32results about How to "Comprehensive" patented technology

The invention discloses an intelligent monitoring and evaluating method and system for terrestrial carbon disturbance in a permafrost region, and belongs to the field of carbon cycle research in the permafrost region. The method comprises the following steps: collecting 13 background element data in a permafrost region; calculating to obtain a permafrost region carbon disturbance evaluation index; carrying out credibility evaluation on the permafrost region carbon disturbance evaluation indexes; monitoring regional background elements and river particle organic carbon output characteristics and changes of the permafrost region, and calculating a change rate of a carbon disturbance evaluation index according to monitoring data; using a numerical model to identify a carbon disturbance high-risk area and time period of the permafrost region, and identifying key disturbance factors and influences; and analyzing the change trend of the carbon disturbance evaluation index, and establishing a prediction model by using a machine learning method. The method has the advantages of comprehensiveness, dynamics, effectiveness and support for carbon disturbance attribution and predictive analysis.

The invention discloses a recommendation method and system for reversely matching sales products by using a density clustering algorithm, and belongs to the technical field of information processing. The method comprises the following steps: acquiring a historical cluster; obtaining customer information; performing recommendation matching according to the historical cluster and the customer information to obtain a recommendation result; and screening out recommended sales products from the recommendation result. According to multi-dimensional static and dynamic information sets such as comprehensive information of customers, existing assets of the customers and real-time retrieval condition information of the customers, target sales products needed by the customers are calculated and analyzed in real time. The method has the advantages that static past historical information of the customer user and real-time actual needs of the current session are considered, comprehensiveness is high, real needs of the customer can be met as much as possible, customer satisfaction is achieved, customer experience can be improved for a long time, customer stickiness is improved, and the long-term goals of cost reduction and efficiency improvement of an operator are achieved.

The invention discloses strength detection equipment for a special-shaped precast concrete component, which belongs to the technical field of building material detection and structurally comprises a suspension seat, a lifting frame, an L-shaped clamping arm and an edge strength detection rod. The suspension seat is connected to the lower side of a sliding table at the bottom of the portal frame, and L-shaped clamping arms are movably installed on the two sides of the lifting frame respectively. The end part of the clamping and supporting head is fixedly connected with a bearing rod, and the edge strength detection rod is detachably and fixedly mounted at the end part of the bearing rod; at least two cross-shaped strength detection rods are arranged below the suspension seat; the special-shaped concrete prefabricated component strength detection device can perform strength detection on the edge, the upper side of the bottom and the inner side of the side wall of the special-shaped concrete prefabricated component to verify whether irregular defects exist in the special-shaped concrete prefabricated component or not, is wide in detection range and high in comprehensiveness, controls the special-shaped concrete prefabricated component to perform multi-direction large-amplitude oscillation in space on the basis, and improves the detection accuracy. Various irregular vibrations possibly suffered in the construction environment are simulated, and whether the vibration meets the use requirements or not is verified.

The invention relates to the technical field of medical images, in particular to a nervous system medical image case database construction system based on artificial intelligence, which comprises a nervous system medical image database module, a teaching interactive learning platform module, a user self-test module and a user online examination module. The teaching system truly restores a diagnosis report written in a clinical working environment of a doctor, organically combines book knowledge with clinical practice, can arouse the learning enthusiasm and initiative of imaging medical students and living training users aiming at complex nervous system medical imaging teaching, improves the teaching quality and practical skills, and improves the teaching efficiency. The learning effect is fed back in real time through the computer, rapid fusion of theoretical knowledge and clinical practice is promoted, accurate lesson preparation of teachers is facilitated, a flexible and convenient education mode and an accurate and individualized training mode are achieved, the training process of image resident physicians is accelerated, the teaching efficiency and quality are improved, and the system adapts to a modern teaching mode.

The invention discloses an intelligent arrangement and verification method and system for a monthly plan of a distribution network, relates to the technical field of distribution network maintenance, and solves the problems that mutual exclusion in all maintenance requirements is difficult to comprehensively consider and constraints in various aspects involved in the maintenance requirements cannot be comprehensively considered in the prior art. According to the method, the constraint condition in the formulation process of the monthly distribution network plan is set, the constraint condition is quantified into the violation degree of the constraint based on the penalty coefficient and the indicator function, the minimization of the violation degree of the constraint is taken as a target function, and the monthly distribution network plan with the minimization of the violation degree of the constraint is solved by using the simulated annealing algorithm. According to the method, conflicts with the monthly plan of the main network, repeated power failure constraints, guaranteed power supply constraints, window period constraints, accompanying stop and simultaneous stop constraints, power supply switching mutual exclusion constraints, holiday and festival constraints, operation risk constraints and important user / sensitive user constraints are considered in constraint conditions, so that the finally obtained monthly plan of the distribution network can well avoid the constraints; and then an optimal power failure maintenance scheme under each constraint is obtained.

The utility model provides a drainage pipe video detection robot, which relates to the technical field of drainage management and comprises a bottom plate, a base is fixedly connected to the edge, close to one side, of the top of the bottom plate, a first through hole is formed in one side of the base, and a rotating shaft is rotatably connected to the interior of the first through hole. The outer surface of the rotating shaft is fixedly sleeved with a connecting block, a sliding groove is formed in the top of the connecting block, a contraction block is slidably connected into the sliding groove, and a matched connection block is fixedly connected to the top of the contraction block. The utility model solves the problems that the device cannot be widely used due to the facts that the conventional drainage detection is generally carried out on part of drainage near a drainage port and the effect of the conventional drainage detection is very one-piece, and the effective detection effect of the device is inconvenient, the conventional method is clumsy and not applicable, and the use cost of the device is low. And the use effect of the device is reduced.

The invention relates to underground space'prevention-breaking-installation 'integrated intelligent emergency equipment and an application method, and the equipment comprises a walking and deployable device, a sensing module and an intelligent control module which are arranged in the walking and deployable device, and a breaking device and an installation device which are arranged at the top of the walking and deployable device. The forcible entry device and the mounting device are arranged adjacently; the method comprises the following steps: 1, deploying and starting; 2, sensing and evaluating; 3, performing three-dimensional reconstruction; 4, decision making and planning; 5, executing first-aid repair; 6, monitoring and adjusting in real time; 7, finishing operation and withdrawing; according to the invention, forcible entry, installation and monitoring are integrated, the whole process of emergency repair can be covered, various conditions after an underground space disaster can be effectively handled, data can be automatically collected and analyzed, three-dimensional reconstruction and decision optimization can be carried out, and dependence on manpower is reduced. Many tasks such as forcible entry, supporting, monitoring and repairing are executed, and meanwhile real-time risk assessment and intelligent early warning are achieved.

The invention belongs to the technical field of medical data information processing, and discloses a human nutrient element deficiency risk intelligent prediction method based on conventional test data, comprising the following steps: acquiring basic personal information and conventional test data of a subject; performing data cleaning on the acquired data information; the individual nutrition status is comprehensively evaluated, and risk labels of nutrient element deficiency are marked in a standardized mode; training a human nutrient element deficiency risk prediction model; determining an optimal threshold value of the human nutrient element deficiency risk prediction model; and evaluating the feasibility of human nutrient element deficiency risk prediction based on conventional test data. By adopting the human nutrient element deficiency risk intelligent prediction method based on the conventional inspection data, the capability of identifying the human nutrient element deficiency risk is comprehensively improved, the detection cost is reduced, the detection time is shortened, dynamic monitoring and immediate feedback of the nutrition status are realized, and the human nutrient element deficiency risk intelligent prediction method is suitable for popularization and application. The method has the characteristics of comprehensiveness, high efficiency, accuracy and real-time dynamic monitoring.

The application discloses a brain glioma segmentation and three-dimensional visualization model training method and system based on multi-modal fusion, and comprises the following steps: inputting multi-modal medical image data into a Laplacian pyramid multi-modal fusion learning model to generate a fusion graph, then inputting the fusion graph into a U-net segmentation model comprising an encoder and a decoder to obtain a segmentation mask under the multi-modal fusion graph; and finally, based on the multi-modal fusion graph and the segmentation mask, adopting a Marching cubes (MC) algorithm to perform three-dimensional reconstruction visualization of brain regions and brain tumor region labeling. The brain glioma segmentation and three-dimensional visualization model training method and system based on multi-modal fusion provided by the application optimizes the disadvantages of insufficient information and incomplete modeling under single modal, fully utilizes the advantages of the completeness of multi-modal data, performs multi-modal fusion, segmentation and three-dimensional visualization, can more comprehensively assist surgeons in treatment, and improves the accuracy in the operation process.

The application discloses an AFS, ARS and DYC cooperative control method of a distributed electric drive vehicle based on DDPG. The method utilizes a cooperative control method and a deep reinforcement learning method, designs and develops a vehicle stability control method based on a centroid side slip angle and a yaw angular velocity, takes driving signals provided by a driver and measured or estimated vehicle state information as input, and judges the stability of the vehicle. When the active safety system needs to intervene, a DDPG-AAD model trained offline by a strategy deep gradient algorithm is used to coordinately control AFS, ARS and DYC systems, precise and independent control of each wheel is realized, and thus the active safety driving stability of the vehicle is improved.

This utility model relates to the field of communication equipment technology and discloses an emergency communication device for tunnels. The device includes a communication unit with an internal loudspeaker. A sliding groove is formed inside the fixing plate, and a slider is slidably connected inside the groove. A buckle and a limiting ring are engaged. This utility model enables normal communication by fixing an interface to the bottom of the communication unit. During the connection process between the interface and the connecting cable, loosening may occur. In this case, because the buckle is engaged with the bottom of the limiting ring, the spring provides elastic force, and the slider is pushed by the telescopic rod towards the communication unit. Simultaneously, because the buckle and slider are fixedly connected, the sliding action between the slider and the groove keeps the limiting ring constantly pushed to fit against the interface, preventing loosening of the interface and the connecting cable.

The invention provides a natural ecosystem investigation method. The natural ecosystem investigation method comprises the following steps: S1, acquiring a high-resolution remote sensing image and DEM data, and dividing ecosystem types; s2, typical ecological problems of the ecological system are determined, sample plot design and sample plot dynamic arrangement are carried out, investigation points are arranged in a sample plot, and sampling analysis is carried out; and S3, performing data analysis according to the plaque partition map, the sample plot location map and the remote sensing image map. According to the dynamic survey method combining quadrat / transect and sampling point actual ground survey, the mutual verification of ground, remote sensing and model data is realized by combining a satellite remote sensing and model simulation technology with multiple data sources, typical / important ecological problem partitions in a watershed ecosystem range are found out and verified, and a watershed ecological system is established. Support is provided for design and implementation of the ecological engineering project, and a data index basis is provided for acceptance of the ecological engineering project.

The present application relates to a VR motion training teaching method and system based on motion capture technology, which comprises the following steps: when a training instruction is received, identifying its motion type; matching a virtual sub-scene based on the identified motion type, and obtaining teaching and training information; collecting and comparing the motion sensor data of the target object; when abnormal comparison data is identified, identifying its abnormal type; identifying the continuous motion data associated with the abnormal comparison data; providing teaching and training feedback to the user end based on the teaching audio and video data, the abnormal comparison data, and the continuous motion data; the present application distinguishes different motion types, and matches the corresponding virtual sub-scenes and teaching and training information, and at the same time, based on the current abnormal data combined with the continuous motion data for analysis, not only points out the specific errors in the user's motion, but also analyzes and feeds back the causes of the errors in the connection of the continuous motions, which helps the user to fully understand the problems existing in their own motions and make targeted improvements.

The application discloses a multi-parameter fusion and intelligent perception electrocardio health evaluation method and system, relates to the technical field of electrocardio health evaluation, and has the technical scheme as follows: based on the electrocardio function imbalance data of a target evaluation object, a comprehensive electrocardio evaluation path of at least two different types of evaluation dimensions is dynamically generated; if the initial evaluation coefficient indicates that the electrocardio health evaluation has deviation, a feedback evaluation path is dynamically generated based on the type of the abnormal evaluation path segment, and the actual feedback evaluation path of the target evaluation object when performing the evaluation task along the feedback evaluation path is collected; the feedback evaluation coefficient is obtained by comparing the actual feedback evaluation path with the feedback evaluation path; the comprehensive evaluation coefficient is obtained according to the initial evaluation coefficient and the feedback evaluation coefficient, the electrocardio health risk grade of the target evaluation object is output according to the comprehensive evaluation coefficient, and the accuracy and reliability of the evaluation result are improved.

The application is suitable for the field of bioinformatics and molecular diagnosis technology, and provides a TP53 gene heterozygous deletion and copy number variation detection method based on targeted sequencing. Through core technical innovations such as customized probe design, dynamic reference set correction, improved HMM model and KDE bimodal judgment, the application realizes the synchronous and accurate detection of TP53 gene LOH / CNV and mutation. Compared with traditional detection technology, the application effectively solves the problems of CN-LOH missed detection and insufficient integrated analysis of mutations and structural variations, and the coincidence rate with whole exon sequencing reaches 100%. The method has the outstanding advantages of high sensitivity, high specificity, rapid efficiency and controllable cost, can accurately determine the TP53 multiple hit state, and provides reliable molecular diagnosis basis for risk stratification, prognosis evaluation and individualized treatment decision of AML / MDS and other myeloid tumor patients, and is more suitable for clinical routine popularization and application.

The application relates to the technical field of disaster prevention and control, and discloses an underground pipe network gas disaster early warning and prevention and control method and system based on end-cloud cooperation, which comprises the following steps: constructing a monitoring matching score and a leakage posterior probability of a candidate leakage source space unit; generating a benchmark concentration sequence of the candidate leakage source space unit under a ventilation-only scenario by using a benchmark concentration model; screening a difference concentration sequence with leakage gas as a leakage concentration sequence, and identifying a monitoring time when the leakage gas appears in the leakage concentration sequence; constructing a leakage gas existence probability function, generating a leakage gas existence probability of each candidate leakage source space unit, dividing a dangerous area according to the leakage gas existence probability, and screening an optimal repair entrance in combination with a pipe network topological structure. The application realizes quantitative evaluation of leakage risk and accurate deduction of a ventilation benchmark, improves the leakage identification accuracy, weakens environmental interference, and forms an automatic and high-precision underground pipe network gas disaster early warning and prevention and control process.

The present application relates to a kind of impact dynamic performance test and evaluation method of composite structure of cement-based material of ballastless track, belong to the field of cement-based material performance test.Test sample is layered or embedded composite structure of cement-based material.A certain quality drop hammer is repeatedly dropped from high, drop hammer gravity potential energy is absorbed by sample, and dynamic impact damage is generated to sample.High-definition camera shoots the surface topography of sample after each impact, and the computer program calculated is used to calculate the lateral deformation size of sample, the number and total area of upper surface crack and interfacial separation crack.Innovatively, cumulative drop hammer impact energy, impact expansion coefficient, lateral deformation size, the number and total area of upper surface crack and interfacial separation crack are used to evaluate the impact dynamic performance of composite structure, with the advantages of being able to restore ballastless track entity structure, high intelligent degree, high evaluation index precision and strong comprehensiveness, suitable for high-speed rail ballastless track structure impact dynamic performance evaluation.

The invention relates to the technical field of fuse protection cover detection, and discloses a defect detection method and system for a drop-out fuse protection cover, and the method comprises the steps: obtaining a protection cover image, and obtaining defect features; classifying the defect features into structural defects and surface defects; calculating a structure defect index; comparing the structure defect with a historical structure defect to obtain a structure deterioration index, and judging the grade of the structure defect according to the structure defect index and the structure deterioration index; obtaining pollution characteristics, obtaining pollution characteristic change conditions in a preset time period, obtaining pollution indexes according to the pollution characteristic change conditions, and determining pollution grades according to the pollution indexes; and obtaining a defect degradation grade, and carrying out maintenance early warning. According to the invention, full-process intelligent detection of the drop-out fuse protection cover from image acquisition, feature recognition, defect classification, defect quantification to early warning output is realized.

This invention discloses a temperature and humidity monitoring system for a lithography machine, comprising: a BLG file pre-reading module for reading BLG files generated by the lithography machine, wherein the BLG file includes equipment operating status data and environmental parameter data in binary format based on IEEE 754 floating-point encoding, and the environmental parameter data includes temperature and humidity; the BLG file pre-reading module is also used to decode each data in the BLG file based on the IEEE 754 floating-point encoding standard to obtain decoded data; and a database preprocessing module for preprocessing the decoded data and converting it into structured temperature and humidity data, writing the structured temperature and humidity data into a database, and storing it in the database by category according to temperature and humidity. This invention also discloses a method for monitoring the temperature and humidity of a lithography machine. This invention enables the real-time reading of temperature and humidity data of the lithography machine, thereby achieving monitoring of the machine's condition, improving efficiency, increasing data backup capacity, and enabling analysis of historical data.

This application relates to the field of component analysis technology, specifically a crack resistance analysis method and system based on load factors and environmental factors. The method includes: acquiring historical load data and historical temperature data of the object to be analyzed, wherein the historical load data and historical temperature data are acquired in a simulation model; establishing a load-temperature coupled field model based on the historical load data and historical temperature data; inputting the load-temperature coupled field model into a crack resistance prediction model to obtain crack resistance analysis results, specifically including: obtaining corresponding second variable values ​​based on changes in first variable values ​​in the load-temperature coupled field model; obtaining corresponding first variable values ​​based on changes in second variable values ​​in the load-temperature coupled field model; constructing a variable dataset based on the acquired multiple first variable values ​​and multiple second variable values; and inputting the variable dataset into the crack resistance prediction model to obtain crack resistance analysis results.

The utility model provides a testing device of a laser radar lens. The laser radar lens is a transmitting end lens or a receiving end lens. The test device comprises a light source configured to emit test light to the laser radar lens; the reference plane is fixedly arranged relative to the laser radar lens and is used for calibrating the position of a light-emitting surface or a light-sensing surface corresponding to the laser radar lens; the imaging module is configured to at least move to a first set position and a second set position along the optical axis of the laser radar lens; the first set position is the position when the imaging module images the test light focused by the laser radar lens, and the second set position is the position when the imaging module images the reference plane; the position detection module is configured to obtain coordinates of a first set position and a second set position. Thus, through the testing device provided by the embodiment of the invention, common testing of the defocusing amount and the focal length of the laser radar lens can be effectively realized, and the hardware cost and the process cost are reduced.

The present invention proposes a psychological state assessment method based on feature extraction, which relates to the fields of mental health and deep learning. The method comprehensively collects individual physiological indicators, behavioral data and language usage characteristics, uses principal component analysis to extract main dynamic features, and constructs a psychological state assessment model based on machine learning; the model can receive the physiological indicators, behavioral data and language usage characteristics of the person to be assessed as input, and output the corresponding psychological state and its confidence; by regularly evaluating the model performance and adjusting and optimizing it, it is ensured that the model accuracy continues to meet the standards. The present invention can improve the real-time, accuracy and intelligence level of psychological state assessment, and provide a new monitoring and early warning method for the field of mental health.

The invention relates to the technical field of feeding and discharging forming equipment, and discloses automatic feeding and discharging forming equipment for rubber products, the automatic feeding and discharging forming equipment comprises a processing main body, and further comprises a second sliding limiting rod, a discharging assembly and a forming assembly, the back of the processing main body is fixedly connected with a connecting supporting plate, and an equipment control panel is arranged in the processing main body; the front face of the machining body is fixedly connected with a feeding supporting plate, the interior of the feeding supporting plate is rotationally connected with an oil film winding roller, a cutting knife is arranged in the machining body, a forming base table is arranged at the top of a connecting supporting plate, and the discharging assembly is arranged in the machining body. A second spring is arranged to push a second limiting ring outside a second sliding limiting rod to enable a movable supporting block on the second sliding limiting rod to extrude downwards, and the movable supporting block extrudes to drive a second transmission roller to extrude and limit a rubber raw material outside a first transmission roller, so that the processing is more comprehensive; and the rubber product processing efficiency is improved.

The application discloses a kind of development adjusted reservoir engineering research whole-process informatization method, comprising: collecting reservoir static, production, test, monitoring, test data;Divide research and analysis object, carry out data splitting and classification;Automatic process visualization index;Man-machine interactive data iteration verification, and improve data and analysis index;Data export is converted and format conversion;Man-machine interactive scheme deployment optimization.The application can optimize the interactive relationship between reservoir engineering comprehensive researchers and programmatic platform software, form the optimization method of reservoir engineering comprehensive research quality and efficiency, and greatly improve the whole-process work efficiency of development adjusted reservoir engineering research.

This invention provides a method and system for evaluating the heterogeneity of deep massive carbonate reservoirs. The method selects reservoirs in the mid-to-late development stage and delineates target evaluation layers based on sedimentary cycle information; selects strata with physical properties meeting set requirements as tight layers; comprehensively considers different reservoir types, pore structure characteristics, and dynamic / static requirements to determine evaluation parameter types and decide on target index parameters; uses the entropy weight method to determine the weights of target index parameters, calculates a comprehensive heterogeneity evaluation index, draws a heterogeneity distribution map, and formulates heterogeneity grading standards based on the inflection points of the cumulative curves in the distribution map; and constructs a planar heterogeneity distribution visualization model combined with a reservoir geological model. This approach overcomes the shortcomings of existing technologies, such as incomplete parameter consideration, limited applicability, and insufficient accuracy, achieving high-quality evaluation of the heterogeneity of deep massive carbonate reservoirs based on reasonable investment and multi-scale parameters.

The invention provides a carbon value accounting method, system and device of a wind and light storage virtual power plant and a storage medium, and belongs to the technical field of carbon emission, and the carbon value accounting method comprises the steps: selecting an index for calculating the carbon value of the wind and light storage virtual power plant; collecting original data corresponding to the indexes; preprocessing the original data to obtain processed original data; constructing a carbon value accounting model; and inputting the processed original data into the carbon value accounting model to obtain a carbon value accounting result. According to the method, the blank of related research of the current wind and light storage virtual power plant is filled, the carbon value generated during operation of the wind and light storage virtual power plant is checked instead of optimized scheduling, and the carbon value generated by the wind and light storage virtual power plant can be calculated according to the carbon value checking model; therefore, compared with the research only aiming at the economic dispatching of the virtual power plant in the past, the carbon value of the virtual power plant can be more intuitively measured and calculated, and the method is more comprehensive.

The invention relates to the technical field of mining engineering, environmental geotechnical engineering and water and soil conservation, and particularly discloses a coal mining subsidence area water and soil loss similar simulation device and experimental method.The coal mining subsidence area water and soil loss similar simulation device comprises a support and an experimental box, the experimental box is installed on the support, an experimental soil body is arranged in the experimental box, and a subsidence crack simulation system is arranged in the experimental soil body; the top of the experiment box is matched with a rainfall system; the subsidence fracture simulation system comprises a middle box body arranged in the middle of the experiment box, the middle box body is embedded in an experiment soil body of the experiment box, an experiment soil body is also arranged in the middle box body, and one or more fracture plates are embedded in the middle box body in a matched mode. The method can physically reproduce a complete erosion path of'surface runoff collection-fracture preferential flow-lateral matrix infiltration 'of the subsidence area, and accurately quantify the effect of the fracture in acceleration of water and soil loss.

This invention discloses a performance testing system for an air energy storage heat exchange module, comprising a saturated humidification / salting subsystem, a cooling fluid subsystem, a heat storage fluid subsystem, a DCS control subsystem, and a second heat storage fluid subsystem. Stable high-pressure air, generated by a drive motor, air compressor, and high-pressure storage tank, enters the saturated humidification / salting subsystem for humidification / salting, then enters the second heater / first cooler for heating / cooling. Afterward, it enters the heat exchange device under test and exchanges heat with the hot fluids in the heat storage fluid subsystem and the second heat storage fluid subsystem. The cooling fluid subsystem provides a cold source for the first cooler. The high-pressure air after heat exchange passes through a third cooler and a silencer before being discharged into the atmosphere. This invention can conduct tests on the flow heat transfer performance and cycle stability of heat exchange devices under different operating parameters, and features high versatility, a wide operating range, good stability, and strong comprehensiveness.

The invention relates to an intersection overflow state recognition method, system and device based on radar data and a medium, and the method comprises the steps: obtaining the position information of an entrance stop line through radar software or a trajectory analysis radar, and introducing a map and / or trajectory analysis to calibrate the exit overflow detection range of each entrance of a target intersection; screening track points in an outlet overflow detection range to obtain a track point set; solving at least one state evaluation index based on the track point set; determining an outlet overflow state by comparing the state evaluation index with a preset state threshold value; and if it is determined that exit overflow occurs, determining existence and ending of an exit overflow event of the target intersection according to the collected continuous overflow times and continuous non-overflow times. According to the invention, through accurate space calibration, efficient data processing, scientific state evaluation and comprehensive event determination, the problem that the overflow identification capability of the existing radar trajectory technology in a complex and changeable urban traffic environment is limited is effectively solved.