30results about How to "Resolve dependencies" patented technology

The invention discloses a time sequence generation method and system based on uncertainty quantization and frequency domain constraint, and belongs to the technical field of artificial intelligence and data mining. Outputting a mean value of the completion value and a variance representing the uncertainty of the completion result; an entropy weight adaptive mask generation mechanism is constructed, a soft mask matrix of continuous values is generated according to variance and local observation density, and high uncertainty corresponds to low mask weight; constructing a mixed loss function containing time domain weighted loss and frequency domain consistency loss; and training a diffusion model based on the soft mask matrix and a mixed loss function to generate a regularized high-fidelity time sequence. According to the method, the Bayesian uncertainty quantization and soft mask mechanism is introduced, so that the problems that a binary mask mechanism in the prior art is rigid and cannot sense completion errors are solved, and meanwhile, the periodic characteristics of generated data are ensured in combination with frequency domain constraints.

The present application relates to a method for extracting an acetabular facies lunata model, in particular to a method for extracting an acetabular facies lunata model based on mixed surface fitting, which solves the technical problem of low precision and robustness of the existing method for extracting an acetabular facies lunata model. The present application realizes rough extraction of the acetabular facies lunata model through spherical surface fitting, and then realizes accurate extraction of the acetabular facies lunata model in combination with ellipsoidal surface fitting, which combines the stability of spherical surface fitting and the anatomical fidelity of ellipsoidal surface fitting. In particular, in the case of complex pathologies such as hip dysplasia, the present application can still maintain high extraction accuracy, and improve the accuracy and reliability of clinical diagnosis and surgical planning. Meanwhile, in the iteration process of ellipsoidal surface fitting, an adaptive fault tolerance threshold is introduced, which effectively solves the problems of sensitivity to noise and strong parameter dependence of traditional methods, and has better robustness in processing complex acetabular morphology.

The utility model relates to the field of robot trolleys, and particularly provides a composite robot trolley. The trolley comprises a carriage, the top of the carriage is provided with the robot and a tray, the trolley is provided with an access cover, an access cover lock catch, pulleys, a console, a controller mounting frame, foot cups, supporting feet and pulleys, and the sliding access cover is opened and closed through one-hand operation of a magnetic lock catch. A closed cable management channel is formed by a cable fixing buckle on the inner side of the cover plate and the hollow cart grip, the equipment troubleshooting difficulty is lowered, an operator can complete state monitoring without changing the position when pushing the grip, meanwhile, through the matching structure of pulleys arranged at the four corners of the bottom and lifting foot cups, the safety of the operator is improved, and the safety of the operator is improved. Manual free pushing is achieved to adapt to a narrow space, stable parking can be achieved through rigid connection of the supporting feet and the anti-skid rubber pads after positioning, and the problem of track dependence of a traditional AGV is solved.

The utility model discloses a massage device of replaceable battery, include: massage device main part, the massage device main part one side embedded type installation changes the electricity box, sets up the battery in the electricity box, and the battery is detachable design, the utility model discloses a detachable battery design, supports double battery alternation and charges, realizes " one uses one fills " mode, improves the endurance time of massage device, thoroughly solves the pain point of equipment downtime during charging, also is convenient for the convenience of the repair problem of the maintenance problem of massage device battery problem, and the user can complete opening and closing only by pressing the box cover, and the auxiliary fixing of screw is combined, and the dismounting efficiency and structural stability are taken into account, avoid the tool dependence problem caused by traditional screw full fixation, the conductive plug and the electric socket adopt card type connection, cooperate the hole limit design, ensure the insertion accuracy, the contact resistance reduces, avoid the interface loosening caused by vibration simultaneously, and the power supply stability is obviously superior to the welding or ordinary insertion scheme.

The invention relates to an interrupt response time detection method and device, equipment, a medium and a program product. The interrupt response time detection method comprises the steps that in response to monitoring that a timer used for interrupt response time detection in an operating system is overtime, a detection program reads a first timestamp from character equipment in a kernel mode of the operating system and triggers the character equipment to send an event notification signal to the detection program, the detection program is a program used for detecting the interrupt response time in a user mode of the operating system, and the first timestamp is a timestamp when the operating system generates the current interrupt; in response to the received event notification signal, the detection program calls a callback interface corresponding to the event notification signal in a user mode in the operating system, and obtains a second timestamp from the callback interface, the second timestamp being a timestamp that the operating system starts to process the current interruption by using the callback interface; based on the first timestamp and the second timestamp, the detection program determines an interrupt response time for the current interrupt.

This application provides a real-time communication management method, apparatus, and device for industrial control networks, relating to the field of industrial control communication technology. A real-time communication management method for industrial control networks, applied to a management node in the industrial control network, includes: parsing preset configuration information and network structure information in the industrial control network to obtain a communication cycle; periodically sending real-time control messages to multiple slave nodes in the industrial control network based on the communication cycle; calculating the amount of non-real-time messages sent by each slave node according to the real-time control messages and the amount of non-real-time messages sent by the management node to each slave node; and sending and receiving non-real-time messages in the industrial control network based on the calculation results. According to embodiments of this application, the response speed of real-time messages and the transmission and processing speed of non-real-time messages are improved, thereby increasing network bandwidth utilization.

This invention discloses an offline navigation method and system based on plain text and local AI. The method parses the user-input text start and end point information using a local offline AI model, combines it with a pre-stored local text-based geographic knowledge base to perform path reasoning, and generates plain text walking steps. The system does not rely on GPS, BeiDou, or other satellite positioning signals or external networks; all calculations and data storage are completed locally on the terminal, and it can generate simulated GPS coordinates and visually assisted navigation. This invention is applicable to scenarios such as signal-free spaces, indoor environments, and visually impaired assistance, and features high privacy, strong stability, and a wide range of applications.

This utility model discloses an automatic inventory device and system for livestock RFID tags. The device includes a power supply unit, a main control chip, sensor devices, and a communication device. The power supply unit is connected to the main control chip and supplies power to the automatic inventory device. The main control chip is connected to the sensor devices, which identify livestock and transmit the identification results to the main control chip. The communication device is connected to the main control chip and includes an RFID read / write module and a 4G wireless terminal module. The RFID read / write module reads RFID ear tags from livestock and transmits the read RFID tag data to the main control chip. The 4G wireless terminal module transmits the data to a server. This utility model significantly reduces server load and network requirements, solving the problems of excessive reliance on servers and high network demands in existing technologies.

This application relates to a method, system, electronic device, and storage medium for early warning of acute mountain sickness. The method includes: collecting physiological data from a step test conducted on a subject at a target plain altitude; generating at least one physiological principal component based on the step test data; performing cluster analysis on the at least one physiological principal component to obtain risk classification clusters; obtaining the actual high-altitude Lake Louise score of the subject in each risk classification cluster and calculating the score interval proportion to determine the risk classification label; and providing an early warning of acute mountain sickness to the user based on the risk classification label. This solves the problems in related technologies, such as high dependence on specialized testing equipment and laboratories, time-consuming testing processes, inability to screen individuals before they enter high altitudes, difficulty in achieving non-invasive and simple screening, and inability to effectively determine the acute mountain sickness tolerance of new subjects, thus hindering personalized early warning and prevention.

The application discloses a knowledge-based temporal convolution neural network (KB-TGCN) blast furnace fault diagnosis method. The method can solve the space-time dependence and sample imbalance problem of the blast furnace ironmaking process. First, the calculated variables that can further reflect the process state are calculated by using the variables directly detected by the sensor. Then, the knowledge-based graph structure is constructed according to the spatial position and calculation relationship of the variables. Subsequently, a one-dimensional time information extraction module is embedded in the graph convolutional neural network. Therefore, the TGCN can capture time information while maintaining the original spatial relationship. By using the knowledge-based graph structure, the KB-TGCN can fully mine the spatial information of different blast furnace positions. In addition, the method uses a focal loss function with an adaptive balance factor instead of a traditional cross-entropy loss function to overcome the sample imbalance problem.

The utility model provides a kind of integrated stealth water column antenna, through the integration design of shell, water pump assembly, ground net plate and signal transmission component, significantly reduce antenna volume and promote stealth performance, shell columnar structure inlaying injection channel and isolation magnetic ring, realize the physical isolation of radio frequency signal and seawater, avoid the radar scattering problem caused by exposed metal parts of traditional shipborne antenna;Water pump assembly is directly connected with the lower side of shell, and forms radiator by injecting seawater, and after communication, pump can be stopped to realize antenna invisibility, signal transmission component and ground net plate are horizontally arranged on the upper end surface of shell, form compact plane layout, ground net plate arranged on the upper end surface of shell floats in sea level during use, only makes nozzle part above sea level, greatly enhances stealth performance, avoids the technical problem that water column antenna in the prior art is only applicable to ship platform use, use scene has great limitation, cannot meet the stealth demand.

The application provides a distribution difference measurement method and system based on convex peak estimation, and a medium, and belongs to the field of random measurement and statistical analysis. The method constructs a concave-convex self-weight measurement system based on simple four arithmetic operations, calculates the cumulative difference and cumulative similarity of each sample point to the whole sample, obtains a composite measured weight, and relativizes it into a concave self-weight and a convex self-weight, takes a convex self-weighted mean as a convex peak estimation, replaces a traditional arithmetic mean, and realizes unbiased measurement of the centralized position of the distribution. The convex self-weighted mean based on the convex peak and the square of the peak difference is used to construct a standard peak difference, to reconstruct the statistics and the variance analysis statistics, and to eliminate the dependence of these statistics on the homogeneity assumption of the variance by using a correction factor to quantify the difference of the three elements. The method does not require normality test and normalizing conversion, and is suitable for single sample test, two sample test, paired test, completely random design and random block design and other statistical scenes of sampling distribution with centralized position.

The utility model discloses a train container overturning and unloading device and method, and belongs to the field of train transportation. The container lifting device comprises a container lifting appliance used for lifting a container from a train carriage; overturning clamping arms are symmetrically mounted on the left side and the right side of the body; and the overturning clamp is used for clamping the container and driving the container to overturn, so that the materials in the container are cleaned and unloaded. The utility model aims to solve the problem that a gap between adjacent containers in a train carriage is extremely small, so that the containers need to be uniformly hoisted and transferred to a special track or an open space of hoisting equipment by using a special container sling to realize concentrated unloading. Aiming at the pain points that the distance between adjacent containers is extremely small and the unloading process is tedious in a railway transportation scene, the unloading efficiency and safety are remarkably improved through an innovative structural design and an operation method.

This invention relates to the field of power system control technology, and discloses a photovoltaic grid-connected flexible DC transmission and energy storage coordinated control system and method. The system includes: a system state perception module, which collects operating data to generate an original state vector; a digital twin and forward-looking risk assessment module, which calculates a forward-looking risk gradient vector based on real-time simulation of digital twins; a transient coordinated control module, which generates transient coordinated actions by fusing state and risk vectors through deep reinforcement learning and establishes an experience playback pool; an energy optimization management module, which establishes an economic power baseline using real options theory and dynamically corrects its model parameters using data from the experience playback pool; and a hierarchical coordinated instruction execution module, which integrates transient actions and the economic baseline and issues final control instructions. This invention uses digital twins and deep reinforcement learning for risk prediction and transient control, and uses real options theory to dynamically price flexibility, achieving coordinated optimization of system transient safety and economic operation.

The utility model belongs to the field of high-speed connector production, and discloses an automatic wafer and GND signal sheet assembling mechanism of a high-speed connector, which comprises an equipment large bottom plate and a TRAY disc, and further comprises a GND signal sheet stock bin mounted on the equipment large bottom plate, the TRAY disc is placed in the GND signal sheet stock bin, an in-stock-bin carrying mechanism is arranged below the GND signal sheet stock bin, and the GND signal sheet stock bin is arranged below the GND signal sheet stock bin. A GND signal sheet servo feeding mechanism is arranged behind the GND signal sheet stock bin, a GND signal sheet pre-positioning mechanism is arranged at one end of the GND signal sheet servo feeding mechanism, and an XZR three-axis servo assembling mechanism is arranged above the GND signal sheet rotation correction mechanism. According to the automatic assembling mechanism for the wafer and the GND signal sheet of the high-speed connector provided by the utility model, a full-automatic and self-adaptive assembling mechanism for the GND signal sheet and the wafer is provided, and the assembling process of automatic taking, automatic feeding, automatic assembling and self-adaptive intelligentization of the GND signal sheet is realized; a multi-axis servo linkage mechanism assembling mode and an intelligent electric control programmable driving program are matched with a precise mechanical structure to achieve product assembling.

The invention discloses a ballistic analysis method based on space-time rotation coding and dynamic mask reconstruction. The ballistic analysis method comprises the following steps: acquiring ballistic trajectory data observed by a radar; performing normalization processing on the ballistic trajectory data by adopting a split-axis normalization method, and mapping each trajectory point into a space-time Token sequence in a high-dimensional feature space; constructing a feature extraction network comprising a multi-layer space-time rotation attention mechanism; 2, performing mask processing on the space-time Token sequence generated in the step 1 by adopting a double-layer mask strategy, extracting feature representation through a space-time rotation Transform encoder, mapping back to an original physical space through a physical perception reconstruction task head, and optimizing model parameters based on a physical perception composite loss function to complete self-supervised pre-training; respectively setting corresponding lightweight task heads and loss functions for downstream trajectory prediction, missile classification or drop point prediction tasks based on the weight of the pre-training model, and splicing each task head with a space-time rotation Transformer encoder; and finishing model fine tuning of a specific task by training a task head. The precision and adaptability of ballistic analysis in a complex battlefield environment are improved.

The embodiment of the application relates to the field of power systems, and provides a power distribution network traveling wave fault positioning method and device based on an improved barrel theory optimization algorithm, computer equipment and a storage medium, the method comprising: determining a traveling wave energy attenuation matching item and a topological connectivity consistency item based on a basic physical relationship of traveling wave propagation of a target power distribution network to be positioned; constructing a double-dimension fused power distribution network optimization model conforming to traveling wave propagation characteristics and power distribution network topological constraints according to the traveling wave energy attenuation matching item and the topological connectivity consistency item; and solving the power distribution network optimization model based on the improved barrel theory optimization algorithm to obtain a power distribution network traveling wave fault positioning result associated with the target power distribution network. The implementation of the method improves the efficiency and accuracy of traveling wave fault positioning.

The application provides a plug-in dependency analysis and architecture extension method and system for a low-code platform, relates to the technical field of low-code platforms, and comprises the following steps: converting plug-in source code into an abstract syntax tree through static code analysis, extracting an interface contract and verifying compatibility; eliminating circular dependencies through dependency graph construction and topological sorting, determining a compatible version to generate a dependency relationship chain; calculating a minimum impact surface based on a plug-in call index table, constructing a function extension registration center and an interface directory, and realizing loose coupling calls between plug-ins. The application solves the plug-in dependency conflict problem and improves the platform extensibility and stability.

This invention relates to a comprehensive verification system based on data characteristics, comprising the following steps: (1) Data feature verification based on time series similarity, initially determining target users through a similarity measurement process, and ensuring that the minimum number of normal users undergo secondary verification, initially balancing the quantity gap between normal and abnormal samples during secondary verification; (2) Data feature verification system based on IPSO-PCSVM; (3) Simulation and analysis of examples. In the context of new energy big data, there are complex mutual influences between power grid behavior, user behavior, environmental demand, and demand-side resource operation. There are numerous mutual influencing factors and complex interactions. By analyzing the influence weights between interactive influencing factors and quantifying their effects, a comprehensive verification system for new energy operation data based on data characteristics is constructed, thereby providing a systematic analysis method for new energy big data analysis.

This invention belongs to the fields of medical image processing, hemodynamic simulation, and deep learning technology, and relates to a rapid prediction method for the flow field in type B aortic dissection. The method includes: acquiring CT image data of the type B aortic dissection to be analyzed; performing three-dimensional segmentation and reconstruction to obtain a geometric model of the aortic dissection, and dividing the data into grids; mapping the aortic dissection geometric model onto regular grid points to construct an input geometric function; inputting the input geometric function into a pre-trained operator network for forward computation to obtain the predicted blood flow field distribution, thus achieving rapid prediction. The operator network includes: a lifting layer for mapping the input geometric function to a high-dimensional feature space; a Fourier layer for extracting global and local features in the blood flow field; and a projection layer for projecting the feature vector output by the Fourier layer back to the target dimension to obtain the blood flow field function.

This invention provides a self-adhesive flexible ultrasonic patch, solving the problems of unstable probe fixation and poor adhesion in existing pipeline inspection methods. The patch includes a flexible ultrasonic transducer assembly, which is composed of an 8*16 unit array and a multi-layer composite structure consisting of a matching layer, a piezoelectric layer, a backing layer, and an encapsulation layer. The matching layer is a composite material of PDMS-doped graphene and tungsten powder; the piezoelectric layer is a PZT-5H piezoelectric column array; the backing layer is a magnetic sound-absorbing composite material of PDMS-doped tungsten powder, porous graphene, and neodymium iron boron nanoparticles; and the encapsulation layer is a pure PDMS integrated encapsulation. This invention integrates magnetic adsorption functionality into the backing layer, enabling rapid, non-destructive installation and stable contact between the patch and the pipeline. Utilizing a flexible multi-layer structure to adapt to pipeline curvature, it combines excellent surface adaptability with ultrasonic testing performance, making it suitable for wall thickness detection and long-term monitoring of metal pipelines. It is easy to install and highly stable.

The application discloses a kind of methods of no coding automation test software, belong to the technical field of automation testing, including execution flow chart drawing, node attribute configuration, edge attribute configuration, component configuration item test, flow configuration test, flow data test etc.Step.The application is verified by building constraint rule base with component type as index key to prepositive regular configuration item, and the mapping relationship of global unique identifier and execution method is established at edge and component level to reflect driving flow automatic operation, solve the problem of long development cycle and high labor cost caused by traditional software testing needs to write test script line by line;By setting data flow log containing input and output data snapshot at the end of each edge and component, and establishing the difference degree comparison and type consistency checking mechanism of upstream node output and current node input, the problem that traditional test log can only record as a whole and cannot locate specific node level data anomaly is solved.

The invention relates to an underwater target recognition method based on a Conformer model, and belongs to the technical field of underwater target recognition. According to the collected and processed data, constructing a model based on a conformer, and carrying out training; and inputting the data processed in the step 1 into the trained model based on the conformer to obtain a denoised clean underwater sound audio. According to the method, the conformer is applied to underwater acoustic target recognition, the global dependence modeling capability of the Transformer and the local structure capturing capability of convolution are fused, the problem of long-time dependence and local structure coexistence of underwater acoustic signals can be well solved, and therefore accurate target classification is achieved.

A device abnormal behavior tracing method, system, medium and product relate to the field of Internet of Things security. The method receives network data by monitoring the resident service process, dynamically updates the version identifier and generates the process shard node, so as to realize the logical isolation of the process state and establish the predecessor context association. At the same time, the cross-shard data dependency edge is generated based on the resource version mapping table. When the abnormal alarm is received, the priority reverse search is performed from the target process shard node by using the shard association and the cross-shard data dependency edge. The present application solves the problems of "state pollution" and "dependency explosion" caused by the existing full life cycle trace graph construction by cutting the long-running process into discrete logical units according to the business boundary, eliminates the interference of irrelevant historical business, and improves the accuracy of device abnormal behavior tracing.

The application discloses a front-end multi-developer independent running system and method, the development front end comprises several independent development platforms, any development platform runs a first service, and a first load balancing component corresponding to the first service; the background service end comprises a registration center, a gateway connected to the registration center, and a proxy server connected with the gateway; the first load balancing component is used for registering instance information corresponding to the first service to the registration center when the first service starts; the proxy server is used for forwarding network requests of any development platform to the gateway, the gateway is used for searching and confirming corresponding instance information in the registration center based on IP addresses and / or instance names in the received network requests; the registration center is also used for notifying the gateway and the proxy server to return instances corresponding to network requests to corresponding development platforms; automatic matching of multiple request addresses to the registration center is realized, and parallel development of multiple persons is realized.

The application discloses a kind of corridor in multi-person sit-up detection method based on vision, which is installed two cameras in the corridor between the same side wall interval, covers 12 test points, uses human key point detection technology to obtain tester head, crotch, knee, foot and other key point coordinates;Through calculating hook foot score, knee bending score, getting up score and lying down score four evaluation indexes, the action norm of tester is judged;System first extracts getting up interval, then searches lying down frame between adjacent getting up interval to form counting interval, and the proportion of hook foot and knee bending standard frame is counted in each counting interval, and when the proportion exceeds the set threshold value, it is determined as an effective sit-up;Finally, the number of sit-ups completed by the tester is obtained by accumulating all effective counting intervals.The application can realize simultaneous detection of multiple people, automatically judge the action norm, improve the detection efficiency and accuracy, and is suitable for sports testing, fitness training and other scenes.

The invention provides a laser radar extinction coefficient inversion method based on adaptive divergence constraint, and relates to the technical field of atmospheric remote sensing detection, and the method comprises the steps: constructing an inversion model; initializing a search interval of the extinction coefficient at the reference point; selecting a heuristic value of the current extinction coefficient, substituting the heuristic value into the inversion model, and judging a divergence state of the heuristic value based on a process integral state item; if in an over-divergence state, setting the tentative value as a search upper bound; if the search is in the non-divergent state, judging whether the search upper bound is defined or not: if so, setting the tentative value as the search lower bound; if not, increasing the heuristic value, and returning to substitute the heuristic value into the inversion model; judging whether the updated search interval width is smaller than a threshold value or not; if yes, calculating an extinction coefficient profile based on the heuristic value; and if not, updating the heuristic value, and then substituting the heuristic value into the inversion model. According to the method, the physical stability characteristic of forward numerical deduction is used as a constraint, and high-precision independent inversion is realized.

The invention relates to the technical field of medical data application, and discloses a doctor seeing amount prediction method and device, electronic equipment, a storage medium and a program product, and the method comprises the steps: obtaining historical doctor seeing amount sequence data of a target medical institution module; dividing the historical treatment amount sequence data into a plurality of local time sequence blocks to form a local time sequence block sequence; inputting the local time sequence block sequence into a feature extraction module to obtain block feature vectors corresponding to the local time sequence blocks, and forming a block feature vector sequence; the block feature vector sequence is input into an encoder, the encoder encodes the block feature vector sequence so as to capture the dependency relationship between the different local time sequence blocks in the global range, and depth feature representation is output; and inputting the depth feature representation into a prediction head, and decoding to generate a doctor seeing amount prediction value in a future time period. According to the invention, the accuracy of doctor seeing amount prediction can be improved.

The application discloses an end-to-end magnetic resonance brain image automatic reorientation method, which comprises the following steps: reading in a brain image to be processed, adjusting the brain image to a standard shape, normalizing an image array of the standard shape brain image, inputting the normalized image array into a deep learning model to obtain a pre-result, combining the pre-result and an affine matrix equivalent to the process of adjusting the brain image to the standard shape and normalizing the image array of the standard shape brain image, constructing a transformation matrix contained by the brain image and the standard shape brain image after being reoriented, and finally packaging and outputting the reoriented brain image and the standard shape brain image. The application utilizes the deep learning technology, predicts the transformation matrix contained by the brain image after being reoriented through the image array of the brain image, and directly reorients the brain image, so that the process is simple and efficient, and the problems of complex process or excessive dependence on templates in the existing brain image automatic reorientation method are effectively solved.

The application discloses an answer generation model training data acquisition method and an answer generation model training method, and relates to the technical field of computers. The answer generation model training data acquisition method comprises the following steps: acquiring a plurality of sample questions; acquiring an answer corresponding to a first sample question by using a first inference model, wherein the first sample question is one of the plurality of sample questions; determining the complexity identification of the first sample question based on the answer corresponding to the first sample question and a preset reference answer; determining a sample inference chain and a sample answer corresponding to the first sample question based on the complexity identification of the first sample question; and determining first sample data based on the first sample question, the complexity identification of the first sample question, the sample inference chain and the sample answer, and stopping the operation until sample data is acquired based on all sample questions. According to the application, training data with different inference chain lengths is determined based on the complexity of the questions.