54 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.

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.

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.

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.

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 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.

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.

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.

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.

A system and method are disclosed for monitoring health conditions based on data collected by a wearable device such as an activity tracker or a smart watch. Deep learning algorithms are configured to process an input vector that includes monitored parameter data collected by the wearable device as well as embedding data obtained from health records corresponding to a user account registered to the wearable device. In some embodiments, the input vector can also include social determinants data and / or demographic data. The output of the deep learning algorithms provides classifiers that represent probabilities that the user of the wearable device has an underlying health condition. If any underlying health condition is detected, then the user can be notified directly, via the wearable device or an associated application or technology, or indirectly, via a primary care provider associated with the user.

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 belongs to the field of auxiliary diagnosis of autism spectrum disorders, and particularly relates to an autism spectrum disorder recognition method based on a residual gated graph convolutional network, which comprises the following steps: acquiring rs-fMRI data and demographic data; dividing the rs-fMRI data of the subject into a plurality of brain regions, and calculating an average time sequence of each brain region; calculating a Pearson's correlation coefficient matrix of each brain interval of the subject, and enhancing the matrix through Fisher Z conversion to obtain a functional connection matrix; calculating similarity of the subjects based on the demographic statistical data and similarity of the functional connection matrix, and taking a product of the two similarities as connection strength of the subjects; constructing a crowd graph by taking the subjects as nodes and taking the connection strength and the adjacency matrix between the subjects as an edge relationship; and inputting the crowd graph into the edge weight learnable residual gated graph convolutional network classifier to obtain a classification result. According to the invention, the early diagnosis capability of the autism spectrum disorder is improved.

This invention provides a method and system for optimizing the allocation of urban children's service facilities, comprising the following steps: First, an intelligent projection model is constructed based on population statistics, birth rate data, and death rate data of each street in the target area. This model projects the population age structure of each street for a preset year, obtaining predicted time-series data on the number of children and their spatial distribution density. Second, by combining the types, quantities, and spatial distribution of existing children's service facilities in each street, street types with different stages of supply-demand matching are identified. Third, by further combining the thermal distribution of the child population with the walkable range of children's service facilities, residential areas not covered by children's service facilities are identified. Fourth, based on the identification results of street types with different stages of supply-demand matching and residential areas not covered by facilities, the allocation levels of different types of children's service facilities in each street are compared horizontally to assess the balance of children's service facility allocation and generate optimization suggestions.

A computer-implemented method integrates payment card data into a financial treasury management system. The method involves receiving payment card transaction data tagged with merchant category codes and filtering it based on the organization's category. Financial data such as sales, location, and cash flow is also acquired. Using this data, a resource optimization recommendation is generated and automatically provisioned by transmitting a command to a server. Additional features include receiving demographic data, calculating performance benchmarks, generating predictive indicators, and providing resource discounts or lending products based on the integrated data. Alert indicators are generated when transaction data deviates from expected patterns, prompting organizations to address potential issues.

A visual tracking system for tracking and identifying persons within a monitored location, comprising a plurality of cameras and a visual processing unit, each camera produces a sequence of video frames depicting one or more of the persons, the visual processing unit is adapted to maintain a coherent track identity for each person across the plurality of cameras using a combination of motion data and visual featurization data, and further determine demographic data and sentiment data using the visual featurization data, the visual tracking system further having a recommendation module adapted to identify a customer need for each person using the sentiment data of the person in addition to context data, and generate an action recommendation for addressing the customer need, the visual tracking system is operably connected to a customer-oriented device configured to perform a customer-oriented action in accordance with the action recommendation.

The application discloses a method and system for evaluating the accessibility of service facilities in urban and rural community life circles. First, high-precision road networks, residential plots, four types of public service facilities, and population statistics data are obtained. A walking travel impedance map containing traffic obstacles is constructed based on the road network. The single accessibility index is calculated using an improved two-step mobile search method. The facility weight is determined by the analytic hierarchy process, and the comprehensive accessibility index is obtained. The accessibility is spatially superimposed with population density and aging degree to identify the short-board area of facility configuration. The comprehensive accessibility, population size, and aging degree are used to calculate the rectification priority, and a hierarchical rectification priority map is generated. The application fully considers the walking traffic obstacles, facility service capacity, and distance attenuation, and quantitatively evaluates the actual situation. The short board can be accurately identified, and the rectification priority is given. The application provides efficient and reliable data support and intelligent decision-making basis for the layout optimization of public service facilities in urban and rural community life circles.

Provide a system. 【Solution means】 Means for collecting demographic data, Means for collecting location information of competing facilities, Means for collecting floating population data, Means for analyzing the collected demographic data, the location information of competing facilities, and the floating population data, Means for identifying an appropriate site based on the analysis result, Means for calculating rent and operating costs based on the selected site, Means for proposing an optimal operation model, A system including the above.

The invention discloses a historical population space reconstruction method and system based on altitude driving, a terminal and a storage medium, and the method comprises the steps: obtaining population statistical data in a historical period, and carrying out the preprocessing, and obtaining target historical population data; acquiring historical spatial data, performing matching processing on the historical spatial data and the target historical population data to obtain a three-dimensional structure database, and performing mask extraction and resampling processing to obtain target altitude data; constructing a population and altitude quantitative mapping relation model according to the target historical population data and the target altitude data; and according to the population and altitude quantitative mapping relation model, performing preliminary space distribution processing and loop iterative calculation on the target historical population data to obtain a historical population space reconstruction result. According to the method, the population distribution is quantitatively associated with the altitude, so that the population number in the historical period can be subjected to refined space distribution in the geographic unit, and the accuracy of generation of the historical population space reconstruction result is effectively improved.