises a tester main body, a portable handle, a heat dissipation port, fan blades, a motor, a filter screen, an air inlet, a box cover, a lock catch, a buffer sponge, a hinge, a digital display screen, a control knob, a control button, an indicator light, a power interface, a ground interface, a measurement interface, a circuit board, a voltage sensor, a microprocessor and a current sensor, the portable handle is fixedly connected to the upper end of the tester main body. According to the transformer capacity tester, the built-in voltage sensor, the built-in current sensor and the built-in frequency measuring device ensure high precision and reliability of measurement, which are crucial for accurately evaluating the working capacity and efficiency of the transformer, and the design of the measuring interface enables the tester to be suitable for transformers of different models and specifications. And the application range is widened.

The invention discloses a dry quenching circulating air volume online prediction method and system based on an AGRU-PLS model, and belongs to the technical field of dry quenching production process intelligent prediction. According to the method, the production process data of the dry quenching full-process technology is collected, and a corresponding information database is constructed and stored; preprocessing the data, including cleaning and filling missing data, and finally performing standardization processing on the data; performing feature processing on the data in a correlation analysis mode, and finding out variable features with high correlation with the circulating air volume in the whole process; establishing an AGRU-PLS model, establishing a characteristic and circulating air volume covariance maximum model through an outer model, and solving a data collinearity problem in a mode of solving latent variables by iteration; the method comprises the following steps: establishing an Attention-GRU internal model, and mining nonlinear and dynamic relationships among data; the model is updated, and online prediction of the circulating air volume is achieved; and the prediction result of the circulating air volume is converted into a given value of the circulating fan, and the given value is written into UaExpert software to achieve control over the circulating fan.

The invention provides a real-time analysis method for measuring chemical substances in a brain of a living body. The real-time analysis method comprises the following steps: setting test parameters, and calculating the number of times of cyclic measurement; de-noising, checking, caching and measuring the collected original data by adopting a multi-thread working mode based on the number of cyclic measurement times; and verifying the clean data for the second time by using the verification algorithm, and comparing whether the data of the verification interval after the second verification is consistent with the original data of the same interval. High time resolution is realized; performing dynamic monitoring; real-time data processing; performing multi-parameter analysis; long-term monitoring; accumulating data; the sensitivity is high.

The present invention discloses an environmental situation awareness data engineering system based on multi-source data fusion, which relates to the technical field related to environmental situation awareness, including a multi-source data acquisition module, a multi-source data processing module, an environmental evolution analysis module, an ecological restoration assessment module, an ecosystem evolution module and a visualization observation module. The present invention also discloses an environmental situation awareness method based on multi-source data fusion, including collecting environmental data, effectively integrating the data, using model evolution trends and prediction results and the possible impact of environmental changes on human behavior, and presenting them to end users in charts. The UEB model of the present invention is applicable to a variety of climate and terrain conditions, and has high accuracy and reliability in complex environments of high-cold plateaus. The UEB model can help analyze and predict the impact of human activities on environmental elements, as well as the impact of environmental changes on human behavior, deeply explore the interaction between human activities and environmental changes, and provide insights for decision makers.

The utility model relates to a brain fatigue detection and recovery system based on a TGMA and an STM32 single-chip microcomputer, which comprises a power supply module, a control module, a wireless transmission module, an electroencephalogram acquisition module and a music playing module, and is characterized in that the power supply module is respectively connected with the control module, the wireless transmission module, the electroencephalogram acquisition module and the music playing module; a signal receiving end of the control module is connected with the upper computer through the wireless transmission module, the upper computer is connected with the electroencephalogram acquisition module through the wireless transmission module, and a signal output end of the control module is connected with the music playing module through the wireless transmission module. According to the utility model, electroencephalogram acquisition is carried out on a testee through the electroencephalogram acquisition module, acquired data is transmitted to the upper computer for processing and analysis through Bluetooth, the upper computer transmits an instruction to the single chip microcomputer and the music playing circuit for working through the communication module, and brain fatigue of the testee is relieved by listening to music. The utility model has the advantages of low cost, small volume, easy operation and the like.

The utility model provides a bank outlet delivery machine control system. The bank outlet delivery machine control system comprises a client, a delivery total device, a dispatching center and an outlet terminal. Data communication connection is established between the client and the delivery total device; and data communication connection is established between the delivery total device and the dispatching center and the network terminal. Wherein the delivery total device comprises a delivery middleware and a delivery transaction cloud, and the delivery middleware adopts an intelligent picking-up cabinet.

The invention provides a classification method and device for key cell types and subtypes of a thoracic aortic dissection. The method comprises the following steps: preprocessing a thoracic aortic dissection and a normal contrast tissue sample to obtain cell types; determining suspected key cell types of the thoracic aortic dissection according to the proportion of cell types in the aortic dissection and the normal control tissue sample, and obtaining cell subtypes corresponding to the suspected key cell types of the thoracic aortic dissection based on gene expression data of the suspected key cell types; determining the suspected key cell subtypes of the thoracic aortic dissection according to the cell subtypes corresponding to the suspected key cell types of the thoracic aortic And according to the suspected key cell type of the thoracic aortic dissection and the suspected key cell subtype of the thoracic aortic dissection, determining the key cell type and subtype of the arterial dissection. Through the method, the key cell type and subtype of the thoracic aortic dissection can be determined.

The invention discloses a rescue guidance method and device and a medium, and the method comprises the steps: obtaining the help data of a help seeker; based on the help seeking data, determining the severity of a help seeking event corresponding to the help seeker; based on the severity, determining a target rescue guidance strategy for the help seeker; and based on the target rescue guidance strategy, guiding the help seeker to process the help event.

The utility model discloses a purging device additionally arranged on an automatic alignment reading head of coke oven equipment, and relates to the field of coking equipment. On the basis of the original air compressor system of the coke oven equipment, the blowing electromagnetic valve of the code identification system is additionally arranged, the PLC is used for controlling the starting and stopping of blowing, the reading head gas blowing pipeline is additionally arranged, and particles in the atmosphere are blown through high-pressure gas of the air compressor in a severe environment, so that the atmospheric visibility of a working area of the reading head is improved, and the reading head is more stable in working. And the light beams emitted by the optical fiber emitter in the code plate identification system can work normally, so that the code plate identification system is suitable for severe industrial environments, and the maintenance-free level is really achieved. According to the utility model, the stability of the code plate identification system in a severe industrial environment is improved, the automation degree of four locomotives is improved, the external environment interference is reduced, and a solid foundation is laid for intelligentization. Meanwhile, the labor intensity of personnel can be reduced, the frequency of cleaning the reading head lens is reduced, and particles in the atmosphere are prevented from being attached to the lens surface to affect the recognition precision.

The invention discloses an object searching method, electronic equipment and a computer readable storage medium. The method comprises the steps that cloud equipment receives an object searching signaling from terminal equipment; wherein the object searching signaling is generated by the terminal equipment in response to an object searching operation of a user; and based on the object searching signaling, performing visual object searching in the to-be-searched area by using the large model. In this way, the object searching accuracy and efficiency can be improved.

The utility model provides a transformer area branch monitoring device based on low-voltage loop fault discrimination and positioning, which comprises a branch monitoring terminal host, an auxiliary machine, a wireless temperature sensor and an open-close type high-precision current transformer, and the analog signal input end of the wireless temperature sensor is the analog signal input end of the transformer area branch monitoring device. The digital signal output end of the wireless temperature sensor is connected with the digital signal input end of the branch monitoring terminal host, and the digital signal output end of the open-close type high-precision current transformer is connected with the digital signal input end of the branch monitoring terminal host. The control signal output end of the branch monitoring terminal host is connected with the control signal input end of the auxiliary machine, the control signal output end of the auxiliary machine is the control signal output end of the transformer area branch monitoring device, and the transformer area branch monitoring device achieves fault judgment and positioning of transformer area branch monitoring through the hardware components.

The invention relates to the technical field of power sensors, in particular to a high-isolation voltage sensor which comprises an insulating shell and an isolation assembly arranged in the insulating shell. A pretreatment assembly and a post-treatment assembly are arranged on the two sides of the insulating shell respectively; the preprocessing assembly is used for adjusting the gain of an input signal to a linear working area; and the post-processing component is used for reducing nonlinearity of the output signal. According to the invention, light transmission is carried out in a light insulation and insulation epoxy sealing environment, so that interference of external light can be effectively prevented, and the purity of signals is ensured. Meanwhile, the sealing environment is also beneficial for realizing high-voltage physical insulation, and the safety and the stability of the system are ensured. And the insulation grade of 50KV can be reached, which means that the device can normally work in ultrahigh voltage-withstanding occasions such as a high-voltage high-isolation power supply, and safe and stable operation of an electric power system is ensured.

The invention discloses a network fault traceability method for air traffic control voice communication, which comprises the following steps: step 1, collecting voice communication network multi-source data, the voice communication network multi-source data comprising service machine account data, equipment machine account data, fault characterization data and network monitoring data; 2, a voice communication network multi-source entity recognition algorithm is built, and multi-source entity relation prediction is carried out; and step 3, establishing a multi-source entity fault tracing algorithm of the voice communication network, and performing network fault tracing. The invention relates to the technical field of communication networks, and can solve the problem that in the prior art, aeronautical communication network fault tracing is not comprehensive, accurate and efficient.

The present invention provides a river network hydraulic calculation modeling method based on BIM and GIS platform. Aiming at the problems of large modeling workload, high data processing difficulty and low modeling efficiency of existing river network hydraulic calculation software, the data processing and data intercommunication capabilities of the existing BIM+GIS platform are utilized to efficiently realize the establishment of river network waterway calculation models of different details and dimensions under different waterway regulation schemes, including one-dimensional, two-dimensional and three-dimensional hydraulic models.

The invention relates to a network security collaborative protection system based on Internet of Things equipment in the field of data processing, which comprises a security system, the security system comprises a network monitoring and prevention module and equipment protection modules, and access modules are in signal connection between the multiple equipment protection modules and the network monitoring and prevention module. The network monitoring and prevention module is in signal connection with an Internet of Things module, the equipment protection module is in signal connection with Internet of Things equipment, and the equipment protection module is carried in the Internet of Things equipment. According to the method, the access authority in the security system is set, so that low-authority tourists and registered users do not have data interaction with the collaborative protection module, the risk that data of the collaborative protection module serving as dynamic protection crashes due to access of a large amount of data is reduced, and the overall reliability of the security system is improved.

The invention discloses a codebook-free near-field beam forming method and device based on deep learning, equipment, a medium and a product, and relates to the field of near-field communication, and the method comprises the steps: constructing and training a convolutional neural network model; the convolutional neural network model comprises a plurality of feature extraction modules, and each feature extraction module comprises two convolutional layers, two regularization layers and two activation layers; the filling is set to be 1 and the size of a convolution kernel is set to be 2 * 2 in the first layer of convolution, and the filling is set to be 0 and the size of the convolution kernel is set to be 2 * 2 in the second layer of convolution; inputting the current channel state information into the trained convolutional neural network model, and determining an optimal beam forming vector; and adjusting a transmitting signal of an antenna array based on the optimal forming vector to form a directional beam, and completing near-field beam forming. According to the invention, the overhead brought by beam training can be effectively reduced, and higher beam forming precision can be obtained.

The invention discloses a wagon balance compliance monitoring method and system based on a monitoring rule, and relates to the technical field of wagon balance compliance monitoring, and the system comprises the following components: an intelligent monitoring algorithm module which carries out the learning and analysis of preprocessed data through employing an advanced machine learning or deep learning algorithm, and carries out the analysis of the data; the module can automatically identify and extract the compliance mode of the wagon balance, the monitoring accuracy and efficiency are improved, the intelligent monitoring algorithm module adopts a neural network model, the compliance mode is automatically learned and identified from a large amount of wagon balance weighing data, the efficiency and accuracy of the system are greatly improved, and the system reliability is improved. And meanwhile, the neural network model has strong data processing capability, can process massive real-time data and extract key information and characteristics from the data, so that the system can monitor the compliance state of the wagon balance in real time and find abnormal or illegal behaviors in time.

The utility model discloses an intelligent monitor for reading heat and temperature data, and the monitor comprises a first meter reading module which is used for reading the real-time data of a building heat meter through a first RS-485 interface circuit and / or an M-BUS interface circuit; the second meter reading module is used for reading real-time data of the indoor temperature regulator through the second RS-485 interface circuit and / or the RF wireless communication module; the intelligent monitor can read real-time data of the heat meter and the temperature regulator at the same time, has a wired data acquisition mode and a wireless data acquisition mode, and not only enhances the flexibility of data acquisition, but also can adapt to various monitoring environments; the master control module has strong data processing capacity and can receive, process and analyze data from the two meter reading modules, the processed data is sent to a cloud server through the data transmission module, and an efficient, reliable and easy-to-manage heat and temperature data monitoring solution is provided for a user. The method is suitable for various application scenes such as intelligent buildings and intelligent homes.

The present invention discloses a method and system for monitoring urban drainage and flood prevention data, which specifically relates to the field of urban drainage technology, including S1, drainage and flood prevention area determination, determining the data in a target city as a target drainage and flood prevention area, and then dividing it into sub-areas according to equal time and equal area division methods, and numbering the sub-areas in the target drainage and flood prevention area in sequence as 1, 2, ..., i, ..., n according to equal time, and in sequence as 1, 2, ..., j, ..., m according to equal area; S2, drainage system data collection, acquiring the drainage system data in the target drainage and flood prevention area in real time, and transmitting it to the drainage system data processing step; the present invention simultaneously analyzes and judges the drainage system data and meteorological data, can smoothly integrate and analyze data from multiple different sources, ensure the comprehensiveness and depth of the monitoring data, and improve the overall monitoring effect.

This invention relates to the field of power generation coordination control technology, specifically to a method, apparatus, and equipment for coordinated control of complementary combined power generation. The method involves acquiring operational data of the complementary combined power generation system; formulating a complementary coordinated control strategy based on the system's operational constraints and energy balance objectives; constructing a multi-channel fuzzy pulse neural network computational model with polarity and promoters to formally represent and execute the strategy according to the coordinated control strategy; inputting current operational data into the constructed multi-channel fuzzy pulse neural network computational model to trigger corresponding neurons and pulse transmission rules for computational evolution; and parsing the final output of the multi-channel fuzzy pulse neural network computational model to generate specific control commands for energy storage devices, controllable power generation devices, and grid interaction, thereby achieving dynamic power balance and stable operation of the complementary combined power generation system. This method provides more reliable and flexible energy coordination control for the complementary combined power generation of distributed photovoltaic and cascaded small hydropower.