247 results about "Selection criterion" patented technology

The invention discloses a ground motion intensity measure optimization method for seismic response prediction. The method includes the following steps: (1) building a building damage database; (2) optimizing ground motion intensity measures; (3) constructing a machine learning model; and (4) predicting damage states. According to the method, a combination of optimal ground motion intensity measures is selected by an elastic-net algorithm, wherein the efficiency and practicability in a current selection criterion are updated based on the goodness of fit and regression coefficient of the elastic-net model, thereby avoiding an assumption that intensity measures and structure response need to obey a logarithmic linear relationship and the limitation of intensity measure dimensions in traditional methods. By using the combination of optimal ground motion intensity measures as input variables, the prediction accuracy can be remarkably improved, and meanwhile the number of samples required is reduced.

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.

While a first view of a three-dimensional environment is visible, a computer system detects a first input meeting selection criteria. If, when the first input was detected, a user was directing attention to a first portion of the first view that has a spatial relationship to a viewport through which the three-dimensional environment is visible, the computer system displays a user interface object including affordances for accessing functions of the computer system; otherwise, the computer system forgoes displaying the user interface object. While a different view of the three-dimensional environment is visible, the computer system detects a second input meeting the selection criteria. If, when the second input was detected, the user was directing attention to a second portion of the different view that has the same spatial relationship to the viewport, the computer system displays the user interface object; otherwise, the computer system forgoes displaying the user interface object.

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.

A computer implemented method of dynamic runtime computer code monitoring, the method comprising steps that a computer processor is programmed to perform, the steps comprising: during execution of a computer code, detecting a plurality of system calls initiated during the execution, during the execution of the computer code, selecting a least one of the detected system calls, based on a selection criterion, and analyzing the selected system call, according to at least one predefined rule.

A method for replacing by a HPLMN or a user equipment a set of URSP rules used by the user equipment communicating with a MNO network, the set of URSP rules being called current set of URSP rules, by another set of URSP rules, called new set of URSP rules, the user equipment cooperating with a secure element, the method including storing in the secure element a plurality of URSP rules; when the home network or the user equipment decides to switch from the current set of rules to the new set of rules, sending to the secure element a switching command comprising a list of selection criteria of the new set of URSP rules; replacing in the secure element the current set of URSP rules by the new set of URSP rules, and sending a refresh command.

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.

The invention relates to a power distribution network fault detection method based on generalized S transformation containing variable factors, and belongs to the technical field of power distribution network fault detection. Data such as a time-frequency spectrum and transient energy are obtained through generalized S transformation containing variable factors, and three line selection criteria of a time-frequency spectrum comprehensive similarity coefficient, a transient energy peak value and a transient energy relative entropy are constructed; and multi-criterion fusion is realized in combination with a D-S evidence theory, so that a line selection result of a single criterion is subjected to comprehensive analysis of multi-criterion fusion, and a more accurate line selection result is obtained. According to the method, accurate line selection can be carried out in different fault distances, fault lines, fault initial angles, fault grounding resistances and noise environments, and the method has good adaptability, sensitivity and anti-interference performance. According to the method, the calculated transient energy characteristics are converted into a reliability distribution function to construct an evidence combination, and different fault characteristic quantities are utilized to measure the credibility to construct a line selection criterion, so that mutual complementation and mutual fusion are realized, and a more accurate line selection result is obtained.

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.

Methods, apparatus, systems, and articles of manufacture for the generation and application of models for immunotherapy prediction and treatment are disclosed. A balance of accuracy and recall rate may be applied to at least one of a toxicity-related model or a therapeutic effect-related model to configure an immunotherapy treatment of a patient and / or a group of patients. Model outputs may be evaluated differently depending on determining patient selection criteria to trigger different actions.

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 discloses a waveform design method and system for tracking a sea surface maneuvering target by an unmanned ship-mounted radar, relates to the technical field of radar communication, and aims to solve the technical problem of inaccurate maneuvering target tracking in a sea surface clutter environment. The method is technically characterized by comprising the following steps: predicting a target state by using a marginalized particle filter algorithm, and obtaining a predicted measurement value; generating a hypothesis tree according to the observation data; performing target state estimation on each assumed branch by using a marginalized particle filter algorithm; a multi-hypothesis tracking algorithm is used to calculate an association probability and update a hypothesis weight, hypothesis pruning and fusion are carried out, and final target state estimation is obtained; a plurality of waveform selection criteria are used as a model, and an interactive multi-criterion selection method is utilized to determine an optimal criterion with the highest effective probability and an optimal transmitted waveform parameter. According to the method, false alarms caused by sea clutters can be effectively handled, the performance of the unmanned ship-mounted radar for processing complex tracking scenes can be improved, and a more accurate and robust target tracking result can be obtained.

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.

Systems and methods are disclosed herein that relate to Session Management Function (SMF) selection based on subscription data. In one embodiment, a method performed by first network node in a core network of a cellular communications system comprises sending, to a second network node, a request for SMF selection subscription data of a UE and receiving, from the second network node, SMF selection subscription data of the UE in response to the request, the SMF selection subscription data of the UE comprising one or more SMF selection criteria and one or more conditions for applying the one or more SMF selection criteria. The method further comprises performing SMF selection for a PDU session of the UE based on the SMF selection subscription data of the UE. In this manner, improved SMF selection is provided.

The present invention provides a reservoir numerical simulation grid design method, which comprises: step 1, optimizing the model area and formulating the area selection criteria; step 2, establishing reservoir models with different grid steps and conducting numerical simulation research; step 3, optimizing the dynamic and static comprehensive evaluation parameters and establishing a model grid step evaluation parameter library; step 4, scoring and optimizing the grid step based on the reservoir type, and establishing a scoring standard suitable for the reservoir type in a specific research area. The reservoir numerical simulation grid design method of the present invention draws on the concept of typical volume units, and aims at the problem that the large step grid cannot accurately describe the small geological body and its spatial variation, and the small step grid calculation time greatly increases and convergence problems. By establishing a dynamic and static comprehensive evaluation parameter system, the different grid step models are comprehensively scored, and the quantitative optimization of the grid step is realized.

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.