187 results about "Selection criterion" patented technology

The present invention relates to a computer-implemented method and system for generating a video editing project using artificial intelligence (AI) and machine learning (ML) techniques. The method includes processing a collection of video clips to generate text-based metadata, receiving selection criteria to identify relevant video clips, and generating a natural language prompt based on the selection criteria. The prompt, comprising instructions and context, is provided to a large language model (LLM), which processes the input and outputs data for constructing a video project data model. The project data model includes timing data for salient snippets within the selected video clips. A dynamic and interactive web-based user interface is rendered to visually represent the project data model, offering a timeline view and editing tools for refining the video project. This system streamlines the video editing process by integrating AI-driven content analysis with user-directed editing, resulting in a tailored video project that aligns with user-defined thematic elements.

A method executed by a computing entity includes identifying, using a securely passing process and based on at least one of a public benefit project type and a public benefit project geographic location of selection criteria for a set of public benefit credit assets, a secure first token on an object distributed ledger representing the set of public benefit credit assets. The method further includes establishing, using the securely passing process, control over the secure first token representing the set of public benefit credit assets, where only a device possessing control over the secure first token may modify the secure first token.

The invention discloses an HRV estimation method of a millimeter wave radar. The method comprises the following steps: firstly, positioning a human body by using the range resolution characteristic of an FMCW radar, and preprocessing noise and interference existing in an echo signal; secondly, a grey wolf optimization algorithm is introduced, the maximum mutual information coefficient and the minimum reconstruction error serve as fitness functions, a traditional variational mode decomposition method is optimized, and self-adaptive separation of vital sign signals is achieved. Meanwhile, an optimal heartbeat component is selected from decomposed modals based on a modal selection criterion of a correlation coefficient. And finally, extracting a time parameter corresponding to the heartbeat wave crest, further obtaining IBI, and calculating the time-frequency domain characteristics of the HRV through the IBI. According to the method, the heartbeat signals are effectively extracted through the improved mode decomposition method and the mode selection criterion, and then high-precision estimation of the heart rate variability is achieved.

A method includes obtaining video data of a dental patient. The method further includes obtaining an indication of selection criteria in association with the video data. The selection criteria includes conditions related to a target dental treatment of the dental patient. The method further includes performing an analysis procedure on the video data. Performing the analysis procedure includes determining a first score for each frame of the video data based on the selection criteria. Performing the analysis procedure further includes determining that a frame satisfies a first threshold condition based on the first score. The method further includes providing the first frame as output of the analysis procedure.

An embodiment provides a server UE, especially UE acting as positioning session coordinator, having a transceiver and a controller,wherein the transceiver is configured to receive positioning request (from its higher layers or from a second entity),wherein the controller is configuredto initiate and / or maintain a positioning session for a target UE, wherein the positioning session has at least a measurement between the target UE and an anchor UE; to select out of a plurality of UEs at least one anchor UE fulfilling one or more anchor UE selection criteria; andto coordinate assignment of the configuration associated with at least one resource for transmission and / or for reception with the target UE and the anchor UE involved in the positioning session.

A point cloud generated at least in part using a lidar sensor is received. A geometric mesh based on the point cloud is determined. A seed geometric face formed in the geometric mesh is selected based on one or more seed selection criteria. Starting from the seed geometric face, neighboring geometric faces of the geometric mesh that meet one or more relative neighbor selection criteria are iteratively selected into a region group, and an operable region indicated by the region group is detected.

An image set is refined by selection criteria among captured images, such that images within the set must satisfy criteria such as feature matching among a plurality of frames or positional changes between frame pairs or sufficient overlap of reprojected points of one image into another image such that the reprojected points or features are observed in the frustum or coordinate space of the another image.

The invention relates to an e-commerce live broadcast intelligent item selection method and system. The method comprises the following steps: S1, constructing a multi-dimensional commodity selection criterion system, and collecting original data of a to-be-recommended commodity under each criterion; step S2, subjective weight calculation; s3, objective weight calculation; and S4, carrying out weight fusion and scheme evaluation. According to the method, weight quantification verification is performed through the analytic hierarchy process and the entropy weight method, and the fusion coefficient is dynamically adjusted in combination with the business scene, so that the problems of subjective experience contradiction, poor cold start adaptability and low decision transparency of traditional product selection are solved, and an experience quantification-data verification-weight fusion decision chain is formed; and finally, the product selection scientificity is improved, the scene adaptability is enhanced, and the decision transparency is improved.

Aspects of the subject disclosure may include, for example, selecting a latency comparison, a throughput comparison, a security comparison, a reliability comparison, movement information or a combination thereof for an end user device executing a communication service according to a service type resulting in a selection criteria, wherein the comparisons are evaluations of each of different available connections; and generating a switching decision by selecting one of the connections. Other embodiments are disclosed.

Methods, apparatus, and processor-readable storage media for providing an automated workload migration framework are presented herein. An example computer-implemented method includes obtaining one or more requests for migrating a plurality of workloads, where the one or more requests comprise information corresponding to characteristics associated with the plurality of workloads. The process can include analyzing the one or more requests by applying one or more migration selection criteria to the characteristics associated with the plurality of workloads and selecting at least one of a plurality of migration services to use for migrating the plurality of workloads based on a result of the analyzing. The process can also include generating a set of instructions to migrate the plurality of workloads using the selected at least one migration service and automatically triggering the migration of the plurality of workloads based at least in part on the set of instructions.

Aspects of the subject disclosure may include, for example, selecting a latency comparison, a throughput comparison, a security comparison, a reliability comparison, movement information or a combination thereof for an end user device executing a communication service according to a service type resulting in a selection criteria, wherein the comparisons are evaluations of each of different available connections; and generating a switching decision by selecting one of the connections. Other embodiments are disclosed.

The invention provides a robust classification method and device for dynamic label distribution threshold values based on category self-adaption. According to the method, features of noise training data are extracted based on a CNN model, a category prediction result is output, data in a credible data queue are grouped according to tag categories, and tag distribution of each noise training data is calculated; adaptively updating a label distribution threshold value of the category level based on the label distribution; dividing the training data into a clean data subset, a purified data subset and a noise data subset based on a label distribution threshold; then applying different regularization strategies and loss functions in the subsets, updating model parameters based on a total loss function, and selecting a batch of data from the clean data subsets based on a small loss selection criterion to update a trusted data queue; and finally, training to obtain a classification model for predicting the real category of the unseen data. According to the method, data containing label noise can be accurately detected, and robust training of an effective classification model is carried out.

The invention provides a gene function prediction method and system based on multi-label active learning, and the method comprises the steps: selecting gene-function pairs forming an initial set from an unlabeled data set according to an initial information score quantified by the uncertainty of gene function prediction, label correlation and label distribution imbalance; according to a selection standard of feature diversity, label space diversity and sample-label pair interaction diversity, a standby set is selected in combination with the initial information score; the gene function prediction efficiency and accuracy are remarkably improved, reliable technical support is provided for large-scale gene function research, and the method is particularly suitable for complex function prediction scenes such as research fields of new gene function discovery, disease-related gene function annotation and the like and has important practical application value.

Automatically generates sales materials optimized for each customer. [Solution] A program that causes one or more processors to execute the following steps: acquiring basic customer information, information related to transactions with the customer, and external customer information; analyzing each acquired piece of information to extract keywords and the context of those keywords to identify the customer's potential problems; selecting the company's services to solve the problems based on the identified problems and selection rules that define the selection criteria for the company's services, and determining proposal requirements that include the company's services and the problems; incorporating the proposal requirements into a prompt template and generating a prompt that instructs a generating AI model to generate text content that constitutes sales materials for the customer; and inputting the prompt into the generating AI model and incorporating the obtained text content into a document template to generate sales materials for the customer.

Disclosed are techniques for wireless communication. In an aspect, a user equipment (UE) or network component may select a measurement window type corresponding to the positioning reference signal (PRS) processing window (PPW) or a measurement gap (MG) for measurement processing of each instance of a positioning frequency layer (PFL) for a positioning session of the UE based on one or more selection criteria.

A fatty liver risk assessment and prediction model based on artificial intelligence comprises the following steps: data collection: selecting hospital physical examination crowds of all large hospitals in all regions of the country from January 2020 to January 2023, screening queue research volunteers according to a selection standard, performing reexamination once every year, and performing queue follow-up visit for three years in total, measuring indexes: obtaining research data by performing questionnaire survey, physique measurement and biochemical index detection on a research object, screening out six NPC patient death risk factors such as age, race, gender, StageM, StageT and StageN by combining AI algorithms such as LASSO, XGBoost, DT and RF on the basis of an SEER database and clinical data of local NPC patients, successfully constructing an NPC patient death risk prediction model, and determining the NPC patient death risk. And the model is subjected to internal evaluation, internal verification and external verification, so that a relatively good risk prediction capability is shown, and the method has important clinical significance for evaluating the prognosis of the NPC patient, and relatively high popularization and application values are shown.

There is provided a technique for achieving inter-satellite optical communication for a satellite having a limited calculation capability. One aspect of the present disclosure relates to an earth station, including: a data acquisition unit that acquires a predicted orbit data sequence indicative of a predictive ephemeris of a satellite for a predetermined period, and a communication unit that transmits the acquired predicted orbit data sequence to a relay satellite, wherein the data acquisition unit acquires a first data sequence that is the predicted orbit data sequence having a first data amount and a second data sequence that is the predicted orbit data sequence having a second data amount smaller than the first data amount, and the communication unit transmits the first data sequence or the second data sequence as orbit information of a satellite to a relay satellite, the first data sequence or the second data sequence selected in accordance with predetermined selection criteria.

Solutions are disclosed that provide service differentiation to prioritize which user equipment (UE) is assigned to the radio resource control (RRC) inactive state, due to limitations on the number of UEs that a base station can support in that state. If a UE has an ongoing packet session (e.g., protocol data unit, PDU, session) meeting selection criteria, that UE is prioritized for the RRC Inactive state. UEs that do not have an ongoing packet session meeting the selection criteria are permitted to go to the RRC Idle state. Since resuming the RRC Connected state from the RRC Inactive state is faster than establishing the RRC Connected state from the RRC Idle state, the UEs having the packet session meeting the selection criteria experience less packet delay when resuming data transmission after a period of inactivity. The selection criteria may thus be generally related to packet delay budgets.

The disclosure generally describes methods, software, and systems for assigning incoming documents to a pre-defined layout class. A digitalized document corresponding to an original document is obtained. The digitalized document can be compressed, using a compression algorithm and a plurality of compression dictionaries, to generate a plurality of compressed documents. A respective compression ratio for each compressed document can be generated. A matching compression ratio associated with a first compressed document can be identified. The matching compression ratio can be identified as matching a selection criterion to identify a document layout matching the digitalized document. A first document layout associated with the compression dictionary used to generate the first compressed document can be assigned to the digitalized document. The assigned layout can be used to extract one or more data entries from the digitalized document to generate a record.

An edge device acquires image data including camera images or scans of target objects, such as grains harvested by a combine, and applies a deep learning detection model to detect objects and characteristics associated with the objects in the images so that the images can be categorized into categories representing embodied characteristics associated with the target objects in the captured images. The edge device compares the embodied characteristics associated with the images to the selection criteria to determine which images are transmitted to a central server for subsequent training of the deep learning detection model on the server. An out-of-distribution detection model on the edge device can also distinguish between in- distribution images and out-of-distribution images among the captured images so that out-of- distribution images are also transmitted to the server for model training.

The application provides a test scheme for checking data retention performance of NOR type Flash memory, focuses on the influence of erase-write cycles on the data retention performance, unifies the erase-write cycle number of the Flash memory test, stipulates clear temperature selection criteria, provides a reference for the Flash memory related test, and comprises the following steps: step one: determining the basic test algorithm of the NOR type Flash memory as the Checkerboard algorithm from the algorithm design complexity and the fault coverage; step two: improving the Checkerboard algorithm process and determining the data retention fault determination step; step three: carrying out a pre-experiment to determine the data retention performance test temperature, erase-write number and sample number of the NOR type Flash memory; step four: determining the erase-write number of the data retention test at normal temperature and the sample number under each erase-write number; step five: determining the test pattern, failure criterion, test duration and test cycle; step six: carrying out the data retention test combined with the erase-write cycle based on the non-replacement timing truncation test; and step seven: test data processing, fitting the average failure time under different erase-write numbers with the erase-write number to obtain the corresponding relationship between the average failure time and the erase-write number.

A search unit performs a search process. In the search process, a first process and a second process are iteratively performed. The first process is a process of selecting a change-target state variable from a plurality of state variables included in an evaluation function, based on the amounts of change in the value of the evaluation function caused by updating the values of the individual state variables and a first function that is a function representing a selection criterion for the change-target state variable according to the amounts of change. The second process is a process of updating the value of the selected change-target state variable. A control unit switches the function used by the search unit in the search process to a second function different from the first function.

The present invention provides a recording medium storing a video game processing program and a video game processing system, which can set a selection criterion for a new target object according to a selection criterion for a similar target object. Among one or more target objects (target objects for which the selection criterion has been stored) for which the character has already stored the selection criterion, a similar target object similar to the new target object (hereinafter referred to as "new target object") newly acquired by the character is extracted, and at least for the actions set in common between the similar target object and the new target object, according to the selection probability of each action in the selection criterion stored in association with the similar target object, the selection probability of each action in the selection criterion stored in association with the new target object is set.

A method and apparatus for highlighting a program listing in a set of program listings based on selection criteria. The selection criteria may indicate that the a broadcaster has agreed to pay a service provider in return for the service provider ensuring that a program listing, corresponding to the program of the broadcaster, is highlighted in a program page that displays a set of program listings, such as television program listings. If there are multiple program listings, listed in a program page, that are to be highlighted, then details of the respective contracts may be used to determine which program listing to highlight. Such details may include the total contract value, a ratio of contract value-to-page view, and / or the time of contract formation.

A method and apparatus are disclosed for upgrading libraries in a source code program by evaluating libraries in the source code program for predetermined selection criteria specifying library performance limitations to identify at least a first library which does not meet the plurality of predetermined selection criteria and then identifying a first alternative library that is suitable for substitution for the first library so that the source code program may be automatically modified to replace the first library with the first alternative library, thereby generating a modified source code program having an upgraded library functionality.

The invention discloses a data label protection method and device in longitudinal federated learning and a medium, belongs to the field of data security, is used for initializing a ciphertext layer list, a to-be-reconstructed layer list and a selection criterion parameter in a longitudinal federated learning system before a first round of training, and comprises the following steps: 1, carrying out model layer masking processing based on secret sharing, comprising secret sharing and reconstruction processing; 2, the model is safely updated, wherein the model comprises safe forward propagation and back propagation; step 3, shadow model updating: locally constructing a training shadow model, and calculating a gradient value; 4, selecting and adjusting a model layer needing to be masked according to a preset privacy budget threshold value, and updating the ciphertext layer list and the to-be-reconstructed layer list according to the adjusted masked model layer; and step 5, re-executing the model layer masking processing in the step 1 by using the new ciphertext layer list and the to-be-reconstructed layer list, and starting the next round of training until completion. According to the method, the data label security in longitudinal federated learning can be improved.

A computer-implemented method of accessing, by one or more processors, database tables that include a first row storing a first set of data that includes selection criteria values and first data values and a second row storing a second set of data that includes the selection criteria values and second data values. After determining the first and second sets of data share the selection criteria, the method groups the first and second row to generate a grouped row that indicates a comparison of data based on certain data formats. The method iteratively performs the grouping across the database tables to generate a plurality of grouped rows which are incremented by a counter value to reflect the total number of grouped rows. The method generates a performance metric based on the counter value incremented.

Disclosed herein are methods and systems for filtering entity profiles. A method includes receiving, from a plurality of data sources and for a plurality of medical entities, clinical data and online interaction data; generating a plurality of entity profiles for the plurality medical entities; calculating one or more clinical metrics and one or more online interaction metrics for the plurality of entity profiles from the clinical data and the online interaction data; executing a model using identifications of the plurality of entity profiles and the one or more clinical metrics and the one or more online interaction metrics as input to generate influence scores for the plurality of entity profiles; selecting a subset of the plurality of entity profiles responsive to each entity profile of the subset having an influence score satisfying a selection criteria; and generating a record comprising identifications of the subset of the plurality of entity profiles.