14results about How to "Improve completion efficiency" patented technology

The invention provides an optical cable design intelligent drawing system and method based on fusion of multi-source acquisition data. Through combination of the large model processing layer and the core function layer, automatic analysis, association and compliance detection of the multi-source collection data are realized, the work of manually completing verification and compliance detection of the multi-source collection data in the prior art is replaced, and the manual workload is greatly reduced, so that the multi-source collection data verification and compliance detection can be realized in a complex scene, and the multi-source collection data verification and compliance detection efficiency is improved. Automatic processing can be completed based on the combination of the large model processing layer and the core function layer of the system, and the technical effect of improving the completion efficiency and precision is generated due to the reduction of the manual workload.

The invention relates to a container control method and electronic equipment. The container comprises a movable mechanical arm, and a visual assembly and an end effector located at the tail end of the mechanical arm are arranged on the mechanical arm. The container control method comprises the steps that in response to an obtained handover instruction for target goods, the photographing pose of a mechanical arm is calibrated according to a target handover position indicated by the handover instruction, a target photographing pose is obtained, and after the mechanical arm is controlled to move to the target photographing pose, a first image of a first position identifier is collected through a visual assembly; and according to the first image, the mechanical arm is controlled to execute handover operation on the target goods through the end effector. According to the method, the photographing pose of the mechanical arm is automatically calibrated based on the target handover position, the mechanical arm collects the image of the visual recognition beacon through the photographing pose calibrated in real time, the accuracy of the image used for space visual positioning is higher, and therefore the mechanical arm can be more accurately controlled to execute handover operation.

The embodiment of the invention provides a causal path completion method and device, equipment and a storage medium, and relates to the technical field of network security. In response to the path completion instruction, acquiring a path breaking point from the causal path, and determining a context data packet according to the path breaking point; performing large language model reasoning on the context data packet based on a vector database to obtain verification plan data of the candidate path, and arranging the verification plan data according to the verification platform information to obtain an instruction sequence containing at least one atomic action instruction; performing verification on the instruction sequence to obtain a verification result corresponding to each atomic action instruction; and performing decision judgment on the candidate path according to the verification plan data and the verification result to obtain a judgment result, and complementing the causal path based on the judgment result. The whole process from fracture point positioning, candidate path reasoning to verification completion is automatic, the processing efficiency is effectively improved, and the accuracy and credibility of a completion result are guaranteed.

This invention relates to a method and system for optimizing meal replacement intake time based on circadian rhythms, belonging to the field of nutrition management technology. It includes: collecting basic user information, sleep time, and wake-up time; determining a sleep-wake cycle based on sleep and wake-up times; retrieving user age and gender based on the basic information and dividing the sleep-wake cycle into physiological time periods; retrieving health goals and physical fitness parameters based on the basic information to determine the types of meal replacement foods; determining the initial time for meal replacement intake based on physiological time periods and selecting recommended food types; determining a type-based intake adjustment value based on the recommended food types; adjusting the initial time for meal replacement intake based on the type-based intake adjustment value to obtain a recommended meal replacement intake time and outputting it. This invention improves the efficiency of users in achieving their health goals during nutrition management.

The application discloses a target detection method and a related device, which can quickly complete a target detection task, improve the completion efficiency of the target detection task, and further improve user experience. The method of the application comprises the following steps: when target detection needs to be performed on a target image, the target image containing an object to be detected is acquired first, and then the target image is input into a target model. Next, the target model performs feature extraction on the target image, thereby obtaining first features of the target image. Then, the target model encodes the first features of the target image, thereby obtaining second features of the target image. Subsequently, the target model decodes the second features of the target image based on a preset query vector, thereby obtaining third features of the target image. Finally, the target model acquires a detection result of the target image based on the third features, and the detection result can be used to determine position information of the object and a category of the object. Thus, the target detection on the target model is completed.

The invention discloses an engineering innovation practical ability cultivation method and system based on a domestic EDA platform and AI-PBL, and belongs to the field of engineering education and intelligent teaching. A domestic EDA tool is taken as an engineering practice carrier, real engineering problems and subject competition tasks are taken as driving, and a stepped progressive project system driven by an ability matrix is constructed, so that the engineering innovation practical ability is cultivated. And systematic fusion of professional knowledge learning, engineering practice training and innovative design capability cultivation is realized. In the implementation process, an artificial intelligence technology is introduced to carry out intelligent support, design assistance, debugging analysis and engineering practice behavior data processing on the learning process, and the engineering practice ability, team cooperation ability and innovative design ability of students are comprehensively evaluated based on a multi-dimensional ability evaluation index system. According to the method, the problems of course content splitting, discontinuous ability cultivation chain and single evaluation mode in existing EDA practical teaching are solved, and the engineering practice task implementation efficiency and ability evaluation consistency are improved.

The application relates to a smart factory robot scheduling method and system, a terminal and a storage medium, and relates to the technical field of smart factories. The method comprises the following steps: receiving a task instruction from a production management system, and adding the task instruction to a task pool; obtaining running state information of robots in the smart factory; selecting at least one task instruction from the task pool, and filtering candidate robots for executing the task instruction and generating a candidate robot set according to a matching relationship between a task type of the task instruction and a robot state; calculating a task completion time of a to-be-scheduled task for the to-be-scheduled task; comparing and analyzing each candidate robot in the candidate robot set based on the task completion time, and determining a target robot for executing the to-be-scheduled task; and distributing the to-be-scheduled task to a task queue of the target robot. The application has the effect of improving the problem of low task completion efficiency caused by unreasonable robot scheduling.

The invention belongs to the technical field of sea temperature complementation, and particularly relates to a sea temperature complementation method and system based on space-time prior and a flow matching generation model. The method comprises the following steps: inputting sea surface temperature SST data, weekly mean value SST data and a mask for four continuous days of the sea surface, carrying out rough completion of space-time residual learning, introducing a lightweight 3D-CNN space-time residual learning mechanism, obtaining a rough completion graph, and explicitly modeling a space-time evolution rule of sea temperature data; then, introducing a conditional flow matching generation strategy based on optimal transmission into the repair of a total image generated by conditional flow matching, and carrying out refined reconstruction on the roughly completed image to obtain a complete sea surface temperature image; a curved and random Markov chain sampling path in a traditional denoising diffusion probability model DDPM is replaced, the problem that the reasoning efficiency is low due to dependence on hundreds of steps of random denoising is solved, and efficient reasoning under the condition of few steps is achieved.

This application relates to the field of cable testing technology, and in particular to a method, apparatus, computer device, and storage medium for missing data completion. The method includes: acquiring initial temperature data of the target cable at each sampling time within a target sampling period; determining missing temperature data in the initial temperature data, and the missing sampling time corresponding to the missing temperature data; constructing a spline interpolation function corresponding to the target sampling period based on the initial temperature data at each sampling time within the target sampling period; and completing the missing temperature data using the spline interpolation function. This application can effectively complete missing data.

The application provides a text completion method and device, electronic equipment and computer storage medium, the method is applied to the computer technical field, the method comprises the following steps: obtaining a target text input by a user, matching the target text by using a first prefix tree to obtain a first matching result; determining whether the number of recommended texts matched with the target text in the first prefix tree is less than a preset number according to the first matching result, and obtaining a second matching result according to a target classification model in the case of determining yes; merging the first matching result and the second matching result to obtain a merged result, and completing the target text according to the merged result. In this way, the efficiency and accuracy of text completion can be improved.

This invention provides an indoor unit control method, device, and air conditioner. The method includes: determining a target rotation speed based on the current coil temperature; controlling the indoor unit to adjust its rotation speed based on the target rotation speed, so that the indoor unit can continuously operate at the adjusted rotation speed for a first preset time; if it is determined that the next coil temperature is in a first range, controlling the indoor unit to reduce the fan speed based on the adjusted rotation speed; if it is determined that the next coil temperature is in a second range, controlling the indoor unit to increase the fan speed based on the adjusted rotation speed. The indoor unit control method, device, and air conditioner provided by this invention analyze the system pressure value based on the coil temperature and adjust the indoor unit's fan speed accordingly, so that the coil temperature under high-temperature self-cleaning mode is always maintained within the normal temperature range, ensuring that the outlet air temperature is stable at 56°C, improving the efficiency of high-temperature self-cleaning, and avoiding shutdown caused by sudden increases or decreases in system pressure due to unilaterally maintaining the outlet air temperature by adjusting the frequency.

The present application belongs to the technical field of machine vision, and relates to product surface defect detection, and is a kind of all-around defect detection method and system for valve oil seal industrial defects. The method comprises the following steps: collecting a top view image of the valve oil seal, obtaining lip radius and lower spring seat radius data from the front end interface, and positioning and detecting the lip rubber head and the lower spring seat; collecting a side view image of the valve oil seal, obtaining metal skeleton height and lip height data from the front end interface, and positioning and detecting the metal skeleton, lip bottom edge and compression spring; collecting a bottom view image of the valve oil seal, positioning and detecting the lower spring seat; and integrating the obtained detection information to determine qualified products and unqualified products. The present application has the ability to detect different types of valve oil seals, the detection system has good compatibility, the algorithm has good robustness, and meets the quality inspection requirements.

The application provides a multi-dimensional risk information visualization method and system based on cognitive load optimization, and relates to the technical field of data visualization. It includes: social risk multi-dimensional data attribute analysis and classification; calculating the perception efficiency coefficient of each channel; fusing scene prior, data-driven and user-defined three-source signal to calculate information importance weight, and combining dimension complexity to construct cognitive load function; under the constraint of channel mutual exclusion, the optimal mapping configuration of data attribute to visual channel is solved with the goal of minimizing total cognitive load; the current task type of the user is identified, the view importance weight is calculated, and after stability control processing, the screen space is dynamically optimized and allocated through a nonlinear allocation algorithm; finally, a multi-view linkage interface is rendered and presented. Through the perception efficiency driven visual encoding optimization and task driven layout dynamic adaptation, the cognitive load of the management personnel is significantly reduced, and the risk judgment efficiency and system usability are improved.

The invention relates to the technical field of Internet of Things node positioning, and discloses an Internet of Things positioning data completion method, which comprises the following steps: acquiring a distance matrix of partial observation between nodes; extracting observation distances from each node to all other nodes to form a one-dimensional distance sequence, and converting the one-dimensional distance sequence into a Hankel matrix through a sliding window; constructing a three-dimensional Euclidean distance observation tensor, namely, an observation EDT tensor; establishing a joint optimization model based on structured prior and deep low-rank prior to obtain a complete EDT tensor; solving the joint optimization model by adopting an alternating direction multiplier method framework based on Plug-and-Play, and iteratively updating and outputting a complete EDT tensor; the complete Euclidean distance matrix is inversely converted into the complete Euclidean distance matrix for node positioning of the Internet of Things, and the method aims at improving the data recovery precision and robustness under the condition that the distance measurement information is seriously lost.