238 results about "Evaluation data" patented technology

This invention provides an intelligent wake-up method, an intelligent control system, an electronic device, and a storage medium. The intelligent control system includes at least a control module and an LED light panel. The LED light panel is equipped with an LED light source module. When the wake-up conditions are met, the control module controls the color temperature of the LED light source module to be equal to a color temperature threshold during the wake-up period. The color temperature threshold is configured based on color temperature-emotion evaluation data. During the wake-up period, the control module controls the output power of the LED light source module to change linearly with time, causing the illuminance of the LED light panel to change from dark to bright, simulating the sunrise process, thereby waking up the user. The difference between the integral of the LED light panel's illuminance over time and the eye exposure threshold is within a preset range. The eye exposure threshold is configured using eye exposure data, arousal evaluation data, and sleep quality data.

A method is provided for controlling how a privacy enhancement technology (PET) is applied to a data stream, the method being performed by an evaluation device (2, 3). The method includes: evaluating at least one parameter of the data stream or the data content of the data stream, wherein the at least one parameter indicates a characteristic that influences how PET is applied; determining a change in the at least one parameter; generating a privacy signal based on the change in the at least one parameter; establishing a signaling channel (16) to a server (6), wherein the signaling channel is different from a data stream channel (15) used for transmitting the data stream; and sending the privacy signal to the server via the signaling channel to influence how PET is applied to the data stream.

The application relates to the technical field of robot vision control, and discloses a robot air attitude real-time correction method based on vision prediction. The method collects a vision data sequence of a robot air attitude, calculates attitude prediction parameters at each time point through a vision processing algorithm, and generates an initial data set; subsequently, adjacent attitude points are analyzed through clustering based on a space-time proximity relationship, consistent sections and conflict sections of motion modes are identified, and a partitioned labeling result is formed. Then, the motion speed and time sequence data of the attitude points in the consistent sections are extracted, the fluctuation characteristics are analyzed in combination with the attitude angle change amount, the motion influence strength under the influence of external environment interference is evaluated, and motion influence superposition evaluation data is generated. Finally, the attitude deviation points in the evaluation data whose response values exceed a reference value and are located in the conflict sections are detected, a deviation point set is constructed, the points needing correction are marked according to the detailed attitude information of the deviation points, real-time attitude correction instructions are generated and output.

The application discloses a parking effect evaluation method, an electronic device and a storage medium. The parking effect evaluation method comprises the following steps: acquiring first image data collected by a vehicle-mounted surround-view camera; performing image processing on the first image data to obtain a target bird's-eye view; performing parking space detection processing on the target bird's-eye view to determine parking space corner point coordinates; and evaluating the parking effect according to the parking space corner point coordinates and vehicle size parameters. In this way, the first image data is collected by the vehicle-mounted surround-view camera, the target bird's-eye view is obtained through image processing, the parking space corner point coordinates are determined through parking space detection, and the parking effect evaluation is completed in combination with the parking space corner point coordinates and the vehicle size parameters, thereby solving the problems that the automatic parking effect evaluation depends on preset scenes and other additional auxiliary conditions, the adaptation range is limited, and the evaluation data is difficult to obtain, and effectively improving the accuracy of the evaluation result and the ability to adapt to complex and variable actual parking scenes.

The present application relates to geothermal resource development and evaluation technical field, especially to the balanced water and heat type geothermal resource dynamic evaluation method, including: collecting the flow, temperature and pressure data of the produced fluid and the recharging fluid, and carrying out time synchronization, outlier elimination and time series reconstruction processing on the data to form a continuous operation data set; jointly analyzing the time series change of the operation data set, extracting flow response characteristic quantity and heat exchange response characteristic quantity, and dividing the underground heat reservoir into flow and heat storage units according to the similarity of the characteristic quantity; on the scale of the flow and heat storage unit, respectively establishing a flow structure model and a heat exchange structure model, and coupling them, through a unified state variable to describe the corresponding relationship between the fluid migration behavior and the energy transfer behavior, a flow and heat storage dynamic evaluation model is constructed; based on the model, the change of the state variable of each flow and heat storage unit with time during the recharging operation process is calculated, and the dynamic evaluation data is obtained.

The application provides a satellite communication power adaptive regulation method, system and device, which divides the space where satellite communication belongs into multiple space grid areas according to a preset space division scale; acquires satellite sensing data, space weather data and near-earth weather data in each space grid area to determine communication link loss evaluation data corresponding to each space grid area; generates space interference summary information according to the loss evaluation data corresponding to each space grid area and location data thereof; and adjusts the transmission power of satellite communication in each space grid area according to the space interference summary information. The method and system of the application collect weather data in the space area and the near-earth area thereof to determine loss evaluation data, and realize dynamic adaptive adjustment of satellite transmission power in each space grid area based on the loss evaluation data, thereby improving the reliability of satellite communication in a complex space environment.

This invention discloses a method and apparatus for determining the power limit value of a power battery. The method includes: acquiring target operating condition data of the vehicle; determining a first power limit ratio value of the power battery in a pulse temperature rise table based on a first temperature value and the target temperature value of the power battery; determining a second power limit ratio value of the power battery based on the vehicle's power performance target data and target evaluation data; determining the minimum value between the first and second power limit ratio values ​​as the target power limit ratio value of the power battery; and determining the power limit value of the power battery based on the target power limit ratio value and the allowable power value of the power battery. This invention solves the technical problems that high-temperature power limit protection methods for batteries cannot cover operating conditions with fast vehicle speed response, and cannot simultaneously consider the safety of battery and vehicle use, vehicle power performance, and user experience.

The application provides a visual language large model adaptive bias evaluation method for evaluating bias performance of a target model on a specific task, and the method comprises the following steps: S1, obtaining an initial evaluation dataset, wherein the initial evaluation dataset comprises a plurality of evaluation data; S2, fine-tuning a preset large language model using the initial evaluation dataset in a preset fine-tuning manner to obtain an initial data generator; and S3, generating evaluation data based on the initial data generator to perform multiple rounds of bias evaluation on the target model, wherein in each round of bias evaluation, based on all evaluation data corresponding to the last round of bias evaluation, a data generator corresponding to the last round of bias evaluation is iteratively updated according to a preset objective function to obtain a current round data generator, and the current round data generator is used to generate a current round evaluation dataset to perform bias evaluation on the target model.

The present application relates to the technical field of transformer evaluation, and particularly relates to a light-weight medium-high frequency transformer conversion efficiency evaluation method and system, which comprises the following steps: obtaining structure winding parameters, light-weight parameters and operation condition parameters of a transformer to be evaluated, and constructing an evaluation data set; constructing an efficiency evaluation model, which at least comprises an iron loss sub-model and a copper loss sub-model, and setting model parameters of the iron loss sub-model and the copper loss sub-model as to-be-identified parameters; obtaining test data corresponding to the transformer to be evaluated, and performing parameter calibration on the to-be-identified parameters; inputting the evaluation data set into the calibrated efficiency evaluation model, outputting loss decomposition results and efficiency results of each working condition point, and obtaining conversion efficiency evaluation results. Through the present application, the problem that the efficiency evaluation of a light-weight medium-high frequency transformer in the prior art relies on experience or single-point testing and is difficult to model and calibrate in multiple working conditions, thereby leading to large deviation, is effectively solved, and accurate evaluation of multiple working condition loss decomposition and conversion efficiency is realized.

We provide the system. [Solution] A data acquisition method for obtaining actual animal-based food shape data, An artificial intelligence means having a generative model for generating the three-dimensional shape of alternative ingredients from acquired shape data and similar data, A three-dimensional printing method for forming alternative food ingredients three-dimensionally using plant-derived raw materials based on the generated three-dimensional shape, A data processing means for feeding back evaluation data obtained from consumers to the generation model, A system that includes this.

A battery diagnosis device may include a database configured to store design data during design process for a battery, process data collected during a process of manufacturing the battery, evaluation data collected during a process of evaluating the battery, and field data collected during a field process with the battery. A data link unit is configured to link the design data, the process data, the evaluation data, and the field data. A processor configured to, by executing an algorithm stored in a memory, (i) extract features based on each of the design data, the process data, the evaluation data, and the field data in the order of the field data, the evaluation data, the process data, and the design data, and (ii) generate battery status information including information about the cause of deterioration of the battery and the timing of deterioration of the battery based on the extracted features.

The application discloses a mechanical arm task allocation method and device and a storage medium. The method comprises the following steps: acquiring current vibration spectrum data, current joint current data and current environment temperature of each mechanical arm, and analyzing assembly task data from a task instruction; inputting the current vibration spectrum data into a life prediction model to output residual life data of each component; inputting the current joint current data, the current environment temperature and the assembly task data into a loss evaluation model to output loss evaluation data of each component caused by the task instruction; determining an actual life attenuation constraint value based on a preset dynamic adjustment strategy set, the current environment temperature and the loss evaluation data; inputting the residual life data and the loss evaluation data into a double-target optimization model, and generating task allocation data based on a preset energy consumption constraint threshold and the actual life attenuation constraint value. The application can improve the service life of each component of the mechanical arm.

The present disclosure relates to a prostate image-based evaluation method, device, equipment, medium and product, the method comprising: acquiring first image data of a prostate target area matched with a structure evaluation model, the structure evaluation model comprising a structure morphology network and a structure evaluation network; performing feature extraction on the first image data through the structure morphology network to obtain morphology feature data, the morphology feature data representing quantitative information of a structure morphology of the prostate target area; and performing structure evaluation according to the morphology feature data through the structure evaluation network to determine structure evaluation data of the prostate target area. The present embodiment solves the problem of insufficient accuracy of an artificial evaluation mode, guarantees the objectivity and repeatability of prostate evaluation tasks, and provides assistance for promoting the standardization iteration of prostate intervention technology.

Disclosed herein a method and device for acquiring training data for inference model. The method includes: identifying a state indicator indicating whether there is a similarity between preceding selected image data and previously acquired image data subsequent to the selected image data based on acquisition of image data around the device; generating a similarity between the preceding selected image data and the acquired image data based on presence of a similarity in the state indicator; generating selected evaluation data including a score of the acquired image data according to an evaluation using acquired feature information of the acquired image data based on determining that the similarity exceeds a first reference value; and / or selecting the acquired image data as the selected image data for the training data to replace the preceding selected image data based on determining that the score of the acquired image data exceeds the score of the preceding selected image data.

To appropriately assess customer emotions in a call center. [Solution] An information processing device comprising: an acquisition unit that acquires text data indicating the content of a conversation between a customer and an operator in a call center; an evaluation unit that inputs evaluation data based on the text data and a prompt including a request to select from multiple candidates that categorize the customer's emotions into a large language model (LLM) and acquires the output of the large language model to evaluate the customer's emotions; and an output unit that outputs the processing result of the evaluation unit.

The application discloses a Bloom cognitive hierarchy constraint-based achievement-oriented education diagnosis method and system. The method takes course outline text and student evaluation data as input, and realizes the automatic diagnosis of course goal achievement through three structural modifications in the large language model Transformer architecture: the logarithmic value of the cognitive hierarchy transfer matrix is embedded as a learnable bias item in the attention score calculation path to realize feature coding of cognitive hierarchy perception; the continuous differentiable relaxation technique is used to establish an end-to-end differentiable inference path for the course goal achievement weight; and the Bloom partial order constraint is coded as a training loss, so that the diagnosis result meets the cognitive hierarchy progressive relationship. The three modifications are optimized by a joint loss function, which significantly improves the diagnosis accuracy and promotes the interpretability and scientificity of the large language model diagnosis in the achievement-oriented education scene.

The application discloses a disc shear process parameter multi-objective optimization method based on machine learning and NSGA-II, acquires existing disc shear cutting related data of a factory, and constructs a disc shear cutting quality evaluation data set; a multi-model prediction system containing ANN, XGBoost, LightGBM and CatBoost is established, combined with Bayesian optimization to realize automatic optimization of hyperparameters, and the optimal prediction model combination suitable for different defects is screened; based on the optimal model combination, an NSGA-II multi-objective optimization model is constructed, and under the constraint of industrial operation parameters, a Pareto process parameter solution set is obtained, and the optimal solution is screened. The method combining industrial measured data, multi-model prediction and multi-objective optimization algorithm is adopted to mine the internal coupling correlation between process parameters and cutting quality, realize the collaborative improvement of multiple defects, and has important guiding significance for improving the cutting quality of the strip steel and enhancing the production benefit.

The application belongs to the technical field of big data processing, and discloses an intelligent automobile accessory warehouse management system and method based on the Internet of Things; the method comprises the following steps: collecting automobile accessory attribute data, marking the accessories and cleaning the data in sequence, and constructing an accessory basic database; collecting original sensing data and associating the accessory basic database, obtaining a multi-source storage data set, performing accessory partitioning, and generating optimal warehouse layout information; obtaining real-time position information of the accessories, combining the optimal warehouse layout information, and outputting an efficient work optimization path; collecting accessory warehouse entry and exit records in real time, performing state prediction, and outputting referenceable inventory information; performing quality detection on the accessory basic database based on the referenceable inventory information, and outputting accessory evaluation data; collecting behavior data of workers and performing behavior pattern analysis, and generating behavior evaluation data; constructing a warehouse strategy, and sending the warehouse strategy to a preset automobile accessory management system; and high-efficiency and high-precision warehouse management is realized.

The application relates to the technical field of medical systems, and particularly discloses a new-born baby comprehensive development monitoring and intervention guidance system which comprises a data acquisition module, a development stage identification module, a multi-dimensional development evaluation module, a deviation calculation module, an intervention scheme generation module and an intervention execution and feedback module; the data acquisition module is used for acquiring multi-dimensional development data of a new-born baby, wherein the multi-dimensional development data at least comprises physiological parameters, neurobehavioral data, physical growth data, feeding data and sleep data; and the development stage identification module is used for determining a current development stage according to a corrected age of the new-born baby. Through multi-dimensional data acquisition and a whole-process standardized preprocessing mechanism, the new-born baby physiological, neurobehavioral, physical growth, feeding and sleep multi-dimensional development data are integrated, the systematic errors and external interference of multi-source heterogeneous data are eliminated through a standardized preprocessing process, and the stability, reliability and effectiveness of the development evaluation data are ensured.

The disclosure relates to a method and a control device for evaluating data from a vehicle's environment using at least one sensor device of the vehicle. The method comprises several process steps. In a first step, external environmental data is acquired by the sensor device outside the vehicle. Furthermore, internal state and / or interaction data is acquired by the sensor device inside the vehicle. Finally, a real-time comparison of the external environmental data and the internal state and / or interaction data is performed using an AI-based processing unit.Furthermore, the compared data is evaluated to provide action options tailored to the identified needs of vehicle users, and control signals are generated to provide and / or adapt vehicle functions based on the action options.

This invention discloses a method and system for evaluating the uniformity of asphalt pavement based on image recognition, belonging to the field of quality monitoring technology. The method includes the following steps: generating a baseline state snapshot and storing it in a state buffer; generating a lightweight feature signature; calculating the difference between the corresponding dimensions of the feature signature and the predicted feature vector; acquiring the actual aggregate distribution and texture information of the current frame as a new full feature set, generating a real-time uniformity evaluation result for the current frame; and constructing and outputting a standardized evaluation data package. This invention introduces a construction data-driven feature prediction and lightweight feature signature fast verification mechanism, intelligently skipping the complete calculation of redundant frames during continuous acquisition and only analyzing frames with abrupt feature changes. This solves the problem of severe computational waste and evaluation results lagging behind the construction progress caused by the existing technology of performing complete feature calculations on every continuously acquired image frame.

This invention provides a technology maturity evaluation system and method for scientific and technological achievements. The system includes: a multi-source data fusion module for integrating basic information on scientific and technological achievements, automatically captured data, and historical evaluation data; data processing to establish a standardized database; an evaluation standard management module storing data from a thirteen-level technology maturity evaluation system; an intelligent algorithm evaluation module for quantifying and assigning values ​​to each indicator, weighting and summing all indicator values ​​to calculate a comprehensive score, and then calibrating the comprehensive score obtained by the system with expert opinions to obtain the evaluation result; a dynamic tracking and iteration module for updating the evaluation results; a result output and optimization guidance module for visualizing the evaluation results; and a permission management and security module for controlling different permissions for the management, expert, and application ends. This invention achieves objective quantification, dynamic tracking, deviation calibration, and customized guidance for the maturity of scientific and technological achievements.

The invention relates to a patient decision support system and operating method based on self-care algorithms that evaluate patient activity for patients diagnosed with liver cirrhosis, which is intended to monitor and manage patients' health conditions, provides regular data tracking and personalised recommendations, tracks patients' daily and weekly activities, medication use, diet, and exercise routines, collects and evaluates the data, and presents user-specific recommendations, and which uses artificial intelligence and care algorithms to determine, on the basis of the patient's health data, which treatment and care pathways are the most appropriate.

A comprehensive prediction method for drinking water taste based on sensory evaluation and physicochemical parameters is disclosed. The method includes the following steps: S3, sensory evaluation data collection, where the sensory evaluation data includes the following dimensions: odor and taste; and S4, physicochemical parameter detection, including at least the following indicators: pH value, total hardness, and free chlorine concentration. S5, data standardization and preprocessing; S6, construction of a comprehensive taste prediction model: based on the standardized sensory evaluation data and the processed physicochemical parameter data, a multivariate fusion data model is constructed; and S7, inputting each variable according to the pattern of a multiple linear regression model to obtain the final calculation result under the control of multiple variables in the model. This invention's prediction method features a unified evaluation scale, strong comparability of results, significantly improved objectivity of the evaluation, quantitatively correlates taste and physicochemical indicators, and ensures that different evaluators maintain consistency in their evaluation starting point and scale, thereby significantly reducing random fluctuations in the model input data and improving the stability of the prediction model.

This invention discloses a multi-dimensional data-driven quantitative assessment method and system for team situational awareness, relating to the fields of aviation safety and human factors engineering. The technical problem it addresses is that existing multi-dimensional data suffers from inconsistent dimensions and a lack of quantitative team collaboration, making it difficult to directly assess team situational awareness. This invention collects evaluation data and eye-tracking data from team members during task execution. Based on subjective data, it calculates individual situational awareness scores and constructs a team collaboration coefficient. Using the weighted average of individual situational awareness scores as a benchmark, it applies the team collaboration coefficient nonlinearly to obtain a comprehensive team situational awareness score. This score is then standardized and correlated with the eye-tracking data to obtain the analytical results. This invention achieves a quantitative assessment of team situational awareness by fusing subjective and objective data, providing a reference for evaluating team cognitive status.

The present application relates to big data technology, and discloses a bad review classification method based on a BERT model, which comprises the following steps: data integration and data cleaning are performed on evaluation information to obtain effective evaluation data, and manual sentiment labeling is performed on the effective evaluation data to obtain labeled data; the labeled data is used to perform parameter tuning on a pre-trained BERT model, the trained BERT sentiment classification model is used to classify the evaluation data, positive sentiment data is removed, and data with an emotional category that is not equal to a star level in the evaluation is extracted, screened and labeled; the labeled data and the effective evaluation data are used to retrain the BERT model; negative sentiment data is subjected to word segmentation, a BTM (Bigram Topic Model) is used to extract a bad review theme of the negative word segmentation, and the evaluation information is classified according to the bad review theme. The present application also provides a bad review classification device, equipment and medium based on the BERT model. The present application can improve the accuracy of customer bad review information extraction.