113 results about "Age groups" patented technology

The embodiment of the invention relates to a processing method and device of an Alzheimer disease risk prediction model. The method comprises the steps that DT I-ALPS feature information of dementia crowds and healthy crowds of a specified age group is obtained in a big data collection and volunteer recruitment mode, and a corresponding model data set is constructed and recorded as a first data set; constructing a three-classification prediction model for predicting the risk of the Alzheimer's disease as an Alzheimer's disease risk prediction model corresponding to a specified age group; training an Alzheimer disease risk prediction model based on the first data set; after model training is finished, DT I-ALPS feature information, input by the user, of any tested person of the specified age group is input into the Alzheimer disease risk prediction model for prediction, and a corresponding classification probability vector is obtained and fed back to the current user. According to the invention, prediction accuracy and prediction stability can be improved.

The invention discloses a children education knowledge boundary management method, system and device based on a large model, and relates to the technical field of intelligent education, and the method comprises the steps: carrying out the intention recognition of the input and historical dialogues of a target user, and obtaining the question and answer intention of the target user; retrieving the target answer from a pre-constructed knowledge base; wherein the target answers are standard answers most related to the question and answer intention, and each standard answer conforms to the education value required by the target age group; generating reply information under constraint conditions according to the question and answer intention and the target answer; wherein the constraint condition is used for controlling the reply information to be consistent with the content of the target answer; the knowledge boundary management of the reply information can be ensured to be controllable.

The embodiment of the invention provides an intelligent recommendation method and system based on child digital picture book reading. The method comprises the following steps: constructing a recommendation model based on self-supervised learning and a convolutional neural network CNN; in the self-supervised learning module, feature representation of a comparison mechanism optimization model combined with user cognition is introduced; constructing a dynamically updated user portrait, wherein the user portrait comprises a current cognitive level label of the user; in response to a reading request of a user, self-adaptive fusion is carried out on a user portrait and the reading request, an age-worthiness evaluation factor of the picture book is introduced in the fusion process, and the age-worthiness evaluation factor is determined based on the matching degree of the character difficulty, the picture complexity and the user cognitive level of the picture book. And taking the fused label vector as the input of a trained recommendation model to obtain a recommendation list. According to the embodiment of the invention, the feature representation of the model is dynamically optimized in combination with the cognitive development stage of the user, the reading ability difference of different age groups is accurately adapted, and the recommendation accuracy and adaptability are improved.

The invention provides a dynamic advertisement putting strategy generation method and system based on user behaviors, and relates to the technical field of advertisement putting. The method comprises the following steps: constructing a user behavior sequence; determining an association relationship between the behavior pattern and the sensitive attribute group; based on the incidence relation and the current advertisement putting strategy, the probability that the groups with the different sensitive attributes receive the specific advertisement is evaluated, and quantitative different risk measurement is obtained by calculating the difference index of the advertisement receiving probabilities among the groups; taking the different risk measurement as a constraint condition, adjusting an advertisement putting rule, and obtaining an adjusted advertisement putting strategy; and performing advertisement putting according to the adjusted advertisement putting strategy. According to the method provided by the invention, the technical problem of how to avoid the difference when the dynamic user behavior sequence and the associated context information are utilized to generate the advertisement putting strategy is solved, the difference elimination of the users of the specific age group is remarkably reduced, and the putting fairness is improved.

The present application discloses a method, system and device for managing the knowledge boundary of children's education based on a large model, which relates to the field of intelligent education technology. The method includes: performing intent recognition on the input and historical conversations of the target user to obtain the question and answer intention of the target user; retrieving the target answer from a pre-built knowledge base; wherein the target answer is the standard answer most relevant to the question and answer intention, and each of the standard answers conforms to the educational values ​​required by the target age group; generating reply information under constraints based on the question and answer intention and the target answer; wherein the constraints are used to control the reply information to be consistent with the content of the target answer; the present application can ensure that the knowledge boundary management of the reply information is controllable.

The invention belongs to the field of diet management, and particularly relates to a nutrition diet management system and method.The management system comprises a data storage module used for storing raw material library data, nutrition standard data of students of all ages and basic information data of schools. The nutrient distribution weight is re-planned according to the differentiated requirements of all age groups on key nutrients such as protein, calcium and vitamins. The method has the advantages that the defect that a traditional average distribution mode does not depend on age difference is overcome, the matching degree of nutrition distribution and standard intake of each age group is increased by 60% or above, calcium and high-quality protein supply is enhanced for adolescent students, and the health problems of slow growth, obesity and the like caused by nutrition imbalance are effectively solved. The method has the core advantages that nutrition support matched with the growth stages of students is provided for the students, healthy development of the bodies is guaranteed from a nutrition supply source, and the students are assisted to obtain the most suitable nutrition nourishment in different growth stages.

The invention relates to the technical field of child health assessment, in particular to a child body fat rate adaptive prediction method and system based on trajectory feature collaboration.The method comprises the following steps that a child physical examination data set is obtained, height and weight changes are analyzed, difference ratio screening samples are calculated, waistline change slope assessment stability screening samples are extracted, and a child body fat rate prediction result is obtained; calculating a sign proportion difference to adjust a training weight, identifying an age group residual difference to adjust model parameters, and adjusting a prediction slope generation result in combination with a body fat trend direction and a body weight trend direction. According to the method, samples are screened through height and weight tracks, abnormal data are eliminated in combination with fluctuation continuity of waistline change slope, a feature weighting coefficient is set according to proportion deviation of height, weight and muscle amount, and a response coefficient is adjusted through a distance relation between a grouping mean value of age group residual errors and a concentration interval. And the change path is judged by utilizing the consistency of the body fat and body weight prediction trend, so that non-trend prediction offset is avoided, and the stability of the model and the sample adaptability are improved.

The invention belongs to the technical field of bioinformatics, and discloses an epigenetics age evaluation system and method based on machine learning. Comprising the following steps: collecting methylation data of a user in real time; screening out methylated feature data from the methylated data, and compressing the methylated feature data into hidden feature data; obtaining historical feature data, and constructing an age evaluation model; inputting hidden feature data acquired in real time into the age evaluation model, predicting an epigenetic age, and marking the epigenetic age as a predicted age; systematic disturbance is carried out on the predicted age, the predicted error value of each simulated age is calculated, and the simulated age corresponding to the predicted error value with the minimum numerical value is used as a corrected age; calculating a relative age, and taking a mean value of the relative age and the corrected age as an epigenetics age of the user; according to the method, the adaptability and accuracy of the model on different individuals and age groups can be improved, so that the accuracy and timeliness of epigenetics age assessment are improved.

The invention provides a portrait beautifying real-time processing method based on a deep neural network, and the method comprises the steps: carrying out the age classification processing of a face region in a feature map through an initialized age recognition neural network module, analyzing the face age indication features of the face of a user, judging the age group of the user, and outputting an age classification label; performing differentiation analysis on each face age indication feature according to the age classification label, taking a differentiation analysis result as a weight distribution basis, distributing weight coefficients to different face age indication features according to importance degrees, and obtaining face feature vectors for different age groups; and according to an eye processing strategy in the personalized beautification processing scheme, performing refined processing on the eye region, and adjusting eye contour enhancement strength and color saturation parameters according to the age group of the user to obtain image data subjected to eye beautification processing.

The invention discloses a health monitoring and alarming system and method for animal individuals in a zoo, belongs to the field of zoo animal health monitoring, and solves the technical bottleneck through cooperation of a sensing layer, an edge computing layer and a cloud analysis layer. The system particularly sets differentiated threshold values for animals of different age groups, genders and health conditions, the dynamic baseline adjustment and multi-source data fusion algorithm is combined, the anomaly detection precision is remarkably improved, meanwhile, a grading alarm mechanism and feedback driven model optimization form a closed loop, the conversion from passive response to active early warning is achieved, and the system is suitable for the animal health monitoring and early warning of animals of different age groups, genders and health conditions. Potential health risks can be identified 12-24 hours in advance, and efficient and accurate technical support is provided for animal health management.

The invention relates to the technical field of population prediction, and discloses a population prediction method and device based on combination of an ARIMA model and a queue element method. The method comprises the steps of obtaining historical migration population data of a to-be-predicted region, determining a difference order through ADF test, preliminarily determining the range of an autoregression order and a moving average order by using an autocorrelation function and a partial autocorrelation function, and constructing an ARIMA model; the optimized ARIMA model is adopted to fit historical migration population data, a migration population prediction result is obtained, and migration population data of each age group in the target prediction time period is output in combination with age structure data of floating population of the reference year; taking the migration population data of each age group as input parameters of migration population in a queue element method; according to a preset sum growth rate, selecting a western mode of a numeral-demann region model life table as a death model; and setting the average life expectancy according to a preset birth ratio, and realizing permanent resident population prediction of the to-be-predicted region.

The invention discloses an economic early warning identification method based on big data analysis. The economic monitoring precision and multi-dimensional control are remarkably improved. In the financial dimension, the accumulated income and expenditure difference value and the cost monitoring value are accurately compared, the monitoring threshold value is flexibly calibrated by means of the adaptive cost index, and the economic dilemma is sensitively informed. In the age level, the average age of the group is considered, different age indexes are matched according to age monitoring values to optimize a threshold value, and the economic pressure bearing difference of each age group is considered. And time dimension: locking one-quarter and four-quarter special time periods, finely regulating and controlling by virtue of corresponding time indexes, and conforming to seasonal income fluctuation characteristics. According to the technical scheme, the method comprises the following steps of: selecting a group number, calling a proper personnel index according to the group number, accurately measuring the family scale influence, performing multi-dimensional collaborative operation, breaking through the previous single-dimensional limitation, practically enhancing the accuracy and reliability of economic early warning monitoring, starting from big data and multiple dimensions, and bringing remarkable advantages for an economic early warning monitoring model.

The application provides an emotion regulation ability detection method and device based on a brain-computer interface. The emotion regulation ability detection method can adjust emotion evoking materials presented in a detection process and detection models and detection features used according to the age of a subject, so that the detection process can accurately adapt to test populations of different age groups, and the accuracy of the prediction results output by the detection model is effectively improved.

The invention relates to medicine and can be used for overcoming stuttering by developing the rhythmic component of speech. Exercises are performed on a step-by-step basis. In a first step, exercises are performed for the muscles of the respiratory, phonatory and articulatory systems. In a second step, an individual non-speech rhythm is cultivated. In a third step, a sense of rhythm is developed. In a fourth step, a poetic speech rhythm is cultivated. In a fifth step, a prosaic speech rhythm is cultivated. In a sixth step, narrative and interrogative intonations are cultivated. In a seventh step, rhythmic processes are trained to become automatic in independent speech. The method makes it possible to overcome psychogenic and neurogenic stuttering, without the use of medication or the risk of relapse, and is suitable for all age groups.

The present invention relates to a universal transparent guide for direct perforation of dental dams that is suitable for different age groups, both adults and / or infants. It also features references for centering the dam in the oral cavity and the coupling of the dam holder, which allows for absolute isolation in less time by facilitating the orientation and perforation of the dental dam regardless of whether it is thick, opaque, and / or black.

The invention belongs to the field of identity authentication, and discloses a touch screen behavior-based age group identification method and a related device, and the method comprises the steps: obtaining touch screen behavior data of a user; converting the touch screen behavior data into a touch screen track dynamic video sequence and a touch screen track image; obtaining an age group recognition result of the user through a pre-trained age group recognition model according to the touch screen track dynamic video sequence and the touch screen track image; wherein the pre-trained age group recognition model is constructed based on a neural network model, and is used for extracting features of each touch screen track dynamic video in the touch screen track dynamic video sequence to obtain first features and extracting features of a touch screen track image to obtain second features; and fusing each first feature with the second feature to obtain a plurality of fused features, and outputting an age group prediction result of the plurality of fused features. Through multi-dimensional behavior analysis and dynamic mode capture, the age group identification accuracy is improved, and the limitation that complex behavior information is difficult to capture by traditional artificial features is overcome.

The glasses leg comprises a main body and a split body, an adjusting assembly is arranged between the main body and the split body, the adjusting assembly comprises a limiting block and an adjusting connecting piece, and an inserting groove extending in the length direction of the adjusting connecting piece is formed in the adjusting connecting piece; the inner groove wall of the insertion groove is provided with a plurality of positioning grooves communicated with the insertion groove, the limiting block movably penetrates through the outer wall of the glasses leg and is separably inserted into the insertion groove, and the different positioning grooves arranged along the length direction of the adjusting connecting piece are respectively used for limiting different clamping positions of the limiting block in the length direction of the adjusting connecting piece. The length of the adjusting connecting piece located between the main body and the split body is adjusted by adjusting the length of the adjusting connecting piece, so that multi-gear adjustment is formed on the length of the glasses legs, the glasses legs can adapt to different sizes of heads by freely adjusting the length of the glasses legs, and the wearing requirements of different people at different age groups are met.

The application belongs to the technical field of bioinformatics, and discloses an epigenetic age assessment system and method based on machine learning; comprising: collecting methylation data of a user in real time; screening methylation feature data from the methylation data and compressing the methylation feature data into hidden feature data; obtaining historical feature data and constructing an age assessment model; inputting the hidden feature data obtained in real time into the age assessment model, predicting an epigenetic age, and marking the epigenetic age as a predicted age; systematically perturbing the predicted age, calculating a prediction error value of each simulated age, taking a simulated age corresponding to a minimum prediction error value as a corrected age; calculating a relative age, and taking a mean value of the relative age and the corrected age as an epigenetic age of the user; the application can improve the adaptability and accuracy of the model on different individuals and age groups, thereby improving the accuracy and timeliness of epigenetic age assessment.

The application belongs to the technical field of urban planning, and discloses a kind of public service facility layout planning method and system friendly to old people, the method comprises: obtaining the portrait information of old people in community, and identifying vulnerable old age groups;According to the portrait information of vulnerable old age groups, set the minimum accessibility guarantee condition of individualization;Pre-optimization is carried out on the alternative scheme to improve the satisfaction rate of the minimum accessibility guarantee condition of vulnerable old age groups;On the premise that the satisfaction rate of vulnerable old age groups is not reduced, the overall travel convenience of all old age groups is optimized as a target for comprehensive optimization;From a plurality of comprehensive optimization schemes, the final public service facility layout scheme is determined;Thus, the problem of ignoring the heterogeneity within the old age group in the prior art can be effectively solved, and the scientificity and humanization of public service facility layout planning are significantly improved.

The invention belongs to the field of medical image processing and artificial intelligence, and particularly relates to a construction method and application of a bone age evaluation model based on label distribution learning, and the method comprises the steps: constructing a bone age evaluation model which comprises a sub-model A, K sub-models B, a selection unit and a convolutional network C; k corresponds to different age groups; training the sub-model A by adopting the training sample set, and training the model B of the corresponding age group by adopting the training sample set of each age group; the model A obtains predicted bone age label probability distribution A according to each input image; the selection unit is used for substituting the distribution A into a normal probability density function with the real bone age of the input image as the center, calculating a normal distribution probability value, selecting a sub-model B of an age group corresponding to the age of the input image, and predicting again according to the input image to obtain predicted bone age label probability distribution B; and the convolutional network C is used for integrating the distribution A and the distribution B to generate final bone age label probability distribution. The accuracy of bone age evaluation can be improved.

The present invention provides an SSD fault prediction method, device and medium based on multi-task learning, which relates to the technical field of machine learning. The method includes: preprocessing and normalizing the data in the obtained hard disk logs, obtaining a plurality of initial SSDs and the initial data of each initial SSD, obtaining a list of target age groups and a list of key features corresponding to each target age group, obtaining a list of target SSDs corresponding to each target age group and a list of target key feature values corresponding to each target SSD, obtaining a target multi-task learning model, obtaining a target stacking result, obtaining a first other classifier and a second other classifier, and obtaining a first other prediction result; obtaining a second other prediction result, and based on the target stacking result, the first other prediction result and the second other prediction result, obtaining a final prediction result corresponding to each target SSD, so as to improve the accuracy of SSD fault prediction.

The utility model discloses a fence structure and a child appliance, and relates to the technical field of child appliances, the fence structure comprises a fence main body and a connecting assembly, the fence main body comprises a first supporting position and a second supporting position which are oppositely arranged in a first direction, and a flexible connecting piece connected between the first supporting position and the second supporting position, the first supporting position, the second supporting position and the flexible connecting piece jointly define a containing cavity with the variable size in the first direction. The connecting assembly is connected between the first supporting position and the second supporting position so as to adjust the distance between the first supporting position and the second supporting position. According to the technical scheme, a user can correspondingly adjust the depth of the containing cavity corresponding to children of different age groups or different heights, on one hand, the user experience can be improved, and on the other hand, due to the fact that the depth of the containing cavity can be adjusted, the occupied space can be reduced when the containing cavity is stored.

This invention provides a facial recognition method, apparatus, and electronic device. The method involves acquiring a target image and the age parameter of a face to be recognized within the target image; extracting target facial features from the target image; and determining whether the face to be recognized matches the target identity based on the age parameter, the target facial features, and the feature classification results corresponding to the target identity. The feature classification results include standard facial features for multiple age groups corresponding to the target identity. This approach takes into account that a person's appearance changes with age. Therefore, during facial recognition, the facial features of the face to be recognized are matched with standard facial features that match its age parameter, thereby improving the accuracy of facial recognition.

This invention relates to the field of cognitive testing techniques and sensor-based measurement systems to create a block design test-based cognitive ability and psychomotor profile assessment system that can be used in various age groups. This system integrates testing media in the form of physical blocks, digital simulations, or a combination of both, as well as a rotation sensor-based data acquisition module to record the orientation and movement of the blocks in real-time during the assembly process. The obtained rotation data is then processed to analyze the level of accuracy, speed, interaction patterns, and movement coordination that represent the user's cognitive abilities and psychomotor profile. Unlike conventional methods that rely on subjective observations by the examiner, this system is capable of conducting assessments objectively, measurably, and based on quantitative data.Furthermore, this system enables more efficient testing by storing results digitally for monitoring, evaluation, and research. This invention is intended to support a variety of applications, from monitoring cognitive development in children, evaluating cognitive performance in adults, to early detection of cognitive and psychomotor decline in the elderly.

This application relates to automated assistants that accommodate multiple age groups and / or vocabulary levels. Described herein are techniques for enabling an automated assistant to adjust its behavior depending on a detected age range and / or "vocabulary level" of a user that is interfacing with the automated assistant. Data indicative of utterances of the user can be used to estimate one or more of an age range and / or vocabulary level of the user. The estimated age range / vocabulary level can be used to influence aspects of a data processing pipeline employed by the automated assistant. Aspects of the data processing pipeline that can be influenced by the age range / vocabulary level of the user can include one or more of automated assistant invocation, speech-to-text processing, intent matching, intent resolution, natural language generation, and / or text-to-speech processing. In some implementations, one or more tolerance thresholds associated with one or more of these aspects such as grammatical tolerance, vocabulary tolerance, etc. can be adjusted.

This application provides a physiological age prediction method, apparatus, device, and medium. By acquiring fundus images, the method predicts age groups based on ocular features in the images, and then determines an age offset based on lesion features in the images. Based on the age group prediction results and the age offset, the user's physiological age can be obtained. Furthermore, this application can adjust the resolution of fundus images, using low-resolution images for age group prediction and high-resolution images for lesion detection. This allows physiological age to be predicted using fundus images, saving prediction costs and shortening prediction time.

The utility model relates to the technical field of early-stage investigation of urban and rural planning, and discloses a folding type children investigation device which comprises a plurality of connecting plates, a plurality of holes are formed in each connecting plate, a plurality of connecting blocks are arranged on one side of each connecting plate, a cylindrical batten is fixedly connected to the outer wall of each connecting block, and the cylindrical batten is fixedly connected to the outer wall of each connecting block. The cylindrical battens are slidably connected to the inner walls of the holes, a counter is fixedly connected to the top of each connecting block, a buckle switch is fixedly connected to one side of each connecting block, a voice guide switch is fixedly connected to the other side of each connecting block, and a sound outlet is formed in the other side of each connecting block. According to the utility model, planning space is provided for participants of different age groups through the four surfaces of the outer side wall of the equipment, then information is known through display information on one side of the connecting block or voice of the sound outlet, and the cylindrical battens are inserted into the inner walls of the holes, so that compared with traditional equipment, the children research is enhanced.

The invention relates to a method for constructing a growth model of a brain in a life cycle, and the method comprises the steps: obtaining brain MRI images of individuals of different age groups, and dividing the cerebral cortex into n regions; constructing a morphological feature network for sMRI of the brain MRI image of the individual, and performing morphological feature similarity degree analysis to obtain a first phenotype; constructing a functional network for the fMRI of the brain MRI image of the individual; constructing a structure-function coupling matrix for the morphological feature network and the function network, and calculating to obtain a second phenotype; selecting the first phenotype and the second phenotype of each individual as dependent variables and the age of each individual as a smooth item to carry out GAMLSS modeling, and selecting JSU distribution to respectively fit the change of the first phenotype and the second phenotype along with the age to generate a reference growth curve. The method can be used for studying the growth mode of the brain network in the whole life cycle, studying life cycle association between morphological characteristics and functional characteristics of different areas and the like.

The invention discloses a clinical prediction model for the dyslipidemia probability of a child hepatolenticular degeneration patient and a design method, and belongs to the technical field of medical information. The clinical prediction model comprises an input module for receiving patient parameter indexes consisting of an age group (Age group, lt, 10 years old or more), alanine aminotransferase (ALT), gamma-glutamyltransferase (GGT), homocysteine (Hcy), superoxide dismutase (SOD) and platelet count (PLT); the processing module is connected with the input module and calculates the prediction probability of the patient according to the model, and the output module is connected with the processing module and outputs the probability of dyslipidemia of the child hepatolenticular degeneration patient, which is finally obtained by the clinical prediction model. The prediction model established by the invention has good distinction degree, calibration degree and clinical practicability, has relatively high accuracy, and can be conveniently used for early recognition and risk prediction of dyslipidemia caused by hepatolenticular degeneration of children.

The utility model relates to the technical field of leg supporting, in particular to a leg supporting device for bone surgery, which comprises a hollow column, fixing and clamping mechanisms are movably arranged on two sides of the hollow column at the bottom end, and each fixing and clamping mechanism comprises a lifting rod, a wedging groove, a fixing screw, a threaded rod and a rotating handle. The lifting rods are pulled out of the hollow columns up and down, then the rotating handles on the two sides of the bottom ends of the two hollow columns are rotated, the threaded rods move towards the interiors of the hollow columns to be fixed, the corresponding height is determined, and one ends of the threaded rods are clamped into the wedging grooves in the two sides of the lifting rods to be fixed. At the moment, the patient can place the whole leg on the U-shaped bearing block, the gravity of the leg downwards extrudes a buffer spring to enable the buffer spring to generate elastic deformation, supporting is conducted through the brought reverse acting force, the device is provided with a supporting mechanism capable of being adjusted in a lifting mode, the device can be suitable for being used by patients of different age groups, and the optimal supporting and fixing point can be found conveniently.