28results about How to "Precisely formulated" patented technology

The invention discloses a transcranial magnetic stimulation treatment individualized parameter optimization system based on artificial intelligence, and relates to the technical field of transcranial magnetic stimulation optimization systems. The transcranial magnetic stimulation treatment individualized parameter optimization system based on artificial intelligence comprises a data acquisition preprocessing module, a feature extraction module, a treatment parameter prediction module and a treatment effect evaluation module, and the data acquisition module is used for acquiring brain function data of a patient in real time; the feature extraction module is used for performing feature extraction on the preprocessed brain function data and clinical data; the treatment parameter prediction module is used for determining a treatment scheme suitable for the current condition of the patient according to the transcranial magnetic stimulation treatment parameter prediction result; the treatment effect evaluation module is used for continuously monitoring brain function data of the patient in the treatment process. The problems that in traditional transcranial magnetic stimulation treatment, parameter setting depends on experience and a general guide, individualized optimization and parameter adjustment are lacked, and consequently the treatment effect is inaccurate and the treatment time is long are solved.

The invention discloses a PICC catheter real-time data acquisition-based nursing quality monitoring system, and relates to the technical field of nursing quality monitoring, the system comprises a data acquisition module, a real-time analysis module, a long-term tracking module, a risk dynamic evaluation module, a nursing intervention module and a patient monitoring module, and the modules are in electric signal connection. According to the nursing quality monitoring system based on PICC real-time data collection, by continuously monitoring physiological parameters of a patient and PICC related data, nursing personnel can respond to demand changes of the patient in time, PICC related complications can be effectively recognized and prevented, abnormal conditions can be found in time, intervention measures are taken, and the nursing quality is improved. Therefore, the risk of complications is reduced, the safety of the patient is improved, nursing personnel can make a personalized nursing plan more accurately, the pertinence and effectiveness of nursing are improved, and the treatment effect of the patient is improved.

The invention relates to a warehouse logistics scheduling method and system based on cloud computing, and relates to the technical field of warehouse logistics scheduling, and the method comprises the steps: jointly building a logistics scheduling model through a plurality of edge cloud computing nodes, and the logistics scheduling model comprises an edge scheduling scheme generation model and a comprehensive scheduling scheme generation model; determining at least one first optimal edge cloud computing node based on the computing power resource demand of the warehouse logistics scheduling task; each first optimal edge cloud computing node generates a model through an edge scheduling scheme, generates a plurality of candidate warehouse logistics scheduling schemes based on the warehouse logistics scheduling task, the warehouse node state information and the logistics vehicle state information, screens the plurality of candidate warehouse logistics scheduling schemes, and determines a plurality of target warehouse logistics scheduling schemes; through the comprehensive scheduling scheme generation model, the optimal warehouse logistics scheduling scheme is generated based on the multiple target warehouse logistics scheduling schemes, warehouse logistics scheduling is carried out, and the method has the advantage of improving the intelligent level of warehouse logistics scheduling.

The invention discloses a task scheduling method and device based on intelligent MRP operation, a medium and a program product. The task scheduling method comprises the steps that first real-time production data in the production process is obtained; performing data preprocessing on the first real-time production data to obtain second real-time production data; carrying out stream data analysis processing on the second real-time production data based on an Flink framework to obtain a real-time data analysis result; the real-time data analysis result is input into a trained intelligent MRP operation model, an MRP production scheduling plan is generated by the intelligent MRP operation model according to real-time productivity and user order demands, and the intelligent MRP operation model is constructed based on a machine learning algorithm and is trained by using historical MRP data; and finally, carrying out production task scheduling according to the MRP production scheduling plan. According to the invention, the accuracy of MRP operation is effectively improved, and the instantaneity and responsiveness of generating the MRP production scheduling plan are further improved, so that the production efficiency is improved, and the resource waste is reduced.

The invention discloses a human resource outsourcing service system and method based on big data, and relates to the technical field of human resource management and big data, and the system comprises a data collection and integration module which is used for collecting human resource data from a data source, and carrying out the cleaning, integration and storage; and the big data analysis module is electrically connected with the data acquisition and integration module. According to the human resource outsourcing service system and method provided by the invention, the collected and integrated data is processed and analyzed through the big data analysis module, and the defects in the service are identified and improved, so that the management layer of an enterprise can make a decision more objectively and scientifically depending on the support of big data, and the management efficiency of the enterprise is improved. The big data analysis result provides comprehensive and accurate information for the management layer, and helps the management layer to better understand market demands, personnel dynamics and project execution conditions, so that a development strategy which is more practical is formulated.

The invention relates to a solid fuel combustion characteristic test technology, and aims to provide a focusing single particle suspension variable atmosphere ignition combustion experiment device and method. A second microporous plate and a feed hopper are arranged at the top of a combustion chamber main body of the device, and a first microporous plate and a gas buffer cavity are arranged at the bottom; the two laser emitters are arranged in an included angle shape, and the energy of a single laser beam is lower than a fuel particle ignition threshold value; the two paths of laser intersect in the central area of the cavity to form a space energy focus, and the superposed energy of the two beams of laser can be absorbed at the position to reach an ignition threshold value; and light paths of diagnosis equipment in the optical acquisition module are intersected in a focus area. According to the invention, through a strategy of airflow disturbance and microwell plate blocking, particles completely move in airflow; the ignition behavior has spatial selectivity, the success rate is high and controllable, and the research is closer to the actual application scene. Through the design of single-particle fixed-point triggering, the system complexity and the control difficulty can be reduced, and the operation stability and the experiment repeatability can be improved.

The invention provides a traditional Chinese medicine supply chain collaborative management system and method based on an industrial internet, and solves the problems of traditional Chinese medicine supply chain collaborative management and the like, and the method comprises the following steps: S1, supply chain data collection and preprocessing; s2, selecting a data analysis algorithm; s3, carrying out model training; s4, detecting the prediction performance of the model, and evaluating the risk of the supply chain; and S5, supply chain collaborative management is carried out. The method has the advantages of good management effect, high safety and the like.

The invention, which relates to the technical field of orchard picking management, discloses an orchard picking adaptive management system comprising an environment monitoring module, a data analysis and prediction module, an automatic control module, an intelligent picking module, a pest and disease monitoring module and a pest and disease control module. The environment monitoring module is used for collecting orchard environment data and transmitting the orchard environment data to the data analysis and prediction module, and the data analysis and prediction module is used for preparing and preprocessing the data, determining a model order and establishing, checking and optimizing an ARIMA model for yield prediction. According to the invention, through the integrated ARIMA model, the orchard picking adaptive management system can carry out accurate yield prediction based on the historical time sequence data of the orchard; the problems of inaccurate orchard yield prediction, complex data processing and model establishment, difficult model optimization and selection, lack of basis for picking plan making and low orchard management efficiency can be solved.

The present application relates to the technical field of livestock data processing, in particular to a livestock and veterinary breeding data analysis system, which comprises: a state transition analysis module collects data of the breeding cycle of female livestock, integrates the data of all female livestock to construct a transition probability matrix, predicts the future state transition path of female livestock according to the transition probability matrix, and generates a female livestock state transition evaluation result. In the present application, by analyzing the data of each state of the breeding cycle of female livestock, the state change path of female livestock at different stages is determined, accurate prediction and quantitative evaluation of the state in the breeding cycle are realized, and the formulation of the breeding plan is more accurate. By evaluating the residence time and transition trend of each stage, the best breeding time is predicted, and the overall breeding efficiency is improved. Based on the similarity analysis of behavior data such as activity frequency, body temperature and number of reproductions, individual female livestock is divided into different behavior groups, and more targeted reproduction management strategies are formulated for different groups.

The utility model relates to the technical field of analgesic medicine dispensing, in particular to a multi-formula analgesic medicine dispensing device which comprises a dispensing instrument and an infusion tube. The medicine dispensing instrument comprises a plurality of peristaltic pumps and a control system, one end of each infusion tube penetrates through the corresponding peristaltic pump and is connected with the corresponding solvent bottle, the other end of each infusion tube is connected with the analgesia pump box, and the peristaltic pumps are used for controlling the infusion tubes to input medicine into the analgesia pump box. The control system is used for controlling the rotating speed of each peristaltic pump according to a set formula, so that the preparation of the analgesic is realized. The rotating speed of each peristaltic pump is controlled through the control system, so that the preparation of analgesics with different formulas is realized, and the use is convenient.

The application discloses a regional breeding strategy generation method based on corn trait big data, and relates to the technical field of agricultural breeding, comprising the following steps: collecting and integrating multi-source heterogeneous corn regional test data, extracting agronomic trait data, and constructing a structured data set; according to the agricultural ecological environment characteristics and the climate zoning method, the main corn producing areas are divided into a preset number of ecological regions; a multi-dimensional data space-time analysis framework is constructed, and the structured data set is sequentially subjected to global descriptive statistical analysis, trait space-time evolution analysis, trait coordination relationship analysis, trait feature dimension reduction analysis, and ecological zoning and feature portrait analysis; and based on the space-time analysis results, customized corn breeding strategies for different ecological regions are generated. Through the innovative multi-dimensional space-time analysis framework, the space-time evolution law and complex relationship of corn traits are systematically analyzed, and scientific decision support is provided for regional breeding.

The present invention belongs to the technical field of drilling positioning, and in particular, relates to a tool and method for replacing crack faults in helicopter center reduction joints, comprising a drilling jig mechanism installed on a positioning platform, the drilling jig mechanism comprising a mounting plate, a pressing plate and a drilling jig, the mounting plate being provided with a plurality of stepped holes, the pressing plate being provided with guide holes corresponding to the stepped holes one by one; an elastic rubber pad being provided on the stepped end surface of the stepped hole, the inner support sleeve of the elastic rubber pad being provided with a drilling jig, the outer diameter of the drilling jig being smaller than the inner diameter of the stepped hole and larger than the inner diameter of the guide hole. The tool can be used to position the replaced old center reduction joint, and to accurately configure the positioning holes of the new part.

This application provides a human-computer interaction method and system for emergency rescue scenarios. The method involves parsing and processing the multimedia information received from an emergency rescue requester to obtain an emergency rescue situation awareness model. Based on this model, a deep reinforcement learning algorithm is used to select possible emergency response strategies. Medical knowledge graph technology is then used to analyze the relationship between the requester's symptoms and possible causes to generate an emergency rescue guidance plan. Based on this guidance plan, a traffic flow prediction algorithm is used to optimize the rescue route in real time. Combined with road condition information collected using IoT technology, the route of the rescue vehicle is dynamically adjusted to generate an optimal rescue route and the latest rescue progress notification. Finally, the optimal rescue route and the latest progress notification are used to visualize the emergency rescue operation process, generating intuitive visual guidance. The technical solution provided by this application significantly improves the speed, accuracy, and effectiveness of emergency response.

The application provides a global marketing strategy real-time regulation and resource optimization system for a baking chain enterprise, belongs to the field of baking marketing management systems, and solves the problems of being unable to coordinate multi-store resources and regulate global marketing strategies and the like. The system comprises a data acquisition layer, a data processing layer, a core function layer, a business logic layer, a decision interaction layer and a data output layer. The core function layer comprises a three-dimensional database module, a strategy configuration interface module, a marketing strategy simulation module, a compliance verification module, a strategy data feedback and optimization module, a resource elasticity allocation engine module and a new store site selection evaluation module. The business logic layer comprises a business rule engine module, a permission and security control module and an event and notification module. The decision interaction layer comprises an intelligent decision module, a PC end management background and a mobile end APP. The data output layer comprises a data report output module, a chart output module and a system docking output module. The application can realize global marketing strategy regulation and resource optimization for multi-stores.

The invention relates to the technical field of big data resource services, and particularly discloses a server storage space optimization method which comprises the steps of comparison of data sets needing to be optimized, strategy feasibility evaluation and storage space performance judgment, and specifically comprises the following steps: firstly, obtaining the data sets needing to be optimized of the server storage space by comparing data access frequency with reference frequency; according to the method, the feasibility evaluation index of the data deletion strategy is judged, adjustment and optimization are performed according to the change of the feasibility evaluation index, and the data deletion strategy is recorded as the data deletion preset strategy, so that data deletion operation is performed on the data set to be optimized in the storage space of the server, and the burden of the storage space is reduced. The released storage space can be redistributed to other data, the resource utilization rate of the storage space is improved, and the storage performance of the server storage space after data deletion is judged, so that the optimization of the server storage space is fed back.

The invention discloses a method for detecting racemic ketoisoleucine calcium impurities in a compound alpha-keto acid tablet, which comprises the following steps: dissolving a racemic ketoisoleucine calcium reference substance in a solvent to obtain a reference substance solution, taking the solvent as a blank solution, injecting the blank solution into a liquid chromatograph until a base line is stable, and measuring the content of the racemic ketoisoleucine calcium impurities in the compound alpha-keto acid tablet. Injecting the reference substance working solution into a liquid chromatograph for detection; the method comprises the following steps: dissolving a sample in a solvent to obtain a test solution, injecting the test solution into a liquid chromatograph, recording a chromatogram, calculating the single impurity of the racemic ketoisoleucine calcium by an external standard method, and calculating the total amount of the impurities. The invention belongs to the technical field of racemic ketoisoleucine calcium impurity determination, and particularly relates to a method which can accurately detect some specific racemic ketoisoleucine calcium degradation impurities, is not interfered by other components in compound amino acid, meets the requirement that the degree of separation among the impurities meets the applicability of a chromatographic system, and is high in detection accuracy. The sample treatment is simple and convenient, the sample detection result is accurate and reliable, and the sensitivity is high.

The invention relates to the technical field of artificial intelligence data processing, provides a traffic data processing method and device based on AI service, a storage medium and a terminal, and aims to improve the accuracy and real-time performance of traffic data processing. Processing data by using the real-time traffic operation prediction model, optimizing the model, receiving and optimizing real-time traffic operation data, and the like. Through the technical means of feature extraction and model matching, prediction error monitoring and model optimization, real-time data receiving and verification, data detection and optimization and the like, accurate processing and real-time prediction of traffic data are realized. The method is mainly characterized by comprising a closed-loop optimization mechanism, data abnormity early warning and continuous data and model optimization, the accuracy and real-time performance of traffic data processing are remarkably improved, and more reliable data support is provided for traffic management and urban planning.

The invention discloses a bus timetable generation method based on travel time and passenger flow probability prediction. The method comprises the following steps: S1, collecting data; s2, preprocessing to obtain an original data set; s3, obtaining a resampling data set; s4, constructing and training a travel time and passenger flow long-term probability joint prediction model; s5, filling the predicted resampling data set to obtain a prediction data set of an input format accepted by the optimization model; s6, selecting a prediction data set for evaluating the optimal resampling granularity in the step S3; s7, constructing a super-large-scale random multi-target mixed integer programming model; s8, inputting the prediction data set of the input format accepted by the optimization model into a super-large-scale random multi-target mixed integer programming model; and S9, designing a sparse multi-objective optimization algorithm of constraint optimization, and generating a bus timetable. According to the method, the prediction model and the optimization model are constructed and trained through an artificial intelligence technology and an algorithm, so that the bus timetable is efficiently and accurately generated.

The invention discloses a highway engineering project collaborative management system and method based on artificial intelligence, relates to the technical field of project collaboration, solves the technical problem that a construction department and a design department cannot implement a construction scheme through field collaboration in the prior art, and particularly relates to the technical field of planning and design collaboration. The construction planning department and the design department cooperate to obtain an accurate planning scheme, and the design department performs corresponding region design after defining the region planning of the construction planning department according to the highway engineering coverage region of the field detection of the construction planning department; and design and construction collaboration: in the previous step, the planning and design collaboration determines a planning scheme, the design and construction collaboration is carried out according to a design planning drawing, the design planning drawing of the design department is subjected to main body conversion through the construction department, and the design of the planning area is subjected to materialized display.

The utility model relates to the field of seedling raising substrates, and discloses a seedling raising substrate proportioning device which comprises a shell, a plurality of material boxes are fixedly connected to the upper surface of the shell, and discharging bins are fixedly connected to the positions, located below the material boxes, of the inner wall of the shell. Spiral discharging rods are rotatably connected to the inner side walls of the multiple discharging bins, a supporting plate is fixedly connected to the position, located below the multiple discharging bins, of the inner wall of the shell, stirring rollers are rotatably connected to the lower surface of the supporting plate, and a baffle is connected to the position, located below the stirring rollers, of the side surface of the shell in a clamped mode; a substrate box is slidably connected to the side surface of the shell and located below the baffle; according to the device, the effect of accurately preparing the seedling culture substrates in different proportions can be achieved, and the practicability and universality of the device are improved.

The utility model discloses a battery piece etching additive adding device which comprises an installation bottom plate, an adding platform is arranged at the upper end of the installation bottom plate, a raw material table is arranged at the front end of the installation bottom plate, a plurality of first raw material tanks are arranged at the upper end of the raw material table, and first discharging pipes are arranged at the rear ends of the first raw material tanks. A first control valve is arranged on the first discharging pipe, a plurality of adding mechanisms are arranged on the adding platform and are in one-to-one correspondence with the first raw material tanks, a first mixing tank is arranged at the rear end of the mounting bottom plate, a first feeding hopper is arranged at the upper end of the first mixing tank, a first driving motor is arranged at the upper end of the first mixing tank, and a second feeding hopper is arranged at the lower end of the first driving motor. A first stirring shaft is arranged in the first mixing tank, and a first stirring paddle is arranged on the first stirring shaft. According to the adding equipment for the battery piece etching additive, all components can be accurately prepared and mixed in proportion, and the performance stability of the battery piece etching additive can be guaranteed.

The invention discloses a regulation and control method and system for food purification, and relates to the technical field of food purification regulation and control. The regulation and control method for food purification comprises the following steps: collecting initial ozone purification data; calculating an ozone correlation coefficient; and formulating a regulation and control strategy. The method comprises the following steps: collecting initial ozone purification data of an ozone reaction experiment through a sensor, preprocessing the initial ozone purification data to obtain ozone purification data, performing data analysis on the ozone purification data to obtain an ozone correlation coefficient, and performing comprehensive ozone evaluation on the ozone correlation coefficient to obtain a comprehensive ozone evaluation index; finally, a regulation and control strategy is obtained according to the comprehensive ozone evaluation index, and the regulation and control strategy is sent to preset personnel for processing, so that the effect of improving the regulation and control accuracy of food purification is achieved, and the problem of low ozone utilization rate in the food purification process in the prior art is solved.

The present invention discloses a tactile ultrasonic medical detection probe and medical equipment, which relate to the technical field of medical equipment, and include an ultrasonic piezoelectric detection module and a tactile module, wherein the ultrasonic piezoelectric detection module includes a piezoelectric sensor array element layer, and the tactile module includes a tactile sensor array element layer, wherein the piezoelectric sensor array element layer and the tactile sensor array element layer are arranged on the same layer. The present invention fuses the morphological structure image obtained by ultrasonic detection with the tissue elasticity image obtained by the tactile imaging system to improve the accuracy and efficiency of diagnosis.

The present invention relates to the field of gas pipeline monitoring, and in particular to an intelligent gas pipeline network monitoring method and system thereof, comprising acquiring pipeline network data information, establishing a pipeline network integrity level identification neural network model, using the acquired historical pipeline network data information as a training sample, and inputting it into the pipeline network integrity level identification neural network model; defining the pipeline network pressure according to the judgment of the integrity of the pipeline network; calculating the pipeline network pressure adjustment parameter in combination with the pipeline network related data information; adjusting the preset pipeline network pressure according to the pipeline network pressure adjustment parameter; calculating the maintenance frequency of the gas pipeline network system according to the output result of the pipeline network integrity level identification neural network model; establishing a pipeline network health monitoring model through the adjusted pipeline network pressure situation, and realizing the monitoring of the operating status of the gas pipeline network system.

The invention relates to the field of data processing, and particularly provides an energy-saving control method and system for a data center machine room, and the method comprises the following steps: carrying out the implicit representation mining of a monitoring data flow template through employing an implicit representation model, and obtaining a template data implicit representation array, obtaining a key data detection result on the basis of the template data implicit representation array and the key data detection model, obtaining a linkage type detection result on the basis of the key data detection result and the linkage type recognition model, iterating the template data implicit representation array on the basis of the results and the models, and performing loop optimization to obtain a linkage type detection result; and obtaining a target implicit representation model, a target key data detection model and a target linkage type identification model until a preset judgment standard is met. According to the method, the detection precision of key data and linkage types in the machine room monitoring data stream is high, an accurate machine room energy-saving control strategy can be conveniently formulated, and the energy consumption of the machine room can be saved.

The invention belongs to the technical field of production management, and particularly relates to a process-based chemical industry production and marketing linkage management system, which performs sales value and production value evaluation of various products by periodically calling production records and sales records of various chemical products in an enterprise. Therefore, the advantage levels of various products are extracted and fed back to the production department and the sales department in time, an information sharing platform is provided for the production department and the sales department without human participation, and high-efficiency close connection between the sales department and the production department is realized. Therefore, the advantage level of the product is associated with the production schedule, so that a production department can perform production adjustment more accurately according to market requirements, and meanwhile, the advantage level of the product is associated with the sales object, so that a sales department focuses on sales of the advantage product, and targeted adjustment of the sales object based on production is reflected; and the market demand is actively responded.

The invention relates to the field of material mechanical property testing device development, in particular to a variable ammonia-alcohol-hydrogen environment multi-type corrosion testing device and a variable ammonia-alcohol-hydrogen environment multi-type corrosion testing method.The variable ammonia-alcohol-hydrogen environment multi-type corrosion testing device comprises a first reaction kettle, a second reaction kettle and a third reaction kettle, the second reaction kettle is a constant displacement stress corrosion device, and the third reaction kettle is an electrochemical corrosion test device; the first reaction kettle, the second reaction kettle and the third reaction kettle are respectively connected with a gas distribution device for supplying gas and a tail gas recovery device for recovering tail gas through pipelines; the first reaction kettle, the second reaction kettle and the third reaction kettle are connected with the stepless pressure regulating device through pipelines; and the first reaction kettle, the second reaction kettle and the third reaction kettle are respectively connected with a water bath circulating temperature control device through water jackets. According to the device and the method, actual working conditions can be accurately simulated, and a constant-load tensile stress corrosion test, a constant-displacement stress corrosion test and an electrochemical corrosion test of ammonia-alcohol-hydrogen in different corrosion environments can be synchronously or asynchronously realized.

The utility model discloses an accurate preparation device for mixed petroleum coke, which relates to the technical field of petroleum coke and comprises a working frame, a mixing tank arranged on the upper portion of the working frame, a driving component arranged at one end of the mixing tank, a working component arranged in the mixing tank and connected with the driving component, and an auxiliary component arranged at the other end of the mixing tank. The auxiliary assembly is connected with the working assembly, and a discharging assembly is arranged on the lower portion of the mixing tank and connected with the mixing tank. Brand new components and a brand new connection relation are adopted in the petroleum coke preparation device, a traditional preparation device is abandoned, and a mode of stirring while crushing is adopted, so that petroleum coke raw materials can be fully crushed and can be fully mixed at the same time, and the accurate preparation effect is ensured.