354results about How to "Increase motivation" patented technology

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 provides a UE5-based automatic construction and release method, and relates to the technical field of software development, the UE5-based automatic construction and release method comprises a construction module and a release module, and the construction module comprises the basic steps of construction triggering, pre-construction task execution, client and server packaging, log recording and automatic alarm. The release module comprises the basic steps of differential packet generation, version detection and automatic release, the intelligent prediction trigger carries out deep learning analysis on project development historical data, the peak period of code submission and the code conflict risk can be accurately predicted, construction is automatically triggered in the low-risk and resource idle period, and the construction efficiency is improved. The problem of low resource utilization efficiency caused by lack of multi-dimensional comprehensive judgment in a traditional construction triggering mode is effectively avoided.

The invention discloses rock crushing and coring equipment for geotechnical engineering investigation, and belongs to the technical field of drilling equipment. The rock crushing and coring equipment for geotechnical engineering investigation comprises a drilling tool, a sampling barrel and a high-pressure water supply device, and further comprises a triggering part, a coring part and a control part, and the triggering part is arranged at the end, away from a drill bit of the drilling tool, of the sampling barrel; a first sliding groove is formed in the water flow reversing part, the high-pressure water supply device communicates with a water outlet in the drill bit through the water flow reversing part, the water flow reversing part communicates with the first sliding groove, and the water flow reversing part is used for communicating the high-pressure water supply device with the first sliding groove when the triggering part is triggered; one end of the sliding sleeve is hermetically and slidably connected into the first sliding groove; the cut-off part is connected with the other end of the sliding sleeve, and when high-pressure water is introduced into the first sliding groove, the sliding sleeve drives the cut-off part to move into the sampling barrel. According to the rock crushing and coring equipment for geotechnical engineering investigation, the drill bit can be cooled by using high-pressure water, the abrasion of the drill bit is reduced, and a rock core is cut off by using the high-pressure water as power, so that the integrity of the obtained rock core can be ensured.

The invention belongs to the technical field of artificial intelligence, and relates to an occupational interest evaluation method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining personal basic information, existing occupational experience and future occupational tendency of a user; a question recommendation model is adopted, and according to the personal basic information, the existing occupational experience and the future occupational tendency, occupational interest evaluation questions for the user are obtained; rewriting the occupational interest evaluation question according to the question rewriting cue word by adopting a language model to generate a rewritten evaluation question; obtaining reply content of the user for the rewritten evaluation question; and predicting the occupational interest tag of the user according to the reply content by adopting a tag classification model. In addition, the invention also relates to a block chain technology, and data such as personal basic information, existing occupational experiences and future occupational tendencies can be stored in a block chain. According to the invention, the participation degree of the user and the accuracy of the evaluation result can be improved.

The invention relates to a source network load storage collaborative planning method and system considering a multi-agent mixed game, and the method comprises the following steps: building a power distribution network collaborative planning model considering a source network load storage agent master-slave-cooperation mixed game, and enabling the power distribution network collaborative planning model to be a double-layer model, comprising an upper-layer master-slave game sub-model of a power distribution network operator and other subjects and a lower-layer cooperative game sub-model between a source load storage side subject; and solving the power distribution network collaborative planning model by adopting a solving strategy combining a target cascade analysis method and an adaptive coefficient alternating direction multiplier method to obtain an optimal planning scheme of a new line, a distributed power supply and an energy storage device. Compared with the prior art, the method has the advantages that efficient configuration and coordinated utilization of source network load storage resources can be realized, and the planning reliability is improved.

The invention discloses a household rehabilitation monitoring system for the disabled, and relates to the technical field of medical rehabilitation, and the system comprises the following components: a VR training platform, an electroencephalogram acquisition and processing module, a brain wave analysis and feedback module, and a personalized training content generation module. By integrating the VR training platform and the electroencephalogram collection and analysis technology, high personalization and intelligentization of rehabilitation training are achieved, the system can analyze electroencephalogram signals of a user in real time, the attention level, the emotional state and the rehabilitation progress of the user are accurately evaluated, the training difficulty and content are dynamically adjusted accordingly, and the rehabilitation training effect is improved. The real-time feedback and adjustment mechanism ensures that rehabilitation training is always matched with the current state of the user, so that the rehabilitation training effect is remarkably improved, meanwhile, generation of personalized training content meets specific requirements of different users, and the training experience and satisfaction degree of the user are improved.

The linear guide rail with the cooling structure comprises a guide rail body and a sliding block, a sliding groove is formed in the sliding block, the sliding block is arranged on the guide rail body in a sliding mode through the sliding groove, the guide rail body is installed on a gasket, a first installation groove in the length direction of the guide rail body is formed in the surface of the gasket, and a cooling pipe is arranged in the first installation groove. An air cooling structure is further arranged in the sliding block. According to the utility model, the cooling pipe is laid on the gasket, and the circulating cooling liquid is introduced into the cooling pipe to cool the guide rail above the cooling pipe; an air cooling structure is further arranged in the sliding block, the sliding block is cooled in the movement process of the sliding block, power in a certain direction can be increased for the sliding block by closing an air outlet in the front end or the rear end of the air cooling structure, and the movement speed of the sliding block is increased.

The invention discloses a multi-microgrid operation optimization method considering supply and demand flexible double responses. The method comprises the following steps: establishing a cost optimization model of multi-microgrid electric energy cooperation sharing; a gas turbine, a waste heat boiler and an organic Rankine cycle power generation device are introduced to construct a supply side response model for flexible output of electricity and heat energy of the cogeneration unit; a demand side establishes a demand side flexible response model by considering transferability and replaceability of the electric heating load; and a multi-microgrid electric energy sharing cooperative operation model is established based on the Nash negotiation theory, and then the model is decomposed into a microgrid alliance benefit maximization sub-problem and a benefit distribution sub-problem. And in the cooperative income distribution sub-problem, the micro-grids negotiate with each other by taking the electric energy contribution and the marginal contribution degree of the micro-grids in cooperation as bargaining capabilities, so that fair distribution of cooperative income is realized. According to the optimization method provided by the invention, the advantages of flexible supply and demand and resource coordination and complementation can be brought into full play, and the condition of unreasonable income distribution of each micro-grid in the multi-micro-grid cooperation system is improved.

The invention discloses a collaborative scheduling method and system for a centralized energy storage power station to participate in a joint market, and the method comprises the steps: enabling an energy storage station and a new energy station to form a joint system, taking the maximization of the income of the joint system in a green power and spot market as an optimization target, and constructing a joint system optimization scheduling model considering a green power transaction electric quantity decomposition curve; carrying out optimization scheduling on the capacity of the shared part of the energy storage; independently participating in power market competition by using the residual capacity after energy storage sharing, constructing a double-layer optimization model of participating in spot goods-peak regulation-green power combined market by energy storage, and solving the double-layer optimization model to obtain an energy storage operation strategy; and calculating the contribution degree level of each subject in the joint system, calculating a profit distribution proportion according to the contribution degree level, and further performing profit distribution on each subject in the joint system. According to the invention, flexible diversity of participation of centralized energy storage in multiple types of markets and multiple operation modes can be brought into full play, so that the energy storage utilization rate and the operation income are improved.

The invention relates to the technical field of electricity transaction, in particular to a green electricity-carbon market linkage-based green electricity transaction matching method, which comprises the following steps of S1, data acquisition and preprocessing: acquiring green electricity transaction data, and cleaning, screening and preprocessing the acquired green electricity transaction data; s2, establishing a green electricity-carbon market linkage model: establishing the green electricity-carbon market linkage model; s3, green electricity transaction matching calculation: calculating an optimal green electricity transaction matching scheme to realize cost and benefit optimization; s4, risk assessment and control: assessing the risk of the transaction scheme, and formulating risk control measures; s5, transaction execution and monitoring: executing the transaction according to the transaction scheme and performing real-time monitoring, collecting and analyzing data, and dynamically adjusting and optimizing the scheme; according to the invention, energy structure optimization and greenhouse gas emission reduction targets are promoted to be realized, and powerful support is provided for development of renewable energy sources and carbon emission reduction.

The invention discloses an electric vehicle ordered charging and discharging method and system, and the method comprises the steps: obtaining the number of electric vehicles meeting the requirements in a target range, the number of agents, and the parameter information of the electric vehicles, and building a V2G-based electric vehicle response capability constraint condition according to the parameter information; establishing a response capability value acquisition rule of the electric vehicle under an electric vehicle response capability constraint condition based on V2G, and establishing an electric vehicle charging and discharging strategy double-layer optimization model containing the response capability value of the electric vehicle; and according to an improved multi-population genetic optimization algorithm, solving the electric vehicle charging and discharging strategy double-layer optimization model to obtain the optimal charging power of each time period so as to obtain a final electric vehicle charging and discharging strategy. By optimizing the scheduling strategy, the power grid load fluctuation can be effectively reduced, and the power grid operation stability is improved. Meanwhile, by considering the scheduling willingness and scheduling capability of the electric vehicle user, the user can obtain the maximum income when participating in the V2G plan, so that the participation enthusiasm of the user is improved.

The invention relates to the technical field of education. The invention discloses a smart vocational education method and a control system thereof, and the system comprises a data collection module which is used for collecting learning data of students, a data processing and analysis module which carries out the comprehensive scoring of the learning data of the students through a scoring formula, and a personalized recommendation module which is used for initializing the learning paths of the students, collecting the learning feedback of the students, and carrying out the comprehensive scoring of the learning data of the students. The system comprises a data acquisition module used for acquiring data, a data processing and analysis module used for adjusting a learning path until a preset learning target is reached, a teaching evaluation module used for comprehensively evaluating various indexes of students, and a system integration module used for integrating the data acquisition module, the data processing and analysis module, the personalized recommendation module and the teaching evaluation module. The intelligent vocational education control system provides highly personalized learning experience for students through student feature recognition, adaptive learning path adjustment and comprehensive teaching effect evaluation. The system can dynamically adjust the learning resources and activities according to the learning characteristics and demands of each student, thereby improving the learning efficiency and motivation.

The invention discloses a cloud energy storage operation mechanism based on thermal inertia of an urban building air conditioning system, which relates to the field of energy storage and comprises the following steps: (1) establishing a fixed-frequency air conditioner virtual energy storage monomer model and an aggregation model based on the thermal inertia of the urban building air conditioning system; (2) designing a cloud energy storage operation mechanism taking air conditioner aggregation virtual energy storage as a main leasing resource, and establishing a cloud energy storage operator model, a cloud energy storage user model and a transaction pricing strategy; and (3) solving the cloud energy storage operation model by taking the minimum power consumption cost of the user as a target, and distributing and evaluating the social total welfare brought by the cloud energy storage mechanism. According to the energy storage operation mechanism provided by the invention, the electricity consumption cost of the subscribing user can be effectively reduced, and the early-stage investment and the later-stage operation and maintenance cost of an operator are reduced; and under the dual-carbon background, the strategy is also beneficial to the real-time consumption of new energy on the user side.

The invention provides a decentralized hierarchical federated learning method and system, and edge servers. The method comprises the following steps: a plurality of edge servers respectively receive gradient ciphertexts sent by different participant clients; the plurality of edge servers aggregate the received gradient ciphertext based on a secure multi-party computing protocol to obtain an aggregation model ciphertext; according to the secure multi-party computing protocol, in a non-trusted multi-user network, a plurality of edge servers respectively holding different gradient ciphertexts jointly compute aggregation model ciphertexts based on the gradient ciphertexts, and each edge server only obtains part of data in the aggregation model ciphertexts. The gradient ciphertext held by the edge server is not leaked to other edge servers; and the edge server issues the aggregation model ciphertext to the participant client. By using the scheme of the invention, the security of model aggregation can be improved.

A low-carbon economic dispatching method for a combined cooling, heating, power and hydrogen supply type comprehensive energy system comprises the steps that firstly, a combined cooling, heating, power and hydrogen supply type comprehensive energy system model is established in a simulation platform, then a comprehensive energy multi-target optimization dispatching model based on stepped carbon transaction is established, and finally an optimization dispatching solving method for the combined cooling, heating, power and hydrogen supply type comprehensive energy system is established. According to the invention, a high-efficiency and low-carbon comprehensive energy system transaction mechanism is realized, a hydrogen energy multi-element utilization structure is introduced to form a combined cooling, heating, power and hydrogen supply type comprehensive energy system, and the reliability and flexibility of the system are improved; a stepped carbon transaction mechanism is introduced, so that the enthusiasm of a subject to participate in the carbon market and the decarburization and emission reduction level of the system are improved; according to the method, the solution of the particle swarm algorithm is improved, the solution efficiency of the algorithm is improved, and a more flexible and quicker optimization strategy is provided for real-time scheduling of the system.

The invention relates to a demand side management method based on 5G smart power grid daily load characteristic clustering analysis, which adopts a K-means clustering analysis method to analyze user historical load data, classifies user loads with different characteristics, obtains different power utilization habits and characteristics of different types of users, and excavates demand side response potentials of different users. A demand side management model is constructed based on user load characteristic clustering analysis, and users with different load characteristics are considered to select different time-of-use electricity price strategies to improve user satisfaction; when bidirectional interaction is carried out between the smart grid and a demand side, a smart grid and demand side interaction management model based on the game theory is adopted to realize benefit consideration of the smart grid and the demand side; aiming at the influence of inaccurate demand baseline prediction on interaction, an enhanced interaction strategy is adopted to deal with uncertainty; the method has the advantages of establishing the demand management model based on the load characteristics, optimizing the resource configuration of the power grid, maximizing the net profit of the power grid, reducing the demand fluctuation and improving the stability.

The invention relates to the technical field of low-carbon emission reduction, and discloses an energy low-carbon transformation analysis method based on Internet of Things, which comprises the following steps: S1, collecting data of different energy types and real-time production, transmission, storage and use data through Internet of Things equipment, and constructing a multi-energy data fusion platform; s2, according to the collected energy data, performing comprehensive analysis on different energy types by using a multi-energy collaborative optimization model, and determining the optimal ratio of different energy in conversion efficiency, use time period and economic cost; and S3, collecting user energy consumption behavior data through the Internet of Things equipment, and constructing a user behavior prediction model. Data of multiple energy types are integrated through the Internet of Things technology, intelligent allocation is achieved through a collaborative optimization model, the energy utilization efficiency is improved through multi-energy collaborative management, carbon emission is reduced, the system can flexibly meet the conversion requirements of different energy sources, the resource utilization rate is maximized, and dependence on a single energy source is reduced.

The invention discloses a cleaning agent recycling system, and relates to the technical field of detergent recovery, the cleaning agent recycling system is characterized in that the inner side wall of a filtering tank body is fixedly connected with a ceramic filtering plate, the high-performance ceramic filtering plate is uniformly provided with ultra-micropores, the aperture of the ultra-micropores is less than or equal to 1nm, the top of the ceramic filtering plate is provided with a slope, and the top of the slope is provided with a water inlet. The outer side wall of the filtering tank body is fixedly communicated with a feeding pipe, the feeding pipe is positioned above the ceramic filtering plate, and the bottom of the filtering tank body is fixedly communicated with a return pipe; through cooperative use of the filtering tank body, the ceramic filtering plate, the slope and the feeding pipe, cleaning agent molecules can be accurately screened out conveniently according to the characteristics that the diameter of the cleaning agent molecules is smaller than 1 nm, and the diameter of oil dirt impurities, bacteria and the like cleaned by a cutter is larger than 1 nm, and meanwhile the oil dirt impurities, bacteria and the like are effectively blocked. Therefore, the cleaning agent and the oil dirt impurities can be fully separated, the filtering effect is improved, and the recycling rate of the cleaning agent is increased.

The invention provides a load regulation and control strategy considering multiple market superposition, and relates to the technical field of power systems. The method comprises the following steps: S1, inputting load side resource feature data of multiple markets; s2, calculating indexes of the fluctuation rate, the peak-valley difference ratio, the discharge load support rate, the load transfer capability and the load interruption capability of each resource main body as feature vectors of each resource main body, constructing a feature vector set of each resource main body, and hierarchically aggregating the feature vectors in the feature vector set of all the resource main bodies by adopting a DBSCAN clustering algorithm; s3, on the basis of clustering results of all the feature vectors, in combination with constraint conditions, establishing a load side resource aggregation model with the lowest operation cost as an objective function; and S4, calling a commercial solver to solve the load side resource aggregation model to obtain an optimal load side resource hierarchical aggregation scheme. According to the invention, the problems of heterogeneity of each load resource, difference in response capability and low enthusiasm of users participating in demand response in the existing load management can be effectively solved.

The invention provides a method and device for a virtual power plant to participate in market transaction, and the method comprises the steps: solving a target response amount by taking a minimum cost function as an optimization target after constructing the virtual power plant, determining a target excitation compensation price based on the target response amount and the minimum cost function value, and then taking a maximum preset benefit function as an optimization target, based on the target response amount and the target excitation compensation price, the target electricity purchase and sale amount and the target peak load shifting amount are solved, the electricity utilization cost of the virtual power plant is minimized, the economic benefit of the virtual power plant is maximized, the electricity utilization experience of a user is improved, and in addition, the target response amount and the target excitation compensation electricity price are obtained through the minimum electricity utilization cost. The enthusiasm of the user to change the power demand is improved, the power shortage condition is relieved, the abnormal power utilization condition caused by the power shortage is avoided, and the power utilization efficiency is improved.

The invention relates to the technical field of household cleaning equipment, in particular to an active obstacle crossing type driving wheel and a robot thereof. The active obstacle crossing type driving wheel is mainly applied to the cleaning robot, a front wheel is arranged on the front side of the bottom of the cleaning robot, the active obstacle crossing type driving wheel comprises a power source, a main wheel and an auxiliary wheel, the main wheel and the auxiliary wheel are arranged at the bottom of the cleaning robot and share power output of the power source, and the main wheel is located on the rear side of the gravity center of the cleaning robot. The auxiliary wheels are located on the front side of the gravity center of the cleaning robot. According to the active obstacle crossing type driving wheel and the robot thereof, the main wheel and the auxiliary wheel are distributed on the two sides of the gravity center of the cleaning robot, when the cleaning robot faces an obstacle, the supporting position of the cleaning robot is changed, so that the whole cleaning robot inclines backwards, and the height of the front side of the cleaning robot is increased due to inclination; therefore, the obstacle higher than the chassis can be climbed over, and the obstacle crossing ability of the cleaning robot is improved.

The invention discloses a decision-making method for a light storage and charging multifunctional charging station to participate in peak regulation auxiliary service based on reinforcement learning, and relates to the field of power system analysis and calculation. Establishing a cost objective function through comprehensive analysis of charging service income, electricity purchasing and selling cost, peak regulation response income and peak regulation deviation punishment cost; obtaining a peak regulation operation constraint condition based on confluence analysis of an electric power and electric quantity balance constraint, a peak regulation capacity constraint, an energy storage system charging and discharging constraint, an electric vehicle charging constraint and a spinning reserve capacity constraint; and establishing a peak regulation auxiliary service decision model according to the cost objective function and the peak regulation operation constraint condition, and training through a reinforcement learning algorithm to obtain an energy storage charging and discharging strategy. According to the method, cost-benefit factors such as system operation and maintenance cost and carbon emission reduction benefit are considered, and optimization of peak regulation cost benefit can be realized when the light storage and charging multifunctional charging station participates in peak regulation auxiliary service.

The invention relates to the technical field of gearboxes, in particular to an electric gearbox assembly which comprises a box body and a motor, a power transmission shaft is arranged at the power output end of the motor, an intermediate shaft is arranged in the middle of the box body, a synchronous gear ring is slidably connected to the middle of the intermediate shaft, a power output shaft is arranged in the middle of the lower end of the box body, and a shifting gear shifting mechanism is arranged in the middle of the box body. The shifting gear shifting mechanism is composed of a mounting column, a second spring, a second steel ball, a four-wheel-drive shifting fork, a locking column and a sleeve, the box body is formed by splicing a left box body and a right box body, transmission flanges are fixedly connected to the two ends of the power output shaft, and a motor connecting cover is fixedly connected to the connecting position of the left side of the box body and the power transmission shaft; a gear shifting rotating arm is rotationally connected to the outer side of the box body, the two ends of the gear shifting rotating arm penetrate through the box body, and a rocker arm plate is fixedly connected to the upper end of the gear shifting rotating arm.

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 a tracking and tracing system based on big data analysis. The system comprises a data quality verification module, an anonymization technology module, a multi-dimensional supervision module and a cooperative ecological module. According to the invention, cleaning and verification of original data are realized through the data quality verification module, wrong, redundant and missing data are removed, consistency verification is carried out on data of different data sources by using a data comparison algorithm, and the accuracy and consistency of the data are ensured; through data encryption and authority control, confidentiality of data in storage and transmission processes is ensured, and data leakage and unauthorized access are prevented; an early warning mechanism and a problem solving scheme are designed, so that related personnel can be timely notified to solve problems, and the timeliness and efficiency of supervision are improved; a cooperation relationship and a data sharing platform are established, cooperation and information sharing among participants are promoted, a preferential policy and a reward mechanism are designed, all parties are stimulated to actively participate in system construction and data sharing, and the power and effect of cooperation are enhanced.

The invention discloses an automatic salary data generation method and system for the express industry, and relates to the field of salary data processing, and the method comprises the steps: creating a salary model, naming the salary model, and selecting an applicable person; uploading the historical salary list file of the selected applicable personnel to the system, and obtaining related salary data; analyzing the salary document of the historical months, and obtaining element items of the franchise company; establishing a mapping relation between the franchise company element items and the standard element items through an intelligent matching algorithm; and presenting the generated mapping relation to the financial staff of the franchise company, and adjusting and confirming the matching rule by the financial staff of the franchise company. According to the method, the advanced natural language processing technology is utilized, intelligent analysis of various salary related terms and descriptions is supported, the accuracy and consistency of salary calculation are ensured, automatic salary generation is achieved, a large amount of manpower and time are saved, and better use prospects are brought.

The invention discloses a portable wearable waste amyotrophy treatment system based on a surface myoelectricity feedback technology. The portable wearable waste amyotrophy treatment system comprises a pair of devices, a button type hydrogel electrode plate and an upper computer. The pair of devices are worn on symmetrical muscles on the left side and the right side of a patient through button type hydrogel electrode plates respectively and used for collecting electromyographic signals of the two muscles and conducting electric stimulation on the two muscles. A hardware circuit in the device communicates with an upper computer, receives a control instruction and sends collected electromyographic signals to the upper computer; electrical stimulation amplitude, frequency and pulse width parameters are controlled to output electrical stimulation waveforms; the upper computer is used for setting electrical stimulation parameters, receiving and processing electromyographic signal data and determining whether to trigger electrical stimulation or not according to an electromyographic value of a patient, and comprises an electromyographic feedback training mode and a rehabilitation treatment effect evaluation module, calculates RMS, MVC and MPF parameters of left and right muscles of the patient in the treatment process and measures limb circumferences of the left and right muscles. And the treatment effect is evaluated.

The invention discloses a garbage classification recycling excitation method and system. The weight, classification accuracy, classification participation frequency and variety diversity of garbage are comprehensively considered. The weight of the garbage is the most direct influence factor, the classification accuracy of the garbage reflects the accuracy degree of garbage classification of the user, the classification participation frequency of the garbage reflects the enthusiasm and continuity of the user participating in garbage classification, and the variety diversity of the garbage reflects the recognition and treatment capacity of the user on different types of garbage. The four factors jointly influence an integral calculation value in garbage classification and recovery excitation, so that the accuracy and the fairness of integral calculation are improved, garbage classification behaviors of the user can be comprehensively evaluated, and the user is excited to more actively participate in garbage classification and recovery activities.

The invention provides a user answer information processing method, system and device and a medium. The processing method comprises the steps of obtaining first answer information of a user about a target exercise; if the first answer information does not meet the preset requirement, obtaining second answer information about the target exercise of the user; and if the second answer information does not meet the preset requirement, putting the target exercises into a wrong question book corresponding to the user. According to the invention, a more reasonable and accurate exercise interaction mode and a wrong question collection mode are provided for the user, and a feedback mechanism of'switching back 'can be provided for question doing errors of students in the learning process, so that the real mastering condition of the students for exercises can be identified more accurately; according to the method, the answers which are actually understood correctly by the students but are wrongly selected due to mistaken clicking, misoperation and the like are eliminated, so that the wrong questions which are not really mastered by the students are collected, a reliable basis is provided for subsequent tutoring, the learning state of the students can be evaluated more accurately, and a more targeted teaching strategy is formulated.

The invention discloses dual-drive dry grinding equipment, which belongs to the field of grinding equipment and comprises a grinding cylinder, two ends of the grinding cylinder are respectively and fixedly provided with a grinding cylinder rotating shaft, a grinding rotor is arranged in the grinding cylinder, two ends of the grinding rotor are respectively and fixedly provided with a rotor transmission shaft, and the rotor transmission shafts and the grinding cylinder rotating shafts are concentric and non-coaxial and can relatively independently rotate. According to the grinding equipment, in the grinding process, the grinding cylinder can be rotated to drive a grinding medium to roll, the grinding efficiency is greatly improved, meanwhile, the grinding medium is evenly stressed on the inner wall of the grinding cylinder to shear and collide, generation of static electricity is reduced, and therefore hardening and accumulation of powder on the inner wall are reduced, and the powder is more evenly ground; by rotating the grinding rotor, higher power is provided for the grinding medium in the grinding inner cavity, so that the grinding efficiency is improved again, the rotor transmission shaft and the grinding cylinder rotating shaft are of a concentric and heteroaxial structure, the grinding cylinder and the grinding rotor can rotate and operate at different rotating speeds, the grinding device is suitable for operation under different working conditions, and the error-tolerant rate is higher.