13 results about "Adaptive user interface" patented technology

In accordance with the present disclosure, one or more computing devices and / or methods are provided. In an example, an emotional state of a user may be determined based upon one or more signals generated by one or more sensors and / or user activity of the user. A communication interface may be controlled based upon the emotional state.

A rendering event is detected during a rendering cycle of a user interface (UI) being rendered on a device. In response to the detection, monitoring is initiated of a data structure containing a set of elements of the UI. From the monitoring, an element in the set of elements is detected to include a violation of an accessibility requirement. A classification of the violation is generated, which includes one or more from a set including a type, a severity, and a priority of the violation. A remedy corresponding to the violation and the classification is selected and a modification of data of the element in the data structure in a memory of the device is performed in real time during the rendering cycle to form a corrected element, correcting the violation of the element. The UI is rendered with the corrected element during the rendering cycle.

A computer-implemented method is provided for dynamically altering a user interface (UI) display by a computer-implemented method for altering a computer monitor display without recompilation of code. The method includes developing the UI display in FXML syntax that creates an FXML file. Data for display are mapped to particular fields in the UI display, within the FXML file. A JAVA Archive (JAR) file with the FXML file is deployed to a client device. The JAR file is executed with the FXML file to produce the UI display on the client device. The displays on the UI display are populated as defined by the FXML file.

An innovative system for integrating generative artificial intelligence (AI) capabilities within Software as a Service (SaaS) platforms. By leveraging advanced AI techniques, seamless data synchronization, intelligent task management, and predictive workflow optimization across multiple SaaS platforms are described. Key components include an AI-driven data synchronization system, an intelligent cross-platform task manager, and an adaptive user interface. The system also features a cross-departmental health monitoring and notification mechanism, alongside an intent-based interaction system. This solution enhances organizational efficiency, improves decision-making, and provides unprecedented levels of automation and insight in managing complex SaaS ecosystems.

The invention relates to an AI-based multi-dimensional constraint adaptive user interface layout method and device, and the method comprises the steps: collecting equipment performance data and user behavior data of a user terminal; inputting the user behavior data into a pre-trained lightweight deep learning model, and predicting a next operation intention and a high-frequency operation area of the user; inputting equipment performance monitoring data and the high-frequency operation area into a preset multi-dimensional real-time constraint model to solve a balanced optimal solution among different constraints, and obtaining an optimal user interface layout strategy meeting a preset system operation fluency threshold value; calculating complexity quantitative indexes of interface elements according to the optimal user interface layout strategy; and dynamically adjusting rendering parameters and a layout structure of the user interface according to the complexity quantitative indexes of the interface elements. By adopting the method and the device, the dynamic adjustment process of the user interface layout can be smoother.

The invention provides an adaptive user interface dynamic rendering method and device, equipment, a medium and a product, and relates to the technical field of interactive design, and the method comprises the following steps: obtaining source data aiming at a current user interface on a browser; symbolizing the user interaction data to obtain symbolized interaction data, and converting the natural language information into an original feature vector; performing interface change prediction according to the original feature vector to obtain a prediction vector; verifying the prediction vector according to the symbolized interaction data; a large model layer in a preset neural symbol renderer is adopted, interface change information is generated according to the prediction vector, and the interface change information at least comprises an interface change rule set; and according to the interface adjustment rule set, performing interface rendering by adopting a preset rendering engine to obtain an updated user interface. According to the method, the intelligence, transparency and credibility of self-adaptive adjustment of the user interface are improved.

At least one processor may receive data indicating a sequence of actions. The at least one processor may generate a unified embedding from the sequence of actions, wherein the unified embedding can encode respective embeddings of the respective actions encapsulating action characteristics and sequential positions and respective importance scores of the respective actions. The at least one processor may process the unified embedding with a trained machine learning model to thereby predict a next likely action. The at least one processor can configure a user interface or other computer element to perform and / or enable the next likely action in response to the predicting.

An audio system (1) comprising an audio device (10) and a charging cradle (20) for storing the audio device (10). The charging cradle (20) comprises a cradle housing (200) with a device bay (201), a status detector (202), a cradle input interface (203), a rechargeable battery (204), and a cradle controller (205). The device bay (201) is configured to accommodate the audio device (10) when the audio device (10) is stored in the charging cradle (20). The status detector (202) is configured to detect whether the audio device (10) is stored in the charging cradle (20), determine a corresponding storing status, and provide the determined storing status in a cradle status signal (CS) to the cradle controller (205). The cradle input interface (203) is configured to detect user input actions and provide indications of detected user input actions in a cradle input signal (UC) to the cradle controller (205). The rechargeable battery (204) is configured to receive electric energy from an external energy source, store the received electrical energy, and provide stored electric energy (P) to the audio device (10) through the cradle controller (205) and / or the device bay (201). In the audio system (1), the cradle controller (205) is configured to provide a user output signal (UO) comprising an indication of control commands in response to receiving indications of detected user input actions in the cradle input signal (UC) and / or in dependence on the cradle status signal (CS), such that, for identical indicated user input actions, the control command indication in the user output signal (UO) differs for different storing status indications in the cradle status signal (CS). This enables using the controls of the cradle input interface (203) for different purposes, depending on whether the audio device (10) is stored in the charging cradle (20), and may thereby reduce the number of user controls required on the audio device (10) and / or the charging cradle (20).

A cross-platform service engages and connects influencers and consumers by facilitating content generation in connection with electronic-commerce platform. An influencer / content generator facing portal presents a set of tools to enable influencers to create content for use on the e-commerce side and to facilitate transactions related to influencer compensation. A consumer facing portal presents adaptive user interfaces to engage remotely connected consumers by presenting influencer-generated “looks” and tools to selectively navigate and select / deselect presented looks and explore look and products and ultimately to handle transactions for purchasing of products.

An audio system (1) with an adaptive user interface includes an audio device (10) and a charging case (20) for storing the audio device (10). The charging case (20) includes a case housing (200) having a device compartment (201), a status detector (202), a case input interface (203), a rechargeable battery (204), and a case controller (205). The device compartment (201) is configured to accommodate the audio device (10) when it is stored in the charging case (20). The status detector (202) is configured to detect whether the audio device (10) is stored in the charging case (20), determine the corresponding storage state, and provide the determined storage state to the case controller (205) in a case status signal (CS). The case input interface (203) is configured to detect user input actions and provide an indication of the detected user input actions to the case controller (205) in a case input signal (UC).

A method for providing information to a vehicle occupant may involve determining one or more inputs using one or more vehicle sensors. The method may further involve determining a layout of each of a multitude of user interface (UI) elements of an infotainment system, at least partially, based on the one or more inputs. The method may also involve providing information to the vehicle occupant by displaying the multitude of UI elements on the infotainment system, at least partially, based on the layout of each of the multitude of UI elements.

An audio system comprising an audio device and a charging cradle for storing the audio device. The charging cradle comprises a cradle housing with a device bay, a status detector, a cradle input interface, a rechargeable battery, and a cradle controller.The device bay is configured to accommodate the audio device when the audio device is stored in the charging cradle.The status detector is configured to detect whether the audio device is stored in the charging cradle, determine a corresponding storing status, and provide the determined storing status in a cradle status signal to the cradle controller.The cradle input interface is configured to detect user input actions and provide indications of detected user input actions in a cradle input signal to the cradle controller.The rechargeable battery is configured to receive electric energy from an external energy source, store the received electrical energy, and provide stored electric energy to the audio device through the cradle controller and / or the device bay.In the audio system, the cradle controller is configured to provide a user output signal comprising an indication of control commands in response to receiving indications of detected user input actions in the cradle input signal and in dependence on the cradle status signal.This enables using the controls of the cradle input interface for different purposes, depending on whether the audio device is stored in the charging cradle, and may thereby reduce the number of user controls required on the audio device and / or the charging cradle.

An innovative system for integrating generative artificial intelligence (AI) capabilities within Software as a Service (SaaS) platforms. By leveraging advanced AI techniques, seamless data synchronization, intelligent task management, and predictive workflow optimization across multiple SaaS platforms are described. Key components include an AI-driven data synchronization system, an intelligent cross-platform task manager, and an adaptive user interface. The system also features a cross-departmental health monitoring and notification mechanism, alongside an intent-based interaction system. This solution enhances organizational efficiency, improves decision-making, and provides unprecedented levels of automation and insight in managing complex SaaS ecosystems.