24 results about "Life stage" patented technology

Provided are a method for battery derating protection, an electronic device, and a storage medium. In the method, application stages of a to-be-tested battery are correspondingly adjusted based on decline of a state of health of the to-be-tested battery; when the to-be-tested battery is in a beginning of life stage or a middle of life stage, a state-of-charge usage interval of the to-be-tested battery is set to an initial usage interval; when the to-be-tested battery transitions from the middle of life stage to an end of life stage, the state-of-charge usage interval is narrowed to a limited usage interval; when the to-be-tested battery transitions from the safety of life stage to the hazard of life stage, the to-be-tested battery is forcibly discharged to the lower limit of the limited usage interval; after completing forced discharge, the state-of-charge usage interval of the to-be-tested battery is set to a single value.

The invention provides a bearing fault diagnosis and accurate operation and maintenance method based on a fault stage, and the method comprises the following steps: S1, calculating fault feature indications for various bearing faults according to vibration signals collected under a specific working condition; s2, determining a starting point of each bearing fault stage according to the fault feature indication; s3, fault diagnosis is carried out according to the current full-life stage of the bearing; and S4, based on the fault diagnosis in the step S3, formulating a maintenance, maintenance or thorough overhaul strategy based on the bearing fault stage. According to the method, the problem that a fault warning is sent out too early due to the fact that a fault stage is not considered in traditional threshold setting is solved, and waste caused by premature decommissioning of parts is avoided. The problem that a fault warning is sent out too late due to the fact that the fault stage is not considered in traditional threshold setting is solved, the situation that the warning is sent out in the failure stage is avoided, and therefore the situation that a whole machine system faces reliability and safety threats is avoided.

The invention discloses a biological age assessment method and system based on full life cycle DNA methylation and application, and belongs to the technical field of bioinformatics. The method comprises the following steps: firstly, carrying out quality control and standardization treatment on obtained original DNA methylation data; then, screening differential methylation sites significantly related to calendar age as features; then, by taking calendar age as a target variable, constructing a regression model by adopting a LightGBM gradient lifting framework to obtain a methylated clock model; then, predicting the DNA methylation age of the individual by using the model, and calculating an epigenetic age acceleration value based on the deviation between the DNA methylation age and the calendar age; and finally, carrying out correlation analysis on the age acceleration value and health or physiological indexes of different life stages, so as to evaluate the biological aging state of the individual and predict related health risks. The method covers the whole life cycle, is suitable for Chinese population, and can provide an effective tool for clinical disease risk prediction, health management and anti-aging intervention effect evaluation.

The application discloses a kind of space rolling bearing life stage identification method based on CAHTL, utilize CAHTL network to carry out space rolling bearing life stage identification, CAHTL network includes pre-encoding network, heterogeneous transfer learning network and same domain general contrast learning network;Space rolling bearing life stage identification includes the following steps: S1, information compensation;S2, heterogeneous transfer learning network pretraining;S3, construct feature transfer loss function;S4, construct same domain general contrast learning loss function;S5, construct classification loss function;S6, construct the joint loss function of CAHTL, using random gradient descent and momentum asynchronous update mode will joint loss function training to convergence;S7, utilize CAHTL network to the sample to be measured of target domain classification.The application can utilize the known life stage training sample of small, non-equivalent, partial information defect of space rolling bearing historical working condition under current working condition to the sample to be measured and carry out higher accuracy life stage identification.

The invention provides a charging parameter adjustment method and device, a chip system and a program product, and relates to the technical field of communication. According to different life stages and / or different charging types and / or different charging stages of a life cycle, multiple sets of CV parameters are preset respectively, and each set of CV parameters comprises a temperature range, a charging voltage and a charging current corresponding to one life stage and / or one charging type and / or one charging stage. When the life stage, the charging type or the charging stage are changed, a set of CV parameters is determined, and then the battery is charged according to the charging current in the set of CV parameters. The multiple sets of CV parameters are respectively preset for different life stages, and / or different charging types, and / or different charging stages, so that the corresponding relation among the temperature, the charging current and the charging voltage is not unique, and the attenuation speed of the service life of the battery can be slowed down by dynamically adjusting the CV parameters.

A method is disclosed for directing targeted advertisements to potential multicultural consumers, who are a subset of members of an ethnic group associated with a homeland country and a native language. Information data associated with the members of the ethnic group is retrieved, which includes an age, a household size, a household income, and a number of visits to the homeland country for each of the members. A culture cycle model for the ethnic group representing a plurality of life stages of the members is generated, and then at least one of the life stages to which the potential consumers belong is identified. Based on that identified life stage, characteristics of the advertisements to be directed to the potential consumers are determined, including a language of the advertisements, and then the advertisements are directed to the potential consumers.

This invention relates to the field of data processing technology for predictive purposes, and discloses a method for adjusting the power generation performance of an energy system throughout its entire life cycle. The method determines the parameter boundaries of a wind-solar-storage power supply system, divides the entire life cycle planning period into multiple consecutive life stages, and determines the load demand input for the entire life cycle. It sets a baseline power generation performance at the initial commissioning stage, calculates the degradation maintenance level for each stage, establishes a monotonic mapping relationship between the degradation maintenance level and maintenance intensity, constructs a stage-dependent model for calculating available power generation capacity coupled with degradation and maintenance, and obtains available power supply capacity parameters for each stage of the entire life cycle. It generates a maintenance time series distribution through Monte Carlo simulation and constructs a set of life cycle power generation performance evolution scenarios. With the goal of minimizing the total cost throughout the entire life cycle, a mixed-integer linear programming model is constructed to obtain the optimal capacity configuration and adjust the power generation performance throughout the entire life cycle. This method solves the problems of ignoring degradation maintenance and inaccurate planning, achieving the goal of accurate and reliable life cycle data at a low cost.

This invention relates to a method for collaborative carbon-health accounting throughout the entire lifecycle of power modules, comprising: S1: collecting data from power modules and performing cross-stage data association and alignment based on digital twin identifiers; S2: determining the electricity carbon emission factor; calculating dynamic operating carbon emissions based on the carbon emission factor and real-time power loss; S3: calculating carbon emissions during manufacturing, use, and end-of-life stages, and normalizing them into a product-level full lifecycle carbon footprint value; S4: randomly sampling the remaining lifespan and future green electricity penetration rate using a random simulation method, calculating the probability distribution of net carbon gains from tiered utilization, and outputting retirement decision recommendations; S5: calculating cryptographic hash values, digitally signing key data packets, and generating zero-knowledge proofs. This method achieves seamless data integration across the entire manufacturing-operation-retirement chain, collaborative dynamic accounting of carbon emissions and health status, repeatable calibration of thermal resistance aging parameters, probabilistic quantification of retirement decisions, and reliable anchoring of data sources.

We provide the system. [Solution] Means of collecting user activity data, A means of analyzing the user's lifestyle based on the aforementioned activity data, A means of generating suggestions tailored to the user's cultural background and life stage, A means for notifying the user terminal of the aforementioned proposal, A means of receiving user feedback and continuously learning, A system that includes this.

The application provides a vulnerability management method and device, a storage medium and a computer device, wherein the method comprises: obtaining and storing asset vulnerability information corresponding to a target organization; for each vulnerability data, determining a target stage currently occupied by the vulnerability data from each life stage included in a preset vulnerability life cycle; according to the target stage, marking a state of the vulnerability data and interacting with a target person having a target agency authority matched with the target stage; generating interaction description information according to an interaction result, and determining a new target stage currently occupied by the asset vulnerability from the each life stage according to a target stage corresponding to a current state mark; the interaction description information is used for feedback to a corresponding target person in the new target life stage; returning to the step of marking a state of the vulnerability data according to the target stage until the stored vulnerability data is cleared.

The invention discloses a batch verification maximization fault diagnosis system and method for life stage migration. The dependence on target domain labeling is remarkably reduced while cross-stage high-precision fault recognition is achieved. The system comprises a life stage pseudo-domain division label generation module which inputs source domain and target domain test data containing timestamps or residual service life information and outputs data subsets corresponding to all stages; the stage perception sharing-specific feature coding module is used for inputting original signal data of each stage and a corresponding stage label, and outputting a shared feature and a stage specific feature; the channel-stage fusion selection module is used for receiving the shared features and the stage specific features from the stage perception sharing-specific feature coding module and outputting fused features; and the multi-stage batch nuclear norm maximization migration module is used for inputting fusion features and stage label information, respectively calculating a Softmax output matrix for each pseudo-domain, and maximizing the batch nuclear norm of the Softmax output matrix so as to enhance cross-stage discrimination and feature consistency.

The techniques described herein relate to systems and methods for generating deliberative committees of age-stratified large language models (LLMs). An example method for generating a dialogue between at least first and second age-stratified LLMs trained to generate simulated responses to questions that respective first / second persons would have provided in a particular life stage comprises receiving a prompt comprising a question, executing the first LLM to generate a first simulated response to the question that the first person would have provided in the first life stage, executing, using the prompt and / or the first simulated response, the second LLM to generate a second simulated response to at least the question that the second person would have provided in the second life stage, and generating, using the response(s), an output representing a third simulated response to the question that the first / second persons would have collectively determined to provide in their particular life stages.

The application discloses a biological age evaluation method and system based on whole life cycle DNA methylation and application, and belongs to the technical field of bioinformatics. First, the obtained original DNA methylation data is subjected to quality control and standardization processing; then, differential methylation sites significantly related to calendar age are screened as features; next, taking calendar age as a target variable, a regression model is constructed by adopting a LightGBM gradient boosting framework to obtain a methylation clock model; subsequently, the model is used to predict the DNA methylation age of an individual, and an epigenetic age acceleration value is calculated based on the deviation of the DNA methylation age from the calendar age; finally, the age acceleration value is subjected to correlation analysis with health or physiological indexes in different life stages, so as to evaluate the biological aging state of the individual and predict related health risks. The application covers the whole life cycle, is suitable for Chinese population, and can provide an effective tool for clinical disease risk prediction, health management and anti-aging intervention effect evaluation.

Techniques for evaluating the effectiveness of an intervention for a condition of a plurality of subjects are disclosed. First data can be received from a plurality of activity monitors respectively associated with the plurality of subjects. Each of the activity monitors can measure at least some activity by a respective plurality of subjects over a time period. For each of the plurality of subjects, second data can be received that identifies one or more indicators of a life stage or a quality of life condition of each of the plurality of subjects receiving a therapy, nutrition, or intervention over at least some portion of the time period. The first data and the second data can be input into at least one machine learning (ML) model that can process the first data and the second data. The ML model can determine that the intervention is relatively effective, or that the intervention is relatively ineffective.

The invention relates to the technical field of machine learning, and discloses a mold life evaluation method based on machine learning, which comprises the following steps: collecting mold data, and extracting features related to a mold physical failure mode; self-adaptive decomposition is carried out, decomposition parameters are adjusted, and signal components are obtained; constructing an integrated model to obtain a residual service life prediction value of the mold; analyzing the feature contribution degree, optimizing a model input feature set, and outputting a maintenance decision suggestion based on an analysis result; and deploying the integrated model to an edge computing device, and adjusting an evaluation strategy according to degradation characteristics of the mold in different life cycles to realize real-time life evaluation and decision support. According to the method, the accuracy and reliability of mold life prediction can be remarkably improved, the model transparency is enhanced, and closed-loop management from prediction to maintenance decision is realized.

The system according to the embodiment aims to provide comprehensive support to single women to help them cope with various life stages and challenges. [Solution] A system according to an embodiment includes a collection unit, an analysis unit, and a provision unit. The collection unit collects user data. The analysis unit analyzes the data collected by the collection unit. The provision unit provides various types of support based on the analysis results obtained by the analysis unit.

This invention discloses a method and system for predicting the aging trend of a battery across its life stages. The method includes: S1, acquiring early aging characteristic data of the first life stage of the battery to be predicted and corresponding load condition information; S2, constructing a condition-aware model based on a cross-attention mechanism, using battery data from no-load switching as the main input and corresponding load condition information as the condition input to train the condition-aware model; S3, using the condition-aware model to output the evolution sequence of subsequent aging characteristics of the battery to be predicted from the early stage of the first life stage in a time-series prediction manner, the evolution sequence of subsequent aging characteristics covering the remaining lifespan of the first life stage and the aging characteristic changes of the second life stage after load condition switching; S4, estimating the battery health state based on the evolution sequence of subsequent aging characteristics to generate a cross-life stage aging trajectory prediction curve from the first life stage to the second life stage, thereby improving the robustness and practicality of the prediction.

The invention discloses a data element full-life-cycle log anomaly detection method based on knowledge distillation, and relates to the technical field of big data anomaly detection, and the method comprises the steps: training an initial teacher model on a label-free log, fitting an over-threshold value through a peak value over-threshold method and generalized Pareto distribution to remove extreme samples, and forming a purification training subset; on the basis, a robust teacher model is trained again, and a lightweight student model is obtained through distillation. In the online detection stage, a cascade strategy of rapid screening of a student model and fine determination of a teacher model is adopted; in order to enhance the robustness and discrimination ability of anomaly detection, on the teacher side, the uncertainty of a teacher model, the teacher-student prediction distribution difference and the mahalanobis distance of a representation space are jointly utilized to construct an anomaly score, and the limitation of dependence on single statistics is avoided. According to the method, a two-stage log anomaly detection framework is adopted, and efficient log anomaly detection under an unsupervised condition is realized through combination of knowledge distillation and an extreme value theory.

Embodiments of the present application disclose a method, system, storage medium and electronic device for predicting a vulnerability life stage, wherein the method comprises: obtaining basic information of a vulnerability to be predicted; calculating a repair parameter of the vulnerability to be predicted according to the basic information; calculating a distribution probability value of the vulnerability to be predicted according to the basic information and the repair parameter based on a preset vulnerability life cycle prediction function; and determining a life stage of the vulnerability to be predicted according to the distribution probability value based on a mapping relationship between a preset vulnerability life stage and a distribution probability. The method and system associate the life cycle prediction of the vulnerability with time and the code base of the vulnerability, construct a probability density function for predicting the life stage of the vulnerability, and finally determine the life stage of the vulnerability through the mapping relationship between the vulnerability life stage and the distribution probability, so that the life stage of the vulnerability can be more accurately predicted, and the repair of the vulnerability by engineering personnel is more targeted.

The invention discloses a performance evaluation method and device for a card type interface generation tool, a storage medium and electronic equipment, and the method comprises the steps: in a process of generating a card type interface for mobile equipment through employing a to-be-evaluated tool, carrying out the recognition of a current life cycle stage of the card type interface, and obtaining a current life stage of the card type interface; determining a target evaluation dimension from the candidate evaluation dimensions based on the current life stage of the card type interface, and determining a target evaluation weight from the candidate evaluation weights based on the target evaluation dimension; acquiring performance evaluation data of the to-be-evaluated tool based on the target evaluation dimension to obtain target performance data, and determining a target performance score corresponding to the current life stage based on the target performance data, the target evaluation dimension and the target evaluation weight; and determining a performance evaluation result of the to-be-evaluated tool in the current life stage based on the target performance score and the target evaluation weight. By executing the technical scheme of the invention, the accuracy of performance evaluation can be improved.

An object of a system according to an embodiment is to provide appropriate support when a woman forms a career according to a life stage.SOLUTION: A system according to an embodiment includes a career advice unit, a compatibility support unit, a career plan creation unit, a mental support unit, and a networking support unit. The carrier advice unit provides a carrier advice according to the life stage. The compatibility support unit supports compatibility between childcare and work. The career plan creation unit creates a career plan. The mental support portion provides mental support. The networking support unit supports networking.SELECTED DRAWING: Figure 1

The invention discloses a transfer learning diagnosis system for mechanical characteristics of a full-life circuit breaker of power grid assets, and relates to the technical field of equipment state monitoring and diagnosis. Comprising a data acquisition module, a life stage determination module, a dynamic reference knowledge base module, a matching module and a diagnosis module. The system determines a target life stage of a to-be-diagnosed circuit breaker by acquiring current operating parameters and mechanical characteristic data of the to-be-diagnosed circuit breaker; based on historical asset group data, constructing and maintaining a migration diagnosis reference library containing multiple life stage reference diagnosis parameters and a migration relation representing evolution laws of the reference diagnosis parameters; matching corresponding reference parameters according to the target life stage; and generating a comprehensive diagnosis result by judging whether the deviation degree of the current mechanical characteristic data relative to the matching reference exceeds a preset threshold value or not. The mechanical characteristic diagnosis of the circuit breaker is converted from static threshold judgment to dynamic full-life migration diagnosis, and the adaptability and accuracy of diagnosis and the engineering guidance value of state evaluation are improved.

The present invention provides a method for rearing flies, comprising the steps of introducing one or more different life stages of flies into a room comprising six walls, wherein at least one of the walls is solid and the other walls are solid, formed by mesh, bars or wires or are a combination thereof; controlling the temperature in the room with an heating and cooling which is arranged in the floor; and ventilating emissions from the room. Another object of the present disclosure relates to a room for rearing flies, comprising six walls, wherein at least one of the six walls is solid and the other walls are solid, formed by mesh, bars or wires or are a combination thereof; an heating or cooling which is arranged in the floor; a ventilator for ventilating emissions from the room; elements for providing water and / or insect nutrition; and oviposition media and attractants.

The application discloses a kind of multi-weight index fusion's rolling bearing health state degradation failure evaluation method, comprising: collecting the vibration signal of rolling bearing full life stage, constructs the vibration signal full life data set of rolling bearing;Calculate the multiple characteristic indexes of each vibration signal in data set;Respectively calculate the spearman rank correlation coefficient of each characteristic index;Based on monotonicity, correlation and robustness, the weight coefficient of normalized feature index is calculated;The multiplication and addition of each screened feature index in the vibration signal full life data set of rolling bearing and its corresponding weight coefficient are carried out, to obtain the health factor of each vibration signal, and draw the rolling bearing health factor curve;According to rolling bearing health factor curve, determine the degradation state starting point and degradation state of rolling bearing and failure state starting point and failure state.The present application can accurately characterize the performance of rolling bearing slow degradation state.