7 results about "Functional data analysis" patented technology

The invention relates to the technical field of medical informatization, in particular to an MCI cognitive trajectory and bidirectional outcome dynamic prediction method based on a joint model. The method comprises the following specific steps: firstly, constructing a univariate joint model, then constructing a multivariate joint model, and then constructing a function type multivariate joint model; performing parameter estimation and statistical inference on the model; fitting evaluation is carried out on the function type multivariable joint model based on multi-longitudinal cognition and multi-state outcome; and finally, carrying out individualized dynamic prediction. According to the method, a baseline or longitudinal nerve image is processed by using a function type data analysis technology, and a change track is reconstructed; a plurality of cognitive assessments are used as longitudinal measurement indexes, covariants such as age and gender and functional nerve images are used as predictive factors, two-way outcome of MCI and occurrence time of the two-way outcome are set as survival outcomes, a joint model based on multi-longitudinal cognitive multi-state outcomes is constructed, early screening of high-risk groups is assisted, and the survival outcomes of the high-risk groups are determined. And powerful support is provided for optimal distribution of medical and medical and health resources.

In order to explore the effectiveness of the functional data analysis method in the hyperspectral image processing, the application proposes a classification method combining the Gaussian regression mixture model and the MRF hyperspectral function data; first, the polynomial regression is used to fit the hyperspectral image pixel spectrum curve, so as to express the pixel spectrum information in the form of function; then, the neighborhood relationship is introduced to establish the Markov random field model, and the neighborhood Gaussian regression mixture model is established in combination with the Gaussian regression mixture model; finally, according to the maximum posterior probability criterion, the final hyperspectral image classification result is obtained. Since the spatial-spectral information of the hyperspectral image is fully combined, the algorithm has high-precision classification result, and effectively improves the classification performance of the hyperspectral image.

The invention discloses an individual dynamic metabolic abnormality early warning system based on function type data analysis, which can judge whether the dynamic metabolic condition of an individual to be evaluated is abnormal or not according to the fasting metabolic response data of the individual and a healthy reference population and the metabolic response data after a tolerance test, and carries out early warning if the dynamic metabolic condition exists. The system comprises a data input module, a data analysis module and an early warning module, the data input module is responsible for data input, and input data comprises index data of to-be-evaluated individuals and health reference people at multiple time points before and after a tolerance test; the data analysis module is responsible for processing and analyzing the data and calculating a metabolism score of the individual to be evaluated; the early warning module is responsible for judging whether metabolism abnormity early warning is carried out or not, comparing the metabolism score obtained by the data analysis module with a threshold value, if the metabolism score is lower than the threshold value, early warning is carried out, and otherwise, early warning is not carried out.

A seasoning frying reaction kettle temperature adaptive batch control method, steps include: (1) preprocessing the historical data of multiple batches of kettle temperature, removing abnormal points by Savitzky-Golay filtering, aligning multiple batches of trajectories by dynamic time warping algorithm, and then extracting process common characteristics by functional data analysis; (2) build a double-layer architecture of mechanism model iterative correction layer and real-time dynamic control layer; based on real-time kettle temperature and steam valve opening data, online update mechanism model parameters and real-time parameter setting using adaptive batch PID controller, compensate high-frequency disturbance and saturate the output; (3) fuse the outputs of mechanism model iterative correction layer and real-time dynamic control layer to generate the final steam valve control command of the reaction kettle. This method does not require additional sensors, only relies on conventional measurement data, improves temperature control accuracy, working condition adaptability and multi-batch production stability.

An apparatus for calculating an optimized functional signature, comprising at least a processor; and a memory containing instructions configuring the at least a processor to receive a vitality profile relating to a user, wherein the vitality profile comprises a plurality of function data; analyze the plurality of function data to link a temporal element to each of the plurality of function data; calculate a functional signature as a function of the analyzed plurality of function data linked to a temporal element; generate an optimized functional signature as a function of the functional signature, wherein generating the optimized functional signature further comprises: identifying at least one constraint associated with the function signature using a vitality machine learning model; determining a resource allocation as a function of the optimized functional signature; and present the optimized functional signature and the resource allocation using a display device.

This invention discloses an individual dynamic metabolic abnormality early warning system based on functional data analysis. It can determine whether there are abnormalities in the dynamic metabolic status of the individual being evaluated based on fasting and metabolic response data after a tolerance test, and issue an early warning if abnormalities are found. The system includes a data input module, a data analysis module, and an early warning module. The data input module is responsible for inputting data, including indicator data from the individual being evaluated and the healthy reference group at multiple time points before and after the tolerance test. The data analysis module is responsible for processing and analyzing the data and calculating the metabolic score of the individual being evaluated. The early warning module is responsible for determining whether to issue a metabolic abnormality warning by comparing the metabolic score obtained from the data analysis module with a threshold. If the metabolic score is lower than the threshold, an early warning is issued; otherwise, no warning is issued.

The invention discloses a visualization system and method for low-code index arrangement and chart reuse of a linkage label system and a medium, and the method comprises the following steps: realizing accurate group screening through data definition and label integration. Collaborative data filtering of a data set and a label system is carried out to realize rapid group screening; based on a defined data set, a user can arrange a data applet or a data canvas through a self-service pattern component supporting and pulling mode, the complex index calculation requirement is met by means of flexible data operation support, the component reuse efficiency is improved by means of a data applet reuse mechanism, and the user experience is improved. A convenient canvas arrangement and output scheme is combined to adapt to diversified office scenes, meanwhile, non-homologous configuration of a data text component is innovated to break through the limitation of multi-source data integration, and a set of efficient, flexible and functional data analysis and visualization solution is integrally constructed.