3302results about "Electrical appliances" patented technology

A transformer-based student performance prediction and reasoning intervention is disclosed. The system comprises a data repository coupled to a transformer-based prediction module that processes student data through multi-head attention mechanisms to generate performance predictions and identify potential learning shortfalls. A reasoning-enhanced large language model algorithmically generates personalized corrective action plans by applying structured decomposition of learning challenges, multi-step reasoning, and hypothesis testing. An algorithmic prompt formulation system optimizes inputs using field-specific, level-specific, and shortfall-specific templates. The system implements a workflow including shortfall detection against educational thresholds, causal factor analysis, intervention generation, and adaptive refinement based on outcomes. This approach enables early identification of academic challenges and timely implementation of personalized interventions to improve student learning outcomes.

The invention relates to the technical field of artificial intelligence education, in particular to an intelligent homework tutoring system and method based on multi-modal interaction and adaptive learning, and the system comprises a multi-modal input analysis module, a cognitive state dynamic evaluation module, an intelligent decision explanation engine, and a learning effect visualization closed-loop module. The method has the beneficial effects that a three-dimensional adaptive system of explanation granularity-presentation form-interaction frequency is used, and teaching strategies such as visual derivation, concept metaphor and the like can be automatically matched according to cognitive styles of students. Secondly, a'backtracking reinforcement-lateral expansion 'double-intervention mechanism is innovatively used, and the recurrence rate of similar errors is effectively reduced through error real-time detection and correlation knowledge contrast teaching. And finally, constructing a dynamic knowledge graph and an interactive learning report, realizing visual tracking of a learning path, and helping students to establish a systematic knowledge framework.

A computer-implemented method is disclosed for transforming academic test performance into personalized feedback and learning recommendations. The method involves presenting an academic test to a user via a user interface of an online learning platform and receiving the user's submitted answers. The system accesses input parameters including historical user-performance data, correct answers, and coaching session data. The user's responses are compared with the correct answers to identify incorrect responses. A prompt generator creates a prompt to guide and constrain an AI engine in analyzing the test responses. The AI engine correlates the incorrect responses with historical performance data and coaching session information to detect learning patterns or recurring errors. Based on the identified patterns, the system generates personalized feedback and targeted learning recommendations to address specific learning gaps. The method enables adaptive, AI-assisted post-assessment guidance, improving learning outcomes through individualized support.

The invention discloses a road roller construction quality real-time monitoring system based on digital twinning, and relates to the technical field of road roller construction intelligent monitoring, and the road roller construction quality real-time monitoring system comprises a data acquisition module which uses a multi-modal fusion sensor network and edge calculation to comprehensively acquire and preprocess data; the digital twinborn model building module is used for modeling by combining physical-data dual drive with geological characteristics; the data transmission module is used for ensuring efficient and safe transmission by using a software defined network and a block chain; the real-time monitoring and analysis module is used for carrying out multi-scale space-time correlation analysis and generating virtual data; and the decision support module fuses deep reinforcement learning and a knowledge graph, supports man-machine cooperation decision, and provides intelligent suggestions for construction. According to the invention, the advantages are obvious, multi-modal acquisition and edge calculation ensure accurate and real-time data, a dual-drive model truly simulates construction, an advanced transmission technology ensures data safety, multi-scale analysis comprehensively evaluates quality, full-process coverage improves construction quality and management intelligence, and cost reduction and efficiency improvement are realized.

The invention discloses a writing brush calligraphy practice correction system based on real-time handwriting analysis. The system comprises a sensing layer used for collecting handwriting tracks, physiological signals, environmental parameters and ink mark characteristics; the edge calculation layer is used for executing noise filtering, coordinate system normalization, multi-modal data alignment and feature primary extraction through an Apache Kafka data pipeline; and the algorithm analysis layer is used for carrying out super-long calligraphy stroke sequence modeling by adopting an S4 architecture time sequence model, introducing a Neural ODE module for modeling, capturing dynamic characteristics in a continuous pen wielding process, constructing a multi-physics-field coupled PINN framework, constraining neural network prediction through a physical loss function, deploying a dual-stage characteristic extractor to extract high-order characteristics, and extracting the high-order characteristics. Book style features are extracted, and the current practicing book of the user is classified in real time; the intelligent correction layer is used for generating a dynamic correction suggestion, constructing a personalized learning path, realizing self-adaptive scoring and providing aesthetic dimension feedback at the same time; and the user interaction layer is used for providing an AR correction interface.

The invention relates to the technical field of test question generation, in particular to an intelligent test question generation method and system based on learning behavior analysis. The method comprises the following steps: acquiring interactive behavior data and score data of learners in a user online learning platform in real time; inputting the interactive behavior data and the score data into a pre-trained knowledge state analysis model to generate a user knowledge state matrix; based on the knowledge state matrix and in combination with a preset teaching target library, identifying a target knowledge point set which needs to be strengthened currently and a corresponding cognitive training type; according to the target knowledge point set needing to be strengthened and the corresponding cognitive training type, a test question element combination algorithm is called, question stems, interference items and question solving path prompts are dynamically assembled, and personalized test questions are generated. The method has the advantages that full-closed-loop intelligent teaching from behavior analysis of the user to targeted training is achieved, and personalized test questions adaptive to individual cognitive vulnerabilities are dynamically generated.

The invention relates to a teacher personalized correction method and system based on a generative algorithm, and relates to the technical field of homework correction, and the method comprises the steps: collecting correction preference information and historical correction data of a teacher; based on the correction preference information and the historical correction data, generating a personalized correction model through machine learning; receiving a homework file uploaded by a teacher end, preprocessing the homework file and extracting key information; according to a generative algorithm and the key information, obtaining a homework score evaluation criterion; homework data uploaded by the student terminal is received; performing correction operation on the homework data according to a generative algorithm, a personalized correction model and a homework score judgment standard to obtain a homework score and a personalized suggestion; and pushing the homework score and the personalized suggestion to the student terminal and the teacher terminal. The method has the effects of improving homework correction efficiency and teaching quality and promoting personalized development of students.

A publishing system with components, including:a system configured to receive at least one document including text that defines a base alphabet in one or more formats;a system configured to provide additional data for a reader to better understand the document which includes:a method of encoding or marking up non-phonetic words in the document to enable the reader to decode sounds of each non-phonetic word; anda system configured to output an encoded document with the text and the additional data in one or more formats,wherein the method of automatically encoding the non-phonetic words to make the encoded words phonetic:for at least one character (“spelling character”) in the non-phonetic word, using a compound character that includes the spelling character and a sound character, wherein the sound characters:are human-readable characters in the base alphabet and / or in one or more secondary alphabets,are added to the spelling characters to indicate that each spelling character makes the usual sound of the sound character,are added so that spelling characters can be visually discriminated from sound characters,are added such that a reader can recognize the non-phonetic word by sight because the spelling of the word is unchanged, andare added to the spelling characters such that the spelling characters and the sound characters remain human-readable such that the spelling character and the sound character of each compound character are within one visual field; andautomatically outputting the encoded words in a human-readable form / format such that the compound characters in the encoded word visually indicate which of the spelling characters have a sound other than their usual sound and what sound each character makes in the non-phonetic word when it does not make its usual sound.

A smart busy board is provided utilizing a technology driven timer which can be set to predetermined time intervals for each of a plurality of interactive components disposed on the smart busy board. The timer mechanism and some of the interactive components are connected to electrical elements hidden within the interior housing of the smart busy board. Each of the interactive components engage the infant or toddler with some type of sensory output, such as movement, sound, light, and touch for a predetermined time interval. The busy board is designed to stimulate frontal lobe and cognitive development and improve motor skills.

Processing circuitry of a learning platform may be configured to maintain a graph database describing student learners. Processing circuitry may obtain new student learner data and load the data into the graph database. Processing circuitry may receive an engagement or interaction from the new student learner and responsively extract new learnings about the new student learner which are loaded into the graph database. Processing circuitry may receive an inquiry from the new student learner and in response, extract the new student learner data and the new learnings from the graph database and contextualize, using a large language model, a learning unit from the educational content provided by the learning platform as a response to the inquiry using the new student learner data and the new learnings. Processing circuitry may further return the learning unit contextualized by the large language model to the new student learner.

Aspects of embodiments pertain to a method for determining an Input / Output (I / O) device configuration for a music teaching system. The method may comprise receiving a plurality of I / O device configurations of a music teaching system; receiving, for a given I / O device of the music teaching system, an initial I / O device configuration; and determining an updated I / O device configuration for the given I / O Device, based on the initial I / O device configuration of the given I / O Device and at least one of the plurality of received I / O device configurations. The determining is performed such that the updated I / O device configuration has improved device performance compared to the initial I / O device configuration.

The invention provides an anesthesia virtual simulation training system fusing knowledge, skills and a thinking closed loop. The anesthesia virtual simulation training system comprises a medical knowledge base module, a clinical thinking module, a skill training module, an examination question brushing module, a knowledge graph module and an intelligent platform bottom layer framework. The intelligent platform underlying architecture comprises a data middle platform, an AI engine and a 3D engine, collects student behavior data of each module, constructs a dynamic student ability portrait through a gradient boosting tree algorithm and a collaborative filtering recommendation model, analyzes knowledge blind areas and skill shortages, plans a personalized learning path and pushes targeted training content, and provides a personalized learning result. A closed-loop process of evaluation, learning, practice and re-evaluation is formed; and deep fusion of theoretical knowledge, clinical thinking and skill operation is realized through a cross-module collaboration mechanism. The problems that traditional anesthesia teaching is high in practical operation risk, scattered in resource and insufficient in individuation are solved, and the clinical comprehensive ability and teaching quality of anesthetists are effectively improved.

The invention relates to the technical field of auxiliary training, and discloses an AR auxiliary training system for improving the diagnosis and treatment capability of general practitioners on undifferentiated diseases, and an immersive training environment is constructed by adopting an augmented reality technology. The system comprises an environment sensing module, a space positioning module, a case data module, a virtual rendering module, an interactive acquisition module, an intelligent response module, a state control module and an evaluation calculation module. The environment sensing module adopts an RGB-D camera and an inertial measurement unit to collect environment and head movement data of a user; the spatial positioning module determines a virtual patient placement position based on an SLAM algorithm; the virtual rendering module renders a three-dimensional virtual patient in a real environment; the interaction acquisition module supports voice and gesture multi-mode interaction; the intelligent response module generates an intelligent patient answer; the evaluation calculation module carries out comprehensive evaluation from three dimensions. The invention provides a highly immersive and intelligent training environment, and has the advantages of low cost, reusability and high standardization degree.

The invention discloses a personalized teaching content generation method and system based on a digital portrait, and the method comprises the steps: collecting the multi-dimensional learning data of a student in real time, analyzing the data keyword of the student, constructing the portrait of the student, generating a teaching target based on the portrait of the student, and enabling the teaching target to comprise a teaching theme, exercises related to the theme, and knowledge points related to the theme. Converting the teaching target into an executable instruction of a large language model through a structured prompt engineering technology; the large language model generates initial teaching content according to the teaching instruction; verifying and optimizing the generated initial teaching content to ensure that the generated teaching content conforms to a teaching target and can adapt to the current cognitive level and learning requirements of students; and outputting the verified and optimized teaching content to the students and automatically adapting to the content presentation form according to the learning style preference of the students.

The invention discloses a whole-process vascular interventional operation training method and system based on a virtual reality technology, and the method comprises the steps: firstly, developing a vascular interventional mechanics and collision simulation module, and achieving the deformation simulation of a blood vessel and a guide wire through the combination of position dynamics, a region shape matching technology and a Cosseerat elastic rod model, the collision between the blood vessel and the guide wire is treated by adopting a wide-to-narrow three-layer progressive collision detection method; secondly, constructing an immersive virtual operation scene through model construction and rendering optimization; visual angle roaming, instrument operation and interface interaction are fused, and multi-mode interaction control driving intervention training is achieved; finally, based on a'module-event 'dual-drive framework, operation tasks such as anesthesia, puncture, radiography, intervention, stent release and hemostasis are sequentially connected in series through a unified state machine, and whole-process training is achieved. The accuracy and stability of blood vessel and guide wire simulation are improved, the training immersion sense is enhanced, interventional operation whole-process training is achieved, and high teaching and practical value is achieved.

The invention provides a power equipment three-dimensional dynamic updating method and system for virtual reality training, and the method comprises the steps: collecting the working state data of power equipment in real time through a sensor; processing the working state data based on a preset function model, and calculating the physical state change of the power equipment; according to the physical state change, adjusting physical attributes of the three-dimensional model of the power equipment in real time so as to simulate physical effects of thermal expansion, stress concentration or structural deformation; loading the adjusted three-dimensional model into a virtual reality environment, and performing real-time display through a virtual reality rendering platform; and after the user executes the interactive operation through the virtual reality equipment, the working state of the power equipment is updated, and the influence of the operation on the three-dimensional model of the equipment is dynamically fed back, so that a virtual-real linkage closed-loop training process is formed. The virtual model can change in real time along with the collected data, and the technical verisimilitude and operability of virtual training are remarkably improved.

The invention discloses an intelligent education robot question answering system based on voice recognition and a knowledge graph, and particularly relates to the technical field of artificial intelligence. The method comprises the following steps: performing feature extraction on a user voice signal to obtain a text sequence and a multi-modal context feature; recognizing subject domain judgment and question answering intentions based on supervised classification and keyword rule fusion, and outputting a subject domain prior probability and a question answering target vector; determining polysemy words in the text sequence by using a context window, generating a semantic item sequence and semantic item confidence, constructing a subject domain sub-graph based on a subject domain prior probability, and obtaining a candidate reasoning path and a path scoring vector; determining a target teaching concept and an optimal reasoning path by combining Bayesian inference and consistency verification; generating a personalized question answering result aiming at the question asked by the user through fact retrieval and knowledge derivation in combination with the question answering target vector; accurate and efficient intelligent teaching question answering can be realized, and question answering accuracy and intelligent interaction capability of the education robot are effectively improved.

The invention discloses a family education auxiliary method and interaction system based on an intelligent agent mode, and belongs to the technical field of data processing, and the method specifically comprises the steps: obtaining the multi-source data of family education, building an intelligent agent model of cross-dimension situation perception capability based on the multi-source data, and enabling the intelligent agent model to carry out the multi-dimension situation perception capability according to the evolution trend of three-dimensional association, the intelligent agent model automatically deduces the appearing negative education situation, when a risk node is predicted, an education intervention scheme is generated, the education intervention scheme comprises a learning task and a real-time prompt for a parent communication mode, and in the execution process of the education intervention scheme, the intelligent agent model carries out different levels of task pushing on students and parents at the same time, so that the education intervention effect is improved. The student side obtains learning tasks, the parent side obtains interactive guidance, cooperative auxiliary optimization is carried out on family education, learning progress and parent-child communication can be promoted in the same education process, and it is ensured that the education process has dynamic adaptability and systematic management ability.

The invention relates to the technical field of artificial intelligence education, in particular to a Russian spoken language practice personalized recommendation method and system based on artificial intelligence, and the method comprises the steps: 1, outputting a phoneme sequence with a timestamp through Russian automatic voice recognition; 2, collecting an exercise interruption position and repeated read-after behavior data; 3, generating a dynamic learner portrait; 4, mapping high-frequency errors in the learner portrait into abnormal path weights of map nodes; 5, a lattice tail error option and a non-matching body verb interference item are injected; 6, when the voice fluency attenuation of the learner exceeds a dynamic threshold value, the sentence complexity is reduced; and 7, calculating an error rate descent gradient based on the exercise completion data, and dynamically adjusting the abnormal path weight of the knowledge graph. Through audio stream analysis and syntax tree construction, the system can accurately identify errors of the learner in grammar, pronunciation and other aspects, and the learning efficiency is improved.

In one embodiment, a system receives a set of coaching items including a number of questions each associated with an expected answer; connects to a coaching session including one or more participants and a virtual coaching agent; for each question and for at least a subset of the participants: transmitting the question, by the virtual coaching agent, to the client device used by the participant; receiving an answer to the question by the participant, the answer including media of the participant; receiving text of utterances spoken by the participant during the answer; generating one or more evaluation scores for the answer based on evaluating at least the content of the answer to the question; and transmitting an overall evaluation score for each of the subset of participants based on the generated evaluation scores for that participant.

The invention provides a student course learning evaluation method and device and electronic equipment, and relates to the technical field of education informatization. The method comprises the following steps: acquiring reply data of questions asked by a student in a learning process of a target course; performing feature extraction on the answer content to obtain answer content features and semantic category labels; standard answers corresponding to the questions are extracted according to the knowledge graph, and candidate answer features are generated; selecting a corresponding target answer feature according to the semantic category label; calculating the semantic similarity of the answer content features and the target answer features, and determining whether the answer content is correct or not according to the semantic similarity and a similarity threshold value; counting the number of correct answer contents, and calculating the answer accuracy; and according to the answer correct rate and the answer state, determining a knowledge mastering score of the student for the target course, and according to the knowledge mastering score and a score threshold, determining a mastering degree of the student for the target course. According to the invention, the accuracy of student course mastering degree evaluation can be improved.

The invention relates to the technical field of information, and discloses an intelligent adaptive education training system based on big data, and the system comprises a data collection and integration module which is used for collecting learning behavior data and physiological data of learners from a plurality of education platforms and physiological data sources; the dynamic student portrait generation module is used for automatically generating and updating a dynamic student portrait according to the learning behavior data and the physiological data collected by the data acquisition and integration module; the personalized feedback and learning path optimization module is used for generating personalized learning feedback according to the dynamic student portrait and automatically adjusting a learning path by utilizing a multi-objective optimization algorithm; the system implementation and optimization module is used for detecting operation of the data acquisition and integration module, the dynamic student portrait generation module and the personalized feedback and learning path optimization module for integration, testing and optimization; and the data acquisition and integration module comprises a multi-source data integration unit.

The invention provides a digital twinborn medical education training method and system. The method comprises the following steps: generating case information and scoring rules of AI digital patients based on clinical real cases; constructing a physical training environment which comprises a training model, an environment construction object and an operation sensing device; creating a digital training environment mapped with the physical training environment in real time, wherein the digital training environment comprises an AI digital dummy and an interactive operation process; responding to operation input of the trainee in the physical training environment or the digital training environment; through a server synchronization engine, real-time bidirectional interaction between entity operation of the physical training environment and virtual operation of the digital training environment is realized; and dynamically collecting cross-environment operation data, and generating a clinical ability evaluation report based on case information and scoring rules. The method has the beneficial effects that a medical education evaluation-diagnosis-treatment full operation chain is deeply fused, the clinical practice ability is remarkably improved, and medical risks are effectively prevented and controlled.

The invention belongs to the field of virtual reality teaching application, and provides a teaching atmosphere automatic adaptation method and system in an immersive teaching environment. The method comprises the following steps: acquiring an eye movement image; recognizing a fixation point; carrying out ROI tracking; carrying out ROI boundary fusion; adaptively optimizing the object; adjusting the brightness of the ROI; and watching object interaction. According to the method, the immersion and interactivity of a future classroom can be improved, the use experience of an immersive virtual environment is facilitated, and deep fusion of an intelligent teaching environment and self cognition of a user is promoted.

The invention provides a cross-culture teaching adaptive guiding method and system integrating narrative reasoning and digital interaction, and relates to the technical field of digital interaction. According to the method, the first feature vector is constructed by collecting the culture background and the emotional state of the learner, and the culture portrait label is generated in combination with the multi-dimensional culture evaluation; guiding to generate multi-modal narrative data, executing semantic reasoning and conflict identification, and generating a personalized interaction script; behavior feedback is deployed and monitored in real time in a digital interaction environment, dynamic iteration and closed-loop optimization of teaching content are realized, and culture sensitivity and teaching adaptability are improved.

The invention discloses a medical operation AR practical training system based on mixed reality and reinforcement learning and a training method thereof, and relates to the technical field of medical education and medical operation training. The system comprises an MR terminal presentation and interaction module, a case and scene management module, a multi-mode operation data acquisition and evaluation module, a reinforcement learning training strategy engine module, a practical training process control module, a training examination management module and the like, a vivid medical scene is constructed in an MR environment, and data such as operation tracks, force and step time sequences of students are acquired in real time; the evaluation result is coded into a state to be input into the reinforcement learning model, the case difficulty, the prompting mode and the training rhythm are adjusted in a self-adaptive mode, individualized, procedural and quantifiable skill training and assessment are achieved, and the method is suitable for various operations such as cardio-pulmonary resuscitation, endoscopic surgery and puncture catheterization.

The invention relates to a clinical surgery experiment virtual simulation teaching method and device, equipment and a medium. The method comprises the following steps: responding to an obtained teaching task configuration file; the teaching task configuration file comprises a clinical scene and an evaluation standard; calling a corresponding three-dimensional digital physiological model according to the teaching task configuration file, and performing special effect rendering according to the clinical scene to obtain a visual virtual simulation experiment scene; responding to the obtained user action data, performing real-time deformation on the three-dimensional digital physiological model, and generating feedback parameters; the feedback parameter is used for indicating the interaction control to work according to the feedback parameter; and comparing the user action data with preset standard expert action data, and generating a teaching evaluation result based on an evaluation standard. By adopting the method, high fidelity can be carried out on the whole process of clinical surgery experiment teaching, effective technical support is provided for medical skill teaching, and the method is suitable for multi-scene and multi-level medical teaching practice requirements.

The invention relates to the technical field of robot teaching, and discloses a robot infant teaching system and device based on somatosensory interaction. According to the method, a somatosensory data acquisition module acquires skeleton point motion time sequence data and an interactive behavior video stream of a target child through a depth camera and an inertial sensor; the multi-modal feature fusion module is used for extracting dynamic track features from the skeleton motion data, analyzing behavior semantic features of the video stream, and generating a fusion interaction feature set through cross-modal association fusion; the interaction sensitivity calculation module is used for calling a pre-training dynamic weighting network model to carry out attention distribution on the fusion features and generating a teaching interaction sensitivity coefficient set containing different teaching link response sensitivity distributions; the abnormal behavior tracing module is used for generating a teaching behavior abnormal tracing result for indicating an abnormal source link and a deviation type; and the interaction strategy generation module generates a self-adaptive teaching strategy according to the traceability result and sends the self-adaptive teaching strategy to the robot motion control unit.

The invention discloses a music teaching method and system based on a vocal music live classroom, and relates to the technical field of music teaching, and the method comprises the steps: respectively collecting audio signals of a teacher end and a student end in the vocal music live classroom, carrying out the preprocessing, and generating frame-level acoustic feature vectors of teachers and students; based on frame-level acoustic feature vectors of teachers and students, generating a mapping feature vector, category probability and an adversarial sample set through mapping, domain discrimination and a CTC model, constructing a total loss function in combination with a loss function value of the model, and performing iterative optimization, gradient fixed-point rounding and feedback of model parameters; according to the invention, through constructing the total loss function, introducing the gradient inversion layer and the gradient fixed-point rounding mechanism, combining the three-state HMM state path and calculating the pronunciation quality logarithm score, the robustness and precision of student pronunciation evaluation in a vocal music live broadcast teaching scene are significantly improved, and thus a high-resolution teaching feedback basis is provided for teachers.

The invention relates to the technical field of VR teaching, in particular to a remote VR clinical medicine teaching system. The system comprises a first device, a second device and a server, the first equipment is used for enabling the student to enter the virtual medical teaching scene through the virtual reality equipment; the second equipment is used for the teacher to control the content and progress of the virtual medical teaching scene; the server is used for storing data of a virtual medical teaching scene and interaction information of students and teachers and communicating with the first equipment and the second equipment; the server further comprises a multi-modal data fusion module used for integrating various data types from the first device, including physiological data, voice data and video data, so as to generate a comprehensive student learning state report; the distributed edge computing node network is used for carrying out data preprocessing and preliminary analysis on edge nodes close to the first equipment; and the dynamic anatomical model generator is used for generating an interactive dynamic human anatomical model in real time according to teaching requirements.