67 results about "Individual based" patented technology

A computer system for generating a virtual reality replicant persona for interaction may be provided. The computer system may include at least one processor in communication with at least one memory device. The at least one processor may be programmed to (i) receive a plurality of data about an individual from a plurality of sources; (ii) generate a replicant persona of the individual based upon the plurality of data, wherein the replicant persona is configured to replicate one or more of mannerisms of the individual, appearance of the individual, personality of the individual, historical information of the individual, and conversational talking points of the individual; (iii) conduct a plurality of conversations of the individual; and (iv) update the replicant persona based upon the plurality of conversations.

A method may include transmitting a request for registration by an individual having a condition to a user device associated with the individual, the request including a subset of data associated with the individual; receiving a confirmation of the subset of medical record data and at least one of a first device identification associated with a first device or a second device identification associated with a second device based on the request; determining a risk probability of an adverse event; assigning a position associated with the individual in an ordered list of individuals having the condition based on the risk probability; monitoring update information from the first device and / or the second device; determining an updated risk probability of an adverse event based on the update information; and assigning an updated position associated with the individual in the ordered list of individuals based on the updated risk probability.

Systems, methods and non-transitory computer readable media for generating and operating artificial entities are provided. Some disclosed embodiments may involve receiving information related to a source individual; generating an artificial entity associated with the source individual based on the received information; receiving data reflecting an interaction with the artificial entity; and determining a manner for the artificial entity to respond to the interaction based on the collected information.

A computer-implemented method of determining one or more sets of features to predict the presence of a particular phenotypic characteristic comprises: (a) receiving patient data comprising, for each of a plurality of patients: a feature profile comprising a respective feature status for each of a plurality of features for that patient; and an indication of whether that patient expresses the particular phenotypic characteristic; (b) using a genetic algorithm to generate a plurality of generations of individuals, wherein each individual comprises a subset of the predetermined plurality of features, each generation of individuals generated based, at least in part, on a plurality of fitness scores, each fitness score corresponding to a respective individual in the previous generation, and parameterizing a predictive accuracy of the set of features, each fitness score being calculated based at least in part on the patient data; (c) repeating step (b) until it has been performed N times; (d) from the plurality of individuals generated in steps (b) and (c), selecting a subset of the individuals based on their fitness scores; (e) clustering the selected subset of individuals to generate a plurality of clusters of individuals, based on the similarity of their respective subsets of features; (f) from each cluster, identifying a respective characteristic feature set based on the frequency with which features appear in individuals in that cluster.

The invention relates to the technical field of multi-objective optimization, and discloses a multi-aircraft task allocation method and system based on collaborative multi-population optimization, and the method comprises the steps: obtaining the target coordinates of each flight task and the flight parameters of each aircraft; m populations are generated; any individual in any group corresponds to one task allocation strategy; setting iteration parameters for each population, and controlling iteration of each population; identifying an evolution rhythm state of each population; performing cross-population information exchange and population iterative optimization based on the evolution rhythm state; when a preset iteration termination condition is reached, obtaining a candidate solution of each population; and screening the comprehensive recommendation individuals based on the candidate solution of each population, and obtaining a corresponding task allocation strategy. According to the method, the multi-population collaborative optimization capability is improved, and a high-quality multi-aircraft task allocation strategy can be effectively generated.

A system for identifying connections between individuals based on relationships found in data. The system includes a database containing data records and fields and identifying individuals involved in each record. The database is provided to a computer which executes a machine learning algorithm configured to identify connections between the individuals based on clusters in the data contained in the database, where the machine learning algorithm provides output data identifying clusters of activity relationships, a group label for each cluster when known, and scores for each of the individuals for each of the clusters in which they appear. A communication system algorithm sends actionable communications to particular ones of the individuals based on the output data. Unsupervised learning may be used for initial system training, and supervised learning for ongoing training.

The present invention relates to a method for implementing a transaction with a merchant server (2) involving the verification of at least one criterion relating to an attribute of the identity of an individual at the origin of said transaction, characterized in that it comprises the implementation by data processing means (21) of said merchant server (2), of steps of: Receiving from a terminal (1) of the individual a first set of verifiable identifiers (VP1) including at least one unique verifiable identifier for the implementation of the transaction, called the main verifiable identifier, and a verifiable identifier relating to said attribute of the identity of said individual but not necessary for the implementation of said transaction, called the secondary verifiable identifier, said first set being signed by the client terminal (1); Verifying: said signature of the first set of verifiable identifiers;the validity of each verifiable identifier of the first set of verifiable identifiers; each criterion relating to an attribute of the identity of said individual based on said verifiable identifier relating to said attribute of the identity of said individual; Transmission, to a validation server (3) of the transaction, of a second set of verifiable identifiers (VP2) including said main verifiable identifier and a verifiable identifier relating to said merchant [Fig. 1];

This application relates to the field of artificial intelligence and provides a method, apparatus, electronic device, and storage medium for optimizing the design of urban drainage systems. The method includes: constructing an objective function based on multiple decision variables and optimization objectives of the urban drainage system design; generating an initial population based on constraints and dividing the initial population into multiple subpopulations; iteratively executing the following steps until the iteration termination condition is met, and outputting the optimal solution: if in the convergent evolution stage, selecting the first parent individual from the subpopulation with the smallest convergence value, selecting the second parent individual from the current subpopulation, and generating the first new individual based on the first and second parent individuals; if in the diversity evolution stage, selecting the third parent individual from the diversity archive, selecting the fourth parent individual from the current subpopulation, and generating the second new individual based on the third and fourth parent individuals; and updating the current subpopulation. This application achieves a balance between convergence and diversity, improving optimization efficiency and quality.

Described herein are systems and methods that related to techniques for managing individual data (such as patient data). In examples, systems can be configured to obtain data associated with individual profiles; obtain data associated with individual samples indexed in accordance with a period of time; and for each individual, link one or more entries of the individual profile corresponding to the individual with individual samples corresponding to the individual based on the period of time and the profile for each individual. In some examples, the system can generate workflow profiles corresponding to each individual of the plurality of individuals based on linking the one or more entries of the individual profile with individual samples. The system can then de-identify the workflow profiles corresponding to each individual of the plurality of individuals to generate limited workflow profiles that are used to test one or more models in a development environment.

The invention provides a model preprocessing method and system for a lithology identification model, and the method comprises the steps: obtaining a hyper-parameter range of a plurality of hyper-parameters in a pre-constructed lithology identification model, constructing a first preset number of individuals based on the parameter range of the plurality of hyper-parameters, completing the initialization of a population, updating the initialized population in a preset round; each update round comprises global optimization and local optimization; in the global optimization step, the position of the individual is updated based on the distance between the individual and the target individual, and the updated position of the individual is obtained; in the step of local optimization, the position of each individual in the global optimization group is optimized again based on the individual influence parameter group, and local optimization is completed; and after updating of a preset round, screening a final individual through the fitness, performing model training on the lithology identification model by applying hyper-parameters of the individual, and performing lithology identification after training is completed.

We provide the system. [Solution] A means for receiving communication data from multiple information devices and analyzing that communication data to identify each individual's interests and emotions, A means for generating multiple activity suggestions tailored to each individual's interests and emotions based on the analysis results, A means for transmitting the generated activity proposals to each information device and receiving responses to the activity proposals, A means of adjusting and deciding on the optimal activities among individuals based on their responses, Means for making reservations and transactions related to the decided activities, A system that includes means to analyze information related to meal planning and automate the selection of the optimal restaurant or delivery procedures.

Systems, methods and non-transitory computer readable media for generating and operating artificial entities are provided. Some disclosed embodiments may involve receiving information related to a source individual; generating an artificial entity associated with the source individual based on the received information; receiving data reflecting an interaction with the artificial entity; and determining a manner for the artificial entity to respond to the interaction based on the collected information.

A system providing self-service access to locked merchandise comprising: (a) providing a fixture that restricts access to the locked merchandise, wherein the fixture can automatically lock or unlock, allowing or restricting access to the locked merchandise; (b) providing a means of uniquely identifying an individual attempting to access the merchandise; (c) measuring a set of behaviors of the individual during any time the fixture is an open mode; (d) assessing whether the set of behaviors of the individual are suspicious or not relative to a set of suspicious event thresholds; (e) storing the individual and their set of behaviors as accessible records in at least one database; and (f) providing an algorithm which determines future access privileges of the individual to the enclosure based on a set of variables. Additionally, a system for maximizing sales of and minimizing theft of merchandise in a retail environment, the system comprising: (a) providing a merchandise fixture, wherein the merchandise fixture can allow or restrict access to the merchandise; (b) presenting a questionnaire to an individual; (c) providing a means of uniquely identifying the individual attempting to access the merchandise; and (d) allowing or restricting access to the merchandise based on the individual's responses to the questionnaire.

The application discloses a pre-examination abnormal registration group detection method based on a community discovery algorithm. A graph structure for representing the association relationship between examinees is constructed, then the examinees are divided into communities or non-community individuals based on the graph structure, and then the graph structure is subjected to message passing to generate the embedded representation corresponding to the examinees, and whether there is a risk is predicted according to the embedded representation corresponding to the examinees, so as to determine the confidence degree corresponding to the examinees and the preset label, and then generate a risk score for the examinees. Then, the high-risk examinee characteristics are counted based on the risk score, so that the high-risk label marking and dyeing of the high-risk examinee nodes are performed, and the label propagation of the high-risk label in the graph structure is performed. Through the method, the risk characteristics can be counted, the risk label can be marked and propagated based on the graph structure, so that the examinee group that may have risks can be determined in a big data manner before the examination, and the efficiency and accuracy of the risk prediction of the examinees before the examination are improved.

The present invention relates to the field of data processing, and in particular to a large-scale model recommendation method and system based on individual user-side behavior. The method: obtains user behavior data of a target user; inputs the user behavior data into an active analysis model to perform user profiling, and obtains the target user's behavior preference information; based on the behavior preference information and the target user's current geographical location, predicts the target user's behavior trajectory information within a preset time period in the future through a behavior construction model; the behavior trajectory information includes the target user's behavior nodes whose predicted execution probability reaches a preset threshold within a preset time period in the future; and recommends to the target user a comprehensive service unit that matches the current geographical location based on the behavior trajectory information. Through the active analysis model and the behavior construction model, a comprehensive analysis of user behavior and the environment in which they are located is performed from different angles, thereby improving the accuracy and efficiency of information recommendations, providing users with a variety of comprehensive service information, and improving user experience.

A system for identifying connections between individuals based on relationships found in data. The system includes a database containing data records and fields and identifying individuals involved in each record. The database is provided to a computer which executes a machine learning algorithm configured to identify connections between the individuals based on clusters in the data contained in the database, where the machine learning algorithm provides output data identifying clusters of activity relationships, a group label for each cluster when known, and scores for each of the individuals for each of the clusters in which they appear. A communication system algorithm sends actionable communications to particular ones of the individuals based on the output data. Unsupervised learning may be used for initial system training, and supervised learning for ongoing training.

A computer-implemented cognitive assessment tool is provided for assessing cognitive ability of an individual while multi-tasking. In one embodiment, a computer processing system on which the tool is implemented may receive form the individual first responses to a first task and second responses to a second task, where the first task and the second task are presented to the individual simultaneously. The system may determine that the first task and the second task are performed by the individual based on the first responses and the second responses, and compute a cognitive measure using one or both of the first responses and the second responses. Further, computing the cognitive measure may be based on performance measures of one or both of the first responses and the second responses. Based on the cognitive measure, the system may output a cognitive assessment to the individual.

The invention discloses a resource scheduling method and computer equipment, and relates to the technical field of resource scheduling, and the method comprises the steps: forming an initial population through a path chain constructed by a task set and a node set, and calculating the final score of an individual based on the switching time information and load information of a task; dividing the initial population into a local development sub-population and a global exploration sub-population based on similarity values between different path chains; adjusting the proportion of the sub-populations based on the fitness improvement rate of the initial population; for the individuals in the current population, executing path exchange and random disturbance operation according to the visual range parameters of the sub-populations to which the individuals belong, and updating a path chain in the current population; and repeatedly executing the starting and subsequent steps of calculating the similarity value, and when a termination condition is met, taking the path chain with the highest final score in the current population as a target resource scheduling scheme. The technical problem of extensive resource scheduling in related technologies is solved, and the technical effect of improving the resource scheduling reliability is achieved.

The invention relates to a group behavior identification method based on a 3D human body skeleton. The method comprises the following steps: S1, obtaining training set data; s2, extracting a first feature vector of each independent individual based on the first skeleton sequence in combination with a backbone extraction network, and verifying a first individual classification result and a corresponding individual behavior labeling result; s3, splicing the first feature vectors of the independent individuals to obtain a first group feature, and processing the first group feature by adopting a self-attention-cross attention neural network to obtain a second group feature; s4, target features are extracted based on the second group features, a first group behavior classification result is obtained, and model parameters of the backbone extraction network are modified based on the difference between the first group behavior classification result and a corresponding group behavior labeling result; and S5, carrying out group behavior identification on the first skeleton sequence to be identified by utilizing the trained backbone extraction network, the first classification model, the second classification model and the first skeleton sequence to be identified. Compared with the prior art, the method has the advantages of reducing the training sample size level and the like.

The present application relates to the technical field of intelligent conference, in particular to a conference interaction method and computer program product based on personal intelligent agent, comprising sending conference basic data and personal intelligent agent participation request to a person who intends to participate in the conference; receiving participation feedback of the person who intends to participate in the conference in response to the personal intelligent agent participation request; according to the participation feedback, organizing the personal intelligent agent to conduct virtual conference according to the conference basic data, obtaining intelligent agent conference record; sending the intelligent agent conference record to all participating personal intelligent agent corresponding participating persons, so that the participating persons modify and confirm; receiving the modification data of the personal intelligent agent speech sent by the participating persons; calling AI to adjust the intelligent agent conference record according to the modification data, generating conference summary; sending the conference summary to all participating persons for confirmation. The problem of how to balance the demand of the participating person for the right to participate in the conference and the right to participate in the conference of the personal intelligent agent is better solved.

The invention discloses a method, a device, equipment, a medium and a product for identifying the co-space-time risk of a migrant bird, and relates to the field of migration tracking analysis, and the method comprises the steps: employing a taxonomy information retrieval database platform to obtain migrant bird tracking data; the taxonomy information comprises an objective, a subject, a genus, a species and a common name; performing visual analysis on the motion trail of each individual based on the migrant bird tracking data to obtain individuals suitable for clustering and individuals not suitable for clustering; on the basis of the individuals suitable for clustering, according to parameters of different migrant bird species, utilizing a T-DBSCAN algorithm to identify intermittent place information; determining the stay duration of each region according to the region boundary based on individuals not suitable for clustering; according to the stop place information or the stop duration of each area, determining the common space-time condition of different migrant bird species; determining space-time co-occurrence characteristics according to the space-time co-occurrence conditions; the space-time co-occurrence characteristics are used for determining the space-time co-occurrence risk of the migrant birds According to the invention, the time-space sharing risk can be accurately identified.

The present disclosure includes systems and methods for posture control of cloud environments. Various embodiments include scanning a cloud environment for posture control data; identifying configurations associated with one or more resources in the cloud environment; generating one or more alerts related to the one or more resources based on the configurations; and assigning the one or more alerts to one or more individuals. The one or more alerts can then be sent to the one or more individuals based on the assigning.

A method for determining a finite impulse response filter, including generation of a plurality of individuals presenting configuration parameters, and cyclic implementation of the following operations in relation to each current population of configuration parameters: evaluation by an objective function of each individual, evaluation by at least one constraint function of each individual, selection of a group of individuals among all the individuals based on their evaluations by the objective function and the constraint function and formation of parent individuals, crossover of parent individuals to form a new population, mutation of individuals in the new population, and verification of a stopping criterion.

The invention provides a PMU multi-working-condition test sequence automatic scheduling method and system, and relates to the technical field of power system automatic testing, and the method comprises the steps: collecting working condition data, constructing a working condition vector, initializing a priority sequence corresponding to each working condition, and generating a task sequence based on the priority sequence; analyzing a hysteresis phenomenon during working condition switching based on the task sequence, constructing a hysteresis significant factor, and obtaining the task sequence; analyzing an error nonlinear cumulative effect of a working condition based on the hysteresis significant factor, and constructing an error cumulative factor; analyzing the risk degree of dung beetle individuals falling into a local optimal solution based on the hysteresis significant factors and the error accumulation factors, and constructing dynamic factors; and updating a priority sequence of the dung beetle individuals based on the dynamic factors, and reordering to obtain an optimal task sequence to realize automatic scheduling. According to the invention, unplanned interruption caused by temperature drift is effectively avoided, and the detection efficiency is improved.

The embodiments of the disclosure provide a method for selecting a task network, a system and a method for determining actions based on sensing data. The method of the embodiments of the disclosure includes: mapping the sensing data into an input feature vector; feeding the input feature vector into a specific task network to generate an output feature vector via the specific task network, in which the specific task network is trained based on a plurality of first individuals and a plurality of second individuals, the first individuals belong to a first population, the second individuals belong to a second population, and the first individuals and the second individuals are evolved via a coevolution process; and determining an output action according to the output feature vector, and setting a second specific individual based on the output action, in which the second specific individual belongs to the second population.

A system for providing data privacy risk of data privacy related data objects for assigning an access right for processing and storing the data objects, including receiving more than one data object and extracting data from the data objects, generating at least one identity space, wherein the identity space includes those data objects which include extracted data elements concerning a group of individuals or a subset of the group of individuals, and wherein the group of individuals differs from the group of individuals of each other identity space, calculating at least one privacy risk for each identity space and for the contained individuals depending on re-identification probabilities of each individual based on the extracted data elements in the identity space and depending on a set of background knowledge which is assumed to be known, exporting the extracted data and export the calculated privacy risk.

The invention provides a dispatching method, device and equipment based on a genetic algorithm and a storage medium, and relates to the technical field of task scheduling. To-be-dispatched tasks, task starting and ending time, skills required by the tasks, to-be-dispatched employees, employee shift time and employee skills are input; based on a skill matching principle and a time matching principle, randomly allocating tasks to be dispatched to employees to be dispatched to obtain an initial population; calculating the fitness of the individual based on the distance matrix; wherein elements in the distance matrix represent passing duration between the task places, and the fitness and the total transition time are in a negative correlation relationship; and selecting parent individuals according to the fitness to carry out crossover operation to obtain a new population, returning to the step of calculating the fitness to carry out iterative operation, and when iteration is finished, converting current population information into dispatching information and outputting the dispatching information to a user terminal. According to the invention, not only can the adaptability of dispatching tasks and employees on time and skills be ensured, but also the labor efficiency can be improved.

The present invention provides a model preprocessing method and system for a lithologic identification model, the method comprising the following steps: obtaining parameter ranges of multiple hyperparameters in a pre-constructed lithologic identification model, constructing a first preset number of individuals based on the parameter ranges of the multiple hyperparameters, completing an initialization population, and performing a preset round of updates on the initialization population; including global optimization and local optimization in each update round; in the global optimization step, updating the position of the individual based on the distance between the individual and a target individual to obtain an updated position of the individual; in the local optimization step, re-optimizing the position of each individual in the global optimization population based on an individual influencing parameter group to complete local optimization; after the preset round of updates, screening the final individual by fitness, applying the hyperparameters of the individual to the lithologic identification model for model training, and performing lithologic identification after the training is completed.

This invention provides a method, electronic device, and storage medium for determining a cigarette filter rod production plan. The method includes: determining initial leading individuals based on a first evaluation result of simulated production of each initial individual in an initial population; updating the initial population to obtain a offspring population; determining offspring leading individuals based on a second evaluation result of simulated production of each offspring individual in the offspring population; adjusting the offspring individuals according to an adjustment strategy, and determining new offspring leading individuals based on a third evaluation result obtained from simulated production of the adjusted offspring individuals; determining a target leading individual based on the initial leading individuals and the offspring leading individuals; and determining a new initial population and initial leading individuals based on the initial population and the offspring population if the termination condition is not met. This invention can quickly generate multiple high-quality production plans adapted to different needs, improving production efficiency. It also provides an electronic device and a computer-readable storage medium for executing the above method.