424 results about "Skill level" patented technology

The invention provides an intelligent human resource training recommendation method and system, and relates to the technical field of data processing, and the method comprises the steps: obtaining post data, skill data, performance data, training records and development target data of a target, building an employee database, and constructing a knowledge graph; post data, skill levels, performance expressions, training records and individual development targets of the employees are integrated to form a comprehensive portrait; dividing all courses according to difficulty levels, selecting courses with corresponding difficulty according to post requirements and performance data of the employees, and generating a group of preliminary course lists matched with current skill levels and post requirements of the employees; semantic analysis is carried out on skill requirements of employee portraits and recommended course contents, a semantic analysis result is obtained, and according to employee portrait data, a semantic matching algorithm is used to calculate the matching degree between the employees and each training content; and according to the matching degree scores of the employees and the training contents, generating a course list subjected to semantic matching optimization.

Apparatuses, systems, and methods are provided for training employees are provided. The method comprises: (1) receiving, by one or more processors from a user device associated with an employee, an answer associated with a question; (2) generating, by the one or more processors via a chatbot, values associated with one or more metrics of the answer; and / or (3) performing, by the one or more processors, at least one of the following: (i) determining a skill level of the employee based upon the values associated with the one or more metrics of the answer; (ii) presenting, to the employee via the user device, a second question based upon the values associated with the one or more metrics of the answer; and / or (iii) presenting, to the employee via the user device, an explanation based upon the values associated with the one or more metrics of the answer.

The invention discloses a student employment information management system based on artificial intelligence, and relates to the technical field of student employment management, and the system comprises the following components: an intelligent skill improvement planning module which constructs a skill map covering different industries and vocations, combines the vocational planning of students and the current skill level, and carries out the intelligent skill improvement planning; a personalized ability improvement plan is automatically generated by using a machine learning algorithm, students are helped to improve themselves in a targeted manner, transparency and normalization of a young employment market are significantly improved by introducing an honesty employment credit scoring system, and the system sets a negative list system for students with default behaviors, so that the system can improve the ability improvement efficiency of the students. According to the technical scheme, dishonest behaviors in the employment market are effectively restrained, the measure not only protects legal rights and interests of enterprises and avoids recruitment risks caused by information asymmetry, but also promotes honesty construction of student groups, improves credibility of the whole employment environment, and accurately evaluates and supervises credit of students.

The invention belongs to the technical field of artificial intelligence, and particularly relates to a multi-modal mixed interview question generation system and method based on artificial intelligence. According to the method, customized interview questions are provided for candidates with different backgrounds and different skill levels by dynamically selecting questions based on candidate resumes and knowledge maps, the question difficulty and knowledge emphasis are automatically adjusted through multiple rounds of answering effects and interviewer labeling data, the effectiveness and flexibility of interview evaluation are improved, and the interview evaluation efficiency is improved. Answering results and behavior anomaly detection are fused, knowledge mastering is evaluated, potential non-behavior factors can be found, manual question screening time is shortened through an automatic process, consistency of interview experiences of different candidates is guaranteed, subjective prejudice is reduced, new knowledge documents and post description can be accessed at any time, a multi-modal graph is continuously iterated, and the method is high in practicability and high in practicability. And changes of new technical fields and new post requirements are adapted.

The invention discloses an aircraft surface curved surface skin replacing method and a replacing device thereof, a primary hole is manufactured according to a reverse hole drill bushing, then the coaxiality of a curved surface drill jig hole is verified according to the reverse hole drill bushing and a step pin, finally, a replaceable drill bushing is used for reaming step by step, and accurate skin hole manufacturing is achieved. According to the method, a traditional curved surface skin replacing, assembling and machining method is changed, the difficulty of replacing the curved surface skin is lowered, the requirements for the skill level and experience of an operator are lowered, the scrap proportion of parts is reduced, the rework assembling quality is improved, the rework efficiency is improved, and the rework manufacturing cost is lowered.

The invention discloses a game level generation recommendation method, system, device and medium, and the method specifically comprises the steps: carrying out the combined modeling of multi-modal data through a multi-task learning network, and generating a dynamic user portrait vector, the main task of the multi-task learning network is used for predicting the skill level of a player, and the auxiliary task of the multi-task learning network is used for predicting the skill level of the player; auxiliary tasks of the multi-task learning network are used for classifying interest labels and analyzing emotional tendencies; inputting the dynamic user portrait vector into a dual-channel generative adversarial network, generating a candidate level set, and screening initial recommended levels through a playability evaluation algorithm; and calculating the matching degree between the skill score of the user and the level challenge degree in real time according to a difficulty-skill dynamic balance model, and dynamically adjusting the level parameters of the initial recommendation level through the matching degree to obtain a first recommendation level. According to the method, key problems in traditional game level design and recommendation are effectively solved, and efficient, personalized and real-time game level generation and recommendation with optimized user experience are realized.

The invention provides a remote training method and system based on virtual reality. The method comprises the following steps: performing personalized customization processing on a training environment by utilizing a professional background, a skill level and a learning target of a student to obtain a simulation operation scene; according to the simulation operation scene, carrying out natural language processing algorithm analysis processing on the obtained language instruction, generating an operation prompt, superposing the operation prompt into a visual interface of a student through an augmented reality technology, and carrying out real-time monitoring and automatic correction on an operation process of the student to obtain a personalized guidance scheme; and based on the personalized guidance scheme, performing decision tree algorithm classification analysis processing on the behavior data of the trainees, and comprehensively evaluating the performance of the trainees from multiple dimensions in combination with an educational psychology theory to obtain a multi-dimensional performance evaluation report. According to the technical scheme provided by the invention, the pertinence and effectiveness of training are remarkably improved.

The invention discloses a multi-dimensional candidate matching evaluation method and system, and relates to the technical field of human resource management. The method comprises the following steps: constructing an evaluation index system containing multiple dimensions according to a target post demand; collecting multi-dimensional data of candidates, wherein the multi-dimensional data comprises personal backgrounds, skill levels, character traits and occupational experiences; based on the evaluation index system, performing standardization processing on the multi-dimensional data of candidates; calculating the score of each dimension in the evaluation index system according to the standardized multi-dimensional data; calculating a matching weight of each dimension through a preset weight distribution model; and according to the score and the matching weight of each dimension in the obtained evaluation index system, calculating the comprehensive matching degree of the candidate and the target post, and outputting a matching degree analysis report. Through multi-dimensional comprehensive evaluation, a weight distribution model and a personalized matching degree analysis report, more objective and scientific candidate matching evaluation is provided, and the accuracy of recruitment decision is improved.

The invention discloses a power plant thermotechnical DCS comprehensive training system, and relates to the technical field of thermotechnical training, and the system comprises the steps: carrying out the technical analysis of a power plant thermotechnical process based on a DCS comprehensive training system, and determining the training demand information; determining a plurality of learning paths, and constructing DCS training environment parameters; obtaining user test data, making a plurality of training plans for training based on the user test data, and determining a plurality of training results; screening the plurality of training plans to generate a recommended review list; and obtaining a thermotechnical training information set, and performing operation optimization verification on the power plant. The technical problems that in the prior art, a complex operation scene of a thermal DCS (Distributed Control System) of a power plant is difficult to truly simulate, and personalized training paths for different user requirements and skill levels are lacked, so that training pertinence is insufficient, learning evaluation is incomplete, and skill improvement efficiency is poor are solved. The technical effects of enhancing the training effect and improving the skill improvement efficiency are achieved.

The invention discloses a driving skill level classification method based on multi-dimensional data fusion. The method comprises the following steps: (1) acquiring behaviors, physiological data and environmental data of a driver in real time through a driving simulator, eye movement tracking glasses and a physiological sensor; and (2) processing and analyzing the multi-dimensional data by using a CNN-LSTM classifier (CNN-LSTM-attention) so as to evaluate the skill level of the driver. According to the method, control skills and cognitive skills are comprehensively evaluated, key parameters including steering, braking, eye movement frequency, concentration duration and the like are captured in real time by using a driving simulator, eye movement tracking glasses and a physiological sensor, and a CNN-LSTM-attention classifier is constructed. According to the method, the complexity of the scene is quantified, the classifier is trained according to different scenes, the accuracy is improved, and meanwhile, the reliability of driving ability evaluation is enhanced by using multi-dimensional data.

According to another embodiment, a method may include: receiving, at a centralized controller, a play data for players using a plurality of basketball hoop devices, the play data comprising shot data comprising ball flight trajectory data, shot angle data, shot distance data, and shot success data; calculating, by the centralized controller, a skill level for each of the plurality of players using the play data; applying, by the centralized controller, a skill leveling algorithm to the shot data to determine parameters for each basketball hoop device based on the skill level of each of the players, wherein the parameters comprise a hoop height, a hoop angle, and a hoop distance; and communicating, by the centralized controller, the parameters to local controllers at the respective basketball hoop device, wherein the local controllers control actuators at the respective basketball hoop devices to implement the parameters.

The invention discloses a robot arm floating clamp and a debugging method thereof, belongs to the field of machine manufacturing, and solves the problem that a teaching robot arm cannot be quickly debugged in the prior art. A flange plate is fixed on the manipulator, a pneumatic chuck is arranged on the flange plate, a clamping jaw is arranged on the pneumatic chuck, a floating module is arranged between the flange plate and the pneumatic chuck, the floating module comprises a middle connecting plate and a bottom plate, the middle connecting plate is connected with the flange plate in a sliding mode, and the middle connecting plate is connected with the bottom plate in a sliding mode. The two sides of the middle connecting plate are respectively provided with an adjusting block I, and the adjusting blocks I are connected with the flange plate through springs I. Adjusting blocks II are arranged on the two sides of the bottom plate respectively, and the adjusting blocks II are connected with the middle connecting plate through springs II. A linear guide rail and a spring structure are adopted, so that the clamp can freely float within a certain range, rapid debugging and teaching of the robot arm are achieved through the dynamic offset, and the requirement for the skill level of debugging personnel is lowered.

The invention relates to the technical field of social humanistic science research, in particular to an engineer engineering skill proficiency evaluation method, which comprises the following steps: identifying the core skill category of an engineer, collecting the skill level input of the engineer to establish a personnel skill inventory, generating original skill data input, and inputting based on the original skill data. According to the method, through identification of core skill categories of engineers and collection of skill level input, and in combination with structural analysis of task on-time completion rate, a direct mapping relation is generated between the engineer ability and actual performance data, and the deviation that ability evaluation depends on subjective impressions singly is avoided. On the basis of clear division of project stages and process nodes, the change trend of skill requirements is quantized into skill numerical value weights in different stages, and skill evaluation has time sequence dynamics by extracting associated information between the stages and the skill.

The present invention relates to an intelligent wooden man robot and motion analysis system capable of measuring skill. The system analyzes the weights of the hitting points in each area of ​​the wooden man according to the distance from the key hitting point; uses a pressure sensor to obtain the force data of hitting the wooden man; monitors the hitting points and force of the wooden man, and calculates the hitting skill value in combination with the weights of the hitting points in each area of ​​the wooden man; uses a K-means cluster analysis method to obtain the skill level of different hitting skill values, and emits lights of different brightness at the hitting points according to different skill levels; extracts the image feature data of the hitting action video stream, compares it with the standard action image feature data, and evaluates the trainee's action in combination with the corresponding skill level; and emits lights of different colors according to the evaluation results of the hitting action. The present invention solves the problem that it is difficult to interact with lights according to the accuracy of different hitting parts of the wooden man in the prior art to accurately evaluate the trainee's skill and action.

The invention provides a curling match video description method based on a large language model. According to the method, the videos are intelligently analyzed, and detailed text description is generated, so that curling players can more deeply know each detail of a match with less time, detailed tactical analysis and action guidance are provided, and the skill level of the players can be improved more quickly. According to the method, the advantages of a video analysis technology and a large language model are combined, comprehensive, detailed and deep natural language description of curling match videos is achieved, the accuracy and comprehensiveness of curling match video description are improved, and richer match information and analysis means are provided for audiences and coaches.

The invention discloses an intelligent sharing yoga lesson booking platform system, and relates to the technical field of intelligent sharing, which comprises the following steps: a user registers an account and verifies the identity; analyzing social media activities, comments and feedback contents of the user, and identifying an emotional tendency of the user by using a natural language processing technology; personalized course recommendation is provided; evaluating the yoga skill level of the user, and planning an optimal learning path for the user; the user reserves a course according to the recommended course list and completes a payment process; feedback is submitted after the course ends, so that personalized course recommendation and learning path planning are improved; according to the method, highly personalized course recommendation is provided by using a natural language processing technology, so that the user satisfaction is improved; the skill level is evaluated and an optimal learning path is planned by applying a reinforcement learning algorithm, so that skill improvement is promoted; and the recommendation strategy and the learning path planning are continuously improved by collecting user feedback, so that the self-learning and adaptive capacity of the system is enhanced, and the service quality is further improved.

The invention discloses a building safety education training system based on interactive experience, relates to the technical field of construction site safety education, and aims to solve the problems that traditional building worker safety education lacks pertinence and is difficult to meet specific safety requirements of various types of work, and the teaching mode is relatively single. The system comprises a database, a personalized learning recommendation module, an interactive learning module and a learning progress and achievement tracking module. The database is used for pre-storing safety knowledge of various construction work types; the personalized learning recommendation module is used for screening and recommending learning content suitable for the worker from a pre-stored database covering safety knowledge of various construction work types according to the work type information and learning history of the construction worker, and the learning content comprises a document and a video course. The method has the advantages that precise education content conforming to the work type and the knowledge level of each worker is provided for the worker, and the safety awareness and the skill level of the building worker are improved.

The invention relates to a skill grade evaluation method and system for talent management. The skill grade evaluation method comprises the steps of obtaining target occupational information, corresponding occupational element information and assessment index information; constructing a multi-channel evaluation model based on the occupational element information and the assessment index information; obtaining target skill data and performing preliminary evaluation to generate a standardized evaluation result; obtaining target historical behavior data and extracting skill mode features and implicit capability features; inputting the skill mode features and the implicit capability features into a multi-channel evaluation model to generate a personalized evaluation result; in conclusion, according to the skill grade evaluation method and system for talent management provided by the invention, standardized evaluation is carried out on skill data by constructing a multi-channel evaluation model, and dynamic correction is carried out in combination with implicit features extracted from historical behavior data; the method has the advantages of dynamically capturing skill demand changes, identifying skill synergistic effects, mining recessive ability characteristics and providing timeliness occupational planning.

The invention discloses a method, a system and a device for testing and calibrating an electric control handle, a movement device is adopted to control the movement of the electric control handle, the automatic testing and calibration of the electric control handle are realized by collecting the displacement angle and output in the testing process of the electric control handle, the influence of the skill level of an operator can be avoided, the efficiency is improved, and the testing accuracy is improved. And in the calibration process, through iterative adjustment of the relation line, the final performance of the electric control handle is enabled to be better, and the precision of the electric control handle is improved.

The invention relates to the field of project intelligent management, and provides an electrical construction task intelligent management system and method, and the method comprises the steps: firstly obtaining the number of a target building, searching a corresponding building information model according to the number, then carrying out the deep building analysis of the target building based on the information model, so as to determine the construction task level, and at the same time, carrying out the construction task management of the target building. The working states and working information of constructors are collected and sorted to form a total set of constructors, the working information of the constructors in the to-be-distributed state in the total set is further analyzed to evaluate the skill levels of the constructors, and finally, the working states and working information of the constructors are analyzed. And according to the determined construction task level and the skill level of the to-be-allocated constructor, scientifically and reasonably allocating the construction task. In this way, reasonable configuration between construction tasks and constructors can be ensured, and then the overall construction efficiency and quality can be improved.

The invention relates to the technical field of internet data processing and resource scheduling, and discloses an intelligent order sending method and system for housekeeping service and a storage medium, and the method comprises the steps that a server side receives original order information containing house investigation data; calling a spatial granularity decomposition model to analyze the order into independent operation area sub-tasks, and calculating the lowest skill level demand in combination with the feature vector; attribute vectors such as comprehensive skill levels and real-time coordinates of service personnel are obtained; constructing a dynamic bipartite graph matching model by taking the subtask set and the attributes of the service personnel as input; an optimal mapping relation list is determined by solving the maximum value of an objective function, and a dispatching instruction is sent. The method further comprises an attendance checking judgment step based on a geofence and a closed-loop iteration step of dynamically updating skill levels according to attendance checking and evaluation data. According to the method, refined disassembly and global optimal scheduling of housekeeping tasks can be realized, and the resource allocation efficiency and the service quality are remarkably improved through a dynamic closed-loop mechanism.

The invention relates to the technical field of intravenous drug configuration teaching, in particular to a teaching system for intravenous drug configuration based on deep learning, which constructs a three-dimensional scene and collects operation data of a user in a virtual environment by acquiring live-action video data of intravenous drug configuration. Through semantic segmentation, an operation track is tracked in combination with a long and short-term memory network, a variable path matrix is generated, an operation score is generated by using a convolutional neural network, wrong operation is identified in time, and real-time feedback is provided. According to the method, training can be carried out only through a computer or VR equipment without depending on a large number of sites and equipment, students are helped to carry out timely correction in each step of operation through model evaluation and real-time feedback, and the operation accuracy and the learning effect are improved. Difficulty gradient adjustment is carried out in combination with scores, it is ensured that the training difficulty is matched with the skill level of students, personalized teaching is achieved, and the teaching effect is improved.

The invention provides a real-time adjustment method and system for a virtual motion scene in meta-universe intelligent motion, and relates to the technical field of meta-universe, and the method comprises the steps: obtaining the motion parameter information of a user, calculating a scene matching score, dividing a difficulty level region, and detecting the motion state and physiological data of the user in real time; and calculating a skill grade score and dynamically adjusting scene difficulty distribution and rendering parameters. According to the method, the accurate matching of the virtual scene and the exercise ability of the user is realized, the immersion and individuation degree of interaction experience are improved, meanwhile, the system resource allocation is optimized, and the smooth operation of the meta-universe exercise environment is guaranteed.

An interactive basketball board game system having a substantially planar surface serving as a game court with removable perimeter borders that define a playing area. The system includes basketball hoops and backboards secured to end borders, and miniature basketballs. The court surface features magnetic-receptive material enabling interchangeable court illustrations. The system incorporates authentic basketball simulation mechanics requiring balls to bounce once before shooting attempts, foul calling systems, and alternating possession rules. The compact, portable design allows for easy assembly, disassembly, and storage while providing comprehensive basketball gameplay experiences suitable for various skill levels and player counts.

The invention discloses a disabled training support evaluation system, and relates to the technical field of disabled training, and the system comprises a multi-dimensional evaluation module, a quantitative evaluation module, a qualitative evaluation module, and a visual report module. According to the system, a multi-dimensional comprehensive evaluation system including knowledge mastering, skill application, learning attitude and emotion development is constructed, the learning effect of the disabled students is comprehensively covered, and the multi-dimensional evaluation not only pays attention to the knowledge and skill levels of the students, but also deeply investigates the learning attitude and emotion development conditions of the students, so that the learning efficiency of the disabled students is improved. Therefore, one-sidedness possibly brought by single-dimension evaluation is avoided, meanwhile, the system adopts a qualitative and quantitative combined mode, interference of subjective judgment is reduced, objectivity and accuracy of evaluation results are ensured, the comprehensive and objective evaluation system provides more accurate and reliable feedback for trainees and trainees, and the training efficiency is improved. And the two parties can better understand the learning progress.

The invention relates to the technical field of sports medicine data analysis, and discloses a sports medicine data intelligent analysis method and device.The sports medicine data intelligent analysis method comprises the following steps that firstly, a unified time axis is set, and then physiological index data, sports performance data, sports injury data and rehabilitation process data of a single athlete are collected according to the time sequence; classifying to form a data set; 2, analyzing the skill level of a single athlete in an uninjured state, and generating a corresponding level coefficient; 3, the health level of a single athlete in the injury state is analyzed, a corresponding injury coefficient is generated, and multi-dimensional analysis is more comprehensive; 4, a horizontal threshold value and an injury threshold value of a fixed range and a monitoring period of a fixed duration are set, the health state and the injury risk of a single athlete are evaluated in combination with the horizontal coefficient and the injury coefficient, a corresponding early warning signal and a corresponding exercise suggestion are generated, any node in a time axis has the corresponding horizontal coefficient or injury coefficient, and the health state and the injury risk of the single athlete are evaluated. And the intelligent evaluation precision is high.

The invention discloses a skill grade evaluation system for talent management. The skill grade evaluation system comprises a demand analysis module, a data collection and preprocessing module, a skill mapping module, a skill level analysis module, a development path planning module and a system optimization module. The invention belongs to the technical field of human resource management, and particularly relates to a skill grade evaluation system for talent management, which is characterized in that skill data are converted into feature vectors through a data preparation unit, a Gaussian mixture model is defined, and model parameters are iteratively optimized through a parameter estimation unit; calculating the posterior probability that a new data point belongs to each skill category through the trained model, and achieving the classification of skill levels; the skill level is analyzed based on a decision tree and an entropy theory, accumulated residual entropy is calculated to evaluate the uncertainty of overall skill distribution, the influence degree of residual uncertainty analysis features on skill evaluation is calculated, and optimal features are selected according to information gains to achieve skill level evaluation.

To allow a work orderer to easily select an operator having a skill level appropriate to the work having been ordered by the work orderer.SOLUTION: A server 10 includes: a communication unit 11 which receives, from an orderer terminal 200, work request information containing a work content and work time period for the work content having been input by a work orderer; a requested skill level determination unit 12 which determines a requested skill level indicating a skill of remote operation requested to an operator by the work orderer on the basis of the work request information received by the communication unit 11; an operator database 18 which stores a skill level of each of a plurality of operators; and a list information generation unit 13 which extracts operators having skill levels of the requested skill level or higher from the operator database 18, and generates the operator list information for presenting the extracted operators to the work orderer. The communication unit 11 transmits the operator list information to the orderer terminal.SELECTED DRAWING: Figure 1

The invention provides a post recommendation and learning path generation method based on skill level entity extraction, and relates to the technical field of person and post matching, and the method comprises the steps: obtaining job seeker data and post data; extracting skills and skill levels of job seekers and posts from the data by using a large language model (LLM), and confirming the extracted skill data through an ESCO classification method; on the basis of the extracted skill data, according to the defined similarity constraint and calculation formula of the job seekers and the posts, similarity calculation is carried out on the job seekers and the posts, and post recommendation is carried out on the basis of the similarity; and analyzing the extracted skill data of the job seekers and the posts to form a visual learning path diagram. By the adoption of the scheme, accurate matching and recommendation of the job seeker and the post are achieved.

A method includes monitoring in a gaming session game play of a first player playing a game on a device of a first platform, and monitoring game play of a second player playing the game on a device of a second platform. A first valuation of a performance metric measuring gaming effectiveness is determined for the game play by the first player. A second valuation of the performance metric is determined for the game play by the second player. A difference between the first valuation and the second valuation does not satisfy a threshold band of operation that is based on global skill levels of the first and second players. The game play of the first player is augmented to modify the first valuation so that the threshold band of operation is satisfied in order to normalize effectiveness of playing the video game between the first and second players.