83 results about "Demographic data" patented technology

The invention provides a number card distribution system based on message middleware, relates to the field of data management, and solves the technical problem of high data storage security risk of an existing number card distribution system. The system comprises a message center module which is used for processing asynchronous communication and data transmission in the system by adopting a distributed message middleware cluster; the data security module is used for managing distribution data of each region by adopting a data fragmentation storage mechanism; and the demand prediction module is used for predicting the number card demand quantity of the next period according to the sales data and the demographic data of each region, and guiding the formulation of a sales strategy of the next period. The method and the device are used in the whole-process management process of the number card distribution service.

The invention relates to the technical field of carbon emission evaluation, and relates to a carbon emission evaluation method and system based on multi-source heterogeneous data, and the method comprises the steps: obtaining the space matching data of a target region boundary and parking spaces, and generating the number and distribution information of effective parking spaces; the time sequence dynamic remote sensing data, the traffic density fluctuation data and the demographic data are fused, a parking space activeness factor model is constructed, and the parking space use intensity is output; predicting the vehicle type distribution proportion of the target area by using a neural network, and calculating the annual average driving distance of the vehicle; calculating a dynamic vehicle carbon emission factor and a static vehicle carbon emission factor according to the time dynamic nature and the regional difference of the power grid energy; and calculating the total carbon emission of the target area by integrating the vehicle type distribution proportion, the annual average driving distance and the carbon emission factor based on a collaborative correction mechanism of the parking space resource tensity and the parking space use intensity. The objective of the invention is to realize community-level high-precision carbon emission accounting and improve the spatial resolution and adaptability of carbon emission accounting.

Methods, systems, and computer program products are provided for shared latent space-based debiasing. An example system includes at least one processor configured to: transform data from each of a target domain, which lacks protected features, and a separate source domain, which contains these features, into correlated latent representations; jointly train a cross-domain protected group estimator on the representations; and debias a downstream machine learning model an adversarial learning technique that leverages the group estimator.

The invention provides an urban building group three-dimensional function partitioning and floor population dynamic distribution method and device, and relates to the technical field of urban space information processing. The method comprises the steps of constructing semantic feature vectors of multi-source POI data based on a BERT model and domain specific vocabularies to generate fusion data; building a floor position probability distribution model according to a three-layer progressive reasoning structure and a reasoning technology; carrying out three-dimensional function partitioning according to the function coupling strength and an improved spectral clustering algorithm; building-level demographic data are generated, and a differentiation attraction model is constructed; and solving the floor population distribution constraint optimization model according to the improved Haff model to obtain population dynamic distribution of each floor. According to the method, granularity limitation of traditional function division is broken through, floor-level refined three-dimensional function division and population dynamic distribution prediction are realized, and important decision support is provided for applications such as commercial site selection, emergency evacuation path planning, public service facility configuration optimization and the like in smart city construction.

Methods and apparatus are disclosed regarding an e-commerce system that places customers into a plurality of clusters and tailors services provided to a customer based on the cluster in which the customer is placed. In one embodiment, the e-commerce system defines the clusters based on purchase history data for customers having sufficient purchase history data. The e-commerce system then places customers without sufficient purchase history data into one of the defined clusters based on demographic data for the customer and demographic data for the customers in the cluster.

The invention discloses a neurodegenerative disease analysis method and device based on multi-modal data and a terminal, and the method comprises the steps: obtaining target user data corresponding to a user, and determining a data type according to the target user data, the data category comprises more than one of gait feature data, demographic data, cognitive data and bioelectricity detection data; and adopting a risk assessment method corresponding to the data category to determine a risk level corresponding to the user according to the target user data. Since the acquired target user data contains other data categories except the gait feature data, and the risk level corresponding to the user is assessed by adopting the corresponding risk assessment method according to the data categories, the problem that the existing method focuses on single analysis of the gait data can be effectively solved; and comprehensive analysis is not carried out in combination with demographic data, cognitive information and the like of different individuals, so that the comprehensiveness of neurodegenerative disease analysis is limited.

This invention relates to the field of ecological protection zone identification technology, and particularly to a method for improving the accuracy of the Human Footprint Index. The method comprises the following steps: S1, Population Grid Redistribution: A construction land mask is extracted from land cover data. Population statistics data from the construction land mask and population grid data are input into the iURBAN algorithm to redistribute the population grid data. Population statistics data are then used to verify the accuracy of the population grid data before and after redistribution. S2, Fragmentation Index Scoring: A movement speed grid is calculated. City tiers are classified based on land cover data. Based on the city tier classification and movement speed grid, different levels of urban patches representing urban edges are obtained. Landscape pattern indicators representing fragmentation are calculated, and fragmentation index scores are assigned based on the landscape pattern indicator calculation results. S3, Human Footprint Index Calculation. This invention redistributes population data from the population grid to optimize the population distribution and improve the accuracy of the population grid data.

A disclosed example includes accessing computer-generated impression records, the computer-generated impression records based on network communications received at a server of a database proprietor from client devices, the computer-generated impression records indicative of accesses to media at the client devices; accessing self-reported demographic data and behavioral data from a database of the database proprietor, the self-reported demographic data and the behavioral data corresponding to user accounts registered with the database proprietor and associated with the client devices; comparing the self-reported demographic data with a probability distribution of higher-accuracy demographic data; determining different adjustments for corresponding ones of self-reported demographics of the self-reported demographic data based on the comparison; adjusting the corresponding ones of the self-reported demographics based on corresponding ones of the different adjustments to generate adjusted user demographic data; and assigning the adjusted user demographic data to corresponding ones of the computer-generated impression records.

The invention provides a crowd health-oriented environment risk dynamic regulation and control method and a storage medium, relates to the field of public health, and systematically integrates macroscopic environment monitoring and demographic statistics data, multi-pollutant air quality health indexes and individual-level longitudinal queue data. A multi-pollutant air quality health index is used as priori knowledge through a constructed fusion module, an individual-level causal model is processed, a processed health risk function is coupled with a pollution control marginal cost function and refined health economic evaluation parameters, and a comprehensive optimization function is constructed. And performing probabilistic representation and propagation on uncertainty of all key parameters in the target function, finally solving to obtain a control threshold range with a confidence interval, re-substituting the optimized control threshold into the multi-pollutant air quality health index calculation framework, evaluating the risk level change of the multi-pollutant air quality health index calculation framework under a historical reference, and calculating the multi-pollutant air quality health index. And an empirical support from historical data is provided for the rationality and feasibility of an optimization result.

The invention relates to an infant asthma three-branch classification auxiliary judgment method and a medium, and relates to the technical field of data processing. The method comprises the following steps: collecting and preprocessing tidal respiration data and demographic data of infants, and performing heterogeneous feature extraction and grouping log-likelihood ratio acquisition on the preprocessed tidal respiration data and demographic data to obtain a log-likelihood ratio corresponding to each group; and performing hierarchical Bayesian fusion on each log-likelihood ratio to obtain a fusion result, and performing asthma risk auxiliary judgment of three-branch classification based on the fusion result. Compared with the prior art, the method can assist in judging the infant asthma more objectively and accurately based on the tidal respiration data.

The application discloses a coronary heart disease prediction method fusing cardiopulmonary exercise parameter time sequence information, and comprises the following steps: collecting multidimensional health data of a patient; preprocessing the multidimensional health data; extracting features from the preprocessed data; performing time sequence analysis on the extracted features by using a deep learning model; inputting the time sequence analysis result and static features into a classification model to perform coronary heart disease prediction, outputting a prediction result and generating a related health report. By acquiring demographic data, basic medical information and cardiopulmonary exercise test data of a target object, specifically including age, gender, body mass index, socio-economic information, past history, complications, clinical examination and inspection, exercise capacity, cardiovascular function and ventilation perfusion and the like, the coronary heart disease is predicted by fusing static parameters and time sequence information, so that dynamic changes in the health data of the patient can be better captured, and the prediction accuracy is improved.

A method for managing computer resource use in computer-implemented risk assessment of a subject in respect of a context. Demographic subject data for the subject is passed to a first trained machine learning model trained on first context-specific historical risk outcomes correlated with historical demographic data corresponding to the demographic subject data. If a first threshold assessment from the first trained machine learning model is passed, the subject is approved. Responsive to failing the first threshold assessment, supplemental context-related subject data for the subject, in addition to the demographic subject data, is passed with the demographic subject data to a second trained machine learning model trained on second context-specific historical risk outcomes correlated with the historical demographic data and with historical context-related data corresponding to the supplemental context-related subject data. If a second threshold assessment from the second trained machine learning model is passed, the subject is approved.

The present invention concerns a method for calculating one or more isovists of a physical or extended reality environment, comprising the steps of: providing at least one electronic acquisition apparatus configured to obtain a plurality of georeferenced and physiological, and / or psychological, and / or environmental, and / or perceptual and / or demographic data, and to take a frame of the physical or extended reality environment, detect physiological variations and / or environmental variations; calculating a behaviour indicator comprising at least one positioning parameter for each user from the georeferenced data acquired by means of electronic acquisition apparatus; calculating a perception indicator comprising at least one or more physiological and / or environmental parameters for each user by means of electronic acquisition apparatus; providing a relationship identifying algorithm; identifying for each user one or more statistically significant physiological and / or environmental parameters by means of the relationship identifying algorithm by identifying a relationship between the positioning parameter and the aforesaid physiological and / or environmental parameters; associating for each user the positioning parameter with the identified, statistically significant parameters to define respective data units; defining a positioning threshold and a physiological and / or environmental threshold; grouping into respective experience sets data units having respective statistically significant physiological and / or environmental parameters differing from each other by a value lower than the respective threshold and respective positioning parameters differing from each other by a value lower than the positioning threshold, calculating at least one isovist for each experience set; representing each isovist calculated in a graphic interface of an electronic display apparatus.

The invention provides a Parkinson's disease freezing gait prediction method and device based on eye movement characteristics, equipment and a medium. The method comprises the following steps: acquiring target information corresponding to a target object; the target information comprises target demographic data, target clinical features and target eyeball motion parameters collected at a certain time point, and / or target demographic data, target clinical features and target eyeball motion parameters continuously collected according to a preset frequency within a preset time; and inputting the target information into the target frozen gait prediction model, so that the frozen gait prediction model analyzes and processes the target information to obtain a static frozen gait risk assessment result and / or a dynamic frozen gait risk assessment result corresponding to the target object. According to the scheme, through multi-dimensional integration and collaborative verification of traditional clinical phenotypes and objective indexes of eye movement, non-invasive efficient evaluation of frozen gait risks is achieved, and objective basis and key technical support can be provided for early diagnosis and early treatment of disease subtypes.

The systems and methods disclosed herein generate a personalized inner voice audio output that replicates or otherwise shares the acoustic characteristics of a speaker's self-perceived voice, which can differ from their externally perceived voice due to bone conduction effects. The systems and methods disclosed herein can generate a provisional voice clone (e.g., parameters of a voice model) of the speaker's voice (e.g., using a recording of the speaker's voice), and can apply a frequency shift to compensate for the absence of bone-conducted low-frequency adjustment that occurs during natural speech production. A trained artificial intelligence model predicts and applies one or more additional acoustic parameter adjustment values (e.g., formant structure, spectral envelope, prosodic patterns) to the provisional voice clone based on one or more factors (e.g., demographic, anatomical, content, environment). The provisional voice clone can be iteratively refined based on received user feedback (e.g., until the output aligns with the speaker's perception of their inner voice).

The invention relates to the field of health behavior prediction and rehabilitation management, and discloses construction and application of a stroke patient home functional exercise compliance risk prediction model. The method comprises the following steps: collecting demographic and clinical data and scale evaluation data of a stroke patient, and carrying out missing value processing and preprocessing; identifying a compliance potential category by adopting potential profile analysis, and determining an optimal cutoff value of a total score of a scale through subject working characteristic curve analysis to form a dichotomy result; key predictive factors are screened in a training set by applying LASSO regression, and a'non-good compliance 'predictive model is established by incorporating the key predictive factors into multivariate Logistic regression; an online dynamic column graph webpage calculator is developed based on the Shiny technology, and a user is supported to input variables in real time and output a prediction probability and a confidence interval; and the discrimination degree, the calibration degree and the clinical net income are analyzed and evaluated through five-fold cross validation, Hosmer-Lemeshop test and decision curve analysis. According to the invention, rapid identification and hierarchical management of high-risk patients can be realized, and a basis is provided for follow-up visit and individualized intervention.

This disclosure describes systems, software, and computer implemented methods that include identifying a set of baseline neurometrics for a first subset of an audience; exposing the first subset of the audience to a collection of media and measuring neurometrics of the audience during exposure to the media; identifying demographic data associated with the first subset of the audience, wherein the demographic data includes a plurality of parameters associated with individual members of the audience; identifying demographic data associated with a second subset of the audience, the second subset of the audience comprising audience members that respond to at least a portion of the collection of media; and generating a predictive model of the audience's response to the collection of media by.

We provide the system. [Solution] A means for analyzing demographic data and attribute data acquired from an information processing device, Based on the analysis results obtained, a means for selecting the optimal location for commercial activities, A means of determining the implementation site, taking into account the availability and resources of the selected implementation site, A means of presenting a confirmed location for implementation and personnel allocation suitable for commercial activities, A means of providing an optimal sales plan based on user input information, A system that includes this.

The invention provides an autism diagnosis method based on multi-modal super-dimensional calculation and electronic equipment, and relates to the technical field of biomedical information. The method comprises the following steps: acquiring resting-state electroencephalogram data, eye movement tracking data and demographic data of a tested object; respectively carrying out typical feature extraction on the resting-state electroencephalogram data and the eye movement tracking data, respectively encoding electroencephalogram feature data and eye movement feature data into an electroencephalogram super-dimensional vector and an eye movement super-dimensional vector through super-dimensional calculation, and encoding the demographic data into a demographic super-dimensional vector; integrating the electroencephalogram super-dimensional vector and the eye movement super-dimensional vector through a weight fusion and residual enhancement mechanism to obtain a feature fusion super-dimensional vector, and integrating the feature fusion super-dimensional vector and a demographic super-dimensional vector through an adaptive fusion strategy to obtain a tested object super-dimensional vector of each tested object; and determining a diagnosis result of the target tested object according to a similarity calculation result with the plurality of class super-dimensional vectors. The autism diagnosis accuracy can be improved.

Methods and apparatus to apply household-level weights to audience measurement data at a household-member level are disclosed. An example method to determine demographics of populations to measure media audiences of populations includes determining demographics for members of a first household of a sub-population. First demographics of a first member of the first household are different than second demographics of a second member of the first household. The example method includes calculating a first household-level weight for the first household based on a demographics distribution of the sub-population and aggregate demographics of a population. The example method includes applying the first household-level weight to the first demographics of the first member, applying the first household-level weight to the second demographics of the second member, and estimating a demographics distribution of the population to measure a media audience of the population based on the weighted first demographics and the weighted second demographics.

Particular embodiments described herein provide for a system, an apparatus, and a method to help enable communication routing based on general location and / or demographics. The system, apparatus, and method can include or enable receiving a communication from an electronic device, determining a general location of the electronic device based at least in part on data and / or metadata included with the communication, and routing the call based on the general location of the electronic device. In some examples, the system, apparatus, and method can include or enable determining demographic data related to the user the electronic device and routing the call based on the general location of the electronic device and the demographic data.

This application provides a method and system for infectious disease risk prediction based on a large language model and wastewater monitoring. The method includes: acquiring a multimodal time-series dataset of a target area in a first time period, wherein the multimodal time-series dataset includes wastewater epidemiological data sequences of the target disease, vaccination data sequences of the target disease, clinical monitoring data sequences of the target disease, environmental data sequences, and demographic data sequences obtained based on technologies such as multipathogen hybridization capture sequencing and PCR; converting the multimodal time-series dataset into a text time-series data sequence; inputting the text time-series data sequence into a preset risk prediction model to generate corresponding feature vectors, and predicting the trend of hospitalization rate changes of the target disease based on the feature vectors; and predicting the risk level of the target disease in the target area based on the trend of hospitalization rate changes and the wastewater epidemiological data sequence, thereby improving the accuracy of infectious disease area risk prediction.

Methods, apparatus, and systems are disclosed to collect impressions associated with over-the-top media devices. An example apparatus includes memory; and at least one processor to execute instructions to access a first request, the first request from a user-controlled client device, the first request including an over-the-top device identifier that identifies an over-the-top device that presents media, in response to determining a user of the user-controlled client device is a panelist of a first server, store the over-the-top device identifier with demographics corresponding to the panelist, access a second request, the second request from the over-the-top device, the second request including the over-the-top device identifier and a media identifier, and log an impression associated with the media identifier and the demographics, the impression corresponding to the panelist of the first server.

A device may receive input data that includes demographic data, power demand data, power source data, power route data, technology data, industry data, and problem data associated with a geographic location, and may identify a section of the geographic location from the demographic data. The device may identify power sources of the section, and may estimate power generation and power demand for the section. The device may determine whether the power demand is greater than the power generation for the section. The device may utilize a quantum computer and a power optimizer model with the input data associated with the section to determine optimized power insights for the section based on determining that the power demand is greater than the power generation for the section, and may perform actions based on the optimized power insights for the section.

A method (200) for planning a product (105) comprises steps of determining responses of a plurality of potential users (120) to the product (105); wherein first responses are determined in a first format by means of a first method and second responses are determined in a second format by means of a second method; creating a requirements model based on the first and second responses by means of a machine learning technique (140); and determining requirements for the product (105) based on the requirements model.

A system and a method for motion measurement and recovery using artificial intelligence is provided. The system receives user data associated with a first user. The user data comprises demographic data, medication data, and historical data. The system receives video data indicative of an activity performed by the first user. The system determines anatomical data associated with the first user based on processing of the video data. The anatomical data includes joints data for one or more anatomical joints of the first user and movement data associated with each of the one or more anatomical joints of the first user. The system generates, using an artificial intelligence (AI) model, a score for the activity performed by the first user based on the user data and the anatomical data. Additionally disclosed the system and method for motion measurement and recover using artificial intelligence utilizes marker-less motion technology for capturing movement data.

The invention discloses a population data generation method and device and a computer readable storage medium, and the method comprises the steps: carrying out the conversion of an initial population sample from an attribute domain to a copula domain, obtaining a copula domain sample, carrying out the vectorization coding representation of the copula domain sample, and obtaining a matrix sample; performing diffusion model training and sample generation based on the matrix sample to obtain a new matrix sample; and decoding the new matrix sample to obtain a copula domain vector sample, and performing quantile function mapping on the copula domain vector sample to obtain an attribute domain demographic data generation sample. According to the method, the initial population sample is converted to the copula domain, the correlation mode between the attribute variables is reflected through the copula density function, the influence of edge distribution is avoided, the intrinsic dependency constraint relation between the variables can be effectively captured, and the population sample data with high feasibility and diversity is generated.

A satellite image of a geographic region is cropped. Each pixel of the cropped satellite image is brightened. A first portion of the brightened satellite image is sampled and has a centroid defined by a geographic location. A second portion of the brightened satellite image centered on the centroid is generated. The first and second portions have different resolutions. The first and second portions are processed to generate respective first and second outputs where each output is indicative of features therein. The first and second outputs are processed to generate an estimated census metric associated with the centroid. The estimated census metric is compared with a corresponding metric from collected census data to generate a difference therebetween. The location of the centroid is moved to a revised location and the process is repeated until the difference is less than a prescribed threshold.

The invention discloses a subway evacuation dynamic decision simulation system based on virtual reality and artificial intelligence, and the system comprises an environment modeling module, an intelligent agent generation module, an evacuation behavior decision module, a path planning module and a man-machine interaction module which are in mutual communication coupling. The environment modeling module is used for constructing a three-dimensional subway tunnel evacuation scene and integrating dynamic data of a fire scene, the agent generation module generates a heterogeneous agent group based on demographic data, and the evacuation behavior decision module adopts an improved social force-agent model and a finite-state machine to realize agent behavior decision. The path planning module implements a three-level navigation algorithm to realize global path planning and local path dynamic adjustment, and the man-machine interaction module acquires behavior data of participants through VR equipment and interacts with a simulation environment in real time. The method has the advantages that real person evacuation behavior and intelligent agent interaction is realized through a highly simulated environment and an intelligent decision model, and the efficiency and scientificity of subway tunnel emergency evacuation drilling are improved.

A computer-implemented method for determining risk scores using machine learning based on sensor data. The method includes receiving sensor data and demographic data for a user, determining a pattern of behavior based on the sensor data and demographic data, identifying a plurality of test groups based on other users that exhibit similar patterns of behavior to each other where sensor data from other users' electronic devices are received, identifying a test group corresponding to the user from among the plurality of test groups, determining a risk score using a trained risk analyzer machine learning model trained with historical sensor data, historical demographic data, and feedback data indicative of incidents, identifying risk mitigation strategies based on the risk score, refining the risk mitigation strategies using an iterative machine learning process as additional feedback data is collected, and retrieving risk mitigation communications from a database when the risk score exceeds a threshold.