22 results about "Process assessment" patented technology

The invention relates to the technical field of electronic technology education and teaching management, in particular to an electronic experiment process assessment method which comprises the following steps: 1, data preprocessing: continuously collecting experiment data of students, and forming a high-quality training data set through preprocessing; 2, student experiment operation behavior identification based on deep learning: carrying out classification and model training on the training data set according to operation behaviors, wherein the model training comprises an anomaly detection aspect and a behavior identification aspect; 3, circuit identification and simulation based on deep learning: utilizing a deep learning target detection algorithm and a multi-target tracking technology to realize real-time tracking and identification of the components taken by the students from the container, and converting connecting lines into a circuit diagram; and 4, establishing a scoring model. According to the invention, through real-time monitoring and evaluation of operation behaviors and experiment results of students in an electronic experiment, comprehensive and scientific assessment of the experiment process of the students is realized, and the teaching efficiency is improved.

The invention relates to a collaborative learning process evaluation and intervention system and method, and belongs to the technical field of artificial intelligence. The method comprises the following steps: acquiring multi-modal original data from an online collaboration environment in real time through a data acquisition module, performing timestamp synchronization, preprocessing and packaging, and generating a standardized synchronization event stream; a dynamic multilayer heterogeneous interaction graph is constructed or updated in real time based on the event flow through a graph construction module, wherein the graph comprises student nodes, concept nodes and workpiece nodes; carrying out snapshot analysis on the atlas through an analysis engine in a preset time window, and calculating and outputting a multi-dimensional social measurement index reflecting a collaboration process state; and continuously monitoring the index time sequence through an AI tutor intervention module, and when a predefined cooperation mode is detected, triggering a decision-making mechanism to generate an intervention action and feeding the intervention action back to the online cooperation environment. Therefore, real-time, objective and multi-modal evaluation of the collaborative learning process is realized, and accurate and timely intervention is carried out, so that the quality and effect of collaborative learning are improved.

The invention discloses a method and system for obtaining copper pipe welding parameters, and the method comprises the steps: obtaining a first length verification copper pipe with the same specification as a copper pipe required by actual welding, and dividing the verification copper pipe into a plurality of verification areas from the first to the Nth; executing a first verification step on the first area when the verification copper pipe is in a non-ventilation state; sequentially introducing protective gas into the verification copper pipe according to a preset flow gradient, and sequentially executing a second verification step on the S adjacent verification areas under different flows; oxidation information in the verification copper pipe is obtained, and a welding parameter comparison table of the current verification copper pipe is generated based on the oxidation information; and on the basis of the welding parameter comparison table, welding parameters of the current welded copper pipe are obtained. The method can effectively verify the internal protection effect of the copper pipe during copper pipe brazing under the conditions of various heating temperatures, heating time and gas flow, and is beneficial to certification and use of copper pipe induction brazing process evaluation.

The invention discloses an intelligent pediatric nursing teaching AI inquiry system and method based on a digital background, and relates to the crossing field of education informatization and artificial intelligence. The system comprises a front-end interaction module, a voice processing module, a teaching knowledge base module, an intelligent question and answer engine module, a teaching evaluation and feedback module, a background management module, a data analysis module and a virtual simulation operation linkage module, and the teaching knowledge base integrates on-duty competition certificates and traditional Chinese medicine pediatric characteristic knowledge and supports knowledge graph and vectorization retrieval; the intelligent question and answer engine adopts a retrieval enhancement generation technology and is combined with a standardized inquiry dialogue state machine to guarantee the answer accuracy. The method comprises the steps of case selection, multi-modal interaction, intelligent question and answer, process evaluation, virtual simulation linkage, adaptive recommendation and the like. According to the pediatric nursing teaching system, simulated inquiry training, refined process evaluation and teaching ecological closed-loop optimization are realized, the professionality, safety and individuation of pediatric nursing teaching are improved, and core ability cultivation of nursing talents is assisted.

The invention provides a homework supervision method and device, equipment and a storage medium, and the method comprises the steps: obtaining homework process data and homework result data of a user, and determining a homework correction result corresponding to the homework result data; based on the homework process data, the homework result data and the corresponding homework correction result, homework process evaluation and homework result evaluation are carried out; the homework evaluation result of the user is determined based on the process evaluation result and the achievement evaluation result obtained through homework process evaluation and homework achievement evaluation, homework process data, homework achievement data and a homework correction result are fused for evaluation, the one-sidedness problem that only the final correctness is concerned in a traditional scheme is solved, and the user experience is improved. The finally determined homework evaluation result can give consideration to the learning attitude and the learning effect, and the real learning state of the user can be reflected more comprehensively and objectively, so that an education basis with higher reference value is provided for teachers and parents, and accurate learning condition diagnosis and personalized tutoring can be realized.

The utility model discloses a pressure maintaining and blasting test tool for a cloth-sandwiched diaphragm, which integrates dual functions of pressure maintaining test and blasting test, not only can effectively discriminate early leakage or abnormal bumps caused by hidden defects such as uneven distribution of internal fibers, but also can accurately measure the ultimate blasting strength of the cloth-sandwiched diaphragm, and realizes comprehensive evaluation of product performance. By adopting a sealing mode of combining vacuum adsorption and a high-finish sealing ring, a soft and weak cloth clamping membrane can be uniformly, flatly and tightly attached without damage at the beginning of a test, stable and reliable initial sealing is formed, the problem of extrusion damage or untight sealing possibly caused by a traditional mechanical clamp is fundamentally solved, and the test efficiency is improved. A solid foundation is laid for the authenticity of a test result, and the accuracy of test pressure data and the reliability of pressure maintaining process evaluation are jointly guaranteed through the application of an inflation system integrated with a one-way valve and a high-precision monitoring instrument.

In an example embodiment, instead of sending the state of the UI picture as a whole to the LLM to generate or modify one or more values on the UI picture, an identifier and a data type of data on the UI picture are collected and sent to the LLM. The LLM is indicated to return a list of expressions defining what needs to do to meet the user cues. The list of process evaluation expressions is then invoked to actually manipulate the data content.

The invention discloses a transformer bushing replacement training device and method based on multi-mode perception and intelligent evaluation. According to the device, on the basis of a modularized entity training tool, a multi-mode sensing system and an intelligent evaluation system are innovatively integrated. The multi-modal sensing system concurrently collects multi-dimensional physical signals in the whole operation process through a deeply-integrated moment, sound vibration and vision sensing unit. The intelligent evaluation system utilizes a multi-source information fusion analysis algorithm to carry out dynamic comparison and deep correlation analysis on real-time sensing data and a standard process database, and a quantitative and accurate operation process conformity evaluation report is automatically generated. According to the method, the fundamental problems of subjective, lagging and incapability of quantification of process evaluation in traditional training are solved, the skill training is spanned from'result observation 'to'process intelligent diagnosis', and the objectivity, the accuracy and the efficiency of the training are remarkably improved.

The invention relates to an identification method and identification equipment for a medical scale, and aims at reducing the manual analysis step of a doctor, improving the data processing speed and efficiency and enhancing the protection for the privacy of a patient through character scanning identification and automatic processing evaluation of the scale. The check code verification is carried out on the evaluation scale, so that the recognition capability of the check code used for recognizing the validity of the evaluation scale on the evaluation scale is improved, the accuracy of character scanning and the validity of the evaluation scale are ensured, and particularly, the accuracy is enhanced when handwritten contents of a doctor are processed. The comprehensive evaluation tool based on the deep learning model can quickly integrate evaluation scale scores, clinical symptoms and other related indexes in real time, more comprehensive diagnosis support is provided, and the influence of human errors and subjective factors is reduced. The workload of hospitals in the aspects of data management and analysis is reduced through the automatic and electronic process, and hospital resources can be more effectively distributed to other important tasks.

The invention discloses an electric power operation violation identification method and system based on an AI large model, and belongs to the technical field of electric power safety detection. The method comprises the following steps: deploying existing detection equipment on a power operation site in a target area, acquiring behavior image parameters of operating personnel and real-time operation data of the equipment, and constructing an initial score of personal operation; according to the method, three dimensions of intermediate correction signals, environment evaluation and process evaluation are integrated, a complete report including a scoring result, violation types and time, equipment influence conditions and environment and process problem points is generated, personnel behavior management and control, equipment risk early warning, field environment adaptation and operation process specifications are integrated, and the method is high in practicability and high in practicability. The defect that a traditional scheme only focuses on the comprehensiveness of a single link is overcome, full-chain and multi-dimensional technical support is provided for power operation safety management, and the occurrence risks of personal injuries, equipment damage and large-area power outage accidents are practically reduced.

This invention relates to the field of environmental risk assessment, specifically to an artificial intelligence-based multidimensional dynamic weighted soil ecological risk assessment system. This system is a full-process soil ecological risk assessment platform, comprising modules for data management, screening value calculation, risk assessment, and risk characterization. The data management module acquires pollutant concentrations and toxicity parameters; the screening value calculation module calculates ecological screening values ​​using either the species sensitivity distribution method or the assessment factor method; the risk assessment module is divided into two stages: the first stage compares concentrations with screening values, and the second stage conducts a detailed assessment using the quotient method, probability method, or evidence weight method when risks exist; finally, the risk characterization module generates a risk distribution map, displaying the risk values ​​of points or areas. This constructs a complete risk assessment process from initial screening to detailed assessment, realizing a full-process assessment of soil ecological risk, and the assessment results can directly support subsequent site management decisions.

The invention discloses a training method and rewarding method for a reasoning process evaluation model, and the method comprises the steps: generating a plurality of reasoning contents tau for a given problem x through a large reasoning model, enabling each reasoning content tau to have a plurality of reasoning steps a, carrying out the marking of the correctness of each reasoning step a, and carrying out the rewarding of the reasoning content tau. Obtaining a plurality of data sets with correctness labels in the inference step a; and performing scoring training on each generated step a for a plurality of set problems x through a constructed correctness label in a reference data set with an expected evaluation function by utilizing a reasoning large model. According to the technology, the problem of complex information redundancy in the process inference model is effectively relieved by constructing the state evaluation function and the contrast loss function, meanwhile, modeling is conducted through the context dependency relationship between the steps, the distinguishing capacity of the process reward model for the correct steps and the wrong steps is improved, and the accuracy of the process reward model is improved. Therefore, the accuracy of a large model reasoning result is improved.

This invention relates to the field of intelligent manufacturing technology and discloses an intelligent manufacturing quality inspection method and system based on artificial intelligence, including: S1, performing quality inspection on continuously produced products; S2, generating a single-piece quality state to characterize the quality features of the individual product; S3, organizing multiple single-piece quality states according to manufacturing sequence information or time information; S4, constraining the continuity of the single-piece quality states in the time dimension; S5, based on a multi-level quality state expression structure; and S6, outputting the process quality state. By constructing a multi-level quality state expression structure containing a single-piece quality state layer and a process quality state layer, and introducing a process evaluation constraint mechanism based on time continuity in the process quality state construction and judgment process, the manufacturing process quality inspection is expanded from discrete single-piece judgment to overall quality state judgment of a continuous production process, thereby improving the ability to characterize quality changes in the manufacturing process.

The application discloses a kind of simulated interactive quality evaluation systems and methods of intravenous infusion, it is related to medical teaching equipment technical field.The simulated interactive quality evaluation system of intravenous infusion includes: exhaust process evaluation module, puncture process evaluation module and drip speed adjustment module.The application carries out exhaust operation accuracy evaluation by the exhaust data obtained, simultaneously based on exhaust operation accuracy degree judges whether completion exhaust operation, if yes, then based on puncture operation accuracy degree judges whether completion puncture operation, if yes, then based on the drip speed adjustment parameter obtained carries out drip speed adjustment, judges whether completion drip speed adjustment, to realize the drip speed adjustment efficiency of simulated intravenous infusion exhaust and puncture interactive quality evaluation process in process, solve the drip speed adjustment efficiency not high in simulated intravenous infusion exhaust and puncture interactive quality evaluation process in prior art.

The invention relates to the technical field of block chain application, in particular to a financial practical training process assessment and credit authentication system and method based on a block chain, and the system comprises a process data collection and evidence storage module, a decentralized credit asset generation module, a conditional privacy sharing and verification module and a block chain network. The method comprises the following steps: collecting and processing training process data of a user on a financial training platform; generating a verifiable voucher containing a capability assertion set based on the data, and writing voucher integrity information into the block chain; conditional privacy verification is provided to a verifier through selective disclosure or zero knowledge proof under user authorization. According to the invention, the truth and credibility of the training data and the credit voucher are ensured by using the tampering resistance of the block chain, user privacy protection and information minimum disclosure are realized through a cryptographic technology, and the problems of insufficient credibility, data islands and privacy disclosure existing in a traditional centralized authentication mode are solved.

The invention relates to a welding parameter determining method and device and a computer readable storage medium, and relates to the technical field of engineering manufacturing. The method comprises the following steps: receiving a first process evaluation element input by a user; retrieving a first target process assessment matched with the first process assessment element in a process assessment database, wherein the process assessment database is established based on the process assessment element contained in each process assessment in the plurality of verified process assessments and an execution standard referenced by each process assessment; in response to the first target process assessment retrieved in the process assessment database, determining the welding parameters in the first target process assessment as target welding parameters; and in response to the fact that the first target process assessment is not retrieved in the process assessment database, determining target welding parameters by utilizing the process knowledge graph based on the first process assessment elements.

The invention relates to a capability appreciation evaluation method and device, computer equipment, a readable storage medium and a program product. The method comprises the following steps: estimating an initial capability vector of each testee through a constructed capability model and a test database; in the culture process, testing the testee based on a new test item to obtain process evaluation data; adjusting the dynamic difficulty of each testee through a dynamic item parameter model; updating the ability model of the testee, and re-determining the ability vector of the testee in each dimension; based on the terminal point capability vector, predicting the capability of the testee through a prediction model to obtain a predicted capability, and determining an appreciation score of the testee; and analyzing the average value-added value of the whole culture group, analyzing the culture links based on the average value-added value, and outputting a culture suggestion report. Therefore, the influence of the individual initial capability difference can be stripped, and the three-dimensional real growth values on different capability dimensions under the intervention of specific culture can be accurately quantified.

The present invention discloses a bonding construction process assessment method, device, equipment and computer-readable storage medium, which are applied to the field of equipment manufacturing technology, comprising: obtaining basic bonding information and process parameters of each bonding element to be assessed based on the bonding process to be assessed; determining the detection method corresponding to the bonding element to be assessed based on a pre-established correspondence between the assessment element combination and the detection method; for each bonding element to be assessed, using the detection method corresponding to the bonding element to be assessed to detect the sample to obtain the detection result; the sample is made based on the process parameters of the relevant bonding element to be assessed; based on the detection result corresponding to each bonding element to be assessed, a bonding process assessment of the bonding process to be assessed is generated; thereby completing the bonding process assessment. The present invention can achieve standardization of bonding process assessment, effectively avoid the problem of missing items or duplication, and improve the accuracy and completeness of the assessment.

The present invention provides a congenital heart disease process assessment method and system based on ultrasound data, which obtains a dynamic checklist of the target detection personnel corresponding to the detection time, and retrieves the attribute information of the target detection personnel, and generates an initial time series diagnosis tree based on the attribute information and the dynamic checklist; retrieves the ultrasound data intercepted by the physician end, obtains the annotation information and the interception time of the ultrasound data, and fills the corresponding ultrasound data into the dynamic checklist corresponding to the inspection node in the initial time series diagnosis tree based on the annotation information and the interception time to obtain the ultrasound time series diagnosis tree; determines the abnormal items in the ultrasound time series diagnosis tree, and splices the dynamic checklists in the ultrasound time series diagnosis tree based on the abnormal items to obtain an abnormal sequence list corresponding to the abnormal items; generates a heart prediction change map based on the trend prediction strategy and the ultrasound data in the abnormal sequence list and sends it to the detection end.

Systems, computer program products, and methods are described herein for resource distribution process assessments using advanced computational models for data analysis and automated processing. The present disclosure is configured to receive a request to generate a resource distribution document from a borrower, the resource distribution document comprising a transfer of a plurality of resources from a lender to the borrower. Further, the present disclosure may analyze borrower metadata associated with the borrower comprising credit history, market trends, and collateral quality. Further, the present disclosure may generate a borrower capacity, analyze a regulation database, and generate the resource distribution document. Additionally, or alternatively, the resource distribution document may be generated and stored on a blockchain. Further, the present disclosure may generate a smart contract comprising terms associated with the resource distribution document and transfer, based on execution of the smart contract, the plurality of resources from the lender to the borrower.

The application provides a preset model fine-tuning method, a preset model-based question and answer method and equipment, and relates to the technical field of artificial intelligence. The fine-tuning method comprises: rewriting a sample question by using a preset model to obtain a retrieval question; retrieving based on the retrieval question to obtain a retrieval result for the retrieval question; reflecting the retrieval result by using the preset model to obtain a reflection result for the retrieval result; generating an answer to the sample question based on the retrieval result by using the preset model in the case where the reflection result represents that the retrieval result meets a predetermined answer generation condition; evaluating the retrieval result and the answer respectively to obtain a process evaluation score for the retrieval result and a result evaluation score for the answer; and fine-tuning parameters of the preset model based on a training sample obtained from the sample question, the answer, the retrieval result, the process evaluation score and the result evaluation score.

The invention relates to a robot welding forming method, device and equipment, a medium and a product, and relates to the technical field of welding forming. On the premise that the assembly quality requirement is met, the influence factors influencing curved surface segmented rib plate welding seam forming are analyzed, the single curved surface segmented rib plate robot welding forming process is evaluated, the welding forming process is obtained, the welding forming stability of the robot is guaranteed through control over the welding posture and the welding gun angle, and the welding efficiency is improved.