5086 results about "User information" patented technology

The invention discloses a lower limb motion data real-time analysis method and system applied to rehabilitation guidance, and the method comprises the steps: calling a personalized model according to user information, converting real-time motion data into historical motion feature vectors, inputting the historical motion feature vectors into a real-time prediction module, and generating multiple frames of future motion feature vectors through coding and decoding; calculating a deviation value between each future motion feature vector and a preset threshold range to obtain a motion deviation value, calculating a motion risk proportion of each future motion feature vector, performing weighted fusion to obtain a motion risk probability, and generating an equipment parameter adjustment value and pose adjustment information through reverse mapping; and finally, according to risk probability assessment training stage promotion, synchronously displaying correction information and adjusting equipment operation parameters. According to the method, the dynamic model is constructed through pre-training, real-time prediction of future motion features is realized in combination with the lightweight LSTM, and the predictability and personalized adaptation ability of rehabilitation guidance are improved.

The invention discloses a liver disease diagnosis and treatment strategy recommendation method based on a knowledge graph, a medium and equipment, and the method comprises the steps: collecting the basic information of a user, constructing a space-time correlated individual liver disease knowledge graph according to the basic information of the user, and enabling the knowledge graph to comprise a disease cause feature node, a pathology grading node, a complication early warning node and a treatment response node which are correlated with each other; inputting the individual hepatopathy knowledge graph into a hierarchical reinforcement learning model for joint reasoning, and outputting multiple groups of strategy options including an antiviral treatment scheme, a liver protection drug combination and a metabolic intervention measure; analyzing a topological propagation path of a complication early warning node through a complication prediction sub-model, and dynamically adjusting an initial candidate diagnosis and treatment strategy set; and updating the individual hepatopathy knowledge graph when obtaining the basic information of the new user. According to the method, multi-dimensional data fusion and dynamic strategy optimization of liver disease diagnosis and treatment are realized, and the accuracy and timeliness of a diagnosis and treatment scheme are remarkably improved.

The invention discloses a dynamic power distribution network deduction method based on graph neural network perception and a privacy protection type Transform model. The method comprises the steps of collecting source load storage historical data in a power distribution network and performing standardization processing; performing time sequence segmentation; establishing a dynamic topological structure model of the power distribution network; extracting spatial features of the dynamic topological structure of the power distribution network by using a graph neural network; the spatial features are converted into time sequence data, the time sequence data are combined with time sequence data obtained after time sequence segmentation, and a source network load storage time sequence data set is established; differential privacy processing is carried out; training a Transform model, in the training process, using a differential privacy optimization technology, adding noise to the gradient when the gradient is updated each time, and finally obtaining a trained DP-Transform model; and inputting a specific scene, and deducing the state of the power distribution network by using a DP-Transform model. According to the method, the interpretability of deducing the state of the power distribution network by using the Transform is improved, so that the Transform model can fully receive the graph structure input of the network topology structure of the power distribution network, and privacy protection on user information in the deducing process is considered.

The invention discloses a multi-beam cooperative scheduling method and a multi-beam cooperative scheduling system for low-orbit satellite communication, which mainly solve the problems of poor beam scheduling flexibility and difficulty in adapting to time-varying requirements in a high-dynamic environment in the prior art, and the implementation scheme of the multi-beam cooperative scheduling method comprises the following steps of: collecting online user information by a low-orbit satellite through a wide beam; a hopping beam position is generated by using adaptive clustering under the constraint of channel resources; a hopping beam scheduling algorithm based on deep reinforcement learning outputs an optimal scheduling strategy according to the real-time environment variable; and optimizing a beam hopping time frame structure in each scheduling period, covering accessed users in a beam position through spot beams, and sending service data and control information to complete efficient service transmission. The method can adapt to changes of user distribution and service requirements in low-orbit satellite communication, the utilization rate of spectrum resources is improved, communication delay is reduced, the overall performance and service quality of the system in a high-dynamic environment can be enhanced, and the method can be used for dynamic beam position division, hopping beam scheduling and hopping beam resource allocation in a multi-beam low-orbit satellite communication scene.

The invention discloses a database management method and management system, and relates to the technical field of general database management, and the system comprises a user information management module, a work management module, a salary settlement module, an evaluation feedback module, an analysis prediction module, a multi-terminal integration module and a safety guarantee module. In the invention, a role-based access control permission model is constructed in a permission control layer and a module definition, and a field-level data control mechanism is implemented for three roles of a platform administrator, a customer enterprise and an employee, for example, the employee can only check a specific public field in a salary list, and sensitive fields such as a salary calculation formula are dynamically shielded; through a permission inheritance mechanism, the system automatically adds a filtering condition that employee ID = current user ID for a query request of an employee role, data isolation is ensured, a multi-dimensional data relation graph of employee-post-customer-contract is constructed, and a dynamic association path between entities is mapped in real time through a visual view.

The invention relates to the technical field of neuromuscular electrical stimulation, and provides a multi-modal feedback self-adaptive adjustment neuromuscular regulation and control treatment system, which comprises wearable working equipment for outputting pulse electric signals to adjust nerves and muscles to form movement or adjustment feeling, electromyographic signals, motion data and user feeling input are collected to conduct feedback adjustment on output parameters of the output pulse electric signals; the handheld control equipment is used for being connected with the wearable working equipment and controlling the output working mode and the working state of the wearable working equipment; and the server-side equipment is used for managing user information and preference of the handheld control equipment, setting function authority of the handheld control equipment, acquiring data acquired by the wearable working equipment, and realizing self-adaptive output of output parameters of the pulse electric signals of the wearable working equipment based on a self-adaptive reinforcement learning algorithm. Adaptive optimization of millisecond-level dynamic electrical stimulation parameters is realized through a multi-modal feedback data fusion technology in combination with a layered reinforcement learning architecture.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a product decision optimization method, device, equipment and medium based on a knowledge graph. And generating a user feature portrait in combination with the user related information, taking the user feature portrait and the information in the knowledge graph as an input state, taking the product information set as an action space, training and generating a decision model based on a preset incentive mechanism, outputting a target item by using the decision model, and updating the knowledge graph and the decision model based on user feedback information. The comprehensiveness of an input state is improved through a fusion modeling mode containing user information, product information and environment information, a dynamic updating mechanism is constructed in combination with a knowledge graph and user feedback, a decision model is driven to be continuously optimized, and then the pertinence of a recommendation result and the self-adaptive capacity of a system are improved.

The invention relates to the technical field of semantic analysis, can be applied to business scenes of financial science and technology, medical health and the like, and discloses an intention analysis and strategy generation method, device, equipment and medium, and the method comprises the steps: obtaining interaction data, recognizing an interaction type according to metadata features, selecting a corresponding analysis model to analyze and process data, and generating a text corpus; current user information is extracted from the text corpus, user intention score analysis is executed based on an intention analysis strategy corresponding to the interaction type, and a current user intention score is generated; and generating a demand list according to the user information, the intention score and the interaction type, and generating and outputting an interaction strategy based on the user information and the demand list. Through interaction data processing and automatic intention scoring analysis, the demand list and the interaction strategy of the customer can be quickly and accurately generated, the customer information processing efficiency and accuracy are improved, the workload of manual input and analysis is reduced, and the customer service quality and the response speed are improved.

A system uses a large language model (LLM) to implement a controlled artificial intelligence chat environment. The system may control interaction with the LLM using prompt templates that may be selected, customized, and / or modified based on information known about the user with whom the LLM will be interacting. Further, the system may evaluate output of the LLM to make changes to the LLM, the prompt templates, and so on. In some implementations, the system may use evaluation training data to adapt and fine-tune the LLM and / or another language model to evaluate output of the LLM in order to evaluate the efficacy of the chronic condition and / or disease management coaching path(s), and make improvements to the online or offline implementation of the language model in the future.

The invention relates to the technical field of computers, and provides a multi-modal learning resource intelligent recommendation method and system based on an AI large model, and the method comprises the steps: carrying out the intention analysis of interaction behavior data and user information based on the AI large model, and obtaining a user feature vector; obtaining multi-modal resource data based on the user feature vector, and integrating the multi-modal resource data to obtain a resource representation vector; mining implicit association between resources and knowledge points and a mapping relation between user requirements and target skills based on a knowledge graph in combination with user feature vectors and resource representation vectors to obtain a knowledge network; generating candidate recommended learning resources based on the context awareness information and the knowledge network; and performing sorting optimization on the candidate recommendation learning resources based on the user feature vector and the resource representation vector in combination with the current stage index of the multi-modal resource data, and generating an initial resource recommendation list. According to the embodiment of the invention, the content features of the learning resources are comprehensively captured, and the resource recommendation accuracy is improved.

The invention discloses a digital identity verification method and device based on a zero-trust architecture, terminal equipment and a storage medium, and belongs to the field of network security, and the method comprises the steps: obtaining an identity verification result according to user information and multi-factor identity verification information; according to the identity verification result, generating a session token and creating a session; collecting behavior data, equipment fingerprint data and geographic position data of the user during the session in real time, and dynamically adjusting the access authority stored by the session token according to the behavior data, the equipment fingerprint data and the geographic position data; each time a request sent by a client is received, the zero-trust architecture gateway determines the current session state of the server by verifying the current session token. Therefore, through the implementation of the invention, various identity authentication technologies can be organically integrated, continuous identity authentication under a zero-trust architecture is realized, and the security of digital identity authentication is improved.

According to various embodiments, a system and method for verifying a user's identity using both document-based and biometric data is disclosed. The system may prompt a user to upload an image of a government-issued identification document and extract user information from the image using optical character recognition (OCR). The system may also extract the embedded face image from the ID and prompt the user to take a real-time selfie while performing one or more randomized actions or poses. A facial recognition engine may compare the extracted ID image to the live selfie to determine a similarity score. Based on this match, along with optional document authenticity checks, the system may confirm the user's identity in real-time for use cases such as account access, onboarding, and regulatory KYC compliance.

The invention discloses an automatic feasibility research report generation method fusing a knowledge graph and a large model, and relates to the technical field of leather inlaying, and the method comprises the following steps: extracting and cleaning information from multi-source heterogeneous data, and carrying out standardization processing on terminologies; constructing a knowledge graph, and converting the knowledge into embedded vectors which can be processed by a computer; according to user information, related sub-graph information is accurately retrieved from the knowledge graph, and cue words containing professional knowledge are dynamically combined; the large model generates a first draft according to cue words, a system automatically checks, and when conflicts are found, the model is required to be regenerated; and integrating the content which is verified to be correct with related standard terms, automatically adding a data reference source, and generating a document which is standard in format and clear in risk point. According to the method, real-time and automatic professional knowledge conformity checking and self-correction can be carried out on technical parameters and logic assertions output by the model in the generation process.

The invention provides an attack defense method and device for an e-commerce intelligent customer service large model, and relates to the technical field of artificial intelligence security, and the method comprises the steps: 1, monitoring an interaction data flow between a user and an intelligent customer service in real time, recognizing an abnormal interaction behavior, and activating a multi-layer defense strategy when the abnormal behavior is detected; 2, based on a multi-layer defense strategy, sensitive words, special character sequences and potential injection marks in an input text are recognized and processed through the dynamically updated multi-field sensitive word detection rule base and the special symbol matching rule set, and a preliminarily filtered text is generated; according to the method, various malicious attacks aiming at the e-commerce intelligent customer service large model are effectively resisted, the user information security is maintained, and the customer service quality and the e-commerce operation reliability are improved.

The invention discloses an intelligent question-answering system training method based on machine learning, and the method comprises the steps: optimizing a knowledge learning sample to obtain optimized knowledge, determining a knowledge weight, constructing an industry knowledge base, fusing multi-modal question content to obtain fused question content, and carrying out the training of the intelligent question-answering system. Obtaining industry description information and a user portrait according to the fused question content and the user information, and inputting the fused question content, the industry description information and the user portrait into a question and answer reinforcement learning model to obtain answer content, and obtaining a first reward signal, a second reward signal and a dynamic reward weight according to the answer content and the user question response information, adjusting the question and answer reinforcement learning model, inputting the multi-modal question content into the adjusted question and answer reinforcement learning model to obtain optimized answer content, and updating the industry knowledge base by adopting a user interaction log and the knowledge weight. According to the method, intelligent question and answer system training can be accurately and efficiently carried out, and meanwhile powerful support is provided for intelligent question and answer services of all industries.

The invention belongs to the technical field of catering informatization service, and provides an automatic matching catering menu pushing system, which comprises a user data acquisition module, a catering menu pushing module and a catering menu pushing module, the menu data management module stores and manages menu classification, labels and states, and obtains content feature data; the user portrait construction module generates a multi-dimensional portrait according to the multi-aspect information of the user; the menu matching module combines collaborative filtering and a content recommendation algorithm, and generates a recommendation menu based on the user portrait; the intelligent pushing module pushes dishes of nearby merchants according to the portraits, and the pushing effect is evaluated through the click rate and the conversion rate; according to the method, personalized and accurate catering menu recommendation is realized, and real-time updating and optimization are carried out in combination with geographic positions and time period factors, so that personalized pushing which better fits user preferences and dining environments is provided.

The invention relates to a distributed data security storage and encryption system based on an AI technology. The system comprises a data acquisition and preprocessing layer used for acquiring original data and preprocessing the original data to obtain an identifiable data object; the AI identification and strategy decision layer is used for identifying data features of identifiable data objects based on an interpretable AI model to obtain an encrypted instruction packet; the encryption execution and distributed storage layer is used for performing encryption storage processing on the original data content according to an encryption instruction packet to obtain data access interface information; and the dynamic access control layer is used for obtaining user information in response to a data access request instruction of a user, recombining and decrypting the data by using the data distribution mapping index based on the access control strategy table, and returning a plaintext data fragment. By adopting the system, a high-strength, differentiated and multi-level security mechanism can be realized through the AI, intelligent encryption strategy decision is carried out, and the security requirements of multiple scenes and multiple types of data are met.

A mobile consumer device with a display, processor(s), and memory: identifies a merchant device in proximity to the consumer device based on broadcasted information transmitted by the first merchant device, the broadcasted information including a first identifier corresponding to the first merchant device; transmits the first identifier to a server and receives from the server an electronic communication including identification and transaction information associated with the merchant; displays the identification information, receives user selection of the merchant identification information; and in response, displays the merchant transaction information, receives supplemental user information, and transmits the supplemental transaction information to the server for completion of the transaction.

The invention discloses an intelligent parking method and device based on multi-source data fusion and a medium, and relates to the technical field of big data technologies. The method comprises the following steps: collecting multi-source parking data, and analyzing the multi-source parking data to generate a parking lot label library; generating a user tag based on historical search records and residence time preferences of the user, and constructing a user information database; when it is detected that a user triggers a parking request, performing multi-dimensional matching calculation on a user tag and a parking lot tag library to obtain a recommended parking space sequence; and optimizing the recommended parking space sequence based on the real-time traffic state and the user credit score to generate a final navigation path. According to the method, a dynamic parking recommendation mechanism is constructed by collecting and analyzing the multi-source parking data and the user preference data.

The invention discloses an intelligent rehabilitation training system based on multi-parameter detection and a control method, and relates to the technical field of intelligent rehabilitation training, the system comprises a user information acquisition unit, a multi-source parameter acquisition unit, a rehabilitation training plan customization unit, a feedback and control unit and a quantitative evaluation unit; multi-source detection parameters corresponding to movement, physiology and environment of a target user are collected in real time through a preset sensor, the health-related data and the multi-source detection parameters are fused, a rehabilitation training domain knowledge graph is accessed to construct a training scheme recommendation model, and a personalized rehabilitation training plan of the target user is output; according to the achievable degree of the target user for each rehabilitation training action, real-time feedback is provided through a visual interface and voice prompt, and the target user is guided to adjust the training action; a brand new solution is provided for rehabilitation training based on multi-parameter detection, the training state of the user can be monitored in real time, a personalized training scheme is generated, and the rehabilitation effect and efficiency are remarkably improved.

A system and method for an intelligent hair drying / styling apparatus with user information transmission and storage capabilities is herein provided. The hair drying / styling apparatus houses a control circuit board and an infrared or temperature sensor (or camera) in order detect an individual's hair condition moisture level to determine a user specific, customizable dryer setting. The information detected by the sensor is stored locally, on a proximal Internet-enabled device, or on a remote or cloud-based server and accessed by the hair drying / styling apparatus through a wireless local area network connectivity function. This innovation will enable any number of hair professionals and / or end consumers to improve styling and dry time. According to the present invention, energy usage is reduced to enable a more efficient design.

The invention relates to the field of large language models, and provides a safety guarantee method for text generation of a large language model. The existing watermarking technology can detect whether a text comes from a specific model or not, but cannot trace the identity of a user, so that responsibility can not be traced when the text is spread or tampered for the second time. According to the main scheme, a statistical signal is embedded in a generated text based on a relaxed red-green dictionary method, and a model tends to select a green list token by adjusting the token sampling probability when the language model is generated; the user information is a mobile phone number or an identity card number, Base4 coding is carried out, and offset information is obtained; in the basic watermark text, starting from the first green token, generating a synonym list based on the context every two continuous token positions, and selecting corresponding synonyms for replacement according to the offset so as to implicitly embed user information; the method comprises the following steps: detecting a basic watermark, recovering a text by using a Transform-based sequence denoising auto-encoder, and extracting user information according to a replacement position and an offset.

The invention relates to a full-process order life cycle management method, system and device and a medium, and the method comprises the following steps: obtaining user information and user demands, and building a work order; according to a preset rule, work order distribution is carried out, related information is supplemented, and a pre-sales scheme is generated; technical feasibility, resource requirements and risks of the pre-sales scheme are automatically assessed, and an assessment report is generated; project research and development are carried out based on the pre-sales scheme and the evaluation report, the research and development progress is updated in real time in the research and development process, and research and development results are uploaded after research and development are completed; the research and development results are tested based on the automatic test script, and a test report is automatically generated; generating a delivery list based on research and development results and test reports, and automatically sending the delivery list to the user; and obtaining questions fed back by the user, performing automatic classification according to the questions, and performing adjustment according to a classification result until the order is completed. Compared with the prior art, the device has the advantages of high automation degree and the like.

The invention provides a face recognition method and device, electronic equipment and a medium, and the method comprises the steps: processing a scaled to-be-recognized face image through a face detection model, and determining the coordinates of a face region and a plurality of key points in the original to-be-recognized face image based on the recognition result of the face detection model; based on the coordinates of the plurality of key points in the to-be-recognized face image and the coordinates of the plurality of key points in a preset face template, aligning a face region in the to-be-recognized face image to the preset face template, and outputting an aligned face image of a preset size; processing the aligned face image through a face recognition model comprising a down-sampling module, and generating a target face feature of the face image to be recognized; the user information of the target user corresponding to the to-be-recognized face image is determined based on the similarity between the target face feature of the to-be-recognized face image and the feature vector of the user in the database, so that the calculation amount in the face recognition process is reduced, and the accuracy and precision are both considered.

The invention discloses a universal web development framework implementation method for full-ciphertext transmission, and the method comprises the steps: a front end obtains a national cryptographic symmetric key of a rear end for data encryption, generates a request message, and sends the request message to the rear end; after uniqueness of the request message is obtained through the distributed lock, signature verification is carried out by the rear end; the back end decrypts the encrypted message to obtain the user information and the secret key, and the secret key is stored in a thread local variable; adding a paging annotation and a log annotation to the decrypted request body data; a configuration change event is monitored in real time, and latest configuration data is pulled and updated to the Bean object after configuration change; an MQ adapter is utilized to realize automatic routing of a new message and an old message; the link ID is carried when the external interface is requested. The development cost of the basic function module is effectively reduced.

A multi-access point (M-AP) coordination method comprises receiving a coordination control frame, by a processor of a second access point (AP), wherein the coordination control frame is transmitted from a first AP, wherein the coordination control frame comprises at least one user information field for at least one shared AP, and each of the at least one user information field comprises an AP ID of a shared AP and coordination transmission parameters information of the shared AP; identifying, by the processor, the second AP as the shared AP if the AP ID of the second AP is in one user information field; and transmitting, by the processor, a packet during a transmission opportunity (TX OP) shared by the first AP based on the coordination transmission parameters information in the user information field containing the AP ID of the second AP.

The invention relates to the technical field of emotion regulation and control, in particular to an emotion regulation and control system based on a self-adaptive virtual reality scene, which comprises an emotion monitoring module, a virtual reality device, a self-adaptive regulation and control module, a feedback module, an emotion guiding module and an effect evaluation module, the emotion category and the emotion intensity are analyzed and judged; the virtual reality equipment is used for providing virtual reality experience for a user; the self-adaptive regulation and control module is used for adjusting elements and parameters of the virtual scene; the feedback module is used for collecting evaluation on the emotion regulation effect, analyzing the evaluation and generating a feedback report; the emotion guiding module is used for providing emotion guiding suggestions; and the effect evaluation module is used for quantifying the effect of emotion regulation and control and evaluating the effect of emotion regulation and control. According to the invention, real-time monitoring and dynamic regulation and control of the emotion of the user can be realized, personalized virtual reality experience is provided, and more effective mental health support is provided for the user.

Approaches to electronic device security are described. A representation of user information describing a user device, visible in a graphical presentation of a user-specific polygraph via a graphical user interface (GUI) presented via a display device is generated. First information associated with the user is gathered. Second information indicating activity associated with the user that has been generated by an application executed on the electronic computing device is gathered. Determining whether the user of the electronic computing device has deviated from normal activity by correlating portions of the first information with portions of the second information. Directing the user to an approval workflow via the browser in response to a determination that the user has deviated from normal activity.

The invention relates to the technical field of information security, in particular to a user information protection method and device based on a dynamic desensitization strategy, and the method comprises the steps: determining sensitive data and a sensitivity score thereof through a named entity recognition model and a sensitivity scoring algorithm, extracting scene parameters, and determining a scene risk score through a risk quantification algorithm; and then a dynamic desensitization strategy generation algorithm is called to generate a target desensitization strategy, and finally, the strategy is used for desensitization and a reversible desensitization data identifier is generated. Through the series of steps, the desensitization strategy is dynamically generated according to different use scenes, the problem of scene adaptability deficiency caused by static desensitization strategy stiffness is solved, meanwhile, the reversible desensitization reduces the security risk caused by reverse cracking of rules, excessive desensitization is avoided, and the data availability is improved.

The invention discloses an implementation method for constructing a unified user authentication center based on an OIDC framework, and the method comprises the steps: S1, integrating user data sources, and constructing a unified science and technology management user information base; s2, constructing a unified user authentication center of the science and technology management industry; s3, related functions of each business platform system in the science and technology management industry are upgraded, OIDC unified user authentication service docking is completed, and unified identity management is realized; and S4, system interfaces of all service platforms in the science and technology management industry are comprehensively and jointly debugged, and seamless cooperation of all the service platforms in the science and technology management industry and the OIDC unified user authentication center is ensured. The method has the advantages that the problems of informatization cross-system and cross-platform identity management and authority control in the science and technology management industry are solved, efficient and safe user identity management is realized, the system safety is enhanced, the system convenience is improved, the system integration complexity is reduced, and the informatization system management efficiency is improved.