24results about How to "Guaranteed effective use" patented technology

The invention relates to the technical field of geological exploration, in particular to a geological exploration safety monitoring and early warning method and system, and the method comprises the following steps: carrying out the exploration region division based on a geological exploration data set, carrying out the risk assessment and density assignment of geological units in combination with the risk degree, and generating a geological risk density map. According to the method, through geological risk assessment and density assignment, exploration area division and risk assessment, and in combination with risk level judgment of geological units, safety monitoring and early warning in the geological exploration process are more refined and scientific, and by means of stress analysis simulation and terrain sensitivity analysis, the safety of the geological exploration process is improved. According to the geological disaster early warning method, the stress response of the geological unit under natural and artificial loads is revealed, the capability of identifying risk points and sensitive areas in an exploration area is improved, early warning is carried out on geological disasters in the early stage, the real-time performance and pertinence of geological disaster early warning are optimized, and losses caused by the geological disasters are reduced.

The invention relates to a high squint SAR imaging processing method under Doppler frequency distance time varying. The method comprises the following steps: firstly, carrying out linear walking correction and distance compression according to a squint angle; then distance partitioning and azimuth upsampling are carried out according to the pulse repetition frequency, the instantaneous Doppler bandwidth and the Doppler frequency time-varying quantity along with the distance, azimuth spectrum ambiguity caused by the change of the Doppler center frequency along with the slope distance is eliminated through azimuth spectrum extension, and sub-block splicing is carried out after upsampling of all sub-blocks is completed; carrying out azimuth space-variant resampling in a two-dimensional frequency domain, and eliminating azimuth space-variant in a range gate; then consistent compression and stot interpolation are carried out, and two-dimensional accurate focusing is completed; and finally, correcting image distance position time shift caused by linear walking correction, and intercepting an effective imaging area to obtain a focused SAR image. According to the method, the Doppler spectrum fuzzy problem caused by Doppler frequency distance time variation can be effectively eliminated, so that effective application of a traditional large squint algorithm is ensured, and a correctly focused SAR image is obtained.

The embodiment of the invention discloses an image data acquisition method, a storage medium and an image acquisition device, and belongs to the field of image processing. Through a double-lens orthogonal synchronization mode, that is, when the first image sensor (sensor0) outputs half-frame data, the synchronization pulse signal is triggered to control the second image sensor (sensor1) to start to output frame data of the second image sensor (sensor1), so that accurate and synchronous acquisition of image data of the two sensors is realized. According to the synchronization mode, the problem of data coverage possibly occurring under the condition that each sensor only has a single buffer area is avoided, and data output of the two sensors is carried out alternately, so that the integrity and accuracy of data are ensured.

The invention provides a man-machine collaborative program repairing method based on a large language model, relates to the technical field of automatic program repairing, and remarkably improves the accuracy and success rate of program repairing. According to the method, a large language model is guided through preliminary analysis of manual teaching, errors in a program can be more accurately positioned and repaired by combining a repairing process of multiple iterations and more information introduced step by step, misjudgment and omission are reduced, and the program repairing efficiency is greatly improved. Compared with a traditional method, blind exploration of a large language model on complex problems is avoided through a man-machine cooperation mode, time and computing resources are saved, and adaptability of program repair is enhanced. According to the method, program defects of various types and complexity can be handled, and simple grammar errors or complex logic errors can be effectively handled through a step-by-step deep repair process.

The invention relates to the technical field of recycling of cutting fluid in the silicon wafer cutting industry, in particular to a large circulation process method based on back-end automatic allocation, the amount of pure water used in the process allocation method is approximately equal to the amount of water lost by filter pressing, and the loss of pure water can be greatly reduced; and when the COD value is kept unchanged, the addition amount of the cutting fluid is far smaller than the filter pressing loss amount, so that the waste of the cutting fluid is reduced, and the finished product water is supplied to the slicing end more quickly.

An object is to provide a submerged arc welding wire that generates less fumes at the time of welding and can form a weld metal with high strength and excellent cryogenic toughness to find suitable use as a welding material for high-Mn content steel materials for use in cryogenic environments. A metal-cored wire for submerged arc welding contains specific components.

The invention discloses a cross-domain disease prediction method based on graph self-supervised transfer learning. The method comprises the following steps: processing functional magnetic resonance imaging data and clinical phenotype data; modeling by functional magnetic resonance imaging data of a subject to form a brain feature structure topological graph; nodes of the brain feature structure topological graph are sampled to obtain sub-graphs, and # imgabs0 # sub-graphs with the highest intimacy score are selected; mapping the node features of the target sub-graph to a low-dimensional vector space to obtain a node embedding matrix; the node embedding matrix is converted into a reconstruction matrix, and the Euclidean distance between an original feature vector and a reconstruction feature vector is calculated to obtain a generation learning score; establishing a comparison relationship between the target node and the adjacent sub-graph, and calculating a comparison learning score; generating a learning score and comparing the weighted sum of the learning score to obtain a prediction probability value of the disease category; and inputting to-be-migrated data into the prediction model to obtain a prediction result of the corresponding disease category. The cross-domain disease prediction accuracy and efficiency are improved.

The invention discloses a list data processing method and device, equipment and a storage medium, relates to the technical field of data processing, and discloses a list data processing method comprising the following steps: obtaining an initial list; according to a plurality of preset interception logics, performing interception processing on list data in the initial list; according to interception processing results generated under the interception logics, interception marks are added to the list data, and the interception marks corresponding to the interception logics are different; and screening list data according to the interception mark, and generating an issuing list. According to the method and the device, the marketing optimization path can be traced back and recovered easily, so that an enterprise can better understand the actual effect of a marketing activity, and adjustment and optimization can be carried out according to needs.

The present invention proposes a processor with pipeline processing design and an execution path prediction method. The processor with pipeline processing design includes a memory controller, an instruction cache module, a sending unit, a scheduler and an execution unit; the execution path prediction method includes: taking the execution of the instruction as the predicted satisfied condition of the conditional jump; when the instruction with a jump request is read, detecting whether the satisfied condition of the conditional jump corresponding to the conditional jump prediction instruction occurs; when the satisfied condition of the conditional jump does not occur, the pipeline continues to execute the next instruction; when the satisfied condition of the conditional jump occurs, the program pointer moves to the specified position requested by the satisfied conditional jump instruction, and the pipeline continues to execute the instruction from the specified position requested by the conditional jump instruction. The present invention can reduce the effect loss due to incorrect prediction by designing the cache column with a jump address, thereby improving the execution efficiency of the program.

The invention provides an intelligent scheduling allocation method based on personnel information, and relates to the technical field of scheduling, the attendance occupation information of target personnel during scheduling allocation is determined according to personnel scheduling information, and scheduling control parameters of shifts to be scheduled are generated according to the attendance occupation information; according to the fluctuation distribution, determining a configuration data set distributed by the work tasks of the target personnel in the scheduling period, and determining a configurable rule of the target personnel during shift allocation scheduling according to the configuration data set and the scheduling control parameters; determining dynamic allocation characteristics of the target personnel during shift allocation scheduling according to the task allocation decision; and determining task allocation constraints of different shifts in the scheduling period according to the configurable rule and the dynamic allocation characteristics, and automatically allocating target personnel in the scheduling period according to the task allocation constraints. Therefore, the dynamic rule flexibility of target personnel allocation during scheduling allocation is improved.

This invention provides a water utility call system, comprising: an extension unit connected to the system via a session boundary controller; a session boundary controller for receiving external call requests from customers via the extension unit, forwarding them to a voice processing module, and simultaneously recording corresponding call target information; and a voice processing module with a built-in call control module for: upon receiving a forwarded call request from a customer, calling a historical call record storage database containing a mapping relationship between call target information and target staff identification; determining the target staff identification recorded in the historical call record storage database based on the call target information; and notifying the session boundary controller to initiate a call request to the target staff through the corresponding extension unit.

The invention provides a crop breeding decision analysis system. The crop breeding decision analysis system comprises a data input module, a data processing module, a data analysis module and a result display module, the data input module is used for receiving user material data uploaded by a user; the data processing module is connected with the data input module and is used for preprocessing the user material data; the data analysis module is connected with the data input module and the data processing module, and is used for analyzing the preprocessed user material data based on the sub-module selected by the user and / or the parameters set by the user to obtain an analysis result; and the result display module is connected with the data analysis module and is used for generating a visual chart and / or a data table based on the analysis result and displaying the visual chart and / or the data table to the user. According to the method, the dependence of breeding personnel on professional bioinformatics knowledge and programming skills can be reduced, key analysis steps in the whole breeding process are simplified, the data analysis efficiency and the integrated support capability of breeding decision are improved, and the application of SNP data in breeding practice is promoted.

The invention relates to the technical field of machine vision, in particular to a new energy field station multi-dimensional monitoring system based on machine vision, which comprises a path planning subsystem and a fault identification subsystem, and has the following functions: the path planning subsystem plans an unmanned aerial vehicle inspection path based on station dynamic demand driving by using a greedy-genetic fusion algorithm; and the fault identification subsystem is used for constructing a multi-modal input neural network, taking the visible light image, the infrared thermal imaging or the fusion of the visible light image and the infrared thermal imaging as input, and identifying a station fault by utilizing machine vision. The unmanned aerial vehicle routing inspection path is planned through the greedy-genetic fusion algorithm, the routing inspection efficiency and the routing inspection precision are improved compared with manual routing inspection, the effectiveness of path planning is guaranteed compared with traditional unmanned aerial vehicle routing inspection, and redundant routing inspection and endurance waste are avoided.

The present invention relates to the technical field of human behavior recognition, and in particular discloses a human behavior recognition method based on radar micro-Doppler characteristics and hybrid multi-networks. By preprocessing the original human body signal of the radar, a micro-Doppler spectrogram representing the micro-Doppler characteristics of human behavior is generated, 1DCNN is used to extract the spatial features of the time series and speed up the network operation efficiency, LSTM is used to capture the time correlation features between sequences to improve the recognition accuracy, the weight allocation mechanism of Attention can focus on more important time features, ensure the effective use of all time and alleviate the problem that the network recognition accuracy decreases due to the long-term memory of LSTM and further improve the recognition accuracy, and the extracted MDF is input into the Softmax classifier to complete the recognition of human behavior. The present invention has the advantages of simple network structure, low computational complexity, fast reasoning speed, high recognition accuracy, etc., and can meet the requirements of accurate and real-time human behavior recognition.

The invention discloses a pipeline transportation device which comprises a clamping groove, an angle adjusting device, a rolling ball component and a fixing piece. Notches are formed in the centers of the angle adjusting devices, and the angle adjusting devices are symmetrically distributed with the to-be-conveyed pipeline as the central axis; the first ends of the at least two rolling ball components are connected with the angle adjusting device through the notches; and the fixing piece is used for fixing the angle adjusting device in the clamping groove. According to the pipeline support, the pipeline can be conveniently transported on the pipeline support in a long, narrow, closed and radioactive pipe ditch, the traditional labor of manually carrying the pipeline in the pipe ditch is avoided, and the construction efficiency is improved; and meanwhile, the residence time of constructors in a high-radiation environment is shortened, and the health and safety of the constructors are guaranteed. In addition, the construction difficulty and the working intensity are reduced. The conveying tool is flexible in design, convenient to disassemble and assemble and capable of being adjusted according to the sizes of a pipe ditch and a to-be-conveyed pipeline.

The invention discloses a battery charging and discharging method and system suitable for a lamp. The method comprises the steps that the geographic position of the lamp and electricity price information are acquired according to longitude and latitude; a target electricity price time period is predicted through the day-ahead electricity price of the place where the lamp is located, whether the current lamp is in the target electricity price time period or not is judged, and a corresponding charging and discharging strategy is executed, and the target electricity price time period is the current day lowest electricity price time period; according to the real-time electricity price and the actual use condition of the lamp, the strategy of mains supply and battery discharging is dynamically adjusted to optimize the charging and discharging strategy; the maximum energy storage threshold value of the battery and the remaining capacity of the battery are obtained, the required charging amount is calculated, the charging duration is calculated according to the required charging amount, and charging is carried out according to the charging duration matched with the target electricity price period, so that the problems of short supply of power in the peak power consumption period and great surplus of power in the valley power consumption period are solved; the time period with the lowest electricity price is intelligently selected for commercial power supply or charging, and the electricity utilization cost is reduced.

The invention provides an intelligent medical online service system and an online service method. The system comprises a service platform, terminal equipment, a community service station and a hospital service terminal, the service platform is connected with a community service station and a hospital service terminal; the terminal equipment is used for a user to register and access the service platform; the service platform comprises a registration and login module, a self-service module, a doctor-seeing appointment module, a doctor-seeing statistics module, a service appointment module, an evaluation module and an optimization module, a user accesses the platform through the terminal equipment, obtains services through different modules, completes inquiry and evaluation, gives preliminary auxiliary diagnosis suggestions through the platform, and optimizes the diagnosis through the terminal equipment. The user is helped to obtain some reference suggestions before appointment to see a doctor, so that the user can better understand the own illness state; the system can reasonably allocate resources of doctors and treatment equipment, ensures effective utilization of the resources, and improves the accessibility of treatment service; and the system performance and the user experience are improved through continuous optimization.

The utility model relates to the technical field of spray drying, in particular to high-sugar carbohydrate spray drying equipment which comprises a drying machine body, a hot air pump is fixedly connected to the top of the drying machine body, an air outlet is formed in the bottom of the hot air pump, and a hot air pipe is inserted into the air outlet. One end of the hot air pipe penetrates through the top of the drying machine body and is located in the drying machine body, the top of the drying machine body is fixedly connected with an equipment frame, one side of the equipment frame is fixedly connected with a first driving motor, and an output shaft of the first driving motor is connected with a rotating shaft through a coupler; one end of the rotating shaft is connected to the inner wall of one side of the equipment frame through a bearing, two second belt wheels are fixedly connected to the outer wall of the rotating shaft, and two equipment plates are fixedly connected to the top of the drying machine body. And the production cost is saved.

The utility model relates to the technical field of sensor testing, in particular to a sensor handheld power supply test box, which comprises a shell, a circuit board, a battery and a display part, and is characterized in that the shell comprises a first shell and a second shell, the second shell is provided with a mounting block, the first shell is provided with a mounting groove for embedding the mounting block, and the mounting block is provided with an elastic limiting block; a limiting groove allowing the elastic limiting block to be embedded is formed in the side wall of the mounting groove, a first limiting assembly, a second limiting assembly and a third limiting assembly are arranged in an inner cavity of the first shell, the second limiting assembly and the inner wall of the containing space form a first cavity allowing a battery to be placed, and the third limiting assembly and the inner wall of the containing space form a second cavity allowing a display part to be placed; according to the product assembly, on one hand, the assembly process of the test box is simplified by adopting a screw-free design, the product yield and the production efficiency are improved, on the other hand, the internal space of the test box body is effectively utilized through the segmentation area, the overall structure is more compact, and assembly is simple and reliable.

The invention relates to the technical field of sample pre-detection, in particular to a cold rolling lubricant pre-detection method and system based on production analysis. The method comprises the following steps: regularly collecting cold rolling lubricant samples on a cold rolling production line, and carrying out ultraviolet and infrared spectrum analysis and sample chemical performance evaluation analysis to obtain chemical performance indexes of the cold rolling lubricant samples; monitoring the physical parameter data set of the cold rolling lubricant sample in real time by using an on-line monitoring sensor arranged in the cold rolling production line, and evaluating and analyzing the physical performance of the sample to obtain the physical performance index of the cold rolling lubricant sample; the cold rolling production process on the cold rolling production line is subjected to production process parameter real-time monitoring and lubricant performance analysis, meanwhile, sample production pre-inspection treatment and sample use suggestion analysis are conducted, and a cold rolling lubricant sample pre-inspection use suggestion scheme is generated so as to execute corresponding cold rolling lubricant sample pre-inspection use suggestion work. According to the invention, more accurate optimization of the cold rolling lubricant production process can be realized.

The invention discloses a list data processing method, a list data processing system and a storage medium, relates to the technical field of data processing, and discloses a list data processing method which comprises the following steps: intercepting a to-be-processed list according to a plurality of preset list interception logics, reading associated data which is not contained in the to-be-processed list and is used for performing interception processing on the list interception logics under the condition that the to-be-processed list is subjected to interception processing through core logics in the list interception logics; generating an issuing list according to the interception processing result; and sending the preset marketing content to the target customer included in the issuing list. The resource waste in the list data processing process is effectively avoided, and the processing efficiency is improved.

The invention, which belongs to the technical field of hydropower station management, relates to a rule-reasoning-based comprehensive management method for an age repair process of a hydropower station, and the method comprises the following steps: step 1, establishing a graph modeling standard age repair process library based on semantic recognition; comprising the steps of graph modeling rule construction and work ticket semantic recognition matching based on a UIE framework; and Step 2, establishing an age repair process management and control based on semantic recognition automatic discrimination. Through combination of a graph modeling technology and a semantic recognition technology, custom configuration and intelligent matching of an age repair process and lean management and control of key links are realized, so that the efficiency and accuracy of age repair work are improved, human errors are reduced, and safe operation of hydropower station equipment is ensured.

The invention, which relates to the technical field of material management, discloses a material fund management control system comprising the following components: an environmental benefit evaluation module, an intelligent sorting and fund distribution module, a dynamic adjustment and feedback module, a partner management module and a transparent management interface module. According to the invention, through integration of the environmental benefit evaluation module and the intelligent sorting and fund distribution module, accurate quantitative evaluation of the green degree of materials, intelligent sorting of purchase plans and automatic fund distribution are realized, so that the green material identification capability of enterprises is improved; and multiple factors such as cost-benefit ratio, supply stability, technical feasibility, market trend and the like are comprehensively considered through an intelligent algorithm, so that fund distribution is more scientific and reasonable, the green purchasing efficiency of enterprises is improved, effective utilization of funds is ensured, and a solid foundation is laid for sustainable development of the enterprises.

The present application relates to the field of wind power generation technology, and discloses a wind farm multi-dimensional intelligent diagnosis and fault early warning system based on data driving.The present application comprises a state perception quantization module, a state assumption generation module, a verification generation implementation module, a confidence degree synthesis calculation module and a diagnosis report generation module; the system generates state signals by identifying abnormalities and using dynamic threshold values to monitor wind turbine operation data in real time; generates fault root assumption based on diagnosis knowledge graph and historical cases; plans and executes multi-dimensional verification chain for each fault root assumption, obtains quantitative evidence from power curve, operation data, log records and other sources; fuses the evidence and calculates the reliability of each fault root assumption through a confidence degree synthesis algorithm, and outputs a high confidence degree diagnosis conclusion; finally, a structured report containing abnormal information, diagnosis results, visualized evidence and operation and maintenance suggestions is automatically generated; the present application improves the operation and maintenance efficiency and reliability of the wind farm.