315results about How to "Avoid inefficiency" patented technology

The invention relates to the technical field of optimization methods, in particular to an action type model optimization method based on reward feedback, which comprises the following steps of: SI, constructing a multi-level reward function; s2, starting and initializing; s3, observing a current web environment state; s4, executing the action; s5, environment feedback; s6, constructing a Reward model reward signal processing module; s7, reward signal processing; s8, constructing an action evaluation network; s9, action evaluation; s10, updating the strategy; s11, judging whether the task is completed or a termination condition is reached; according to the method, a more comprehensive action feedback mechanism is established, the final reward is considered, the effect of the intermediate action is fully utilized, the action of the intelligent agent is evaluated and fed back more meticulously, the intelligent agent is guided to explore and utilize the environment more reasonably, and the user experience is improved. And an action feedback mechanism encourages the intelligent agent to try more actions which may contribute to realizing the target, and meanwhile, invalid or harmful actions are avoided, so that the exploration of the intelligent agent in the web environment is more efficient.

The invention relates to the technical field of quality management, and discloses an engineering project quality automatic evaluation system based on AIGC and BIM point cloud algorithms. Comprising the steps of preprocessing point cloud data and image data, identifying potential quality defects through a neural network identification model, constructing a BIM model and a point cloud model of a building structure, performing difference comparison on the point cloud model and the BIM model, evaluating the quality grade of the building structure, and generating a quality evaluation report of an engineering project. Compared with the prior art, the method can ensure that the point cloud model and the BIM model can accurately and consistently represent all the point locations of the building structure, and can accurately and visually evaluate and analyze the actual quality information of the building structure by performing difference comparison on the point cloud model and the BIM model. Therefore, the quality problem of the building structure in the real three-dimensional scene can be accurately evaluated, and the method has high timeliness and accuracy.

The invention discloses an intelligent wireless charging power distribution method and system, and aims to improve the efficiency and safety of simultaneous charging of multiple devices, and the system design comprises a plurality of key modules: a device detection and recognition module automatically recognizes the charging devices and collects the power demands of the charging devices; the power demand analysis module calculates the power demand of each device according to the device electric quantity and the charging mode, and the power distribution control module dynamically adjusts the power output according to the priority, the distance and other factors; the real-time monitoring and feedback module ensures the stability and safety of the charging process, and the data recording and learning optimization module optimizes the charging strategy by analyzing historical data. Through cooperative work of the modules, the system can adjust the charging power in real time, optimize the charging efficiency, improve the user experience, and ensure the safety of the charging process. The system shows good adaptability in a multi-device environment, and important reference and application prospects are provided for development of a wireless charging technology.

The invention provides a lightweight potential diffusion model design method and system based on evolutionary neural architecture search, and the method employs a super-network technology to train a plurality of network architectures at the same time, combines an evolutionary genetic algorithm in an architecture search process, and trains a multi-layer perceptron as a score predictor, so as to improve the performance of the model. According to the method, the optimal architecture is efficiently screened out in a large-scale search space through the assisted evolution genetic algorithm, and the resource consumption and the calculation cost needed in the traditional architecture design process are remarkably reduced. According to the method, the pre-trained teacher model is introduced in combination with the knowledge distillation technology to supervise the training of the student model, and the potential diffusion model can be lightened while the stable performance of the potential diffusion model is ensured. Through the method, an efficient neural network architecture can be automatically designed, efficient deployment of the potential diffusion model can be realized, and a brand-new and low-cost solution is provided for optimization of the diffusion model.

The invention relates to the technical field of water quality monitoring, and discloses an automatic equipment control method for water treatment equipment, which is characterized in that a water treatment process is modeled into a Markov decision process, and dynamic and optimal control on the water treatment equipment is realized. The model comprehensively considers a plurality of dimensions such as raw water quality, treatment water quality, equipment operation state and treatment flow, and defines comprehensive state space and action space. By designing a reward function, multiple indexes such as the water quality standard-reaching rate, the equipment operation efficiency and the energy consumption are evaluated, and a deep reinforcement learning algorithm is adopted to continuously optimize a control strategy so as to maximize accumulated rewards. According to the method, the defects of response lag, strategy stiffness, lack of global optimization capability and the like of a traditional control mode based on a threshold value and manual intervention are overcome, the method can be adaptive to complex and changeable water quality conditions and equipment operation states, the treatment efficiency is improved, the water quality safety is ensured, and the operation cost is reduced.

The invention discloses an assembling device for an extracorporeal circulation blood path attached tube, which comprises a production line, and a conveying device for clamping a catheter and driving the catheter to move forwards is arranged on the production line. The assembling device further comprises an automatic catheter feeding and cutting device, an automatic flow stopping clamp feeding and assembling device, a flow stopping clamp detecting device, a catheter gluing device, an automatic female needle base feeding device, an automatic antibacterial cap feeding and assembling device, a visual detecting device and an automatic discharging device which are sequentially arranged in the moving direction of the production line. The device has the beneficial effects that cutting, feeding and automatic conveying of the guide pipe in the extracorporeal circulation blood path attached pipe are achieved, a flow stopping clamp, a mother needle base and an antibacterial cap are sequentially assembled at a corresponding assembling station, after part of stations are assembled, automatic detection can be carried out, inferior-quality products, waste products and the like are prevented from entering the next working procedure, and after assembling is completed, the production efficiency is greatly improved. And the extracorporeal circulation blood path attached pipes can be automatically discharged and conveyed, and automatic machining of the extracorporeal circulation blood path attached pipes is achieved.

The invention discloses a multi-task intelligent coordination execution method and system based on a pension accompanying robot, and belongs to the technical field of multi-task intelligent coordination execution, and the method comprises the steps: S1, carrying out the initialization of the system according to a current environment and preset parameters; s2, collecting information of the user and the surrounding environment thereof through an integrated sensor; s3, performing fusion analysis processing according to the collected information, predicting the behavior trend of the user, identifying the current demand of the user according to a data analysis result and a prediction result, and automatically generating a task; by integrating advanced data fusion, behavior pattern recognition and prediction, demand recognition and task evaluation, the intelligent level and service quality of the system are remarkably improved, and more accurate behavior pattern recognition and trend prediction are realized through membership function and sliding window prediction; and in combination with the behavior pattern and the trend prediction result, tasks meeting user requirements are generated, and priorities are set through a multi-dimensional evaluation model, so that the efficiency and rationality of task execution are ensured.

The invention relates to the technical field of knowledge management, in particular to a knowledge base management system based on artificial intelligence, which comprises a knowledge acquisition module, a knowledge arrangement module, a knowledge updating module, a knowledge recommendation module, a user interaction module, a knowledge security module and a system management module. The system automatically obtains and sorts structured and unstructured data from multi-source data, generates a knowledge graph and performs hierarchical classification. The content of the knowledge base is dynamically adjusted and updated through time sequence analysis and a self-adaptive updating mechanism, and personalized recommendation is achieved in combination with user behaviors and historical queries. The system adopts an advanced encryption standard and a role access control technology to ensure the security of the knowledge base, so that the knowledge acquisition, arrangement and recommendation efficiency is remarkably improved, meanwhile, the high availability and data security of the system are ensured, and the system is suitable for a large-scale knowledge management scene.

The invention discloses a DRAM (Dynamic Random Access Memory) repair method, test equipment, a storage medium and a computer program product, relates to the technical field of memory repair, and discloses the DRAM repair method, which can find and locate potential fault points in the DRAM in real time by dynamically acquiring an error unit address of the DRAM to provide an accurate target for subsequent repair work. And judging whether the error unit is really damaged or not by performing a repeated read-write test on the error unit. According to the invention, when the number of errors reported by the error unit reaches the preset number of times, it is judged that the error unit is damaged, misjudgment caused by a single test error is avoided, meanwhile, invalid or excessive tests on the damaged unit are prevented, and the test time and resources are saved. And finally, through a remapping technology, the service life of the chip is prolonged, the system shutdown risk caused by chip faults is reduced, and the stability of the DRAM is improved.

An in-situ biogas purification method for anaerobic digestion of sludge based on exogenous hydrogen supply relates to the field of solid waste resource utilization and renewable energy technology. The purpose of the present invention is to solve the problems of low hydrogen solubility and insufficient carbon dioxide bioconversion in the biogas purification process, as well as the inhibitory effect of excessive hydrogen dosage on biogas production by anaerobic digestion of sludge. The present invention utilizes the anaerobic digestion process of sludge in an anaerobic environment to produce biogas, and adds hydrogen to the process by direct hydrogen input or zero-valent iron corrosion, so that hydrogen penetrates into the liquid phase. The hydrogenotrophic methanogens in the system use hydrogen as an electron donor and carbon dioxide in the biogas produced by anaerobic digestion of sludge as an electron acceptor to convert hydrogen and carbon dioxide into methane to achieve in-situ biogas purification. The present invention can obtain an in-situ biogas purification method for anaerobic digestion of sludge based on exogenous hydrogen supply.

The invention provides a geological exploration sampling method and sampling equipment based on vibration drilling and obstacle recognition, and belongs to the technical field of geological exploration. The geological exploration sampling method comprises the following steps: 1, starting drilling; 2, switching a vibration mode; 3, obstacle recognition; 4, grouting assistance; and 5, recovering drilling and completing sampling. According to the geological exploration sampling method, the adaptability to complex stratums can be improved by switching the rotary drilling mode and the vibration drilling mode, a multi-sensor module is adopted in the obstacle recognition step, and pressure, sound waves and vibration signals are collected in real time, so that the obstacle type is accurately judged, and a basis is provided for subsequent drilling mode adjustment. In the grouting assisting step, grouting equipment is adopted to inject grout into an obstacle area from grouting micropores in the front end of a drill bit through a grouting channel so as to effectively weaken an obstacle structure. By means of the method, efficient drilling and sampling operation under the complex stratum condition can be achieved, the drilling tool jamming risk is reduced, adaptability is high, and efficiency is high.

The invention provides a circuit board test method and device based on a flying probe tester. According to the method, a test point set is determined by obtaining a design file of a circuit board, establishing an electrical connection model and identifying components and pins on the circuit board. And generating test combination set data by analyzing the conduction relationship between the test points, and further generating test scheme data. And based on the test scheme data, a test path is generated by using a path optimization algorithm, finally, the flying probe tester is used for testing, and a test report is generated according to a test result. The flying probe tester adopts the combination of an annular probe and a sharp needle probe, the annular probe is used for a pin connector to ensure accurate contact, and the sharp needle probe is used for other types of components to improve the test precision and adaptability. Compared with a traditional test method, the test scheme can be generated more efficiently, the test path can be optimized more efficiently, the test time is remarkably shortened, and the reliability and accuracy of circuit board testing are improved.

The invention provides a method and a device for determining wireless signal intensity in an area and electronic equipment, which are used for improving the efficiency of determining signal intensity distribution in the area so as to realize the purpose of determining the signal distribution condition of a target signal source in the area in real time. The method comprises the steps of determining a target polyline corresponding to an obstacle in a target area in a polar coordinate system taking a target signal source as a pole based on size information of the obstacle in the target area, and determining target information that a propagation path of a target signal passes through the target polyline; wherein the target information comprises the number of the pixel points on the propagation path penetrating through the obstacle and the polar coordinates of the pixel points; based on the target information, determining signal intensity information of the pixel points in the target area; wherein the signal intensity information comprises the position information of the pixel points and the signal intensity on the pixel points.

The invention discloses a pressure air tightness test fixture for a rectification bearing casing and a use method, the test fixture comprises a bottom plate and a cover plate connected to the upper space of the bottom plate through a B-level equal-length double-end stud, the bottom plate and the cover plate are respectively provided with a first sealing ring and a second sealing ring in a matched manner, and the cover plate is provided with a plurality of screw holes; a first pressing plate and a second pressing plate are fixed between the bottom plate and the cover plate through an arch-shaped frame and a C-shaped hexagonal head compression screw, a first sealing gasket and a second sealing gasket are arranged on the first pressing plate and the second pressing plate in an attached mode respectively, and an adapter nozzle is connected to the first pressing plate. The fixture realizes the pressure airtightness test of the whole part welding seam, solves the prominent problem of low efficiency of single support plate welding seam one-by-one test, and improves the pressure airtightness test quality and the part processing efficiency.

The invention provides a control method and device of a drilling and tapping machine and electronic equipment, and relates to the field of data processing. The method comprises the steps that temperature data and deformation data which are sent by a nano-film sensor and aim at a processing object are obtained, and the nano-film sensor is located in a processing area corresponding to the processing object; according to the temperature data and the deformation data, a temperature distribution diagram of the machining area is determined; based on the temperature distribution diagram, surrounding type cooling equipment of the drilling and tapping machine is controlled to cool the machined object in real time; determining a first thread image of a thread corresponding to the processing object according to the deformation data; acquiring a second thread image which is sent by image acquisition equipment of the drilling and tapping machine and aims at a thread corresponding to the processing object; and based on the first thread image and the second thread image, adopting a preset support vector machine model to generate a quality result of a thread corresponding to the processing object. According to the technical scheme, quality detection can be conveniently conducted on the threads machined by the drilling and tapping machine.

The invention discloses an automatic labeling method combined with multi-source log data. The method comprises the following steps: 1) preprocessing an application and a tool: generating a corresponding application program log by using related information in a target application program; meanwhile, modifying an attack plan and an attack tool of an attacker; 2) attack execution: executing the attack by using the preprocessed attack tool and the designed attacked application program, and generating an attack log at the same time; 3) data marking: constructing a provenance graph by using an audit log; positioning attack injection points of different types of logs; all system calls in the thread are divided into different processing programs, processing program IDs are recorded, and a tree structure of a processing program derivation relation is constructed; and 4) marking malicious sub-graphs. According to the method, the auditing log, the traffic log and the application program log are integrated, so that the full view of the network attack can be captured from different dimensions, and the accuracy of attack behavior recognition is improved.

The invention relates to the technical field of leakage detection, and discloses a natural gas leakage quantitative detection method and system based on voiceprint, and the method comprises the steps: collecting a vibration signal of a sound wave sensor, determining the position of a leakage point according to a voiceprint array, and obtaining the fluid leakage flow speed of each fluid detection region, preprocessing the fluid leakage flow velocity to obtain the leakage flow velocity, constructing a leakage flow velocity sample for the corresponding fluid detection area according to the leakage flow velocity, and determining the current leakage environment according to the increasing quantity, the decreasing quantity and the negative quantity; acquiring the historical leakage flow rate in the same leakage environment as the current leakage environment, comparing the leakage flow rate with the historical leakage flow rate, judging whether to correct the leakage flow rate according to the comparison result, and determining a leakage correction factor according to the similar result of the leakage flow rate and the historical leakage flow rate data set. And determining a leakage interval according to the leakage type and the final leakage flow velocity. The method has the characteristic of good quantitative detection of leakage.

The invention discloses an intelligent bed reservation method from outpatient service to hospitalization, and the method comprises the following steps: S1, visiting a doctor in an outpatient service: a patient visits the doctor in an outpatient department through a reservation or registration system, and a doctor carries out the diagnosis of the patient after the inquiry. The intelligent bed appointment management platform is combined with the HIS system and the bed management system, bed resources of a hospital can be automatically matched, inquired and managed, real-time and intelligent bed allocation is achieved, low efficiency and errors of manual management are avoided, meanwhile, AI prediction is combined, and the management efficiency is improved. According to the method, the bed use condition can be monitored and dynamically predicted in real time, bed cleaning and hospital discharge time can be arranged in advance, the maximum bed use rate is ensured, the resource waste phenomenon caused by improper bed management is reduced, a patient can easily inquire the bed state and the predicted hospital admission time through an App or a self-service terminal and know the bed distribution progress at any time, and the patient experience is improved. And anxiety is reduced.

The invention discloses an equipment operation and maintenance fault checking method and device, equipment and a medium. Through the pre-trained equipment fault diagnosis model, in combination with the real-time operation data, the historical fault case and the instruction template, the fault reason of the to-be-analyzed equipment can be quickly positioned, the maintenance suggestion is determined, the troubleshooting efficiency is improved, the time required by manual troubleshooting is reduced, and the overall operation and maintenance efficiency is improved. Through the reasoning layer in the equipment fault diagnosis model, the target troubleshooting thinking chain can be determined based on the input troubleshooting prompt, and the troubleshooting problem and the execution relation of each level are determined, so that the diagnosis process is organized and clear, and redundant and repeated troubleshooting work is reduced. The real-time operation data is checked in sequence according to the execution relation through the grading processing layer in the equipment fault diagnosis model, the fault problem can be quickly locked, and blindness and low efficiency of traditional manual checking are avoided. And the equipment fault removal knowledge base provides powerful knowledge support for fault diagnosis.

The utility model relates to the field of food processing, and discloses a vacuum freeze drying device for dried fruit production, which comprises a box body, the top of the box body is fixedly connected with an electric push rod, the output end of the electric push rod is fixedly connected with a box door, the upper side and the lower side of the rear part of the box door are fixedly connected with inner plates, and the rear sides of the inner plates are slidably connected with outer plates. A connecting plate is fixedly connected between the adjacent sides of the rear portions of the two outer plates, a fixing rod is slidably connected into the connecting plate, and a first motor is fixedly connected to the top of the rear side of the fixing rod. According to the food drying device, through mutual cooperation of the box body, the box door, the outer plate, the inner plate, the connecting plate, the fixing rod, the first motor, the rotating disc, the push rod, the limiting block, the electric push rod, the base, the sliding rod, the vacuum equipment and the freezing equipment, the first motor is driven to work, food is continuously vibrated in the drying process, and the situation that water remains in food due to food accumulation is prevented; the taste and the preservation time of the food are greatly influenced.

This invention relates to the field of air pollution control technology, and in particular to a spray tower for effectively purifying air pollution. The spray tower includes an air inlet fixed to the bottom of one side, a suction hood fixed to the upper surface of the spray tower, and an exhaust pipe fixed to the top of the suction hood. An anti-clogging recovery component and a spraying mechanism are installed inside the spray tower, and a collection box is fixed to one side of the spray tower corresponding to the position of the anti-clogging recovery component. This invention utilizes a spray pipe mechanism to enhance the rate of the neutralization reaction through the synchronous rotation of a rotating disk and a rotating block, and enhances the spatial separation of the two solutions through centrifugal force, reducing cross-mixing. This avoids ineffective neutralization of acid and alkali solutions and achieves continuous and efficient treatment. Combined with the anti-clogging recovery component, the activated carbon balls inside the fixed cylinder are promptly recovered and cleaned, ensuring that efficiency is not reduced due to clogging during air pollution purification, and preventing ineffective adsorption of activated carbon balls due to prolonged use.

The sand blasting device comprises a sand blasting cabinet used for containing a treated workpiece, a movable groove allowing a sand blasting pipe to stretch into the cabinet body is formed in the upper end of the sand blasting cabinet, and a sand blasting pipe moving assembly capable of being connected with the sand blasting pipe to guide the sand blasting pipe to move is arranged beside the sand blasting cabinet. And a jacking rotating assembly which extends into the cabinet body and is used for bearing a treated workpiece is arranged below the sand blasting cabinet, so that the inner surface and the outer surface of the treated workpiece can be effectively treated. Through the arrangement of the sand blasting pipe movement assembly which specifically comprises the lifting assembly, the transverse moving assembly and the sand blasting pipe adjusting assembly and works cooperatively with the jacking rotating assembly, comprehensive and uniform sand blasting treatment on the inner surface and the outer surface of the circular workpiece is achieved, the treatment efficiency and consistency are remarkably improved, the low efficiency and inconsistency caused by manually holding a sand blasting gun by hand are avoided, and the working efficiency is improved. Compared with the prior art, the sand blasting device has the remarkable advantages that the sand blasting efficiency, quality and environment-friendly performance of the circular workpiece are remarkably improved.

The invention relates to the technical field of flexible quality inspection, in particular to a production line synchronous flexible quality inspection method, system and device and a medium. The method comprises the following steps: acquiring product switching information and new product detection demand information; obtaining existing equipment configuration information, and calculating a detection station adjustment scheme and a detection parameter configuration scheme; the detection station is adjusted according to the adjustment scheme, the new product is detected through the adjusted station, and an initial detection result is obtained; the detection result is compared with a preset qualified range, and if the result exceeds the qualified range, an optimization adjustment instruction is triggered; according to the optimization adjustment instruction and the actual detection difference degree, optimization adjustment parameters are calculated and an adjustment scheme is updated, manual intervention is not needed, intelligent adjustment of the detection station can be automatically completed, and the automation and flexibility level of the quality inspection process is improved; meanwhile, through closed-loop adjustment control, an adjustment scheme is continuously optimized, and the detection quality and the stability of the product quality are effectively improved.

The invention provides a method for controlling the thickness of an anti-abrasion surface coating of an impeller. The method comprises the following steps that S1, a light source projects light spots to the surface of an impeller plane material; s2, an image acquisition device acquires a light spot image P1 of the surface of the impeller plane material and completes calibration; s3, setting parameters of a comparison model P0; s4, the spray gun sprays wear-resistant paint to the surface of the impeller plane material; s5, an image obtaining device obtains an impeller plane material surface light spot image and transmits beam angle data detected in real time to the controller; and S6, the controller compares the data in the S5 with the data in the S3, and when it is judged that the wear-resistant coating reaches the initial set value, work is stopped. According to the method for controlling the thickness of the anti-abrasion surface coating of the impeller, the spraying shape and the thickness of the coating can be automatically and accurately controlled according to set parameters, and the problem that the spraying thickness is not accurate during spraying of existing spraying equipment is solved.

The invention provides a distributed computing system based on pre-scheduling resource collaborative adaptation, and relates to the technical field of resource collaborative allocation systems. The distributed computing system based on pre-scheduling resource collaborative adaptation aims at solving the problems that in the prior art, resource scheduling is not flexible, and application configuration and resource scheduling are lack of coordination. By introducing a dynamic scheduling mechanism of the resources, organic combination of resource pre-scheduling and flexible allocation is realized. Meanwhile, through cooperation of application configuration and resource scheduling, optimal distribution and execution of calculation tasks are achieved, the system is composed of a server side and a client side, the client side has pre-scheduling resources and is used for feeding back the resource state in real time and receiving and executing the calculation tasks, and the server side is responsible for monitoring and scheduling of global resources and task distribution. And through a designed heuristic collaborative adaptation algorithm, the server can dynamically schedule resources in the pre-scheduling resources, and high efficiency and stability of task execution are ensured.

The invention discloses an NFC testing method based on machine learning, and relates to the technical field of wireless communication testing, and the testing method comprises the specific steps: S100, data collection and preprocessing: carrying out the basic testing of an NFC signal under different environment conditions, collecting the multi-dimensional data of signal intensity, transmission speed and error rate, and carrying out the data collection and preprocessing; by introducing deep fusion of the electromagnetic field theory and the machine learning technology, dimensions and methods of NFC testing are greatly enriched, the electromagnetic field theory serves as an important branch of physics, an accurate mathematical model and an experimental verification method of the electromagnetic field theory provide a solid theoretical basis for propagation characteristics of NFC signals in a complex environment, and the electromagnetic field theory and the machine learning technology are combined in advance. In combination with the strong data processing and prediction capability of a machine learning algorithm, the attenuation, reflection and diffraction phenomena of NFC signals in different media can be predicted theoretically, the model can be continuously corrected and perfected through actual test data, and the accuracy and reliability of a prediction result are ensured.

The invention discloses a data classification and grading method, system and device based on big data and a medium, and relates to the technical field of data processing. The method comprises the following steps: acquiring to-be-graded data of a plurality of data nodes and a reference index table of a central management node; extracting content features and business attributes of the to-be-graded data, and generating corresponding data feature identifiers according to the content features and the business attributes; scanning each data feature identifier by adopting a preset sensitive word bank to generate a corresponding data sensitivity score, and evaluating each data sensitivity score through a preset data evaluation matrix to obtain corresponding data grade information; and associating the reference index table of the central management node based on the data feature identifier and the data level information of each data node to obtain a hierarchical index table, and allocating a corresponding access path to each data node in the hierarchical index table. By implementing the technical scheme provided by the invention, the data classification and grading efficiency can be improved.

The utility model relates to the technical field of dandelion seeds, in particular to a dandelion seed treatment device which comprises a treatment box, a separation assembly is arranged in the treatment box, a conveying pump is fixedly installed at the top of a supporting plate, a recycling assembly is arranged on the side face of the conveying pump, and a seed collecting assembly is arranged at the bottom of the treatment box. By arranging a separating assembly, a hair collecting long strip, a first drawing rod, a filter screen and a hair collecting cylinder, hair removing treatment on dandelion seeds is achieved, firstly, two second electric telescopic rods are controlled to stretch out and draw back asynchronously through a button control box, and the dandelion seeds are separated for the first time; according to the device, the seeds are separated from the treatment box, then a first pull rod is pulled to enable a hair collecting long strip to move for secondary separation, finally, a first electric telescopic rod is controlled to enable a hair collecting barrel to roll for final separation, finally, the seeds fall into a seed recycling assembly through small holes to be recycled, and the separated hair in the treatment box is collected by arranging the recycling assembly.

The invention relates to the technical field of medical informatization, and discloses a management method based on an intelligent physical examination queuing and calling system, which is characterized in that a physical examination queuing and calling management process is modeled into a Markov decision process by constructing an intelligent calling model, and a queuing strategy and a calling management scheme are dynamically adjusted. The model defines a multi-dimensional state space including physical examination person information, queuing conditions, physical examination equipment and calling equipment, and an action space including actions of adjusting the sequence of physical examination items, guiding physical examination persons, sending calling notifications and the like. By designing a reward function which comprehensively considers the satisfaction degree, the waiting time, the equipment utilization rate and the emergency response capability of physical examinees, a deep reinforcement learning algorithm is adopted to train a model, and a strategy is continuously optimized by taking maximization of accumulated rewards as a target. The physical examination efficiency and the service quality are improved, the waiting time of physical examinees is shortened, the coping ability of the system to emergencies is enhanced, and the physical examination system has remarkable technical advantages and application value.

The invention discloses an artificial intelligence-based automatic cleaning and disinfection system for thoracic surgery operating instruments in the technical field of medical disinfection equipment. The artificial intelligence-based automatic cleaning and disinfection system comprises a classification box, a cleaning module, a disinfection module, a collection module and a control module, a sub-packaging assembly is arranged in the classification box, and the sub-packaging assembly is used for sub-packaging various surgical instruments according to different attributes; the cleaning module is used for cleaning the surgical instruments subpackaged by the subpackaging assembly; the disinfection module is used for disinfecting the surgical instruments; the acquisition module is used for identifying attributes of the surgical instruments in the classification box; the control module is used for controlling operation of the subpackaging assembly based on the recognition result of the collection module, judging cleaning parameters and disinfection parameters needed by the surgical instruments in the recognition result and controlling operation of the cleaning module and the disinfection module. According to the scheme, cleaning and disinfection parameters are intelligently identified and automatically adjusted, so that each instrument can be cleaned and disinfected most suitable for the characteristics of the instrument, and the cleaning and disinfection quality is effectively guaranteed.