142results about How to "Achieve quantification" patented technology

The invention discloses a cranial nerve double-path stimulation intelligent regulation and control method and system for Parkinson's disease, and relates to the technical field of medical treatment and neural engineering, and the method comprises the steps: obtaining an electroneurographic signal of a target patient based on a stimulation electrode, and determining neural activity features according to the electroneurographic signal; the stimulating electrodes comprise a first stimulating electrode and a second stimulating electrode; determining a nerve evaluation value according to the nerve activity characteristics, and generating a co-stimulation parameter based on the nerve evaluation value; initial stimulation parameters of the stimulation electrode are adjusted based on the co-stimulation parameters, the target patient is stimulated through the stimulation electrode, and cranial nerve two-way stimulation intelligent regulation and control for the Parkinson's disease are completed. According to the invention, by introducing the abnormal oscillation mode and evaluating the synchronism characteristics of the neural network in real time, the neural activities of the deep brain and the vagus nerve area are comprehensively quantified, and the accuracy of nerve regulation and control is improved; by generating collaborative stimulation parameters and comprehensively considering the mutual influence of the two stimulation pathways, intelligent collaborative regulation and control are realized.

The invention relates to an ICU patient dysphoria video recognition method based on space-time motion detection. Compared with the prior art, the defect that dysphoria video recognition is difficult to carry out on an ICU patient is overcome. The method comprises the following steps: acquiring and preprocessing a data set; constructing an ICU patient dysphoria identification model; training an ICU patient dysphoria identification model; obtaining video stream data to be identified; iCU patient dysphoria atom action recognition; and performing dysphoria quantitative classification based on an RASS score table. According to the method, the Slowfast basic model is improved, the detection precision and speed of the model are remarkably improved, the dysphoria behavior of the patient is automatically and accurately detected and understood from the perspective of space-time motion detection, the dysphoria condition of the patient is automatically scored according to the RASS score table, and accurate recognition of the dysphoria video of the ICU patient is achieved.

The invention relates to the technical field of electrical safety, in particular to an electrical operator behavior analysis and safety risk prevention and control system which comprises a behavior data acquisition module, a data preprocessing module, a behavior analysis module, a historical risk database, a safety risk assessment module and a real-time early warning module. Wherein the behavior data acquisition module is used for acquiring behavior data and environment data of operating personnel; the behavior analysis module is used for constructing a behavior recognition model; the security risk assessment module is used for performing multi-dimensional risk assessment; the real-time early warning module is used for sending out early warning signals in various forms; according to the invention, through combination of accurate behavior feature identification, multi-dimensional risk assessment and a dynamic early warning technology, the problems of insufficient real-time monitoring of operation behaviors, incomplete risk assessment and untimely early warning response in the prior art are solved, and the safety and risk prevention and control capability in the electrical operation process are improved.

The invention discloses a puncture robot tumor ablation method and system based on magnetic resonance. The method comprises the following steps: scanning a focus through medical imaging examination to obtain a preoperative magnetic resonance image; reconstructing to obtain a three-dimensional model of the focus and surrounding tissues, and planning to obtain an optimal puncture path; updating the position relation between the needle point of the puncture needle and the focus center in real time, feeding back deviation information of the needle point position, and guiding the puncture needle to a tumor ablation area in real time; two-way ablation is adopted, real-time temperature monitoring and whole blood circulation dynamic monitoring are conducted, and ablation power and time are correspondingly adjusted; the ablation effect is consolidated by adopting a postoperative wound management and closing technology; the ablation effect is evaluated through magnetic resonance imaging examination and postoperative biopsy. According to the puncture robot tumor ablation method based on magnetic resonance, tumor ablation can be achieved, temperature and blood flow monitoring is effectively carried out, and the ablation effect and the residual focus condition are reflected in real time through a comprehensive postoperative evaluation method.

A large model agent generation content quality evaluation method based on double baselines comprises the steps that data generated by human beings is acquired, preprocessing and semantic segmentation are carried out, and data samples after semantic segmentation are formed; performing theme extraction on the data samples after data segmentation to form a theme list; the content of the data forming the theme list is generated through an intelligent agent workflow and the content of the data forming the theme list is directly generated through a large model, and an evaluated sample and a contrast sample are obtained; comparing and scoring the data sample after semantic segmentation, the evaluated sample and the contrast sample; selecting a sorting algorithm to carry out score conversion on the graded and compared samples; and performing statistical verification and result analysis. According to the method, a comprehensive, reliable and efficient solution is provided for quality evaluation of the generation content of the large model agent. The method not only can accurately evaluate the content quality, but also provides powerful support for continuous optimization of an intelligent agent system.

The invention relates to the technical field of flow measurement, in particular to a particle energy type high-frequency on-line three-phase flow metering method, which comprises the following steps: acquiring three-phase flow information, microwave signal intensity curves and environmental information parameters of a plurality of fluid samples, determining interfered categories, fitting sample curves, determining interfered characteristic fluid samples, and calculating the particle energy type high-frequency on-line three-phase flow according to the interfered characteristic fluid samples. The method comprises the following steps: acquiring a microwave signal intensity curve of a to-be-measured fluid by utilizing microwave irradiation, preliminarily determining and judging whether three-phase flow information of the to-be-measured fluid is accurate or not, determining whether to calibrate and compensate the microwave irradiation or not, selecting output information based on a comparison condition of the three-phase flow information, or giving out an abnormal early warning to a metering environment, and further, outputting the output information. According to the invention, abnormal risk identification is rapidly carried out according to the specific environment condition of the mixed fluid, the measurement mode is adaptively optimized, and the detection precision of three-phase flow information is improved.

The invention discloses an electric power operation safety risk identification method and system based on fine granularity detection, relates to the field of electric power operation safety management, and solves the problems that the area proportion of substances on the surface of equipment is difficult to obtain through image analysis software, and the parallax value of a target pixel point is difficult to obtain through an SAD algorithm. The method solves the technical problems that a model is not constructed by taking a convolutional neural network as a basic framework to carry out region judgment and double early warning is not carried out, and comprises the following steps: obtaining a corrosion area proportion and a wear area proportion through image analysis software to obtain an equipment comprehensive damage proportion; a high-resolution binocular camera is used for collecting video data of an electric power operation site; obtaining a parallax value of a target pixel point and a corresponding parallax map, and obtaining a depth value and a three-dimensional coordinate of a corresponding point after obtaining the parallax value through an SAD algorithm; and a model is constructed by taking the convolutional neural network as a basic framework to judge the vehicle type, and whether an early warning signal is triggered or not is judged according to two judgment conditions.

The invention discloses a person and post matching system based on candidate geographical location information and retail stores, and relates to the technical field of post matching systems. The candidate geographic position information and retail store-based person and post matching system comprises a candidate information management module, a retail store information management module, a commuting data analysis and path planning module, a candidate and store matching module and a result display and feedback adjustment module. By collecting and processing commuting modes and time period preferences of candidates, a commuting path is planned in combination with a map service API, and commuting time considering congestion and congestion influence is calculated, so that the matching accuracy and practicability are improved. In addition, the system also combines factors such as working experience, skills and the like to carry out matching result optimization, so that bidirectional selection is realized, and the matching satisfaction degree is improved. And the result display and feedback adjustment module enables the user to visually see the matching result.

The invention discloses a mobile robot for autonomously mapping in an unknown closed space and a working method. The mobile robot comprises a robot main body, a three-dimensional laser radar, a two-dimensional laser radar, an inertial measurement unit and a wheel type odometer, according to the method, a mathematical model of scene information density is constructed, so that the relationship between the information density and navigation and map construction performance of a robot main body is obtained, quantification of the sparse degree of point clouds in an unknown environment space is realized, and autonomous navigation and decision making of the mobile robot in the unknown environment are realized; then, determining a target point based on the point cloud information density, constructing a three-dimensional point cloud map of the unknown closed environment by using a three-dimensional laser radar, and performing path planning and navigation on a two-dimensional grid map based on the two-dimensional laser radar to realize autonomous mapping of the mobile robot in the unknown environment; according to the invention, full-automatic path planning and obstacle avoidance in an unknown closed environment can be realized without relying on manual intervention, so that accurate mapping is carried out on the unknown environment, and the efficiency is high.

The invention relates to the technical field of model simulation, in particular to an energy consumption simulation method and system suitable for a grinding machine. The method comprises the following steps that a common material list of the grinding machine is obtained; extracting material attribute data according to the common material list of the grinding machine to obtain a material attribute data set; acquiring to-be-polished workpiece data and grinding wheel data of a polisher; utilizing a finite element analysis technology and the material attribute data set to carry out contact area grid model construction and material attribute assignment on the to-be-polished workpiece data and the grinding wheel data of the polisher to obtain a grid model endowed with material attributes; performing contact area calculation according to the grid model endowed with the material attributes to obtain contact area data; simulation parameter setting is carried out according to the contact area data, and a simulation parameter setting table is obtained. According to the method, thermal-mechanical dynamic coupling solution is introduced into modeling in the grinding process, so that the problem of unbalanced grinding energy consumption caused by insufficient consideration of the thermal effect is solved.

The invention discloses a method for processing urbanized big data based on geographic information data, and relates to the technical field of electric digital data processing. The method for processing urbanized big data based on geographic information data comprises the following steps: collecting and processing data, obtaining a time resolution coefficient and an adjustment index, obtaining a comparison result, and obtaining a regulation and control scheme. According to the method, the first time data is obtained by obtaining the time data and performing data preprocessing on the time data, then the time resolution coefficient is obtained based on the first time data, and meanwhile the regulation and control index is obtained according to the first time data and the reference time data; and comparing the obtained time resolution threshold with the time resolution coefficient to obtain a comparison result, and finally evaluating the time resolution based on the comparison result and the regulation index to obtain a regulation scheme, thereby achieving the effect of improving the accuracy of data acquisition frequency regulation when processing urbanized big data. The problem that in the prior art, when urbanization big data is processed, data collection regulation and control are not accurate is solved.

The invention discloses an SAR image classification network interpretability analysis method based on attribution reasoning. The SAR image classification network interpretability analysis method comprises the following steps of 1, obtaining an SAR image data set and a trained Transform classification network; 2, constructing an attention attribution measurement model, and calculating an attribution reasoning matrix of each level of the Transform classification network; 3, measuring the contribution value of the attention head, searching for a connection relation with a high contribution value in an attention mechanism, and carrying out interpretability analysis on a network structure; 4, constructing an attribution score matrix, quantifying the contribution degree of each layer of input Token to a network decision, and carrying out interpretability analysis on a key path of the network; and step 5, performing non-key Token pruning, and realizing input Token lightweight of the Transform classification network. According to the attribution reasoning interpretability analysis method provided by the invention, the action mechanism of the model can be explained from two perspectives of network structure analysis and network feature transfer analysis, and the interpretability of SAR image classification based on Transform is effectively improved.

The invention discloses an integrated vehicle lamp test and simulation system and a test method, and belongs to the field of vehicle lamp test. The system comprises a cabinet, an upper computer, a foresight camera camera obscura and a Labcar module. The upper computer is used for performing operation management on the whole test and simulation system, monitoring a test state, managing test parameters and test data, generating a test report, simulating a traffic scene, performing automobile dynamics configuration, editing and generating an automatic test script and a test sequence; the cabinet is used for performing power supply management on the test and simulation system, providing a power supply and a control signal for the Labcar module, and communicating with the upper computer and the Labcar module; the foresight camera camera obscura is used for capturing a virtual traffic scene. According to the integrated vehicle lamp test and simulation system and the test method, the systematic test capability is enhanced, the scene interaction verification capability is improved, the detection precision and objectivity are improved, the small defect detection capability is enhanced, and test data quantification and traceability are realized.

The invention relates to the field of heating cigarettes, in particular to a tobacco shred internal sizing adhesive force testing method which comprises the following steps: inserting a to-be-tested cigarette into a heating cavity of a heating smoking set, and heating and smoking; separating and taking out the heated and smoked cigarette to be detected from the heating smoking set, and dividing the cigarette to be detected into two parts, namely a tobacco shred section and a filter stick section; and inserting an extraction piece into the tobacco shred section along the axial direction of the tobacco shred section, separating the tobacco shreds and the cigarette paper in the tobacco shred section at a constant speed by means of the extraction piece, measuring the tensile force used in the separation process, and representing the adhesive force degree of the applied glue in the tobacco shreds according to the tensile force. The method can accurately, scientifically and objectively reflect the capability of bonding the tobacco shred section and the cigarette paper by the adhesive in the to-be-detected cigarette, quantitatively, standardly and objectively reflect the bonding force degree of the applied adhesive in the tobacco shred, and provides effective analysis data for the improvement of the tobacco shred formula and process of the heated cigarette; quantitative analysis is carried out on the internal sizing adhesive strength degree of tobacco shreds with different formulas and processes, and optimization and improvement are guided.

The invention provides a blueberry industry regional competitiveness evaluation model construction method, system and device and a medium, and belongs to the technical field of agricultural industry big data, and the method comprises the following steps: determining a blueberry industry regional competitiveness evaluation index system according to comparative advantages and competitive advantages in industrial competitiveness evaluation; calculating the weight of each evaluation index by using a weighting method, and determining the final weight of the evaluation index according to the Lagrange condition extremum principle; calculating the competitive power comprehensive index of the blueberry industry area; a data collection platform, a data calculation platform and a data release platform are built in advance, and collection of data corresponding to blueberry industry regional competitiveness evaluation indexes and calculation, analysis and release of the evaluation indexes are carried out. According to the method, the regional competitiveness of the blueberry industry is quantified, so that the development conditions of the blueberry industry in different regions can be directly compared; automatic data acquisition, index calculation, data storage and sharing are realized through a software platform, and the working efficiency is improved.

The invention discloses a method for calibrating a handle of an anchor rod trolley, which belongs to the field of automatic control and comprises the following steps of: dividing control signals of the handle into IN1 and IN2 according to a shaft 1 and a shaft 2; the IN1 and the IN2 are converted into calibration values R1 and R2; the minimum value and the maximum value of the handle in the positive and negative directions of the shaft 1 and the shaft 2 are calibrated; points are taken from intervals from the minimum value to the maximum value of the calibrated handle in the positive and negative directions of the shaft 1 and the shaft 2, and the intervals are equally divided into n intervals; according to the action characteristics of the execution unit in each working mode, independently setting return values in the controller for each point in the positive and negative directions of the shaft 1 and the shaft 2 in each calibration interface to obtain positive and negative characteristic curves of the shaft 1 and the shaft 2 matched with the corresponding working mode; and according to the R1 and the R2 in the current working mode, the R1 and the R2 are converted into corresponding control quantities PWM1 and PWM2 by searching positive and negative characteristic curves. Aiming at the low adaptability of the anchor rod trolley handle in the prior art, the anchor rod trolley handle adapts to different working modes.

The invention relates to the technical field of concurrent resource optimization, in particular to a concurrent resource optimization method and system, equipment and a medium. The method comprises the following steps: firstly, acquiring a system running state in real time through a resource monitoring interface, and performing idle judgment in combination with multiple dimensions such as a connection number, idle duration and request waiting; then, based on idle detail content, intelligently matching an optimization opportunity, and generating an optimization strategy through dynamic balance of an idle degree and a request density; finally, resource scheduling is carried out on the target optimization area, efficient utilization of concurrent resources is achieved, and user experience is improved.

The application discloses a photoelastic transparent soil three-dimensional stress-deformation full-field cooperative measurement device and a use method thereof. The device comprises a loading system, a stress-strain measurement system and a model test system. The model test system comprises an optical platform and a model groove arranged at a central position of the optical platform and used for containing a sample to be tested. The loading system is arranged above the optical platform and used for applying axial pressure to the sample to be tested. The stress-strain measurement system comprises a camera module, a laser module, a light source module, a guide rail and a control system II. During work, the camera module, the laser module, the light source module and the guide rail are adjusted by the control system II, so that the camera is scanned around the sample to be tested, deformation images are collected, full-field strain is obtained, and a three-dimensional digital model of the soil body is reconstructed. The device has high integration, can obtain stress distribution information of any cross section and any direction in the material, and overcomes the inherent defects that a two-dimensional photoelasticity cannot reflect stress gradient in the thickness direction.

The present application relates to the technical field of multi-cause intelligent analysis in medical diagnosis, and particularly relates to an osteoporosis detection method and system based on data analysis and artificial intelligence. The method comprises the following steps: S1: obtaining primary osteoporosis data and secondary osteoporosis data and determining synergistic data, and determining antagonistic masking data according to the synergistic data; S2: obtaining a first layer dominant right conversion sequence according to the synergistic data and the antagonistic masking data; S3: obtaining a synergistic data internal dominant relationship sequence and an antagonistic masking data internal dominant relationship sequence respectively according to the synergistic data and the antagonistic masking data, and generating a complete dominant relationship graph in combination with the first layer dominant right conversion sequence. The present application separates and analyzes the synergistic and antagonistic modes of primary and secondary osteoporosis, constructs a dynamic dominant right sequence, quantifies the evolution of mixed cause weights, and provides data support for individualized precise diagnosis and treatment.

The invention relates to the technical field of fuel ratio regulation and control, in particular to a fuel self-adaptive ratio regulation and control method for a waste multi-fuel combustion boiler, which comprises the following steps of: obtaining combustion characteristic parameters of various fuels, calculating combustion performance values of the various fuels, grouping and dividing the fuels according to the combustion performance values, and regulating and controlling the fuel ratio of the waste multi-fuel combustion boiler. Calculating a difference value of two groups of fuel combustion performance mean values to obtain an initial performance difference value, determining a fuel proportioning parameter according to the initial performance difference value, monitoring and analyzing temperature data and waste gas emission amount data in a boiler operation process, calculating a temperature fluctuation value and a waste gas emission fluctuation value to obtain a combustion quality influence coefficient, and calculating a combustion quality influence coefficient according to the temperature fluctuation value and the waste gas emission fluctuation value; collecting a steam pressure oscillogram and feed water flow in equipment operation parameters, calculating a steam pressure fluctuation value and a feed water flow fluctuation value to obtain an equipment operation influence coefficient, performing weighted fusion on the combustion quality influence coefficient and the equipment operation influence coefficient to obtain a comprehensive influence value, and performing calibration analysis on an initial performance difference value according to the comprehensive influence value; therefore, the self-adaptive regulation and control of the fuel ratio parameters are realized.

The application discloses an energy consumption metering method and device based on digital twinning, which comprises the following steps: collecting building energy consumption related data based on a pre-constructed building energy consumption digital twinning model; analyzing the energy consumption of the building according to the building energy consumption related data, and giving topological correlation characteristics, multi-scale time characteristics, equipment health characteristics and environmental lag characteristics; combining a pre-constructed energy consumption coefficient prediction model to analyze the topological correlation characteristics, multi-scale time characteristics, equipment health characteristics and environmental lag characteristics, and giving environmental influence coefficients, topological correlation coefficients and space utilization coefficients; determining a benchmark energy consumption prediction model through the environmental influence coefficients, topological correlation coefficients and space utilization coefficients, combining an energy consumption compensation coefficient, and giving building target energy consumption, so as to realize accurate prediction of benchmark energy consumption and dynamic compensation of actual energy consumption, realize accurate metering of building energy consumption, and improve the analysis accuracy of building energy consumption.

The invention provides a non-drug intervention strategy making method and system for an insomnia patient, and the method comprises the steps: obtaining a traditional Chinese medicine physiological reference parameter of the patient, mapping the traditional Chinese medicine physiological reference parameter to a continuous physiological waveform, removing a static component matched with a traditional Chinese medicine physiological reference from the continuous physiological waveform, and obtaining a non-drug intervention strategy of the patient; obtaining a pure stress shock waveform triggered by external disturbance, and calculating a permeation gain of the environment characteristics to the pure stress shock waveform in the environment path; calculating the interference intensity of the traditional Chinese medicine syndrome characteristic data on the pure stress shock wave form in the syndrome path; performing state object division on the current sleep state of the patient based on the ratio relationship between the permeation gain and the interference intensity; and dynamically adjusting the output weights of the physical environment adjustment instruction, the traditional Chinese medicine syndrome adjustment instruction and the cognitive intervention instruction in a preset non-drug intervention library based on the recognition result of the state object and the recovery characteristic time parameter of the physiological steady state in the corresponding state. And a dynamic self-adaptive household non-drug intervention scheme is provided.

The invention belongs to the technical field of semiconductor manufacturing and testing, and discloses a matching evaluation method, system and device of a WAT testing machine and a storage medium. The method comprises the following steps: acquiring test data of a target and a reference machine, generating comparability conditions based on information such as products and stations to perform data alignment and preprocessing, and outputting an alignment data set and a quality index; calculating a multi-dimensional feature vector including distribution, risk, trend and wafer spatial features for each test item based on the alignment data; the feature vector and the alignment quality index are fused, a difference score is calculated, and evaluation is carried out in combination with a self-adaptive threshold value dynamically generated based on historical data and parameter importance; and finally, outputting a difference parameter list and an evaluation result, simultaneously introducing an AI model to carry out comprehensive judgment, and continuously optimizing through a feedback closed loop. Through the method, automation, quantification and intelligentization of machine matching evaluation are realized, and evaluation efficiency, consistency and accuracy are remarkably improved.

The application discloses an intelligent bid evaluation auxiliary decision-making system based on an AI large model, relates to the technical field of intelligent bid evaluation, and comprises a data acquisition module, an information extraction module, a graph construction module, a factor matching module and an intelligent scoring module; the data acquisition module acquires original data of bid invitation and bid documents; the information extraction module performs multi-modal information extraction on the original data to generate a structured factor set; the graph construction module analyzes the structured bid invitation factor set and constructs a bid invitation demand knowledge graph; the factor matching module aligns and maps the structured bid factor set with the knowledge graph to generate a matching relationship network; and the intelligent scoring module utilizes an AI large model, combines historical bid evaluation cases and real-time market quotations, and outputs a multi-dimensional preliminary quantitative scoring vector of bidders; the system can improve the completeness of bid evaluation information extraction and the objectivity of bid evaluation results, and assists efficient development of bid evaluation work.

The invention provides a method and system for accurately controlling the temperature of an adhesive production reaction kettle, and relates to the technical field of adhesive production, and the method comprises the steps: applying a transient heating pulse to the reaction kettle in adhesive production, collecting the surface temperature data of a container wall, processing the data, calculating a temperature decline curve, and extracting key information of heat transfer characteristics. A heat abnormal area caused by uneven mixing is identified based on spatial distribution of key information, and the thermal state change of the adhesive reaction degree is estimated in combination with a time change mode. And adjusting a heating pulse mode and a working state of the stirring device according to the abnormal area and the change mode, and introducing a pause detection stage to collect surface temperature feedback under weak heating pulses so as to confirm an adjustment effect. And finally, associating the key information with the reaction degree based on feedback to generate a temperature adjusting command, and adjusting the heating or cooling intensity, so that accurate control on the temperature of the reaction kettle can be realized, and the production quality and efficiency are improved.

This invention relates to the fields of tunnel engineering and 3D geological modeling technology, specifically to an intelligent modeling method and system for 3D geological uncertainty in tunnels based on transition probability geostatistics and sparse boreholes. The method includes: S1, integrating multi-source data to construct a 3D geological conceptual model; S2, statistically characterizing a one-dimensional transition probability matrix, calculating and fitting a spatial continuity and 3D anisotropic variability function model; S3, calculating the prior spatial probabilities and transition adjustment factors for various lithologies, obtaining the posterior lithology distribution of nodes through Bayesian intelligent updating, and initially assigning lithology categories to nodes through random sampling; S4, assigning the most probable lithology category to each grid node, calculating the variance of lithology values ​​across all implementations, and measuring model uncertainty; S5, outputting the optimal 3D uncertainty model for the tunnel; and S6, verification and evaluation. This invention can effectively achieve 3D heterogeneous modeling and explicit quantification of uncertainty under strong geological constraints.

The application provides a wireless charging system, method, external charging device and storage medium, including an implantable medical device and an external charging device for wireless energy transmission with the implantable medical device, the wireless charging system further includes a voice prompt module and a control module, the control module is configured to: control the external charging device to work in a scanning mode to obtain a charging efficiency local distribution map for a region where the implantable medical device is located; based on the charging efficiency local distribution map, determine at least one optimal charging target position, and generate user navigation instructions corresponding to the optimal charging target position; control the voice prompt module to broadcast the navigation instructions to guide the user to move the external charging device to the optimal charging target position, the scheme solves the problem that the user cannot determine the best charging position, thereby causing difficult alignment, low charging efficiency, and improves the alignment accuracy, energy transmission efficiency, operation safety and user operation convenience of wireless charging.

The application belongs to the technical field of artificial intelligence, and discloses a question and answer identification method and device, electronic equipment and readable storage medium, the method comprises the following steps: receiving a question and answer request for a target question; based on the question and answer request for the target question, a pre-trained question and answer model is used to determine the answer corresponding to the target question; wherein the question and answer model is a student model obtained based on a second sample data set and a teacher model, and the teacher model is constructed based on a first sample data set and a transformer-based bidirectional encoding representation model. In this way, when question and answer identification is performed, the response speed of question answering can be improved and resource consumption can be reduced.

The application relates to a ROV-based pressure-maintaining fixed-depth seawater in-situ measuring device and application thereof, and belongs to the technical field of seawater in-situ measurement. The pressure-maintaining fixed-depth seawater in-situ measuring device comprises a measuring cylinder, a gas sensor, an upper end cover driving assembly and a lower end cover driving assembly. The measuring cylinder comprises a cylinder body, an upper end cover and a lower end cover. The cylinder body is installed on an ROV, and the top end and the bottom end of the cylinder body are both provided in an open manner. The upper end cover is used for opening or closing the top end opening of the cylinder body, and the lower end cover is used for opening or closing the bottom end opening of the cylinder body. The gas sensor is arranged in a measuring cavity surrounded by the upper end cover, the lower end cover and the cylinder body. The upper end cover driving assembly and the lower end cover driving assembly are both connected to the control system of the ROV, so as to drive the upper end cover and the lower end cover to be synchronously opened or synchronously closed. The ROV-based pressure-maintaining fixed-depth seawater in-situ measuring device can realize in-situ measurement of seawater samples at different water depths, and can be used for measuring the balance time of the gas sensor under different water pressure environments.

The present application relates to the field of medical care informatics, and in particular to a method for determining the state of a drug-dependent person. It includes: obtaining an infrared image of a preset body position of a drug-dependent person; obtaining an infrared norm deviation according to the infrared image and a norm database; obtaining the physical fitness deviation of the drug-dependent person, which is obtained according to the BMI index deviation, body fat rate deviation, vital capacity deviation, closed-eye one-leg standing time deviation, grip deviation and reaction time deviation; obtaining the mental health deviation of the drug-dependent person, which is obtained according to the anxiety deviation, depression deviation, drug dependence deviation and psychological defense deviation; obtaining the overall deviation of the drug-dependent person according to the infrared norm deviation, physical fitness deviation and mental health deviation of the drug-dependent person, and then determining the state of the drug-dependent person. The present invention can determine the state of a drug-dependent person.