182results about How to "Increase engagement" patented technology

The invention discloses a mirror image type industry linkage engine system and method based on a knowledge graph, and relates to the technical field of industry linkage engines, and the system comprises a data collection module which collects multi-industry data in multiple modes, and the cleaning accuracy is 90% or above; the knowledge graph construction module is combined from bottom to top and from top to bottom, and is used for distributed storage and block chain evidence storage; the industry mirror image model generation module is used for generating a model through machine learning, and the association accuracy is 95% or above; the linkage analysis and decision module is used for finding a linkage strategy through an intelligent algorithm; and the user interaction module has a graphical interface, is fast in response, can feed back optimization, and supports multi-language and VR / AR display. The system is accurate and efficient in data processing, integrates multi-source data to construct the knowledge graph, is deep and comprehensive in industry analysis, simulates industry relations to assist decision making, is intelligent and reliable in decision making support, provides strategies and evaluation, is convenient and friendly in user experience, improves interactivity through multiple technologies, promotes accurate decision making of enterprises, and promotes collaborative development and innovation of the industry.

The invention relates to the technical field of disease follow-up visit, in particular to a health state assessment system applied to disease follow-up visit, which comprises a data acquisition module, a data preprocessing module, a health state assessment module, a personalized health management suggestion module, a dynamic health risk prediction module and a visualization module, the data acquisition module acquires multi-dimensional data of a patient and performs data fusion and integration, the health state evaluation module evaluates the health state of the patient based on multi-level feature extraction and a deep learning model, and the personalized health management suggestion module combines a health state evaluation result and historical data to obtain a personalized health management suggestion result. Customized health management suggestions are generated through a rule engine, and the dynamic health risk prediction module predicts future health risks of patients and provides real-time early warning by using a time sequence analysis model. The visualization module displays health assessment and management suggestion results through a chart and an interactive interface, and the accuracy and individuation degree of health management are improved.

The invention discloses a smart home energy management optimization method in an Internet of Things environment. According to the method, the Internet of Things technology is utilized, intelligent identification and classified management are carried out on equipment, multiple energy management strategies are preset, and a user can conveniently and autonomously adjust; energy data is monitored in real time through a sensor and an intelligent electric meter, an energy consumption rule is mined by using a big data analysis technology, and a demand trend is predicted; constructing an intelligent energy dispatching center, and formulating a dynamic energy distribution scheme by using an optimization algorithm; a mobile phone application and an intelligent control panel are developed, and a user is supported to check data, control equipment and carry out personalized customization; and meanwhile, equipment firmware upgrading and remote management are realized. According to the invention, energy consumption can be reduced, cost can be controlled, equipment collaboration and energy distribution efficiency can be improved, user experience can be enhanced, system maintenance and upgrading are facilitated, and intelligent household energy management is more efficient, intelligent and flexible so as to adapt to diversified household requirements.

The invention discloses an AI auxiliary limb rehabilitation system, and belongs to the field of communication control systems, the AI auxiliary limb rehabilitation system combines a sensing module, an AI analysis module, a VR interaction module, a feedback module and the like, comprehensively collects limb movement and physiological data, introduces gamification elements, improves the patient participation degree through target setting, an award mechanism and interesting tasks, and improves the rehabilitation effect. A personalized rehabilitation plan is generated by using a deep learning algorithm, an emotion recognition unit can adjust the plan according to a psychological state, environment self-adaption and real-time adjustment of training difficulty to ensure training safety and is challenging, data cloud storage facilitates remote monitoring, third-party equipment is compatible with extended monitoring ability, and the training efficiency is improved. A brand-new, efficient and personalized solution system scheme is provided for limb rehabilitation.

The invention, which relates to the technical field of artificial intelligence and skill training examination, discloses a multi-crowd adaptive training evaluation system comprising the following components: a user data management module, an RAG module, an answer processing module, a score analysis module, an intensive training module and a question bank updating module. According to the method, comprehensive and accurate assessment of the user ability is realized by constructing a multi-crowd adaptive training assessment system, the system constructs the user ability portrait by collecting historical data and real-time performance of the user in multiple dimensions and utilizing advanced data processing and analysis technologies, and dynamically adjusts the training content and difficulty, so that the user ability assessment efficiency is improved. According to the method and the system, the ability level and the learning requirement of different users are adapted, the personalized training mode not only improves the participation degree and the learning efficiency of the users, but also helps the users to quickly and accurately identify the ability weakness of the users, and powerful support is provided for subsequent improvement.

The invention discloses an emotional pressure relieving and monitoring method combined with a virtual reality technology, and the method comprises the following steps: S1, providing a virtual environment for a user through a virtual reality device, and enabling the user to interact with the environment through wearing a virtual reality head-mounted device and using a controller; s2, collecting physiological data of the user in real time through a biosensor, wherein the physiological data comprises heart rate, brain wave, electrodermal response and oxyhemoglobin saturation; s3, inputting the physiological data in the S2 into a long-short-term memory network model for processing, and predicting emotional changes; s4, adjusting the virtual reality environment in real time to adapt to the current emotional state of the user based on the emotional state analysis and prediction result of the long-short-term memory network model; and S5, repeating the steps S2 to S4 to monitor the emotion of the user. According to the method, solid technical support is provided for emotion pressure management and monitoring based on the virtual reality technology, and a traditional static emotion regulation method can be effectively replaced.

The invention discloses a light-weight government affair questionnaire intelligent touch and analysis system and method based on a fusion message, and the system comprises an integrated message application platform operation interface which is used for the submission, application, strategy definition and transmission of a customer message; the questionnaire engine is used for generating questionnaires, issuing strategies and performing multi-dimensional statistical analysis on questionnaire results; the intelligent message scheduling engine is used for realizing AI generation of rich media messages, multi-channel intelligent reach distribution, optimal reach mode selection and summary analysis of reach mode results; and the electronic fence data engine is used for processing operator real-time signaling big data and capturing operator numbers and accurate touch short messages in a specified range. An efficient and convenient short message creation and auditing mechanism, flexible and diversified questionnaire construction, intelligent rich media message generation, accurate regional orientation and audience access, intelligent distribution, high interactivity, comprehensive and deep data analysis and report generation can be realized.

The invention relates to the technical field of user data processing, in particular to a user portrait enhancement method based on a dynamic tag, which is applied to a system method for designing data acquisition, data processing, data analysis and data classification of a user information and user portrait data use platform. By analyzing the user behavior in real time and dynamically adjusting the label in the user portrait, the more accurate and comprehensive user portrait can be constructed, and the real-time interest and long-term preference of the user can be captured. Based on the dynamically updated user portraits, the system can provide highly personalized recommendation services, commodity recommendation, content recommendation or service recommendation can be closer to the real demands of the users, and the satisfaction degree and participation degree of the users are improved.

The invention relates to the technical field of digital marketing, in particular to a digital advertisement putting method based on big data, and the method comprises the following steps: initializing an advertisement model, importing advertisement request time sequence data, carrying out time sequence analysis, adjusting an enqueue rule and a processing rate, calculating request distribution in a differentiated time period, and generating model parameter configuration. According to the invention, through a queuing theory and time sequence data analysis, advertisement time sequence and processing efficiency optimization, time sequence analysis and parameter adjustment, advertisement timeliness is enhanced, user activity peak synchronization is ensured, user participation degree and advertisement effect are improved, and recalculation of service time and estimation of waiting time support real-time monitoring of service efficiency. Accurate matching of advertisement resources and user requirements is achieved, real-time adjustment of strategies and simulation testing rapidly adapt to market changes, the resource utilization efficiency and ROI are improved, and precision and economic benefits of advertisement putting are remarkably improved through fine management and data driving optimization.

The invention relates to the technical field of director and picture synthesis methods, in particular to an intelligent director and picture synthesis method of a panoramic live broadcast system, which comprises the following steps: acquiring panoramic video data shot by a panoramic camera; obtaining user feedback data; based on the panoramic video data, generating a shot selection strategy by using a deep reinforcement learning algorithm; detecting a live broadcast key event in real time by using a target detection and tracking algorithm based on the panoramic video data; generating a picture shooting plan sequence according to the shot selection strategy and the live broadcast key event; performing intelligent editing and synthesis on the panoramic video data based on the picture shooting plan sequence; and outputting the synthesized live video. And updating parameters of the deep reinforcement learning algorithm based on the user feedback data, thereby realizing full automation of the program directing process, greatly improving the efficiency, and enabling the system to continuously learn from live broadcast experience through the deep reinforcement learning algorithm and gradually improve the decision-making ability of the system.

The invention provides an AI-driven multi-dimensional short video matrix analysis and management system, and relates to the technical field of information prediction.The AI-driven multi-dimensional short video matrix analysis and management system is characterized in that audience modal information when a short video is played is obtained by performing audience verification on a traffic feature set, and click attribute information when a short video user clicks the short video is determined according to the audience modal information; determining audience acceptability of the short video content according to the access like data, and determining a delivery matching coefficient during short video delivery according to the audience acceptability and the click attribute information; according to the behavior characteristic information, determining a perception monster degree when the short video user watches the playing of the short video; and performing trend analysis on the dynamic interest tag of the short video user according to the delivery matching coefficient and the user behavior sequence subjected to the correction constraint, so as to perform short video recommendation on the short video user. According to the method, the user experience and the platform activity degree can be improved under the influence that dynamic interests and complex preferences of the user are difficult to accurately capture from the recommended content.

The invention provides an intelligent dynamic pushing method and device based on marketing canvas construction, equipment and a medium, and the method comprises the following steps: obtaining basic data of a marketing canvas, and constructing a marketing canvas model according to the basic data; adjusting a marketing pushing strategy weight according to the real-time behavior and historical preference of the user; on the basis of the adjusted marketing pushing strategy weight, a pushing path is optimized according to user feedback and context information; based on the generation model, automatically generating personalized contents of the user and evaluating a pushing effect in real time; according to the method, a marketing canvas model based on multiple data is constructed, data such as products, customers, channels and communication strategies are combined, and real-time behaviors of users are dynamically analyzed and predicted by using a deep learning model. In this way, the accuracy of the user portrait can be improved, the pushing strategy can be updated and adjusted in real time, and therefore accurate personalized pushing is achieved.

The invention provides a virtual resource acquisition method and device, equipment and a storage medium, and belongs to the technical field of multimedia. The method comprises the following steps: displaying a resource prompting component on a playing interface of multimedia resources, wherein the resource prompting component is used for prompting to obtain virtual resources associated with the multimedia resources; in response to the fact that the resource prompt component meets the interaction condition, displaying that a first virtual container moves on the playing interface, the first virtual container being used for loading the virtual resource; and in response to a trigger operation on the first virtual container, displaying that the virtual resources appear after the first virtual container is opened. According to the technical scheme, the interestingness of playing the multimedia resources is increased, the information transmission efficiency and the man-machine interaction efficiency are improved, and the conversion rate of the virtual resources is improved.

The invention relates to a digital human personalized emotion interaction method, which belongs to the technical field of emotion calculation, and comprises the following steps: S1, carrying out emotion quantification on interaction input of a user to obtain a pleasure-wake-dominate PAD emotion value in a continuous dimension space; s2, performing emotion state evaluation on the user interaction input emotion to obtain an interaction input emotion evaluation function; s3, calculating a digital human emotion transition probability matrix by using a Bayesian network; s4, calculating an emotional response calculation value of the digital human character corrected by the big five-factor model in the current emotional state; s5, the corrected emotion response passes through an emotion influence factor matrix, and a response with complex emotion features is output; and S6, performing PAD emotional space coordinate calibration on the emotional intensity of the digital person on the six basic emotions to obtain an emotional response of the digital person.

The invention provides an aquatic product traceability management method and system based on a block chain, and relates to the technical field of aquatic product management, the aquatic product traceability management method based on the block chain comprises the following steps: establishing an aquatic product traceability network platform, and obtaining aquatic product full life cycle data in real time; performing anomaly verification on the acquired aquatic product full life cycle data based on a data verification method, and storing the verified data in an encrypted form in an aquatic product tracing network platform through a curve encryption algorithm; collecting feedback information after the user inquires the aquatic product traceability information through the aquatic product traceability network platform; and analyzing the collected user feedback information, and adjusting and optimizing aquatic product full life cycle management according to an analysis result. According to the method, the data is stored to the block chain in an encrypted form through a curve encryption algorithm, so that the security and non-tampering property of the data are ensured, and comprehensive optimization and guarantee are provided for production and management of aquatic products.

The invention discloses a space neglect rehabilitation training system based on artificial intelligence. The system comprises a space neglect evaluation module used for evaluating the space neglect condition of a patient through a space neglect evaluation program; the rehabilitation program setting module is used for setting a rehabilitation program of the mobile wearable equipment by utilizing a rehabilitation program setting model according to the related data of the patient; the wearable equipment execution training command module is used for executing a corresponding rehabilitation task by the mobile wearable equipment according to the rehabilitation program set in the rehabilitation program setting module and recording the completion condition of the rehabilitation task; and the terminal collection feedback module is used for reading the training data of the patient, evaluating and judging the training compliance of the patient by utilizing the training data of the patient and constructing a training effect analysis model, and generating an adjustment strategy of a rehabilitation training scheme. Through the system provided by the invention, the training compliance and effect of the patient can be comprehensively and objectively evaluated, and the quality and efficiency of rehabilitation treatment are improved.

The invention discloses a cognitive impairment screening device and method based on an AR eye tracker and a brain-computer interface. The device comprises an augmented reality scene generation module, an eye tracker data acquisition module, a brain-computer interface data acquisition module and a cognitive impairment screening module. The augmented reality scene generation module is used for generating and displaying an augmented reality scene containing a cognitive task and acquiring task scene image information; the eye tracker data acquisition module is used for acquiring an eye movement data information set when a user completes a cognitive task in an augmented reality scene in real time; the brain-computer interface data acquisition module is used for acquiring an electroencephalogram signal information set in real time when a user completes a cognitive task in an augmented reality scene; and the cognitive impairment screening module is used for carrying out comprehensive evaluation processing on the acquired task scene image information, the eye movement data information set and the electroencephalogram signal information set to obtain cognitive impairment information of the user.

The invention is suitable for the technical field of advertisement pushing, and particularly relates to a digital media advertisement pushing method and system, and the method comprises the steps: dividing an internal region of a shopping mall into a plurality of sub-regions, each sub-region corresponding to a category, marking the deployment position of a Bluetooth gateway in each sub-region, and carrying out the pushing of a digital media advertisement through the Bluetooth gateways, reading a Bluetooth beacon signal of the visitor, extracting a unique identifier, acquiring consumption data of the visitor through pre-bound identity information, and determining an interest category of the visitor; acquiring video monitoring data of an entrance and an exit of the shopping mall, and identifying the number of visitors; and if the number is 1, passing the identity information. According to the method, the same item is pushed to all the visitors of the same bank, so that not only can personalized commodity recommendation and promotion information be pushed, but also attention and interaction of the visitors to the information can be increased, the attraction of the advertisement is improved, and thus the advertisement pushing accuracy and the participation degree of the visitors are improved.

The invention belongs to the technical field of heavy-load assembled building robots, and particularly discloses a rigid-flexible coupled deformable man-machine cooperation handle. The device comprises a U-shaped guide rail, a sliding mechanism arranged on the U-shaped guide rail in a sliding mode, a sliding rail locking device, a shear fork type telescopic device, a handle end locking device and a handle operation platform fixedly provided with an operation grip and a six-dimensional force sensor. The opening of the U-shaped guide rail faces upwards and is fixedly arranged on the back of the sucker mechanism; one end of the shear fork type telescopic device is rotationally connected with the handle operating platform through two rotary connecting rods, the other end of the shear fork type telescopic device is fixedly connected with the sliding mechanism, and a sliding rail locking device is arranged on the sliding mechanism; and a handle end locking device is arranged on one rotary connecting rod. The position of the handle can be flexibly adjusted and fixed, force interaction with the robot can be accurately achieved by means of the sensor on the handle, and the safety and efficiency of operation are all-dimensionally improved. The method can be widely applied to man-machine cooperation of prefabricated part installation.

According to the system for evaluating the treatment effect of the AUD patient through the electroencephalogram power spectrum characteristics, the electroencephalogram activity is captured through an electroencephalogram monitoring sensor, the electroencephalogram power spectrum characteristics in a resting state are calculated through a data processing unit, the electroencephalogram power spectrum characteristics are compared with a preset reference value or index modes in different psychological states, and the treatment effect of the AUD patient is evaluated. To identify features of brain activity of the patient. The preset value is based on a classification of subconsciousness and consciousness reactions of the AUD patient and statistically validated. The system judges the brain activity state and the treatment effect of the AUD patient according to the analysis result of the electroencephalogram power spectrum characteristics, and the analysis and judgment result is displayed through an output unit. The system can accurately evaluate the treatment effect of the new treatment method of subconsciousness memory degradation on the AUD patient, so as to provide accurate treatment and prevention strategies for the AUD patient.

The invention relates to the technical field of power system control, and discloses a flexible load control technical method based on a high-current switch built-in electric energy meter, which comprises the following steps: monitoring current and voltage in real time, and inputting data into a fuzzy logic control system; formulating a fuzzy rule, and judging a current state through fuzzy logic control; implementing a safe load removal and reset strategy for a super-capacitance power utilization scene, and executing an overcurrent opening operation; setting a maximum load threshold value according to different power utilization environment characteristics, and formulating a load control strategy; and a multi-stage power control scheme is implemented, and a load control security authentication mechanism is established. According to the method, electricity utilization characteristic research in typical application scenes is carried out, a load flexible control technology is researched in combination with a switch built-in scheme, a multi-scene and multi-cost control strategy is made through multi-stage power control, overcurrent opening and self-adaptive closing functions, flexible control over power consumers is achieved, and the electricity utilization management level is improved.

According to the distributed energy management system for the smart power grid and the optimal scheduling method thereof, efficient, intelligent and sustainable management of power resources is realized by integrating advanced data acquisition, processing, optimal scheduling, control execution and user interaction modules. The system adopts a multi-dimensional optimization scheduling strategy and a self-adaptive control strategy, and is combined with a digital twinning technology, so that the accuracy of real-time monitoring and prediction of the running state of the power grid is improved, and the response speed and the decision-making capability of the system are enhanced. The system can automatically adjust the operation parameters of the distributed power generation resources and the energy storage system, realizes accurate load control, improves the energy utilization efficiency, reduces the operation cost, and promotes the sustainable development of a power grid. Meanwhile, the transparency of the system and the participation degree of users are improved through the use of the user interaction module, and powerful technical support is provided for construction and operation of an intelligent power grid.

The invention provides an intelligent game role dynamic extension and cooperative combat method for a virtual battlefield, and relates to the technical field of intelligent games, the method adopts an UpDeT module to dynamically increase or reduce the number or type of agents according to the real-time battlefield condition and strategy requirements of the virtual battlefield; state features and action features corresponding to different agent types of different scenes are converted to a unified feature space through a feature mapping function; based on a self-attention mechanism of Transform, carrying out fusion processing on the feature representation of each agent to obtain a fusion feature; generating a cooperative combat decision according to the fusion feature and the communication information; therefore, the problems of fixed roles, poor expansibility and difficulty in strategy migration in the prior art are solved, the generalization ability of the intelligent game strategy is improved, and the intelligent game level is improved.

The invention discloses an activity recall matching method, system and device in a game scene and a medium, and the method specifically comprises the steps: setting activity configuration data according to business demand data of game activities, and storing the activity configuration data in a MySQL database, the activity configuration data comprising basic configuration data and advanced configuration data; constructing a Redis cache cluster, monitoring the MySQL database through a Canal component, and synchronizing the activity configuration data to the Redis cache cluster in real time; and acquiring user portrait attribute data from a preset game user database in real time, and determining an activity recall result of each user by matching the user portrait attribute data with the activity configuration data based on a preset activity rule matching engine. Accurate matching and personalized pushing of the activities are achieved, the activity conversion rate and the user participation degree are remarkably improved, and powerful support is provided for continuous optimization of game operation strategies.

The invention relates to the technical field of medical diagnosis accompanying services, and discloses an order matching calculation method for diagnosis accompanying services, which is used for optimizing the distribution and matching process of the diagnosis accompanying services. The method comprises the following steps of setting patient information, when the patient information is generated, marking the patient information as an accompanying diagnosis event, enabling one piece of patient information to correspond to one accompanying diagnosis event, collecting disease condition keywords, obtaining patient disease condition filling content information in the accompanying diagnosis event, and collecting disease condition keywords in the patient disease condition filling content information, the method comprises the steps of forming a set, setting an illness condition keyword library and danger degrees, executing a first person screening strategy according to an illness condition danger degree value of a patient and accompanying diagnosis person information in an accompanying diagnosis person set, generating a first target person set, executing a first order matching strategy according to the first target person set, and generating an accompanying diagnosis service order. And when the diagnosis accompanying service cycle corresponding to the diagnosis accompanying service order is finished, executing a personnel score optimization strategy.

The invention belongs to the technical field of medical systems, and provides a chronic disease management system which comprises a data acquisition module which monitors physiological indexes of a patient in real time through intelligent wearable equipment and automatically uploads measurement data; the data processing and analysis module automatically uploads the collected data to a cloud server, and establishes a disease prediction and risk assessment model; the health management module formulates a personalized health management plan for the patient according to the analysis result; the remote medical module provides remote communication and consultation between a patient and a doctor; the data sharing module is used for sharing and exchanging data among different medical institutions; the interaction module provides a patient operation interaction interface and registers and records basic information and illness state records of the patient; according to the invention, by establishing the disease prediction and risk assessment model, the patient is helped to know the health condition of the patient in advance and prevent the occurrence of diseases, and according to the analysis result of the disease prediction and risk assessment model, a personalized health management plan is made for the patient to realize accurate health management.

The invention discloses an engineering safety video generation method and system based on a generative large model. The method comprises the following steps of obtaining an application field and a theme requirement of a required engineering safety video; on the basis of application fields and theme requirements, a retrieval enhancement generation mechanism is adopted to retrieve in the multi-modal knowledge base to obtain related data, and a large language model is utilized to generate a training script copywriting; extracting cue words from the training script copywriting, and based on the cue words, generating a corresponding image by using a diffusion model; and converting the training script copywriting into an explanation audio, and finally synthesizing a virtual explanation video with synchronous mouth shapes by an audio driving model. The method can be suitable for a plurality of engineering scenes such as buildings, mining industry, tunnels, high-altitude operation and the like, has the characteristics of process automation, high content specialty, high generation efficiency and high cross-scene adaptability, and effectively improves the production efficiency and training effect of engineering safety education videos.

The invention relates to the technical field of ideological and political education, in particular to an ideological and political education interaction system based on social media, which comprises a social media monitoring module, a content analysis and classification module, an interaction mode optimization module and an education content updating module. According to the method, the participation enthusiasm and the core concern of the student are accurately captured by monitoring the online learning community and analyzing the social media data in real time, and the emotional tendency and the related discussion of the student are effectively collected by deeply analyzing the post content, so that the accurate classification of the content and the identification of mainstream and edge viewpoints are realized; the online education platform can adjust an interaction mode and increase simulation discussion according to actual responses of students, teaching is more attractive and targeted, the learning motivation and participation degree of the students are improved by dynamically updating education content and synchronizing social hotspots, the personalized and dynamic teaching process is achieved, and the teaching experience is improved. Therefore, the attraction and interactivity of education are effectively improved.

The invention discloses an intelligent evaluation method for an ideological and political education effect, which comprises the following steps of: firstly, capturing data for spreading ideological and political education contents from a plurality of new media platforms by using a web crawler, storing the data in a local database, and then preprocessing the data; constructing an ideological and political education effect evaluation model, and performing quantitative evaluation on the ideological and political education effect of the preprocessed data by using machine learning and natural language processing technologies based on multi-dimensional indexes; and finally, analyzing and visually displaying the evaluation result of the data, and comprehensively judging the spreading degree of the ideological and political education according to the quantitative evaluation result of the ideological and political education effect evaluation model. Through cross-platform data capture, big data analysis, sentiment analysis, deep learning and other methods, the ideological and political education effect under new media platform propagation is comprehensively and dynamically evaluated.

The invention discloses a lung cancer early screening database management system, which relates to the technical field of database management and comprises a data acquisition module, a data arrangement module, a calculation module and an analysis module. The system integrates detection results of multiple biomarkers and individual clinical characteristics, provides a more accurate and more comprehensive lung cancer risk assessment database management system, can significantly improve the screening accuracy, reduces unnecessary excessive diagnosis and treatment, and improves the screening efficiency. The system considers clinical feature information such as age, gender, smoking history and family history, and constructs a comprehensive risk scoring system, so that the screening accuracy is further improved, the lung cancer risk of an individual can be comprehensively reflected, and the possibility of missed diagnosis and misdiagnosis is reduced.