4612results about "Electrical appliances" patented technology

The invention relates to the technical field of online network teaching, and discloses an online network teaching practice method based on a virtual technology, and the method comprises the steps: obtaining virtual scene data, and carrying out the integration and building of a dynamic knowledge graph and a multi-modal teaching resource library; learning behavior features are extracted according to the cognitive features of the learner, knowledge difficulty levels are divided, and immersive learning is guided; constructing a cognitive evaluation model, optimizing a learning path through hierarchical reinforcement learning, and generating a self-adaptive teaching instruction; collecting interaction track data to generate an operation thermodynamic diagram, and evaluating the skill mastering degree; complexity parameters of the virtual scene are dynamically adjusted, a virtual-real linkage experiment simulation environment is constructed, and skill training closed-loop feedback is achieved. The invention further relates to specific implementation modes of resource integration, cognitive feature extraction, learning path optimization and the like. According to the method, the personalized and immersive experience and skill training effect of online teaching are improved, and the method is suitable for the field of online network teaching.

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 traditional Chinese medicine acupuncture and moxibustion teaching, in particular to a multi-view fused traditional Chinese medicine acupuncture and moxibustion visual teaching system which comprises a basic data construction module, an immersive environment building module, a multi-view interactive teaching module, a collaborative annotation conflict processing module, an annotation result auditing module and a model and data optimization module. Compared with the prior art, the traditional Chinese medicine acupuncture and moxibustion visual teaching method has the advantages that a new traditional Chinese medicine acupuncture and moxibustion visual teaching paradigm of data-driven cognition, interactive verification logic and intelligent optimization iteration is constructed through a closed loop of'problem definition-technical breakthrough-effect guidance ', space and modal limitations of traditional teaching are broken through, and the traditional Chinese medicine acupuncture and moxibustion visual teaching method is suitable for popularization and application. In addition, deep fusion of traditional Chinese medicine inheritance and modern medical education is achieved, and a reproducible digital solution is provided for standardized and precise acupuncture and moxibustion teaching.

The invention relates to the technical field of physical education, in particular to a physical education method and system based on multimedia and holographic AR fusion, and the method comprises the following steps: collecting the motion data of a trainee based on a multi-source sensor array, constructing a motion parameterized model, and generating a holographic projection generation module through the cooperation with a standard motion database; a holographic AR teaching image is generated in real time, an environment perception module is combined to carry out adaptive projection on illumination and spatial layout, a spatial positioning module is used to establish coordinate mapping between a trainee and a virtual image, and a multi-channel feedback device is started to output visual, tactile and auditory signals. And finally, comparing the action parameters with the standard action data to automatically generate a training report containing wrong action labels and correction suggestions. According to the method, the motion capture precision and the interactive immersion can be effectively improved, and efficient and extensible technical support is provided for modern physical education and training.

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 provides a multi-agent collaborative teaching interaction method and system in an education scene, and relates to the technical field of intelligent education, and the method comprises the steps: building a knowledge point dependency graph; constructing an optimal teaching path set; forming a collaborative teaching network and calculating a teaching path overlapping degree matrix to divide teaching tasks; acquiring learning data to generate learning difficulty indication information; and matching the teaching path with the highest adaptation degree according to the difficulty information, and adjusting the corresponding intelligent agent to carry out supplementary explanation. According to the invention, efficient collaborative configuration of intelligent teaching resources can be realized, accurate teaching support is provided for personalized difficulties of learners, and the teaching efficiency and the learning effect are improved.

The invention provides a classical music cross-modal high-reliability experimental data set construction method for full-scene teaching application, and the method comprises the steps: constructing an original data set through collecting audio, video, music score and other multi-modal data, carrying out the standardization of each modal data through a preprocessing technology, and obtaining a multi-modal data set in a unified format; according to the semantic feature vectors, a knowledge graph is constructed, nodes represent semantic relations between music elements, edges represent semantic relations between the elements, a graph convolutional network is adopted to encode the knowledge graph, and semantic representation of the teaching content is obtained; a virtual reality rendering technology is adopted, multi-modal teaching resources are integrated into an immersive teaching scene, a content sequence is presented in real time, and dynamic teaching experience is obtained; and continuously collecting interaction data of the learner, updating the knowledge graph and the semantic feature vector, and optimizing the cross-modal fusion model by adopting an incremental learning algorithm to obtain a self-adaptive teaching data set.

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.

A user directed video generation method and system obtains a natural language-based communication from a user requesting that a computer-implemented system generate a virtual environment that is based on a description that is provided by the user. The description is interpreted by a trained neural network. Representations of pixel patterns are generated by a trained neural network in accordance with the interpretation. The representations of the pixel patterns are evaluated for consistency with context and then selected based on the evaluation. The selected pixel patterns are embodied in a video stream that is provided to the user. Natural language that may be in audio form may be generated to accompany the video stream.

The invention discloses an intelligent scene type CPR visual training system based on an MR technology, which belongs to the technical field of non-special measurement for specific variables and comprises a training request sensing module, an intelligent scene automatic generation module, a sensing data acquisition module, a visual display and voice prompt module and a network performance evaluation management and control module. According to the method, the performance parameters of the sensing source nodes built in the simulation human body model are acquired and analyzed in real time, so that the data feedback precision in the training process is improved, and the data feedback precision in the training process is further improved; the problem of poor CPR visual training experience caused by lack of real-time performance monitoring and feedback mechanisms in the prior art is effectively solved.

The invention discloses a holographic projection system based on an AI large model. According to the invention, through the nano-scale optical coating and environment self-adaptive adjustment technology, harmful blue light is effectively filtered, environment light parameters are dynamically matched, the problem that eyes are injured by a common screen is solved, and the method is especially suitable for long-time learning scenes of children. The holographic projection core module adopts a naked eye 3D light field technology, presents complex models such as dinosaur, marine organisms and the like in a three-dimensional suspension manner through high-fidelity color restoration and dynamic depth-of-field adjustment capability, and is matched with gesture touch control and voice instructions of multi-mode interaction hardware, so that a user can directly touch a virtual object, and the real-time performance of the virtual object is improved. Experience upgrading from plane observation to space interaction is achieved, and knowledge such as English learning and animal and plant cognition is converted into interactive games and story narration through virtual teacher images and scene scripts. The autistic children can complete social dialogue training under the guidance of the virtual role, the system analyzes emotion fluctuation in real time and adjusts a guidance strategy, and social fear is gradually eliminated.

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.

The invention pertains to a content customization system (100) that provides dynamically personalised content utilising a multifaceted understanding of user behaviour and preferences. The system (100) integrates artificial intelligence with psychological and neuroscientific insights to tailor content, such as text, images, audio etc., to individual users in real-time. The system (100) comprises a Multifaceted Understanding Engine (MUE) (102) that processes the user data through a Neuro Psycho Artificial Intelligence (NPAI) module (106) to generate a dynamic psychological profile of the user, based on which a specialized prompt generation module (107) generates content customization instructions or "prompts" to retrieve content from a repository server (111) that further gets refined by utilizing Large language model (112), thereby delivering a seamless and personalized content experience to the user in real time.

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.

A method for predicting gas explosion. The method includes: obtaining a geometric model with spatial obstacles; determining a simulation dataset of the gas explosion based on the geometric model, where the simulation dataset is a dataset including process data of multiple gas explosion scenes in the geometric model, and a state vector of a spatial grid node in the simulation dataset includes a first moment, coordinate information and a target pressure value; optimizing, using the simulation dataset, a physics-informed GNN to obtain an optimized physics-informed GNN; and predicting the gas explosion in an obstructed gas explosion scenario using the optimized physics-informed GNN. This method is applied to use optimized physics-informed GNN to realize spatiotemporal second-level prediction of overpressure distribution and explosion wave propagations occurring in the obstructed gas explosion scenario, enhance the accuracy, the reliability and the efficiency of gas explosion prediction in the obstructed gas explosion scenario.

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 belongs to the technical field of online learning, and discloses a real-time interactive online Chinese language learning platform. Comprising the steps of constructing a virtual culture interaction scene; in the dialogue interaction process, continuous dialogue fragments are collected in real time; performing multi-level language bias error analysis on the continuous dialogue segments, identifying language errors, making corresponding language correction suggestions according to the language errors, and feeding back the language correction suggestions to the user through a progressive feedback mechanism; collecting multi-modal data of a user, carrying out nonlinear feature mapping, generating a multi-dimensional state feature vector, and dynamically evaluating a cognitive load and a learning state; the cognitive load and the learning state are fused, interaction regulation and control strategy reasoning is carried out, and the interaction mode and the interaction difficulty in dialogue interaction are dynamically optimized according to an interaction regulation and control strategy; according to the method, accurate control and dynamic regulation and control of the whole Chinese language learning process of the user are realized, personalized online Chinese learning experience is provided, and comprehensive improvement of the language ability of the user is promoted.

The invention discloses a multi-modal emotion calculation enabling adaptive interactive language learning system and a matching method thereof, and belongs to the technical field of artificial intelligence, and the system comprises a multi-modal emotion real-time perception and quantification module MHAE-Net, a personalized adaptive dialogue and intervention strategy module ADIS-RL, and a virtual dialogue partner interactive interface module EC-NLG. The multi-modal emotion real-time perception and quantification module MHAE-Net is composed of a voice signal acquisition and processing unit, a voice emotion analysis unit, a text emotion analysis unit, a facial expression emotion analysis unit, a physiological signal emotion analysis unit and a multi-modal emotion fusion and decision-making unit. The interactive strategy is dynamically adjusted, the oral anxiety of the language is effectively relieved, the oral confidence is improved, the system adopts the multi-mode emotion calculation technology, the accuracy and robustness of emotion recognition are improved, the targeted interactive strategy is designed for different emotion states, and personalized emotion support and language practice are provided for learners.

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 figure modeling and fitness action teaching method and system based on non-contact action capture, and the method carries out the real-time monitoring of a human body posture through a millimeter wave radar, carries out the 3D human body posture reconstruction and analysis through combining with a human body posture frame of Google image processing, and achieves the high-precision action capture. The method can be used for human body modeling, body building action scoring and action guidance, action evaluation and real-time feedback in body building teaching can be effectively supported, the millimeter wave radar is adopted for human body posture capture, external markers or wearable equipment are not needed, constraint on user activities is avoided, and use convenience and comfort are improved. The 3D posture of the human body can be accurately reconstructed in combination with a deep learning neural network, and real-time processing and analysis are carried out. The method not only can realize accurate motion capture, but also can be combined with fitness motion scoring and guidance, is widely applied to the fields of virtual fitness, exercise rehabilitation and the like, and has great application potential.

A method for generating augmented reality (AR) instructional content is disclosed. The method advantageously provides an AR graphical user interface for generating AR instructional content for performing a task from user-input text descriptions of the task. The method advantageously leverages generative artificial intelligence to enable a code-free and motion-capture-free experience for authoring the AR instructional content, including virtual avatar animations demonstrating performance of the steps of the task. Additionally, the method advantageously overcomes the contextual barrier by enabling the user to author context-aware AR instructions that understand the context and blend physical reality with virtual components.

The invention provides an AIGC digital human-based MOOC video generation method and device, and relates to the technical field of artificial intelligence content generation. The method comprises the following steps: inputting a target action sequence into a target digital human model, driving the target digital human model to execute a corresponding target action according to the target action sequence, and obtaining a target digital human teaching video; constructing a target virtual teaching scene by adopting a virtual engine, and embedding the target digital human model into the target virtual teaching scene to obtain a target teaching digital human model; determining a video background image and decoration and voice parameters of a target digital human model according to the target courseware by adopting a multi-mode AI model; and based on a preset template and the video parameters, according to the target digital person teaching video, the target teaching digital person model, the video background image, the decoration of the target digital person model and the voice parameters, generating a MOOC video. The method can improve immersion and practical operation effect, realizes teaching according to materials, reduces manpower and time cost, and is suitable for large-scale course production.

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.