54 results about "Interactive computing" patented technology

A device may as implemented by an interactive computing system configured with specific computer-executable instructions, capturing one or more image frames of a video game, receiving, from one or more sensors, eye tracking information associated with a user playing the video game, associating the eye tracking information with the one or more image frames, identifying at least a first frame based at least in part on the eye tracking information, identifying at least one feature of interest within the first frame based on the eye tracking information, and outputting an indication associated with the at least one feature of interest.

A computer-implemented method includes accessing data associated with log-in attempts of an interactive computing environment from attempt logs. The method further includes detecting a success percentage of log-in attempts by an entity. Additionally, the method includes identifying the entity as a credential-stuffing attacker based at least in part on the success percentage of log-in attempts by the entity. Moreover, the method includes restricting access to the interactive computing environment by the entity.

Systems, methods, apparatuses, and computer program products of a user interface configured for automated generation and optimization of room layout designs. One method may include determining a relative position token for each of a plurality of elements according to a function of at least one relative position token of at least one other element. Each relative position token comprises at least one discrete non-Cartesian value of each of the elements. The method further comprises determining a Cartesian position for each of a plurality of elements according to a function of at least one of the relative position tokens to generate a room layout; displaying, in an interactive computerized user interface, at least one generated room layout; and based upon input from the interactive computerized user interface, transmitting at least one of the generated plurality of room layouts and a request for a selection of the transmitted room layouts.

An interactive computer-implemented method for testing an HVAC system includes: - input of at least one document (11) relating to the HVAC system by a user into a data processing system (4), the documents containing schematic representations of the HVAC system; - in the data processing system (4), extracting a plurality of functional blocks (880) (106) from the schematic representations by a machine learning system (8); - detecting inconsistencies, including missing documents or information, within the data processing system depending on the result of the extraction (108); - a conversation agent (5) in the data processing system interacting with the user to request missing documents or information relating to the HVAC system (107, 101); - Creating a report based on the extraction and detection of discrepancies (109).

The invention discloses an AIAgent trigger execution mechanism of a linkage Notebook or a visual front end, and relates to the technical field of artificial intelligence and interactive computing. The mechanism comprises an event monitoring module, a trigger condition configuration module, a condition matching module, an AIAgent scheduling module and a result feedback module. The event monitoring module captures a front-end user interaction event in real time and outputs standardized data; the trigger condition configuration module stores a trigger rule preset by a user and supports dynamic adjustment; the condition matching module compares the standardized data with a trigger rule, and generates a trigger signal when a condition is met; the AIAgent scheduling module calls a corresponding Agent according to the trigger signal and transmits parameters; and the result feedback module converts the execution result into a front-end displayable form and updates the execution result to the front end. According to the method and the device, dynamic collaboration of the AIAgent and the front end is realized, the problems of rigid triggering mode and low interaction efficiency in the prior art are solved, the automation and convenience of intelligent task execution are improved, and the method and the device are suitable for scenes of data analysis, program development and the like.

In some aspects, a computing system can train a risk assessment model, using a training process, for determining a risk indicator. The training process can include: accessing a set of features; determining, using a selector network, a set of selected features and an indicator vector; and training the risk assessment model using the set of selected features and the indicator vector. The computing system can determine the risk indicator for a target entity using the trained risk assessment model. The computing system can transmit, to a remote computing device, a responsive message including at least the risk indicator for use in controlling access of the target entity to one or more interactive computing environments.

The invention provides an intelligent teaching evaluation system and device, and the system comprises an obtaining module which is used for obtaining multi-source training data; wherein the multi-source training data comprises VR motion capture data, multi-scene practical operation data, man-machine collaborative auditing data, voice question and answer data and theoretical learning data; the interaction calculation module is used for determining a plurality of VR interaction features according to the VR motion capture data, the multi-scene practical operation data and the man-machine cooperation auditing data; and the AI evaluation module is used for determining an evaluation result according to the plurality of VR interaction features, the voice question and answer data, the theoretical learning data and an AI evaluation algorithm. Through deep analysis and fusion of multi-source data, the method shows unique and remarkable advantages in nuclear emergency medical rescue teaching evaluation. Specifically, on the basis of VR motion capture data and multi-scene practical operation data, interaction features during nuclear emergency medical rescue in a VR virtual scene are extracted, and advantages and deficiencies of students in nuclear emergency medical rescue skill learning are accurately positioned.

Systems, computer program products, and methods are described herein for digital resource allocation via an interactive computational framework. The present disclosure includes receiving credentials at a first endpoint device, authenticating the credentials, receiving a digital resource allocation request from the first endpoint device, the digital resource allocation request comprising parameters of a user associated with the authenticated credentials and item parameters of an item associated with the digital resource allocation request, retrieving user data associated with the user, determining, using a machine learning model, a digital resource allocation proposal based on the user data, generating, using a generative AI model, based on the digital resource allocation proposal, a smart contract comprising ownership, appending the smart contract to a distributed ledger, and transferring digital resources according to the smart contract.

A system can generate a risk assessment associated with a target entity. The system can access a request for a risk indicator associated with a target entity. The system can also access a model in a test environment and run an ATP tool on the model. The ATP tool can execute a set of deployment steps using the model and determine a completion status of each of the set of deployment steps. The system can deploy the model to a production environment when the set of deployment steps is successful. The system can determine the risk indicator using the model. The system can transmit, to a remote computing device, a responsive message comprising at least the risk indicator to control access of the target entity to one or more interactive computing environments.

A human interface device (HID)-compatible portable gaming device includes a display; a position sensor; a joystick; and a processor in communication with the display, the joystick, and the position sensor. The processor has programmed instructions that, when executed, cause the processor to receive a first signal from the position sensor indicating a change in orientation of the portable gaming device, receive a second signal from the joystick indicating a change in position of the joystick, assign a first weight to the first signal and a second weight to the second signal; aggregate the first signal with the second signal based on a weighted sum of the weighted first signal and the weighted second signal to obtain a third signal, and update a user interface on the display according to the third signal.

The invention is suitable for the field of data processing, and discloses a vNPU computing power scheduling method for teaching practical training, terminal equipment and a storage medium. The vNPU computing power scheduling method for teaching and practical training comprises the steps that a vNPU computing power pool is generated, a container creation request from a student terminal is received, the vNPU computing power pool is composed of independent logic computing power units formed by virtualized division of a plurality of physical NPUs, and the container creation request is used for requesting creation of a computing power container containing an interactive computing environment; creating a computing power container according to the container creation request, and scheduling a target vNPU from a vNPU computing power pool according to the container creation request; binding the target vNPU to a computing power container; and the scheduling device starts the computing power container, and the computing power container provides teaching and practical training services for the student terminal through the interactive computing environment. According to the invention, the NPU resource utilization rate and the flexibility of teaching practical training are improved.

An electronic device includes one or more processors, a user interface, and a memory. The device operates an electronic shopping interactive computing environment. Upon initiation of an interactive session, the processors determine a fraudulent return propensity score based on various input parameters, including device-level activities such as subscriber identification module card swaps, factory resets, and application reinstalls. When the propensity score exceeds a predefined threshold, the processors preclude one or more user interaction events, such as shopping cart interactions or product returns, from occurring in the shopping environment. The system can employ a machine learning algorithm to generate a normalized propensity score, enhancing fraud detection accuracy. This proactive approach mitigates the risk of fraudulent returns, protecting retailers from financial losses and maintaining the integrity of the e-commerce platform.

Interactive Computer Device for Real-Time Machine Learning Driven Data Interpretation

A system can efficiently determine whether an identity is manipulated. The system can receive entity data and interaction data associated with a target entity. The system can determine, based on the entity data and the interaction data, one or more risk signals associated with the target entity using one or more artificial intelligence models. The system can generate a linked graph structure based on a first graph structure and a second graph structure each generated using the entity data and the interaction data. The system can apply the one or more risk signals to the linked graph structure to determine a risk indicator associated with the target entity. The system can provide a responsive message based on the risk indicator. The responsive message can be used to control access of the target entity to an interactive computing environment.

An online security analysis system determines a categorical value in an online activity and also determines conversion factors that are associated with the categorical value. Based on the conversion factors, the online security analysis system identifies at least one aggregated value for a numerical feature that is associated with previous online activities for the categorical value. In addition, the online security analysis system generates an embedding vector that describes the aggregated value associated with the categorical value. The embedding vector is provided to an online activity analysis model that is trained to generate prediction data for the online activity, based on the aggregated values associated with the categorical value. The prediction data is transmitted to an online system for use in controlling access of a client device to a function of the online system.

Embodiments are described herein for establishing, in an interactive computing environment operating via at least one server device, a first user with a first user access type for managing communications between a plurality of users. The first user access type may allow the first user to communicate directly via the interactive computing environment with a second user having a second user access type and a plurality of third users having a third user access type in. The second user access type may permit the second user to identify the third users based on identification parameters and a relationship between the third users and the first user in the interactive computing environment. The third user access type may prevent the third users from directly communicating with the second user without an approval of the first user to protect a privacy associated with the third user.

Systems and methods for predicting future risk for a target entity are provided. A risk assessment system receives historical risk assessment data of the target entity and identifies a target cluster that matches the historical risk assessment data. The target cluster is identified from a group of clusters determined using high dimensional clustering based on risk assessment data of a set of entities. The risk assessment system identifies a set of nearest neighbors of the target cluster and determines a prediction of future risk for the target entity based on the target cluster and the set of nearest neighbors. The risk assessment system transmits a responsive message, which can include the prediction of future risk, to a remote computing device for use in controlling access of the target entity to one or more interactive computing environments.

Systems, methods, apparatuses, and computer program products of a user interface configured for automated generation and optimization of floorplan designs. One method may include automatically generating a plurality of floorplans. At least one of the room's corner offsets is determined after at least one other room's position has been determined. The method further includes scoring a plurality of generated floorplans according to a scoring function; calculating, for at least one generated floorplan, whether it has a path with width at least as large as a number from a door of the respective generated floorplan to an exit; displaying, in an interactive computerized user interface, a subset of the generated plurality of floorplans that has been selected based on the scores of the floorplans; and based upon input from the interactive computerized user interface, transmitting at least one of the generated plurality of floorplans.

The present invention provides an operation device for SIMD calculation instructions, comprising: a data packing pipeline register for receiving and storing a SIMD calculation instruction to be processed and a group of operands corresponding to the instruction; a fixed-point decoder for decoding and rearranging the operands corresponding to the fixed-point integer instruction and transmitting them to a fixed-point integer operator; a fixed-point integer operator for performing integer operations on the operands processed by the fixed-point decoder; a floating-point decoder for decoding and rearranging the operands corresponding to the floating-point instruction and transmitting the rearranged operands to a floating-point multiplier or a floating-point divider according to the instruction; a floating-point multiplier for performing floating-point multiplication and addition on the operands processed by the floating-point decoder; a floating-point divider for performing floating-point division on the operands processed by the floating-point decoder; and an operation result arbiter for selecting the operation results of the calculation components to output the final SIMD calculation result.

Interactive Computer Device for Global Smart Campus Management

Abstract In some aspects, a computing system can generate and optimize a neural network for risk assessment. The neural network can be trained to enforce a monotonic relationship between each of the input predictor variables and an output risk indicator. The training of the neural network can involve solving an optimization problem under a monotonic constraint. This constrained optimization problem can be converted to an unconstrained problem by introducing a Lagrangian expression and by introducing a term approximating the monotonic constraint. Additional regularization terms can also be introduced into the optimization problem. The optimized neural network can be used both for accurately determining risk indicators for target entities using predictor variables and determining explanation codes for the predictor variables. Further, the risk indicators can be utilized to control the access by a target entity to an interactive computing environment for accessing services provided by one or more institutions. Abstract 20 26 20 53 15 06 J ul 2 02 6 A b s t r a c t 2 0 2 6 2 0 5 3 1 5 0 6 J u l 2 0 2 6

Systems and methods for consolidating data sources for expediting validation processes are described herein. A user interface can be provided to a first entity. First risk assessment data associated with the first entity can be received via the user interface. Second risk assessment data associated with the first entity can be received. The first risk assessment data and the second risk assessment data can be validated. The first risk assessment data and the second risk assessment data can be output for display on the user interface. A responsive message including the validated first risk assessment data and the validated second risk assessment data can be transmitted to a remote computing device for use in controlling access of the first entity to one or more interactive computing environments.

An electronic device and method preclude user interaction events in an electronic shopping interactive computing environment. The method involves comparing a shopping cart interaction event to at least one previous user interaction event associated with the user. When a metric associated with the previous user interaction event deviates from a corresponding metric associated with the shopping cart interaction event, the method presents a prompt on a user interface indicating that additional shopping cart interaction events will be unavailable for product return user interaction events. The electronic device includes a user interface, memory, and processors that compare the price of an item with metrics associated with past purchases and returns. If the price exceeds predefined thresholds, the device precludes product return user interaction events, thereby mitigating potential return fraud.

Design of an Interactive Computer Display Device for Personalized Learning Recommendations

Systems, methods, apparatuses, and computer program products of a user interface configured for automated generation and optimization of room layout designs. One method may include determining a relative position token for each of a plurality of elements according to a function of at least one relative position token of at least one other element. Each relative position token comprises at least one discrete non-Cartesian value of each of the elements. The method further comprises determining a Cartesian position for each of a plurality of elements according to a function of at least one of the relative position tokens to generate a room layout; displaying, in an interactive computerized user interface, at least one generated room layout; and based upon input from the interactive computerized user interface, transmitting at least one of the generated plurality of room layouts and a request for a selection of the transmitted room layouts.

In some aspects, a computing system can train a machine-learning model to analyze a graph database for risk assessment. The computing system can use the machine-learning model to identify a risk indicator for a target component of one or more interactive computing environments. The graph database can include a set of nodes where each node represents a respective infrastructure service of one or more infrastructure services and a set of edges connecting individual nodes of the set of nodes. The computing system can generate the risk indicator for the target component based on an output of the machine-learning model The computing system additionally can output a graphical user interface including at least the risk indicator for use in controlling access to the one or more infrastructure services.

Embodiments of the present application provide a method, device, system and storage medium for verifying data processing quality. The method comprises: obtaining a business requirement; writing the business requirement into an interactive computing environment; connecting a target database in a plurality of databases with the interactive computing environment; determining at least one processing verification result of data in the target database based on the business requirement in the interactive computing environment; and sending the at least one processing verification result to a test terminal to enable the test terminal to determine whether the data meets data quality requirements. The present application directly verifies a large amount of data without sampling and error, effectively improving test quality and test efficiency, while reducing labor costs.

A method described herein involves various operations directed toward network security. The operations include receiving a request for a risk indicator of a target entity. The risk indicator can indicate a level of risk associated with the target entity based on whether the target entity is associated with a mobile device emulator. The operations include generating the risk indicator by applying the entity data to an emulator detection model trained on a training dataset comprising a corpus of attribute data and interaction data. Finally, the operations include providing, to a remote computing device, a responsive message comprising at least the risk indicator to control access to an interactive computing environment.

Systems and methods for using machine-learning techniques to provide risk assessment based on multiple sources of data are described herein. Data about an entity can be received, and the data can be authenticated. Integrated risk data about the entity can be received. The integrated risk data can include traditional risk assessment data and nontraditional risk assessment data. An integrated risk assessment value can be determined based on the integrated risk data by aligning a first output from a first risk assessment model and a second output by a second risk assessment model. A responsive message including at least the integrated risk assessment value and associated information for the entity can be transmitted to a remote computing device for use in controlling access of the entity to one or more interactive computing environments.